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• Published: 22 June 2018

The effectiveness of the food and beverage industry’s self-established uniform nutrition criteria at improving the healthfulness of food advertising viewed by Canadian children on television

• Monique Potvin Kent 1 ,
• Jennifer R. Smith 1 ,
• Elise Pauzé 1 &
• Mary L’Abbé 2  

International Journal of Behavioral Nutrition and Physical Activity volume  15 , Article number:  57 ( 2018 ) Cite this article

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Food and beverage marketing has been identified as an environmental determinant of childhood obesity. The purpose of this study is to assess whether the Uniform Nutrition Criteria established and implemented by companies participating in the self-regulatory Canadian Children’s Food and Beverage Advertising Initiative (CAI) had an impact on the healthfulness of food and beverage advertising during television programming with a high share of children in the viewing audience.

Data on food advertising were licensed from Numeris for 27 television stations for Toronto for May 2013 and May 2016 (i.e. before and after the implementation of the nutrition criteria). First, television programs that had a child audience share of ≥35% (when the nutrition criteria applied) were identified. Ten percent of these programs were randomly selected and included in the study. After identifying the food and beverage ads that aired during these programs, the nutritional information of advertised products was collected and their healthfulness was assessed using the Pan-American Health Organization (PAHO) and UK Nutrient Profile Models (NPM). The healthfulness of CAI products advertised in May 2013 and 2016 was compared using Chi-square tests.

Although in May 2016, products advertised by CAI companies were more likely to be categorized as healthier by the UK NPM (21.5% versus 6.7%, χ 2 (1) = 12.1, p  = 000) compared to those advertised in May 2013, the frequency of advertised products considered less healthy in May 2016 remained very high (78.5%) and comparable to that of products advertised by companies not participating in the CAI (80.0% categorized as less healthy). Furthermore, in both May 2013 and May 2016, 99–100% of CAI advertisements featured products deemed excessive in either fat (total, saturated, trans), sodium or free sugars according to the PAHO NPM.

Conclusions

Despite modest improvements noted after the implementation of the CAI’s Uniform Nutrition Criteria, the healthfulness of most products advertised during programs with a high share of children in the viewing audience remains poor. Mandatory regulations are needed.

Food and beverage marketing has been identified as one factor driving the upward trend in global obesity rates among children [ 1 , 2 ]. Indeed, an extensive body of research has shown that children’s exposure to this marketing, much of which promotes food and beverages of low nutritional quality, influences their dietary preferences, purchasing behaviors, and consumption patterns [ 1 , 2 , 3 , 4 ]. Based on this evidence, the World Health Organization has urged countries to develop policies to protect children from the marketing of unhealthy food and beverages [ 5 ].

In Canada, childhood obesity has tripled over the last three decades and currently more than 30% of children and youth have excess weight or obesity [ 6 ]. In the province of Quebec, commercial advertising to children has been banned since the 1980s. In all other provinces in Canada, food and beverage marketing to children is self-regulated by industry. In 2007, the Canadian Children’s Food and Beverage Advertising Initiative (CAI) was implemented by 16 food companies. Currently 18 companies participate including Coca Cola, Danone, General Mills, McDonald’s, and Nestlé, among others (see Table  1 ) [ 7 ]. Under this initiative, eleven companies have committed to not advertise to children less than 12 years old while the remainder have pledged to exclusively advertise “better-for-you” products (as defined by the companies themselves) in various media including television [ 8 ]. Each company established what constituted advertising to children, determined its own nutrition criteria defining which products are healthy enough to advertise to children, and set child audience thresholds that range from 25 to 35% (i.e. the percentage of the audience that must consist of children under 12 years of age before the pledges apply). For example, Hershey Canada has pledged to not advertise at all during television programs where children make-up 30% of the audience, while Kellogg’s has committed to only advertise “better-for-you” products, such as Froot Loops cereal, when children make-up 35% or more of the viewing audience [ 8 ].

Since its implementation, the CAI has been criticized for low participation rates, high child audience thresholds, lax nutritional standards, and very narrow definitions of what constitutes advertising to children [ 9 ]. Research in Canada has concluded that the CAI is insufficiently protecting children from food and beverage marketing on television and the Internet [ 9 , 10 , 11 , 12 , 13 , 14 ]. Indeed, Canadian children (outside of Quebec) view on average between 4 and 7 food ads per hour per station [ 15 , 16 ], and the majority of products advertised are unhealthy and high in sugar, fat and sodium [ 16 ]. Evaluations conducted before and after the implementation of the CAI have shown that these self-regulatory pledges are not limiting children’s exposure to food and beverage advertising on television. In fact, children’s exposure to this type of advertising increased between 2006 and 2009 [ 11 ] and the healthfulness of advertised products on children’s specialty channels did not improve [ 9 ].

In 2014, Uniform Nutrition Criteria were developed by participating CAI companies and these were fully implemented by December 2015 [ 7 ]. These criteria, based on 18 different nutritional recommendations, specify nutrition criteria for 8 product categories including: milk and alternatives, grains, soups, meat and alternatives, vegetables and fruit, occasional snacks, mixed dishes, and meals on the go. No nutrition criteria were established for chocolate, candy, and soft drinks because, as stated by the CAI, these foods would not be advertised to children under the age of 12. Nutrients to limit, as identified in the Uniform Nutrition Criteria, include calories, saturated fat, trans fat, sodium, and total sugars while nutrients to encourage include vitamin D, calcium, potassium, and fibre [ 7 ]. A total of 26 products are listed as compliant with the Uniform Nutrition Criteria and approved for advertising to children [ 8 ].

Though Advertising Standards Canada (ASC), the organization that administers the CAI, undertakes a yearly compliance review [ 8 ], no research to date has evaluated the impact of these new criteria using nutrient profile models used and accepted in the research community. The objective of this study was to fill this gap and assess whether the CAI Uniform Nutrition Criteria has improved the healthfulness of food/beverage advertising during television programming where children make-up a large share of the viewing audience. It was hypothesized that, after its implementation, the Uniform Nutrition Criteria would improve the healthfulness of the advertising seen by children during programming with a high share of children in the viewing audience. It was also hypothesized that the healthfulness of products advertised by CAI companies in May 2016 would be significantly better during television programs with a child audience share of at least 35%, where the new nutrition criteria applied, compared to television programs with a lower child audience share, where it did not.

A quasi-experimental pre-post design with a control group was used in this study to compare the nutritional quality of foods/beverages advertised to children aged 2–11 when viewership of this age group was equal to or greater than 35% in May 2013 (before the development of the Uniform Nutrition Criteria) and in May 2016 (after its implementation). The control group consisted of the nutritional quality of food/beverage advertisements in May 2016 when child viewership ranged from 15 to 34.9%.

Television ratings data were obtained under license for 19 food categories from Numeris for May 2013 and May 2016 for 27 television stations (9 conventional and 18 speciality channels) for Toronto, the largest broadcast audience in Canada. These food categories (defined in Table  2 ) were selected as they are those that are the most advertised to children [ 9 , 12 , 17 ]. The month of May was selected as there are no holidays in this month that could potentially distort advertising expenditures.

Using Nielsen Media Research Borealis ™ analytical software, it was determined which television programs had a child viewership of 15 to 34.9% and which had a viewership of ≥35%. The lower limit of 15% was chosen because it is the child viewership threshold applied in the province of Quebec, where all commercial advertising to children under the age of 13 has been legally prohibited since 1980 [ 18 ]. Children included those between the ages of 2 and 11 as the CAI guidelines apply to children under 12 years of age. The ≥ 35% level was selected as most CAI companies ( n  = 15) have a viewership threshold of 35% meaning that 35% of the audience must consist of children 2–11 years old before the CAI pledges apply. A total of 1536 television programs in May 2013 and 1289 in May 2016 met the ≥35% child viewership criteria while 1832 programs met the 15–34.9% viewership criteria for May 2016 (Table  3 ). For reasons pertaining to feasibility including time and resource constraints, only 10 % of these program samples were selected using a random number generator and were included in study. Using Nielsen Media Research Spotwatch™ software, the food/beverage ads that appeared during the first 30 min of each of these programs were identified.

Each food advertisement was classified as a product ad (if a food and/or beverage were featured) or as a brand ad (if no specific product was featured). Each ad was also classified as to whether it belonged to a company participating in the CAI as of November 2016 (CAI) or not (non-CAI).

Nutritional analysis

The nutrition information of products featured in each ad was collected. Nutrition data for the foods advertised in May 2013 was taken from the Food Label Information Program (FLIP) [ 19 ] which is a branded food composition database. FLIP data from 2013 contains information on ~ 15,500 products from the four largest national retailers by sales (Loblaws, Sobeys, Metro, Safeway), representing approximately 75% of the Canadian food retail market share. Nutrition information for products advertised in May 2013 not found in the FLIP database (essentially fast food and restaurant foods) and those advertised in May 2016 was collected, in order of priority, from Canadian company websites, the Nutrition Fact table on the product found in store, U.S. company websites, or the Canadian Nutrient File.

Collected information included: calories (kcal), total fat (g), saturated fat (g), trans fat (g), sodium (mg), carbohydrate (g), fibre (g), sugars (g), and protein (g) per stated serving size. The specific density (g/mL) of beverages was used to convert servings from millilitres to grams [ 20 ]. All nutrition information was then converted to 100 g servings.

The healthfulness of advertised foods and beverages was assessed using two nutrient profile models namely, the Pan American Health Organization Nutrient Profile Model (PAHO NPM) [ 21 ] and the UK Nutrient Profile Model (UK NPM) [ 22 ]. The former was selected as it considers only negative nutrients (e.g. sodium, free sugars, total fat, saturated fat, and trans fat) and classifies foods more stringently while the latter was selected as it considers both positive and negative nutrients and has been shown to classify foods less stringently and consistently with decisions made by dietitians [ 23 ]. The UK NPM has also shown to have good construct, convergent, and discriminate validity [ 24 ].

The PAHO NPM was used to classify advertised food/beverages according to whether they were excessive in total fat (≥30% of total energy from total fat), saturated fat (≥ 10% of total energy), trans fats (≥ 1% of total energy), sodium (≥ 1 mg per kcal) or free sugars (≥ 10% of total energy) [ 21 ]. Foods were also classified as excessive or not in at least one of these nutrients. The PAHO NPM was modified by applying it to all foods, including unprocessed foods, rather than applying it to processed or ultra-processed foods only. The free sugar content of foods was estimated using formulas suggested by the PAHO NPM [ 21 ].

The UK NPM, was also used to assess the healthfulness of advertised foods in May 2013 and May 2016 using the three-step process developed by the Food Standards Agency in the UK [ 22 ]. This model scores foods based on their content in energy, saturated fat, total sugar, sodium, fruit/vegetable/nut, fibre, and protein per 100 g serving. Foods that score 4 points or more and beverages that score 1 point or more are categorized as ‘less healthy’ [ 22 ]. Foods that do not fall into this category are defined as ‘healthier’.

When multiple food products were shown in the same advertisement, the ad was classified as excessive in fat, sodium and/or sugar as assessed by the PAHO NPM or as less healthy according the UK NPM if it featured at least one product that was categorized as such.

Data analysis

Nielsen’s 19 food categories were condensed by grouping similar products to create 9 more meaningful categories. These included: cold cereal; candy and chocolate; cakes, cookies and ice cream; juice, soft drinks (regular and diet), sports drinks and energy drinks; pizza; compartment snack foods and portable snacks; restaurants (fast food and non-fast food); cheese; and yogurt. The frequency of ads by food categories and CAI participation were tabulated and the percentage change between May 2013 and May 2016 was calculated. Statistical tests (Mann-Whitney U test) compared the energy, total fat, saturated fat, trans fat, carbohydrates, sugar, protein, fibre, and sodium content per 100 g serving of foods and beverages featured in May 2013 advertisements to those in May 2016 for CAI and non-CAI companies. When ads featured multiple products, the nutrition information for the least healthy product as assessed by the UK NPM (i.e. the product with the highest score) was used for this analysis. If several products within the same ad tied for the highest score, one product was randomly selected using a random number generator. Chi-square tests were conducted to determine if the healthfulness of advertised foods as classified by the PAHO and UK NPMs during programming with a high child audience share changed between May 2013 and May 2016. The Mann-Whitney U and Chi-square tests described above were conducted for the ≥35% child viewership sample. Further comparisons were made between products advertised by CAI companies when child viewership was 15–34.9% and ≥ 35% in May 2016. The healthfulness of products advertised in May 2013 and May 2016 when child viewership was at least 35% was also compared by food category using Fisher Exact Tests.

Product versus brand advertising

In May 2016, 0.5% ( n  = 2) and 2.1% ( n  = 7) of total ads were brand advertisements in the 15–34.9% and ≥ 35% child viewership samples, respectively. The remainder were products ads. There were no brand ads in the 35% viewership sample in May 2013.

Frequency of food/beverage advertising per food category in May 2013 and in May 2016 (≥35% sample)

Overall, the frequency of food/beverage advertising was 38.0% higher in May 2016 compared to May 2013. The most frequently advertised product categories in May 2016 (as shown in Table  4 ) were restaurants (33.8% of total ads; 92.9% of which were fast food), candy and chocolate (18.0%), and cold cereal (15.3%). Among beverage categories advertised in May 2016 ( n  = 14), 81.3% were for juices, drinks, and nectars, 12.5% were for regular soft drinks, and 6.3% were for energy drinks (data not shown). In total, yogurt advertising was up by 217%, cold cereal advertising was up approximately 113%, while cheese advertising was up 81%, snack advertising was up 33%, and restaurant advertising was up 40% in May 2016 compared to May 2013. Advertising for fast food restaurants exclusively increased by 40.0% from May 2013 ( n  = 75) to May 2016 ( n  = 105) (data not shown).

Among CAI companies, the frequency of food/beverage advertisements was 55.8% higher in May 2016 compared to May 2013. The CAI product categories that were the most frequently advertised in May 2016 were cold cereals (27.3%), restaurants (19.3%; all of which were for fast food) and candy and chocolate (16.6%). The largest increases in CAI advertising between May 2013 and May 2016 were for yogurt (533%), cheese (125%), cold cereals (113%), and juice and soft drinks (50%). Restaurant advertising, comprised entirely of fast food advertisements, increased 38.5% in May 2016 compared to May 2013.

Nutrient content per 100 g of foods/beverages advertised in May 2013 and May 2016 (≥35% sample)

Overall, products advertised in May 2016 when child viewership was at least 35% contained more sodium (U = 44,057, z = 2.41, p  = .016, r  = 0.10), trans fat (U = 45,950, z = 3.78, p  = .000, r  = 0.16), fibre (U = 44,953, z = 3.12, p  = 002, r  = 0.13), and protein (U = 46,308, z = 3.58, p = .000, r  = 0.15) per 100 g serving compared to those advertised in May 2013 (Table  5 ). In May 2016, products advertised by CAI companies contained fewer calories (U = 8962, z = − 2.92, p  = .004, r  = − 0.17) and total fat (U = 9628, z = − 2.03, p  = .042, r  = − 0.12) per 100 g serving than in May 2013.

Healthfulness of foods advertised in May 2013 and May 2016 (≥35% sample)

Overall in 2016, according to the PAHO criteria, 68.4% of advertisements featured foods/beverages that were excessive in free sugar, 59.8% were excessive in total fat, 59.5% were excessive in sodium, 50.3% were excessive in saturated fat, and 29.1% were excessive in trans fats as shown in Table  6 . According to the PAHO criteria, 100% of food advertisements in 2016 featured products classified as excessive in at least one of these nutrients while according to the UK NPM, 79.1% of ads featured products that were classified as ‘less healthy’. In May 2016, it was 1.5 times more likely that food advertisements were deemed excessive in total fat (49.8% versus 59.8%, χ 2 (1) = 5.64, p  = .018) compared to those that aired in May 2013. Advertisements in May 2016 were also 1.7 times more likely to be deemed excessive in trans fat (19.9% versus 29.1%, χ 2 (1) = 6.25, p  = .012) and sodium (46.5% versus 59.5%, χ 2 (1) = 9.48, p  = .002) compared to May 2013. Conversely, advertisements in May 2016 were 1.7 times less likely to feature food deemed less healthy by the UK NPM compared to May 2013 (86.7% versus 79.1%, χ 2 (1) = 5.48, p  = .019).

Among CAI companies, it was 2.9 and 1.8 times more likely that advertisements airing in May 2016 featured a product classified as excessive in trans fat (10.0% versus 24.2%, χ 2 (1) = 9.69,p = .002) and sodium (44.2% versus 58.6%, χ 2 (1) = 6.10, p  = .014), respectively, compared to those advertised in May 2013. In both time periods, 99–100% of CAI advertisements featured products that were classified as excessive in at least one nutrient according to the PAHO NPM however the frequency of advertisements featuring less healthy products as per the UK NPM was significantly lower in May 2016 compared to May 2013 (93.3% versus 78.5%, χ 2 (1) = 12.1, p  = .000).

Healthfulness of products advertised in May 2013 and May 2016 by food category (≥35% sample)

Cold cereals advertised in May 2016, all of which belonged to CAI companies, were more likely to be excessive in sodium compared to those advertised in May 2013 (98.0% versus 33.3%, p = .000) As for restaurants, foods advertised by CAI companies (i.e. McDonald’s) in May 2016 were less likely to be deemed less healthy (88.5% versus 42.9%, p  = .010) compared to those advertised in May 2013. This was also true for the total sample of restaurant advertisements (81.3% versus 63.6%, p = .010) (data not shown).

Nutrient content per 100 g of foods/beverages advertised by CAI companies in May 2016 (≥35% vs. 15–34.9% sample)

According to Mann-Whitney U tests, foods/beverages advertised by CAI companies contained more sugar (Mdn = 10.9 g and 20.0 g, U = 24,994, z = 2.62, p  = .009, r  = 0.13) and protein (Mdn = 5.0 g and 6.7 g, U = 24,212, z = 1.99, p  = .047, r  = 0.10) per 100 g serving when child viewership was 35% or higher compared to 15–34.5% (Table  7 ).

Healthfulness of foods advertised by CAI companies in May 2016 (≥35% versus 15–34.9% sample)

There were no statistically significant differences in the healthfulness of products advertised by CAI companies in May 2016 as per the PAHO and UK NPMs when child viewership was ≥35% and 15–34.9% (Table  8 ).

Impact of the Uniform Nutrition Criteria

As hypothesised, when using the less stringent UK NPM, the products advertised during television programming with a high child audience share were marginally healthier in May 2016 (when the Uniform Nutrition Criteria applied) compared to those advertised in May 2013 (when it did not). Despite these modest improvements, more than 75% of all food advertisements featured products categorized as ‘less healthy’ and all of them featured products deemed excessive in either fat (total, saturated, trans), sodium or free sugars according to the more stringent PAHO NPM. When we exclusively examined CAI advertisements, results were similar and the overall healthfulness of products advertised in May 2016 was comparable to that of non-CAI companies to which the Uniform Nutrition Criteria did not apply. Though we attempted to compare the healthfulness of products advertised between May 2013 and May 2016 by food category, the sample size of many categories was too small to reliably test differences. Some results suggest that the healthfulness of some product categories advertised by CAI companies may have improved (e.g. fast food) while others suggest a worsening (e.g. cold cereals).

