literature review for empirical research

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Writing a Literature Review

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A literature review is a document or section of a document that collects key sources on a topic and discusses those sources in conversation with each other (also called synthesis ). The lit review is an important genre in many disciplines, not just literature (i.e., the study of works of literature such as novels and plays). When we say “literature review” or refer to “the literature,” we are talking about the research ( scholarship ) in a given field. You will often see the terms “the research,” “the scholarship,” and “the literature” used mostly interchangeably.

Where, when, and why would I write a lit review?

There are a number of different situations where you might write a literature review, each with slightly different expectations; different disciplines, too, have field-specific expectations for what a literature review is and does. For instance, in the humanities, authors might include more overt argumentation and interpretation of source material in their literature reviews, whereas in the sciences, authors are more likely to report study designs and results in their literature reviews; these differences reflect these disciplines’ purposes and conventions in scholarship. You should always look at examples from your own discipline and talk to professors or mentors in your field to be sure you understand your discipline’s conventions, for literature reviews as well as for any other genre.

A literature review can be a part of a research paper or scholarly article, usually falling after the introduction and before the research methods sections. In these cases, the lit review just needs to cover scholarship that is important to the issue you are writing about; sometimes it will also cover key sources that informed your research methodology.

Lit reviews can also be standalone pieces, either as assignments in a class or as publications. In a class, a lit review may be assigned to help students familiarize themselves with a topic and with scholarship in their field, get an idea of the other researchers working on the topic they’re interested in, find gaps in existing research in order to propose new projects, and/or develop a theoretical framework and methodology for later research. As a publication, a lit review usually is meant to help make other scholars’ lives easier by collecting and summarizing, synthesizing, and analyzing existing research on a topic. This can be especially helpful for students or scholars getting into a new research area, or for directing an entire community of scholars toward questions that have not yet been answered.

What are the parts of a lit review?

Most lit reviews use a basic introduction-body-conclusion structure; if your lit review is part of a larger paper, the introduction and conclusion pieces may be just a few sentences while you focus most of your attention on the body. If your lit review is a standalone piece, the introduction and conclusion take up more space and give you a place to discuss your goals, research methods, and conclusions separately from where you discuss the literature itself.

Introduction:

• An introductory paragraph that explains what your working topic and thesis is
• A forecast of key topics or texts that will appear in the review
• Potentially, a description of how you found sources and how you analyzed them for inclusion and discussion in the review (more often found in published, standalone literature reviews than in lit review sections in an article or research paper)
• Summarize and synthesize: Give an overview of the main points of each source and combine them into a coherent whole
• Analyze and interpret: Don’t just paraphrase other researchers – add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
• Critically Evaluate: Mention the strengths and weaknesses of your sources
• Write in well-structured paragraphs: Use transition words and topic sentence to draw connections, comparisons, and contrasts.

Conclusion:

• Summarize the key findings you have taken from the literature and emphasize their significance
• Connect it back to your primary research question

How should I organize my lit review?

Lit reviews can take many different organizational patterns depending on what you are trying to accomplish with the review. Here are some examples:

• Chronological : The simplest approach is to trace the development of the topic over time, which helps familiarize the audience with the topic (for instance if you are introducing something that is not commonly known in your field). If you choose this strategy, be careful to avoid simply listing and summarizing sources in order. Try to analyze the patterns, turning points, and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred (as mentioned previously, this may not be appropriate in your discipline — check with a teacher or mentor if you’re unsure).
• Thematic : If you have found some recurring central themes that you will continue working with throughout your piece, you can organize your literature review into subsections that address different aspects of the topic. For example, if you are reviewing literature about women and religion, key themes can include the role of women in churches and the religious attitude towards women.
• Qualitative versus quantitative research
• Empirical versus theoretical scholarship
• Divide the research by sociological, historical, or cultural sources
• Theoretical : In many humanities articles, the literature review is the foundation for the theoretical framework. You can use it to discuss various theories, models, and definitions of key concepts. You can argue for the relevance of a specific theoretical approach or combine various theorical concepts to create a framework for your research.

What are some strategies or tips I can use while writing my lit review?

Any lit review is only as good as the research it discusses; make sure your sources are well-chosen and your research is thorough. Don’t be afraid to do more research if you discover a new thread as you’re writing. More info on the research process is available in our "Conducting Research" resources .

As you’re doing your research, create an annotated bibliography ( see our page on the this type of document ). Much of the information used in an annotated bibliography can be used also in a literature review, so you’ll be not only partially drafting your lit review as you research, but also developing your sense of the larger conversation going on among scholars, professionals, and any other stakeholders in your topic.

Usually you will need to synthesize research rather than just summarizing it. This means drawing connections between sources to create a picture of the scholarly conversation on a topic over time. Many student writers struggle to synthesize because they feel they don’t have anything to add to the scholars they are citing; here are some strategies to help you:

• It often helps to remember that the point of these kinds of syntheses is to show your readers how you understand your research, to help them read the rest of your paper.
• Writing teachers often say synthesis is like hosting a dinner party: imagine all your sources are together in a room, discussing your topic. What are they saying to each other?
• Look at the in-text citations in each paragraph. Are you citing just one source for each paragraph? This usually indicates summary only. When you have multiple sources cited in a paragraph, you are more likely to be synthesizing them (not always, but often
• Read more about synthesis here.

The most interesting literature reviews are often written as arguments (again, as mentioned at the beginning of the page, this is discipline-specific and doesn’t work for all situations). Often, the literature review is where you can establish your research as filling a particular gap or as relevant in a particular way. You have some chance to do this in your introduction in an article, but the literature review section gives a more extended opportunity to establish the conversation in the way you would like your readers to see it. You can choose the intellectual lineage you would like to be part of and whose definitions matter most to your thinking (mostly humanities-specific, but this goes for sciences as well). In addressing these points, you argue for your place in the conversation, which tends to make the lit review more compelling than a simple reporting of other sources.

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What is a Literature Review? How to Write It (with Examples)

A literature review is a critical analysis and synthesis of existing research on a particular topic. It provides an overview of the current state of knowledge, identifies gaps, and highlights key findings in the literature. 1 The purpose of a literature review is to situate your own research within the context of existing scholarship, demonstrating your understanding of the topic and showing how your work contributes to the ongoing conversation in the field. Learning how to write a literature review is a critical tool for successful research. Your ability to summarize and synthesize prior research pertaining to a certain topic demonstrates your grasp on the topic of study, and assists in the learning process. 

Table of Contents

• What is the purpose of literature review? 
• a. Habitat Loss and Species Extinction: 
• b. Range Shifts and Phenological Changes: 
• c. Ocean Acidification and Coral Reefs: 
• d. Adaptive Strategies and Conservation Efforts: 
• How to write a good literature review 
• Choose a Topic and Define the Research Question: 
• Decide on the Scope of Your Review: 
• Select Databases for Searches: 
• Conduct Searches and Keep Track: 
• Review the Literature: 
• Organize and Write Your Literature Review: 
• Frequently asked questions 

What is a literature review?

A well-conducted literature review demonstrates the researcher’s familiarity with the existing literature, establishes the context for their own research, and contributes to scholarly conversations on the topic. One of the purposes of a literature review is also to help researchers avoid duplicating previous work and ensure that their research is informed by and builds upon the existing body of knowledge.

What is the purpose of literature review?

A literature review serves several important purposes within academic and research contexts. Here are some key objectives and functions of a literature review: 2  

• Contextualizing the Research Problem: The literature review provides a background and context for the research problem under investigation. It helps to situate the study within the existing body of knowledge. 
• Identifying Gaps in Knowledge: By identifying gaps, contradictions, or areas requiring further research, the researcher can shape the research question and justify the significance of the study. This is crucial for ensuring that the new research contributes something novel to the field. 
• Understanding Theoretical and Conceptual Frameworks: Literature reviews help researchers gain an understanding of the theoretical and conceptual frameworks used in previous studies. This aids in the development of a theoretical framework for the current research. 
• Providing Methodological Insights: Another purpose of literature reviews is that it allows researchers to learn about the methodologies employed in previous studies. This can help in choosing appropriate research methods for the current study and avoiding pitfalls that others may have encountered. 
• Establishing Credibility: A well-conducted literature review demonstrates the researcher’s familiarity with existing scholarship, establishing their credibility and expertise in the field. It also helps in building a solid foundation for the new research. 
• Informing Hypotheses or Research Questions: The literature review guides the formulation of hypotheses or research questions by highlighting relevant findings and areas of uncertainty in existing literature. 

Literature review example

Let’s delve deeper with a literature review example: Let’s say your literature review is about the impact of climate change on biodiversity. You might format your literature review into sections such as the effects of climate change on habitat loss and species extinction, phenological changes, and marine biodiversity. Each section would then summarize and analyze relevant studies in those areas, highlighting key findings and identifying gaps in the research. The review would conclude by emphasizing the need for further research on specific aspects of the relationship between climate change and biodiversity. The following literature review template provides a glimpse into the recommended literature review structure and content, demonstrating how research findings are organized around specific themes within a broader topic. 

Literature Review on Climate Change Impacts on Biodiversity:

Climate change is a global phenomenon with far-reaching consequences, including significant impacts on biodiversity. This literature review synthesizes key findings from various studies: 

a. Habitat Loss and Species Extinction:

Climate change-induced alterations in temperature and precipitation patterns contribute to habitat loss, affecting numerous species (Thomas et al., 2004). The review discusses how these changes increase the risk of extinction, particularly for species with specific habitat requirements. 

b. Range Shifts and Phenological Changes:

Observations of range shifts and changes in the timing of biological events (phenology) are documented in response to changing climatic conditions (Parmesan & Yohe, 2003). These shifts affect ecosystems and may lead to mismatches between species and their resources. 

c. Ocean Acidification and Coral Reefs:

The review explores the impact of climate change on marine biodiversity, emphasizing ocean acidification’s threat to coral reefs (Hoegh-Guldberg et al., 2007). Changes in pH levels negatively affect coral calcification, disrupting the delicate balance of marine ecosystems. 

d. Adaptive Strategies and Conservation Efforts:

Recognizing the urgency of the situation, the literature review discusses various adaptive strategies adopted by species and conservation efforts aimed at mitigating the impacts of climate change on biodiversity (Hannah et al., 2007). It emphasizes the importance of interdisciplinary approaches for effective conservation planning. 

How to write a good literature review

Writing a literature review involves summarizing and synthesizing existing research on a particular topic. A good literature review format should include the following elements. 

Introduction: The introduction sets the stage for your literature review, providing context and introducing the main focus of your review. 

• Opening Statement: Begin with a general statement about the broader topic and its significance in the field. 
• Scope and Purpose: Clearly define the scope of your literature review. Explain the specific research question or objective you aim to address. 
• Organizational Framework: Briefly outline the structure of your literature review, indicating how you will categorize and discuss the existing research. 
• Significance of the Study: Highlight why your literature review is important and how it contributes to the understanding of the chosen topic. 
• Thesis Statement: Conclude the introduction with a concise thesis statement that outlines the main argument or perspective you will develop in the body of the literature review. 

Body: The body of the literature review is where you provide a comprehensive analysis of existing literature, grouping studies based on themes, methodologies, or other relevant criteria. 

• Organize by Theme or Concept: Group studies that share common themes, concepts, or methodologies. Discuss each theme or concept in detail, summarizing key findings and identifying gaps or areas of disagreement. 
• Critical Analysis: Evaluate the strengths and weaknesses of each study. Discuss the methodologies used, the quality of evidence, and the overall contribution of each work to the understanding of the topic. 
• Synthesis of Findings: Synthesize the information from different studies to highlight trends, patterns, or areas of consensus in the literature. 
• Identification of Gaps: Discuss any gaps or limitations in the existing research and explain how your review contributes to filling these gaps. 
• Transition between Sections: Provide smooth transitions between different themes or concepts to maintain the flow of your literature review. 

Conclusion: The conclusion of your literature review should summarize the main findings, highlight the contributions of the review, and suggest avenues for future research. 

• Summary of Key Findings: Recap the main findings from the literature and restate how they contribute to your research question or objective. 
• Contributions to the Field: Discuss the overall contribution of your literature review to the existing knowledge in the field. 
• Implications and Applications: Explore the practical implications of the findings and suggest how they might impact future research or practice. 
• Recommendations for Future Research: Identify areas that require further investigation and propose potential directions for future research in the field. 
• Final Thoughts: Conclude with a final reflection on the importance of your literature review and its relevance to the broader academic community. 

Conducting a literature review

Conducting a literature review is an essential step in research that involves reviewing and analyzing existing literature on a specific topic. It’s important to know how to do a literature review effectively, so here are the steps to follow: 1  

Choose a Topic and Define the Research Question:

• Select a topic that is relevant to your field of study. 
• Clearly define your research question or objective. Determine what specific aspect of the topic do you want to explore? 

Decide on the Scope of Your Review:

• Determine the timeframe for your literature review. Are you focusing on recent developments, or do you want a historical overview? 
• Consider the geographical scope. Is your review global, or are you focusing on a specific region? 
• Define the inclusion and exclusion criteria. What types of sources will you include? Are there specific types of studies or publications you will exclude? 

Select Databases for Searches:

• Identify relevant databases for your field. Examples include PubMed, IEEE Xplore, Scopus, Web of Science, and Google Scholar. 
• Consider searching in library catalogs, institutional repositories, and specialized databases related to your topic. 

Conduct Searches and Keep Track:

• Develop a systematic search strategy using keywords, Boolean operators (AND, OR, NOT), and other search techniques. 
• Record and document your search strategy for transparency and replicability. 
• Keep track of the articles, including publication details, abstracts, and links. Use citation management tools like EndNote, Zotero, or Mendeley to organize your references. 

Review the Literature:

• Evaluate the relevance and quality of each source. Consider the methodology, sample size, and results of studies. 
• Organize the literature by themes or key concepts. Identify patterns, trends, and gaps in the existing research. 
• Summarize key findings and arguments from each source. Compare and contrast different perspectives. 
• Identify areas where there is a consensus in the literature and where there are conflicting opinions. 
• Provide critical analysis and synthesis of the literature. What are the strengths and weaknesses of existing research? 

Organize and Write Your Literature Review:

• Literature review outline should be based on themes, chronological order, or methodological approaches. 
• Write a clear and coherent narrative that synthesizes the information gathered. 
• Use proper citations for each source and ensure consistency in your citation style (APA, MLA, Chicago, etc.). 
• Conclude your literature review by summarizing key findings, identifying gaps, and suggesting areas for future research. 

The literature review sample and detailed advice on writing and conducting a review will help you produce a well-structured report. But remember that a literature review is an ongoing process, and it may be necessary to revisit and update it as your research progresses. 

Frequently asked questions

A literature review is a critical and comprehensive analysis of existing literature (published and unpublished works) on a specific topic or research question and provides a synthesis of the current state of knowledge in a particular field. A well-conducted literature review is crucial for researchers to build upon existing knowledge, avoid duplication of efforts, and contribute to the advancement of their field. It also helps researchers situate their work within a broader context and facilitates the development of a sound theoretical and conceptual framework for their studies.

Literature review is a crucial component of research writing, providing a solid background for a research paper’s investigation. The aim is to keep professionals up to date by providing an understanding of ongoing developments within a specific field, including research methods, and experimental techniques used in that field, and present that knowledge in the form of a written report. Also, the depth and breadth of the literature review emphasizes the credibility of the scholar in his or her field.  

Before writing a literature review, it’s essential to undertake several preparatory steps to ensure that your review is well-researched, organized, and focused. This includes choosing a topic of general interest to you and doing exploratory research on that topic, writing an annotated bibliography, and noting major points, especially those that relate to the position you have taken on the topic. 

Literature reviews and academic research papers are essential components of scholarly work but serve different purposes within the academic realm. 3 A literature review aims to provide a foundation for understanding the current state of research on a particular topic, identify gaps or controversies, and lay the groundwork for future research. Therefore, it draws heavily from existing academic sources, including books, journal articles, and other scholarly publications. In contrast, an academic research paper aims to present new knowledge, contribute to the academic discourse, and advance the understanding of a specific research question. Therefore, it involves a mix of existing literature (in the introduction and literature review sections) and original data or findings obtained through research methods. 

Literature reviews are essential components of academic and research papers, and various strategies can be employed to conduct them effectively. If you want to know how to write a literature review for a research paper, here are four common approaches that are often used by researchers.  Chronological Review: This strategy involves organizing the literature based on the chronological order of publication. It helps to trace the development of a topic over time, showing how ideas, theories, and research have evolved.  Thematic Review: Thematic reviews focus on identifying and analyzing themes or topics that cut across different studies. Instead of organizing the literature chronologically, it is grouped by key themes or concepts, allowing for a comprehensive exploration of various aspects of the topic.  Methodological Review: This strategy involves organizing the literature based on the research methods employed in different studies. It helps to highlight the strengths and weaknesses of various methodologies and allows the reader to evaluate the reliability and validity of the research findings.  Theoretical Review: A theoretical review examines the literature based on the theoretical frameworks used in different studies. This approach helps to identify the key theories that have been applied to the topic and assess their contributions to the understanding of the subject.  It’s important to note that these strategies are not mutually exclusive, and a literature review may combine elements of more than one approach. The choice of strategy depends on the research question, the nature of the literature available, and the goals of the review. Additionally, other strategies, such as integrative reviews or systematic reviews, may be employed depending on the specific requirements of the research.

The literature review format can vary depending on the specific publication guidelines. However, there are some common elements and structures that are often followed. Here is a general guideline for the format of a literature review:  Introduction:   Provide an overview of the topic.  Define the scope and purpose of the literature review.  State the research question or objective.  Body:   Organize the literature by themes, concepts, or chronology.  Critically analyze and evaluate each source.  Discuss the strengths and weaknesses of the studies.  Highlight any methodological limitations or biases.  Identify patterns, connections, or contradictions in the existing research.  Conclusion:   Summarize the key points discussed in the literature review.  Highlight the research gap.  Address the research question or objective stated in the introduction.  Highlight the contributions of the review and suggest directions for future research.

Both annotated bibliographies and literature reviews involve the examination of scholarly sources. While annotated bibliographies focus on individual sources with brief annotations, literature reviews provide a more in-depth, integrated, and comprehensive analysis of existing literature on a specific topic. The key differences are as follows: 

References 

• Denney, A. S., & Tewksbury, R. (2013). How to write a literature review.  Journal of criminal justice education ,  24 (2), 218-234. 
• Pan, M. L. (2016).  Preparing literature reviews: Qualitative and quantitative approaches . Taylor & Francis. 
• Cantero, C. (2019). How to write a literature review.  San José State University Writing Center . 

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Module 2 Chapter 3: What is Empirical Literature & Where can it be Found?

In Module 1, you read about the problem of pseudoscience. Here, we revisit the issue in addressing how to locate and assess scientific or empirical literature . In this chapter you will read about:

• distinguishing between what IS and IS NOT empirical literature
• how and where to locate empirical literature for understanding diverse populations, social work problems, and social phenomena.

Probably the most important take-home lesson from this chapter is that one source is not sufficient to being well-informed on a topic. It is important to locate multiple sources of information and to critically appraise the points of convergence and divergence in the information acquired from different sources. This is especially true in emerging and poorly understood topics, as well as in answering complex questions.

What Is Empirical Literature

Social workers often need to locate valid, reliable information concerning the dimensions of a population group or subgroup, a social work problem, or social phenomenon. They might also seek information about the way specific problems or resources are distributed among the populations encountered in professional practice. Or, social workers might be interested in finding out about the way that certain people experience an event or phenomenon. Empirical literature resources may provide answers to many of these types of social work questions. In addition, resources containing data regarding social indicators may also prove helpful. Social indicators are the “facts and figures” statistics that describe the social, economic, and psychological factors that have an impact on the well-being of a community or other population group.The United Nations (UN) and the World Health Organization (WHO) are examples of organizations that monitor social indicators at a global level: dimensions of population trends (size, composition, growth/loss), health status (physical, mental, behavioral, life expectancy, maternal and infant mortality, fertility/child-bearing, and diseases like HIV/AIDS), housing and quality of sanitation (water supply, waste disposal), education and literacy, and work/income/unemployment/economics, for example.

Three characteristics stand out in empirical literature compared to other types of information available on a topic of interest: systematic observation and methodology, objectivity, and transparency/replicability/reproducibility. Let’s look a little more closely at these three features.

Systematic Observation and Methodology. The hallmark of empiricism is “repeated or reinforced observation of the facts or phenomena” (Holosko, 2006, p. 6). In empirical literature, established research methodologies and procedures are systematically applied to answer the questions of interest.

Objectivity. Gathering “facts,” whatever they may be, drives the search for empirical evidence (Holosko, 2006). Authors of empirical literature are expected to report the facts as observed, whether or not these facts support the investigators’ original hypotheses. Research integrity demands that the information be provided in an objective manner, reducing sources of investigator bias to the greatest possible extent.

Transparency and Replicability/Reproducibility.   Empirical literature is reported in such a manner that other investigators understand precisely what was done and what was found in a particular research study—to the extent that they could replicate the study to determine whether the findings are reproduced when repeated. The outcomes of an original and replication study may differ, but a reader could easily interpret the methods and procedures leading to each study’s findings.

What is NOT Empirical Literature

By now, it is probably obvious to you that literature based on “evidence” that is not developed in a systematic, objective, transparent manner is not empirical literature. On one hand, non-empirical types of professional literature may have great significance to social workers. For example, social work scholars may produce articles that are clearly identified as describing a new intervention or program without evaluative evidence, critiquing a policy or practice, or offering a tentative, untested theory about a phenomenon. These resources are useful in educating ourselves about possible issues or concerns. But, even if they are informed by evidence, they are not empirical literature. Here is a list of several sources of information that do not meet the standard of being called empirical literature:

• your course instructor’s lectures
• political statements
• advertisements
• newspapers & magazines (journalism)
• television news reports & analyses (journalism)
• many websites, Facebook postings, Twitter tweets, and blog postings
• the introductory literature review in an empirical article

You may be surprised to see the last two included in this list. Like the other sources of information listed, these sources also might lead you to look for evidence. But, they are not themselves sources of evidence. They may summarize existing evidence, but in the process of summarizing (like your instructor’s lectures), information is transformed, modified, reduced, condensed, and otherwise manipulated in such a manner that you may not see the entire, objective story. These are called secondary sources, as opposed to the original, primary source of evidence. In relying solely on secondary sources, you sacrifice your own critical appraisal and thinking about the original work—you are “buying” someone else’s interpretation and opinion about the original work, rather than developing your own interpretation and opinion. What if they got it wrong? How would you know if you did not examine the primary source for yourself? Consider the following as an example of “getting it wrong” being perpetuated.

Example: Bullying and School Shootings . One result of the heavily publicized April 1999 school shooting incident at Columbine High School (Colorado), was a heavy emphasis placed on bullying as a causal factor in these incidents (Mears, Moon, & Thielo, 2017), “creating a powerful master narrative about school shootings” (Raitanen, Sandberg, & Oksanen, 2017, p. 3). Naturally, with an identified cause, a great deal of effort was devoted to anti-bullying campaigns and interventions for enhancing resilience among youth who experience bullying.  However important these strategies might be for promoting positive mental health, preventing poor mental health, and possibly preventing suicide among school-aged children and youth, it is a mistaken belief that this can prevent school shootings (Mears, Moon, & Thielo, 2017). Many times the accounts of the perpetrators having been bullied come from potentially inaccurate third-party accounts, rather than the perpetrators themselves; bullying was not involved in all instances of school shooting; a perpetrator’s perception of being bullied/persecuted are not necessarily accurate; many who experience severe bullying do not perpetrate these incidents; bullies are the least targeted shooting victims; perpetrators of the shooting incidents were often bullying others; and, bullying is only one of many important factors associated with perpetrating such an incident (Ioannou, Hammond, & Simpson, 2015; Mears, Moon, & Thielo, 2017; Newman &Fox, 2009; Raitanen, Sandberg, & Oksanen, 2017). While mass media reports deliver bullying as a means of explaining the inexplicable, the reality is not so simple: “The connection between bullying and school shootings is elusive” (Langman, 2014), and “the relationship between bullying and school shooting is, at best, tenuous” (Mears, Moon, & Thielo, 2017, p. 940). The point is, when a narrative becomes this publicly accepted, it is difficult to sort out truth and reality without going back to original sources of information and evidence.

What May or May Not Be Empirical Literature: Literature Reviews

Investigators typically engage in a review of existing literature as they develop their own research studies. The review informs them about where knowledge gaps exist, methods previously employed by other scholars, limitations of prior work, and previous scholars’ recommendations for directing future research. These reviews may appear as a published article, without new study data being reported (see Fields, Anderson, & Dabelko-Schoeny, 2014 for example). Or, the literature review may appear in the introduction to their own empirical study report. These literature reviews are not considered to be empirical evidence sources themselves, although they may be based on empirical evidence sources. One reason is that the authors of a literature review may or may not have engaged in a systematic search process, identifying a full, rich, multi-sided pool of evidence reports.

There is, however, a type of review that applies systematic methods and is, therefore, considered to be more strongly rooted in evidence: the systematic review .

Systematic review of literature. A systematic reviewis a type of literature report where established methods have been systematically applied, objectively, in locating and synthesizing a body of literature. The systematic review report is characterized by a great deal of transparency about the methods used and the decisions made in the review process, and are replicable. Thus, it meets the criteria for empirical literature: systematic observation and methodology, objectivity, and transparency/reproducibility. We will work a great deal more with systematic reviews in the second course, SWK 3402, since they are important tools for understanding interventions. They are somewhat less common, but not unheard of, in helping us understand diverse populations, social work problems, and social phenomena.

Locating Empirical Evidence

Social workers have available a wide array of tools and resources for locating empirical evidence in the literature. These can be organized into four general categories.

Journal Articles. A number of professional journals publish articles where investigators report on the results of their empirical studies. However, it is important to know how to distinguish between empirical and non-empirical manuscripts in these journals. A key indicator, though not the only one, involves a peer review process . Many professional journals require that manuscripts undergo a process of peer review before they are accepted for publication. This means that the authors’ work is shared with scholars who provide feedback to the journal editor as to the quality of the submitted manuscript. The editor then makes a decision based on the reviewers’ feedback:

• Accept as is
• Accept with minor revisions
• Request that a revision be resubmitted (no assurance of acceptance)

When a “revise and resubmit” decision is made, the piece will go back through the review process to determine if it is now acceptable for publication and that all of the reviewers’ concerns have been adequately addressed. Editors may also reject a manuscript because it is a poor fit for the journal, based on its mission and audience, rather than sending it for review consideration.

Indicators of journal relevance. Various journals are not equally relevant to every type of question being asked of the literature. Journals may overlap to a great extent in terms of the topics they might cover; in other words, a topic might appear in multiple different journals, depending on how the topic was being addressed. For example, articles that might help answer a question about the relationship between community poverty and violence exposure might appear in several different journals, some with a focus on poverty, others with a focus on violence, and still others on community development or public health. Journal titles are sometimes a good starting point but may not give a broad enough picture of what they cover in their contents.

In focusing a literature search, it also helps to review a journal’s mission and target audience. For example, at least four different journals focus specifically on poverty:

• Journal of Children & Poverty
• Journal of Poverty
• Journal of Poverty and Social Justice
• Poverty & Public Policy

Let’s look at an example using the Journal of Poverty and Social Justice . Information about this journal is located on the journal’s webpage: http://policy.bristoluniversitypress.co.uk/journals/journal-of-poverty-and-social-justice . In the section headed “About the Journal” you can see that it is an internationally focused research journal, and that it addresses social justice issues in addition to poverty alone. The research articles are peer-reviewed (there appear to be non-empirical discussions published, as well). These descriptions about a journal are almost always available, sometimes listed as “scope” or “mission.” These descriptions also indicate the sponsorship of the journal—sponsorship may be institutional (a particular university or agency, such as Smith College Studies in Social Work ), a professional organization, such as the Council on Social Work Education (CSWE) or the National Association of Social Work (NASW), or a publishing company (e.g., Taylor & Frances, Wiley, or Sage).

Indicators of journal caliber.  Despite engaging in a peer review process, not all journals are equally rigorous. Some journals have very high rejection rates, meaning that many submitted manuscripts are rejected; others have fairly high acceptance rates, meaning that relatively few manuscripts are rejected. This is not necessarily the best indicator of quality, however, since newer journals may not be sufficiently familiar to authors with high quality manuscripts and some journals are very specific in terms of what they publish. Another index that is sometimes used is the journal’s impact factor . Impact factor is a quantitative number indicative of how often articles published in the journal are cited in the reference list of other journal articles—the statistic is calculated as the number of times on average each article published in a particular year were cited divided by the number of articles published (the number that could be cited). For example, the impact factor for the Journal of Poverty and Social Justice in our list above was 0.70 in 2017, and for the Journal of Poverty was 0.30. These are relatively low figures compared to a journal like the New England Journal of Medicine with an impact factor of 59.56! This means that articles published in that journal were, on average, cited more than 59 times in the next year or two.

Impact factors are not necessarily the best indicator of caliber, however, since many strong journals are geared toward practitioners rather than scholars, so they are less likely to be cited by other scholars but may have a large impact on a large readership. This may be the case for a journal like the one titled Social Work, the official journal of the National Association of Social Workers. It is distributed free to all members: over 120,000 practitioners, educators, and students of social work world-wide. The journal has a recent impact factor of.790. The journals with social work relevant content have impact factors in the range of 1.0 to 3.0 according to Scimago Journal & Country Rank (SJR), particularly when they are interdisciplinary journals (for example, Child Development , Journal of Marriage and Family , Child Abuse and Neglect , Child Maltreatmen t, Social Service Review , and British Journal of Social Work ). Once upon a time, a reader could locate different indexes comparing the “quality” of social work-related journals. However, the concept of “quality” is difficult to systematically define. These indexes have mostly been replaced by impact ratings, which are not necessarily the best, most robust indicators on which to rely in assessing journal quality. For example, new journals addressing cutting edge topics have not been around long enough to have been evaluated using this particular tool, and it takes a few years for articles to begin to be cited in other, later publications.

Beware of pseudo-, illegitimate, misleading, deceptive, and suspicious journals . Another side effect of living in the Age of Information is that almost anyone can circulate almost anything and call it whatever they wish. This goes for “journal” publications, as well. With the advent of open-access publishing in recent years (electronic resources available without subscription), we have seen an explosion of what are called predatory or junk journals . These are publications calling themselves journals, often with titles very similar to legitimate publications and often with fake editorial boards. These “publications” lack the integrity of legitimate journals. This caution is reminiscent of the discussions earlier in the course about pseudoscience and “snake oil” sales. The predatory nature of many apparent information dissemination outlets has to do with how scientists and scholars may be fooled into submitting their work, often paying to have their work peer-reviewed and published. There exists a “thriving black-market economy of publishing scams,” and at least two “journal blacklists” exist to help identify and avoid these scam journals (Anderson, 2017).

This issue is important to information consumers, because it creates a challenge in terms of identifying legitimate sources and publications. The challenge is particularly important to address when information from on-line, open-access journals is being considered. Open-access is not necessarily a poor choice—legitimate scientists may pay sizeable fees to legitimate publishers to make their work freely available and accessible as open-access resources. On-line access is also not necessarily a poor choice—legitimate publishers often make articles available on-line to provide timely access to the content, especially when publishing the article in hard copy will be delayed by months or even a year or more. On the other hand, stating that a journal engages in a peer-review process is no guarantee of quality—this claim may or may not be truthful. Pseudo- and junk journals may engage in some quality control practices, but may lack attention to important quality control processes, such as managing conflict of interest, reviewing content for objectivity or quality of the research conducted, or otherwise failing to adhere to industry standards (Laine & Winker, 2017).