Our results also showed that contrary to what was hypothesized, foods advertised by CAI companies in May 2016 were not healthier according to both NPMs when child viewership was at least 35% compared to those advertised when child viewership was 15–34.9%. Together, these results suggest that the CAI’s Uniform Nutrition Criteria has not been particularly effective at improving the healthfulness of food/beverage advertising viewed by children aged 2 to 11 on television. This finding is consistent with previous research in Canada [ 9 , 10 , 11 ], the United States [ 25 , 26 , 27 ] and other countries [ 28 ] which has shown that self-regulation has not led to meaningful changes in the healthfulness of products advertised to children on broadcast television. Given this lack of effectiveness, many national and international organizations have called for the introduction of statutory regulations [ 5 , 29 ]. Quebec’s Consumer Protection Act that prohibits commercial advertising to children under 13 years is often lauded as a model for other countries thinking of developing child advertising restrictions [ 30 ]. Indeed, research has shown this law is having some positive impact on children’s exposure to food and beverage advertising [ 12 , 16 ]. For instance, some children in Quebec are exposed to fewer food/beverage advertisements on television and this advertising features fewer promotional techniques designed to appeal to children [ 12 ]. However, since the Consumer Protection Act was not specifically designed to restrict unhealthy food/beverage advertising, children in Quebec are still exposed to a large volume of food and beverage ads that target adolescents and adults and the healthfulness of advertised products are only marginally healthier than those advertised to children outside Quebec [ 16 ].

To effectively protect children from unhealthy food/beverage advertising, robust nutrition criteria defining which products can be advertised to them need to be adopted. Consideration also needs to be given to limiting children’s exposure to the promotion of brands that are largely associated with unhealthy foods (even if an ad features a healthy product), as the effect of advertising likely extends to other products of the same brand, regardless of their healthfulness. Indeed, research has shown that branding affects children’s food preferences and choices [ 31 , 32 ]. An experimental study carried out by Boyland et al. [ 33 ], for example, found that the exposure to television advertisements featuring a healthier fast food meal led to the increased liking for fast food among children but did not result in healthier food choices made in a hypothetical situation. One way of limiting the promotion of brands associated with unhealthy products to children would be to only permit the advertising of brands whose entire product line meets the established nutrition criteria. Alternatively, it has also been suggested that food brands be classified as healthy or unhealthy based on the five most purchased products sold under that brand [ 34 ]. Though we documented a slight increase in brand advertising in May 2016 compared to May 2013, one may expect companies to increase such advertising if more stringent self-regulatory (or statutory) restrictions solely based on nutrient profiling were to be implemented (and adhered to).

Some of our results make one question whether the CAI companies are, in fact, complying with the Uniform Nutrition Criteria. To illustrate, in our May 2016 study sample when child viewership was at least 35%, 15 candy, 16 chocolate bar, and 1 soft drink ads belonging to CAI companies were identified despite their pledge to not advertise these products to children under the age of 12 when child audience thresholds were equal to or exceeded 35%. Some of these non-compliant ads aired on child and youth oriented channels such as YTV, Teletoon, and Much Music during programs that could be expected to appeal to children. For example, M&M’s candy and McDonald’s beverages (including a fruit smoothie, Coca Cola, and iced coffee) were advertised on May 9, 2016 during Just for Laughs Gags airing at 8 pm on YTV where the share of child viewers reached 37.3%. Four non-compliant advertisements (two for M&Ms., one for Skittles and one for McDonald’s beverages) also aired on May 14, 2016 during Mighty Hercules between 9 and 9:30 pm on Teletoon where children made up 42.1% of the audience. Advertisements belonging to seven companies that have pledged to abstain from advertising when child viewership reaches 25–35% were also identified in our sample. Six companies who pledged to only advertise ‘healthier’ foods  advertised products not specifically listed as compliant with the Uniform Nutrition Criteria. Since this study did not assess whether these unlisted products met these nutrition criteria, we cannot say whether the latter six companies are complying with their voluntary commitment. Since ad time is purchased based on projected audience estimates, companies would likely argue that they are complying with the CAI and could not have known that child audiences would be higher than projected. Though this may be true, companies could choose to purchase ad time based on stricter child audience thresholds (also known as “guardbanding”) to increase the likelihood of true compliance [ 35 ]. The examples of non-compliance cited above, whereby candy and sugar-sweetened beverages were advertised during children’s programming, also suggest at the very least that some companies are not complying with the spirit of the CAI. Our findings differ from those published by Advertising Standards Canada (ASC) [ 8 ]. ASC’s 2016 compliance report identified no instances of non-compliance during spot checks that examined 48 h of children’s television programs airing on three child-targeted channels (Teletoon, YTV, and Nickelodeon) during select time periods (e.g., YTV was checked from 6 am to 9 am on weekdays and 6 am-12 pm on Saturday) [ 8 ]. The instances of non-compliance identified in our study were either identified on channels different from those checked by the ASC (e.g. Much Music, CTV) or aired outside the time frames that were examined (e.g. on YTV, after 6 pm). This discrepancy highlights the inadequacy of current monitoring activities led by advertising standard agencies that are industry-funded. Independent monitoring is clearly needed to assess the impact of food/beverage advertising restrictions as well as company compliance.

In addition to non-compliance, the healthfulness of products advertised by the CAI may have only been modestly better in May 2016 compared to May 2013 as measured by UK and PAHO NPMs because the Uniform Nutrition Criteria themselves are not very stringent. For example, over a third (10) of the 26 products that are listed as compliant and approved for advertising to children by the CAI are sugar-sweetened breakfast cereals and include Froot Loops, Frosted Flakes, Alpha Bit Cereal, and Lucky Charms. Fruit flavored snacks such as Fruit by the Foot and Fruit Gushers, whose most predominant ingredient is sugar [ 36 , 37 ], are also among the approved products. Given that many of these products are considered less healthy by the UK NPM (and would be by any other sound nutritional standards), it is not surprising that most CAI advertisements would still be considered unhealthy after the implementation of the Uniform Nutrition Criteria during programming on which it applies. For example, 7 of the 8 compliant CAI products advertised in May 2016 in our sample were deemed less healthy according to the UK NPM. Even if CAI companies were to adopt more stringent nutrition criteria, the voluntary nature of the initiative would still limit its effectiveness in improving the healthfulness of products advertised to children.

Though not related to the CAI or the Uniform Nutrition Criteria, it is interesting to note that our study identified four Red Bull advertisements (one in May 2016 and three in May 2013) during programs where child viewership reached 35% even though Health Canada regulations prohibit the advertising of energy drinks to children [ 38 ]. Similar results have been found on 2 of 10 Canadian child preferred websites where ads for Red Bull appeared on websites where children aged 2–11 constituted more than 45% of website visitors [ 39 ]. The promotion of energy drinks to children is worrisome given the adverse health effects associated with their consumption including anxiety, sleep disturbances, cardiovascular and gastro-intestinal symptoms, and even seizures and death in some rare cases [ 40 , 41 ]. Interestingly, Red Bull GmbH is a member of the Canadian Beverage Association, an industry interest group that claims that all its members “voluntarily commit to not advertise energy drinks in programming … whose primary target audience is children” (i.e. when children under 12 years constitute more than 35% of the audience) [ 42 , 43 ]. The energy drink ads found in our sample are further evidence that voluntary pledges made by industry are ineffective in protecting children.

This study also found that the frequency of food/beverage advertisements was higher in May 2016 compared to May 2013 during programs where children made-up 35% or more of the viewing audience. During this programming, there were on average of 1.6 food/beverage ads per 30-min program in May 2013 while in May 2016, there were 2.6 ads per program. The frequency of ads belonging to CAI companies was also higher in May 2016 (1.4 ads/program) compared to May 2013 (0.8 ads/program). The increase in frequency may be due to a rise in total advertising during television programs though what remains clear is that children’s potential exposure to food/beverage advertising on television has increased.

Strengths and limitations

This study is the first to evaluate the CAI Uniform Nutrition Criteria. Its strengths include the use of Numeris and Nielsen Media Research data and analytical software. Further, this study also applied two nutrient profile models, the PAHO and UK NPMs, which provided a comprehensive assessment of the healthfulness of products advertised to children. Though the UK NPM offered good reliability and validity, it is currently being reviewed to more accurately reflect the latest dietary guidelines, particularly as it pertains to sugar [ 44 ]. The use of the 2013 FLIP data was also a strength given that it coincided with the May 2013 advertising data. However, it did not include nutritional information for fast food therefore this data had to be drawn from 2016 data. Any fast food reformulation between 2013 and 2016 would therefore not be accounted for in our data. This research was also based on the advertising of 19 food categories frequently advertised to children on Canadian television stations. Therefore, our findings cannot be generalized to other food categories, other media, or to non-Canadian television stations. A final limitation is that our research does not specifically evaluate individual company compliance; it is therefore difficult to determine whether the Uniform Nutrition Criteria are to blame for the poor nutritional quality of food advertising to children or whether it is a question of companies not complying with the criteria (or both).

This study adds to the body of evidence showing that industry self-regulation does not lead to substantive improvements in food/beverage advertising directed at children on television, further emphasizing the need for statutory restrictions. To protect children, food/beverage restrictions based on stringent nutrition criteria need to be adopted. The instances of non-compliance cited in this study also highlight the need for effective third-party monitoring to hold food and beverage companies accountable.

Abbreviations

Advertising Standards Canada

Canadian Children’s Food and Beverage Advertising Initiative

Food label information program

Pan American Health Organization Nutrient Profile Model

United Kingdom Nutrient Profile Model

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Potvin Kent, M., Smith, J.R., Pauzé, E. et al. The effectiveness of the food and beverage industry’s self-established uniform nutrition criteria at improving the healthfulness of food advertising viewed by Canadian children on television. Int J Behav Nutr Phys Act 15 , 57 (2018). https://doi.org/10.1186/s12966-018-0694-0

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Visual communication via the design of food and beverage packaging

• Charles Spence   ORCID: orcid.org/0000-0003-2111-072X 1 &
• George Van Doorn 2 , 3 , 4  

Cognitive Research: Principles and Implications volume  7 , Article number:  42 ( 2022 ) Cite this article

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A rapidly growing body of empirical research has recently started to emerge highlighting the connotative and/or semiotic meanings that consumers typically associate with specific abstract visual design features, such as colours (either when presented individually or in combination), simple shapes/curvilinearity, and the orientation and relative position of those design elements on product packaging. While certain of our affective responses to such basic visual design features appear almost innate, the majority are likely established via the internalization of the statistical regularities of the food and beverage marketplace (i.e. as a result of associative learning), as in the case of round typeface and sweet-tasting products. Researchers continue to document the wide range of crossmodal correspondences that underpin the links between individual visual packaging design features and specific properties of food and drink products (such as their taste, flavour, or healthfulness), and the ways in which marketers are now capitalizing on such understanding to increase sales. This narrative review highlights the further research that is still needed to establish the connotative or symbolic/semiotic meaning(s) of particular combinations of design features (such as coloured stripes in a specific orientation), as opposed to individual cues in national food markets and also, increasingly, cross-culturally in the case of international brands.

Introduction

The visual design of food and beverage product packaging is at something of a crossroads. The field currently lies between the traditional art and design approach—often based on the intuitions of creative designers/marketers (and/or the results of focus groups or in-depth interviews; Cheskin, 1957 , 1967 , 1972 ; Lunt, 1981 ; Rapaille, 2007 ; Stern, 1981 )—and the more scientific approach to visual communication (i.e. presenting information graphically, such that it creates meaning concerning the product and its attributes/brand associations; Underwood, 1993 , 1999 ; Underwood & Klein, 2002 ; Underwood & Ozanne, 1998 ; Underwood et al., 2001 ). The latter approach is increasingly coming to be based on our growing understanding of, for example, the crossmodal correspondences (Spence, 2011 , 2012 ; Velasco & Spence, 2019a ; Velasco et al., 2016b ; cf. Batra et al., 2016 ; Schifferstein et al., 2013 ; Skaczkowski et al., 2016 ; Thomson, 2016 ).

Crossmodal correspondences refer to the tendency for a feature or attribute in one sensory modality (e.g. the colours pink and red) to be associated with a sensory feature in another sensory modality (e.g. a sweet taste; Ngo et al., 2013 ; Spence & Parise, 2012 ; Woods et al., 2013 ). Often, these connections between the senses are surprising, much like synaesthesia. Footnote 1 Indeed, some researchers have even suggested that synaesthetic inducer-concurrent relations could be used productively in the field of product design (Haverkamp, 2014 ) and/or product packaging/marketing (cf. Crisinel & Spence, 2012 ). That said, it is important to stress that the approach outlined here, based on crossmodal correspondences, differs from the phenomenon of synaesthesia in that the cross-sensory connections expressed in the former case tend to be shared between people, whereas synaesthesia is defined by the idiosyncratic nature of the inducer-concurrent mapping (see Deroy & Spence, 2013 ; Spence, 2019 ).

Visual design features are not only associated with taste/flavour attributes, Footnote 2 but with a range of connotative and semantic meanings (e.g. green = healthy) as typically assessed by research using the semantic differential technique (e.g. Morich, 1981 ; Snider & Osgood, 1969 ; see also Kunz et al., 2020 ). However, design cues (such as colour) are also used to set consumer expectations around product variant, brand, quality, and price (with black packaging often linked with luxury and premiumness, whereas orange is typically associated with cheapness; see Velasco & Spence, 2019c ; Wheatley, 1973 ). Given that we typically see colour in context (Elliot & Maier, 2012 ), and that context is (at times) influenced by culture, it might be thought that it would be unlikely for there to be many universal meanings associated with specific visual design features, such as a particular hue. That said, Tham et al. ( 2020 ) recently tested English monolinguals, Chinese bilinguals, and Chinese monolinguals in order to establish the conceptual associations that the different groups had with colour words and colour patches. According to their results, white was associated with purity, blue was related to water/sky themes, green was linked to healthy, purple was regal, and pink was linked to female for all three groups. At the same time, however, red and orange were associated with enthusiastic in Chinese, whereas red was associated with attraction in English. In other words, Tham et al.’s results highlight the existence of both a number of cross-cultural similarities and differences in the conceptual associations that different groups of people appear to hold with colours and colour words.

In this narrative review, and in relation to visual design, we are particularly interested in the crossmodal correspondences that may exist between various ‘abstract’ visual features Footnote 3 —colours (either when presented individually or in combination), simple shapes/curvilinearity, and the orientation and relative position of those design elements on the packaging—and the chemical senses (specifically taste/flavour). That said, several other connotative/symbolic/semantics associations of visual features/attributes (e.g. with healthy/natural, price, premiumness, etc.) will also be discussed (see Marques da Rosa et al., 2019 ). It is important to stress here that the term ‘abstract’ here refers to those features that are not associated with a specific object—while many abstract visual design features can be classed as simple stimuli, some patterns and face-like arrangements of lines might be considered complex. Hence, a patch of blue or a specific simple shape like a circle can be considered abstract design features, whereas the picture or outline of a hamburger, say, or the image of some fruit (see Piqueras-Fiszman et al., 2013 ), would not.

Visual design of product packaging based on crossmodal correspondences

While a handful of famous designers and marketers have long been lauded for their design choices that helped boost long-term brand/product success (see Cheskin, 1957 , 1967 , 1972 ; Dichter, 1975 ; Favre & November, 1979 ; Graham, 2016 ), it often appeared as though their decisions were based on intuition, sometimes backed-up by the results of consumer/focus-group research and in-depth interviews (Catterall & Maclaran, 2006 ; Lunt, 1981 ; Samuel, 2010 ). By contrast, an emerging body of empirical research on the crossmodal correspondences is now starting to help establish the connotative meaning of a variety of different abstract visual design features. In particular, a broad array of findings from experimental psychology have helped to establish the meanings (connotative and otherwise) that are associated with (or primed by) everything from colours (Déribéré, 1978 ; Ho et al., 2014 ; Spence, 2020a ; Van Doorn et al., 2014 ) to shapes (Dichter, 1971 ; Mirabito et al., 2017 ; Motoki & Velasco, 2021 ; Spence, 2012 , 2020b ; Spence & Van Doorn, 2017 ; Van Doorn et al., 2017 ; Velasco & Spence, 2019a ; see also Yarar et al., 2019 ), and from curvilinearity to the relative position of various design elements on product packaging (Romero & Biswas, 2016 ; Simmonds et al., 2018b ; Sundar & Noseworthy, 2014 ; Velasco et al., 2015c ).

Several of these visual cues, such as a curved line that, at least when presented horizontally, can be interpreted as a smile (Karim et al., 2017 ; Salgado-Montejo et al., 2015b ; cf. Kühn et al., 2014 ; Windhager et al., 2008 ) and patterns that may be interpreted as looking like a snake, spider, or scorpion (Hoehl et al., 2017 ; Isbell, 2006 ; Van Lee et al., 2013 ; LoBue, 2014 ; Spence, 2021a ) have been associated with possibly innate responses that are (often) attention-capturing, albeit typically negatively valenced in the latter cases. However, the meaning of many other visual design cues is much more likely to be established on the basis of associative learning. Footnote 4 Here it is also important to consider the commonly accepted symbolic and semiotic meaning of packaging design features in the food and beverage marketplace (e.g. cartoon portrait logos and their association, in Western cultures, with their often humorous messages; Barthel, 1989 ; Danesi, 2013 ; Garber et al., 2008 ; Gardner & Levy, 1955 ; Levy, 1959 ; Mick, 1986 ; Plasschaert, 1995 ).

Researchers have, for example, highlighted how the packaging of flavours/varieties of crisps/potato chips tend to be coloured in a specific (albeit somewhat arbitrary) manner (see Piqueras-Fiszman et al., 2012 ). Green packaging, for example, is often (though not always) associated with cheese and onion flavour in the UK, whereas blue packaging typically signals salt and vinegar instead (though see Visser, 2009 , p. 109, on the suggestion that salt and vinegar type crisps are colour-coded purple-pink). As another example, one might take the different colour associations with full-, half-, and low-fat milk that exist in different parts of the world (Simmonds & Spence, 2019 ). In Australia, for example, light milk (i.e. 2% milk) is often tagged with colour-coded caps that are light blue, while full-cream milk often has dark blue caps and labels (Cutolo, 2021 ). By contrast, in the UK, skimmed milk (containing less than 0.3% fat) is typically tagged with red caps, semi-skimmed milk (i.e. less than 2% fat) is tagged with green, and full-fat milk is tagged with the colour blue.

Different packaging label colours are sometimes also associated with different forms of animal protein (e.g. consider the different colour codes that are often used to help distinguish lamb, beef, poultry, and pork) in the fresh meat category (see Simmonds & Spence, 2019 , for a review). As such, a particular hue may be associated with a range of different attributes/qualities, and the extent to which different associations are primed may well ultimately depend on the context in which that colour happens to be presented (see Elliot & Maier, 2012 ; Motoki & Velasco, 2021 ), and the familiarity of the consumer with the conventions of the marketplace in which they happen to find themselves.