One resource designed to assist with the process of deciphering legitimacy is the Directory of Open Access Journals (DOAJ). The DOAJ is not a comprehensive listing of all possible legitimate open-access journals, and does not guarantee quality, but it does help identify legitimate sources of information that are openly accessible and meet basic legitimacy criteria. It also is about open-access journals, not the many journals published in hard copy.

An additional caution: Search for article corrections. Despite all of the careful manuscript review and editing, sometimes an error appears in a published article. Most journals have a practice of publishing corrections in future issues. When you locate an article, it is helpful to also search for updates. Here is an example where data presented in an article’s original tables were erroneous, and a correction appeared in a later issue.

• Marchant, A., Hawton, K., Stewart A., Montgomery, P., Singaravelu, V., Lloyd, K., Purdy, N., Daine, K., & John, A. (2017). A systematic review of the relationship between internet use, self-harm and suicidal behaviour in young people: The good, the bad and the unknown. PLoS One, 12(8): e0181722. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5558917/
• Marchant, A., Hawton, K., Stewart A., Montgomery, P., Singaravelu, V., Lloyd, K., Purdy, N., Daine, K., & John, A. (2018).Correction—A systematic review of the relationship between internet use, self-harm and suicidal behaviour in young people: The good, the bad and the unknown. PLoS One, 13(3): e0193937.  http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0193937

Search Tools. In this age of information, it is all too easy to find items—the problem lies in sifting, sorting, and managing the vast numbers of items that can be found. For example, a simple Google® search for the topic “community poverty and violence” resulted in about 15,600,000 results! As a means of simplifying the process of searching for journal articles on a specific topic, a variety of helpful tools have emerged. One type of search tool has previously applied a filtering process for you: abstracting and indexing databases . These resources provide the user with the results of a search to which records have already passed through one or more filters. For example, PsycINFO is managed by the American Psychological Association and is devoted to peer-reviewed literature in behavioral science. It contains almost 4.5 million records and is growing every month. However, it may not be available to users who are not affiliated with a university library. Conducting a basic search for our topic of “community poverty and violence” in PsychINFO returned 1,119 articles. Still a large number, but far more manageable. Additional filters can be applied, such as limiting the range in publication dates, selecting only peer reviewed items, limiting the language of the published piece (English only, for example), and specified types of documents (either chapters, dissertations, or journal articles only, for example). Adding the filters for English, peer-reviewed journal articles published between 2010 and 2017 resulted in 346 documents being identified.

Just as was the case with journals, not all abstracting and indexing databases are equivalent. There may be overlap between them, but none is guaranteed to identify all relevant pieces of literature. Here are some examples to consider, depending on the nature of the questions asked of the literature:

• Academic Search Complete—multidisciplinary index of 9,300 peer-reviewed journals
• AgeLine—multidisciplinary index of aging-related content for over 600 journals
• Campbell Collaboration—systematic reviews in education, crime and justice, social welfare, international development
• Google Scholar—broad search tool for scholarly literature across many disciplines
• MEDLINE/ PubMed—National Library of medicine, access to over 15 million citations
• Oxford Bibliographies—annotated bibliographies, each is discipline specific (e.g., psychology, childhood studies, criminology, social work, sociology)
• PsycINFO/PsycLIT—international literature on material relevant to psychology and related disciplines
• SocINDEX—publications in sociology
• Social Sciences Abstracts—multiple disciplines
• Social Work Abstracts—many areas of social work are covered
• Web of Science—a “meta” search tool that searches other search tools, multiple disciplines

Placing our search for information about “community violence and poverty” into the Social Work Abstracts tool with no additional filters resulted in a manageable 54-item list. Finally, abstracting and indexing databases are another way to determine journal legitimacy: if a journal is indexed in a one of these systems, it is likely a legitimate journal. However, the converse is not necessarily true: if a journal is not indexed does not mean it is an illegitimate or pseudo-journal.

Government Sources. A great deal of information is gathered, analyzed, and disseminated by various governmental branches at the international, national, state, regional, county, and city level. Searching websites that end in.gov is one way to identify this type of information, often presented in articles, news briefs, and statistical reports. These government sources gather information in two ways: they fund external investigations through grants and contracts and they conduct research internally, through their own investigators. Here are some examples to consider, depending on the nature of the topic for which information is sought:

• Agency for Healthcare Research and Quality (AHRQ) at https://www.ahrq.gov/
• Bureau of Justice Statistics (BJS) at https://www.bjs.gov/
• Census Bureau at https://www.census.gov
• Morbidity and Mortality Weekly Report of the CDC (MMWR-CDC) at https://www.cdc.gov/mmwr/index.html
• Child Welfare Information Gateway at https://www.childwelfare.gov
• Children’s Bureau/Administration for Children & Families at https://www.acf.hhs.gov
• Forum on Child and Family Statistics at https://www.childstats.gov
• National Institutes of Health (NIH) at https://www.nih.gov , including (not limited to):
• National Institute on Aging (NIA at https://www.nia.nih.gov
• National Institute on Alcohol Abuse and Alcoholism (NIAAA) at https://www.niaaa.nih.gov
• National Institute of Child Health and Human Development (NICHD) at https://www.nichd.nih.gov
• National Institute on Drug Abuse (NIDA) at https://www.nida.nih.gov
• National Institute of Environmental Health Sciences at https://www.niehs.nih.gov
• National Institute of Mental Health (NIMH) at https://www.nimh.nih.gov
• National Institute on Minority Health and Health Disparities at https://www.nimhd.nih.gov
• National Institute of Justice (NIJ) at https://www.nij.gov
• Substance Abuse and Mental Health Services Administration (SAMHSA) at https://www.samhsa.gov/
• United States Agency for International Development at https://usaid.gov

Each state and many counties or cities have similar data sources and analysis reports available, such as Ohio Department of Health at https://www.odh.ohio.gov/healthstats/dataandstats.aspx and Franklin County at https://statisticalatlas.com/county/Ohio/Franklin-County/Overview . Data are available from international/global resources (e.g., United Nations and World Health Organization), as well.

Other Sources. The Health and Medicine Division (HMD) of the National Academies—previously the Institute of Medicine (IOM)—is a nonprofit institution that aims to provide government and private sector policy and other decision makers with objective analysis and advice for making informed health decisions. For example, in 2018 they produced reports on topics in substance use and mental health concerning the intersection of opioid use disorder and infectious disease,  the legal implications of emerging neurotechnologies, and a global agenda concerning the identification and prevention of violence (see http://www.nationalacademies.org/hmd/Global/Topics/Substance-Abuse-Mental-Health.aspx ). The exciting aspect of this resource is that it addresses many topics that are current concerns because they are hoping to help inform emerging policy. The caution to consider with this resource is the evidence is often still emerging, as well.

Numerous “think tank” organizations exist, each with a specific mission. For example, the Rand Corporation is a nonprofit organization offering research and analysis to address global issues since 1948. The institution’s mission is to help improve policy and decision making “to help individuals, families, and communities throughout the world be safer and more secure, healthier and more prosperous,” addressing issues of energy, education, health care, justice, the environment, international affairs, and national security (https://www.rand.org/about/history.html). And, for example, the Robert Woods Johnson Foundation is a philanthropic organization supporting research and research dissemination concerning health issues facing the United States. The foundation works to build a culture of health across systems of care (not only medical care) and communities (https://www.rwjf.org).

While many of these have a great deal of helpful evidence to share, they also may have a strong political bias. Objectivity is often lacking in what information these organizations provide: they provide evidence to support certain points of view. That is their purpose—to provide ideas on specific problems, many of which have a political component. Think tanks “are constantly researching solutions to a variety of the world’s problems, and arguing, advocating, and lobbying for policy changes at local, state, and federal levels” (quoted from https://thebestschools.org/features/most-influential-think-tanks/ ). Helpful information about what this one source identified as the 50 most influential U.S. think tanks includes identifying each think tank’s political orientation. For example, The Heritage Foundation is identified as conservative, whereas Human Rights Watch is identified as liberal.

While not the same as think tanks, many mission-driven organizations also sponsor or report on research, as well. For example, the National Association for Children of Alcoholics (NACOA) in the United States is a registered nonprofit organization. Its mission, along with other partnering organizations, private-sector groups, and federal agencies, is to promote policy and program development in research, prevention and treatment to provide information to, for, and about children of alcoholics (of all ages). Based on this mission, the organization supports knowledge development and information gathering on the topic and disseminates information that serves the needs of this population. While this is a worthwhile mission, there is no guarantee that the information meets the criteria for evidence with which we have been working. Evidence reported by think tank and mission-driven sources must be utilized with a great deal of caution and critical analysis!

In many instances an empirical report has not appeared in the published literature, but in the form of a technical or final report to the agency or program providing the funding for the research that was conducted. One such example is presented by a team of investigators funded by the National Institute of Justice to evaluate a program for training professionals to collect strong forensic evidence in instances of sexual assault (Patterson, Resko, Pierce-Weeks, & Campbell, 2014): https://www.ncjrs.gov/pdffiles1/nij/grants/247081.pdf . Investigators may serve in the capacity of consultant to agencies, programs, or institutions, and provide empirical evidence to inform activities and planning. One such example is presented by Maguire-Jack (2014) as a report to a state’s child maltreatment prevention board: https://preventionboard.wi.gov/Documents/InvestmentInPreventionPrograming_Final.pdf .

When Direct Answers to Questions Cannot Be Found. Sometimes social workers are interested in finding answers to complex questions or questions related to an emerging, not-yet-understood topic. This does not mean giving up on empirical literature. Instead, it requires a bit of creativity in approaching the literature. A Venn diagram might help explain this process. Consider a scenario where a social worker wishes to locate literature to answer a question concerning issues of intersectionality. Intersectionality is a social justice term applied to situations where multiple categorizations or classifications come together to create overlapping, interconnected, or multiplied disadvantage. For example, women with a substance use disorder and who have been incarcerated face a triple threat in terms of successful treatment for a substance use disorder: intersectionality exists between being a woman, having a substance use disorder, and having been in jail or prison. After searching the literature, little or no empirical evidence might have been located on this specific triple-threat topic. Instead, the social worker will need to seek literature on each of the threats individually, and possibly will find literature on pairs of topics (see Figure 3-1). There exists some literature about women’s outcomes for treatment of a substance use disorder (a), some literature about women during and following incarceration (b), and some literature about substance use disorders and incarceration (c). Despite not having a direct line on the center of the intersecting spheres of literature (d), the social worker can develop at least a partial picture based on the overlapping literatures.

Figure 3-1. Venn diagram of intersecting literature sets.

Take a moment to complete the following activity. For each statement about empirical literature, decide if it is true or false.

Social Work 3401 Coursebook Copyright © by Dr. Audrey Begun is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License , except where otherwise noted.

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Research: Overview & Approaches

• Getting Started with Undergraduate Research
• Planning & Getting Started
• Building Your Knowledge Base
• Locating Sources
• Reading Scholarly Articles
• Creating a Literature Review
• Productivity & Organizing Research
• Scholarly and Professional Relationships

Introduction to Empirical Research

Databases for finding empirical research, guided search, google scholar, examples of empirical research, sources and further reading.

• Interpretive Research
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• Introductory Video This video covers what empirical research is, what kinds of questions and methods empirical researchers use, and some tips for finding empirical research articles in your discipline.

• Guided Search: Finding Empirical Research Articles This is a hands-on tutorial that will allow you to use your own search terms to find resources.

• Study on radiation transfer in human skin for cosmetics
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SWRK 330 - Social Work Research Methods

• Literature Reviews and Empirical Research
• Databases and Search Tips
• Article Citations
• Scholarly Journal Evaulation
• Statistical Sources
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What is a Literature Review?

Empirical research.

• Annotated Bibliographies

A literature review  summarizes and discusses previous publications  on a topic.

It should also:

explore past research and its strengths and weaknesses.

be used to validate the target and methods you have chosen for your proposed research.

consist of books and scholarly journals that provide research examples of populations or settings similar to your own, as well as community resources to document the need for your proposed research.

The literature review does not present new  primary  scholarship. 

be completed in the correct citation format requested by your professor  (see the  C itations Tab)

Access Purdue  OWL's Social Work Literature Review Guidelines here .  

Empirical Research  is  research  that is based on experimentation or observation, i.e. Evidence. Such  research  is often conducted to answer a specific question or to test a hypothesis (educated guess).

How do you know if a study is empirical? Read the subheadings within the article, book, or report and look for a description of the research "methodology."  Ask yourself: Could I recreate this study and test these results?

These are some key features to look for when identifying empirical research.

NOTE:  Not all of these features will be in every empirical research article, some may be excluded, use this only as a guide.

• Statement of methodology
• Research questions are clear and measurable
• Individuals, group, subjects which are being studied are identified/defined
• Data is presented regarding the findings
• Controls or instruments such as surveys or tests were conducted
• There is a literature review
• There is discussion of the results included
• Citations/references are included

See also Empirical Research Guide

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Open government data: A systematic literature review of empirical research

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• Volume 32 , pages 2381–2404, ( 2022 )

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Open government data (OGD) holds great potential for firms and the digital economy as a whole and has attracted increasing interest in research and practice in recent years. Governments and organizations worldwide are struggling in exploiting the full potential of OGD and require a comprehensive understanding of this phenomenon. Although scientific debates in OGD research are intense and heterogeneous, the field lacks theoretical integration of OGD topics and their systematic consideration in the context of the digital economy. In addition, OGD has been widely neglected by information systems (IS) research, which promises great potential for advancing our knowledge of the OGD concept and its role in the digital economy. To fill in this gap, this study conducts a systematic literature review of 169 empirical OGD studies. In doing so, we develop a theoretical review framework of Antecedents, Decisions, Outcomes (ADO) to unify and grasp the accumulating isolated evidence on OGD in context of the digital economy and provide a theory-informed research agenda to tap the potential of IS research for OGD. Our findings reveal six related key topic clusters of OGD research and substantial gaps, opening up prospective research avenues and particularly outlining how IS research can inform and advance OGD research.

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Introduction

In the age of the digital economy, data have become a new currency and an indispensable asset for organizations. Data constitutes the foundation of innovative technologies and applications (e.g., AI and IoT) and data-driven insights and management are vital for organizational success. The advancing digitalization in the public sector over the last decade has led to large amounts of data, making the public sector one of the main producers of data in the digital economy. A substantial part of this data pool is freely provided to the public and is commonly referred to as open government data (OGD) (Kim, 2018 ; Lim, 2021 ). As the number and worldwide development of OGD initiatives continue to advance in light of its great importance (Attard et al., 2015 ; Piotrowski, 2017 ), the widely unexplored relationship between OGD and the digital economy becomes of increasing interest.

On the one hand, the digital economy itself constitutes an important driver of OGD adoption and the successful implementation of OGD programs, as IT firms, for instance, supply public administration with mission-critical tangible (e.g., hardware and software), human (e.g., IT consultants), and intangible (e.g., IT and data know how) IT resources. On the other hand, OGD constitutes a new source of innovation and economic growth for the digital economy. OGD offers the potential to create innovation and to increase economic value sustainably - for both the public and the private business sectors. It may serve organizations as a free and meaningful complementary data source in developing new products or services, as well as in improving business intelligence, R&D, and business processes (Magalhaes & Roseira, 2020 ). Thus, OGD and the digital economy are characterized by a reciprocal relationship, in which both sides benefit from each other.

While the public value of OGD in terms of leveling up the transparency of governmental activities, the political participation of citizens and the collaboration between governments and external stakeholders is well-documented (Lee et al., 2019 ; Ruijer et al., 2017 ), its great opportunities and importance for the digital economy and commercial use have been widely neglected. According to the World Wide Web Foundation ( 2017 ), the impact of OGD on the economy even in the top ten countries worldwide remains rather low, averaging four out of ten on their assessment scale. A recent survey of 178 U.S. firms on the use OGD further reveals that the frequency of application varies across different forms of use, ranging from 9% (data to fact) to 44% (data to service) (Magalhaes & Roseira, 2020 ). These figures indicate that firms and the digital economy as a whole seem to struggle in using OGD and exploiting its full potential. This is also reflected in the current research landscape, in which the OGD concept has been predominantly examined in public administration and public management research, while receiving little attention in the field of information systems (IS) and digital business research.

Given its relevance for the digital economy and close relatedness to information systems and various associated research streams (e.g., big data analytics, AI and IoT), it is essential to frame OGD more broadly in the context of the digital economy and build a bridge to IS and digital business research. The stronger involvement of the latter promises great potential for further advancing the OGD concept and filling in the gap pertaining to its role in the digital economy and commercial use, as demanded in the literature (Magalhaes & Roseira, 2020 ). In order to better familiarize the IS and digital business research community with OGD and meaningfully involve it in the scholarly discussion, it is essential to first convey a broad understanding of the concept, its research landscape, and specific starting points for potential research endeavours.

As the role of the digital economy in OGD initiatives and the value potential of OGD is influenced by the antecedents of OGD programs (e.g., sophistication of governmental data infrastructures), the decisions and actions taken by the government for implementing OGD (e.g., strategic positioning and scope of governmental OGD activity), as well as the achieved outcomes and impacts (e.g., efficiency gains through and acceptance of OGD), it seems particularly promising to examine OGD and its relevance for the digital economy along these dimensions.

The research field of OGD has been on the rise over the last decade. While the number and heterogeneity of contributions are increasing, comprehensive literature reviews remain scarce in the context of open government (Tai, 2021 ), in particular from an IS perspective. Most importantly, OGD research lacks theoretical foundation and integration of OGD topics (Hassan & Twinomurinzi, 2018 ), as well as their systematic examination in the context of the digital economy. Taken together, the literature fails to provide a theoretical framework combining theoretical and empirical insights on OGD with regard to its antecedents, decisions, and outcomes, in which the concept is framed more broadly in the context of the digital economy, and which yields a research agenda that meaningfully involves the field of IS and digital business research. To fill in this gap, we conduct a systematic literature review to address the following research questions: (1) what do we know about the antecedents, decisions, and outcomes of OGD and their relation in the context of the digital economy, and (2) how can IS and digital business research inform OGD research in this connection?

To answer these research questions, the remainder of the study is structured as follows: The next section discusses definitional issues of OGD, delineating it from the closely related concepts of open government and open data. We then present an overview of prior literature reviews related to OGD and illustrate their shortcomings and implications for the study at hand. Subsequently, we describe the methodological approach and results of the systematic review of OGD literature and develop an overarching theoretical framework to integrate and synthesize thematic clusters of OGD research. Based on this, we derive a research agenda for future research on OGD providing concrete research avenues for IS and digital business research. In the final section, the findings and implications are discussed in the context of prior research and the digital economy.

Defining open government data between the poles of open government and open data

OGD is closely related to other concepts, in particular, open government and open data. Although it may be viewed as a hybrid of both of these more general concepts (Sayogo et al., 2014 ), the extensive number of dedicated OGD studies in recent years indicates not only the increasing scholarly interest but also that OGD has established itself as a distinct concept and research stream separate from its superordinates, open government and open data. This also becomes apparent when looking at differentiated definitions of each concept. To begin with, open government is generally defined as “a multilateral, political, and social process, which includes in particular transparent, collaborative, and participatory action by government and administration” (Wirtz & Birkmeyer, 2015 , p. 382). Although OGD can be viewed as a manifestation thereof underlying the same principles of transparency, collaboration and participation (Wirtz et al., 2019 ), it sets itself apart from the general concept through its data character and thus its inherently closer link to information systems.

This data characteristic is – besides the openness – the common denominator of the OGD and the open data concept and separates both from the open government concept. A widely used definition of open data refers to data that “can be freely used, modified, and shared by anyone for any purpose” (Open Knowledge Foundation, 2021 ). The definition of open government and its delineation from open data has been subject to many debates in the literature (Bogdanović-Dinić et al., 2014 ; Karkin & Yavuz, 2017 ; Kim, 2018 ; Sayogo et al., 2014 ). Although some earlier approaches use both terms synonymously (Janssen et al., 2012 ; Veljković et al., 2014 ), there is meanwhile consensus in the literature that OGD constitutes a subform of open data and the special distinguishing mark is that OGD is data collected by means of public funding and/or provided by public sector organizations (Borgesius et al., 2015 ; Kim, 2018 ; Lim, 2021 ). Accordingly, OGD is defined as “non-confidential, non-privacy-restricted data collected using public funding that is made freely available for anyone to download” (Lim, 2021 , p. 1) or put more simple as “[p]ublic sector information made available to the public as open data” (Kim, 2018 , p. 20). Thus, its government relatedness is the decisive element distinguishing it from open data.

For a better understanding of the scope and nature of OGD, the OECD (Ubaldi, 2013 ) has developed a typology of OGD, distinguishing between seven major categories: (1) business data (e.g., chamber of commerce information and official business information with regard to company or industry data), (2) registers and data pertaining to patents, trademarks, and public tenders, (3) geographic data (e.g., topographic and address data), (4) legal data (e.g., court decisions, legislation data), (5) meteorological data (e.g., weather and climate data), (6) social data (e.g., population, employment, and public health data), and (7) transport data (e.g., vehicle registrations, traffic, and public transport data). This typology underlines the particularities of OGD and indicates its various application opportunities and value for businesses.

Prior literature reviews on OGD

The widespread scientific interest in OGD is reflected in a large number of studies, which have been the motivator and starting point for various overview studies. With a view to placing our systematic literature review in the existing field of literature reviews and determining its potential contribution to future OGD research, we first identified and analyzed the thematically relevant set of previous literature reviews. We systematically searched for literature reviews in different databases, including EBSCO (including Academic Search Premier, Business Source Premier, and EconLit with Full Text), Web of Science, ScienceDirect, ProQuest, and Google Scholar. This yielded a total of twelve dedicated literature reviews that were obtained for further analysis. To determine the scientific added value of our study, it is important to contrast the core structure and key topics of these literature reviews briefly and concisely, see Table  1 .

The literature reviews identified can be classified into three clusters: (1) reviews treating OGD as a side aspect, (2) reviews focusing on a specific aspect of OGD literature, and (3) reviews with a general approach towards OGD literature. The first cluster contains four out of twelve reviews identified. These reviews do not clearly distinguish between open government, open data, and OGD, and thus mix OGD studies in their analysis with those from one of the other research streams. To begin with, Hossain et al. ( 2016 ) provide a general systematization of the research field of open data, addressing OGD as one of five subareas and deriving corresponding research implications. The other three reviews in this cluster focus on OGD including OGD studies as a subset in their analyses . While Wirtz and Birkmeyer ( 2015 ) concentrate on the development of an integrative framework to better understand open government in general, Criado et al. ( 2018 ) attempt to explain the phenomenon of open government by means of a comprehensive analysis of existing literature and provide a comprehensive overview without deriving overly specific research implications. Likewise, Tai ( 2021 ) also provides a comprehensive review of open government research, focusing on three aspects, namely its conceptual development, its use and implementation, as well as the impacts or outcomes of open government initiatives. However, an integrated consideration as applied by the above-mentioned reviews in the first cluster confounds a clear picture of OGD research and carries the risk of arriving at undifferentiated and ultimately inaccurate conclusions. Therefore, it is essential to conduct review studies that are solely dedicated to the field of OGD, as is the case with the second and third cluster of review studies.

The second cluster is the largest and is composed of six out of twelve literature reviews identified. These reviews analyze a certain segment of OGD literature depending on a selected subtopic. The work of Attard et al. ( 2015 ) clearly focuses on the description of OGD initiatives and their respective components. They are less concerned with mapping and structuring the literature as a whole but rather with analyzing OGD initiatives and related approaches. In contrast, Ruijer and Martinius ( 2017 ) set their focus more specifically by examining literature and deriving specific research implications in relation to the democratic impact of OGD. Safarov et al. ( 2017 ) have a different emphasis by orienting their literature evaluation and systematization towards the development of an OGD utilization framework and pointing out utilization-specific research opportunities. Moreover, the literature review of Haini et al. ( 2020 ) has a special view upon studies concerning influence factors of OGD adoption in public sector organizations, identifying 16 influence factors and classifying them according to three dimensions (i.e., technological, organizational, and environmental). In contrast, Purwanto et al. ( 2020 ) focus on the citizen perspective in their review and analyze studies that deal with drivers of and barriers to citizen engagement with OGD. They identify seven groups of drivers and three categories of barriers, developing a conceptual model of citizen engagement with OGD. Finally, Francey and Mettler ( 2021 ) review case studies and examine empirical evidence on the effects of OGD, deriving nine stylized facts. While all of the studies in the second cluster provide valuable insights into the field of OGD, they only do so for the respective subtopic analyzed. None of these reviews systematizes the entire field of research and identifies the implications for further necessary research. Although Safarov et al. ( 2017 ) make a well-conceived attempt to broadly analyze and systematize based on their grouping along four key topics and the further subdivision thereof, their findings still remain specific in that they are primarily concerned with the utilization of OGD. Thus, the reviews in this cluster do not allow to make profound comparisons among subtopics within the field or to draw general conclusions in order to improve our understanding of relationships among subtopics and the state of research as a whole. This can only be achieved by reviews with a comprehensive perspective, like those in the third cluster of our literature review analysis.

This cluster is the smallest and comprises only two reviews, indicating the lack of reviews with a comprehensive focus on OGD research. These approaches are most relevant to our study because they likewise address the OGD topic as a whole. In doing so, Zuiderwijk et al. ( 2014 ) examine individual studies in relation to their topic and theoretical foundation. They offer a brief outlook on potential fields of research related to the three core topics they identified, including theory and development; policies, use, and innovation; as well as infrastructures and technology. Saxena’s ( 2018 ) systematic literature review likewise classifies OGD studies into three general clusters, i.e. theoretical and conceptual research, applied research, and user-focused research. Despite their valuable contributions both studies lack theoretical foundation and integration of the clusters. Moreover, both reviews each propose a very general taxonomy to structure research. Both taxonomies contain three clusters and appear to be little differentiated given the heterogeneity of the current research landscape. Paired with their purely descriptive nature of analysis, they only provide basic research implications that lack thematic specification and thoroughness.

The above-mentioned studies in each cluster constitute a thorough selection of OGD-related literature reviews in peer-reviewed journals. However, a literature search in the databases of AIS, IEEE, and ACM shows that several literature reviews on OGD have also been published in conference proceedings, which also should be acknowledged at this point. These contributions can also be classified according to the proposed clusters and are subject to the same shortcomings and criticism. While the broad and very early approach of Novais et al. ( 2013 ) can be assigned to the third cluster of reviews, all of the other review attempts belong to the second cluster, as they focus on specific aspects in connection with OGD, in particular, barriers or problems associated with OGD implementation and development (Bachtiar et al., 2020 ; Crusoe & Melin, 2018 ; Neto et al., 2018 ; Roa et al., 2019 ), but also challenges and opportunities associated with OGD (Hassan & Twinomurinzi, 2018 ), or the impact of civil servants’ behavioral factors on the opening of government data (Kleiman et al., 2020 ).

Overall, the analysis of literature reviews confirms the conceptual autonomy of OGD and its independent research stream (emphasized in the above-mentioned definitional considerations), since eight out of twelve reviews are specifically dedicated to OGD. Our findings further show that previous review approaches lack theoretical integration of OGD issues and do not consider them in the context of the digital economy. Accordingly, they do not provide answers to our research questions of what we know about the antecedents, decisions, and outcomes of OGD and their relation in connection with the digital economy and how IS and digital business research can inform OGD research in this respect. Given the increasing importance of OGD and the digital economy as well as their reciprocal relationship, it is essential for the further development and a better understanding of the OGD concept to systematically theorize and synthesize the respective body of knowledge. Our systematic literature review goes beyond prior literature reviews and addresses their shortcomings by developing a theoretical review framework of antecedents, decisions, and outcomes of OGD, elaborating them in relation to the digital economy and deriving a theory-informed research agenda to tap the potential of IS and digital business research for OGD.

Methodology of the systematic literature review

Literature selection.

The literature review is based on established methodological recommendations regarding a general literature review’s overall structure and the related process of identification and selection of relevant studies (Tranfield et al., 2003 ; Webster & Watson, 2002 ). In order to comprehensively and systematically search for and select relevant studies, we followed further procedural guidelines according to the well-established PRISMA flow process adhering to its individual steps of identification, screening, eligibility, and final inclusion (Liberati et al., 2009 ).

To identify relevant records from established and relevant academic databases, we initially conducted a title, abstract, and subject search in different databases, including EBSCO (including Academic Search Premier, Business Source Premier, and EconLit with Full Text), Web of Science, ScienceDirect, and ProQuest . The search included the terms “open government data”, “data openness”, and “open data” in combination with “government” and “governance”. For the purpose of scientific rigor and quality, the search was limited to articles published in peer-reviewed academic journals in English language (Wang et al., 2019 ). Subsequent to the identification and elimination of duplicate records, editorial notes, and comments, the retrieved articles were first screened regarding title and abstract to determine and exclude irrelevant studies. The remaining articles were then subjected to a full-text review to exclude any studies that were not empirical and whose thematic focus was not clearly attributed to the field of OGD. This initial literature approach resulted in a total of 125 articles conforming to the selection criteria. To complement this set of literature with meaningful conference papers, we likewise searched the databases of AIS, IEEE, and ACM, yielding another 37 relevant articles. To minimize the risk of missing relevant studies, we finally screened the Google Scholar database using the same search terms with attention to the same criteria, since Google Scholar is the most comprehensive database (Gusenbauer, 2019 ; Martín-Martín et al., 2020 ) and is considered to be especially useful for identifying influential studies within specific fields of research (Martín-Martín et al., 2017 ; Zientek et al., 2018 ). In this way, seven additional eligible studies were identified and added to the selection, resulting in a final set of 169 relevant studies from the overall literature search, which represents the basis of the following preparation and analysis. Similarly to the entire selection process and assessment of eligibility, the further review, coding, and classification of the literature was performed by two reviewers. They were supported by a third reviewer who took a mediating role to assist once again in case of disagreement. The analysis of the literature consisted of two steps. The first step of our approach comprised the identification of key topic clusters in the literature by means of a bottom-up coding approach in order to determine what kind of topics are actually prevalent in the literature without constraining the result to certain areas. The second step referred to the theoretical integration of these clusters by means of a framework-based approach. In the following, we explain the methodological procedures underlying these two steps of analysis in more detail.

Identification of key topic clusters

In this first step of the analysis, the individual studies were assigned to individual clusters according to their respective content and thematic structure. Due to the thematic complexity of OGD and the associated heterogeneity of research, as well as different foci of the individual studies, the development and final formulation of the individual key topic clusters were designed and refined through a stepwise systematic coding process. This coding process relied on the approach of Saldaña ( 2013 ) and incorporated techniques of initial coding and pattern coding. Initial coding is an open form of coding, in which qualitative information is broken down into discrete aspects. While initial coding is the first step of analysis and serves “as a starting point to provide the researcher with analytic leads for further exploration” (Saldaña, 2013 , p. 101), pattern coding takes the analysis to a higher and more abstract level by refining the codes developed in the initial coding step and merging them into superordinate categories. The openness of this two-step approach already indicates that it follows an inductive procedure without a predefined coding scheme. This means that the formed concepts or categories emerge from the given data, which is characteristic for a bottom-up approach (Urquhart, 2013 ). Following this procedure, relevant information from the respective studies was initially coded. The resulting codes were then carefully and repeatedly examined to determine patterns in terms of similarities, correlations, and dissimilarities. The respective key topic clusters were then compared regarding their overall degree of similarity or distinction and refined, if necessary, in order to achieve optimum accuracy and consistency. This procedure yielded a final set of six key topic clusters, including (1) general/conceptual development (OGD theory), (2) drivers/barriers (OGD antecedents), (3) adoption/usage/implementation (OGD decisions), (4) success/performance/value (OGD outcomes), (5) acceptance/satisfaction/trust in government (OGD impacts), and (6) policies/regulation/law (OGD governance). The literature was then analyzed and structured according to these key topic clusters and a number of other classification criteria, including study type, method of analysis, data collection, and research perspective. The results of this step of analysis are depicted in the overview and evolution of the OGD literature.