Such market-/country-specific differences also speak to the role of culture (built on habit and prior experience/exposure) in determining the meaning of colour in a given context (see also Jonauskaite et al., 2019a ). It is important to stress, though, that in contrast to the often-published observations of those in marketing who, over the years, have attempted to map out the abstract meaning of colours (e.g. Aslam, 2006 ; Jacobs et al., 1991 ; Wheatley, 1973 ), or emotional associations with colours (e.g. Adams & Osgood, 1973 ), colour is nearly always seen in context (Elliot & Maier, 2012 ; though see also Amsteus et al., 2015 ). Furthermore, researchers have recently argued for the importance of context in terms of a theory of semantic discriminability (Mukherjee et al., 2022 ; Schloss et al., 2021 ). According to the latter researchers, the mapping of a colour to a particular concept is often inferred on the basis of other stimuli in the comparison group, rather than being based directly on the strength of the underlying association. Footnote 5 Figure  1 frames Mukherjee and colleagues’ distinction in the context of the colour of potato chip packaging. What their theory means, in practice, is that sometimes the inferred colour–flavour mapping need not necessarily reflect the strongest colour–flavour association.

adapted from Schloss et al. ( 2018 )

Distinction between colour–flavour associations and inferred mappings, showing colour–flavour association strengths for flavours ‘Cheese and onion’ and ‘Salt and vinegar’ with crisp packaging colours blue, green, and pinkish-purple (thicker lines connecting flavours with colours indicate stronger associations). What such a hypothetical situation highlights is how the colour–flavour mapping may result from inference rather than direct association. Figure

Various abstract visual design features normally exist on product packaging alongside semantic information concerning brand name, product description, (any) product imagery, and/or possibly also serving suggestions (Rebollar et al., 2012 ; Simmonds & Spence, 2019 ; Thomson, 2016 ; Visser, 2009 ). Although product, and other kinds of, visual imagery seen on packaging (or seen through transparent windows in the packaging) undoubtedly play an important role in determining the consumer’s impressions of a variety of food and beverage products (Simmonds & Spence, 2017 , 2019 ; Simmonds et al., 2018a ), reviewing the literature documenting the role played by such concrete (typically semantically meaningful) visual cues falls beyond the scope of this targeted narrative review. This review will instead focus specifically on abstract visual design features and their relation to product taste/flavour, healthiness, price, etc. Those readers interested in the influence of product imagery are directed to Simmonds and Spence’s ( 2019 ) review.

Review outline

In ‘ On the meaning associated with individual abstract visual packaging cues ’ section, we review what is currently known about the connotative meanings (including crossmodal correspondences) associated with specific design features such as colour, shape, orientation/position, and the use of convention-defying visual designs. In ‘ Combining abstract visual design features ’ section, the discussion is extended to the meaning of combinations of abstract visual cues using, as a recent commercial example, the under-researched combination of colour and stripes (i.e. a band of colour that differs from the colour on either side of it). Applied researchers have now deconstructed a number of elements of food and beverage packaging design in order to try and discern how to optimize everything from the connotation of ‘healthiness’ (Cavallo & Piqueras-Fiszman, 2017 ; Huang & Lu, 2013 , 2015 ; Marques da Rosa et al., 2019 ; Reinoso-Carvalho et al., 2021 ), spiciness (Gil-Pérez et al., 2019 ), and quality (Pombo & Velasco, 2021 ; Wang, 2013 ). To date, however, only limited research has investigated the influence of vertical or horizontal orientation on consumer perception and product sales. This is demonstrated by the fact that in recent books on packaging (e.g. Velasco & Spence, 2019a , b ), there is virtually no mention of the topic. As such, there is a need to review the existing literature and make recommendations for future research. The ‘ Conclusions and future directions ’ section offers some directions for future research. Areas that are not covered by this review include the consumers’ response to innovations in specific packaging design/technology, nor will issues related to the sustainability of product packaging be discussed (e.g. Associated Press, 2013 ; Azzi et al., 2012 ; Rundh, 2005 ; Silayoi & Speece, 2007 ).

Note that in addition to providing an up-to-date review of the literature on visual aspects of packaging design, we also highlight several further concrete areas for future packaging research. These include determining which of the many meanings associated with specific abstract design features such as colours or packaging shapes are primed in the mind of the consumer under everyday conditions (i.e. away from the specific task constraints typically imposed by the experimenter in most laboratory research). Having determined several different meanings that are associated, individually, with specific visual design features, further research is clearly also needed to help determine which cues dominate and/or how different abstract design features combine to convey specific meanings to consumers in different markets/contexts (Visser, 2009 ). A priori, one might consider whether sub-/super-/additive interactions will be observed when various visual design cues (e.g. colour and shape) are combined. Alternatively, however, it would also seem possible that one cue, such as colour might tend to dominate over other cues (such as, for example, colour dominating over shape, typeface, or texture). At the same time, however, it is also important to stress the fact that the intramodal perceptual grouping (Wagemans, 2015 ) of visual cues may give rise to a different meaning/association entirely than that associated with, or primed by, the individual sensory cues (see Dreksler & Spence, 2019 ).

Over the years, a number of different theoretical accounts have been put forward in order to try and explain the meanings/associations that may be primed by different visual design features (see Table 1 for a summary of the various accounts that have been used to help explain the meaning of abstract visual design cues). The accounts include (a) grounded cognition theory where, for example, a ‘strong is heavy’ metaphor is activated, and thus congruency dictates that heavy objects should appear at the bottom of packaging (Fenko et al., 2018 ), (b) conceptual metaphor theory where healthy foods are associated with high verticality, and thus should be situated at the top of product packaging (Wang & Basso, 2021 ), (c) the connotative meaning account based on the semantic differential technique (see Table 2 for a summary of the various different methods used by researchers in this area), and crossmodal correspondences (e.g. green = healthy; Morich, 1981 ), (d) the theory of semiotics where signs convey meaning (e.g. cartoon portrait logos mentioned above; Barthes, 1977 ; Chandler, 2017 ), and (e) various evolutionary explanations where stripes may have evolved to attract attention. Ultimately, in terms of parsimony, it would obviously be desirable to consider whether any unifying explanatory account might be invoked/developed to help provide an overarching explanation for the meaning of visual design. However, when we take a careful look at each visual design cue in turn (see below), there is as yet little progress in developing such a commonly agreed account of visual design.

As highlighted in Fig.  2 , it is clear that there are multiple roles for visual design cues, both related to communicating meaning, or setting expectations, as well as in terms of attentional capture in a realistic visual (multisensory) environment (e.g. Peng-Li et al., 2020 ). Certainly, there is interest in those factors that facilitate attentional selection (Reutskaja et al., 2011 ). Here, it is worth stressing that visual design of product packaging has not only been shown to set specific expectations but can also modify people’s product experience. Very often, the approach used by researchers in this area is first to establish the expectations that are primed in the mind of the consumer on being presented with specific packaging designs. Thereafter, on occasion, researchers will then assess whether the differing expectations set by different packaging designs carry through to influence the consumer’s experience of the product itself (de Sousa et al., 2020 ; Togawa et al., 2019 ; Van Rompay et al., 2019 ; cf. Carvalho & Spence, 2019 ).

Assessment of visual design choices regarding specific individual design features (e.g. use of a particular colour or shape) at various stages of the packaging (design) journey

Ultimately, of course, the role of effective product packaging is not solely to communicate with the consumer and, on occasion, to enhance product experience, packaging also plays an important role in capturing the consumer’s attention on the shelf or online product display (see Fig.  2 ). It is intriguing to note here how a distinct body of research has attempted to assess the effectiveness of attentional capture, and the ease of finding a given target product on a more or less realistic shelf/online display (Reutskaja et al., 2011 ; Zhao et al., 2017 ). Ultimately, of course, the success of packaging designs is reflected in long-term sales, though here there simply tends to be less publically available research (Sugermeyer, 2021 ; cf. Kroese et al., 2016 ; Kühn et al., 2016 ).

On the meaning associated with individual abstract visual packaging cues

In this section, we review the evidence concerning the various meanings that may be associated with specific abstract visual cues in the context of product packaging (focusing primarily on the case of food and beverage packaging). Here, the focus will be on the meanings that consumers associate with colours, basic shapes, visual textures (Barbosa Escobar et al., 2020 ; see also Matthews et al., 2019 ), as well as the orientation and relative position of specific design elements. At the outset, it is worth highlighting the fact that there are different denotative, connotative, semiotic, and semantic meanings potentially associated with specific abstract visual design features, either when presented individually, or more commonly, when presented in combination (see Visser, 2009 ). That is, abstract visual design features may be associated with a specific product, brand, or category of product (see Baxter et al., 2018 ). Abstract visual design features such as colour or shape may also come to be associated with other product attributes such as healthiness, naturalness, indulgence, luxury, or cheapness (see Cavallo & Piqueras-Fiszman, 2017 ; Mai et al., 2016 ; Piqueras-Fiszman et al., 2012 ; Schuldt, 2013 ; Tijssen et al., 2017 ; Velasco & Spence, 2019c , for examples). There is also a ‘green/environmental concern’ association with unsurprisingly, the colour green (see Schloss et al., 2018 , in the context of recycling).

The focus in this review will primarily be on trying to understand the ‘meaning’ of various different abstract visual design features in terms of the crossmodal correspondences that have been established with sensory properties of the food and beverage products themselves, such as sweetness. At the same time, however, we will also summarize the relevant literature on the connotative meanings of abstract visual design features, such as active–passive, good-bad, dominant-submissive, that have been established by research using the semantic differential technique (Adams & Osgood, 1973 ; Henson et al., 2006 ; Osgood et al., 1957 ). Over the years, Word Association (Piqueras-Fiszman et al., 2013 ), Implicit Association Tests (Parise & Spence, 2012 ), and Conjoint Analysis (Ares & Deliza, 2010 ; Baptista et al., submitted; Gislason et al., 2020 ), as well as focus group research (Lunt, 1981 ; Rapaille, 2007 ; Stern, 1981 ) have all been used by those researchers wanting to establish the more abstract, symbolic/semiotic meanings that may be associated with specific abstract visual design features (typically when embedded in product packaging) (see Table 2 for a summary of techniques). We presumably also need to consider the benefits of the consumer neuroscience, or neuromarketing approaches to design (see also Huang et al., 2021 ). However, it should be noted that despite a longstanding interest in the consumer neuroscience of product packaging (see Weinstein, 1981 , for early research), the body of research that has been published to date remains fairly limited (see Moya et al., 2020 , for a review).

Having set the background for our consideration of the various meanings associated with abstract visual packaging design cues in the world of food and beverage packaging, we will now take a closer look at each of the main visual design features in turn, starting with perhaps the most frequently studied abstract visual design feature, namely colour.

On the multiple meanings of packaging colour and other visual appearance cues

Perhaps the single most extensively studied visual design feature on product packaging is colour (Baptista et al., 2021 ; Crilly et al., 2004 ; Danger, 1968 , 1987 ; Déribéré, 1978 ; Favre, 1968 ; Huang & Lu, 2013 ; Kovač et al., 2019 ; Labrecque & Milne, 2012 , 2013 ; Labrecque et al., 2013 ; Merlo et al., 2018 ; Theben et al., 2020 ; Wheatley, 1973 ; see Spence & Velasco, 2018 , for a review). Consider here only Coca-Cola’s dominant use of (and association with) the colour red (and rounded white text) which has been successfully linked to the brand and, by doing so, has seemingly managed to overcome any potential language/cultural barriers (Van Den Berg-Weitzel & Van Den Laar, 2001 ). The colour red and round typeface both also convey/prime notions of sweetness (Velasco et al., 2015b ; Velasco et al., 2018a , b ; Woods et al., 2016 ). However, in certain contexts red also acts as an indicator of temperature (i.e. warmth, think about the colour on taps; Ho et al., 2014 , see Spence, 2020b , for a review) and can signal danger/prime avoidance motivation (Lunardo et al., 2021 ; cf. Labrecque & Milne, 2012 ), as well as attraction (Tham et al., 2020 ). In other words, a particular hue of product packaging may be associated with a range of attributes/qualities, and the extent to which any one of these different associations are primed may well depend on the context, or category, in which that colour is presented (Amsteus et al., 2015 ). Intriguingly, Coca-Cola’s main international competitor (Pepsi) rebranded some years ago, choosing the colour blue (Cooper, 1996 ), presumably to help distinguish itself within the cola beverage category (see also Baxter et al., 2018 , on the importance of brand colour).

For further evidence of the learning of arbitrary associations between packaging colour scheme and flavour consider only the crisps/potato chips category, mentioned earlier (Piqueras-Fiszman et al., 2012 ). That said, there appears to be some degree of consistency with which different colours are used to signal different flavour variants. For instance, Velasco et al. ( 2015a ) demonstrated that congruency (e.g. red/tomato), relative to incongruency (e.g. yellow/tomato), between the colours used in product packaging and flavour labels facilitated their participants’ visual search performance (as evidenced by reduced reaction times) for target crisp packets. Packaging colour is, then, sometimes used to signal variation within a category, whereas, at other times, it may be associated with a particular brand (and thus indirectly also with a category instead).

Occasionally, however, brands have deliberately chosen to contravene the colour code of the category. Take, for example, the use of blue packaging for cheese-and-onion flavour crisps, and green packaging for salt-and-vinegar, introduced by Walkers in the UK to try to secure exposure of customers to their new flavour variety (c. 1984; see Piqueras-Fiszman et al., 2012 ). This decision was apparently based on the notion that our shopping choices are, in large part, based on colour (see Spence & Velasco, 2018 , for a review). Other crisp manufacturers in the UK had historically tagged salt-and-vinegar with blue. So, by packaging their new flavour variant (cheese and onion) in the well-establish blue of salt and vinegar, the idea was that consumers would shop by colour and hence be inadvertently exposed to a new flavour variant. Spence and Piqueras-Fiszman ( 2012 ) highlighted the example of a white wine that was called ‘Red’ and which had a bright red label, as an ultimately unsuccessful example of incongruency. Hence, sometimes abstract visual design features such as hue are chosen after considering both their ability to differentiate the product from others in the marketplace and the specific connotative meaning of the hue. The reader is referred to Labrecque and Milne ( 2013 ) for further discussion of colour norms and the benefits of colour differentiation in the marketplace (see Spence & Velasco, 2018 ; Vermeir & Roose, 2020 , for reviews).

In addition to pink and red being associated with sweetness, Woods et al. ( 2016 ) demonstrated that white and blue were associated with saltiness, green and yellow with sourness, and black and green with bitterness. Consumers have also been shown to perceive a candy bar with a green label as being healthier than one with a red label, even when the caloric information on the labels happens to be identical (Schuldt, 2013 ). While the majority of the research that has been published to date has tended to focus on the colour of outer packaging, it is interesting to note that inner packaging colour has started to attract the attention of researchers, especially for those products such as individual yoghurt pots, where the consumer often consumes the product directly from the packaging (see van Esch et al., 2019 ; see also Krishna et al., 2017 , on the importance of distinguishing between inner and outer packaging).

Taken together, the research that has been published to date highlights the multiple meanings that may be associated with a given colour in the context of food and beverage packaging. Given that packaging colour may be associated with one of a number of attributes including flavour (Piqueras-Fiszman et al., 2012 ), variant (Cutolo, 2021 ), brand (as in the case of signature colours; Baxter et al., 2018 ), but also more generally with other attributes such as healthfulness (Mai et al., 2016 ; Schuldt, 2013 ; Tijssen et al., 2017 ; see also Cavallo & Piqueras-Fiszman, 2017 ) and luxury/cheapness (see Velasco & Spence, 2019c ; Wheatley, 1973 ; see also Hagtvedt, 2014 ; Huang & Lu, 2013 ; Spence & Velasco, 2019 , for other examples), the relevant question becomes: Which of the many possible meanings dominates in the mind of the consumer in any given situation or context? It is worth noting that a problem with much of the laboratory/online research conducted to date is that the dimension of interest to researchers has often been presented to consumers in the response scale’s anchor labels. This is obviously unlike the conditions of everyday life, where the most salient dimension of meaning might well be determined by the aisle in a supermarket, or the category that the consumer is inspecting, or perhaps by the consumer’s current thoughts/objectives/goals (see Huang & Lu, 2015 ). Indeed, it is even possible that there may be a hierarchy of associations with some being dominant over others, again possibly depending on context.

Beyond hue, it is important to note how other visual appearance properties, such as lightness/saturation (Mai et al., 2016 ) and glossiness (De Kerpel et al., 2020 ; see Spence, 2021b , for a recent review) can also convey different messages/meanings when present on product packaging. For example, light and pale colours tend to be associated with healthfulness. That being said, as Mai et al. ( 2016 ) have noted, lightness may have different meanings for different people, and the association between lightness and perceived healthiness can be moderated by other factors including the goals of the consumer. Glossiness, on the other hand, tends to be associated with greasy and/or unhealthy foods by the majority of consumers (see Spence, 2021b , for a review).

It is at around this point that one might be tempted to ask, do visual design cues, such as colour, do anything more than merely set/prime a consumer’s expectations? And here, while online research that merely assesses expectations is just so much easier to conduct (e.g. Woods et al., 2015 ), nevertheless there are a few studies showing how changes to the visual appearance of the receptacle in which a product is packaged can significantly influence not just people’s expectations, but also their experience (cf. Carvalho & Spence, 2019 ). At the same time, however, it is important to note that the power of any visual cue, such as colour, as discussed in this section, to modulate taste is dependent not only on the strength or robustness of the association between the colour and the related taste, but also the degree of discrepancy between the consumer’s expectation and their actual experience (e.g. see Schifferstein, 2001 ; Spence & Piqueras-Fiszman, 2012 , for reviews).

Shape, packaging, and crossmodal correspondences

Given what we have seen so far, it should be clear that the shape of product packaging may convey (or prime) multiple distinct meanings to the consumer. Specific packaging shapes may be associated with quality, brand, gender, healthfulness, and strength (see Hine, 1995 ; Stern, 1981 ). And, just as for the case of colour, the various different theoretical accounts all have something to say regarding the meaning(s) of shape cues in product packaging (see Table 1 ). One recent area of interest amongst researchers has been on the crossmodal correspondences between shapes and taste/flavour (Velasco et al., 2016a , 2016b ). The latest research has highlighted the fact that basic shape properties are associated with taste in a manner that can, at times, seem almost synaesthetic (Cytowic & Wood, 1982 ) though, importantly, is not (Deroy & Spence, 2013 ). Roundness, for example, tends to be associated with sweetness, whereas angularity tends to be associated with bitterness, sourness, and saltiness (Spence & Deroy, 2012 , 2013 ). Sourness is also associated with asymmetrical, rather than with symmetrical, visual designs (see Salgado-Montejo et al., 2015a ; Turoman et al., 2018 ). Given such findings, shape-taste correspondences can be incorporated into a range of design elements including everything from typeface (de Sousa et al., 2020 ; Mead et al., 2020 ; Velasco & Spence, 2019b ; Wang et al., 2020 ) to lines and shapes on/of labels (Li et al., 2022 ; Matthews et al., 2019 ), transparent windows (Simmonds et al., 2019 ), and even the distinctive image moulds of specific packaging forms or silhouettes (Meyers, 1981 ; Overbeeke & Peters, 1991 ; Spence & Piqueras-Fiszman, 2012 ; Wang & Sun, 2006 ). While certain shapes are associated with specific flavours, atypical food packaging might attract attention and increase product salience (cf. van Ooijen et al., 2016 ). However, as the latter researchers point out, atypical packaging can also have a detrimental effect on the consumer’s product evaluation. Specifically, it can enhance the processing of product information which, in turn, decreases the persuasiveness of weak (i.e. unconvincing) messaging.