Theoretical integration of key topic clusters

The second step referred to the theoretical integration of these clusters and thus their arrangement in a common complex of meaning. Here, we applied a framework-based approach (Paul & Criado, 2020 ), developing an overarching theoretical review framework that organizes the theoretical relationships among the identified thematic clusters of OGD in terms of a relationship map (Watson & Webster, 2020 ). This framework-based approach to literature was informed by previous literature reviews (Kessler & Chakrabarti, 1996 ; Lane et al., 2006 ; Raisch & Birkinshaw, 2008 ) and is particularly based on the antecedents, decisions, and outcomes (ADO) framework by Paul and Benito ( 2018 ), which is regarded as “an excellent framework to organize the findings (i.e., constructs and its ensuing relationships) of past research in a structured assembly” (Lim et al., 2021 , p. 537). The ADO framework approach appeared to be particularly suitable as it provides overarching and general theoretically linked dimensions to which the specific clusters could be meaningfully assigned. Thus, the framework-based approach, i.e. the predefined dimensions of the ADO framework and their relationships given by prior literature, provides an established but at the same time only rough grid, which is specified with the core clusters identified by means of the bottom-up method in the first step of the analysis. The theoretical review framework developed in this second step of analysis and the corresponding theoretical integration of the core clusters in the context of the digital economy are presented in the synthesis of OGD literature. The framework finally also serves as a point of reference for deriving the theory-informed research agenda for IS and digital business research (Fig. 1 ).

Development of open government data research

Overview and evolution of the OGD literature

To provide a better understanding of the extent and evolution of the empirical OGD literature, this section gives a brief overview of its general development and current state. To begin with, Fig.  1 illustrates the distribution of qualitative and quantitative empirical OGD studies over the last 10 years.

Considering that OGD has evolved as an independent research stream out of general open government and open data research, it is not surprising that empirical research on OGD developed with a certain time lag in comparison to both of these more general research streams. Although OGD-related research was initially, in particular, an integral part of open government research, the first empirical and dedicated OGD studies appeared in 2011. Academic interest has increased significantly since 2014 and, measured by the number of empirical studies, of which a total of 107 (about 63%) studies are of a qualitative and 62 (about 37%) are of a quantitative design, remains high. The peak in 2016 and 2017 is due to a comparatively greater number of pertinent conferences and respective publications in these years. The decline in 2020 may be a result of the coronavirus pandemic, which has disrupted and delayed research projects and funding in general (Callaway et al., 2020 ).

Corresponding to the allocation of qualitative and quantitative empirical studies, the majority of the studies apply qualitative content analyses based on either an individual or comparative approach (61.54%). The application of quantitative methods is consequently lower in total, whereby publications using methods of complex empirical research, such as regression analysis and structural equation modeling, with a combined share of 18.93%, number even fewer, as opposed to publications based on descriptive statistics (19.53%). Figure  2 depicts the distribution of the applied methods of analysis.

Number of studies according to applied method of analysis

Table  2 presents the identified key topic clusters and provides selected descriptive statistics how these key topics have been approached in terms of study type, data collection, and research perspective.

Table  2 shows that the largest share of the research focuses on the key topic (4) OGD outcomes and accounts for 28.99% of the literature reviewed, which is not surprising given the extensive impact of OGD on different performance and success levels. The key topic, with an almost equal number of assigned studies, is the group (3) OGD decisions with 28.40%, followed by the key topics (2) OGD antecedents with 15.98%, and (1) OGD theory with 11.24%. While the share of studies in key topic (6) OGD governance remains in the double-digit percentage range (10.65%), the level of scientific interest measured by the number of publications within key topic (5) OGD impacts is significantly lower (4.73%). Furthermore, like the overall distribution of qualitative and quantitative empirical research occurs the composition with regard to the individual key topic clusters, so that the number of qualitative studies clearly predominates in each key topic. Notably, key topic (5) OGD impacts constitutes an exception, where the exact opposite is the case. This pattern can be explained by the fact that research on OGD is still at a relatively early stage.

In summary, the analysis reveals the great scope and heterogeneity of the research landscape of OGD in terms of research focus and methodology. The pronounced imbalance between qualitative and quantitative studies in favor of the former indicates that OGD is still an emerging field of research. Given this emergent state of research, quantitative empirical studies are essential to confirm causality of theoretical relationships and effects of evolving issues proposed by conceptual or qualitative research, and to address associated concerns of validity. In particular, little empirical robust knowledge is available in the areas of acceptance/satisfaction/trust in government, policies/regulation/law general/conceptual development, and drivers/barriers. This also holds when it comes to understanding the user perspective in the context of OGD, which is generally neglected in the field, but in particular in these areas. A remarkable exception to this pattern is the area of acceptance/satisfaction/trust in government, which has so far only focused on the user perspective, while disregarding the provider perspective. However, this would be especially important in view of the struggling implementation and diffusion of OGD in several public organizations. The user perspective so far has also strongly emphasized the individual level (e.g., citizens) and should increasingly consider the organizational level (e.g., firms) for a better understanding of the role of OGD in the digital economy.

Synthesis of the OGD literature

The synthesis of the OGD literature is based on the theoretical review framework and theoretically integrates the previously identified key topic clusters with reference to the digital economy. Figure  3 depicts the review framework and the theoretical relationships among the identified key topic clusters.

Overarching theoretical review framework

The framework may serve as a thematic relationship map of empirical OGD research, particularly illustrating the associations among antecedents, decisions, and outcomes of OGD, as well respective focus areas of research and neglected topics. The antecedents in terms of the drivers and barriers explain the reasons for a certain behavior, while decisions determine the forms of behavior (i.e. adoption, usage, or implementation of OGD), and outcomes comprise the assessments that result from decisions and the associated behavior (i.e., success, performance, and value or acceptance, satisfaction, and trust in government) (Lim et al., 2021 ). All these processes take place in a governance and regulatory setting, in which policies, regulation, and law may affect this process in terms of institutional moderators. These layers underlie the general and conceptual development of OGD, which is the overarching object of action and knowledge, and thus constitutes the point of reference for all other elements in the framework. The synthesis of OGD literature is conducted along these dimensions in the following.

General conceptual development of OGD

Perspectives on ogd.

Regarding the general conceptual development of ‘Open Government Data’, various studies contrast four ways of perceiving the term in recent years (Alexopoulos et al., 2018 ; Gonzalez-Zapata & Heeks, 2015 ; Jetzek et al., 2013 ): (1) the bureaucratic perspective conceiving OGD as a bureaucratic mechanism to enhance information quality, effectiveness and efficiency of government policy making, and legitimacy of polices (cf. Alexopoulos et al., 2018 ; Gonzalez-Zapata & Heeks 2015 ), (2) the technological perspective conceiving OGD as a technological innovation of public administration building up a data infrastructure to host a freely available public database of accurate, complete, and timely public sector data (cf. McNutt et al., 2016 ; Meijer, 2015 ), (3) the political perspective conceiving OGD as a part of government accountability to the citizens, thus providing insights into government affairs, transparency of governmental action, and the option for civic participation in policymaking (cf. Zhao & Fan, 2018 ; Meijer, 2015 ), and (4) the economic perspective conceiving OGD as source of economic value creation, providing several opportunities for the commercialization of these data in new goods and services (cf. McBride et al., 2019 ; Zhao & Fan, 2018 ; Berrone et al., 2017 ).

The digital economy’s role in the OGD ecosystem

Against the background of the OGD ecosystem model presented by Dawes et al. ( 2016 ), these perspectives of the literature can be interpreted as to portray four fields of stakeholder interactions in OGD settings. In this context, the bureaucratic perspective focuses on the interaction between the policymakers and the implementing authorities by surveilling the effects (increase in the quality of information, the effectiveness of administrative action, the legitimacy of public policy) (cf. Alexopoulos et al., 2018 ), while the political perspective regards OGD as a means for democratic processes and decision-making, as it investigates the role of OGD in government accountability, transparency, and citizen participation. Correspondingly, the technological perspective portrays the interaction between OGD providers (public authorities) and OGD intermediaries (i.e., the digital economy) by stating the technical characteristics of the data infrastructure. The economic perspective, however, lays its focus upon the creation of value for the OGD customers, i.e., the citizens, by investigating how OGD yields public value to them. Against this background, firms of the digital economy assume an intermediary function matching technical data supply from the government with information demand of the OGD customers. In a nutshell, the task of digital firms in the OGD ecosystem is to access the data supplied by the government, to gather the information contained in OGD by electronic data processing and analytics software, and to commercialize this information in their products and services. Figure  4 outlines the OGD ecosystem and sketches the role of the digital economy as a data intermediary facilitating the interaction between the executive government authorities and the citizens.

Open government data ecosystem (based on Dawes et al., 2016 and Kassen, 2013 )

Scope of government activity and the digital economy

Besides the general role of the digital economy, both the scope of digital business opportunities and the business approach are crucial to the digital economy. In this context, the literature raises interesting points regarding the scope of government activity in data-based service provision. Some studies find evidence for governments simply providing public data and setting the legal and technical framework by data formats and access rights, while leaving further processing and marketizing of these data completely to interested stakeholders, like NGOs, companies, or private citizens (cf. Alexopoulos et al., 2018 ; Berrone et al., 2017 ; Dawes et al., 2016 ; McNutt et al., 2016 ). However, another strand of OGD literature finds more complex forms of governmental open data platforms, providing data via APIs and data-based apps that enable the user to filter and manipulate the chosen data set and to embed the data in other data processing programs (cf. McBride et al., 2019 ; Zhao & Fan, 2018 ; Berrone et al., 2017 ). In this case, government provides OGD products and services on its own in competition to possible private sector offerings. In this context, contemporary OGD research presents a spectrum of government involvement in the presentation and processing of publicly accessible data by presenting diverging roles of government in OGD programs, i.e. data provision and standard-setting versus data service platform hosting. Consequently, the scope of government activity and the sophistication of governmental data infrastructures for the compilation, analysis, and provision of public sector data significantly influences the economic margin and targets of digital private business with OGD. Besides the theoretical setting of the digital economy’s role in the OGD ecosystem, the antecedents of OGD programs, the decisions and actions taken by the government for OGD implementation, as well as the achieved outcomes and impacts also determine the position of the digital economy in OGD programs and how to create value from public sector data.

The following subsection provides a synthesis of the findings of previous research on the antecedents, decisions, and outcomes of OGD with special reference to the digital economy, elaborating their significance for IS and digital business research (Table  1 in the online Appendix summarizes these findings). The representative studies presented in the following subsection (and in Table  1 in the online Appendix) were selected due to their high resonance in scientific research (high Google Scholar citation score) and their publication in particularly influential scientific, peer-reviewed journals (high journal impact score).

Antecedents, decisions, and outcomes of OGD and the digital economy

Ogd antecedents: drivers and barriers.

When considering the antecedents and determinants of OGD programs, previous studies more often refer to barriers emerging from the OGD ecosystem (cf. Barry & Bannister, 2014 ; Janssen et al., 2012 ; Ruijer et al., 2017 ), rather than the drivers and enablers (cf. Young, 2020 ; Zhenbin et al., 2020 ; Susha et al., 2015 ). For the factors triggering or fostering OGD policies, the findings of previous studies distinguish among political and social factors, operational and technical properties of agency equipment, or economic opportunities for OGD usage. In case of political and social OGD determinants, political and social demand for transparency and accountability (Barry & Bannister, 2014 ; Janssen et al., 2012 ; Zhenbin et al., 2020 ) is perceived as a major trigger for OGD programs alongside with increasing citizen engagement and participation in government affairs (Young, 2020 ; Welch et al., 2016 ). Regarding the operational and technical drivers, previous studies highlight the importance of a cultural anchorage of electronic data processing and sharing in public administration (Zhenbin et al., 2020 , Yang et al., 2015 ) in combination with a well-developed data infrastructure within the agency operated by qualified specialists (Young, 2020 ; Welch et al. 2016 ). In this context, economic pressure arises from a large share of private companies providing public services to the citizens for profit. Studies such as Young ( 2020 ) find that the opportunity to augment extant or create new public services by using public sector data bears opportunities to create new sources for economic growth (cf. Young, 2020 ; Zhenbin et al., 2020 ; Susha et al., 2015 ). This is even more the case if the national economy possesses the resources for exploiting the information contained in public sector data (high GDP) and exhibits a large productivity in providing ICT services (high share of the IT industry) (cf. Young, 2020 ; Susha et al., 2015 ). In this context, the state of the digital economy as well as the maturity of governmental data infrastructures appear as drivers for both the successful implementation of OGD programs and the successful exploitation of these data in public services. Consequently, IT firms thus function as software and hardware suppliers to public administration in digitally underdeveloped economies, while they assume the role of a private sector competitor in the delivery of public services in digitally advanced countries.

Barriers to implementing an OGD policy emerge from problems with (1) data compilation on the part of the government or the executive agencies (institutional constraints), with (2) data access caused by technical failures or dysfunctional data portals (technical constraints), or with (3) data application on the part of the citizens (societal barriers). Accordingly, data compilation barriers refer to factors that hinder the respective agencies to collect, compile, or transfer suitable data due to legal constraints (Yang et al., 2015 ; Barry & Bannister, 2014 ), due to the complexity of the organizational structures of government agencies (Ruijer et al., 2017 ; Welch et al., 2016 ; Yang et al., 2015 ), and/or due to the lack of their data management capacities and capabilities (Ruijer et al., 2017 ; Young, 2020 ). In contrast, data access barriers emerge from the properties of the data infrastructure. Major impediments in data access arise from a lack in system interoperability if governmental software and data formats are not compatible with its civic counterparts (Smith & Sandberg, 2018 ; Barry & Bannister, 2014 ) or from a lack in technical support and constant updating of data platforms due to staff shortages (Janssen et al., 2012 ). Furthermore, the literature also finds that the introduction of registered access to public data creates another great obstacle for OGD as most people are unwilling to register officially on public data platforms for occasional data access (cf.Barry & Bannister, 2014 ; Ruijer et al., 2017 ). Regarding the obstacles emerging from the properties of the user, i.e. the citizens, previous research argues that the success of OGD programs is to be attached to the ability of society to make use of the published data. Obstacles emerge from the inability of the users to achieve a practical use of these data; this might either be due to the societal inability of information processing (e.g., low ICT equipment, low levels of education, low income, etc.) (Barry & Bannister, 2014 ; Ruijer et al., 2017 ), or due to the uselessness of the provided data such that the citizens cannot apply the information to achieve any value (Smith & Sandberg, 2018 ; Janssen et al., 2012 ). Considering these findings, all barriers provide starting points for digital business to step in and solve the issue. In case of data compilation constraints, IT firms adapt solutions from private sector products and services to provide a customized data infrastructure to public authorities aiming to publish their data. To overcome data access barriers, private IT firms host government data for public retrieval as business partners of public authorities and provide the information via their own data services and applications. Finally, to solve data application barriers, the digital economy provides IT specialists and data analysts processing government data and create a useful summary and analysis of OGD for the citizens.

OGD decisions: Adoption, usage, and implementation

Although the relevant drivers and obstacles open corresponding business opportunities for the digital economy, actual policy decisions regarding the adoption of OGD measures, as well as their implementation and subsequent use, are of crucial importance for business practice. As stated before, government activity in providing data-based applications to its citizens is of major importance for the type of digital business. Accordingly, previous research analyzed the decisions regarding OGD policy and strategy as well as the intensity of governmental OGD activities (Gascó-Hernandez et al., 2018 ; Dawes et al., 2016 ). Depending on the scope of governmental data processing and data-based service provision, Dawes et al. ( 2016 ) propose a spectrum of OGD policies presenting three archetypes of OGD strategy, starting with (1) the data-oriented OGD policy aiming at the provision of accurate, unbiased datasets from public sector entities without any further service features (cf. Wang & Lo, 2016 ; Yang & Wu, 2016 ), followed by (2) the intermediate program-oriented OGD policy providing public data via an OGD platform displaying basic data analysis features and APIs (cf. Chatfield & Reddick, 2017 ; Parycek et al., 2014 ), ending up with (3) the use- and user-oriented OGD policy focusing on the creation of public value by embedding public sector data within data-based public services (Gascó-Hernandez et al., 2018 ).

Despite these strategic considerations, governmental adoption decisions also have a major impact upon the organizational and technical preparations to get public administration ready for OGD (Chatfield & Reddick, 2017 ; Yang & Wu, 2016 ; Parycek et al., 2014 ). Closely connected to the strategic setting is the scope of publication permissions from high-level authorities ranging from data publication restrictions to the support of interactive data services. Furthermore, the government’s adoption decisions also shape the maturity of the authorities’ data infrastructure by defining the technical capacity as well as the interoperability and connectivity to citizen devices (Bonina & Eaton, 2020 ; Wang & Lo, 2016 ). Consequently, the ex-ante decisions regarding the adoption of OGD measures also define the way of doing business with OGD. In this regard, the strategic positioning of governmental OGD activities directly determines the scope of the intermediary role of the digital economy. In case of a data-oriented OGD program relying upon a mediocre public data infrastructure, the intermediary role of the digital economy achieves its climax as the government acts as a proper data provider, leaving data analysis, application, and embedment in public services completely to digital firms. However, privatization of data-based public services diminishes if the OGD program place special emphasis upon the user. For a user-oriented OGD program equipped with a well-developed public data infrastructure, utilizing OGD for providing data-based public services is completely in the hands of the government, whereas IT firms provide IT expertise and software solutions to the authorities.

Besides the determining character of ex-ante decisions for digital business with OGD, the ex-post decisions of the government flanking the OGD program also provide opportunities for the digital economy. Linked to the strategic setting of the OGD program is the decision for the target group and user profile of the program (Smith & Sandberg, 2018 ; Parycek et al., 2014 ). Depending on the respective policy intensity, government must decide whether (1) to grant general access for the average citizen in case of a user-oriented approach, or (2) to grant licensed commercial access enabling the embedment of OGD in the products and services offered by private IT firms in case of a program-oriented OGD approach, or (3) to grant access only to IT specialists for retrieving information via data analytics in case of a data-oriented OGD approach.

Furthermore, previous research also investigated the ensuing decisions concerning the interface design and the related features of OGD portals (Wirtz et al., 2019 ; Chatfield & Reddick, 2017 ). Accordingly, OGD portals diverge in the scope of the provided datasets, in the scope of the OGD interface as well as the scope of data service functions, ranging from mere data downloads from government websites to data service hubs created by OGD platforms. As a result, the user profile targeted by the OGD program as well as the design and features of the OGD interface shape business approaches for OGD. Accordingly, IT firms seek to gather, process, and capture value by commercializing OGD in products and services for the citizens in case of a licensed access and a low scope of OGD data service features, responding to the demand of proper data processing on the demand side of the OGD ecosystem. In case of limited specialist access and a high scope of data service functions, IT firms switch towards offering data analytics services to the authorities involved, equivalently responding to the demand of supply-sided data processing and analytics (cf. Bonina & Eaton, 2020 ).

Another relevant field for government decisions flanking the implementation of OGD programs refers to the creation of IT skills and technical expertise required for data management by public authorities (Gascó-Hernandez et al., 2018 ; Wirtz et al., 2019 ; Yang & Wu, 2016 ). Regarding the timescale and the addressees of these measures, current research distinguishes between short- to mid-term educational measures for public employees developing OGD skills and capabilities (cf. Safarov, 2019 ; Yang & Wu 2016 ) and long-term educational measures, increasing common IT knowledge among the population (cf. Gascó-Hernandez et al., 2018 ; Wirtz et al., 2018 ). Short- to mid-term OGD skill development is associated with a variety of options, ranging from internal IT trainings with the respective authorities (Yang & Wu, 2016 ) to joint ventures with the digital economy (Safarov, 2019 ). This decision area thus offers several linkages to digital business, spanning from the provision of training programs for public administration to learning-on-the-job in collaborative partnerships for OGD processing and evaluation. Regarding long-term public IT schooling, the government aims at building up IT skills and capabilities among the population in order to gain skilled employees for public administration (cf. Gascó-Hernandez et al., 2018 ). As a result, private-sector IT companies sell their know-how and IT expertise to educational institutions as mentoring partners for IT practice. All in all, the digital economy assumes the role of a catalyst in the field of digital education and training of the people - as trainers and administrative partners in the short term and as mentors in the long run.

OGD outcomes: Success, performance, and value

Finally, it is of crucial importance not only to the government and public administration whether an OGD program pays off in terms of efficiency, citizen satisfaction, and trust in government. For the digital economy, the question is whether accessing and utilizing OGD provides access to new products and services as well as whether OGD can create new markets for data-based public services. Regarding the outcomes achieved by OGD implementation, most studies refer to the internal effects upon the performance of public administration, such as efficiency gains in administrative procedures and public service provision (Mergel et al., 2018 ; Worthy, 2015 ), transparency of political decisions and policy-making (Wang & Shepherd, 2020 ; Marjanovic & Cecez-Kecmanovic, 2017 ; Jetzek et al., 2014 ), or behavioral effects upon public employees (Marjanovic & Cecez-Kecmanovic, 2017 ; Worthy, 2015 ).

In contrast to these specific administrative and political issues, some studies also refer to spill-over effects upon the interaction of citizens with public authorities (interaction effects), the distribution of information among the population (information effects), as well as the innovation of public services by utilizing OGD (commercialization/innovation effects). Considering interaction effects upon the participation and involvement of citizens into public affairs, previous studies observe a positive effect in citizen engagement in case of OGD programs. Although there is evidence of negative OGD effects upon the polarization in political debates due to different interpretations of government data (cf. Worthy, 2015 ), most studies report positive effects, such as public service innovation through co-creation with citizens and IT firms or synergy effects due to simplified data sharing in collaborations between government agencies and external service providers (Ruijer & Meijer, 2020 ; Máchová & Lněnička, 2017 ; Jetzek et al., 2014 ). Having this mind, interaction effects of OGD programs enable the digital economy to serve as a moderator, facilitating the interaction between government and citizens by easing information processing on the part of the citizens and communication to the citizens on the part of public administration. Furthermore, IT firms relying upon big data analytics might experience competitive advantages in comparison to their international competitors as the cost for gathering public sector data decreases significantly. Consequently, citizen engagement and data sharing provide economic growth potentials to the digital economy. This is also in line with the commercialization and innovation effects observed by several studies (Jetzek et al., 2019 ; Mergel et al., 2018 ; Jetzek et al., 2014 ). Accordingly, previous research finds evidence for OGD spillover effects to the private sector, as implementing OGD enables digital firms to access new information at lower cost, and to generate a footage in the public sector by developing new markets for data-based products and public services.

Acceptance, satisfaction, and trust in government

Considering the consequences on technology acceptance and citizen satisfaction triggered by OGD, previous research observes a positive impact fostered by several preconditions. In case of technology acceptance, studies find that a positive impact relies upon (1) sufficiently intense Internet usage among the population (Gonzálvez-Gallego et al., 2020 ; Afful-Dadzie & Afful-Dadzie, 2017 ), (2) the awareness of individual benefits that emerge when using and applying OGD (Zuiderwijk et al., 2015 ; De Kool & Bekkers, 2014 ), and (3) the degree of OGD usage obligation in G2C interactions (Gonzálvez-Gallego et al., 2020 ; Zuiderwijk et al., 2015 ). Considering citizen satisfaction, broad acceptance and public support of OGD and its application appear as necessary conditions alongside with a sufficiently high information quality, system quality, and service quality (cf. Gonzálvez-Gallego et al., 2020 ). Hence, the maturity of a country’s digital economy directly moderates the impact of OGD on technology acceptance and citizen satisfaction. This is due to developed digital economies displaying both a widespread use of ICT devices and their intensive usage, as well as common IT knowledge among the people. In addition, resident digital firms are in a much better position to support a well-functioning public data infrastructure in the case of an advanced IT industry.

In summary, it can be stated that from the perspective of public administration, the digital economy constitutes both a driver of OGD adoption and a warrant for successfully implementing an OGD program. From the perspective of the digital economy, however, OGD represents a new source of economic growth and business model innovation based upon the development of new resources, i.e., public sector data, and new business opportunities emerging during OGD adoption and implementation.

• Research agenda

The preceding identification of OGD key topic clusters and their synthesis into a theoretical framework with special reference to the digital economy has revealed significant points of connection to IS and digital business research and enables us to develop a theory-informed research agenda for the latter. Although the prior literature review emphasized particularly the core dimensions of the ADO framework, the findings also yield implications for the key topics (1) OGD theory and (6) OGD governance.

(1) OGD theory: General/conceptual development

As the OGD ecosystem theorizes that firms of the digital economy assume an intermediary function matching technical data supply from public authorities with the demand for information on the part of the citizens, empirical research needs to verify how this assumption holds true in practice. Furthermore, future research needs to clarify the impact of government activity and OGD infrastructure maturity upon the business models of related IT firms. Consequently, McBride et al. ( 2019 ) postulate the need for further empirical research, which would enable comparison and differentiation of individual OGD services in their emergence, orientation, and goals. McBride et al. ( 2019 ) consider this especially with regard to data platforms and OGD services, which increasingly evolve from different sources. This corresponds with the implications pointed out by other researchers who identify further needs for empirical research on the characteristics of OGD sources in connection with different national contexts (Alexopoulos et al., 2018 ), data platforms collaboratively developed in joint ventures with IT firms (Meijer & Potjer, 2018 ), and the changes in the OGD portals’ datasets over time (Di Wang et al., 2018 ). Hence, more empirical research is needed, especially case studies regarding the economic OGD perspective, to determine the scope of involvement of private IT firms in OGD programs in general as well as their function within the whole OGD ecosystem in practice. Despite that, the scope of government activity in data-based service provision needs further investigation regarding its impact on the business approach of the digital economy. Consequently, the following questions may guide further research in this direction: How are firms of the digital economy involved in contemporary OGD programs? What is the function/business of digital IT firms in respective OGD programs? How does the scope of governmental OGD activity alter the business model of digital firms?

(2) OGD antecedents: Drivers/barriers

Considering external OGD drivers and barriers, the preceding analysis of OGD research revealed the productivity of the IT industry, as well as the GDP share of the digital economy as key drivers of successful OGD programs. Thus, establishing a causal linkage between the size of the IT industry, the share of the digital economy, and the maturity of OGD programs appears as a suitable goal for further empirical research. Linked to this idea is also the idea of Shao and Saxena ( 2019 ) raising the question of how a society’s cultural characteristics and traditional values act as drivers and/or barriers to the intentions of administrative implementation and the participation of external actors within OGD initiatives. Consequently, the following research questions appear as a good starting point for analyzing OGD drivers and barriers emerging from the digital environment: Does a high productivity of IT firms and large share of the digital economy increase the success of OGD initiatives? Which socioeconomic, demographic, and cultural characteristics of the economy drive or impede OGD implementation?

Turning towards drivers and barriers from inside public authorities, Zhenbin et al. ( 2020 ), for instance, name the need to further investigate which specific drivers influence the motivation of government agencies to engage in OGD development and public service innovation. This has been similarly formulated by Fan and Zhao ( 2017 ), who, in addition to examining the question of which influences generally exert pressure on the internal, organizational orientation in relation to OGD activities, also emphasize the need for further research on the extensive influence of the media. With regard to policy constraints, Young ( 2020 ) identifies the risk within public institutions of intentionally withholding data/information that could be detrimental to the publisher and postulates the need to investigate more closely the existence of these barriers and their potentially negative consequences in the future. Considering the findings from the qualitative literature synthesis, the question arises as to whether collaboration with private IT companies results in a reduction of barriers or an activation of drivers within the agency. This could be empirically determined and investigated in particular by means of interviews and questionnaires. Possible research questions in this direction would be: To what extent do data access, data processing, and data application in public services improve due to collaboration with private IT companies? To what extent do intensive G2B interactions regarding OGD contribute to its successful implementation?

(3) OGD decisions: Adoption/usage/implementation

While synthesizing the findings of previous studies, it became clear that the strategic positioning in OGD adoption, the target groups for OGD usage, as well as the organizational OGD readiness for OGD implementation have a significant impact on the orientation of the corresponding OGD business models. In light of these findings, two promising directions of research emerge for the IS research community investigating OGD in the context of the digital economy: (1) the empirical verification of the assumed correlation between the user-orientation of governmental OGD initiatives and the predominant customer alignment of IT firms’ OGD business models, and (2) the case-study-based investigation of the causal relationship between OGD access barriers and the share of the digital economy in providing data-based public services. Overall, the need for further, user-focused research is obvious and acknowledged. For example, there is a need to identify the types of datasets users of OGD require in order to enable even more active participation and usage (Chorley, 2017 ) and to understand how external users can be motivated to become permanent participants in OGD, while respecting their job situation and other cultural influences (Hermanto et al., 2018 ). Smith and Sandberg ( 2018 ) also point out that instead of the usual data-centric research, more user-centric OGD research is needed in future. In this context, the established theories of IS and digital business research such as the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and the DeLone-McLean IS Success Model become particularly important for the further development of this field of research. Accordingly, the following research questions may guide scholars in conducting further research concerning the OGD adoption and usage approaches: How can IS theories and explanatory models, in particular, the TAM, UTAUT, and IS Success Model be applied in the context of OGD research and theory development to explain acceptance, adoption and usage behavior? How does governmental customization of OGD alter the value proposition and customer composition of OGD business models? What is the impact of OGD access restrictions on the business practices of the IT firms involved?

Another interesting avenue for further research connecting OGD to IS and digital business studies is the topic of building up relevant OGD skills and educational support. The findings from the literature synthesis suggest the digital economy to serve as a catalyst in digital education providing skills and knowledge in the short run, and innovative spirit and educational support in the long run. In this respect, Safarov ( 2019 ) points out that it might be useful to examine in more detail the design and impact of various OGD activities, such as open data awards or specific training programs. Several other researchers also discuss the necessity and value of findings based on integrative methods and trainings regarding the implementation and usage of OGD. In this way, among other things, experimental studies can be performed to determine which training methods can be used most successfully in relation to specific content and data sets in order to ensure a lasting curiosity and interest in OGD (Gascó-Hernández et al., 2018 ).

Further long-term studies will also show how government institutions’ perceptions and usage behavior change over time as the methods are compared (Altayar, 2018 ; Wang & Lo, 2016 ). Wirtz et al. ( 2018 ) postulate the need for further research to examine the degree to which the usage behavior of citizens changes over time and which situational and socio-cultural aspects play a role in this process. In this respect, in addition to the use of longitudinal studies, comparative cross-cultural or cross-country studies can also be used to identify relevant differences and investigate their consequences for user behavior (Saxena, 2018 ). Considering these demands for further research, the following research questions may inspire research regarding the role of the digital economy in creating digital OGD literacy: Do G2B partnerships in OGD increase the digital literacy of public employees? Do OGD training programs and educational measures have a greater effect on the trainees if education involves cooperation with IT firms?

(4) OGD outcomes: Success/performance/value

Since current research on OGD outcomes is concerned with the question of how OGD offers socioeconomic added value to society, there are also potential spin-offs for the digital economy in this context. In the preceding literature synthesis, it became clear that the establishment of OGD programs could generate spillover effects on the competitiveness and innovative strength of the digital economy. Accordingly, the empirical investigation of these effects by means of case studies and time series analyses appears to be a promising goal for further research. Specifically, the following research questions suggest themselves in this context: How does the successful implementation of OGD initiatives affect the competitiveness of IT firms? Is there evidence for a causal relationship between the implementation of OGD programs and economic growth in the digital economy?

However, answering these specific research questions depends largely on the ability to record and evaluate the performance and resultant success of OGD activities. Since the success of OGD activities to be determined or measured extends to many areas among public institutions and external stakeholders, it is generally difficult to comprehensively classify and evaluate success and failure. In response to the challenges posed by the above-mentioned reasons, Marmier and Mettler ( 2020 ) postulate the need for additional research on the level of dedicated quality measurement and evaluation of OGD and its measurement instruments. Similarly, Jetzek et al. ( 2019 ) argue that the answer to the question of how data constructs and their quality are to be measured at the societal level poses another future research need.

Another relevant issue involves the potential value contribution of OGD and describes the need for further research to identify the potential contribution of OGD activities in terms of overall value creation in terms of social, economic, and public value. The origin of this value creation lies in the fact that data from public institutions are first made available in an appropriate quality, wherefrom Luna-Reyes et al. ( 2019 ) derive the need for further research to identify suitable governance and leadership approaches and to examine their influence on the quality of the data to be emitted. Mergel et al. ( 2018 ) further emphasize the large amount of valuable innovations that can be triggered by OGD and point out the need for further research in this regard to broaden and strengthen existing knowledge. Magalhaes and Roseira ( 2020 ) present similar points and show that, albeit the increasing recognition of the potential value for the private business sector, the reasons for or against integrating OGD into business processes, and thus also the potential economic value that can be achieved, still often remain unexploited or even unclear. They emphasize the need for further in-depth analysis at the firm level in order to move from a general top view to explicit insights into the behavior of and consequences for firms in their interactions with OGD. A research question of central importance might consequently be: How can dedicated products and processes be explored and exploited in order to generate sustainable economic and public value in different OGD contexts?

(5) OGD impacts: Acceptance/satisfaction/trust in government

The synthesis of the existing literature on the topic of the consequences and impacts of OGD programs on the general acceptance of OGD, the satisfaction of citizens with its use, as well as the resulting trust in government policy suggests that these impacts are all the stronger in case of a well-developed digital economy. As argued above, this is due to (1) widespread usage of ICT devices among the population, (2) IT-related customer preferences and usage perceptions, and (3) technical support from private IT firms. Taking this implication as a starting point for further research raises the following questions: Does the maturity of the digital infrastructure moderate OGD acceptance and user satisfaction? Do joint ventures of government and private IT firms providing OGD services to the public increase trust in open government?

Against this background, the investigation of external stakeholders’ perceptions and preferences is of central importance and determines the need for further research to explore and scrutinize the differing perceptions and preferences of various stakeholders in terms of OGD activities and outcomes by international comparison. Further research efforts should therefore be undertaken to examine and compare preferences and perceived satisfaction at both the citizen (Saxena & Janssen, 2017 ) and corporate levels (Afful-Dadzie & Afful-Dadzie, 2017 ). Due to the small number of studies dedicated to OGD impacts, it is of interest to broaden the focus from the external stakeholders to an in-depth investigation of the acceptance and satisfaction of governmental agencies’ internal forces, as these act as a starting point or barrier to subsequent external perception and satisfaction (Barry & Bannister, 2014 ). Consequently, scientific progress within the field of OGD antecedents might also spark research efforts in OGD impacts.

(6) OGD governance: Policies/regulation/law

Following the research implications regarding the strategic alignment of OGD programs and the corresponding OGD policy intensity, two research areas become apparent within which further research efforts can contribute to a better understanding of the specific context: the normative composition and implementation of OGD and the potential impacts of norms and policies. For the research area of normative composition and implementation of OGD it is stated that the far-reaching innovations for the state and the economy emerging from the implementation and use of open data in general and OGD in particular, require dedicated and appropriate policies from state authorities. Thus, Khurshid et al. ( 2019 ) state that in the future it will be important to understand the reasons for slow diffusion and a consequently weak adoption of general data policies at the organizational and individual levels. Furthermore, procedural metadata standards and general data quality standards should be preceded by further research (Máchová & Lněnička, 2017 ; Shepherd et al., 2019 ).

In addition to general overview studies, further in-depth analyses of applied standards and directives should be conducted in the future, which in turn will help to provide stronger guidelines for the development of data policies. Regarding the potential impacts of norms and OGD policies, further research is needed to determine how the formulation and implementation of data policies and normative guidelines affect other core aspects, such as subsequent use or the general contribution to success (Kurtz et al., 2019 ). Moreover, it is necessary to investigate, how specific policies that focus on the commercial value of OGD contain the risk of conflict with other open data values (Zuiderwijk et al., 2016 ). In order to identify and classify corresponding dependencies and consequences in this context, comparative and qualitative exploratory approaches are promising to derive conclusions from related policies and directives.

In summary, a number of starting points for IS and digital business research emerge from the findings and insights of previous studies on the various OGD research areas. In the context of the consideration within the ADO framework, various parallels between the identified research questions also become apparent. To provide a general overview of these research implications, Fig.  5 reflects the relevant research questions and depicts their integration into the theoretical review framework in terms of a research agenda for IS and digital business research.

Theory-informed research agenda for IS and digital business research

Discussion and conclusion

Data have become an inherent part and essential driver of the digital economy. The field of OGD has been largely neglected by IS and digital business research, despite its great value potential for firms and the digital economy as a whole. As governments, public organizations, and firms worldwide are struggling in exploiting the full potential of OGD for the digital economy, it is essential to gain a comprehensive understanding of OGD and to frame the concept more broadly in the context of the digital economy in order to advance the field of research accordingly. On the one hand, this particularly requires greater involvement of the IS community in the very interdisciplinary field of OGD research, which is currently dominated by the public administration and public management perspective. On the other hand, it is necessary to theoretically integrate and synthesize the vast body of knowledge to identify research gaps and provide valid research directions.

An important requirement to achieve this is first and foremost conceptual clarity of OGD, which sometimes has been confounded with the related concepts of open government and open data. Our study goes beyond prior research (e.g., Hossain et al., 2016 ; Tai, 2021 ; Wirtz & Birkmeyer, 2015 ) by demonstrating and taking account of the – widely implicitly and tacitly assumed – conceptual autonomy of OGD and acknowledging it as an independent research stream closely related but still distinct from open government and open data research. This is a vital prerequisite for drawing differentiated and valid conclusions for the field and for gaining a clear understanding of the phenomenon. In this connection, we further build on and extend the general conceptual development of OGD and respective studies (e.g., Dawes et al., 2016 ; Kassen, 2013 ) by consolidating different OGD perspectives from the literature and by outlining the role of the digital economy in the OGD ecosystem and the digital economy’s relation to OGD-related government activity.

While previous research has made valuable contributions in structuring the OGD research landscape (e.g., Saxena, 2018 ; Zuiderwijk et al., 2014 ) and analysing certain OGD issues (e.g., Attard et al., 2015 ; Purwanto et al., 2020 ; Safarov et al., 2017 ), it fails to theoretically integrate the OGD concept and its key issues, and neglects the increasingly relevant relationship between OGD and the digital economy.

This study seeks to fill in this gap by conducting a systematic literature review of empirical OGD studies, which synthesizes the body of knowledge into a theoretical framework of OGD antecedents, decisions, and outcomes with special reference to the digital economy, and which further proposes a theory-informed research agenda for IS and digital business research.

Against this background, this study generally stands in line with and extends the findings of earlier comprehensive review approaches towards OGD literature, in particular those of Zuiderwijk et al. ( 2014 ) and Saxena ( 2018 ). However, these studies lack in the coherent linkage and the display of causal relationships between the different research areas as these studies mostly follow a descriptive approach attempting to present a common denominator of the characteristics of the individual studies. This study goes beyond their purely descriptive perspective by developing an overarching theoretical review framework that models the theoretical relationships of the thematic clusters identified in the literature analysis. In addition, this study also captures the more recent developments and novel empirical insights in the field of OGD. This is especially true for the area of OGD outcomes, for which research is based on a mature implementation of OGD systems in administrative practice, but also when it comes to issues such as organizational readiness and OGD skill development in the area of OGD decisions. Moreover, by examining the OGD literature with special reference to the digital economy, our study conceptually intersects with relevant IS and digital business research, demonstrating an interdisciplinary research approach that has been missing in prior OGD literature reviews.

Taken together, the theoretical attempt in conjunction with the focus on the digital economy and the associated inclusion of an IS perspective constitutes a new approach towards OGD literature that yielded novel insights into the field by integrating and explaining scientific progress in emergent topics such as in the areas of OGD decisions and OGD outcomes. Thus, the theoretical contribution of our study to the literature in terms of originality results from the theoretical review framework that theoretically integrates previously separated thematic clusters of OGD and their points of connection to IS and digital business research, thus improving our theoretical knowledge of the field of OGD and its relation to the digital economy. Overall, the synthesis of OGD literature into this theoretical framework represents the main response to our first research question of what we know about the antecedents, decisions, and outcomes of OGD and their relations in the context of the digital economy.

In this context, bridging the gap to digital business is of particular importance as this study represents the first attempt to transfer findings and insights from the mainly public administration- and public management-driven OGD studies to the IS and digital business research domains which might spark further progression in OGD research. The research agenda derived in accordance with the theoretical framework reveals how OGD research may relate to adjacent fields of IS and digital business research, such as interface design, IT and data governance, data security, big data analytics, open data, etc., and provides concrete opportunities and research questions in each thematic cluster.

Although the review provides valuable insights into each of the six key topics, the OGD outcomes appear to be of particular importance. This is not only indicated by the fact that this cluster already comprises the largest number of studies in relation to the other clusters, but also in view of very fundamental unresolved issues pertaining to the digital economy. We know today that the use of OGD opens up far-reaching opportunities for developing innovations and improving operational and business processes, for both the public and the private sector. Notwithstanding the awareness of those opportunities and increasing research on the potential benefits, the level of knowledge regarding how best to exploit and leverage economic value remains in many respects at incomplete (Magalhaes & Roseira, 2020 ; Ruijer & Meijer, 2020 ; Zuiderwijk et al., 2014 ). In particular in this context, but also in any of the other key topics, the research avenues identified indicate that OGD research may greatly benefit from the so far underrepresented IS and digital business perspective. As such it may serve as an important tool to build the bridge from OGD to IS and digital business research.

Overall, the research agenda synthesizes the answers to our second research question of how IS and digital business research can inform OGD research, in particular with regard to its role in the digital economy. The theoretical contribution of our study in terms of utility stems especially from the systematization of the complex and heterogeneous research landscape of OGD, as well as the theory-informed research agenda. The latter makes the field more accessible and tangible for IS and digital business research by showing what issues may be studied and how they are related.

However, our study is not without limitations. Merging information obtained from research databases bears a certain risk associated with information technology limitations and time delays that may prevent the full scope of relevant studies from being represented. In addition, our final sample is limited to studies in English language, which means that we may have missed potentially relevant studies in other languages. Bearing in mind that a complete selection is hardly feasible in terms of practicality and that the literature work on which this study is based was generated with respect to well-established methodological guidelines (Rowe, 2014 ; Webster & Watson, 2002 ), we are nevertheless convinced of the sufficient coverage and informative value provided by our relevant set. In addition, our analysis is limited to empirical studies and does not take account of conceptual approaches. Future research could examine whether the review framework also hold true in this connection and how empirical and conceptual OGD research differ in their distribution across the different key topics .

While our systematization and analyses enhance the level of lucidity and understanding with regard to the overall context of OGD, it should be noted that the six identified key topics require further dedicated attention in order to thoroughly interpret and understand the insights of the respective subareas. In this connection, it should further be noted that some of these topics have also been discussed in related research areas, in particular the more general field of open data, which have not been part of our literature review. Future research could synthesize these research streams and examine how they complement our findings. Finally, our comprehensive approach inherently goes at the expense of a detailed examination and discussion of each key topic. Although the majority of literature reviews on OGD have focused on a special key topic, it remains an important task for future studies to scrutinize recent, widely unexplored subtopics in OGD research, such as innovation and value creation.

In conclusion, although OGD has accumulated a substantial body of knowledge over the last decade, the field is still in an emerging stage and calls for further research to provide answers to a variety of important unresolved issues from an IS perspective. This systematic literature review contributes to a comprehensive understanding of OGD and may serve as a suitable reference point and impetus in bridging the gap between OGD and IS research and exploiting the potential of OGD for the digital economy.

Afful-Dadzie, E., & Afful-Dadzie, A. (2017). Open government data in Africa: A preference elicitation analysis of media practitioners. Government Information Quarterly, 34 (2), 244–255. https://doi.org/10.1016/j.giq.2017.02.005

Article   Google Scholar  

Alexopoulos, C., Loukis, E., Mouzakitis, S., Petychakis, M., & Charalabidis, Y. (2018). Analysing the characteristics of open government data sources in Greece. Journal of the Knowldege Economy, 9 (3), 721–753 https://search.ebscohost.com/login.aspx?direct=true&db=eoh&AN=1726821&site=ehost-live

Altayar, M. S. (2018). Motivations for open data adoption: An institutional theory perspective. Government Information Quarterly, 35 (4), 633–643. https://doi.org/10.1016/j.giq.2018.09.006

Attard, J., Orlandi, F., Scerri, S., & Auer, S. (2015). A systematic review of open government data initiatives. Government Information Quarterly, 32 (4), 399–418. https://doi.org/10.1016/j.giq.2015.07.006

Bachtiar, A., Suhardi, & Muhamad, M. (2020). Literature review of open government data. 2020 International Conference on Information Technology Systems and Innovation (ICITSI) (pp. 329–334).

Barry, E., & Bannister, F. (2014). Barriers to open data release: A view from the top. Information Polity: The International Journal of Government & Democracy in the Information Age, 19 (1/2), 129–152. https://doi.org/10.3233/IP-140327

Berrone, P., Ricart, J., & Carrasco-Farré, C. (2017). The open kimono: Toward a general framework for open data initiatives in cities. California Management Review 59 (1), 39–70. https://doi.org/10.1177/0008125616683703

Bogdanović-Dinić, S., Veljković, N., & Stoimenov, L. (2014). How open are public government data? An assessment of seven open data portals. In M. P. Rodríguez-Bolívar (Ed.), Public administration and information technology. Measuring E-government efficiency (pp. 25–44). Springer New York.

Chapter   Google Scholar  

Bonina, C., & Eaton, B. (2020). Cultivating open government data platform ecosystems through governance: Lessons from Buenos Aires, Mexico City and Montevideo. Government Information Quarterly, 37 (3). https://doi.org/10.1016/j.giq.2020.101479

Borgesius, F. Z., Gray, J., & van Eechoud, M. (2015). Open data, privacy, and fair information principles: Towards a balancing framework. Berkeley Technology Law Journal, 30 (3), 2073–2131. https://doi.org/10.15779/Z389S18

Callaway, E., Ledford, H., Viglione, G., Watson, T., & Witze, A. (2020). COVID and 2020: An extraordinary year for science. Nature, 588 (7839), 550–552. https://doi.org/10.1038/d41586-020-03437-4

Chatfield, A., & Reddick, C. (2017). A longitudinal cross-sector analysis of open data portal service capability: The case of Australian local governments. Government Information Quarterly, 34 (2), 231–243.

Chorley, K. M. (2017). The challenges presented to records management by open government data in the public sector in england. Records Management Journal, 27 (2), 149–158. https://doi.org/10.1108/RMJ-09-2016-0034

Criado, J. I., Ruvalcaba-Gómez, E. A., & Valenzuela-Mendoza, R. (2018). Revisiting the open government phenomenon. A Meta-analysis of the international literature. JeDEM - eJournal of eDemocracy and Open Government, 10 (1), 50–81. https://doi.org/10.29379/jedem.v10i1.454

Crusoe, J., & Melin, U. (2018). Investigating open government data barriers. In P. Parycek, O. Glassey, M. Janssen, H. J. Scholl, E. Tambouris, E. Kalampokis, & S. Virkar (Eds.), Lecture notes in computer science. Electronic government (pp. 169–183). Springer International Publishing.

Google Scholar  

Dawes, S. S., Vidiasova, L., & Parkhimovich, O. (2016). Planning and designing open government data programs: An ecosystem approach. Government Information Quarterly, 33 (1), 15–27. https://doi.org/10.1016/j.giq.2016.01.003

De Kool, D. & Bekkers, V. J. J. M. (2014). The perceived impact of open inspection data on the quality of education in Dutch primary schools: A parent perspective. Social Science Computer Review . https://doi.org/10.1177/0894439314560853

Fan, B., & Zhao, Y. (2017). The moderating effect of external pressure on the relationship between internal organizational factors and the quality of open government data. Government Information Quarterly, 34 (3), 396–405. https://doi.org/10.1016/j.giq.2017.08.006

Francey, A., & Mettler, T. (2021). The effects of open government data: Some stylised facts. Information Polity: The International Journal of Government & Democracy in the Information Age, 1–16. https://doi.org/10.3233/ip-200281 .

Gascó-Hernández, M., Martin, E. G., Reggi, L., Pyo, S., & Luna-Reyes, L. F. (2018). Promoting the use of open government data: Cases of training and engagement. Government Information Quarterly, 35 (2), 233–242. https://doi.org/10.1016/j.giq.2018.01.003

González-Zapata, F. & Heeks, R. (2015). The multiple meanings of open government data: Understanding different stakeholders and their perspectives. Government Information Quarterly, 32 (4), 441–452.  https://doi.org/10.1016/j.giq.2015.09.001

Gonzálvez-Gallego, N., Nieto-Torrejón, L., & Pérez-Cárceles, M. (2020). Is open data an enabler for trust? Exploring the link and the mediating role of citizen satisfaction. International Journal of Public Administration, 43 (14), 1218–1227. https://doi.org/10.1080/01900692.2019.1668412

Gusenbauer, M. (2019). Google scholar to overshadow them all? Comparing the sizes of 12 academic search engines and bibliographic databases. Scientometrics, 118 (1), 177–214. https://doi.org/10.1007/s11192-018-2958-5

Haini, S. I., AB, R., Mohd, N. Z., Zainuddin, N. M., & Ibrahim, R. (2020). Factors influencing the adoption of open government data in the public sector: A systematic literature review. International Journal on Advanced Science, Engineering and Information Technology, 10 (2), 611. https://doi.org/10.18517/ijaseit.10.2.9488

Hassan, M. I. A., & Twinomurinzi, H. (2018). A systematic literature review of open government data research: Challenges, opportunities and gaps. 2018 Open Innovations Conference (OI) (pp. 299–304).

Hermanto, A., Solimun, S., Rinaldo Fernandes, A. A., Wahyono, W., & Zulkarnain, Z. (2018). The importance of open government data for the private sector and ngos in indonesia. Digital Policy, Regulation and Governance, 20 (4), 293–309. https://search.ebscohost.com/login.aspx?direct=true&db=eoh&AN=1724283&site=ehost-live

Hossain, M. A., Dwivedi, Y. K., & Rana, N. P. (2016). State-of-the-art in open data research: Insights from existing literature and a research agenda. Journal of Organizational Computing & Electronic Commerce, 26 (1/2), 14–40. https://doi.org/10.1080/10919392.2015.1124007

Janssen, M., Charalabidis, Y., & Zuiderwijk, A. (2012). Benefits, adoption barriers and myths of open data and open government. Information Systems Management, 29 (4), 258–268. https://doi.org/10.1080/10580530.2012.716740

Jetzek, T., Avital, M., & Bjørn-Andersen, N. (2013). Generating value from open government data. In R. Baskerville, & M. Chau (Eds.), Proceedings of the 34th International Conference on Information Systems (ICIS 2013) . http://aisel.aisnet.org/cgi/viewcontent.cgi?article=1181&context=icis2013

Jetzek, T., Avital, M., & Bjørn-Andersen, N. (2014). Data-driven innovation through open government data. Journal of Theoretical and Applied Electronic Commerce Research, 9 (2), 100–120. https://doi.org/10.4067/S0718-18762014000200008

Jetzek, T., Avital, M., & Bjørn-Andersen, N. (2019). The sustainable value of open government data. Journal of the Association for Information Systems, 20 (6), 702–734. https://doi.org/10.17705/1jais.00549

Karkin, N., & Yavuz, N. (2017). An inquiry for local open government data policy: Is a proactive model of open government data portals possible in Turkey? Current Politics and Economics of the Middle East, 8 (2), 129–150 https://www.proquest.com/scholarly-journals/inquiry-local-open-government-data-policy-is/docview/2213786284/se-2?accountid=10218

Kassen, M. (2013). A promising phenomenon of open data: A case study of the Chicago open data project. Government Information Quarterly, 30 (4), 508–513. https://doi.org/10.1016/j.giq.2013.05.012

Kessler, E. H., & Chakrabarti, A. K. (1996). Innovation speed: A conceptual model of context, antecedents, and outcomes. Academy of Management Review, 21 (4), 1143–1191. https://doi.org/10.5465/amr.1996.9704071866

Khurshid, M. M., Zakaria, N. H., Rashid, A., Kazmi, R., Shafique, M. N., & Nazir Ahmad, M. (2019). Analyzing diffusion patterns of big open data as policy innovation in public sector. Computers & Electrical Engineering, 78 , 148–161. https://doi.org/10.1016/j.compeleceng.2019.07.010

Kim, H. (2018). Interlinking open government data in Korea using Administrative District knowledge graph. Journal of Information Science Theory & Practice (JIStaP), 6 (1), 18–30. https://doi.org/10.1633/JISTaP.2018.6.1.2

Kleiman, F., Meijer, S., & Janssen, M. (2020). Behavioral factors influencing the opening of government data by civil servants.  Proceedings of the 13th International Conference on Theory and Practice of Electronic Governance (ICEGOV), (pp. 529–534) . Association for Computing Machinery.

Book   Google Scholar  

Kurtz, L. P., Santos, P. M., Rover, A. J., Zuiderwijk, A., & Hinnant, C. C. (2019). Open data via websites of Brazilian superior courts of justice: Changes between 2013 and 2017. Information Polity: The International Journal of Government & Democracy in the Information Age, 24 (2), 147–162. https://doi.org/10.3233/IP-180104

Lane, P. J., Koka, B. R., & Pathak, S. (2006). The reification of absorptive capacity: A critical review and rejuvenation of the construct. Academy of Management Review, 31 (4), 833–863. https://doi.org/10.5465/amr.2006.22527456

Lee, S. Y., Díaz-Puente, J. M., & Martin, S. (2019). The contribution of open government to prosperity of society. International Journal of Public Administration, 42 (2), 144–157. https://doi.org/10.1080/01900692.2017.1405446

Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gøtzsche, P. C., Ioannidis, J. P. A., Clarke,M., Devereaux, P. J., Kleijnen, J., & Moher, D. (2009). The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: Explanation and elaboration. PLoS Medicine, 6 (7). https://doi.org/10.1371/journal.pmed.1000100

Lim, T. C. (2021). Patterns in environmental priorities revealed through government open data portals. Telematics and Informatics, 101678 . https://doi.org/10.1016/j.tele.2021.101678

Lim, W. M., Yap, S.-F., & Makkar, M. (2021). Home sharing in marketing and tourism at a tipping point: What do we know, how do we know, and where should we be heading? Journal of Business Research, 122 , 534–566. https://doi.org/10.1016/j.jbusres.2020.08.051

Luna-Reyes, L. F., Najafabadi, M. M., Zuiderwijk, A., & Hinnant, C. C. (2019). The US open data initiative: The road ahead. Information Polity: The International Journal of Government & Democracy in the Information Age, 24 (2), 163–182. https://doi.org/10.3233/IP-180106

Máchová, R., & Lněnička, M. (2017). Evaluating the quality of open data portals on the National Level. Journal of Theoretical & Applied Electronic Commerce Research, 12 (1), 21–41. https://doi.org/10.4067/S0718-18762017000100003

Magalhaes, G., & Roseira, C. (2020). Open government data and the private sector: An empirical view on business models and value creation. Government Information Quarterly, 37 (3). https://doi.org/10.1016/j.giq.2017.08.004

Marjanovic, O. & Cecez-Kecmanovic, D. (2017). Exploring the tension between transparency and datification effects of open government IS through the lens of Complex Adaptive Systems. The Journal of Strategic Information Systems, 26 (3), 210–232.  https://doi.org/10.1016/j.jsis.2017.07.001

Marmier, A., & Mettler, T. (2020). Developing an index for measuring OGD publisher compliance to good practice standards: Insights from opendata.swiss. Information Polity: The International Journal of Government & Democracy in the Information Age, 25 (1), 91–110. https://doi.org/10.3233/IP-180120

Martín-Martín, A., Orduna-Malea, E., Harzing, A.-W., & Delgado López-Cózar, E. (2017). Can we use Google scholar to identify highly-cited documents? Journal of Informetrics, 11 (1), 152–163. https://doi.org/10.1016/j.joi.2016.11.008

Martín-Martín, A., Thelwall, M., Orduna-Malea, E., & Delgado López-Cózar, E. (2020). Google Scholar, Microsoft Academic, Scopus, Dimensions, Web of Science, and OpenCitations' COCI: A multidisciplinary comparison of coverage via citations. Scientometrics, 1–36. https://doi.org/10.1007/s11192-020-03690-4 .

McBride, K., Aavik, G., Toots, M., Kalvet, T., & Krimmer, R. (2019). How does open government data driven co-creation occur? Six factors and a 'perfect storm'; insights from Chicago's food inspection forecasting model. Government Information Quarterly, 36 (1), 88–97. https://doi.org/10.1016/j.giq.2018.11.006

McNutt, J., Justice, J., Melitski, J., Ahn, M., Siddiqui, S., Carter, D., & Kline, A. (2016). The diffusion of civic technology and open government in the United States. Information Polity, 21 (2), 153–170. https://doi.org/10.3233/IP-160385

Meijer, A. (2015). Government transparency in historical perspective: From the ancient regime to open data in The Netherlands. International Journal of Public Administration, 38 (3), 189–199. https://doi.org/10.1080/01900692.2014.934837

Meijer, A., & Potjer, S. (2018). Citizen-generated open data: An explorative analysis of 25 cases. Government Information Quarterly, 35 (4), 613–621. https://doi.org/10.1016/j.giq.2018.10.004

Mergel, I., Kleibrink, A., & Sörvik, J. (2018). Open data outcomes: U.S. cities between product and process innovation. Government Information Quarterly, 35 (4), 622–632. https://doi.org/10.1016/j.giq.2018.09.004

Neto, A. J. A., Neves, D. F., Santos, L. C., Junior, M. C. R., & do Nascimento, Rogério P. C. (2018). Open government data usage overview: A systematic literature mapping.  Proceedings of the Euro American Conference on Telematics and Information Systems (EATIS) . Association for Computing Machinery.

Novais, T., Albuquerque, J. P. de, & Craveiro, G. S. (2013). An account of research on open government data (2007–2012): A systematic literature review. In Scholl H., Wimmer M.A., Tambouris E., Janssen M., & Macintosh A. (Eds.) (pp. 76–83). Gesellschaft fur Informatik (GI) . Retrieved from https://www.scopus.com/inward/record.uri?eid=2-s2.0-84918551984&partnerID=40&md5=8b722dd21af1f1c3743202eaeaae389d

Open Knowledge Foundation. (2021). Open definition: Defining open in open data, open content and open knowledge . Retrieved from http://opendefinition.org/

Parycek, P., Höchtl, J., & Ginner, M. (2014). Open Government Data Implementation Evaluation. Journal of theoretical and applied electronic commerce research, 9 (2), 80–99. https://doi.org/10.4067/S0718-18762014000200007

Paul, J., & Benito, G. R. G. (2018). A review of research on outward foreign direct investment from emerging countries, including China: What do we know, how do we know and where should we be heading? Asia Pacific Business Review, 24 (1), 90–115. https://doi.org/10.1080/13602381.2017.1357316

Paul, J., & Criado, A. R. (2020). The art of writing literature review: What do we know and what do we need to know? International Business Review, 29 (4), 101717. https://doi.org/10.1016/j.ibusrev.2020.101717

Piotrowski, S. J. (2017). The “open government reform” movement. American Review of Public Administration, 47 (2), 155–171. https://doi.org/10.1177/0275074016676575

Purwanto, A., Zuiderwijk, A., & Janssen, M. (2020). Citizen engagement with open government data. International Journal of Electronic Government Research, 16 (3), 1–25. https://doi.org/10.4018/IJEGR.2020070101

Raisch, S., & Birkinshaw, J. (2008). Organizational ambidexterity: Antecedents, outcomes, and moderators. Journal of Management, 34 (3), 375–409. https://doi.org/10.1177/0149206308316058

Roa, H. N., Loza-Aguirre, E., & Flores, P. (2019). A survey on the problems affecting the development of open government data initiatives. In Teran L., Meier A., & Pincay J. (Eds.) (pp. 157–163). Institute of Electrical and Electronics Engineers Inc. Retrieved from https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068367066&doi=10.1109%2fICEDEG.2019.8734452&partnerID=40&md5=edfd3858943a1342f976f8bc20cf71e9

Rowe, F. (2014). What literature review is not: Diversity, boundaries and recommendations. European Journal of Information Systems, 23 (3), 241–255. https://doi.org/10.1057/ejis.2014.7

Ruijer, E., Grimmelikhuijsen, S., & Meijer, A. (2017). Open data for democracy: Developing a theoretical framework for open data use. Government Information Quarterly, 34 (1), 45–52. https://doi.org/10.1016/j.giq.2017.01.001

Ruijer, E., & Martinius, E. (2017). Researching the democratic impact of open government data: A systematic literature review. Information Polity: The International Journal of Government & Democracy in the Information Age, 22 (4), 233–250. https://doi.org/10.3233/IP-170413

Ruijer, E., & Meijer, A. (2020). Open government data as an innovation process: Lessons from a living lab experiment. Public Performance & Management Review, 43 (3), 613–635. https://doi.org/10.1080/15309576.2019.1568884

Safarov, I. (2019). Institutional dimensions of open government data implementation: Evidence from the Netherlands, Sweden, and the UK. Public Performance & Management Review, 42 (2), 305–328. https://doi.org/10.1080/15309576.2018.1438296

Safarov, I., Meijer, A., & Grimmelikhuijsen, S. (2017). Utilization of open government data: A systematic literature review of types, conditions, effects and users. Information Polity: The International Journal of Government & Democracy in the Information Age, 22 (1), 1–24. https://doi.org/10.3233/IP-160012

Saldaña, J. (2013). The coding manual for qualitative researchers (2. ed.) . SAGE Publ.