It is currently unclear what the basis of shape/taste associations might be (Dichter, 1971 ; Gal et al., 2007 ; Obrist et al., 2014 ; Spence & Deroy, 2012 , 2013 ). According to one suggestion, it may simply be that pleasant shapes are linked with pleasant tastes (e.g. round with sweet) while potentially threatening stimuli (e.g. angular shapes and bitterness) may be grouped together. One can think of this as a kind of emotional mediation, or affective correspondence, account (Salgado-Montejo et al., 2015a ). However, according to Obrist et al. ( 2014 ), roundness may be associated with sweetness because of the gradual change in taste sensation that is experienced with this kind of taste stimulus. Obrist et al. demonstrated that people typically experience sweetness as building slowly, having a rounded or smoothed peak, and then decaying slowly on the palate. By contrast, sour tastes are experienced as having a much sharper temporal onset and offset. That said, the fact that many crossmodal correspondences have been incorporated conventionally in product packaging for decades, means it is hard to discount the possibility that consumers have simply internalized (perhaps unconsciously) the regularities of the marketplace.

Cross-cultural research from Bremner et al. ( 2013 ) is of relevance here. These researchers investigated the Himba tribe in Namibia. These hunter-gatherers have no written language nor access to supermarkets. Intriguingly, this group does not show the same taste-shape correspondences that have been documented elsewhere. Specifically, they exhibited no association between angularity and carbonation in sparkling (vs. still) water (cf. Spence, 2019a ). What is more, they associated milk chocolate (i.e. sweet) with angular shapes while matching dark chocolate (i.e. bitter) with round shapes—the opposite of what has been demonstrated repeatedly elsewhere. This suggests that the internalization of the visual communication conventions of the marketplace may well play an important role in explaining certain crossmodal correspondences relevant to product packaging (and/or product forms). Notice here how, should such idiosyncratic results be replicated, they would argue against Obrist et al.’s ( 2014 ) putative account of taste-shape correspondences. The various explanations (see Table 1 ) for the communicative function of shape cues should not, of course, be treated as mutually exclusive, and indeed several explanations have been shown to contribute to explaining a number of the crossmodal correspondences that have been documented in the literature to date (Spence, 2020a ).

Shape may also be associated with health, strength, or possibly even with taste properties (Parise & Spence, 2012 ). There is also a literature on branded ‘image moulds’: That is, distinctive packaging forms or silhouettes (Arboleda & Arce-Lopera, 2015 ) that may become associated with a specific brand (e.g. consider only the contour of a Coca-Cola bottle; Prince, 1994 ) and/or with a specific class of product (Söderlund et al., 2017 ), as happened some years ago with the sloped-shouldered Wishbone salad dressing bottle (see Hine, 1995 ; Meyers, 1981 ). The suggestion is that the most successful packaging forms have become image moulds in lieu of the fact that the shape features (e.g. rounded or angular) are consistent with the key brand attributes (Anon., 1994 ; Gislason et al., 2020 ; Parise & Spence, 2012 ). On occasion, semantically meaningful shapes have been incorporated in packaging design (e.g. as in the successful case of the green tea sold in Japan in a green plastic bottle that itself resembles bamboo; see Visser, 2009 , pp. 8–9).

Importantly, and just as was the case for colour (discussed earlier), given that packaging shapes are associated with a variety of different attributes, consumers may need to be primed to think about taste (gustation) before they discriminate between shapes as a function of taste. That is, consumer goals (or context) may be critical in terms of determining the communicative function of packaging shape. That said, and again, there may also be a hierarchy of values. Addressing these issues constitutes an important task for future applied packaging research. And, once again, future research might benefit from considering how Mukherjee et al.’s ( 2022 ) theory of semantic discriminability. In particular, it would be interesting to know more about the role of context, or comparison stimuli, in determining whether the concepts that are primed in the consumer’s mind by specific shape cues might not reflect inference rather than necessarily direction association.

When orientation biases meaning

The orientation of abstract visual design features (such as shapes) on product packaging also matters when it comes to communicating with the consumer. For instance, people have been shown to respond very differently to triangles as a function of whether they happen to point upwards or downwards (Zhao et al., 2017 , 2020 ). Triangles, or other angular shapes, that pointing downwards/towards the viewer can trigger a short-lasting neural fear response in the human amygdala (Larson et al., 2007 ; Watson et al., 2011 ). One explanation that has been put forward for this finding is that downward-pointing, relative to upward-pointing, triangles generate a change in visual processing that is driven by negative affective properties (Watson et al., 2011 ).

Meanwhile, lines ascending to the right have very different connotations than when the same line ascends to the left instead (see Spence et al., 2019 , for a review). The former appear to be associated with positive dynamism, whereas the latter tend to have a much less positive connotation (see Velasco et al., 2015c ). By way of example, Mead et al. ( 2020 ) reported that right-slanted fonts were effective in evoking thoughts of an advertising campaign that was moving forward (and thus that time was running out) which, in turn, influenced people’s purchasing intentions. Intriguingly, it has even been suggested that the response to oriented lines can appear almost innate (see Karim et al., 2016 ).

Notice here also how, depending on its orientation, the same curved line may look like a smile or a frown (Salgado-Montejo et al., 2015b ). Even the direction in which individual faces are looking (i.e. to the left or right) has been shown to subtly prime different expectations/associations in the mind of the consumer (Park et al., 2021 ). Specifically, leftward-facing people are deemed to be ever-so-slightly more attractive which, in turn, has been shown to promote more positive attitudes towards products.

As another example, the customers in one intriguing study were invited to evaluate the ‘house blend’ of coffee (Van Rompay et al., 2019 , based on work by Rorink, 2018 ). These authors established that horizontal vs. vertical stripes on a poster in a Dutch coffee shop influenced customers’ ratings of the coffee. Van Rompay et al. used the concept of ‘embodied cognition’ to help explain their findings. Specifically, their suggestion was that luxury and power are associated with ‘top-shelf’ and ‘looking down’ on others, respectively. These researchers reported that vertical, relative to horizontal, stripes positively influenced taste experience, quality perception, and purchase intention of coffee. The argument is that a vertically oriented advertising display may invoke perceptions of power (i.e. Machiels & Orth, 2017 ; Schubert, 2005 ; Sundar & Noseworthy, 2014 ; van Rompay et al., 2012 ). The suggestion was that this, in turn, caused the consumers to rate the coffee as having a more powerful/intense taste, relative to those in a horizontally oriented advertisement condition.

Position implicitly conveys meaning

Researchers have explored other indicators of verticality, such as the positioning of elements on product packaging. For instance, Fenko et al. ( 2018 ) assessed the impact of incorporating an image of a lion (as a metaphor for strength) on a package of coffee beans. The lion could either appear at the top or bottom of the packaging. The lion’s location was shown to influence both multisensory flavour perception and purchase intentions. When the image was situated at the bottom of the packaging, the coffee was perceived to be stronger. Fenko and her colleagues argued that this is consistent with the theory of grounded cognition, whereby a ‘strong is heavy’ metaphor is activated, with heavy objects usually located on the ground. Similarly, Togawa et al. ( 2019 ) found that an image of a food item placed lower on the product packaging enhanced both people’s expectations and perceptions of the heaviness of the product’s flavour. Interestingly, the association between position and heaviness influenced consumers’ decisions regarding healthy eating, such that they consumed less of the ‘heavy’ food and tended to choose a healthier snack option instead.

In research exploring the association between healthiness and vertical position, Wang and Basso ( 2021 ) recently demonstrated that people associate healthy food (i.e. fruit salad) with high verticality, whereas unhealthy food (i.e. ice cream) was associated with low verticality instead. These researchers suggested that conceptual metaphor theory could be used to explain their findings in that health is commonly associated with ‘up’ (being upright; sayings such as ‘She is in peak physical condition’), while illness is associated with ‘down’ (being forced to lie down in bed; ‘She felt under the weather’ or being ‘down in the dumps’). Meanwhile, in an earlier study, Deng and Kahn ( 2009 ) reported that the consumer’s goals (e.g. to be healthy) influenced their preferences for the location of objects on product packaging. Specifically, those consumers with a health goal exhibited a weakened preference for packages where the image was situated at the bottom (i.e. heavy location). While the design features whose position has been varied were semantically meaningful stimuli in the above-mentioned cases, it might be expected that similar associations would be documented were it to be the position of an abstract visual design element that was varying instead.

Elsewhere, Simmonds et al. ( 2018b ) demonstrated that the left/right position of transparent windows embedded in product packaging significantly influenced ratings of a range of product qualities (e.g. overall liking, quality, willingness to purchase) for fake brands of lemon mousse, cereal, and chocolate. Finally here, mention should be made of Salgado-Montejo et al. ( 2015b ) study highlighting how the position of a concave/convex line on the front of product packaging (top, middle, or bottom) biased the likelihood with which that design feature was interpreted as a smile. Specifically, the line was more likely to be interpreted as a smile when it appeared at the bottom, rather than the top, of product packaging, thus suggesting a degree of anthropomorphism. Note here that anthropomorphism in product/packaging design tends to increase consumer preference (Batra et al., 2016 ). Similar benefits have now been noted across a wide range of product categories (e.g. Rapaille, 2007 ; Wang & Basso, 2019 ).

Interim summary

An emerging body of scientific research has started to document the various meanings that are associated (by consumers) with specific visual cues/design features in product packaging in the food and beverage category. Colours (and saturation, lightness, and finish/glossiness) on product packaging have all been associated with various taste/flavour properties, product quality, and the healthiness of the product contained within the packaging. Stripes, be they vertical or horizontal, represent an interesting class of design feature in not having a clear connotative meaning (Albertazzi et al., 2021 ; Walker & Walker, 2012 ) established in the literature to date. In contrast to other design features mentioned so far, stripes represent an abstract visual design feature that has (to date at least) seemingly received little research attention from those interested in product packaging (see, for example, the absence of coverage in Velasco & Spence, 2019a ), despite various companies choosing to introduce stripes in their product packaging.

Combining abstract visual design features

Having reviewed the evidence concerning the meaning of individual abstract visual design cues, such as colour, shape, and orientation in product packaging, it seems worthwhile turning to the question of how various combinations of abstract visual design cues may be interpreted by the consumer. This can either be combinations of colours, as in colour pairs or triplets, or combinations of different visual features, such as the combination of colour and shape. However, given the combinatorial explosion that one is soon faced with when combining different visual design features, our focus in this section will be on the associations/meaning that may be associated with, or primed by stripes, given their neglect in the literature on crossmodal correspondences to date, together with their frequent appearance in nature and product packaging.

The use of stripes introduces combinations of visual features such as colour pairs which, in turn, might be expected to generate interesting effects such as colour contrast. The meaning of colour pairs has been well-studied but depends, to a certain degree, on the specific relation between the component parts. For example, side-by-side vs. foreground/background arrangements will need to be considered by package designers, and even which element is in the fore-/back-ground (Woods & Spence, 2016 ; Woods et al., 2016 ; cf. Deng et al., 2010 ; Schifferstein & Howell, 2015 ). Pink on a white background, for example, is more strongly associated with sweetness than (a) when either colour is presented in isolation, (b) when white is presented against a pink background, or (c) when these colours are presented side-by-side instead.

There is a longstanding, separate literature on colour-shape correspondences (e.g. Dreklser & Spence, 2019 ). The research has demonstrated that combinations of colour and form sometimes take on specific symbolic (i.e. the image/association that comes to mind with respect to a product; Kujala & Nurkka, 2012 ) and/or affective (i.e. the emotion elicited by a stimulus) meaning (Ares & Deliza, 2010 ; Kaeppler, 2018 ; Oyama, 2003 ; Spence, 2021c ). One might question whether cues are combined based on similar connotative meanings, as assessed by approaches such as the semantic differential technique (Osgood et al., 1957 ; Snider & Osgood, 1969 ; cf. Henson et al., 2006 ; Kawachi et al., 2011 ; Morich, 1981 ; Oyama et al., 1998 ; Schaefer & Rotte, 2010 ; Suzuki et al., 2005 ). Consider, for example, how red and highly angular shapes often co-occur (e.g. on the front of beer cans; Spence, 2012 ). This constellation of abstract visual design features may go particularly well together because, when presented individually, both stimuli are associated with activity and dominance (rather than with passivity and submissiveness) according to semantic differential analysis (Adams & Osgood, 1973 ).

Ensuring the congruency Footnote 6 of different visual design elements has been suggested to be an important part of successful design (Fürst et al., 2021 ; Heatherly et al., 2019 ; Matthews et al., 2019 ; Salgado-Montejo et al., 2014 ), processing fluency, Footnote 7 and effective visual search (Velasco et al., 2015a ). From a marketing perspective, the wrong combination of design features can exert a drastic negative impact on brand perception and, importantly, sales. Tom et al. ( 1987 ) provide an example where a Swiss coffee brand redesigned their packaging. Although the new packaging won awards for design, sales plummeted. The problem appeared to be that diagonal stripes of mauve were simply not deemed congruent with the conventions of the category (i.e. coffee packaging) by the consumer. Favre and November ( 1979 ) provided several other historic examples of unsuccessful packaging colour rebrands. Hence, having established the connotative meaning of specific visual design features as a function of their position/orientation, manufacturers have a choice to either follow the conventions of the category or go for something different. However, only some brands seem able to carry-off incongruent signalling in the marketplace (cf. Sundar & Noseworthy, 2016 ), especially given the disruption to processing fluency that such incongruency is likely to elicit (Lunardo & Livat, 2016 ; cf. Herrmann et al., 2013 ; Labroo et al., 2008 ). Wheatley ( 1973 ) gives the example of the hugely successful Alpen muesli that came out with matte black packaging for their muesli in the 1970s in a mostly white and sunny yellow coloured product category (i.e. breakfast cereal). More recently, several fabric conditioner brands have similarly attempted to disrupt the colour conventions of the laundry category by again coming out with black packaging in a mostly white and blue packaging colour category. It is interesting to consider here how the desire to stand out on the shelf, and so capture the customer’s visual attention more effectively (see Reutskaja et al., 2011 ; Spence & Piqueras-Fiszman, 2012 ), often leads to the colour (and other visual design) conventions of the category being overturned. This strategy has been used very effectively in recent years in the drinks category, by those such as Gatorade, and more recently, Innocent (the latter with their Bolt from the Blue product launch; see Spence, 2021d ).

Certain combinations of shapes and colours may take on symbolic or semantic associations. Think, for example, of how a red circle or plus sign on a field of white may prime notions of the Japanese flag and the Red Cross, respectively (Chen et al., 2021 ). One might also consider the semantic meaning of the iconic Lucky Strike cigarette packaging showing a red circle against a white background (designed by Raymond Loewy). Furthermore, people typically associate yellow with a crescent shape, presumably because they are reminded of the moon (Dreksler & Spence, 2019 ; Woods et al., 2013 ). It is worth noting that combinations of colours in stripes can be associated with a particular (semantic) meaning which is, at times, dependent on the orientation of the stripes (see below).

Recent commercial examples: on the use and orientation of coloured stripes on product packaging

Given Kentucky Fried Chicken’s (KFC’s) recent decision to update the design of their food product packaging (Anon., 2021 ) and stores (Valinsky, 2020 ) to emphasize their signature vertical red-and-white stripes, we have chosen to use them as a recent commercial example regarding the use of stripes in product branding and how these design elements contribute to perception. Similarly, Devondale—a company offering a range of dairy products—updated their packaging back in 2012 such that it included horizontal light blue-and-white stripes (Hicks, 2012 ). The branding on this iconic Australian range of dairy products is reminiscent of the famous ‘Cornishware’ style of English kitchen pottery. Of relevance, given Devondale’s use of blue-and-white stripes, and the fact that the company has ties to dairy farming, this design may also be intended to evoke thoughts of farms, cottages, and cows (see also Rodionova, 2016 , for supermarkets attempting to create associations by using fake farm names).

Note here how the semantic/affective associations with horizontal light blue-and-white stripes cannot simply be predicted based on the consumer’s response to the individual abstract visual design cues (Spence et al., 2015a , b ). One might consider whether the blue caps on traditional milk bottles could also provide a basis for the use of this combination of colours (i.e. blue cap plus white milk). Abstract patches of blue and white, when presented together, are associated with a salty taste (Woods & Spence, 2016 ; Woods et al., 2016 ). It is, though, worth noting that the participants in Woods and colleagues’ online research were primed to think in terms of the associations between colour pairs and basic tastes, given that they were forced to choose between the basic tastes when responding (cf. Mukherjee et al., 2022 ). Thus, even though the combination of blue and white may be more strongly associated with salty than with other tastes, that does not preclude the possibility that the consumer might be primed to think of milk/dairy more than they are to think of salt on seeing this combination of colours.

Similarly, a particular shade of purple, red, or turquoise might well be expected to prime associations with the branded colours of Cadbury’s chocolate, Coca-Cola, and Tiffany jewellery, respectively, more than with specific taste qualities (see Baxter et al., 2018 ). It would be helpful if future research, in which the associations primed in consumers by viewing specific combinations of colours, were not constrained by a forced-choice design (e.g. as in the open responding required in the Word Association task, for example; Piqueras-Fiszman et al., 2013 ). At the same time, given the multitude of responses that might ensue, it would perhaps help to give the consumer a particular context (e.g. ‘What comes to mind if you saw this particular combination of colours in the refrigerated section of a supermarket?’). A third example of the use of coloured stripes in product packing relates to the LGBTQI + movement and the incorporation of rainbow stripes into product design (e.g. Ralph Lauren t-shirts, ADIDAS shoes; see Yates, 2021, for a number of other examples). By way of example, the incorporation of the LGBTQI + flag, which combines five colours, into product design may have implications for the connotative meaning and brand perception beyond the associations primed by colours.

In relation to KFC and Devondale, products in warm-coloured packaging (e.g. red) are deemed to be less healthy than are those presented in packages using cooler colours (e.g. blue; see Singh, 2006 ; Van Rompay et al., 2016 ). Woods et al. ( 2016 ) demonstrated that colour pairs communicate basic tastes and found that, for example, the pairing of white and red was associated with saltiness. This is interesting considering KFC’s recent rebrand where the red-and-white stripes were made more vibrant. Woods et al. also reported that the combination of white and blue better portrayed saltiness than when using either colour alone; previous research had shown that each colour was associated with saltiness (Favre & November, 1979 ; Spence et al., 2015b ; cf. Velasco et al., 2016a , 2016b ). It might seem odd then that Devondale should choose to use this pairing on dairy products as, although butter is often salted (but can also be unsalted), a company might want to avoid generating an expectation of salty milk. Perhaps the hope is to generate mental imagery associated with Cornishware in those who happen to be familiar with this famous traditional style of pottery from the UK, and that this will override the blue-white/saltiness correspondence (at least in those who are familiar with Cornishware).

A separate literature has explored the perceptual differences generated by lines as a function of whether they are shown horizontally vs. vertically (Avery & Day, 1969 ). People tend to perceive horizontal lines as being shorter than lines of equivalent length presented vertically. Such visual illusions have implications for the form (or orientation) of product packaging in that consumers perceive short, wide packages to hold less volume than tall, slender packages (see Chen & Shi, 2017 ; see also Raghubir & Greenleaf, 2006 ); Raghubir & Krishna, 1999 ; cf. Cheskin, 1951 , pp. 193–194). Think, here, only of Piaget’s conservation task (Piaget, 1952 ). To add another layer of complexity to this issue, the ‘Helmholtz Square’ illusion shows that a square comprised of vertical stripes appears to be shorter and wider than an identical square comprising horizontal stripes (Coren & Girgus, 1978 ; Seriously Science, 2014 ; Thompson & Mikellidou, 2009 ). In all the above cases, while the shape itself does not change, simply altering the orientation leads to a predictable change in visual perception. Interestingly, this may be of benefit to Devondale in their marketing of butter which is presented in rectangular containers. Although speculative, the Devondale container with its horizontal stripes might make the container look taller, thus creating an illusion such that people unconsciously believe they are getting more for their money.