Saxena, S. (2018). Summarizing the decadal literature in open government data (OGD) research: A systematic review. Foresight, 20 (6), 648–664 https://search.ebscohost.com/login.aspx?direct=true&db=eoh&AN=1754758&site=ehost-live

Saxena, S., & Janssen, M. (2017). Examining open government data (OGD) usage in India through UTAUT framework. Foresight, 19 (4), 421–436 https://search.ebscohost.com/login.aspx?direct=true&db=eoh&AN=1674894&site=ehost-live

Sayogo, D. S., Pardo, T. A., & Cook, M. (2014). A framework for benchmarking open government data efforts. 47th Hawaii International Conference on System Sciences (pp. 1896–1905).  https://doi.org/10.1109/HICSS.2014.240

Shao, D. D., & Saxena, S. (2019). Barriers to open government data (OGD) initiative in Tanzania: Stakeholders' perspectives. Growth and Change, 50 (1), 470–485. https://doi.org/10.1111/grow.12282

Shepherd, E., Bunn, J., Flinn, A., Lomas, E., Sexton, A., Brimble, S., Chorley, K., Harrison, E., Lowry, J. & Page, J. (2019). Open government data: Critical information management perspectives. Records Management Journal, 29 (1), 152–167. https://doi.org/10.1108/RMJ-08-2018-0023

Smith, G., & Sandberg, J. (2018). Barriers to innovating with open government data: Exploring experiences across service phases and user types. Information Polity: The International Journal of Government & Democracy in the Information Age, 23 (3), 249–265. https://doi.org/10.3233/IP-170045

Susha, I., Grönlund, Å., & Janssen, M. (2015). Driving factors of service innovation using open government data: An exploratory study of entrepreneurs in two countries. Information Polity: The International Journal of Government & Democracy in the Information Age, 20 (1), 19–34. https://doi.org/10.3233/IP-150353

Tai, K.-T. (2021). Open government research over a decade: A systematic review. Government Information Quarterly, 38 (2), 101566. https://doi.org/10.1016/j.giq.2021.101566

Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14 (3), 207–222. https://doi.org/10.1111/1467-8551.00375

Ubaldi, B. (2013). Open government data: towards empirical analysis of open government data initiatives. OECD working papers on public governance (No. 22) . Organisation for Economic Cooperation and Development (OECD) https://www.proquest.com/working-papers/open-government-data-towards-empirical-analysis/docview/1394263730/se-2?accountid=10218

Urquhart, C. (2013). Grounded theory for qualitative research: A practical guide . SAGE http://www.sagepub.com/upm-data/51468_Urquhart_Chapter_1.pdf

Veljković, N., Bogdanović-Dinić, S., & Stoimenov, L. (2014). Benchmarking open government: An open data perspective. Government Information Quarterly, 31 (2), 278–290. https://doi.org/10.1016/j.giq.2013.10.011

Wang, H.‑J., & Lo, J. (2016). Adoption of open government data among government agencies. Government Information Quarterly, 33 (1), 80–88. https://doi.org/10.1016/j.giq.2015.11.004

Wang, D., Chen, C., & Richards, D. (2018). A prioritization-based analysis of local open government data portals: A case study of Chinese province-level governments. Government Information Quarterly, 35 (4), 644–656. https://doi.org/10.1016/j.giq.2018.10.006

Wang, Y., Han, J. H., & Beynon-Davies, P. (2019). Understanding blockchain technology for future supply chains: A systematic literature review and research agenda. Supply Chain Management: An International Journal, 24 (1), 62–84. https://doi.org/10.1108/SCM-03-2018-0148

Wang, V., & Shepherd, D. (2020). Exploring the extent of openness of open government data – a critique of open government datasets in the UK. Government Information Quarterly, 37 (1). https://doi.org/10.1016/j.giq.2019.101405

Watson, R. T., & Webster, J. (2020). Analysing the past to prepare for the future: Writing a literature review a roadmap for release 2.0. Journal of Decision Systems, 29 (3), 129–147. https://doi.org/10.1080/12460125.2020.1798591

Webster, J., & Watson, R. T. (2002). Analyzing the past to prepare for the future: Writing a literature review. Management Information Systems Quarterly, 26 (2), xiii–xxiii. https://doi.org/10.2307/4132319

Welch, E., Feeney, M., & Park, C. H. (2016). Determinants of data sharing in U.S. city governments. Government Information Quarterly, 33 (3), 393–403. https://doi.org/10.1016/j.giq.2016.07.002

Wirtz, B. W., & Birkmeyer, S. (2015). Open government: Origin, development, and conceptual perspectives. International Journal of Public Administration, 38 (5), 381–396. https://doi.org/10.1080/01900692.2014.942735

Wirtz, B. W., Weyerer, J. C., & Rösch, M. (2018). Citizen and open government: An empirical analysis of antecedents of open government data. International Journal of Public Administration, 41 (4), 308–320. https://doi.org/10.1080/01900692.2016.1263659

Wirtz, B. W., Weyerer, J. C., & Rösch, M. (2019). Open government and citizen participation: An empirical analysis of citizen expectancy towards open government data. International Review of Administrative Sciences, 85 (3), 566–586. https://doi.org/10.1177/0020852317719996

World Wide Web Foundation. (2017). Open data barometer: Global report . Retrieved from https://opendatabarometer.org/doc/4thEdition/ODB-4thEdition-GlobalReport.pdf

Worthy, B. (2015). The impact of open data in the UK: Complex, unpredictable, and political. Public Administration, 93 (3), 788–805. https://doi.org/10.1111/padm.12166

Yang, T.-M., Lo, J., & Shiang, J. (2015). To open or not to open? Determinants of open government data. Journal of Information Science, 41 (5), 596–612. https://doi.org/10.1177/0165551515586715

Yang, T. M., & Wu, Y. J. (2016). Examining the socio-technical determinants influencing government agencies’ open data publication: A study in Taiwan. Government Information Quarterly, 33 (3):378–392. https://doi.org/10.1016/j.giq.2016.05.003

Young, M. M. (2020). Implementation of digital-era governance: The case of open data in U.S Cities. Public Administration Review, 80 (2), 305–315 https://search.ebscohost.com/login.aspx?direct=true&db=eoh&AN=1833568&site=ehost-live

Zhao, Y., & Fan, B. (2018). Exploring open government data capacity of government agency: Based on the resource-based theory. Government Information Quarterly, 35 (1), 1–12. https://doi.org/10.1016/j.giq.2018.01.002

Zhenbin, Y., Kankanhalli, A., Ha, S., & Tayi, G. K. (2020). What drives public agencies to participate in open government data initiatives? An innovation resource perspective. Information & Management, 57 (3), N.PAG-N.PAG. https://doi.org/10.1016/j.im.2019.103179

Zientek, L. R., Werner, J. M., Campuzano, M. V., & Nimon, K. (2018). The use of Google scholar for research and research dissemination. New Horizons in Adult Education and Human Resource Development, 30 (1), 39–46. https://doi.org/10.1002/nha3.20209

Zuiderwijk, A., Helbig, N., Gil-Garcia, J., & Janssen, M. (2014). Innovation through open data: A review of the state-of-the-art and an emerging research agenda. Journal of Theoretical & Applied Electronic Commerce Research, 9 (2), I–XIII. https://doi.org/10.4067/S0718-18762014000200001

Zuiderwijk, A., Janssen, M., & Dwivedi, Y. K. (2015). Acceptance and use predictors of open data technologies: Drawing upon the unified theory of acceptance and use of technology. Government Information Quarterly, 32 (4), 429–440. https://doi.org/10.1016/j.giq.2015.09.005

Zuiderwijk, A., Janssen, M., van de Kaa, G., & Poulis, K. (2016). The wicked problem of commercial value creation in open data ecosystems: Policy guidelines for governments. Information Polity: The International Journal of Government & Democracy in the Information Age, 21 (3), 223–236. https://doi.org/10.3233/IP-160391

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Wirtz, B.W., Weyerer, J.C., Becker, M. et al. Open government data: A systematic literature review of empirical research. Electron Markets 32 , 2381–2404 (2022). https://doi.org/10.1007/s12525-022-00582-8

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Lau F, Kuziemsky C, editors. Handbook of eHealth Evaluation: An Evidence-based Approach [Internet]. Victoria (BC): University of Victoria; 2017 Feb 27.

Handbook of eHealth Evaluation: An Evidence-based Approach [Internet].

Chapter 9 methods for literature reviews.

Guy Paré and Spyros Kitsiou .

9.1. Introduction

Literature reviews play a critical role in scholarship because science remains, first and foremost, a cumulative endeavour ( vom Brocke et al., 2009 ). As in any academic discipline, rigorous knowledge syntheses are becoming indispensable in keeping up with an exponentially growing eHealth literature, assisting practitioners, academics, and graduate students in finding, evaluating, and synthesizing the contents of many empirical and conceptual papers. Among other methods, literature reviews are essential for: (a) identifying what has been written on a subject or topic; (b) determining the extent to which a specific research area reveals any interpretable trends or patterns; (c) aggregating empirical findings related to a narrow research question to support evidence-based practice; (d) generating new frameworks and theories; and (e) identifying topics or questions requiring more investigation ( Paré, Trudel, Jaana, & Kitsiou, 2015 ).

Literature reviews can take two major forms. The most prevalent one is the “literature review” or “background” section within a journal paper or a chapter in a graduate thesis. This section synthesizes the extant literature and usually identifies the gaps in knowledge that the empirical study addresses ( Sylvester, Tate, & Johnstone, 2013 ). It may also provide a theoretical foundation for the proposed study, substantiate the presence of the research problem, justify the research as one that contributes something new to the cumulated knowledge, or validate the methods and approaches for the proposed study ( Hart, 1998 ; Levy & Ellis, 2006 ).

The second form of literature review, which is the focus of this chapter, constitutes an original and valuable work of research in and of itself ( Paré et al., 2015 ). Rather than providing a base for a researcher’s own work, it creates a solid starting point for all members of the community interested in a particular area or topic ( Mulrow, 1987 ). The so-called “review article” is a journal-length paper which has an overarching purpose to synthesize the literature in a field, without collecting or analyzing any primary data ( Green, Johnson, & Adams, 2006 ).

When appropriately conducted, review articles represent powerful information sources for practitioners looking for state-of-the art evidence to guide their decision-making and work practices ( Paré et al., 2015 ). Further, high-quality reviews become frequently cited pieces of work which researchers seek out as a first clear outline of the literature when undertaking empirical studies ( Cooper, 1988 ; Rowe, 2014 ). Scholars who track and gauge the impact of articles have found that review papers are cited and downloaded more often than any other type of published article ( Cronin, Ryan, & Coughlan, 2008 ; Montori, Wilczynski, Morgan, Haynes, & Hedges, 2003 ; Patsopoulos, Analatos, & Ioannidis, 2005 ). The reason for their popularity may be the fact that reading the review enables one to have an overview, if not a detailed knowledge of the area in question, as well as references to the most useful primary sources ( Cronin et al., 2008 ). Although they are not easy to conduct, the commitment to complete a review article provides a tremendous service to one’s academic community ( Paré et al., 2015 ; Petticrew & Roberts, 2006 ). Most, if not all, peer-reviewed journals in the fields of medical informatics publish review articles of some type.

The main objectives of this chapter are fourfold: (a) to provide an overview of the major steps and activities involved in conducting a stand-alone literature review; (b) to describe and contrast the different types of review articles that can contribute to the eHealth knowledge base; (c) to illustrate each review type with one or two examples from the eHealth literature; and (d) to provide a series of recommendations for prospective authors of review articles in this domain.

9.2. Overview of the Literature Review Process and Steps

As explained in Templier and Paré (2015) , there are six generic steps involved in conducting a review article:

• formulating the research question(s) and objective(s),
• searching the extant literature,
• screening for inclusion,
• assessing the quality of primary studies,
• extracting data, and
• analyzing data.

Although these steps are presented here in sequential order, one must keep in mind that the review process can be iterative and that many activities can be initiated during the planning stage and later refined during subsequent phases ( Finfgeld-Connett & Johnson, 2013 ; Kitchenham & Charters, 2007 ).

Formulating the research question(s) and objective(s): As a first step, members of the review team must appropriately justify the need for the review itself ( Petticrew & Roberts, 2006 ), identify the review’s main objective(s) ( Okoli & Schabram, 2010 ), and define the concepts or variables at the heart of their synthesis ( Cooper & Hedges, 2009 ; Webster & Watson, 2002 ). Importantly, they also need to articulate the research question(s) they propose to investigate ( Kitchenham & Charters, 2007 ). In this regard, we concur with Jesson, Matheson, and Lacey (2011) that clearly articulated research questions are key ingredients that guide the entire review methodology; they underscore the type of information that is needed, inform the search for and selection of relevant literature, and guide or orient the subsequent analysis. Searching the extant literature: The next step consists of searching the literature and making decisions about the suitability of material to be considered in the review ( Cooper, 1988 ). There exist three main coverage strategies. First, exhaustive coverage means an effort is made to be as comprehensive as possible in order to ensure that all relevant studies, published and unpublished, are included in the review and, thus, conclusions are based on this all-inclusive knowledge base. The second type of coverage consists of presenting materials that are representative of most other works in a given field or area. Often authors who adopt this strategy will search for relevant articles in a small number of top-tier journals in a field ( Paré et al., 2015 ). In the third strategy, the review team concentrates on prior works that have been central or pivotal to a particular topic. This may include empirical studies or conceptual papers that initiated a line of investigation, changed how problems or questions were framed, introduced new methods or concepts, or engendered important debate ( Cooper, 1988 ). Screening for inclusion: The following step consists of evaluating the applicability of the material identified in the preceding step ( Levy & Ellis, 2006 ; vom Brocke et al., 2009 ). Once a group of potential studies has been identified, members of the review team must screen them to determine their relevance ( Petticrew & Roberts, 2006 ). A set of predetermined rules provides a basis for including or excluding certain studies. This exercise requires a significant investment on the part of researchers, who must ensure enhanced objectivity and avoid biases or mistakes. As discussed later in this chapter, for certain types of reviews there must be at least two independent reviewers involved in the screening process and a procedure to resolve disagreements must also be in place ( Liberati et al., 2009 ; Shea et al., 2009 ). Assessing the quality of primary studies: In addition to screening material for inclusion, members of the review team may need to assess the scientific quality of the selected studies, that is, appraise the rigour of the research design and methods. Such formal assessment, which is usually conducted independently by at least two coders, helps members of the review team refine which studies to include in the final sample, determine whether or not the differences in quality may affect their conclusions, or guide how they analyze the data and interpret the findings ( Petticrew & Roberts, 2006 ). Ascribing quality scores to each primary study or considering through domain-based evaluations which study components have or have not been designed and executed appropriately makes it possible to reflect on the extent to which the selected study addresses possible biases and maximizes validity ( Shea et al., 2009 ). Extracting data: The following step involves gathering or extracting applicable information from each primary study included in the sample and deciding what is relevant to the problem of interest ( Cooper & Hedges, 2009 ). Indeed, the type of data that should be recorded mainly depends on the initial research questions ( Okoli & Schabram, 2010 ). However, important information may also be gathered about how, when, where and by whom the primary study was conducted, the research design and methods, or qualitative/quantitative results ( Cooper & Hedges, 2009 ). Analyzing and synthesizing data : As a final step, members of the review team must collate, summarize, aggregate, organize, and compare the evidence extracted from the included studies. The extracted data must be presented in a meaningful way that suggests a new contribution to the extant literature ( Jesson et al., 2011 ). Webster and Watson (2002) warn researchers that literature reviews should be much more than lists of papers and should provide a coherent lens to make sense of extant knowledge on a given topic. There exist several methods and techniques for synthesizing quantitative (e.g., frequency analysis, meta-analysis) and qualitative (e.g., grounded theory, narrative analysis, meta-ethnography) evidence ( Dixon-Woods, Agarwal, Jones, Young, & Sutton, 2005 ; Thomas & Harden, 2008 ).

9.3. Types of Review Articles and Brief Illustrations

EHealth researchers have at their disposal a number of approaches and methods for making sense out of existing literature, all with the purpose of casting current research findings into historical contexts or explaining contradictions that might exist among a set of primary research studies conducted on a particular topic. Our classification scheme is largely inspired from Paré and colleagues’ (2015) typology. Below we present and illustrate those review types that we feel are central to the growth and development of the eHealth domain.

9.3.1. Narrative Reviews

The narrative review is the “traditional” way of reviewing the extant literature and is skewed towards a qualitative interpretation of prior knowledge ( Sylvester et al., 2013 ). Put simply, a narrative review attempts to summarize or synthesize what has been written on a particular topic but does not seek generalization or cumulative knowledge from what is reviewed ( Davies, 2000 ; Green et al., 2006 ). Instead, the review team often undertakes the task of accumulating and synthesizing the literature to demonstrate the value of a particular point of view ( Baumeister & Leary, 1997 ). As such, reviewers may selectively ignore or limit the attention paid to certain studies in order to make a point. In this rather unsystematic approach, the selection of information from primary articles is subjective, lacks explicit criteria for inclusion and can lead to biased interpretations or inferences ( Green et al., 2006 ). There are several narrative reviews in the particular eHealth domain, as in all fields, which follow such an unstructured approach ( Silva et al., 2015 ; Paul et al., 2015 ).

Despite these criticisms, this type of review can be very useful in gathering together a volume of literature in a specific subject area and synthesizing it. As mentioned above, its primary purpose is to provide the reader with a comprehensive background for understanding current knowledge and highlighting the significance of new research ( Cronin et al., 2008 ). Faculty like to use narrative reviews in the classroom because they are often more up to date than textbooks, provide a single source for students to reference, and expose students to peer-reviewed literature ( Green et al., 2006 ). For researchers, narrative reviews can inspire research ideas by identifying gaps or inconsistencies in a body of knowledge, thus helping researchers to determine research questions or formulate hypotheses. Importantly, narrative reviews can also be used as educational articles to bring practitioners up to date with certain topics of issues ( Green et al., 2006 ).

Recently, there have been several efforts to introduce more rigour in narrative reviews that will elucidate common pitfalls and bring changes into their publication standards. Information systems researchers, among others, have contributed to advancing knowledge on how to structure a “traditional” review. For instance, Levy and Ellis (2006) proposed a generic framework for conducting such reviews. Their model follows the systematic data processing approach comprised of three steps, namely: (a) literature search and screening; (b) data extraction and analysis; and (c) writing the literature review. They provide detailed and very helpful instructions on how to conduct each step of the review process. As another methodological contribution, vom Brocke et al. (2009) offered a series of guidelines for conducting literature reviews, with a particular focus on how to search and extract the relevant body of knowledge. Last, Bandara, Miskon, and Fielt (2011) proposed a structured, predefined and tool-supported method to identify primary studies within a feasible scope, extract relevant content from identified articles, synthesize and analyze the findings, and effectively write and present the results of the literature review. We highly recommend that prospective authors of narrative reviews consult these useful sources before embarking on their work.

Darlow and Wen (2015) provide a good example of a highly structured narrative review in the eHealth field. These authors synthesized published articles that describe the development process of mobile health ( m-health ) interventions for patients’ cancer care self-management. As in most narrative reviews, the scope of the research questions being investigated is broad: (a) how development of these systems are carried out; (b) which methods are used to investigate these systems; and (c) what conclusions can be drawn as a result of the development of these systems. To provide clear answers to these questions, a literature search was conducted on six electronic databases and Google Scholar . The search was performed using several terms and free text words, combining them in an appropriate manner. Four inclusion and three exclusion criteria were utilized during the screening process. Both authors independently reviewed each of the identified articles to determine eligibility and extract study information. A flow diagram shows the number of studies identified, screened, and included or excluded at each stage of study selection. In terms of contributions, this review provides a series of practical recommendations for m-health intervention development.

9.3.2. Descriptive or Mapping Reviews

The primary goal of a descriptive review is to determine the extent to which a body of knowledge in a particular research topic reveals any interpretable pattern or trend with respect to pre-existing propositions, theories, methodologies or findings ( King & He, 2005 ; Paré et al., 2015 ). In contrast with narrative reviews, descriptive reviews follow a systematic and transparent procedure, including searching, screening and classifying studies ( Petersen, Vakkalanka, & Kuzniarz, 2015 ). Indeed, structured search methods are used to form a representative sample of a larger group of published works ( Paré et al., 2015 ). Further, authors of descriptive reviews extract from each study certain characteristics of interest, such as publication year, research methods, data collection techniques, and direction or strength of research outcomes (e.g., positive, negative, or non-significant) in the form of frequency analysis to produce quantitative results ( Sylvester et al., 2013 ). In essence, each study included in a descriptive review is treated as the unit of analysis and the published literature as a whole provides a database from which the authors attempt to identify any interpretable trends or draw overall conclusions about the merits of existing conceptualizations, propositions, methods or findings ( Paré et al., 2015 ). In doing so, a descriptive review may claim that its findings represent the state of the art in a particular domain ( King & He, 2005 ).

In the fields of health sciences and medical informatics, reviews that focus on examining the range, nature and evolution of a topic area are described by Anderson, Allen, Peckham, and Goodwin (2008) as mapping reviews . Like descriptive reviews, the research questions are generic and usually relate to publication patterns and trends. There is no preconceived plan to systematically review all of the literature although this can be done. Instead, researchers often present studies that are representative of most works published in a particular area and they consider a specific time frame to be mapped.

An example of this approach in the eHealth domain is offered by DeShazo, Lavallie, and Wolf (2009). The purpose of this descriptive or mapping review was to characterize publication trends in the medical informatics literature over a 20-year period (1987 to 2006). To achieve this ambitious objective, the authors performed a bibliometric analysis of medical informatics citations indexed in medline using publication trends, journal frequencies, impact factors, Medical Subject Headings (MeSH) term frequencies, and characteristics of citations. Findings revealed that there were over 77,000 medical informatics articles published during the covered period in numerous journals and that the average annual growth rate was 12%. The MeSH term analysis also suggested a strong interdisciplinary trend. Finally, average impact scores increased over time with two notable growth periods. Overall, patterns in research outputs that seem to characterize the historic trends and current components of the field of medical informatics suggest it may be a maturing discipline (DeShazo et al., 2009).

9.3.3. Scoping Reviews

Scoping reviews attempt to provide an initial indication of the potential size and nature of the extant literature on an emergent topic (Arksey & O’Malley, 2005; Daudt, van Mossel, & Scott, 2013 ; Levac, Colquhoun, & O’Brien, 2010). A scoping review may be conducted to examine the extent, range and nature of research activities in a particular area, determine the value of undertaking a full systematic review (discussed next), or identify research gaps in the extant literature ( Paré et al., 2015 ). In line with their main objective, scoping reviews usually conclude with the presentation of a detailed research agenda for future works along with potential implications for both practice and research.

Unlike narrative and descriptive reviews, the whole point of scoping the field is to be as comprehensive as possible, including grey literature (Arksey & O’Malley, 2005). Inclusion and exclusion criteria must be established to help researchers eliminate studies that are not aligned with the research questions. It is also recommended that at least two independent coders review abstracts yielded from the search strategy and then the full articles for study selection ( Daudt et al., 2013 ). The synthesized evidence from content or thematic analysis is relatively easy to present in tabular form (Arksey & O’Malley, 2005; Thomas & Harden, 2008 ).

One of the most highly cited scoping reviews in the eHealth domain was published by Archer, Fevrier-Thomas, Lokker, McKibbon, and Straus (2011) . These authors reviewed the existing literature on personal health record ( phr ) systems including design, functionality, implementation, applications, outcomes, and benefits. Seven databases were searched from 1985 to March 2010. Several search terms relating to phr s were used during this process. Two authors independently screened titles and abstracts to determine inclusion status. A second screen of full-text articles, again by two independent members of the research team, ensured that the studies described phr s. All in all, 130 articles met the criteria and their data were extracted manually into a database. The authors concluded that although there is a large amount of survey, observational, cohort/panel, and anecdotal evidence of phr benefits and satisfaction for patients, more research is needed to evaluate the results of phr implementations. Their in-depth analysis of the literature signalled that there is little solid evidence from randomized controlled trials or other studies through the use of phr s. Hence, they suggested that more research is needed that addresses the current lack of understanding of optimal functionality and usability of these systems, and how they can play a beneficial role in supporting patient self-management ( Archer et al., 2011 ).

9.3.4. Forms of Aggregative Reviews

Healthcare providers, practitioners, and policy-makers are nowadays overwhelmed with large volumes of information, including research-based evidence from numerous clinical trials and evaluation studies, assessing the effectiveness of health information technologies and interventions ( Ammenwerth & de Keizer, 2004 ; Deshazo et al., 2009 ). It is unrealistic to expect that all these disparate actors will have the time, skills, and necessary resources to identify the available evidence in the area of their expertise and consider it when making decisions. Systematic reviews that involve the rigorous application of scientific strategies aimed at limiting subjectivity and bias (i.e., systematic and random errors) can respond to this challenge.

Systematic reviews attempt to aggregate, appraise, and synthesize in a single source all empirical evidence that meet a set of previously specified eligibility criteria in order to answer a clearly formulated and often narrow research question on a particular topic of interest to support evidence-based practice ( Liberati et al., 2009 ). They adhere closely to explicit scientific principles ( Liberati et al., 2009 ) and rigorous methodological guidelines (Higgins & Green, 2008) aimed at reducing random and systematic errors that can lead to deviations from the truth in results or inferences. The use of explicit methods allows systematic reviews to aggregate a large body of research evidence, assess whether effects or relationships are in the same direction and of the same general magnitude, explain possible inconsistencies between study results, and determine the strength of the overall evidence for every outcome of interest based on the quality of included studies and the general consistency among them ( Cook, Mulrow, & Haynes, 1997 ). The main procedures of a systematic review involve:

• Formulating a review question and developing a search strategy based on explicit inclusion criteria for the identification of eligible studies (usually described in the context of a detailed review protocol).
• Searching for eligible studies using multiple databases and information sources, including grey literature sources, without any language restrictions.
• Selecting studies, extracting data, and assessing risk of bias in a duplicate manner using two independent reviewers to avoid random or systematic errors in the process.
• Analyzing data using quantitative or qualitative methods.
• Presenting results in summary of findings tables.
• Interpreting results and drawing conclusions.

Many systematic reviews, but not all, use statistical methods to combine the results of independent studies into a single quantitative estimate or summary effect size. Known as meta-analyses , these reviews use specific data extraction and statistical techniques (e.g., network, frequentist, or Bayesian meta-analyses) to calculate from each study by outcome of interest an effect size along with a confidence interval that reflects the degree of uncertainty behind the point estimate of effect ( Borenstein, Hedges, Higgins, & Rothstein, 2009 ; Deeks, Higgins, & Altman, 2008 ). Subsequently, they use fixed or random-effects analysis models to combine the results of the included studies, assess statistical heterogeneity, and calculate a weighted average of the effect estimates from the different studies, taking into account their sample sizes. The summary effect size is a value that reflects the average magnitude of the intervention effect for a particular outcome of interest or, more generally, the strength of a relationship between two variables across all studies included in the systematic review. By statistically combining data from multiple studies, meta-analyses can create more precise and reliable estimates of intervention effects than those derived from individual studies alone, when these are examined independently as discrete sources of information.

The review by Gurol-Urganci, de Jongh, Vodopivec-Jamsek, Atun, and Car (2013) on the effects of mobile phone messaging reminders for attendance at healthcare appointments is an illustrative example of a high-quality systematic review with meta-analysis. Missed appointments are a major cause of inefficiency in healthcare delivery with substantial monetary costs to health systems. These authors sought to assess whether mobile phone-based appointment reminders delivered through Short Message Service ( sms ) or Multimedia Messaging Service ( mms ) are effective in improving rates of patient attendance and reducing overall costs. To this end, they conducted a comprehensive search on multiple databases using highly sensitive search strategies without language or publication-type restrictions to identify all rct s that are eligible for inclusion. In order to minimize the risk of omitting eligible studies not captured by the original search, they supplemented all electronic searches with manual screening of trial registers and references contained in the included studies. Study selection, data extraction, and risk of bias assessments were performed inde­­pen­dently by two coders using standardized methods to ensure consistency and to eliminate potential errors. Findings from eight rct s involving 6,615 participants were pooled into meta-analyses to calculate the magnitude of effects that mobile text message reminders have on the rate of attendance at healthcare appointments compared to no reminders and phone call reminders.

Meta-analyses are regarded as powerful tools for deriving meaningful conclusions. However, there are situations in which it is neither reasonable nor appropriate to pool studies together using meta-analytic methods simply because there is extensive clinical heterogeneity between the included studies or variation in measurement tools, comparisons, or outcomes of interest. In these cases, systematic reviews can use qualitative synthesis methods such as vote counting, content analysis, classification schemes and tabulations, as an alternative approach to narratively synthesize the results of the independent studies included in the review. This form of review is known as qualitative systematic review.

A rigorous example of one such review in the eHealth domain is presented by Mickan, Atherton, Roberts, Heneghan, and Tilson (2014) on the use of handheld computers by healthcare professionals and their impact on access to information and clinical decision-making. In line with the methodological guide­lines for systematic reviews, these authors: (a) developed and registered with prospero ( www.crd.york.ac.uk/ prospero / ) an a priori review protocol; (b) conducted comprehensive searches for eligible studies using multiple databases and other supplementary strategies (e.g., forward searches); and (c) subsequently carried out study selection, data extraction, and risk of bias assessments in a duplicate manner to eliminate potential errors in the review process. Heterogeneity between the included studies in terms of reported outcomes and measures precluded the use of meta-analytic methods. To this end, the authors resorted to using narrative analysis and synthesis to describe the effectiveness of handheld computers on accessing information for clinical knowledge, adherence to safety and clinical quality guidelines, and diagnostic decision-making.

In recent years, the number of systematic reviews in the field of health informatics has increased considerably. Systematic reviews with discordant findings can cause great confusion and make it difficult for decision-makers to interpret the review-level evidence ( Moher, 2013 ). Therefore, there is a growing need for appraisal and synthesis of prior systematic reviews to ensure that decision-making is constantly informed by the best available accumulated evidence. Umbrella reviews , also known as overviews of systematic reviews, are tertiary types of evidence synthesis that aim to accomplish this; that is, they aim to compare and contrast findings from multiple systematic reviews and meta-analyses ( Becker & Oxman, 2008 ). Umbrella reviews generally adhere to the same principles and rigorous methodological guidelines used in systematic reviews. However, the unit of analysis in umbrella reviews is the systematic review rather than the primary study ( Becker & Oxman, 2008 ). Unlike systematic reviews that have a narrow focus of inquiry, umbrella reviews focus on broader research topics for which there are several potential interventions ( Smith, Devane, Begley, & Clarke, 2011 ). A recent umbrella review on the effects of home telemonitoring interventions for patients with heart failure critically appraised, compared, and synthesized evidence from 15 systematic reviews to investigate which types of home telemonitoring technologies and forms of interventions are more effective in reducing mortality and hospital admissions ( Kitsiou, Paré, & Jaana, 2015 ).

9.3.5. Realist Reviews

Realist reviews are theory-driven interpretative reviews developed to inform, enhance, or supplement conventional systematic reviews by making sense of heterogeneous evidence about complex interventions applied in diverse contexts in a way that informs policy decision-making ( Greenhalgh, Wong, Westhorp, & Pawson, 2011 ). They originated from criticisms of positivist systematic reviews which centre on their “simplistic” underlying assumptions ( Oates, 2011 ). As explained above, systematic reviews seek to identify causation. Such logic is appropriate for fields like medicine and education where findings of randomized controlled trials can be aggregated to see whether a new treatment or intervention does improve outcomes. However, many argue that it is not possible to establish such direct causal links between interventions and outcomes in fields such as social policy, management, and information systems where for any intervention there is unlikely to be a regular or consistent outcome ( Oates, 2011 ; Pawson, 2006 ; Rousseau, Manning, & Denyer, 2008 ).

To circumvent these limitations, Pawson, Greenhalgh, Harvey, and Walshe (2005) have proposed a new approach for synthesizing knowledge that seeks to unpack the mechanism of how “complex interventions” work in particular contexts. The basic research question — what works? — which is usually associated with systematic reviews changes to: what is it about this intervention that works, for whom, in what circumstances, in what respects and why? Realist reviews have no particular preference for either quantitative or qualitative evidence. As a theory-building approach, a realist review usually starts by articulating likely underlying mechanisms and then scrutinizes available evidence to find out whether and where these mechanisms are applicable ( Shepperd et al., 2009 ). Primary studies found in the extant literature are viewed as case studies which can test and modify the initial theories ( Rousseau et al., 2008 ).

The main objective pursued in the realist review conducted by Otte-Trojel, de Bont, Rundall, and van de Klundert (2014) was to examine how patient portals contribute to health service delivery and patient outcomes. The specific goals were to investigate how outcomes are produced and, most importantly, how variations in outcomes can be explained. The research team started with an exploratory review of background documents and research studies to identify ways in which patient portals may contribute to health service delivery and patient outcomes. The authors identified six main ways which represent “educated guesses” to be tested against the data in the evaluation studies. These studies were identified through a formal and systematic search in four databases between 2003 and 2013. Two members of the research team selected the articles using a pre-established list of inclusion and exclusion criteria and following a two-step procedure. The authors then extracted data from the selected articles and created several tables, one for each outcome category. They organized information to bring forward those mechanisms where patient portals contribute to outcomes and the variation in outcomes across different contexts.

9.3.6. Critical Reviews

Lastly, critical reviews aim to provide a critical evaluation and interpretive analysis of existing literature on a particular topic of interest to reveal strengths, weaknesses, contradictions, controversies, inconsistencies, and/or other important issues with respect to theories, hypotheses, research methods or results ( Baumeister & Leary, 1997 ; Kirkevold, 1997 ). Unlike other review types, critical reviews attempt to take a reflective account of the research that has been done in a particular area of interest, and assess its credibility by using appraisal instruments or critical interpretive methods. In this way, critical reviews attempt to constructively inform other scholars about the weaknesses of prior research and strengthen knowledge development by giving focus and direction to studies for further improvement ( Kirkevold, 1997 ).

Kitsiou, Paré, and Jaana (2013) provide an example of a critical review that assessed the methodological quality of prior systematic reviews of home telemonitoring studies for chronic patients. The authors conducted a comprehensive search on multiple databases to identify eligible reviews and subsequently used a validated instrument to conduct an in-depth quality appraisal. Results indicate that the majority of systematic reviews in this particular area suffer from important methodological flaws and biases that impair their internal validity and limit their usefulness for clinical and decision-making purposes. To this end, they provide a number of recommendations to strengthen knowledge development towards improving the design and execution of future reviews on home telemonitoring.

9.4. Summary

Table 9.1 outlines the main types of literature reviews that were described in the previous sub-sections and summarizes the main characteristics that distinguish one review type from another. It also includes key references to methodological guidelines and useful sources that can be used by eHealth scholars and researchers for planning and developing reviews.

Typology of Literature Reviews (adapted from Paré et al., 2015).

As shown in Table 9.1 , each review type addresses different kinds of research questions or objectives, which subsequently define and dictate the methods and approaches that need to be used to achieve the overarching goal(s) of the review. For example, in the case of narrative reviews, there is greater flexibility in searching and synthesizing articles ( Green et al., 2006 ). Researchers are often relatively free to use a diversity of approaches to search, identify, and select relevant scientific articles, describe their operational characteristics, present how the individual studies fit together, and formulate conclusions. On the other hand, systematic reviews are characterized by their high level of systematicity, rigour, and use of explicit methods, based on an “a priori” review plan that aims to minimize bias in the analysis and synthesis process (Higgins & Green, 2008). Some reviews are exploratory in nature (e.g., scoping/mapping reviews), whereas others may be conducted to discover patterns (e.g., descriptive reviews) or involve a synthesis approach that may include the critical analysis of prior research ( Paré et al., 2015 ). Hence, in order to select the most appropriate type of review, it is critical to know before embarking on a review project, why the research synthesis is conducted and what type of methods are best aligned with the pursued goals.

9.5. Concluding Remarks

In light of the increased use of evidence-based practice and research generating stronger evidence ( Grady et al., 2011 ; Lyden et al., 2013 ), review articles have become essential tools for summarizing, synthesizing, integrating or critically appraising prior knowledge in the eHealth field. As mentioned earlier, when rigorously conducted review articles represent powerful information sources for eHealth scholars and practitioners looking for state-of-the-art evidence. The typology of literature reviews we used herein will allow eHealth researchers, graduate students and practitioners to gain a better understanding of the similarities and differences between review types.

We must stress that this classification scheme does not privilege any specific type of review as being of higher quality than another ( Paré et al., 2015 ). As explained above, each type of review has its own strengths and limitations. Having said that, we realize that the methodological rigour of any review — be it qualitative, quantitative or mixed — is a critical aspect that should be considered seriously by prospective authors. In the present context, the notion of rigour refers to the reliability and validity of the review process described in section 9.2. For one thing, reliability is related to the reproducibility of the review process and steps, which is facilitated by a comprehensive documentation of the literature search process, extraction, coding and analysis performed in the review. Whether the search is comprehensive or not, whether it involves a methodical approach for data extraction and synthesis or not, it is important that the review documents in an explicit and transparent manner the steps and approach that were used in the process of its development. Next, validity characterizes the degree to which the review process was conducted appropriately. It goes beyond documentation and reflects decisions related to the selection of the sources, the search terms used, the period of time covered, the articles selected in the search, and the application of backward and forward searches ( vom Brocke et al., 2009 ). In short, the rigour of any review article is reflected by the explicitness of its methods (i.e., transparency) and the soundness of the approach used. We refer those interested in the concepts of rigour and quality to the work of Templier and Paré (2015) which offers a detailed set of methodological guidelines for conducting and evaluating various types of review articles.

To conclude, our main objective in this chapter was to demystify the various types of literature reviews that are central to the continuous development of the eHealth field. It is our hope that our descriptive account will serve as a valuable source for those conducting, evaluating or using reviews in this important and growing domain.

• Ammenwerth E., de Keizer N. An inventory of evaluation studies of information technology in health care. Trends in evaluation research, 1982-2002. International Journal of Medical Informatics. 2004; 44 (1):44–56. [ PubMed : 15778794 ]
• Anderson S., Allen P., Peckham S., Goodwin N. Asking the right questions: scoping studies in the commissioning of research on the organisation and delivery of health services. Health Research Policy and Systems. 2008; 6 (7):1–12. [ PMC free article : PMC2500008 ] [ PubMed : 18613961 ] [ CrossRef ]
• Archer N., Fevrier-Thomas U., Lokker C., McKibbon K. A., Straus S.E. Personal health records: a scoping review. Journal of American Medical Informatics Association. 2011; 18 (4):515–522. [ PMC free article : PMC3128401 ] [ PubMed : 21672914 ]
• Arksey H., O’Malley L. Scoping studies: towards a methodological framework. International Journal of Social Research Methodology. 2005; 8 (1):19–32.
• A systematic, tool-supported method for conducting literature reviews in information systems. Paper presented at the Proceedings of the 19th European Conference on Information Systems ( ecis 2011); June 9 to 11; Helsinki, Finland. 2011.
• Baumeister R. F., Leary M.R. Writing narrative literature reviews. Review of General Psychology. 1997; 1 (3):311–320.
• Becker L. A., Oxman A.D. In: Cochrane handbook for systematic reviews of interventions. Higgins J. P. T., Green S., editors. Hoboken, nj : John Wiley & Sons, Ltd; 2008. Overviews of reviews; pp. 607–631.
• Borenstein M., Hedges L., Higgins J., Rothstein H. Introduction to meta-analysis. Hoboken, nj : John Wiley & Sons Inc; 2009.
• Cook D. J., Mulrow C. D., Haynes B. Systematic reviews: Synthesis of best evidence for clinical decisions. Annals of Internal Medicine. 1997; 126 (5):376–380. [ PubMed : 9054282 ]
• Cooper H., Hedges L.V. In: The handbook of research synthesis and meta-analysis. 2nd ed. Cooper H., Hedges L. V., Valentine J. C., editors. New York: Russell Sage Foundation; 2009. Research synthesis as a scientific process; pp. 3–17.
• Cooper H. M. Organizing knowledge syntheses: A taxonomy of literature reviews. Knowledge in Society. 1988; 1 (1):104–126.
• Cronin P., Ryan F., Coughlan M. Undertaking a literature review: a step-by-step approach. British Journal of Nursing. 2008; 17 (1):38–43. [ PubMed : 18399395 ]
• Darlow S., Wen K.Y. Development testing of mobile health interventions for cancer patient self-management: A review. Health Informatics Journal. 2015 (online before print). [ PubMed : 25916831 ] [ CrossRef ]
• Daudt H. M., van Mossel C., Scott S.J. Enhancing the scoping study methodology: a large, inter-professional team’s experience with Arksey and O’Malley’s framework. bmc Medical Research Methodology. 2013; 13 :48. [ PMC free article : PMC3614526 ] [ PubMed : 23522333 ] [ CrossRef ]
• Davies P. The relevance of systematic reviews to educational policy and practice. Oxford Review of Education. 2000; 26 (3-4):365–378.
• Deeks J. J., Higgins J. P. T., Altman D.G. In: Cochrane handbook for systematic reviews of interventions. Higgins J. P. T., Green S., editors. Hoboken, nj : John Wiley & Sons, Ltd; 2008. Analysing data and undertaking meta-analyses; pp. 243–296.
• Deshazo J. P., Lavallie D. L., Wolf F.M. Publication trends in the medical informatics literature: 20 years of “Medical Informatics” in mesh . bmc Medical Informatics and Decision Making. 2009; 9 :7. [ PMC free article : PMC2652453 ] [ PubMed : 19159472 ] [ CrossRef ]
• Dixon-Woods M., Agarwal S., Jones D., Young B., Sutton A. Synthesising qualitative and quantitative evidence: a review of possible methods. Journal of Health Services Research and Policy. 2005; 10 (1):45–53. [ PubMed : 15667704 ]
• Finfgeld-Connett D., Johnson E.D. Literature search strategies for conducting knowledge-building and theory-generating qualitative systematic reviews. Journal of Advanced Nursing. 2013; 69 (1):194–204. [ PMC free article : PMC3424349 ] [ PubMed : 22591030 ]
• Grady B., Myers K. M., Nelson E. L., Belz N., Bennett L., Carnahan L. … Guidelines Working Group. Evidence-based practice for telemental health. Telemedicine Journal and E Health. 2011; 17 (2):131–148. [ PubMed : 21385026 ]
• Green B. N., Johnson C. D., Adams A. Writing narrative literature reviews for peer-reviewed journals: secrets of the trade. Journal of Chiropractic Medicine. 2006; 5 (3):101–117. [ PMC free article : PMC2647067 ] [ PubMed : 19674681 ]
• Greenhalgh T., Wong G., Westhorp G., Pawson R. Protocol–realist and meta-narrative evidence synthesis: evolving standards ( rameses ). bmc Medical Research Methodology. 2011; 11 :115. [ PMC free article : PMC3173389 ] [ PubMed : 21843376 ]
• Gurol-Urganci I., de Jongh T., Vodopivec-Jamsek V., Atun R., Car J. Mobile phone messaging reminders for attendance at healthcare appointments. Cochrane Database System Review. 2013; 12 cd 007458. [ PMC free article : PMC6485985 ] [ PubMed : 24310741 ] [ CrossRef ]
• Hart C. Doing a literature review: Releasing the social science research imagination. London: SAGE Publications; 1998.
• Higgins J. P. T., Green S., editors. Cochrane handbook for systematic reviews of interventions: Cochrane book series. Hoboken, nj : Wiley-Blackwell; 2008.
• Jesson J., Matheson L., Lacey F.M. Doing your literature review: traditional and systematic techniques. Los Angeles & London: SAGE Publications; 2011.
• King W. R., He J. Understanding the role and methods of meta-analysis in IS research. Communications of the Association for Information Systems. 2005; 16 :1.
• Kirkevold M. Integrative nursing research — an important strategy to further the development of nursing science and nursing practice. Journal of Advanced Nursing. 1997; 25 (5):977–984. [ PubMed : 9147203 ]
• Kitchenham B., Charters S. ebse Technical Report Version 2.3. Keele & Durham. uk : Keele University & University of Durham; 2007. Guidelines for performing systematic literature reviews in software engineering.
• Kitsiou S., Paré G., Jaana M. Systematic reviews and meta-analyses of home telemonitoring interventions for patients with chronic diseases: a critical assessment of their methodological quality. Journal of Medical Internet Research. 2013; 15 (7):e150. [ PMC free article : PMC3785977 ] [ PubMed : 23880072 ]
• Kitsiou S., Paré G., Jaana M. Effects of home telemonitoring interventions on patients with chronic heart failure: an overview of systematic reviews. Journal of Medical Internet Research. 2015; 17 (3):e63. [ PMC free article : PMC4376138 ] [ PubMed : 25768664 ]
• Levac D., Colquhoun H., O’Brien K. K. Scoping studies: advancing the methodology. Implementation Science. 2010; 5 (1):69. [ PMC free article : PMC2954944 ] [ PubMed : 20854677 ]
• Levy Y., Ellis T.J. A systems approach to conduct an effective literature review in support of information systems research. Informing Science. 2006; 9 :181–211.
• Liberati A., Altman D. G., Tetzlaff J., Mulrow C., Gøtzsche P. C., Ioannidis J. P. A. et al. Moher D. The prisma statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: Explanation and elaboration. Annals of Internal Medicine. 2009; 151 (4):W-65. [ PubMed : 19622512 ]
• Lyden J. R., Zickmund S. L., Bhargava T. D., Bryce C. L., Conroy M. B., Fischer G. S. et al. McTigue K. M. Implementing health information technology in a patient-centered manner: Patient experiences with an online evidence-based lifestyle intervention. Journal for Healthcare Quality. 2013; 35 (5):47–57. [ PubMed : 24004039 ]
• Mickan S., Atherton H., Roberts N. W., Heneghan C., Tilson J.K. Use of handheld computers in clinical practice: a systematic review. bmc Medical Informatics and Decision Making. 2014; 14 :56. [ PMC free article : PMC4099138 ] [ PubMed : 24998515 ]
• Moher D. The problem of duplicate systematic reviews. British Medical Journal. 2013; 347 (5040) [ PubMed : 23945367 ] [ CrossRef ]
• Montori V. M., Wilczynski N. L., Morgan D., Haynes R. B., Hedges T. Systematic reviews: a cross-sectional study of location and citation counts. bmc Medicine. 2003; 1 :2. [ PMC free article : PMC281591 ] [ PubMed : 14633274 ]
• Mulrow C. D. The medical review article: state of the science. Annals of Internal Medicine. 1987; 106 (3):485–488. [ PubMed : 3813259 ] [ CrossRef ]
• Evidence-based information systems: A decade later. Proceedings of the European Conference on Information Systems ; 2011. Retrieved from http://aisel ​.aisnet.org/cgi/viewcontent ​.cgi?article ​=1221&context ​=ecis2011 .
• Okoli C., Schabram K. A guide to conducting a systematic literature review of information systems research. ssrn Electronic Journal. 2010
• Otte-Trojel T., de Bont A., Rundall T. G., van de Klundert J. How outcomes are achieved through patient portals: a realist review. Journal of American Medical Informatics Association. 2014; 21 (4):751–757. [ PMC free article : PMC4078283 ] [ PubMed : 24503882 ]
• Paré G., Trudel M.-C., Jaana M., Kitsiou S. Synthesizing information systems knowledge: A typology of literature reviews. Information & Management. 2015; 52 (2):183–199.
• Patsopoulos N. A., Analatos A. A., Ioannidis J.P. A. Relative citation impact of various study designs in the health sciences. Journal of the American Medical Association. 2005; 293 (19):2362–2366. [ PubMed : 15900006 ]
• Paul M. M., Greene C. M., Newton-Dame R., Thorpe L. E., Perlman S. E., McVeigh K. H., Gourevitch M.N. The state of population health surveillance using electronic health records: A narrative review. Population Health Management. 2015; 18 (3):209–216. [ PubMed : 25608033 ]
• Pawson R. Evidence-based policy: a realist perspective. London: SAGE Publications; 2006.
• Pawson R., Greenhalgh T., Harvey G., Walshe K. Realist review—a new method of systematic review designed for complex policy interventions. Journal of Health Services Research & Policy. 2005; 10 (Suppl 1):21–34. [ PubMed : 16053581 ]
• Petersen K., Vakkalanka S., Kuzniarz L. Guidelines for conducting systematic mapping studies in software engineering: An update. Information and Software Technology. 2015; 64 :1–18.
• Petticrew M., Roberts H. Systematic reviews in the social sciences: A practical guide. Malden, ma : Blackwell Publishing Co; 2006.
• Rousseau D. M., Manning J., Denyer D. Evidence in management and organizational science: Assembling the field’s full weight of scientific knowledge through syntheses. The Academy of Management Annals. 2008; 2 (1):475–515.
• Rowe F. What literature review is not: diversity, boundaries and recommendations. European Journal of Information Systems. 2014; 23 (3):241–255.
• Shea B. J., Hamel C., Wells G. A., Bouter L. M., Kristjansson E., Grimshaw J. et al. Boers M. amstar is a reliable and valid measurement tool to assess the methodological quality of systematic reviews. Journal of Clinical Epidemiology. 2009; 62 (10):1013–1020. [ PubMed : 19230606 ]
• Shepperd S., Lewin S., Straus S., Clarke M., Eccles M. P., Fitzpatrick R. et al. Sheikh A. Can we systematically review studies that evaluate complex interventions? PLoS Medicine. 2009; 6 (8):e1000086. [ PMC free article : PMC2717209 ] [ PubMed : 19668360 ]
• Silva B. M., Rodrigues J. J., de la Torre Díez I., López-Coronado M., Saleem K. Mobile-health: A review of current state in 2015. Journal of Biomedical Informatics. 2015; 56 :265–272. [ PubMed : 26071682 ]
• Smith V., Devane D., Begley C., Clarke M. Methodology in conducting a systematic review of systematic reviews of healthcare interventions. bmc Medical Research Methodology. 2011; 11 (1):15. [ PMC free article : PMC3039637 ] [ PubMed : 21291558 ]
• Sylvester A., Tate M., Johnstone D. Beyond synthesis: re-presenting heterogeneous research literature. Behaviour & Information Technology. 2013; 32 (12):1199–1215.
• Templier M., Paré G. A framework for guiding and evaluating literature reviews. Communications of the Association for Information Systems. 2015; 37 (6):112–137.
• Thomas J., Harden A. Methods for the thematic synthesis of qualitative research in systematic reviews. bmc Medical Research Methodology. 2008; 8 (1):45. [ PMC free article : PMC2478656 ] [ PubMed : 18616818 ]
• Reconstructing the giant: on the importance of rigour in documenting the literature search process. Paper presented at the Proceedings of the 17th European Conference on Information Systems ( ecis 2009); Verona, Italy. 2009.
• Webster J., Watson R.T. Analyzing the past to prepare for the future: Writing a literature review. Management Information Systems Quarterly. 2002; 26 (2):11.
• Whitlock E. P., Lin J. S., Chou R., Shekelle P., Robinson K.A. Using existing systematic reviews in complex systematic reviews. Annals of Internal Medicine. 2008; 148 (10):776–782. [ PubMed : 18490690 ]

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Empirical research in the social sciences and education.

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Introduction: What is Empirical Research?

Empirical research is based on observed and measured phenomena and derives knowledge from actual experience rather than from theory or belief. 

How do you know if a study is empirical? Read the subheadings within the article, book, or report and look for a description of the research "methodology."  Ask yourself: Could I recreate this study and test these results?

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Experimental (Empirical) Articles: How Will I Know One When I See One?

Scholarly experimental articles  to conduct and publish an experiment, an author or team of authors designs an experiment, gathers data, then analyzes the data and discusses the results of the experiment. a published experiment or research study will therefore  look  very different from other types of articles (newspaper stories, magazine articles, essays, etc.) found in our library databases..

In fact, newspapers, magazines, and websites written by journalists report on psychology research all the time, summarizing published experiments in non-technical language for the general public. Although that kind of article can be interesting to read (and can even lead you to look up the original experiment published by the researchers themselves),  to write a research paper about a psychology topic, you should, generally, use experimental articles written by researchers. The following guidelines will help you recognize an experimental article, written by the researchers themselves and published in a scholarly journal.

Structure of a Experimental Article Typically, an experimental article has the following sections:

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Look for articles structured in that way--they will be experimental/empirical articles. ​

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As noted above, when you search in a database like APA PsycInfo, it's really easy to find experimental/empirical articles, once you know what you're looking for. Just in case, though, here is a shortcut that might help:

First, do your keyword search, for example:

In the results screen, on the left-hand side, scroll down until you see "Methodology." You can use that menu to refine your search by limiting the articles to empirical studies only:

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• Published: 06 May 2024

The influence and mechanism of female-headed households on household debt risk: empirical evidence from China

• Benyan Tan 1 ,
• Yingzhu Guo 1 &

Humanities and Social Sciences Communications volume  11 , Article number:  569 ( 2024 ) Cite this article

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With the development of society, the number of female-headed households is on the rise. Based on the data from the China Household Finance Survey (CHFS) in 2019, this paper establishes a Tobit model to study the influence of female-headed households on household debt risk. Results indicate that female-headed households can substantially reduce household debt risk, and this conclusion still holds after overcoming endogeneity issues. Further tests on the mediating effect reveal that risk aversion and housing property holding have partial mediating effects and masking effects, respectively, in the path of female-headed households affecting household debt risk. In addition, the heterogeneity analysis indicates that the influence of female-headed households on household debt risk is more significant in third-tier cities, as well as in families without children, families without elderly members, and families with more than two elderly members. The conclusions of this paper provide a reference for the relevant policy measures to reduce household debt risk and promote gender equality.

Introduction

As society progresses, improving women’s social status has become a global trend, and countries have made significant efforts to promote gender equality, resulting in a narrowing of the gender gap (Charles, 2011 ). Women’s social status includes political status, economic status, educational status, legal status, household status, and other aspects, among which women’s household status is an important manifestation of social status. When considering gender role characteristics of households, although it is still predominantly male-dominated worldwide, the status of females in the household is increasing, and it is undeniable that there are more and more households headed by females. The so-called “female-headed households” refers to households where females have the dominant right to make decisions on family affairs. Take Chinese families as an example. According to the Fourth Chinese Survey on the Social Status of Women in 2020, 89.5% and 90.0% of wives participated in major family decisions such as “investment or loan” and “purchase or construction of a house,” respectively. These figures are 14.8 and 15.6 percentage points higher than in 2010.

The improvement of female household status has spurred academic research on topics related to female-headed households. For instance, studies have explored the correlation between female household heads and household poverty (Katapa, 2006 ; Ayodeji et al., 2013 ; Fuwa, 2000 ), the influence of female household heads on household food security (Mallick and Rafi, 2010 ; Sewnet and Wang, 2023 ; Daniel and Augustina, 2022 ), the influence of female household heads on household assets (Kpoor, 2019 ; Debela, 2017 ), the influence of female household heads on housing purchase (Gandelman, 2009 ; Kupke et al., 2014 ), the influence of female household heads on children’s health (Wendt et al., 2021 ; Kennedy and Haddad, 1994 ), etc. However, there has been limited research on the relationship between a female-headed household and household debt. Only a few studies have investigated the influence of female household heads on household debt levels (Ozawa and Lee, 2006 ), debt growth (Long, 2018 ), and debt repayment rates (Wong et al., 2023 ). On the one hand, household debt is an important factor affecting financial stability, and many central banks are highly concerned about the risk of household debt. The Bank of Canada, the Bank of Korea, and the People’s Bank of China have all issued warnings that financial stability will face risks with the aggravation of household debt. According to The research group of the Institute for Advanced Research of Shanghai University of Finance and Economics ( 2018 ), household debt in China is very close to the limit that households can tolerate, and its adverse effects have been transmitted to both the real economy and the financial system, aggravating the likelihood of systemic financial risks. On the other hand, women are characterized by sensitive minds and cautious personalities (Chang, 2015 ), and they are more risk-averse than men (Brooks et al., 2019 ; Fehr-Duda et al., 2006 ), preferring to allocate less risky household assets (Sundén and Surette, 1998 ). Therefore, female-headed households will inevitably have an effect on household debt risk. The objective of this paper is to answer questions such as whether female-headed households can reduce household debt risk and how females’ risk attitudes and asset allocation preferences affect household debt risk. Answers to these questions can help to establish the importance of female participation in family decision-making, provide effective solutions to address household debt risk, and raise awareness about gender equality.

This paper examines the influence of female-headed households on household debt risk. The household debt risk is measured by the ratio of total household debt to total income. Due to the truncation feature observed at zero in the debt-to-income ratio, the Tobit model is selected for testing the impact of female-headed households on household debt risk. To address possible omitted variable bias and endogeneity issues, this paper employs an instrumental variables approach. To correct for potential estimation bias due to self-selection, this paper uses the propensity score matching method and the treatment effect model. Furthermore, in order to account for potential differences in the urban development level and family population structure that may affect the financial decisions of female-headed households, this paper conducts the heterogeneity analysis on them separately. Finally, to further validate the reliability of the empirical results, this paper uses robustness analysis methods such as examining the asset–liability ratio as the indicator of debt risk and changing the regression model.

The contributions of this paper are as follows: (1) Define the connotation of female-headed households and find appropriate variables for female-headed households. In this paper, we consider households with a female household head in the CHFS2019 database as female-headed households. It is because the household head in the CHFS database is not necessarily the household head in the household registration book but rather the person who plays a decisive role in family affairs, which is consistent with this paper’s definition of female-headed households as “households where the female has the dominant right to make decisions on family affairs.” In previous studies, the household heads were usually referred to as the head of household on the household registration booklet (Yang et al., 2019 ), or considered as the oldest family member with the highest income (Posel, 2001 ), or regarded as the female who does not live with their spouse (Sakamoto, 2011 ). Obviously, the household heads defined by previous studies do not necessarily have the dominant decision-making right regarding family affairs. (2) The female-headed households were found to be able to significantly influence household debt. The results of the study found that female-headed households can significantly reduce the risk of household debt, which provides a basis for improving the status of women and the role of women in family decision-making. (3) The influence mechanism of female-headed households on household debt risk is clarified. The results of the study suggest that risk aversion and housing property holding have partial mediating and masking effects, respectively, in the path of female-headed households reducing household debt risk.

The subsequent content of this paper is arranged as follows. Next section is the “Literature review”. Section next to that presents the “Theoretical analysis and research hypothesis”. After this section is the “Research design”. Next section provides the “Empirical results”. Penultimate section is the “Discussion and limitations”. Last section is the “Research conclusions and policy implications”.

Literature review

Literature related to the research topic of this paper mainly includes two aspects: the influence of gender characteristics on debt and the influencing factors of household debt.

Research on the influence of gender characteristics on debt

Existing academic research on the influence of gender characteristics on debt has primarily focused on the influence of female executives on corporate debt. One type of research suggests that female executives have the potential to lower the level of corporate debt. Compared to their female counterparts, male executives tend to exhibit overconfidence in significant corporate decisions and issue more debt (Huang and Kisgen, 2013 ). Conversely, female executives have rational and cautious financing preferences that may help reduce managements’ overconfidence and lead to more rational financing decisions (Zhang et al., 2019 ). Furthermore, female-owned firms face more severe financing constraints due to gender discrimination against women on the supply side of financing (Asiedu et al., 2013 ; Hu, 2015 ). As a result, female CEOs can have a significant negative impact on firms’ debt levels (Setiawan and Navianti, 2020 ). However, firms run by female CEOs that generate less financial leverage may also imply less volatile returns (Faccio et al., 2016 ). Another type of research takes the opposite view, arguing that female executives will raise corporate debt levels. In terms of debt maturity structure, female executives are more likely to hold a greater proportion of short-term debt than male executives (Datta et al., 2021 ), and the presence of female executives will improve the company’s short-term debt financing level (Rocca et al., 2020 ). Regarding differences in corporate ownership, companies with female CEOs and non-state-owned holding companies possess higher debt financing levels, more bank borrowings, and more long-term debt (Xu et al., 2018 ).

Some scholars have also examined the influence of gender characteristics on household debt and found that gender characteristics will have an impact on household debt willingness, debt level, and channels. Male household heads significantly increase the likelihood of household indebtedness (Chai and Zhou, 2020 ), while females are more hesitant to add more unnecessary debt (Almenberg et al., 2021 ). The influence of gender on household debt levels is, to some extent, related to different measurement standards of debt, thus leading to inconsistent conclusions. Some scholars suggest that male household heads incur lower household debt compared to females (Brown and Taylor, 2008 ), while others have found that male-headed households are significantly more indebted than female-headed households (Daniels, 2001 ). Female household heads are more conservative and risk-averse, which has a negative effect on the demand for debt. However, there is a positive effect on the demand for debt from informal financial institutions (Jin and Li, 2009 ). Related to gender discrimination in credit and gender inequality in financial services (Wang et al., 2008 ; Fletschner, 2009 ; Ghosh and Vinod, 2017 ), females have more difficulty in accessing financing through formal financial channels, whereas male household heads are more likely to obtain loans from formal financial institutions (Cai et al., 2022 ; Aterido et al., 2013 ). Gender also influences household debt through factors such as risk attitudes, subjective debt burden, and financial self-efficacy. Females are less risk-tolerant and more cautious compared to men (Huh and Park, 2013 ), and they experience a higher subjective burden of debt and exhibit greater prudence and responsibility when handling household finances and debt (Keese, 2012 ). According to Farrell et al. ( 2016 ), females with high financial self-efficacy are more inclined to hold financial products of investment and savings and avoid debt-related financial products.

Research on the influencing factors of household debt

Household characteristics that affect household debt include household income, demographic structure, financial literacy, and expectations about financial conditions. Some studies have found a consistent negative correlation between income and the debt-to-income ratio. Low-income households face greater debt burdens (Garber et al., 2019 ; Muthitacharoen et al., 2015 ), and debt default problems are more severe in these households (Alfaro and Gallardo, 2012 ). However, it has been argued that higher-income households may also increase their demand for debt and debt burden. This may be related to the purpose for which debt is taken on by households with different incomes (Christelis et al., 2021 , 2015 ), and because of credit constraints, higher-income households are more likely to have access to credit and incur more debt than lower-income households (Heintz-Martin et al., 2022 ; Coletta et al., 2019 ; Borowski et al., 2019 ). Households with females as the highest earners are more likely to be over-indebted, while households with asset income are negatively correlated with over-indebtedness (Angel and Heitzmann, 2015 ). Regarding household demographic structure, Guo et al. ( 2015 ) found that an increasing elderly dependency ratio and a decreasing youth dependency ratio significantly increase household debt. In terms of financial literacy, financially illiterate families with lower net assets and higher credit costs are more likely to fall into excessive debt (Gathergood and Disney, 2011 ). Household debt is also influenced by their expectations about future financial conditions. According to Hyytinen and Putkuri ( 2018 ), households with biased, optimistic expectations experience faster growth in debt and higher debt-to-income ratios. Additionally, excessive optimism about future financial situations can significantly increase debt servicing distress in future periods (Dawson and Henley, 2012 ).

Household debt is also influenced by the personal characteristics of the decision maker, such as age, health status, education level, and financial literacy. In Chinese households, the person responsible for making household decisions is typically the household head. Research has shown that older and healthier household heads are less likely to incur household debt (Chen and Li, 2011 ), and higher education levels are associated with lower household debt (Zhu and Xia, 2018 ). However, socially excluded groups, such as single parents, people with long-term illnesses or disabilities, and the uneducated, often face more severe debt problems (Patel et al., 2012 ). Individuals with lower debt literacy tend to engage in high-cost trading (Bucks and Pence, 2008 ), resulting in higher fees and the use of high-cost borrowing (Lusardi and Tufano, 2015 ). Household financial literacy also affects the channels through which households acquire debt, with those who have higher levels of financial literacy being more likely to obtain loans from formal sources (Huang et al., 2022 ; Klapper et al., 2013 ). Furthermore, household heads who follow patterns of conformity, as well as exhibit neurotic personality traits, significantly increase the probability and scale of household debt (Zhou and Feng, 2020 ).