Thus, the orientation of visual design elements on product packaging, and even the position of packaging on shelving (see Sunaga et al., 2016 , on the lightness-elevation correspondence that can be used to guide shelf positioning), influences perception by priming those attributes that happen to be linked to specific visual design features. Hence, KFC which achieved success via the introduction of vertical red-and-white stripes (see Anon., 2021 ), and Devondale who use horizontal blue-and-white stripes on their brand packaging, may succeed independently of one another due to the influence of several, independent factors helping to determine/constitute the meaning of coloured stripes.

Assessing the effectiveness of stripes in product packaging

Evolutionary theory provides a possible, if highly speculative, explanatory framework for the success/appeal of stripes in the marketing of products in the food and beverage category (see above for the evolutionary account of several other visual design features). Although it is beyond the scope of this narrative review to comprehensively list all of the hypotheses relating to communicating signals, we outline a few particularly relevant ones below. The first thing to point out is that repetitious patterns (e.g. stripes) are common in nature—think of the zebra, zebra fish, or tiger snake, as examples (Coborn, 1991 ; Lieske & Myers, 1994 ). Repetitive patterns may have evolved in nature to stimulate ‘the receiver regardless of the position of the signal’ (Kenward et al., 2004 , p. 412) on the retina. At the same time, however, the incorporation of stripes may serve somewhat different functions in different species. The zebra’s distinctive stripes, for example, help to deter flies from biting them (see How et al., 2020 ), while tigers might have stripes to hide/for camouflage, and bees perhaps to warn off other creatures (though see Stelzer et al., 2010 , for evidence questioning the latter suggestion). In other words, the effect of stripes might rely on the qualities of the stripes, the combination of colours used, and the ecological niche inhabited by the animal.

In much the same way, it has been suggested that the presence of stripes might be used for camouflage or capture attention, colour is important both as an aid to foraging (Foroni et al., 2016 )—though researchers argue about whether it developed to facilitate frugivory or folivory (e.g. Sumner & Mollon, 2003 )—as well as a potential signal for mating/conspecific communication (e.g. Changizi et al., 2006 ; see also Humphrey, 1976 , on the complex evolutionary meanings associated with colour). Hence, evolutionary accounts are currently both limited in the range of visual design cues that they can potentially provide an explanation for, and are often open to other interpretations (both evolutionary and otherwise), meaning that they are of only limited explanatory validity in decoding the visual aspects of packaging design.

Repetitive patterns such as stripes may be used in marketing because images created on the retina can vary in orientation as well as in position. Think, for example, of a shopper in a supermarket moving past a product from right-to-left, and then from left-to-right. This creates image sequences that are mirror reflections of each other. Stripes will be invariant when reflected (i.e. symmetrical), so the use of stripes may contribute to enhanced processing fluency (cf. Bigoin-Gagnan & Lacoste-Badie, 2018 ). Manufacturers of sour products may want to avoid the use of stripes though, given that sourness tends to be associated with visual designs that are asymmetrical (Salgado-Montejo et al., 2015a ; Turoman et al., 2018 ). Remember here how a lack of congruency between visual design elements and expected taste attributes can negatively impact product attitudes (see Ares & Deliza, 2010 ). At the same time, however, it is worth noting that symmetry is processed fluently, and hence tends to be preferred visually (Pecchinenda et al., 2014 ).

One of the problems with products on supermarket shelves is the need to stand out when parts of the packaging may be obscured. Importantly, repetitive patterns such as stripes may be useful because they look similar even when parts of the product (or animal in nature) are obscured and, as such, will still be recognizable to an onlooker (Kenward et al., 2004 ). An important physiological process explaining the usefulness of stripes might be lateral inhibition. Lateral inhibition is defined as ‘the capacity of excited neurons to reduce the activity of their neighbours’ (Cohen, 2011 , p. 1437). Lateral inhibition helps to enhance edges, and ‘makes it easier to distinguish objects from backgrounds under varying light conditions’ (Kenward et al., 2004 , p. 415). As such, stripes have a greater apparent maximum intensity than do solid blocks of colour, and thus they tend to ‘pop out’. As brands have very limited time to attract the attention of potential buyers (Reutskaja et al., 2011 ; Sugermeyer, 2021 ), stripes might work well amongst the myriad products and advertising clutter on shelves. At a psychological level, one might also choose to invoke Gestalt theory to help describe the factors affecting the grouping of elements, such as lines, in product packaging (Ellis, 1938 ; Wagemans, 2015 ). Grouping principles such as grouping-by-similarity, grouping-by-proximity, and good continuation may sometimes also help to predict/explain why visual design features, such as stripes, are grouped in certain ways.

Finally, it is worth noting that stripes may also have other semantic associations, that have been built up through experience, and which may help to explain their meaning to consumers (i.e. independent of any specific evolutionary account). Consumers might, for instance, be primed by the sight of black and white stripes to think of prison uniforms, or perhaps a fashion icon such as Coco Chanel, or a sports team (e.g. Juventus). There are, in other words, likely always going to be a range of explanations behind the ‘meaning(s)’, or associations, that happen to be primed by any given visual design feature. It is important to note that the various explanations should not be treated as mutually exclusive, and indeed several explanations have recently been shown to contribute to explaining many of the crossmodal correspondences that have been documented in the literature (Spence, 2020a ).

The research reported in this section highlight how the meaning attributed by consumers to the combination of different abstract visual cues, such as colour pairs or colour and shape, typically cannot simply be predicted simply on the basis of the consumers’ response to the individual visual cues when assessed in isolation. Sometimes, for example, specific combinations of visual design cues may deliver a configuration that takes on a meaning of its own, as with the thick horizontal blue and white stripes that may be associated with Cornishware pottery, while the individual colours are likely to be associated with a salty taste (see Spence et al., 2015a , b ). By contrast, the red and white vertical stripes of KFC packaging might be expected to cue saltiness and power, possibly enhancing the taste of the product (cf. Fenko et al., 2016 ). One of the important areas for future research on the visual design of product packaging is therefore to understand more about the meaning to consumers of various combinations of abstract visual design cues (e.g. such as the combination involved in coloured stripes).

Conclusions and future directions

The majority of the research on the visual design of product packaging has addressed individual visual design features. However, while this is undoubtedly a fruitful first step, it is crucial to note that any realistic example of food or beverage packaging will inevitably incorporate several visual design elements (see Favre & November, 1979 ; Hine, 1995 ; Visser, 2009 ). Hence, the question immediately becomes one of whether it is possible to predict the consumer’s response to the combination based simply on how they respond to individual abstract visual cues, such as colour or shape/form (Labrecque et al., 2013 ). The limited evidence that has been published to date certainly suggests that while abstract visual design elements that are congruent in terms of their connotative meaning, and/or that are linked by their crossmodal correspondence, are sometimes combined, there are other situations in which a specific configuration of visual design cues takes on a semantic meaning that goes beyond the meaning of the individual cues (Dreksler & Spence, 2019 ; Matthews et al., 2019 ; Spence, 2020a ; Zhao et al., 2020 ; and see Velasco et al., 2014a , for a review). It should, of course, further be remembered that visual design cues are but one element of multisensory packaging design.

Furthermore, although several studies have shown that individual visual design features (e.g. colours) have similar meanings across cultures (Adams & Osgood, 1973 ; Wheatley, 1973 ), some of the meanings (or codes) of packaging would appear to be market specific (Velasco et al., 2014b ). This is obviously an important area for future research as far as international brands are concerned. However, returning to a point we made a moment ago, there is currently very limited evidence assessing whether combinations of features influence consumers from different cultures in similar ways (see Van Doorn et al., 2017 , for one example relating to the influence of the height and width of coffee cups). One intriguing recent approach to establishing the affective or connotative colour associations has been based on machine learning (e.g. Jahanian et al., 2017 ; Jonauskaite et al., 2019b ; see also Schloss et al., 2019 ).

At times, of course, design features are incorporated to make products stand out, and thus facilitate visual search for product packaging (e.g. Jansson, Marlow, & Bristow, 2004 ; Shen et al., 2015 ; Velasco et al., 2015a ; Zhao et al., 2017 ). Importantly, this can help to facilitate information processing (van Ooijen et al., 2016 ) but, depending on how design features are integrated, also has the potential to negatively impact product evaluations (Spence & Piqueras-Fiszman, 2012 ; Sundar & Noseworthy, 2016 ). There is also a growing awareness that certain visual designs that have been shown to work well in the setting of physical bricks and mortar store may need to be modified/simplified to maximize their appeal for the online shopping setting (Reinoso-Carvalho et al., 2021 ).

As our understanding of the meaning, or connotation, of visual design elements of product packaging in the food and beverage category continues to grow, based on the theory of crossmodal correspondences, there is an opportunity to predictively develop packaging that has been optimized to combine visual features such as colour, shape, orientation, and position in order to convey the appropriate meaning (Jacquot et al., 2016 ; Velasco et al., 2014a ; see Spence, 2020a , for a review) and/or capture the consumer’s attention. On occasion, visual design elements may be combined in an attempt to capture the consumer’s attention (see Piqueras-Fiszman et al., 2012 ) but, given the likely loss of processing fluency (Labroo et al., 2008 ; cf. Dohle & Siegrist, 2014 ), this technique should be used cautiously. Of course, any change in product/packaging design may lead to success simply because it is novel and/or captures the shopper’s visual attention (as in the case of the Bolt from the Blue from Innocent Drinks; Spence, 2021d ). However, altering iconic visual designs can all-too-easily lead to a backlash from consumers that can adversely affect sales. PepsiCo discovered this some years ago when they changed their iconic ‘straw in a juicy orange’ design on their Tropicana packaging (Airey, 2010 ; Marion, 2015 ; see also Favre & November, 1979 ). Footnote 8

As highlighted by this review, the scientific approach to visual design of food and beverage product packaging is rapidly contributing knowledge in this field, and helping product designers/marketers to significantly increase sales (Sugermeyer, 2021 ). The emerging understanding of the connotative meaning/crossmodal correspondences that are associated with specific abstract visual design cues, such as colour, shape, orientation, and position means that it is increasingly possible to predictively prime certain attributes. At the same time, however, most product packaging incorporates a variety of design elements, and their meaning, in combination, is not always easy to predict from elements studied in isolation. There is, therefore, a danger of combinatorial explosion should one try to map out the meaning of a wide array of combinations of design features. At the same time, as should have become apparent from the above discussion, researchers and practitioners still remain a long way from developing a commonly agreed account of visual design. Perhaps, though, this should not come as any surprise, given the variety of signs and contexts evoked by the visual design of food and beverage, or for that matter, any other category, of packaging.

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Synaesthesia refers to the phenomenon whereby stimulating one sense (or sensory dimension) leads to automatic, involuntary, and idiosyncratic perceptual experiences in a second sense, or sensory dimension (cf. Oyama et al., 1998 ).

Note that these terms are used scientifically, as opposed to colloquially, usage. As such taste is used to refer to one of the gustatorily determined basic tastes (e.g. sweet, sour, bitter, salty, sour, and umami), whereas flavour refers to the combined experience of taste and smell as in the experience of citrus, fruity, floral, or herbal notes (see Spence et al., 2015a , b ).

Abstract visual design features/properties in packaging design include any simple feature (such as a colour, shape, and visual texture) that does not have an obvious semantic meaning. Note that while signature hues associated with brands might well be said to represent a simple design feature that has become imbued with semantic meaning (i.e. whatever the consumer associates with the brand, e.g. Baxter et al., 2018 ), such individual hues, along with other specific colours, will be treated as abstract visual design features here.

According to Lafontaine et al. ( 2020 , p. 244): ‘Associative learning is defined as learning about the relationship between two separate stimuli, where the stimuli might range from concrete objects and events to abstract concepts, such as time, location, context, or categories’.

Here, already, one might start to wonder whether inferred colour-concept relations (see Tham et al., 2020 ) are as effective in terms of consumer perception/behaviour as the inferred mappings that are presumably often picked-up by the research (see Spence & Levitan, 2022 ).

While congruency is a challenging notion to define, it is generally taken to refer to combinations of features or attributes that are perceived as ‘going well together’, possibly because the elements commonly co-occur, or because they share perceptual affinity/similarity (Amsellem & Ohla, 2016 ; though see Schifferstein & Verlegh, 1996 ).

The widely used notion of ‘processing fluency’ refers to the ease with which a given stimulus configuration can be processed. Processing fluency tends to be higher for those stimuli that are familiar, easy to process, and where the component stimuli are congruent. Processing fluency is positively valenced (Lunardo & Livat, 2016 ; cf. Labroo et al., 2008 ).

One might consider this slightly ironic given that Tropicana source their oranges from Florida where, traditionally, most oranges were the green-skinned variety (see Hisano, 2019 ).

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Acknowledgements

Significance statement.

The visual attributes of product packaging play a key role in terms of communicating with the consumer, not to mention capturing their attention while the packaging is displayed on the shelf or online. Both semantically meaningful and abstract visual design elements combine to convey meaning/prime associations in the mind of the consumer. While traditionally, decisions about visual design were often made intuitively or on the basis of focus groups or in-depth interviews, there has been a recent growth of scientific interest in understanding the way(s) in which various abstract design elements communicate with the consumer. This narrative review summarizes the various theoretical accounts that have been put forward to help explain the meaning of colour, shape, texture, and stripes in product packaging, including accounts in terms of crossmodal correspondences, connotative meaning, symbolic meaning, semantic meaning, and evolutionary accounts. While the primary focus of this review is on using abstract visual design features to communicate taste properties, the signalling of other attributes such as variant, brand, quality, natural/healthy, and price is also discussed where relevant. Several directions for future research that should help determine the likely meaning abstract visual design cues when used in combination are also outlined.

Completion of this review was supported by AHRC ‘Rethinking the Senses’ Grant AH/L007053/1.

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The Impact of Food Service Attributes on Customer Satisfaction in a Rural University Campus Environment

Mireille serhan.

1 University of Balamand, Faculty of Health Sciences, Department of Nutritional Sciences, Deir El Balamand, P.O. Box 100, Tripoli, Lebanon

Carole Serhan

2 University of Balamand, Issam Fares Faculty of Technology, Department of Business Management and Administration, Deir El Balamand, P.O. Box 100, Tripoli, Lebanon

Associated Data

The data used to support the findings of this study are included within the article.

The purpose of this study was to determine different food service attributes that have an impact on customers' overall satisfaction at a rural university cafeteria. Over 5 weeks, 676 cafeteria users, including academics, staff, and students, were selected through convenience sampling. They completed an anonymous-designed survey with closed questions ( n = 29) assessing quality of food and beverages, quality of service and setting, and satisfaction with food service attributes. In order to measure the existence and degree of significant relationships between different research variables, Pearson correlation coefficients were employed to analyse the data. Means of scores and frequencies were calculated. Results indicated that customers' satisfaction with different service attributes was above average. All service attributes had a significant and positive effect on the overall satisfaction. Since most customers (62.9%) would like to continue eating at the cafeteria, the most common improvements suggested to the university management included among others, improving diet quality by offering more nutritious food. Gaining insight into the different food service attributes can enable the university management to meet the needs and expectations of its academics, staff, and students in order to increase their confidence in the food provided.

1. Introduction

Cafeteria food services can be found in hospital facilities, nursing homes, child and senior care centers, prisons, schools, and university campuses. The quality of food service is one of the most relevant items of quality perceived by customers. In health care, the satisfaction of patients is ultimately related to the provided service quality [ 1 ]. In hotel restaurants, the quality of physical environment, service, and food affects guests' satisfaction and intention [ 2 ]. In the higher education milieu, more than ever, food service attributes have become an essential component affecting the quality of campus life [ 3 , 4 ].

The majority of existing research on university food service has focused either on students' satisfaction with products, services, and service environments [ 3 , 5 – 8 ] or on the nutritional intake of students consuming on campus food and their health implications [ 9 – 11 ].

Moreover, the higher education market has become competitive and global [ 12 ]. In this dynamic context, university food service operators have to adapt to changing expectations of their customers, increased competition from fast food segments on and off campus [ 13 ], and economic trends in uncertain markets [ 14 ]. According to Lugosi [ 15 ], when customers' expectations are high, the campus food services are expected to be more responsive. The workplace is a captive environment where the overall satisfaction of consumers could be an important element of the overall eating experience on campus [ 16 ].

Therefore, building on previous research, the evaluation of university food services became essential. No previously published data investigated the quality of food service in Lebanese universities and its effect on customers' satisfaction, leaving a gap in the body of knowledge of costumers' opinions and behaviours of the on-campus food service in Lebanon. This study is aimed at addressing this issue through five main objectives: assess current opinion and explore the determinants of quality of food and beverages (1), service (2), setting (3), price and value (4), and the overall satisfaction of costumers (5) as presented in Figure 1 . The study is also aimed at identifying future avenues for good practice that may inform facilities and service development decisions on what changes they would like to see to improve the on-campus food experience as part of constructive interventions.

Food service attributes and customer satisfaction.

2. Literature Review

2.1. customers' satisfaction in higher education.

By reviewing the existing literature on customers' satisfaction, there are a large number of studies on customer's satisfaction in the private or public business sector. In the context of higher education, few studies on customer's satisfaction have been conducted [ 17 – 19 ]. According to Navarro and Iglesias [ 20 ], numerous attempts have been made by researchers to define the concept of satisfaction in relation to services offered in higher education [ 21 – 23 ]. They acknowledge that satisfaction is the final state of psychological process. Amelia and Garg [ 24 ] stated that the first impression is the one of the main considerations along with the quality and correctness of the served food and the gentleness of the staff in service. In university cafeterias, students make up the majority as users' satisfaction of institutional food services; thus, campus food service is becoming popular and important [ 3 , 18 , 19 , 22 ]. Kwun [ 4 ] has taken into consideration the gender difference while studying the effect of campus food service attributes on perceived value, satisfaction, and consumer attitudes. According to Garg and Kumar [ 17 ], the dining experience has influenced the satisfaction and loyalty of both students and staff customers. In university cafeteria, customer satisfaction is totally related to the served food and beverage quality, variety and choices, to hygiene and cleanliness, and to price and value fairness [ 21 , 25 ]. Based on the aforementioned attributes, there were many factors found to influence customers when choosing a food service.

2.2. Attribute 1: Quality of Food and Beverage

Previous studies indicated the degree of satisfaction with university cafeteria depends mostly on food and beverage quality [ 22 , 26 – 28 ]. Food quality is the quality characteristics of food that is acceptable to customer [ 22 ]. Overall quality of the food and beverage, the taste, the freshness, the nutritious aspect, and the portion size is categorized under food quality measurement. As a core product of a food service operation, food and beverage quality has been given a great importance and has been checked for many aspects such as temperature, texture, flavour, and aroma [ 26 – 29 ]. Food and beverage quality is considered to affect the customers' intentions to come back again to a specific restaurant. Oh [ 23 ] found a high positive relationship between consumer satisfaction with food and beverage quality and their intention to continue eating in a specific restaurant. Furthermore, workplace eating is frequently associated with poor quality and bad food choices which have negative consequences [ 30 ]. Tam et al. [ 25 ] have stated various aspects for encouraging customers to eat healthy. Institutions have a responsibility to provide an environment that makes it easier for students to make healthier food easier. Previous research indicates that many institutions food environments are filled with energy-dense nutrient-poor food that may be heavily promoted [ 31 , 32 ]. Moreover, it is the operators' role to provide a variety of products in their menus that will give its customers more options to choose from. The menu is definitely one of the key indicators of restaurants' marketing plans [ 33 ]. Accordingly, the following research hypothesis is thus posited:

2.2.1. Hypothesis 1

Quality of food and beverage offered at university cafeteria has a significant and positive effect on customers' overall satisfaction.

2.3. Attribute 2: Quality of Service

Service quality is considered a key element in the restaurant sector, bearing in mind that dining in restaurants is essentially a social event [ 34 , 35 ].

In some studies, it was found that service quality was more important than food quality in dining satisfaction. Yuksel and Yusel [ 36 ] suggested that service quality has significant effect on dining satisfaction at an aggregate market level and particularly for adventurous or healthy food seekers.

Furthermore, the quality of the service has been nowadays measured with respect to the customers' expectations and insights towards the offered service [ 37 ]. As per Inkumsah [ 38 ], it was found that customer satisfaction is affected by the quality of offered food service. In the same context, Garg [ 39 ] stated that food service has an impact on customers' perceptions towards a restaurant. Küçükaltan [ 40 ] declared that different customers can judge differently the same food service, and this is mainly related to the customers' opinions regarding the food service provided. If the offered service does not meet or is less than the customers' expectations, then the perceived service quality will be low; if it does exceed the customers' expectations, then the perceived service quality will be high [ 41 ]. Abo-Baker [ 42 ] described service quality as the organization's ability to satisfy the customers, within the determination of specifications, characteristics, and requirements of service that gratify the desires and needs of customers and exceed their expectations.

In the higher education milieu, according to Kim et al. [ 27 ], students' expectations and perceptions regarding the quality of service vary from one student to another and from one semester to the next. Hence, this variation leads to a more complex, diverse, and dynamic business environment, a difficulty in measuring service quality, and a difficulty in identifying the determinants of service quality. Tan et al. [ 43 ] specified that this intangible element is one of the vital components in service quality. Because services are intangible, it is difficult to measure them. Moreover, the employees especially in service quality play a vital role in the success of food service outlets. The personality traits and the use of social networking affect job satisfaction among workers [ 44 ].

Employees' behaviour affects customers' perceptions of service quality [ 45 ]. The interaction between cafeteria staff and customers, such as friendly gestures, e.g., greetings and high levels of responsiveness, cleanliness, and quick service, is important as it influences satisfaction with the service quality [ 46 ]. It is worth mentioning that service operators should enhance the quality of service provided on-campus to discourage students from searching for alternative food service operations off-campus. Students are not limited to on-campus food service quality, as they are aware of surrounding food service quality.

Many instruments were developed and refined by researchers for measuring perceived quality of service in the literature.

SERVQUAL is a known instrument which was implemented by Zeithaml et al. [ 47 ]. It consists of five service dimensions which are tangibles (physical facilities, equipment, and appearance of personnel), responsiveness, reliability, assurance, and empathy.

LODGSERV is another instrument, which was developed to assess service quality in hotels and function halls [ 45 ]. Additionally, Stevens et al. [ 48 ] adopted and refined the DINSERV scale from SERVQUAL and LODGSERV to assess customers' perceptions of restaurant quality. The DINSERV scale comprises 29 statements in five dimensions of the SERVQUAL scale. It is frequently used as a valid measurement tool to evaluate service quality in different hospitality establishments and mainly food service operations which is the case of the current study. Kim et al. [ 27 ] have investigated the relative importance of institutional DINESERV factors on customer satisfaction, return intention, and word-of-mouth in the university dining facility. Recently, service quality is influenced by the utilization of information technology, with reference to the signaling theory [ 49 ]. Accordingly, the following research hypothesis is thus posited:

2.3.1. Hypothesis 2

Quality of service offered at university cafeteria has a significant and positive effect on customers' overall satisfaction.

2.4. Attribute 3: Quality of Setting

According to Kwun [ 4 ], the setting of the campus food service sampled is often referred to its environment and operational facets. The expectations and insights of customers differ based on where they consume. It is noteworthy to mention that the setting has been considered as a further dimension that has an impact on customers' insights towards campuses' food service. Several studies show that cleanliness, dining room environment, comfort level, operating hours and days, atmosphere, and capacity had significant effects on satisfactions and revisit intentions [ 26 , 27 , 50 ].

In a study conducted by Cardello et al. [ 51 ], home and traditional full service restaurants ranked higher than institutional food service, while airline and hospital food service ranked lower than school food service, with reference to the expected acceptability of quality of food.

Hence, prior research by Story et al. [ 52 ] found that food packaging, plate size and design, lighting, and dining companions at the cafeteria influences the individual's immediate setting.

The atmosphere is an intangible component made up of everything related to the brand that will yield an impression towards the specific location. The setting components can also include the seating's organization, the various decorations, and the music ambient [ 28 ]. Various scholars [ 53 – 55 ] identified a relationship among food information and quality, eating behaviours, seating's organization, and food distribution environment. Accordingly, the following research hypothesis is thus posited:

2.4.1. Hypothesis 3

Quality of setting has a significant and positive effect on customers' overall satisfaction with the university cafeteria.

2.5. Attribute 4: Price and Value

In campus food service, it is noteworthy that students have restricted financial resources that influence their choices and decisions of picking food service operations, as they continually seek reasonable prices, due to limited budget [ 56 ]. Similarly, Nadzirah et al. [ 57 ] found that cost is the primary factor in university food service operations since students have limited funds. According to Nadzirah et al. [ 57 ], food service operators should ameliorate their menus through reconsidering their prices and thus ensuring customers are using the university cafeteria and not any off-campus food service operators. Soriano [ 58 ] found that the customers' quality expectations depend on the price they pay for receiving the service and when this price increases the quality expectations will increase consequently. In the same study, they showed that the price of a meal is equally important to other satisfaction determinants.

Several studies have been carried out by many researchers on price fairness or price and value. Price fairness means the judgment of whether an outcome or the process to reach an outcome is reasonable or acceptable [ 59 ]. In the same vein, the price to be paid for a service determines the level of quality to be demanded [ 58 ]. He also stressed that the price (value) of the meal and service are equally important when compared to other service dimensions. Ng [ 21 ] and Xi and Shuai [ 26 ] did consider price and value in assessing students' service quality in dining hall services. Martin-Consuegra et al. [ 60 ] found that perceived price fairness positively influences customer satisfaction. The effect of food quality, price fairness, staff performance, and ambience on students' satisfaction of cafeteria food services by comparing responses from two universities (MBU) was analysed using the partial least squares (PLS) application in Smart PLS computer software [ 61 ].

Similarly, Klassen et al. [ 50 ] found that price is the most significant factor in choosing a food and beverage service provider for students with limited budgets. In another study, customers indicated that receiving the right value for the money paid is among the most important factors that encourage them to revisit a food service establishment again [ 36 ]. Accordingly, the following hypothesis is posited:

2.5.1. Hypothesis 4

Price and value have a significant and positive effect on customers' overall satisfaction with the university cafeteria.

3. Methodology

3.1. research approach and sampling method.

The main aim of this study is to determine cafeteria customers' satisfaction and perceptions of quality of food and beverages and services offered at the university cafeteria. Therefore, in order to empirically test the suggested aforementioned hypotheses in this study, a quantitative research approach, based on the distribution of personally administered questionnaires, was the applied method, allowing respondents to have more time to complete the questionnaire and making it easier and more convenient for them to respond. It involves the collection of customer-based data, which can be analysed statistically [ 62 ]. The target population of this research study included all academics, staff, and students at a rural university in Lebanon. According to official data pertaining to the university for academic year 2018-2019, there are more than 6,000 academics, staff, and students. Due to this large number, it is difficult to use random sampling techniques. Therefore, a convenience sampling technique is the most suitable sampling technique to use in this research.

With reference to the new management body of the university, it is working effectively through different approaches to improve student retention. These approaches include identifying and prioritizing the main reasons for student recruitment and corresponding retention solutions. The new management body of the university has taken the initiative to involve students in the decision-making process about food services, as well as in many other academic/service areas. The management body requested that there should be a process by which the university cafeteria operator will be continuously evaluated; students and other customers will have an input in evaluating the food services on campus. The new management body of the university will monitor the improvement actions for the coming years to measure their efficiency based on student feedback and to identify areas warranting further improvement attention.

3.2. Survey Development

The questionnaire in the current study was adopted from a previously validated tool used by El-Said and Fathy [ 3 ], with modifications. In comparison with El-Said and Fathy [ 3 ], the sample includes more categories (academics and staff), in order to provide more representative results and to improve sample generalizability. It comprised two sections. The first section is aimed at collecting demographic data of cafeteria customers and their behaviour characteristics (academic, staff, student, gender, and age; number of visits to the cafeteria, monthly expenditure, and intention to continue eating at the cafeteria). The second section of the questionnaire consisted of four parts. Statements in these parts were adapted from the DINESERV questionnaire. DINESERV is adapted from the SERVQUAL instrument and was created by Barsky [ 46 ] and designed for the food service industry. The first part of the second section consisted of eight statements and aimed at measuring customers' perceptions of quality of food and beverages offered at the cafeteria. Part two of the second section consisted of 4 statements and aimed at measuring customers' service quality perceptions in the cafeteria. Part three of the second section consisted of 5 statements and aimed at measuring customers' perceptions regarding the quality of the setting. The fourth part of the second section was designed to measure customers' perceptions of price compared to the value they receive. The questionnaire of the last section is aimed at measuring customers' overall satisfaction in terms of overall satisfaction with food and beverage quality, overall satisfaction with service quality, overall satisfaction with the quality of the setting, overall satisfaction with the price paid versus the value obtained, and their overall satisfaction with the dining experience. A 5-point Likert scale will be used for evaluation, where 5 = very satisfied, 4 = satisfied, 3 = neutral, 2 = unsatisfied, and 1 = very unsatisfied.

In order to determine the internal consistency of the survey questionnaire, a Cronbach's alpha coefficient reliability analysis was performed. This method shows an indication of the average correlation between all the items of the research questionnaire on the Likert scale, in this case. The Cronbach's alpha coefficient for the questionnaire was measured to be 0.960. Therefore, the Cronbach's alpha coefficient is well above the 0.7 standard reliability. Item analysis was achieved as well to provide item-to-total correlations and Cronbach's alpha if the item was deleted from the survey questionnaire. To evaluate the construct validity, exploratory factor analysis (EFA) with promax rotation was conducted. Finally, to check the content validity, a convenience sample of panel of experts (6 professors who were familiar with the scope of the study) checked the questionnaire through reviewing the content of each item in the modified version. Results showed that the final version of the questionnaire is valid and reliable and can be used in future studies for testing customers' satisfaction and perceptions of quality of food and beverages and services offered at university cafeterias.

3.3. Implementation and Participants

Before implementation, the survey was piloted to 30 persons (5 academics, 10 staff, and 15 students) to discover the extent of their understanding of sentences as well as the time taken to answer questions. Finally, based on the pilot test review, minor changes were performed to reach the final version of the questionnaire.

In order to calculate the sample size, there is a need to determine the accurate population size, the margin of error, and the confidence level. The most common used margin of error is 5% and the most common used confidence level is 95%. These percentages are standards in quantitative research [ 63 ]. Using the G∗Power sample size software, version 3.1.3 ( http://www.psycho.uni-duesseldorf.de/abteilungen/aap/gpower3/ , Faul et al. [ 64 ]), one of the leading software used for sample size calculation in various fields, a minimum of 362 respondents were required to achieve power for a population of 6000 based on precision level of 5%, confidence internal level of 95%, and P = 0.05.

To guarantee the collection of the targeted sample size, students as part of their work on campus, students were asked to help in the data collection and given information about the research topic and the content of the survey form. Additionally, they were trained on how to deal with respondents and how to gather required data. They approached their peers, as well as academics and staff from different faculties and asked them in person to fill out the questionnaire. It took between 5 and 10 minutes to complete. Anonymity was ensured. A total of 676 questionnaires were collected during the period of December 2018-January 2019. From this number, 24 questionnaires were invalid, and therefore, the total target sample for this study was 652 freshmen, undergraduate, and graduate students, academics, and professional staff employed at this rural university. The latter has an on-campus food service venue with 150 seats.

3.4. Statistical Analysis

Only completed surveys were analyzed. Data was processed and analyzed by the SPSS statistical software, Windows Version 23.0 (SPSS, Inc., Chicago, IL, USA). Means and frequencies as well as coefficients of Pearson correlations were used, in order to achieve the objective of this study. Frequencies were computed to examine demographic and behavioural characteristics of respondents. Means of scores were calculated in order to assess students' perceptions regarding different service attributes.

3.5. Ethical Considerations

For ethical considerations, a written permission to use and modify the survey questionnaire was obtained by the authors of the original questionnaire [ 3 ]. Ethical approval to conduct the study and to contact academics, staff, and students was obtained from the University Management Board. An informed consent was signed by those who agreed to fill the questionnaire.

4.1. Demographic and Behavioural Characteristics of Respondents

The demographic characteristics of respondents are presented in Table 1 .

Demographic characteristics of respondents.

The sample consisted of 37.4% male respondents and 62.6% female respondents. Among the 652 respondents, 83.7% of respondents were university students, 10.9% were academic, and 5.4% were staff.

A high percentage of respondents (62.0%) were aged between 17 and 21 years, 22.0% were between 22 and 24 years old, only 6.60% were between 25 and 35, and 9.4% were 35 years old and above.

Table 2 shows the behavioural characteristics of respondents. As shown in the table, 3.5% of surveyed respondents visited the cafeteria daily, 13.4% visited the cafeteria twice a week, and 26.7% of respondents visited the cafeteria once a week.

Behavior characteristics of respondents.

∗ 1 LBP = 0.00066 USD.

Approximately half of the respondents (56.4%) visited the cafeteria once a month.

Only 8.3% of respondents reported that their monthly average expenditure was above 100 000 Lebanese Pounds, and approximately half of the respondents (48.5%) spent between 10 000 and 50 000 Lebanese Pounds monthly. Furthermore, about 37.1% of respondents did not intend to continue having their meals at the university cafeteria, while almost the majority (62.9%) would like to continue eating at the cafeteria.

4.2. Food Service Attributes and Customer Satisfaction

The means of scores of respondents' perceptions of different research variables were computed, as presented in Table 3 . Respondents rated their levels of satisfaction with attitude statements that were positively phrased using a scale from 1 to 5, with 1 = very unsatisfied and 5 = very satisfied. Firstly, respondents' overall perceptions regarding the quality of food and beverage products presented at the cafeteria were above average (overall mean for the quality of food and beverage items = 3.41). According to the results presented in the table, a high percentage of respondents were satisfied with the taste of food and beverages ( M = 3.46), as well the display ( M = 3.45) and diversity of products ( M = 3.42). Respondents satisfaction with the freshness of food and beverage items ( M = 3.39), the nutritious products ( M = 3.34), and the appropriate serving temperature (M = 3.39) recorded the lowest mean score among the quality attributes. Similar opinions were given about the items related to the quality of service. Respondents' overall perceptions regarding the service quality presented at the university cafeteria were above the average (overall mean for the service quality attributes = 3.53). The friendly treatment by cafeteria staff, the staff knowledge of the items sold, and the cooperation of workers recorded the highest mean score among service quality attributes. Satisfaction means ranged from 3.57 to 3.61. However, the speed of service recorded the lowest mean score ( M = 3.46).

Frequencies and means for the research variables.

The third variable that respondents were asked about was the quality of the setting. The ambience, the lighting, and the organization of the delivery process recorded the highest mean score, above the mean ( M = 3.31). The cleanliness and hygiene ( M = 3.18) as well as the comfort and sitting availability ( M = 3.26) recorded the lowest mean score.

Opinions were given about the price respondents paid compared to the value they received. The value that respondents received was measured in terms of the quality and quantity of food and beverage items they received. As shown in Table 3 , most respondents felt that the quantity of food and beverage items provided was suitable and above the mean score, given the price paid ( M = 3.25). Additionally, respondents' satisfaction with the quality of food and beverage items, given the price paid, was perceived to be not satisfactory ( M = 3.20).

The last research variable measured was respondents' overall satisfaction. Overall respondents' satisfaction was measured using the following statements: overall satisfaction regarding the quality of food and beverage items ( M = 3.42) and overall satisfaction regarding the service quality ( M = 3.51) recorded the highest mean score, above the mean ( M = 3.39). Overall satisfaction regarding the prices ( M = 3.24) and overall satisfaction regarding the setting ( M = 3.38) recorded the lowest mean score.

As shown in Table 4 , the existence and level of correlation between different research variables and respondents' overall satisfaction were investigated using the Pearson correlation coefficient. The results indicated a significant correlation between food and beverage quality and respondents' overall satisfaction ( r = 0.873, P < 0.01). The Pearson correlation coefficient values emphasize the positive correlation between food and beverage quality and students' overall satisfaction. Therefore, H1 was supported after the Pearson correlation testing was performed.

Variables' correlations.

∗∗ Correlation is significant at the 0.01 level (2-tailed).

Furthermore, the results of the Pearson correlation test revealed a significant and positive correlation between service quality ( r = 0.834, P < 0.01), setting quality ( r = 0.836, P < 0.01), and respondents' overall satisfaction ( r = 0.959, P < 0.01). Therefore, the resulting hypotheses H2 and H3 were also supported. Results indicated that there was a statistically significant and positive association between the price and value ( r = 0.853, P < 0.01) and respondents' overall satisfaction, with reference to H4.

5. Discussions and Conclusions

The purpose of this study was to determine the cafeteria customers' overall satisfaction with on-campus food service attributes. The findings suggest some important implications for university food service operator. The food service manager should recognize the customers' characteristics such as age groups. The results of the study showed that the age groups between 17 and 21 are the largest customers. Therefore, the campus food service manager should develop strategies catered to appeal different segments of customers based on the various age groups.

The regression analysis showed that the quality of service was the strongest predictor of customer satisfaction. Thus, university food service operator should continue to train their employees to greet their customers in a polite manner, to be attentive and friendly, and to increase their knowledge about the food items served. Maintaining the quality of their service ensures that they can still continue to meet or exceed costumer expectations [ 65 ]. Lashley [ 66 ] has shown that sincere and affective relationships between the host and the guest can operate in a commercial environment.

Food and beverages quality turned out to be the second important element affecting customer satisfaction. In sum, some of the possible strategic implementations may include more variety of nutritious products, adjusting the serving temperature, and paying more attention to the freshness of the products sold. This result is consistent with the previous findings of Kjøllesdal et al. [ 30 ]. Kjøllesdal et al. [ 30 ] asserted that workplace eating is frequently associated with poor-quality food and bad choices, which have negative consequences. In rural universities, accessing food in places of work, as healthy options and varied choices may be limited. Ham [ 8 ] mentioned that good-quality food service provision can contribute to the overall campus experience. Absence of trust in the quality of food has an impact on diet through avoidance of certain products deemed to be unsafe or untrustworthy [ 67 ]. The challenge for the university food service operator is to provide products and services that enhance and facilitate positive healthy food choices. Given the amount of employees eating at their place of work, most research on this topic relates to the direct importance of making healthy dishes available [ 68 ].