Macro factors that affect household debt primarily include the housing market and the economic environment. Studies have shown that rising house prices (Kim et al., 2014 ; Meng et al., 2013 ), as well as price increases in the economy (Lerskullawat, 2020 ), a booming consumer credit market, and increased investment, are contributing factors (Dumitrescu et al., 2022 ). The widening income gap is also a factor in the growth of household debt, with low-income households experiencing a faster growth rate of their debt (Carr and Jayadev, 2015 ). The development of payment instruments and digital financial inclusion can also impact household debt. The use of mobile payments has also been linked to an increase in household debt (Chai, 2020 ). Additionally, the development of digital inclusive finance has been found to significantly contribute to the rise in household debt (Chen et al., 2022 ; Zhang et al., 2023 ).

In summary, the literature on the influence of gender characteristics on debt and debt influencing factors is rich and provides theoretical support for this paper’s research. However, there are two aspects that still requiring an in-depth study. First, previous research on female-headed households and household debt has mainly focused on the relationship between gender characteristics and debt behavior, while there is a scarcity of literature that examines the influence of female-led financial decision-making on household debt risk from the perspective of female-headed households. Second, the mechanisms through which female-headed households influence household debt have not been thoroughly explored.

Theoretical analysis and research hypothesis

The influence of female-headed household on household debt risk.

Unlike the traditional Chinese concept of “supporting the husband and teaching the children,” females are increasingly taking on senior management positions (Dreher, 2003 ), performing well in both corporate leadership and household maintenance (Anyanwu et al., 2023 ; Iyiola and Azuh, 2014 ; Nwosu et al., 2019 ). A report by the Chinese Academy of Financial Inclusion (CAFI, 2021 ) states that Chinese women perform better overall in financial health than men, especially in terms of balancing income and expenses and rationally planning debts, indicating that women are breaking through gender barriers and are capable of managing family finances rationally. Furthermore, there is a growing focus on promoting female financial empowerment (Ali et al., 2021 ). Efforts have been made to tackle gender inequality in the financial industry (Park et al., 2021 ; Cabeza-García et al., 2019 ), and women’s involvement in managing household finances has been further protected. In terms of debt-related decisions, females tend to be more cautious (Keese, 2012 ; Anon, 2012 ), and evidence suggests that they generally have a better debt repayment performance (Wong et al., 2023 ; Kevane and Wydick, 2001 ; Sharma and Zeller, 1997 ). Financial decisions within households can be influenced by gender and the division of roles among household members, and as the financial managers of the family, female household heads will influence household debt performance. Based on this analysis, this paper proposes the following hypothesis:

H1: Female-headed households significantly reduce household debt risk.

The influence mechanism of female-headed household on household debt risk

If female-headed households have a significant influence on household debt risk, then deeper issues will inevitably arise: how does the female-headed household influence household debt risk, and what is its transmission path? Based on Hypothesis H1 and combining research from sociology, psychology, and economics on the influence of gender characteristics regarding debt issues, this paper proposes that female-headed households affect household debt risk through the following two important mechanisms: risk aversion and housing property holding.

Female attitudes towards debt risk

Numerous studies have demonstrated gender differences in risk preferences (Yuan, 2017 ). Research has shown that females have a lower risk tolerance than males (Grable, 2000 ), and they are generally more risk-averse than males (Nelson, 2015 ; Croson and Gneezy, 2009 ). They are more cautious and conservative and more inclined to risk aversion when taking risks (Saltık et al., 2023 ; Jianakoplos and Bernasek, 1998 ). According to behavioral finance theory, individual economic decisions are often influenced by cognitive biases such as risk preference and overconfidence, leading to irrational decisions. In the financial field, men show higher overconfidence, engaging in more debt acquisition and issuance (Hu, 2021 ; Huang and Kisgen, 2013 ), trading more than rational investors. However, overconfidence may lead to underestimation of risk and overestimation of expected utility (Heaton, 2019 ; Zeng et al., 2023 ), while women’s investment style, influenced by personal characteristics, is more cautious and financially stable (Chang, 2015 ). When faced with uncertainty and risk, women’s risk aversion may lead them to be more cautious about debt-incurring behaviors such as borrowing and more willing to take avoidance measures against increasing household debt risk. Studies have shown that females exhibit greater relative risk aversion when allocating wealth to defined contribution pension assets (Bajtelsmit, 1999 ), and for married households with joint investment decisions, gender differences are an important factor in explaining individual retirement asset allocation, with women’s asset allocation being more risk-averse than men’s (Arano et al., 2010 ). Based on this analysis, this paper argues that the debt risk attitude of the household head is a crucial factor that influences household debt. If the household head tends to take lower risks, they may be more willing to make low-risk debt decisions, thus affecting household debt. Therefore, the following hypothesis is proposed:

H2: Females are more risk-averse, and risk aversion mediates the effect between female-headed households and household debt risk; that is, the more obvious risk aversion presented by female-headed households, the lower the household debt risk.

Female asset allocation preferences

In terms of family asset allocation, females prefer low-risk assets and are more willing to hold low-risk assets such as real estate and bank deposits than higher-risk assets such as stocks, bonds, and other types of financial funds for the purpose of risk aversion and financial stability. In terms of the actual situation of Chinese households, housing assets account for more than 64.9% of the total assets in Chinese households, while housing liabilities account for more than 40% of the total liabilities in Chinese households Footnote 1 . Therefore, on the one hand, due to their own robust characteristics, females may hold more housing property (Liu et al., 2021 ), and household liabilities are mainly housing liabilities (Li, 2022 ). On the other hand, owning more properties also means that housing liabilities may be higher, which increases the risk of household debt. It has been found that the higher the house ownership rate of households in the Nordic countries and the UK, the greater the size of debt (Debelle, 2004 ). A study by He et al. ( 2012 ) based on data from Chinese households also concluded that the higher the proportion of property holding, the higher the probability of household indebtedness. Based on the analysis presented above, the paper proposes the following hypotheses:

H3: Females tend to hold more housing property, and housing property holding preference acts as a masking effect between female-headed households and household debt risk; that is, the higher the proportion of housing property holding presented by female-headed households, the higher the household debt risk.

Based on the analysis presented above, this paper proposes a theoretical model consisting of female-headed households as the independent variable, household debt risk as the dependent variable, and risk aversion and housing property holding as the mediating variables. The model’s mechanism is illustrated in Fig. 1 .

In the figure, “Female-headed household” represents the independent variable, “Household debt risk” represents the dependent variable, and “Risk aversion” and “Housing property” represent the two mediating variables. The symbols “+” and “–” represent the positive and negative interaction relationships between variables, respectively.

Research design

Data source and sample selection.

The data comes from the CHFS2019 database, and the survey sample covers 29 provinces (autonomous regions, municipalities directly under the Central Government), 343 districts and counties, and 1360 village (neighborhood) committees, including 34,643 families and 107,008 family members. The samples in this paper are processed as follows to ensure reliable research results: (1) excluding the samples with missing key variables; (2) excluding the samples with negative income or zero consumption expenditure; (3) Considering the interference of extreme values on model results, this paper applies winsorization to the data of income and liabilities. Furthermore, households with total assets exceeding 100 million yuan have been excluded. After data processing, a total of 20,919 valid sample data was finally obtained.

Variables declaration and descriptive statistics

Variables declaration, explanatory variables.

The core explanatory variable is female-headed households, measured by the female household head variable, and this variable is assigned a value of 1 if the household head is female and 0 otherwise. It should be noted that the household head in the CHFS2019 database refers to those who play a decisive role in family affairs, not necessarily the household head on the registration booklet. This aligns with the paper’s definition of female-headed households as “households where females have the dominant right to make decisions on family affairs.

Explained variables

The paper’s explained variable is household debt risk, which is measured by the debt-to-income ratio, that is, the ratio of total household debt to total income. In the CHFS2019 database, the total household debt encompasses 11 items, namely agricultural liabilities, industrial and commercial liabilities, housing liabilities, store liabilities, vehicle liabilities, other non-financial assets liabilities, financial assets liabilities, education liabilities, credit card liabilities, medical liabilities, and other liabilities. Furthermore, there are five types of income comprising total household income. These include wage income, agricultural income, industrial and commercial income, property income, and transfer income. The higher the debt-to-income ratio, the greater the pressure on the household to use its income to repay its debts and the higher the potential household debt risk, which could lead to a default on the household debt.

Mediating variables

The mediating variables in this paper are risk aversion and housing property holding, which are measured by risk aversion and the proportion of housing assets in total assets, respectively. Among them, risk aversion is a 0–1 variable. For the question in the CHFS questionnaire about “If you have a fund for investment, which investment project would you be most willing to choose?” The answers to “slightly lower risk, slightly lower return” and “unwilling to take any risk” are defined as risk aversion and assigned a value of 1, otherwise 0.

Control variables

This paper examines control variables through three levels: individual characteristics of the household head, family characteristics, and regional characteristics. Individual characteristic variables include the age, education level, and health level of household heads. Family characteristics include family size, the number of participants in social security, the number of participants in medical insurance, whether they have their housing owner-occupied, household consumption expenditure, household savings assets, and whether they use the Internet (the value is assigned to 1 if using smartphones, otherwise it is 0); the variables at the regional level consist of urban and rural background (with a score of 1 for rural households and 0 for urban households), as well as the geographical region (encompassing four regions in eastern, central, western, and northeastern China).

Descriptive statistics

The descriptive statistics of the main variables are presented in Table 1 , where the mean value of the household debt-to-income ratio is 0.853, the mean value of the asset–liability ratio is 0.115, and the percentage of female-headed households is 14%. The mean value of risk aversion of household heads is 0.644, which means that the majority of household heads in the country are risk-averse. The mean value of housing property holdings is 0.649, which means that the average household assets have 64.9% of its total assets in the form of house equity. The mean health level of household heads is 3.247, indicating that the majority of household heads are in between “fairly healthy” and “very healthy.” The mean value of years of education of household heads is 8.786, which means that household heads have an average education level of middle school, reflecting that the education level of household heads is generally not high. The average family size is 3–4 people, and the vast majority of families have owner-occupied housing. The mean value of Internet use is 0.697, which means that more than 2/3 of the households use the Internet, indicating a high Internet penetration rate.

Univariate analysis

Table 2 presents a univariate analysis that compares the mean differences in debt-to-income ratio, asset–liability ratio, risk aversion, and housing property holding between female-headed households and other households. According to Table 2 , it can be seen that: (1) For female-headed households, the mean value of debt-to-income ratio and asset–liability ratio is 0.1165 and 0.1154 smaller than other households, with significance levels of 10% and 5%, respectively; (2) The risk aversion level of female-headed households is higher than that of other households, and the mean difference is significant at the 5% level; (3) The mean proportion of housing assets to total assets in female-headed households is 0.0664 higher than other households, significantly at the 1% level.

Model setting

Since the explanatory variable (debt-to-income ratio) has a clear truncation at 0, the Tobit model is adopted:

In model (1), \(i\) represents the household, \({\rm {{{DIR}}}}_{i}\) is the debt-to-income ratio variable, \(\,{{{\rm {Fhead}}}}_{i}\) is the female-headed households variable, \({{{\rm {Convar}}}}_{i}\) represents the control variable, includes individual, family, and urban–rural background and other characteristic variables, \({{{\rm {Region}}}}_{i}\) represents the regional fixed effect, \({\varepsilon }_{{i}}\) is a random disturbance term. To further investigate the mediating effect of female-headed households on household debt, the following model is constructed:

In model ( 1 ), \({\beta }_{1}\) represents the total effect of female-headed households on household debt risk; In models ( 2 ) and ( 3 ), \({M}_{i}\) is the two mediating variables (risk aversion and housing property holding) in this paper; \({c}_{1}\) is the effect of female-headed households on the mediating variables; \({\gamma }_{1}\) is the direct effect of female-headed households on household debt risk after adding the mediating variables and \({c}_{1}\times {\gamma }_{2}\) is the indirect effect of female-headed households on household debt risk.

According to the mediating effect test process provided by Wen and Ye ( 2014 ), the first step is to test whether the total effect \({\beta }_{1}\) is significant, then determine whether \({c}_{1}\) is indeed significant. Finally, based on the significance of the direct effect \({\gamma }_{1}\) , we can assess the presence of a mediating effect of the two mediating variables between the explanatory and explained variables. To better understand the mediating effect, this paper also refers to the distinction between the mediating effect and masking effect in the mediating analysis method of MacKinnon et al. ( 2000 ), which means that the mediating effect reduces the total effect between the explanatory variable and the explained variable, while masking effect increases the total effect between the explanatory variable and the explained variable. Based on the actual situation in this paper, several possible situations are summarized in Table 3 .

Empirical results

Results of the benchmark regression model.

Table 4 reports the corresponding results of the Tobit model by sequentially adding individual, family, and region characteristic variables, corresponding to columns (1)–(3), and column (4) is the marginal effect of column (3). From columns (1)–(3), female-headed households suppress household debt risk and are significant at 1%; from column (4), household debt risk will decrease by 14.29 percentage points when the household is headed by a female. Therefore, it can be concluded that without considering the influence of risk aversion and housing property holding, female-headed households will significantly reduce the risk of household debt, and H1 is confirmed.

From the parameter estimates of the main control variables: having their owner-occupied housing, larger family size, using the internet, higher household consumption expenditure and rural households are positively associated with household debt risk, while the household head who is older and healthier, the more members participating in social security and larger household deposit assets significantly reduce household debt risk, and the number of participants in medical insurance has no significant effect on household debt risk.

Endogeneity issues

Instrumental variables approach.

Regression models may suffer from endogeneity issues due to omitted variables and reverse causality. When the household debt risk is low, the household may also choose a female as the household head; that is, there may be a mutually causal relationship between the household debt risk and female-headed households. In addition, whether a female is the household head may also be influenced by unobservable factors such as personal personality and social relations. Given the possible estimation bias due to endogeneity issues, this paper adopts the instrumental variable method to estimate the model (1) in two stages. After multiple attempts, the instrumental variable chosen in this paper is the rate of female household heads in the same community, that is, the proportion of the number of households headed by females to the total number of households in the community. On the one hand, the greater the number of households headed by females in the same community, the greater the likelihood that a female is the household head due to the potential influence of the community environment. This satisfies the correlation condition of the instrumental variable. On the other hand, the rate of female-headed households in the same community is not directly related to the household debt risk of other households, so it satisfies the exogeneity condition of the instrumental variable. Therefore, it is theoretically feasible to choose the rate of female household heads in the same community as the tool variable of female-headed households.

Table 5 reports the results of the instrumental variable regression. The t value of the first stage regression of the instrumental variable test is 41.15, which means the rate of female household heads in the same community had a positive effect on female household heads and was significant at 1%, and the F value was 143.02, greater than the critical value of 10, so the problem of weak instrumental variables does not exist. The second stage estimation of the instrumental variable test shows that the Wald test value of the Tobit model passed the 5% significance test, which indicates that the instrumental variables selected in this paper could better overcome the endogeneity issues of the regression model, and after overcoming the endogeneity issues, the female-headed households will still significantly reduce the household debt risk.

Propensity score matching method

The propensity score matching method (PSM) can alleviate the estimation bias caused by the self-selection problem to some extent. The steps of calculating the average treatment effect on the treated (ATT) of female-headed households are as follows: Firstly, variables such as age, years of education, health level, family size, and whether the family has an owner-occupied housing are selected for Logit regression to estimate the propensity score; then, one-to-four propensity score proximity matching, radius matching, and kernel matching are performed; to further validate the robustness of the treatment effects obtained using the propensity score matching method, the bootstrap method was conducted using 500 bootstrap samples, and the bootstrap standard errors and p-values were obtained. Table 6 reports the PSM test results, in which the results of the one-to-four matching reveal that the average treatment effect on treated female-headed households was −24.5%, significant at the 1% level, and the estimates of radius matching and kernel matching are generally consistent with those of the one-to-four nearest neighbor matching. Moreover, all variables demonstrate a standardized deviation of <10% after matching, satisfying the balance requirement.

Boundary sensitivity analysis

The PSM method is prone to hidden bias problems attributed to unobservable variables. To further test the robustness of the results, this paper uses the boundary method to assess the sensitivity of PSM estimation results to hidden biases. The parameter Gamma represents the impact of unobserved confounding factors on household debt risk. If the conclusion is not significant when Gamma is close to 1, it can be inferred that the PSM results are not robust. This paper estimates hidden biases for three matching methods, and Table 7 reports the results of the sensitivity analysis, showing that there is no sensitivity when the Gamma coefficient is between 1 and 2, indicating that the hidden bias problem in PSM estimation can be ignored and that the estimation results based on the PSM model are robust.

Treatment effect model

The treatment effect model is also able to alleviate the estimation bias resulting from the self-selection problem to some extent. The endogenous variable “female-headed households” is a binary dummy variable, allowing for the adoption of a treatment effects model. Table 8 reports the estimation results of the two-step approach of the treatment effect model. The results of the first-stage Probit regression show that the rate of female household heads in the same community has a positive impact on female household heads, and it is significant at 1%. Furthermore, endogeneity tests using likelihood estimation indicate that it passes the significance level test of 5%. The final results of the treatment effect model show that female-headed households still have a significant inhibitory effect on household debt risk, and it is significant at the 1% level.

Analysis of mediating effects

Table 9 shows the results of the mediating effect test: (1) Risk aversion channel. Firstly, this paper tests whether female-headed households have a significant impact on the risk aversion variable, that is, the significance of \({c}_{1}\) . The results show a positive correlation between female-headed households and risk aversion, with a regression coefficient of 0.0234 and a significance level of 5%, indicating that female-headed households will significantly increase the probability of risk aversion. Secondly, this paper determines the significance of \({\gamma }_{2}\) and \({\gamma }_{1}\) . The regression results indicate that risk aversion significantly reduces household debt risk, and even after controlling for the risk aversion variable, female-headed households still significantly reduce household debt risk, i.e., both \({\gamma }_{2}\) and \({\gamma }_{1}\) are significant. Up to now, both direct effect \({\gamma }_{1}\) and indirect effects \({c}_{1}\times {\gamma }_{2}\) are significant. Finally, based on the regression results, it is known that \({c}_{1}\times {\gamma }_{2}\) and \({\gamma }_{1}\) are of the same sign, and the absolute value of the total effect \({\beta }_{1}\) (−0.143) is greater than that of the direct effect \({\gamma }_{1}\) (−0.138), indicating that there is a partial mediating effect of risk aversion in the path of female-headed households on household debt risk.

(2) Housing property holding channel. Firstly, this paper tests whether female-headed households have a significant impact on the housing property holding variable, that is, the significance of \({c}_{1}\) . The results show that the regression coefficient of housing property holding on female-headed households is 0.049, which is significantly positive at the 1% level, indicating that female-headed households will significantly increase the housing property holding. Secondly, the regression results show that housing property holding significantly increases the household debt risk. After controlling the housing property holding variable, female-headed households still significantly reduce the household debt risk as both \({\gamma }_{2}\) and \({\gamma }_{1}\) are significant. Up to this point, both direct effect \({\gamma }_{1}\) and indirect effect \({c}_{1}\times {\gamma }_{2}\) are significant. Finally, based on the regression results, it is known that \({c}_{1}\times {\gamma }_{2}\) and \({\gamma }_{1}\) have different signs, and the absolute value of the total effect \({\beta }_{1}\) (−0.143) is smaller than that of the direct effect \({\gamma }_{1}\) (−0.169). According to MacKinnon et al. ( 2000 ), it can be seen that housing property holding has a masking effect in the path of female-headed household’s influence on household debt risk. Based on the above analysis, H2 and H3 are validated.

Heterogeneity analysis

The influence of female-headed households on household debt risk may vary according to the availability of financial services, the source of household labor and income, and the characteristics of household consumption and expenditure, which tend to be related to the level of urban development and family population structure (Bai, 2021 ; Afjal, 2023 ; Zheng et al., 2023 ), which this paper analyses for heterogeneity. In terms of the differences in the impact of urban development levels, this paper follows the division of urban development levels as noted in the questionnaire to analyze the differences in their impact. The study divides the sample into households in the first-tier, new first-tier, second-tier, and third-tier cities, as well as cities below the third-tier. In terms of differences in the impact of family population structure, the population aged 14 and below is defined as the child population, and the population aged 65 and above is defined as the elderly population. Based on this, the sample is further divided into households with 0, 1, 2, and more children according to the number of children in the family, and households with 0, 1, 2, and more elderly population according to the number of elderly people in the family.

Differences in urban development level

Table 10 presents the impact of female-headed households on household debt risk under different urban development levels. The results show that the inhibitory effect of female-headed households on household debt risk was only significant in households in third-tier cities and below, while no significant effect was observed in households in first-tier and new first-tier cities and second-tier cities.

Differences in family population structure

Table 11 reports the impact of female-headed households on household debt risk when there are differences in family population structure. The findings demonstrate that the inhibitory effect of female-headed households on household debt risk is significant in households without children, without an elderly population, and with two or more elderly persons. However, it is not significant in households with one child, two or more children, or one elderly person.

Robustness test

Replace the measurement indicators of debt risk.

To further demonstrate the robustness of the research results, this paper uses asset–liability ratio instead of debt-to-income ratio to measure household debt risk. Table 12 reports the estimation results of the model with the sequential inclusion of individual, family, and regional characteristic variables and the results show that similar to the debt-to-income ratio, female-headed households also have a negative effect on household debt risk and are significant at the 1% level.

Replace the model

The Tobit model is used to predict the probability of target occurrence. Female-headed households are found to significantly reduce the household debt risk, whereas other household heads also reduce the debt-to-income ratio, while female-headed households may also increase the debt-to-income ratio. Therefore, to eliminate the doubts of the probability model, this paper also employs an OLS regression model to examine the effect of female-headed households on household debt risk. The results show that the regression coefficient of female-headed households on household debt risk is −0.1656, significant at the 1% level.

Provincial fixed effects

The basic model sets regional dummy variables to control for regional fixed effects. To further avoid the estimation error, the paper also controls the provincial fixed effect by setting the provincial dummy variables. The results show that the regression coefficient of female-headed households on household debt risk is −0.373, which is significant at the 5% level, proving that the basic conclusion is robust.

Discussion and limitations

This paper examines the influence of female-headed households on household debt risk using a Tobit model and finds that female-headed household significantly reduces household debt risk, adding to the arguments in favor of female participation in the family economies. This conclusion also supports, to some extent, previous studies that suggest females are less likely to incur debt (Flores and Vieira, 2014 ; Davies and Lea, 1995 ). The discussion of control variables can also be reasonably explained and supported by evidence. As the household head gets older, they may have more assets and financial experience, thereby reducing household debt holdings and household debt risk (Tseng and Hsiao, 2022 ; Abd Samad et al., 2023 ), which is consistent with the life-cycle hypothesis (Modigliani, 1986 ), according to which rational individuals accumulate assets during their working life to cover expenses in old age. The healthier household head borrows less due to illness, thus reducing household debt risk; for example, there are research studies showing that health problems are often the main reason for falling into financial collapse (McCloud and Dwyer, 2011 ). Larger family size implies a greater need for expenditure and, therefore, a greater need for debt, while household financial assets buffer against negative shocks to debt burdens (Stavins, 2021 ), and larger household deposit assets can better cover household expenditures (Bandelj and Grigoryeva, 2021 ), thus reducing household debt risk. The Internet enriches people’s channels for consumption, investment, and borrowing, and some studies have shown a positive correlation between Internet use and household debt leverage ratio (Zhou et al., 2021 ). Social security provides broad and long-term stable risk protection, such as pension, medical care, unemployment, work injury, and maternity insurance. The more members participating in social security, the better the household’s ability to protect itself against uncertain risks such as income shocks, and therefore the lower the demand for debt and the household debt risk. While the number of participants in medical insurance has no significant effect on household debt risk, which may be because the reimbursement ratio of basic medical insurance is generally low and its scope of coverage is limited (Hua, 2023 ), and households still have to bear large medical costs when facing serious illnesses. Additionally, the cumbersome reimbursement process may also cause families to face significant financial pressure in the short term. Rural households significantly increase household debt risk, possibly because they have lower incomes and need to take on more debt compared to their income to meet household expenses (He and Li, 2022 ; Meniago et al., 2013 ). Increasing household consumption expenditure will significantly increase the household debt risk (Kasoga and Tegambwage, 2021 ; Abd Samad et al., 2023 ). This may be due to the presence of a “ratchet effect” (Duesenberry, 1949 ), which means that consumption habits are easy to adjust upward but difficult to adjust downward, thus increasing the risk of household debt. Additionally, having their owner-occupied housing significantly increases the household debt risk, possibly because higher debt is required to purchase a house (Pastrapa and Apostolopoulos, 2015 ).

Regarding the mechanism of influence, risk aversion, and housing property holding have partial mediating and masking effects, respectively, in the path through which female-headed households influence household debt risk. The results are in line with expectations and consistent with some existing research conclusions. Almenberg et al. ( 2021 ) found that risk aversion is inversely related to household debt levels. Attitude towards risk is a key factor in debt or other financial decisions in the presence of risk and uncertainty in the future income distribution (Vargas-Sierra and Orts, 2023 ; Brown et al., 2013 ), and risk aversion tends to lead households to manage their debt more prudently and rationally, reducing the household debt risk by increasing savings, moderating borrowing and choosing low-risk debt (Zhou and Chen, 2020 ; Wang and Tian, 2012 ). While home ownership and higher house values tend to be associated with higher debt levels (Jarmuzek and Rozenov, 2019 ; Abd Samad et al., 2020 ), this may result firstly because borrowing to buy a house increases household debt and then increases the household debt to asset ratio when house prices fall (Gerlach-Kristen and Merola, 2019 ; Meng et al., 2013 ). Secondly, housing for investment may put households under greater financial pressure due to falling markets or longer-than-expected repayment periods (Worthington, 2006 ). Additionally, owning housing property allows households to use increased house values and home equity lines of credit for further loans and financing and further increasing household debt (Coletta et al., 2019 ). The discussion on the influence mechanisms provides insights into women’s influence on household debt risk. While recognizing that risk aversion can increase the prudence of women’s financial decision-making, and females tend to increase housing property holdings in pursuit of conservatism, it should also be recognized that a lack of investment confidence and excessive risk aversion may lead to excessive investment in low-risk assets such as housing, lacking investment in assets that can yield higher returns (Black et al., 2018 ; Ozawa and Lee, 2006 ), which could cause distortion in resource allocation (Keese, 2012 ). Therefore, correctly assessing personal risk attitudes, receiving more financial education and improving financial literacy and fund management skills (Tseng and Hsiao, 2022 ; Philippas and Avdoulas, 2020 ; French and McKillop, 2016 ; Sundén and Surette, 1998 ), and diversifying investments within an acceptable range of risk are also important for the economic health of the household.

Heterogeneity analyses show that, in terms of urban development level, the influence of female-headed households on reducing household debt risk is significant only for households in third-tier and below, which may be related to the financial development of different cities. The lower the level of urban development, the more scarce financial resources tend to be (Liu et al., 2021 ; Pateman, 2011 ), especially in rural areas where economic development is relatively lagging behind, household economic situations are relatively fragile and rural financial infrastructure is underdeveloped with limited loan channels and low credit convenience. These factors make rural households more inclined to borrow from informal sources (Kumar et al., 2017 ; Wong et al., 2023 ) and depend more on their own financial management and risk control, and in this case, the influence of female-headed households on household financial management is more significant. They borrow more cautiously and pay more attention to reducing the household debt risk and maintaining household financial stability. Conversely, the higher the level of urban development, the better the financial infrastructure. Coupled with higher income levels and stronger debt repayment capabilities, it ultimately results in the influence of female-headed households on household debt risk not being significant.

The influence of female-headed households on household debt risk is also varied based on differences in family population structure. This may be linked to expenditure patterns and borrowing purposes. The expenditure responsibilities of male and female household heads are not consistent (Reboul et al., 2021 ). When considering household financial decisions, females tend to prioritize collective spending and exhibit altruistic tendencies. They often take on a significant amount of household responsibilities and are more likely to spend on children and collective goods (Kasoga and Tegambwage, 2021 ; Pahl, 2008 ). Additionally, there is a positive correlation between female-controlled household assets and household spending on children’s clothing and education (Quisumbing and Maluccio, 2000 ). Thus, different family population structures lead to different consumption needs, affecting debt demands and borrowing decisions (Van Winkle and Monden, 2022 ; Kowalski et al., 2023 ). For example, Maroto ( 2018 ) found that children are associated with a decline in wealth for low-and middle-income families. Married couples with children are more likely to incur debts than other types of families (Xiao and Yao, 2020 ), and the number of children and other dependents in the family is positively correlated with household debt (Deng and Yu, 2021 ; Kasoga and Tegambwage, 2021 ). In this study, households without young children or elderly dependents have less financial pressure, allowing more income to be allocated for savings and reducing the relative need for household debt; and therefore, a female household head significantly reduces household debt risk. For households with two or more elderly members, although the financial pressure of supporting multiple elderly members is greater, the continuous improvement in the pension service policy system and the quality of pension services will help effectively reduce the family’s financial burden (Du and Wu, 2023 ; Han et al., 2023 ; Ke and Shi, 2023 ). Additionally, the consideration of preventing medical expenses from elderly illnesses also prompts female household heads to be more cautious in debt decisions, thus significantly reducing household debt risk. For households with one child, two or more children, and one elderly person, providing care for them can lead to economic pressure and an increase in debt demand. However, female household heads do not significantly worsen household debt after risk control due to their prudent considerations. Therefore, the influence of female-headed households on household debt risk is not significant.

Limitations

Firstly, the asset–liability ratio and debt-to-income ratio can reflect the level of household financial leverage and repayment capacity, providing a reasonable measure of household debt risk. However, these indicators do not consider the specific types and structures of household assets and liabilities, nor the source and stability of household income, while different types of assets and liabilities have varying impacts on household debt risk and the source and stability of income also affect a household’s ability to service its debt in the future. Therefore, future studies could consider factors such as debt type, interest rates, employment type, income source, future income and repayment plans, and family credit records to develop a more comprehensive indicator of household debt risk. Secondly, this paper has used cross-sectional data, and in the future, the use of panel data could be considered to study the impact of female-headed households on household debt risk from a dynamic perspective, in order to gain more insights on this topic.

Research conclusions and policy implications

This paper examines the influence and mechanisms of female-headed households on household debt risk from the perspectives of gender and household status. Using CHFS2019 data, we employ the debt-to-income ratio and asset–liability ratio as indicators of household debt risk, and the study demonstrates that female-headed households can significantly decrease household debt risk. Further analysis reveals that female-headed households affect household debt risk through two important mechanisms: risk aversion and housing property holding, and there are partial mediating and masking effects in the path of female-headed households influencing household debt risk. Female-headed households reduce household debt risk through risk aversion and increase household debt risk through increased housing property holding. Differences in the impact of female-headed households on household debt risk vary across different levels of urban development and family population structure, and these differences may be related to financial infrastructure, female consumption, and expenditure characteristics.

The fact that female-headed households significantly reduce the household debt risk and their increasing ability to participate in economic decision-making is an important reference for promoting gender equality and supporting the advancement of females in both the family and society. Encouraging women’s participation in household economic decision-making and management also has a positive effect on the stable management of households and the resolution of household debt risks. The risk attitudes and asset allocation preferences of females have a significant influence on household debt management. This highlights the importance of emphasizing financial education for females and improving their financial skills, which is crucial in reducing household financial decision-making errors. Females should have a clear and correct understanding of their risk attitude and risk tolerance and avoid falling into financial difficulties due to the holding of single assets such as housing property. The different urban development levels and family population structure can affect the role of females in household debt management. This highlights the need for the government to adopt multiple approaches to increase household income and improve the level of financial infrastructure construction in underdeveloped areas while continuing to improve pension insurance policies and laws and regulations on family fertility and parenting.

Data availability

The data that support the findings of this study are available from China Household Finance Survey (CHFS) but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of China Household Finance Survey (CHFS).

The author’s calculations based on data from CHFS2019.

Abd Samad K, Idris NH, Abd Rahman NH, Abdullah Sani A, Mohd Soffian Lee UH (2023) Systematic Literature Review on the Macroeconomic Factors of Household Debt. In: Jaaffar AH, Buniamin S, Rahman NRA, Othman NS, Mohammad N, Kasavan S, Mohamad NEAB, Saad ZM, Ghani FA, Redzuan NIN (eds) Accelerating Transformation towards Sustainable and Resilient Business: Lessons Learned from the COVID-19 Crisis, Vol 1. European Proceedings of Finance and Economics. European Publisher, p 207–223. https://doi.org/10.15405/epfe.23081.18

Abd Samad K, Mohd Daud SN, Mohd Dali NRS (2020) Determinants of household debt in emerging economies: a macro panel analysis. Cogent Bus Manag 7(1):1831765. https://doi.org/10.1080/23311975.2020.1831765

Article   Google Scholar  

Afjal M (2023) Bridging the financial divide: a bibliometric analysis on the role of digital financial services within FinTech in enhancing financial inclusion and economic development. Humanit Soc Sci Commun 10(1), Article 1. https://doi.org/10.1057/s41599-023-02086-y

Alfaro R, Gallardo N (2012) The determinants of household debt default. Econ Anal Rev 27(1):27–54

Google Scholar  

Ali M, Ali I, Badghish S, Soomro YA (2021) Determinants of financial empowerment among women in Saudi Arabia. Front Psychol 12:4049. https://doi.org/10.3389/fpsyg.2021.747255

Almenberg J, Lusardi A, Säve‐Söderbergh J (2021) Attitudes toward debt and debt behavior. Scand J Econ 123(3):780–809

Angel S, Heitzmann K (2015) Over-indebtedness in Europe: the relevance of country-level variables for the over-indebtedness of private households. J Eur Soc Policy 25(3):331–351. https://doi.org/10.1177/0958928715588711

Anon (2012) Who feels constrained by high debt burdens? Subjective vs. objective measures of household debt. J Econ Psychol 33(1):125–141

Anyanwu OC, Oloto SE, Nwokocha VC (2023) Impact of strategic alliance on the innovation of women-owned enterprises in Nigeria. Humanit Soc Sci Commun 10(1), Article 1. https://doi.org/10.1057/s41599-023-02463-7

Arano K, Parker C, Terry R (2010) Gender-based risk aversion and retirement asset allocation. Econ Inq 48(1):147–155. https://doi.org/10.1111/j.1465-7295.2008.00201.x

Asiedu E, Kalonda-Kanyama I, Ndikumana L, Nti-Addae A (2013) Access to credit by firms in sub-Saharan Africa: how relevant is gender? Am Econ Rev 103(3):293–297. https://doi.org/10.1257/aer.103.3.293

Aterido R, Beck T, Iacovone L (2013) Access to finance in sub-Saharan Africa: is there a gender gap? World Dev 47:102–120. https://doi.org/10.1016/j.worlddev.2013.02.013

Ayodeji O, Babatunde A, Francis U (2013) Are female-headed households typically poorer than male-headed households in Nigeria? J Socio-Econ 45:132–137. https://doi.org/10.1016/j.socec.2013.04.010

Bai M (2021) The impact of financial service availability on household consumption volatility and its mechanism. J Commerc Econ 21:49–52. (in Chinese)

Bajtelsmit V (1999) Gender differences in defined contribution pension decisions. Financ Serv Rev 8(1):1–10. https://doi.org/10.1016/S1057-0810(99)00030-X

Bandelj N, Grigoryeva A (2021) Investment, saving, and borrowing for children: trends by wealth, race, and ethnicity, 1998–2016. RSF 7(3):50–77. https://doi.org/10.7758/RSF.2021.7.3.03

Black SE, Devereux PJ, Lundborg P, Majlesi K (2018) Learning to take risks? The effect of education on risk-taking in financial markets. Rev Finance 22(3):951–975. https://doi.org/10.1093/rof/rfy005

Borowski J, Jaworski K, Olipra J (2019) Economic, institutional, and socio-cultural determinants of consumer credit in the context of monetary integration. Int Finance 22(1):86–102. https://doi.org/10.1111/infi.12144

Brooks C, Sangiorgi I, Hillenbrand C et al. (2019) Experience wears the trousers: exploring gender and attitude to financial risk J Econ Behav Organ 163(C):483–515. https://doi.org/10.1016/j.jebo.2019.04.026

Brown S, Garino G, Taylor K (2013) Household debt and attitudes toward risk. Rev Income Wealth 59(2):283–304. https://doi.org/10.1111/j.1475-4991.2012.00506.x

Brown S, Taylor K (2008) Household debt and financial assets: evidence from Germany, Great Britain and the USA. J R Stat Soc Ser A: Stat Soc 171(3):615–643. https://doi.org/10.1111/j.1467-985X.2007.00531.x

Article   MathSciNet   Google Scholar  

Bucks B, Pence K (2008) Do borrowers know their mortgage terms? J Urban Econ 64(2):218–233. https://doi.org/10.1016/j.jue.2008.07.005

Cabeza-García L, Del Brio EB, Oscanoa-Victorio ML (2019) Female financial inclusion and its impacts on inclusive economic development. Women’s Stud Int Forum 77:102300. https://doi.org/10.1016/j.wsif.2019.102300

Cai Z, Ding C, Cai X (2022) How the gender structure of children affects household debt. Finance Trade Econ 43(04):113–128. https://doi.org/10.19795/j.cnki.cn11-1166/f.20220408.009 . (in Chinese)

Carr MD, Jayadev A (2015) Relative income and indebtedness: evidence from panel data. Rev Income Wealth 61(4):759–772. https://doi.org/10.1111/roiw.12134

Chai S (2020) Does mobile payment amplify household debt risk? Micro evidence based on the perspective of family financial leverage. J Southwest Minzu University (Humanit Soc Sci) 41(10):122–133. (in Chinese)

Chai S, Zhou L (2020) An empirical study on household debt, debt level, and influencing factors. Stat Decision 36(22):140–142. https://doi.org/10.13546/j.cnki.tjyjc.2020.22.031 . (in Chinese)

Chang M (2015) Analysis of the relationship between CFO gender, financial robustness, and corporate financing decisions. J Commer Econ 8:93–95. (in Chinese)

Charles M (2011) A world of difference: international trends in women’s economic status. Annu Rev Sociol 37(1):355–371. https://doi.org/10.1146/annurev.soc.012809.102548

Chen B, Li T (2011) A study on the current situation and causes of asset liability of urban household in China. Econ Res J 46(S1):55–66+79. (in Chinese)

MathSciNet   Google Scholar  

Chen C, Fang F, Zhang L (2022) Digital inclusive finance, income levels, and household debt. Econ Survey 39(01):127–137. (in Chinese)

Chinese Academy of Financial Inclusion (CAFI) (2021) Renmin University of China. Women’s financial health is accelerating in China. Int Financ 5:76–80. (in Chinese)

Christelis D, Ehrmann M, Georgarakos D (2015) Exploring differences in household debt across euro area countries and the United States (2015–16). Bank of Canada. https://doi.org/10.34989/swp-2015-16

Christelis D, Ehrmann M, Georgarakos D (2021) Exploring differences in household debt across the United States and Euro Area countries. J Money Credit Bank 53(2–3):477–501. https://doi.org/10.1111/jmcb.12769

Coletta M, De Bonis R, Piermattei S (2019) Household debt in OECD countries: the role of supply-side and demand-side factors. Soc Indic Res 143(3):1185–1217. https://doi.org/10.1007/s11205-018-2024-y

Croson R, Gneezy U (2009) Gender differences in preferences. J Econ Lit 47(2):448–474. https://doi.org/10.1257/jel.47.2.448

Daniel DI, Augustina C (2022) Female-Led agrarian households and the question of sustainable land and food security in an emerging economy: evidence from Tula Baule. Habitat Int 120:102512. https://doi.org/10.1016/j.habitatint.2022.102512

Daniels R (2001) Consumer indebtedness among urban South African households: a descriptive overview. Development Policy Research Unit Working Paper 01/055. University of Cape Town

Datta S, Doan T, Toscano F (2021) Top executive gender, board gender diversity, and financing decisions: evidence from debt structure choice. J Bank Finance 125(1):106070. https://doi.org/10.1016/j.jbankfin.2021.106070

Davies E, Lea SEG (1995) Student attitudes to student debt. J Econ Psychol 16(4):663–679. https://doi.org/10.1016/0167-4870(96)80014-6

Dawson C, Henley A (2012) Something will turn up? Financial over-optimism and mortgage arrears. Econ Lett 117(1):49–52. https://doi.org/10.1016/j.econlet.2012.04.063

Debela LB (2017) Factors affecting differences in livestock asset ownership between male- and female-headed households in Northern Ethiopia. Eur J Dev Res 29(2):328–347. https://doi.org/10.1057/ejdr.2016.9

Debelle G (2004) Macroeconomic implications of rising household debt. SSRN Electron J. https://doi.org/10.2139/ssrn.786385

Deng X, Yu M (2021) Does the marginal child increase household debt?—Evidence from the new fertility policy in China. Int Rev Financ Anal 77:101870. https://doi.org/10.1016/j.irfa.2021.101870

Dreher GF (2003) Breaking the glass ceiling: the effects of sex ratios and work-life programs on female leadership at the top. Hum Relat 56(5):541–562. https://doi.org/10.1177/0018726703056005002

Du P, Wu Y (2023) The changing path, motivational mechanism, and future transformation of China’s rlderly care service policy. Acad J Zhongzhou 3:82–90+2. (in Chinese)

Duesenberry JS (1949) Income, saving, and the theory of consumer behavior. Harvard University Press, Cambridge, MA

Dumitrescu BA, Enciu A, Hândoreanu CA et al. (2022) Macroeconomic determinants of household debt in OECD countries. Sustainability 14(7):3977. https://doi.org/10.3390/su14073977

Faccio M, Marchica MT, Mura R (2016) CEO gender, corporate risk-taking, and the efficiency of capital allocation. J Corp Finance 39:193–209. https://doi.org/10.1016/j.jcorpfin.2016.02.008

Farrell L, Fry TRL, Risse L (2016) The significance of financial self-efficacy in explaining women’s personal finance behavior. J Econ Psychol 54:85–99. https://doi.org/10.1016/j.joep.2015.07.001

Fehr-Duda H, Gennaro M, Schubert R (2006) Gender, financial risk, and probability weights. Theory Decision 60(2-3):283–313. https://doi.org/10.1007/s11238-005-4590-0

Fletschner D (2009) Rural women’s access to credit: market imperfections and intrahousehold dynamics. World Dev 37(3):618–631. https://doi.org/10.1016/j.worlddev.2008.08.005

Flores SAM, Vieira KM (2014) Propensity toward indebtedness: an analysis using behavioral factors. J Behav Exp Finance 3:1–10. https://doi.org/10.1016/j.jbef.2014.05.001

French D, McKillop D (2016) Financial literacy and over-indebtedness in low-income households. Int Rev Financ Anal 48:1–11. https://doi.org/10.1016/j.irfa.2016.08.004

Fuwa N (2000) The poverty and heterogeneity among female-headed households revisited: the case of Panama. World Dev 28(8):1515–1542. https://doi.org/10.1016/S0305-750X(00)00036-X

Gandelman N (2009) Female headed households and homeownership in Latin America. Hous Stud 24(4):525–549. https://doi.org/10.1080/02673030902938397

Garber G, Mian A, Ponticelli J, Sufi A (2019) Household debt and recession in Brazil. In: Haughwout A, Mandel B (eds) Handbook of US Consumer Economics. Academic Press, p 97–119. https://doi.org/10.1016/B978-0-12-813524-2.00004-4

Disney RF, Gathergood J (2011) Financial Literacy ad Indebtedness: New Evidence for UK Consumers, Discussion Papers, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM). SSRN Electronic Journal. Available at SSRN 1851343

Gerlach-Kristen P, Merola R (2019) Consumption and credit constraints: a model and evidence from Ireland. Empir Econ 57(2):475–503. https://doi.org/10.1007/s00181-018-1461-4

Ghosh S, Vinod D (2017) What constrains financial inclusion for women? Evidence from Indian micro data. World Dev 92:60–81. https://doi.org/10.1016/j.worlddev.2016.11.011

Grable JE (2000) Financial risk tolerance and additional factors that affect risk taking in everyday money matters. J Bus Psychol 14(4):625–630. https://doi.org/10.1023/A:1022994314982

Guo X, Chen B, Wu Z (2015) An empirical study on the relationship between population structure changes and household debt growth in China. Stat Decision (4), 96–99. https://doi.org/10.13546/j.cnki.tjyjc.2015.04.027 (in Chinese)

Han Z, Liu T, Liu W (2023) Improving the quality of China’s elderly care services: policy evolution logic and trend foresight—an analysis based on national policy texts from 1989–2020. Soc Secur Stud 3:29–41. (in Chinese)

He L, Li M (2022) Does rising household debt lead to consumption upgrading? Evidence from the Chinese Household Tracking Survey. Jiang-huai Trib 2:26–35. https://doi.org/10.16064/j.cnki.cn34-1003/g0.2022.02.003 . (in Chinese)

He L, Wu W, Xu Q (2012) Analysis of the debt situation, structure, and influencing factors of Chinese families. J Central China Normal Univ: Humanit Soc Sci 51(01):59–68. (in Chinese)

Heaton JB (2019) Managerial optimism: new observations on the unifying theory. Eur Financ Manag 25(5):1150–1167. https://doi.org/10.1111/eufm.12218

Heintz-Martin V, Recksiedler C, Langmeyer AN (2022) Household debt, maternal well-being, and child adjustment in Germany: examining the family stress model by family structure. J Fam Econ Issues 43(2):338–353. https://doi.org/10.1007/s10834-021-09777-1

Article   PubMed   Google Scholar  

Hu Y (2021) Impact of investors’ loss aversion and overconfidence on market performance evidence from China stock markets. 2022–2025. https://doi.org/10.2991/assehr.k.211209.330

Hu Z (2015) Female CEOs, social trust, and corporate financing constraints. Bus Manag J 37(08):88–98. https://doi.org/10.19616/j.cnki.bmj.2015.08.011 . (in Chinese)

Hua Y (2023) The Chinese resident medical insurance system: realistic problems and reform prospects. Acad Res 9:87–95. (in Chinese)

Huang J, Kisgen JD (2013) Gender and corporate finance: are male executives overconfident relative to female executives? J Financ Econ 108(3):822–839. https://doi.org/10.1016/j.jfineco.2012.12.005

Huang X, Wang S, Lin L (2022) Does financial literacy affect the debt leverage of rural households?—Empirical evidence from the 2019 CHFS. J Northeast Agric Univ: Soc Sci Ed 20(6):36–49. (in Chinese)

Huh K, Park KY (2013) A study on the effect of risk tolerance and status quo bias on search behavior of financial information, financial management behavior and satisfaction for economic life of households. Financ Plan Rev 6(1):1–26

Hyytinen A, Putkuri H (2018) Household optimism and overborrowing. J Money Credit Bank 50(1):55–76. https://doi.org/10.1111/jmcb.12453

Iyiola O, Azuh D (2014) Women entrepreneurs as small medium enterprises (SME) operators and their roles in socio-economic development in Ota, Nigeria. Int J Econ Bus Finance 2(1):1–10. ISSN: 2327-8188

Jarmuzek M, Rozenov R (2019) Excessive private sector leverage and its drivers: Evidence from advanced economies. Appl Econ 51(34):3787–3803. https://doi.org/10.1080/00036846.2019.1584383

Jianakoplos AN, Bernasek A (1998) Are women more risk averse? Econ Inq 36(4):620–630. https://doi.org/10.1111/j.1465-7295.1998.tb01740.x

Jin Y, Li H (2009) Informal finance and farmers’ borrowing behavior. J Financ Res 346 (4), 63–79 (in Chinese)

Kasoga PS, Tegambwage AG (2021) An assessment of over-indebtedness among microfinance institutions’ borrowers: the Tanzanian perspective. Cogent Bus Manag 8(1):1930499. https://doi.org/10.1080/23311975.2021.1930499

Katapa RS (2006) A comparison of female- and male-headed households in Tanzania and poverty implications. J Biosoc Sci 38(3):327–339. https://doi.org/10.1017/S0021932005007169

Article   CAS   PubMed   Google Scholar  

Ke W, Shi W (2023) A study on the financial development of China’s elderly care industry. New Finance 9:51–56. (in Chinese)

Keese M (2012) Who feels constrained by high debt burdens? Subjective vs. objective measures of household debt. J Econ Psychol 33(1):125–141. https://doi.org/10.1016/j.joep.2011.08.002

Kennedy E, Haddad L (1994) Are pre‐schoolers from female‐headed households less malnourished? A comparative analysis of results from Ghana and Kenya. J Dev Stud 30(3):680–695. https://doi.org/10.1080/00220389408422332

Kevane M, Wydick B (2001) Microenterprise lending to female entrepreneurs: sacrificing economic growth for poverty alleviation? World Dev 29(7):1225–1236. https://doi.org/10.1016/S0305-750X(01)00032-8

Kim HJ, Lee D, Son JC et al. (2014) Household indebtedness in Korea: its causes and sustainability. Jpn World Econ 29:59–76. https://doi.org/10.1016/j.japwor.2013.12.001

Article   CAS   Google Scholar  

Klapper L, Lusardi A, Panos GA (2013) Financial literacy and its consequences: evidence from Russia during the financial crisis. J Bank Finance 37(10):3904–3923. https://doi.org/10.1016/j.jbankfin.2013.07.014

Kowalski R, Strzelecka A, Wałęga A, Wałęga G (2023) Do children matter to the household debt burden? J Fam Econ Issues 44(4):1007–1022. https://doi.org/10.1007/s10834-023-09887-y

Kpoor A (2019) Assets and livelihoods of male- and female-headed households in Ghana. J Fam Issues 40(18):2974–2996. https://doi.org/10.1177/0192513X19868839

Kumar A, Mishra AK, Saroj S, Joshi PK (2017) Institutional versus non-institutional credit to agricultural households in India: evidence on impact from a national farmers’ survey. Econ Syst 41(3):420–432. https://doi.org/10.1016/j.ecosys.2016.10.005

Kupke V, Rossini P, McGreal S et al. (2014) Female-headed households and achieving home ownership in Australia. Hous Stud 29(7):871–892. https://doi.org/10.1080/02673037.2014.903902

Lerskullawat A (2020) Factors affecting household debt in Thailand. Int J Econ Policy Emerg Econ 13(4):327–336. https://doi.org/10.1504/IJEPEE.2020.109584

Li J (2022) Research on the debt level, structural changes, and causes of Chinese households. Doctoral dissertation, Southwest University of Finance and Economics (in Chinese)

Liu G, Huang Y, Huang Z (2021) Determinants and mechanisms of digital financial inclusion development: based on urban–rural differences. Agronomy, 11(9), Article 9. https://doi.org/10.3390/agronomy11091833

Liu H, Hu S, Chen L (2021) Gender of children and household housing assets. J Zhongnan Univ Econ Law 3:69–78+159. https://doi.org/10.19639/j.cnki.issn1003-5230.2021.0031 . (in Chinese)

Long MG (2018) Pushed into the red? Female-headed households and the pre-crisis credit expansion. Forum Soc Econ 47(2):224–236. https://doi.org/10.1080/07360932.2018.1451762

Lusardi A, Tufano P (2015) Debt literacy, financial experiences, and overindebtedness. J Pension Econ Finance 14(4):332–368. https://doi.org/10.1017/S1474747215000232

MacKinnon DP, Krull JL, Lockwood CM (2000) Equivalence of the mediation, confounding and suppression effect. Prev Sci 1(4):173–181. https://doi.org/10.1023/A:1026595011371

Article   CAS   PubMed   PubMed Central   Google Scholar  

Mallick D, Rafi M (2010) Are female-headed households more food insecure? Evidence from Bangladesh. World Dev 38(4):593–605. https://doi.org/10.1016/j.worlddev.2009.11.004

Maroto M (2018) Saving, sharing, or spending? The wealth consequences of raising children. Demography 55(6):2257–2282. https://doi.org/10.1007/s13524-018-0716-1

McCloud L, Dwyer RE (2011) The fragile American: hardship and financial troubles in the 21st century. Sociol Q 52(1):13–35. https://doi.org/10.1111/j.1533-8525.2010.01197.x

Meng X, Hoang TN, Siriwardana M (2013) The determinants of Australian household debt: a macro level study. J Asian Econ 29:80–90. https://doi.org/10.1016/j.asieco.2013.08.008

Meniago C, Mukuddem-Petersen J, Petersen MA, Mongale IP (2013) What causes household debt to increase in South Africa? Econ Model 33:482–492. https://doi.org/10.1016/j.econmod.2013.04.028

Modigliani F (1986) Life cycle, individual thrift, and the wealth of nations. Science 234(4777):704–712. https://doi.org/10.1126/science.234.4777.704

Muthitacharoen A, Nuntramas P, Chotewattanakul P (2015) Rising household debt: implications for economic stability. Thail World Econ 33(3):3. Article

Nelson JA (2015) Are women really more risk-averse than men? A re-analysis of the literature using expanded methods. J Econ Surv 29(3):566–585. https://doi.org/10.1111/joes.12069

Nwosu II, Onoyima RO, Madu IA, Nwokocha VC (2019) The socioeconomic effects of small-scale women businesses in broom production and marketing industry: a panacea for sustainable development. J Enterprising Communities: People Places Global Econ 13(3):283–295. https://doi.org/10.1108/JEC-11-2018-0080

Ozawa MN, Lee Y (2006) The net worth of female-headed households: a comparison to other types of households. Fam Relat 55(1):132–145. https://doi.org/10.1111/j.1741-3729.2006.00362.x

Pahl J (2008) Family finances, individualisation, spending patterns and access to credit. J Socio-Econ 37(2):577–591. https://doi.org/10.1016/j.socec.2006.12.041

Park CM, Kraus AD, Dai Y, Fantry C, Block T, Kelder B, Howard KAS, Solberg VSH (2021) Empowering women in finance through developing girls’ financial literacy skills in the United States. Behav Sci 11(12), Article 12. https://doi.org/10.3390/bs11120176

Pastrapa E, Apostolopoulos C (2015) Estimating determinants of borrowing: evidence from Greece. J Fam Econ Issues 36(2):210–223. https://doi.org/10.1007/s10834-014-9393-4

Patel A, Balmer NJ, Pleasence P (2012) Debt and disadvantage: the experience of unmanageable debt and financial difficulty in England and Wales: debt and disadvantage. Int J Consum Stud 36(5):556–565. https://doi.org/10.1111/j.1470-6431.2012.01121.x

Pateman T (2011) Rural and urban areas: comparing lives using rural/urban classifications. Reg Trends 43(1):11–86. https://doi.org/10.1057/rt.2011.2

Philippas ND, Avdoulas C (2020) Financial literacy and financial well-being among generation-Z university students: evidence from Greece. Eur J Finance 26(4–5):360–381. https://doi.org/10.1080/1351847X.2019.1701512

Posel RD (2001) Who are the heads of household, what do they do, and is the concept of headship useful? An analysis of headship in South Africa. Dev South Afr 18(5):651–670. https://doi.org/10.1080/03768350120097487

Quisumbing, AR, Maluccio, JA (2000) Intrahousehold allocation and gender relations: new empirical evidence from four developing countries. FCND Discussion Paper No. 84. International Food Policy Research Institute (IFPRI), Washington, DC

Reboul E, Guérin I, Nordman CJ (2021) The gender of debt and credit: insights from rural Tamil Nadu. World Dev 142:105363. https://doi.org/10.1016/j.worlddev.2020.105363

Rocca LM, Neha N, Rocca LT (2020) Female management, overconfidence and debt maturity: European evidence. J Manag Gov 24(3):713–747. https://doi.org/10.1007/s10997-019-09479-9

Sakamoto K (2011) Are female-headed households more vulnerable? From livelihood strategies within communities of southeast Tanzania. J Int Stud 31:77–98

Saltık Ö, Rehman W. ul, Söyü R, Değirmen S, Şengönül A (2023) Predicting loss aversion behavior with machine-learning methods. Humanit Soc Sci Commun 10(1), Article 1. https://doi.org/10.1057/s41599-023-01620-2

Setiawan R, Navianti DR (2020) CEO gender and firm debt policy: an empirical study in Indonesia. In: Hurriyati R, Tjahjono B, Yamamoto I, Rahayu A, Abdullah AG, Danuwijaya AA (eds) Proceedings of the 3rd Global Conference on Business, Management, and Entrepreneurship (GCBME 2018). Atlantis Press. pp. 93–95

Sewnet LA, Wang S (2023) Does the female-headed household suffer more than the male-headed from Covid-19 impact on food security? Evidence from Ethiopia. J Agric Food Res 12:100563. https://doi.org/10.1016/j.jafr.2023.100563

Sharma M, Zeller M (1997) Repayment performance in group-based credit programs in Bangladesh: an empirical analysis. World Dev 25(10):1731–1742. https://doi.org/10.1016/S0305-750X(97)00063-6

Stavins J (2021) Unprepared for financial shocks: emergency savings and credit card debt. Contemp Econ Policy 39(1):59–82. https://doi.org/10.1111/coep.12477

Sundén EA, Surette JB (1998) Gender differences in the allocation of assets in retirement savings plans. Am Econ Rev 88(2):207–211

The research group of the Institute for Advanced Research of Shanghai University of Finance and Economics (2018) Interactive negative feedback effect of corporate and household debt increases difficulty of deleveraging. China Econ Rep 10:94–96. (in Chinese)

Tseng Y-C, Hsiao I-F (2022) Decomposing the factors influencing household debt: the case of China. Appl Econ 54(23):2627–2642. https://doi.org/10.1080/00036846.2021.1992343

Vargas-Sierra C, Orts MÁ (2023) Sentiment and emotion in financial journalism: a corpus-based, cross-linguistic analysis of the effects of COVID. Humanit Soc Sci Commun 10(1), Article 1. https://doi.org/10.1057/s41599-023-01725-8

Wang C, Tian C (2012) Stock market participation, level of participation and its influencing factors. Econ Res J 47(10):97–107

Wang Z, Li X, Wu D (2008) Gender analysis of rural civil finance in China—a case study of microfinance organisations in western China. Soc Sci Res 2:124–132. (inChinese)

Wen Z, Ye B (2014) Mediation effect analysis: methods and model development. Adv Psychol Sci 22(05):731–745. (in Chinese)

Wendt A, Hellwig F, Saad GE et al. (2021) Are children in female-headed households at a disadvantage? An analysis of immunization coverage and stunting prevalence: in 95 low- and middle-income countries. SSM—Popul Health 15:100888. https://doi.org/10.1016/j.ssmph.2021.100888

Article   PubMed   PubMed Central   Google Scholar  

Van Winkle Z, Monden C (2022) Family size and parental wealth: the role of family transfers in Europe. Eur J Popul 38(3):401–428. https://doi.org/10.1007/s10680-022-09611-w

Wong ZY, Kusairi S, Halim ZA (2023) Household consumption and indebtedness: are there disparities between genders, rural–urban areas, and among income groups? Econ Sociol 16(3):30–43. https://doi.org/10.14254/2071789X.2023/16-3/2

Worthington AC (2006) Debt as a source of financial stress in Australian households. Int J Consum Stud 30(1):2–15. https://doi.org/10.1111/j.1470-6431.2005.00420.x

Xiao J, Yao R (2020) Debt types and burdens by family structures. Int J Bank Mark 38(4):867–888. https://doi.org/10.1108/IJBM-07-2019-0262

Xu X, Quan X, Yin H (2018) CEO gender, ownership nature, and corporate debt financing behavior. J Soochow Univ (Philos Soc Sci Ed) 39(04):98–111+192. https://doi.org/10.19563/j.cnki.sdzs.2018.04.013 . (in Chinese)

Yang S, Fan Y, Deng W, et al. (2019) Do built environment effects on travel behavior differ between household members? A case study of Nanjing, China Transport Policy 81(C):360–370. https://doi.org/10.1016/j.tranpol.2017.12.006

Yuan X (2017) Manifestations, causes, and mitigation paths of gender disparities: a literature-based review. Teach Res 7:81–90. (in Chinese)

Zeng H, Zheng L, Li X, Zhang Y, Chen L (2023) Are optimistic CEOs and pessimistic CFOs the best partners? Evidence from corporate cash holdings. Humanit Soc Sci Commun 10(1), Article 1. https://doi.org/10.1057/s41599-023-02469-1

Zhang A, Pan M, Liu B (2019) Overconfidence and corporate financing preference: a bias correction based on executive gender. J Chin Women’s Stud 40(4):53–59. https://doi.org/10.16339/j.cnki.hdxbcjb.2019.04.031 . (in Chinese)

Zhang Z, Ren K, Tan Q (2023) Digital financial development and urban–rural household debt risk differences. Res Financ Econ Issues 3:80–93. https://doi.org/10.19654/j.cnki.cjwtyj.2023.03.007 . (in Chinese)

Zheng H, Qian J, Liu G, Wu Y, Delang CO, He H (2023) Housing prices and household consumption: a threshold effect model analysis in central and western China. Humanit Soc Sci Commun 10(1), Article 1. https://doi.org/10.1057/s41599-023-02258-w

Zhou L, Chai S, Zhou L (2021) How the popularization of the Internet affects the leverage ratio of Chinese households’ debt. South China J Econ 3:1–18. https://doi.org/10.19592/j.cnki.scje.380981

Zhou L, Chen J (2020) Investor risk tolerance and household debt levels - micro evidence from the post-crisis era. Econ Manag 34(6):31–37. (in Chinese)

Zhou L, Feng D (2020) Personality traits and household debt. J Financ Dev Res (2), 32–42. https://doi.org/10.19647/j.cnki.37-1462/f.2020.02.004 (in Chinese)

Zhu W, Xia Y (2018) Research on consumer debt behavior of Chinese residents’ households. J Finance Econ 44(10):67–81. https://doi.org/10.16538/j.cnki.jfe.2018.10.005 . (in Chinese)

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Benyan Tan, Yingzhu Guo & Yan Wu

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BT: Conceptualization, project administration, supervision, methodology, validation, formal analysis, investigation, resources, writing—review and editing. YG (corresponding author): Methodology, software, validation, formal analysis, investigation, resources, data curation, writing-original draft, writing-review and editing. YW: Methodology, software, validation, investigation, resources, data curation, writing—original draft.

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Tan, B., Guo, Y. & Wu, Y. The influence and mechanism of female-headed households on household debt risk: empirical evidence from China. Humanit Soc Sci Commun 11 , 569 (2024). https://doi.org/10.1057/s41599-024-03029-x

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Received : 21 October 2023

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Published : 06 May 2024

DOI : https://doi.org/10.1057/s41599-024-03029-x

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