Furthermore, the university food service operator should pay more attention to the quality of the setting. They should carefully design cafeteria interiors and exteriors to deliver a relaxed and comfortable atmosphere to attract new customers and to retain current ones. University food service operator should maintain the cleanliness and hygiene of the facility to a standard level. The findings are in line with the previous results of Kim et al. [ 7 ]. Improving customer satisfaction with reference to the quality of the setting will not only strengthen the customer loyalty but also improve the facility reputation and this is also good for their businesses. Lugosi [ 15 ] has studied the campus food service experience with reference to student well-being and has emphasized on the campus food service as a cowork space. Among several factors driving social interaction, contemporary designs of university campuses have adopted many of the features of cowork spaces [ 69 – 71 ], with furnishings and layout of the infrastructure of the space, facilitating the positive experience.

Particularly, cleanliness or hygiene was the third most important factor, after food variety and convenient location, which influences costumer selection of a food service to dine in. Although costumers are increasingly concerned about the nutritional value of the food they consume, food safety remains far more important than as the associated risk can be substantial. Food service hygiene is indeed important. Fatimah et al. [ 72 ], in their study, have identified four underlying food service hygiene factors from the consumer perspective: food and location, staff and handling, premise and practices, and ambient scent. The priority should be given to service quality. Low service quality is attributed to low-scale food services.

Moreover, customers tend out to be the least dissatisfied with the price paid, with reference to the quality of food and beverage products provided. The university food service operator should improve the quality of the products served and should offer reasonable pricing, in order to prevent customers from switching to other off-campus restaurants, which will result in less sales and lower revenue in the long term. Higher customer satisfaction should increase revisit/return intention and provide word-of-mouth endorsements of the university food service facility [ 73 ].

From the managerial perspective, the great importance of customer place on the quality of the food service requires that the food service provided by the university campus should take into consideration the customers' insights and perceptions and thus give a push to many institutions to overhaul their campus food service operations. Demand for healthy food and quality of the setting, with reference to the comfort of the sitting area, is an important lever for positive and promising change.

6. Limitations and Future Research

The limitations of the study are that a single university campus cannot represent all the university campuses and all universities in Lebanon. Results should be interpreted with caution. Also, the survey questionnaire was distributed by students. This might affect students' attitudes and opinions as they took the survey. For future research, it would be important to replicate the study on another campus, to determine how and if the findings hold true given a diverse sample, in an urban campus. Another constraint of this research is the feature of its samples. More than 80% of the participants in the survey were students. Surprisingly, the majority of staff and academics were not interested in filling out the survey. Therefore, performing another study in a larger scale is suggested to expand the results of this research and to provide more representative results and to improve sample generalizability. The current study can, however, help to provide a roadmap for helping the university management better understand the key importance of food and service quality. Based on the results, several implications and recommendations could be derived for university management to increase student satisfaction about food and beverage services provided by university cafeteria. University management (1) should investigate about cafeteria users' opinions continuously in order to solve any problems promptly, (2) should institutionalize systems for continuous training of cafeteria employees through customized programs designed for them, (3) should invest in improving the quality of the setting, with reference to the comfort of the sitting area, (4) should invest, in coordination with the cafeteria operator, in offering more nutritious food in order to be able to meet cafeteria users' needs, (5) should give special attention to contract with the best operator, (6) should develop strategies catered to appeal different segments of customers based on the various age groups, and (7) should place more emphasis on identifying and meeting the needs of students and staff (offering late night meals).

Acknowledgments

The authors wish to thank the university administration and the cafeteria operator for their support.

Data Availability

Conflicts of interest.

The authors declare that there is no conflict of interest regarding the publication of this paper.

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Food and social media: a research stream analysis

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• Ruth Areli García-León   ORCID: orcid.org/0000-0002-8984-2348 1 &
• Thorsten Teichert   ORCID: orcid.org/0000-0002-2044-742X 1  

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Interest in food and online communication is growing fast among marketing and business scholars. Nevertheless, this interest has been not exclusive to these areas. Researchers from different disciplines have focused their research on different concepts, target populations, approaches, methodologies, and theoretical backgrounds, making this growing body of knowledge richer, but at the same time difficult to analyze. In order to have a broader overview of this topic, this study analyzes the existent literature regarding food and social media in social sciences in order to identify the main research streams and themes explored. With this purpose, the present paper uses bibliometric methods to analyze 1356 journal articles by means of factor and social network analysis. The study contributes by revealing 4 clusters containing 11 dominant research streams within the social sciences, determining the linkages among the main research discourses, and recommending new future topics of research.

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1 Introduction

Food and social media is highly a controversial topic. While some studies point out that the use of social media can be associated with an increase of unhealthy food intake and Body Mass Index (BMI) (Coates et al. 2019a ; Khajeheian et al. 2018 ), other studies, as well as the OECD and the American Heart Association suggest that the use of social media could be used to sensitize the population regarding obesity and to promote public health regarding food (Chau et al. 2018 ; Li et al. 2013 ; OECD 2017 ).

People use the World Wide Web and social media to seek and share information, for social interaction, and to be part of a social network (Kavanaugh et al. 2005 ; Whiting and Williams 2013 ). Billions of opinions are shared on social networks every day (Mostafa 2019 ), breaking barriers across geographical distance and bringing people closer (Rimjhim et al. 2020 ). Social networks and online communities facilitate consumer-to-consumer communication (Sloan et al. 2015 ), and influence consumers’ opinions, attitudes, consumption experiences, brand perceptions, purchasing decisions, as well as post-purchase communication and evaluation, among others (Jansen et al. 2009 ; Mangold and Faulds 2009 ; Teichert et al. 2020 ).

The rapid growth of online communication among consumers has increased academic interest in electronic word of mouth (e-WOM). Zinko et al. ( 2021 ) define e-WOM as the “web-mediated exchange of information which occurs when one person tells another about their experience with a service or product” (p. 526). E-WOM includes blogs, online reviews, ratings, messages posted on online groups, and social media posts (Hennig-Thurau and Walsh 2003 ). Either as a topic of consumer health, sustainability, or as an opportunity for management development, studies regarding food and social media are gaining importance. Scholars from different disciplines have used different approaches, methodologies, theoretical backgrounds, and populations targets to address this topic. Additionally, due to the novelty of some internet-based communication tools, and the rapid emergence of additional ones, new concepts, definitions, and approaches are emerging too, making this growing body of knowledge difficult to explore.

Although the scope of food and social media research has partly been disclosed in literature reviews, these focus on a particular sub-segment of food consumption, a specific target population, area of research, research method, or a specific new technology or social media. For example, Chau et al. ( 2018 ) centered their research on the role of social media in nutrition interventions for adolescents and young adults. Rounsefell et al. ( 2020 ) explored the impact of social media exposure to image-content on body image and food choices in young adults. Chapman et al. ( 2014 ) analyzed literature regarding the use of social media for public health communication in order to explore the potential of social media as a tool to combat foodborne illness. De Veirman et al. ( 2019 ) studied the persuasive power of social media influencers over young children. Dute et al. ( 2016 ) examined literature regarding the promotion of physical activity, healthy nutrition, and overweight prevention among adolescents and students, through mobile apps. Allman-Farinelli and Gemming ( 2017 ) explored the state of the art in dietary assessment, using smartphone and digital technology regarding technology mediated interventions for dietary change. Tao et al. ( 2020 ) studied the use of text mining as a big data analysis tool for food science and nutrition. And Ventura et al. ( 2021 ) analyzed the topic of food in social media from a consumer-oriented point of view. However, there are no studies offering a general overview of a broad sample of articles within the social sciences regarding food and the use of social media.

Given this, the aim of this paper is to provide a broad bibliometric review for marketing and business scholars, companies, and organizations on past and current research regarding food and social media within the social sciences, in order to reveal the main addressed topics, as well as for suggesting future topics of research in this field of knowledge. To achieve the results, this research uses the co-word analysis of Keywords. Co-word analysis (Callon et al. 1983 ) is a type of bibliometric method which seeks to find connections among concepts that co-occurs in document abstracts, titles, or keywords as assessed by the authors (Zupic and Čater 2015 ). By conducting a co-word analysis of keywords, the present study aims to reveal the main research streams regarding food and social media studied in the social sciences. First, statistical analyses are applied to identify research streams as well as their interconnections in an objective manner. Single research streams are then analyzed in detail by a manual inspection of their key publications. Focal issues of past and current research are highlighted and opportunities for future research are identified.

2 Methodology

2.1 co-word analysis.

One of the most used bibliometric methods is co-citation analysis. Nevertheless, while co-citation analysis connects documents, authors, or journals in order to find the intellectual structure, the knowledge base, or influences on a research field (Small 1977 ; Zupic and Čater 2015 ) the co-word analysis uses the actual words contained in documents to determine relationships among concepts that represent a conceptual space of a field (Zupic and Čater 2015 ). In co-citation analysis, it is assumed that the more two items are cited together, the more likely is that their content is related, and since it takes time to accumulate citations, the analysis reflects the state of the field in the past and not how it could look now or tomorrow (Zupic and Čater 2015 ). In this regard, the co-word analysis offers a more actual state of the field since authors choose the words, concepts, titles, and keywords that best represent their studies. In their articles, authors construct different realities linking scientific and technical concepts that are shared by a specific research community (Callon et al. 1983 ). Therefore, the co-word analysis is more content-driven than the co-citation analysis.

The main target of this analysis is the keywords contained in the articles since keywords are chosen by the authors because they represent in a few words, the main content of the study. Web of Science database (WoS) is frequently used for bibliometric studies in management and organization, and it contains different valuable bibliographical data for indexed documents that include title, article type, authors, keywords, keywords plus, abstract and subject categories or areas, among others (Zupic and Čater 2015 ). Besides the Author Keywords, WoS provides Keywords Plus. They are index terms automatically generated from the titles of cited articles in an article that augment traditional keyword retrieval (Clarivate 2020 ). Therefore, this research analyzes the Author Keywords and the Keywords Plus provided by WoS.

2.2 Identification of literature

The search of documents was made on WoS by using a Keywords string containing the main concepts related to the objective of the research (see Fig.  1 for the overall design, search string, and interim steps taken). Although most of the well-known social media such as Youtube or Twitter appeared in the 2000s, some authors consider that the development of social media started during the 80 s with the introduction of USENET, a type of internet discussion system, real-time online chat services such as Compu Serve’s CB Simulator (1980), the Internet Relay Chat (IRC) (1988), or AOL’s chat rooms (1989) (Edosomwan et al. 2011 ; Lake 2009 ; Sajithra and Patil 2013 ). Others establish this development in the 90 s when the World Wide Web became public and web blogs, list-servers, and e-mail services allowed users to form online communities exploding networked communication (Simonova et al. 2021 ; van Dijck 2013 ). Therefore, in order to have a broader number of articles and consequently a broader scope regarding food and social media research in Social Sciences, the timespan 1990 to 2021 and the citation indexes Social Sciences Citation Index (SSCI) and Emerging Sources Citation Index (ESCI) were used as limiters. The ESCI extends the scope of publications of WoS by including around 3,000 peer-reviewed publications that although they are not yet recognized internationally, meet the WoS high-quality criteria (Francis 2021 ). Besides, Articles, Reviews, or Early Access articles were included in order to capture the most recent published works. Early Access articles in WoS Core Collection are fully indexed articles that the publisher makes available online in a nearly final state (e.g. Articles in Press, Published Ahead of Print, Online First, etc.), they lack publication date, volume, issue, and page number (Clarivate 2021 ).

Sample generation process by steps

With this information, an initial database of 1400 records was created on July, 20 of 2021. Nevertheless, only articles containing Author Keywords and/or Keywords Plus were included; therefore, 29 articles without author Keywords and Keywords Plus were removed. In the end, just 1371 were included in the next analysis.

A first analysis of Keywords contained in the 1371 articles was made by using the KHCoder, a text-mining and text-analysis application ( https://khcoder.net/en/ ). To avoid the analysis of joined words separately, a total of 31 words strings, also called Force Pick Up Words, were chosen to extract different words as one concept (e.g. qualitative_research, corporate_social_responsibility) (see Table S1 in Supplementary material). The word frequency list revealed a total of 3,716 keywords and a total of 21,027 mentions. In order to include just the most representative concepts in the analysis, just concepts mentioned more than 5 times were included. Hence, just 655 Keywords representing 75.81% of all mentions were included in the second analysis.

The second step was an analysis of concepts, conducted by both researchers, in order to find similarities among words due to meaning, writing differences, use of abbreviations, or use of signs to unite words.

After this analysis, a list of 413 Keywords or “code words” containing the initial 655 Keywords was generated (the complete list of words and code words (*) could be seen in Table S2 in Supplementary material). This list of code words was introduced to KHCoder in order to generate a crosstab containing the concepts included in every article. As a result, 15 articles containing none of the 413 Keywords were discarded for further analysis.

2.3 Data analysis

The data were analyzed by using the package UCINET 6 (Borgatti et al. 2002 ), one of the most used software for network visualization (Zupic and Čater 2015 ), in order to generate an overall concept co-occurrence matrix. By executing a core-periphery analysis the core keywords contained in the food and social media literature were separated from the periphery keywords. The stable solution was found in 50 iterations (fitness = 0.609).

Then, a factor analysis was conducted using SPSS in order to group keywords based on their co-occurrences. Factor analysis can determine which indicators, in this case, keywords, may be grouped together. Factor analysis is known as a data reduction technique (Sallis et al. 2021 ). In order to identify groups of bibliometric data, researchers have used different statistical techniques such as factor analysis, cluster analysis, multidimensional scaling, or multivariate analysis (Chen et al. 2016 ; Leydesdorff and Welbers 2011 ; Ravikumar et al. 2015 ; Wang et al. 2012 ; Yang et al. 2012 ), although, for practical use, some authors have not found a difference between cluster analysis and factor analysis (Lee and Jeong 2008 ).

The use of factor analysis has a long tradition in co-word analysis. Considered a quantitative form of content analysis, it can substitute commonly practiced techniques for content analysis, providing precision and validity in the resulting categories while investing less time and resources (Leydesdorff and Welbers 2011 ; Simon and Xenos 2004 ). Many studies have used factor analysis in co-word analysis as a reliable method to discover linkages among scientific documents. For example, by using the words contained in the titles and abstracts of research articles, Leydesdroff ( 1989 ) used factor analysis and cluster analysis to find linkages among biochemistry documents. Leydesdorff and Hellsten ( 2005 ) studied words related to stem-cell by using factor analysis. Leydesdorff and Zhou ( 2008 ) used factor analysis to analyze words of journal titles using Chinese characters. Wang et al. ( 2014 ) analyzed keywords from core journals in the field of domestic knowledge discovery by using factor and cluster analysis. Yan et al. ( 2015 ) analyzed the intellectual structure of the field of the Internet of Things by means of factor and cluster analysis of keywords. Gan and Wang ( 2015 ) used factor analysis to map the intellectual structure of social media research in china by using keywords, and Sun and Teichert ( 2022 ) used factor analysis to study the research landscape of ‘scarcity’ by using author keywords.

In the specific application field of bibliometrics, the method identifies different research streams (Kuntner and Teichert 2016 ). By reducing the number of variables in a dataset, the factor analysis finds patterns and therefore, the underlying structure of the data (Wendler and Gröttrup 2016 ). There are different methods to extract factors. This study applied a principal component analysis (PCA) with an orthogonal factor rotation Varimax with Kaiser Normalization of 15 iterations. Varimax is a very popular rotation method in which each factor represents a small number of variables and each variable tends to be associated with one or a small number of factors (Abdi 2003 ). It enhances clarity, interpretability, and efficiency when distinguishing among the extracted factors (Simon and Xenos 2004 ). PCA finds the linear combination between indicators that extract the most variance in the data and uses both common and specific variance to extract a solution (Sallis et al. 2021 ). Therefore, in order to find the main research streams regarding food and social media, the number of variables (i.e. Keywords) was reduced to identify the underlying structure based on the overall variance. By performing factor analysis, determined keywords are assigned to determined factors based on their factor loadings. Factor loads (FL) inform about the representativeness of a determined keyword for a determined factor, and the usage of a keyword in a research stream (Kuntner and Teichert 2016 ; Sun and Teichert 2022 ). That means that the keywords assigned to one factor are more likely to co-occur than the keywords of other factors. Therefore, by using this method, factors were interpreted as single research streams.

As a result of the analysis, 12 factors emerged, which explain 51.175% of the total variance (see Table S3 in Supplementary material for the complete concepts per factor). Factor 11 was found to address issues related to the pharmaceutical industry and the Food and Drug Administration of United States (FDA) guidance documents. This factor was omitted in the further analysis, as it primarily addresses the pharmaceutical industry does not have a direct relationship with food and social media.

In order to further identify group similarities across research streams, a cluster analysis in SPSS was conducted. Cluster analysis finds natural groups present in the data, but hidden, by identifying important and defining properties (Sallis et al. 2021 ). This analysis revealed four main research clusters that the researchers named: Psychological Research Realm, Action-Oriented Research, Broader Communication Issues, and Service Industry Discourse (see Table 12 for a summary of research clusters and their characteristics).

3 Results and discussion

In the following, the four different clusters of research are explained in detail considering the most representative publications of every factor or research stream.

3.1 Psychological research realm

The Psychological Research Realm contains four research streams; therefore, it is the biggest of the four clusters. These research clusters address mainly, the impact of social media use on consumers. It includes the streams “online tools for healthy diet intervention programs,” “food and use of apps,” “online food advertising exposure,” and “social media and mental disorders.”

3.1.1 Research stream on “online tools for healthy diet intervention programs” (Factor 1)

The first research stream explains 18.94% of the variance of keyword relationships, indicating a research stream of first-highest distinction. While obesity and diet were the most often listed keywords (130 and 123 mentions), the research stream was best represented (in terms of factor loadings) by the keywords diet (FL = 0.922) , followed by intervention. Program, related to (physical) activity, nutrition, prevention, adult, overweight, and association constitute the remainders of the top ten keywords. An inspection of the remaining 103 keywords confirms this focus on application-oriented topics from the perspective of healthy diet interventions. Thus, this research stream clearly addresses the topic “use of online tools for healthy diet intervention programs.”

Representative publications of this research stream (see Table 1 ) reference each more than 14 keywords of factor 1. Regarding theories and conceptualizations, most of the articles refer to healthy diets and the use of online tools. Thus, an inclusive and shared research discourse can be diagnosed.

A closer look at these articles (selected by maximum number of referenced keywords) provides insights about the methods used, the online tools evaluated, as well as the types of insights gained from this research discourse (Table 1 right columns). These articles address the use of online tools for healthy diet intervention programs by using randomized and controlled trial groups, among others. The studies analyze the development of novel online tools as well as the efficacy of other healthy diet intervention tools.

The consumption of junk foods, fast foods, sugar-sweetened beverages, and carbonated drinks and beverages is associated with higher body mass index in children and adolescents due to their high content of free sugar and energy (Gupta et al. 2019 ). In order to promote public health sensitizing the population regarding obesity, the use of social media and new technologies has been recommended by the OECD and the American Heart Association (Li et al. 2013 ; OECD 2017 ).

In this regard, this research stream contains protocols of novel internet-based intervention tools to promote healthy diets (Helle et al. 2017 ; Røed et al. 2019 ), as well evaluations about the effectivity of online tools for intervention programs, and for the delivery of healthy eating information and recipes, among others. Ahmad et al. ( 2020 ) evaluated the effect of the family-based intervention program (REDUCE) on children’s eating behaviors and dietary intake via face-to-face and social media by using Facebook and a WhatsApp group to deliver information about the intervention and as platforms of interaction and problem solving. The authors found small changes in consumption of unhealthy snacks, as well as fruits and vegetables, without clinical impact. Dumas et al. ( 2020 ) explored the effects of an evidence-informed healthy eating blog written by a registered dietitian, finding no effects on dietary intakes, food-related behaviors, and body weight.

While these former studies did not reveal a strong positive impact, there are other studies showing positive results. For example, with the aim of evaluating the value of social media for delivering healthy diet interventions, Chau et al. ( 2018 ) found that the majority of the studies associated with this topic, from 2006 to 2016, showed positive outcomes regarding the use of only basic social media features. Tobey et al. ( 2019 ) evaluated the success of the Food Hero marketing campaign and suggest that in order to disseminate recipes to low-income audiences through social marketing campaigns, is recommended to understand the target audience, to add healthy/customizable recipes to family “go-to” recipe rotations considering the generational influences on family meals, and to create websites that meet the target audience criteria (e.g. simple and visually interesting).

By delivering healthy diet interventions through social media or online tools, studies in this research stream targeted mainly parents. Future research might evaluate the efficacy of social media or novel online tools by targeting parents and children separately, and by delivering strategies designed for each group.

3.1.2 Research stream on “online food advertising exposure” (Factor 5)

Explaining 2.78% of the variance of keyword relationships, the fifth research stream indicates a research stream of fifth-highest distinction. Here, the most often mentioned keywords were marketing and advertising (82 and 63 mentions). However, in terms of factor loadings, the research stream was best represented by the keywords advertising (FL = 0.915) , followed by marketing. Exposure related to (unhealthy) food, television, advergame, beverage, celebrity, youtube, and endorsement constitute the remainders of the top ten keywords. The inspection of the remaining 14 keywords confirms the online advertising exposure approach. Thus, this research stream clearly addresses the topic “online food advertising exposure.”

Representative publications (see Table 2 ), selected by the highest number of reference keywords, reference each more than 6 keywords of factor 5, and address the concept of influencer marketing , and among other social media, they analyze mainly YouTube videos, sharing an inclusive research discourse.

A closer look at these articles reveals that four of six articles of this research stream were led by the same author. In general, the articles of this research stream address the exposure to food advertising online by means of content analysis, questionnaires, and multivariate analysis, among others.

Regarding food and beverage marketing content on social media, Kent et al. ( 2019 ) found that although children and adolescents are exposed to unhealthy food and beverage marketing on social media, adolescents were more highly exposed to food marketing than children through user‐generated, celebrity‐generated content, and other entertainment content. Regarding food and beverage products featured on YouTube videos of influencers who are popular with children, it was found that less healthy products were the most frequently featured, branded, presented in the context of eating out, described positively, not consumed, and featured as part of an explicit marketing campaign, than healthy products (Coates et al. 2019b ).

Studies in this research stream have proved the persuasive power of social media influencer promotion of food, and their impact on children’s food intake, even when including a protective disclosure, due to their credibility and familiarity with children. Some authors situate social media influencers as a new type of advertising source that combines the merits of e-WOM and celebrity endorsement (De Veirman et al. 2019 ). YouTubers featuring videos of food and beverages high in fat, sugar, and/or salt (HFSS) are valued highly by children because they are viewed to fulfill their needs. Children develop sympathetic attitudes towards YouTubers because they are not strangers to them (Coates et al. 2020 ). Children look up to popular influencers who have certain celebrity status and are willing to identify with them while taking on their lifestyles, attitudes, and beliefs. Therefore, (marketing) messages spread by them are perceived as highly credible WOM, rather than as advertising, due to their perceived authenticity (i.e., they have no commercial interests) (De Veirman et al. 2019 ).

It has been discovered that children exposed to influencer marketing in a YouTube video of a branded unhealthy snack (with and without an advertising disclosure) consumed more of the marketed snack and significantly increased intake of unhealthy snacks specifically whereas the equivalent marketing of healthy foods had no effect. Therefore, it has been concluded that influencer marketing increases children's immediate intake of the promoted snack, even when including a “protective” advertising disclosure, which does not reduce the effect of influencer marketing (Coates et al. 2019a , 2019c ). Results reveal that increasing the promotion of healthy foods on social media could not be an effective strategy to encourage healthy dietary behaviors in children (Coates et al. 2019c ).

In sum, most of the articles in this research stream address children and adolescents’ exposure to unhealthy food influencer marketing contained in YouTube videos. Further research could evaluate the use of influencer marketing on children for healthy food intake, not just in YouTube, but also in other video content social media like TikTok, or Instagram. Other studies could compare different target groups (e.g. adults, adolescents, and children) in different countries.

3.1.3 Research stream on “social media and mental disorders” (Factor 8)

The eights research stream explains 1.93% of the variance of keyword relationships, indicating a research stream of eight-highest distinction. The research stream was best represented (in terms of factor loadings) by the keywords depression (FL = 0.793) , followed by anxiety. The same words were, as well the most listed keywords (18 and 17 mentions) . Addiction, disorder, symptom, distress, psychological, stress, well-being, and personality constitute the remainders of the top ten keywords. An inspection of the remaining 6 keywords confirms this focus on application-oriented topics from the perspective of mental disorders. Thus, this research stream clearly addresses the topic “social media and mental disorders.”

Representative publications of this research stream (see Table 3 ) reference each more than 4 keywords of factor 8. Regarding theories and conceptualizations, although this research stream has not a leading theory, they analyze different mental disorders and their relationship with social media. Thus, an inclusive and shared research discourse can be diagnosed.

A closer look at these articles (selected by maximum number referenced keywords) provides insights about the methods applied and types of insights gained from this research discourse (Table 3 right columns). These articles address social media use and mental disorders by using questionnaires, addiction scales, and personality inventories, among others. Hence, antecedents and consequences of social media use and mental disorders are analyzed.

Regarding the antecedents of addictive behaviors, it was found that personality traits and gender, as well as certain mental disorders, are associated with different behavioral addictions. For example, the profiles “elevated levels of gaming and pornography addictions” as well as “highest levels of all addictions” are predominantly male, while the profile “elevated levels of study, Facebook, shopping, and food addictions” are almost exclusively female (Charzynska et al. 2021 ). Besides, it was concluded that “individuals higher in anxiety sensitivity/hopelessness used food or alcohol to cope which, in turn, significantly predicted unhealthy snacking, and hazardous drinking, respectively” (Reaves et al. 2019 , p. 921).

Regarding the use of social media and its impact on mental disorders, Kicali et al. ( 2021 ) found that although food addiction is associated with some personality traits, personal habits, and psychiatric symptoms, more than five hours a day of social media consumption hat a direct relationship with internet and eating addiction. Kircaburun et al. ( 2021 ) found that a Problematic YouTube Use (PYU), which refers to different activities like watching specific YouTube channels or viewing online video games, is associated with loneliness and depression. Other works in this research stream explored images shared on social media and their relationship with mental disorders. E.g., Bogolyubova et al. ( 2018 ) concluded that while in Russian language people shared more images of food with hashtags for stress, images of alcohol were associated with stress hashtags, and hashtags for fear were related to the “scary” in popular culture and not to psychological distress.

Other works in this research stream addressed the impact of the COVID-19 Pandemic on mental health. Bountress et al. ( 2021 ) determined that instead of a single overarching COVID-19 impact, there are discrete impacts of various COVID-related factors. Therefore, they suggest a five-factor COVID model (i.e. exposure, worry, housing/food instability, social media, substance use) which is able to predict the risk of mental health symptomology, as well as other adverse sequelae of the COVID-19 pandemic at large. On the other hand, Panno et al. ( 2020 ) confirmed that COVID-19 related distress is associated with alcohol problems, social media, and food addiction symptoms. Following this line of research, future research might explore further the use of social media for mental health.

3.1.4 Research stream on “food and the use of apps” (Factor 12)

The twelfth research stream explains 1.32% of the variance of keyword relationships, and is the research stream of twelfth-highest distinction. Mobile and adoption, were the most often listed keywords (24 mentions each). Nevertheless, the research stream was best represented (in terms of factor loadings) by the keywords application (FL = 0.621) , followed by mobile. The remainders of the top five words were (Smart)phone and app. A closer look at the main keywords confirms its orientation to application-oriented topics from the perspective of the use of apps, focusing clearly on the topic “food and the use of apps.”

Representative publications reference each more than 2 keywords of factor 12 (see Table 4 ). Although this research stream has not a leading theory, most of the articles investigate the topic of food and the use of apps, sharing an inclusive research discourse. The representative publications chosen by the highest number of referenced keywords (Table 4 right columns), address the use of apps in relation to food by means of literature review, questionnaires, and interviews, mainly. Among others, social media content, as well as antecedents, and contingencies regarding food tourism are analyzed.

Information Communication Technology (ICT) (e.g. internet; mobile technology; and social media platforms among others) influence the daily living activities of persons, specifically Instrumental Activities of Daily Living (IADL) (e.g. activities requiring complex problem solving, cognitive function, coordination, and scheduling) (Quamar et al. 2020 ). In this regard, children interact with and consume visual advertising when visiting sites or applications related to online gaming (23%), food and distribution (18%), entertainment (8%) and fashion (8%), and when using smartphones with Internet access, Chilean children receive 14 min per hour of use of visual advertising more than from other media, such as television (Feijoo-Fernandez et al. 2020 ).

Regarding the antecedents of the use of mobile phones and apps for service purposes, it was found that the adoption of services and apps is driven by individual’s mobile phone technology maturity and business development (Paas et al. 2021 ). An analysis of user’s feedback on Twitter of four prominent food delivery apps and app store reviews of these apps revealed that the main concerns of users are related to issues regarding customer service, orders, food, delivery, time, app, money, drivers, and restaurants (Williams et al. 2020 ). Regarding mobile dining (e.g. use smartphone apps, to find restaurants, to read food menus, to select food, and to order it) it was found that consumers’ purchase intention is shaped by perceived values (i.e. navigation system, review valence, credibility, as well as service, and food quality) (Shah et al. 2020 ).

Other studies explored the use of smartphone apps for healthy lifestyles and dietary change. While Allman-Farinelli and Gemming ( 2017 ) concluded that apps have proven to be effective for glycemic control but not yet regarding weight loss and food intake, other studies found that monitoring apps enable users to set targets and monitor themselves. Besides, it is possible to acquire tailored feedback, and subsequently to raise awareness and increase motivation regarding dietary intake and physical activity. Moreover, apps with incorporated social features, characterized as social media, facilitate social interaction and support, can provide social comparison and social support (Dute et al. 2016 ). Concerning the development of smartphone apps to reduce sugar-sweetened beverage consumption among disadvantaged young adults in nonurban settings or indigenous communities, Tonkin et al. ( 2017 ) identified the importance of design to facilitate comprehension, and that in order to increase satisfaction the use of social features such as audio, leader boards, games, and team challenges could be helpful.

Studies in this research stream explored the use of specific apps for service purposes or dietary change, in just one region or sample. Further research could conduct comparative studies among apps, with different target groups in different geographical areas or regions.

3.2 Action-oriented research

This research cluster analyzes the content of social media and its impact on consumers' food risk information seeking and perception, behavioral intention and buying of green products online, as well as food tourism for destination image and its promotion. It includes the research streams “online food risk communication,” “behavioral intention and buying online,” and “social media and food tourism.”

3.2.1 Research stream on “online food risk communication” (Factor 3)

This research stream of third-highest distinction explains 3.79% of the variance of keyword relationships. Communication and risk were the most often listed keywords accounting 151 and 102 mentions respectively. However, in terms of factor loading, it was best represented by the keywords ( food) safety (FL = 0.827) , followed by ( risk) communication. The remainders of the top ten keywords were the keywords public and (risk) perception related to safety, (food) risk, crisis, and amplification . The remaining 35 keywords indicate its focus on themes from the perspective of online communication, addressing clearly the topic “online food risk communication.”

Table 5 displays the representative publications of this research stream, which reference each more than 8 keywords of factor 3. Most of them address the risk communication concept, sharing therefore an inclusive research discourse. These articles address the topics of online media consumption and food risk by means of surveys and quantitative content analysis, among others. They focus mainly on the coverage of topics related to health risk, consumers´ food risk information seeking, and consumers´ risk perception.

Some studies in this research stream explore how online information sources cover different healthy risk themes. For example, during the 2008 Irish dioxin contamination of food, Shan et al. ( 2014 ) found that social media responded faster than traditional media, using offline and online media news messages as primary sources, in reporting limited topics. Related to the coverage of biological, chemical, nutritional food risks, and related safety issues, Tiozzo et al. ( 2020 ) discovered that the most widely covered topics were nutritional risks and news about outbreaks, controls, and alerts. Moreover, national sources covered food risks, especially during food emergencies whereas thematic sources devoted major attention to nutritional topics.

In regard to the antecedents of consumers’ online information seeking behavior, concerning food safety issues, Wu ( 2015 ) concluded that Facebook use intention is determined by risk perception, emotion, social trust, and support. Regarding Genetic Modification (GM) issues, (Hanssen et al. 2018 ) discovered that the frequency with which people seek information is low, and it is driven by a positive attitude toward science and technology, trust in organizations, negative trust in regulations, as well as by gender and educational level. As a tool for food safety risk, specifically, to combat foodborne illness, Chapman et al. ( 2014 ) identified that the use of social media could be helpful for public health and food safety risk, since social media provide access to real people´s discussions and feedback, allow communicators to reach people where they are, create communities, and can be used to build credibility by providing decision-making evidence.

Regarding risk perception, some studies in this research stream found that risk perception depends on the topics and the online source used by consumers. For example, mixed media have a stronger positive relationship regarding public risk perception (PRP), than traditional media or internet social media (Niu et al. 2022 ). And, in the case of bovine spongiform encephalopathy (BSE), individuals exposed to more internet news had higher risk perceptions in terms of how BSE could affect themselves, while respondents exposed to social networking sites were concerned about how the disease could affect others (Moon and Shim 2019 ).

With most of the articles of this research stream addressing risk perception, or consumers’ food risk information seeking, further research could explore how social media could be used effectively for public health and food safety risk by using quantitative and qualitative methods of research.

3.2.2 Research stream on “behavioral intention and buying online” (Factor 4)

The fourth research stream explains 3.02% of the variance of keyword relationships, indicating a research stream of fourth-highest distinction. The research stream was best represented (in terms of factor loadings) by the keywords organic (FL = 0.765) , followed by purchase, although attitude and intention were the most often listed keywords (79 and 66 mentions) . Theory and (planed) behavior related to buying, food-intake , belief, and acceptance, were the remainders of the top ten keywords. As it can be confirmed by analyzing the remaining 20 keywords, the focus of this research stream relies on the perspective of behavioral intention, addressing thus the topic of “behavioral intention and buying online.”

Representative publications of this research stream (see Table 6 ), selected by the highest number of referenced keywords, contain each more than 7 keywords of factor 4. Addressing the Theory of Planned Behavior (TPB) and/or the Theory of Reasoned Action (TRA) (Ajzen and Fishbein 1980 ), most of the articles address the concept of “behavioral intention” regarding green, or organic products, showing an inclusive and shared research discourse.

With six of seven articles using TPB or TRA, this research stream addresses the topic of behavioral intention regarding green products by means of structural equation modeling.

The TPB is an improved version or extension of the Theory of Reasoned Action (TRA) (Ajzen 1991 ; Hofmeister-Tóth et al. 2011 ). The TPB differs from the TRA, “in that it takes into account perceived as well as actual control over the behavior under consideration” (Ajzen 1985 , p. 12). Ajzen ( 1985 ) explains that actions are controlled by intentions. Therefore, the TPB is a model that predicts behavior based on the intention to perform the behavior and the perceived behavioral control where the attitude towards the behavior , the subjective norm, and the perceived behavioral control influence intention (Aertsens et al. 2009 ).

Studies of this research stream concluded that the information contained in social media tools can influence the intention to perform a behavior regarding green or organic products. Considering green cosmetics purchase intentions, Pop et al. ( 2020 ) point out that social media can increase consumers’ environmental concerns, consumers’ attitudes, subjective norms, altruistic and egoistic motivations, and therefore consumers’ green cosmetics purchase intentions. By using the value-belief-norm theory and the elaboration likelihood model, Jaini et al. ( 2019 ) discovered that e-WOM communications influences consumers’ green cosmetics purchase decisions, with personal norm affecting this choice, especially when they are actively involved in obtaining positive feedback via e-WOM communication. In addition, pro-environmental beliefs, which eventually affect consumers’ personal norms, are affected positively by hedonic, and altruistic value.

Regarding organic food, it was confirmed that consumers’ attitudes towards organic food can be shaped by social media forums and informative webpages featuring product quality and certification. They have a great moderating effect on purchase ratings and reviews that positively influence consumers’ online impulse buying behavior (Tariq et al. 2019 ). Background factors like information (i.e., social media information and labeling), individual (i.e., health consciousness and purchase attitude), and social (i.e., self-perceived vegetarian and environmentalism), impact consumers’ intention of purchasing organic food (Li and Jaharuddin 2021 ). Lim and Lee-Won ( 2017 ) discovered that dialogic retweets (i.e. retweeting user mentions addressed to an organization), are more persuasive than monologic tweets because dialogic retweets lead to a higher level of subjective norms, more favorable attitudes toward behavior, and greater intention to adopt the behavior advocated by an organic food organization in the messages. On the other hand, a lifestyle of health and sustainability influences the attitude of customers toward sustainable consumption and therefore, consumers’ sustainable consumption behavior (Matharu et al. 2021 ). Furthermore, regarding western imported food products in a Muslim country, Bukhari et al. ( 2020 ) found that product attributes, price, self-concept, brand trust, personality, and religiosity are positively correlated with consumers’ purchase intention in Pakistan.

This research stream concluded that the information contained in social media can influence the intention to consume green or organic products. Nevertheless, it is known that there is an intention-behavior gap, identified between positive attitudes toward organic products and actual purchase behavior (Padel and Foster 2005 ; Pearson et al. 2011 ). Thus, further research could explore, by means of mixed methods, how social media could reduce the intention-behavior gap.

3.2.3 Research stream on “social media and food tourism” (Factor 10)

The tenth research stream explains 1.54% of the variance of keyword relationships, indicating a research stream of tenth-highest distinction. While image (58 mentions) and destination, (content) analysis and instagram (30 mentions each) were the most often listed keywords, the research stream was best represented (in terms of factor loadings) by the keywords destination (FL = 0.645) , followed by authenticity. Place, related to travel, culinary, image, wine, and gastronomy constitute the remainders of the top ten keywords. These 10 keywords in this research stream confirm the application-oriented topics from the perspective of food tourism. Therefore, this research stream clearly addresses the topic “social media and food tourism.”

Representative publications of this research stream (see Table 7 ) reference each more than 2 keywords of factor 10. Regarding theories and conceptualizations, although this research stream has not a leading theory, they analyze food tourism and its relationship with social media. Thus, an inclusive and shared research discourse can be determined.

A closer look at these articles (selected by maximum number of referenced keywords) provides insights about the methods applied and types of insights gained from this research discourse (Table 7 right columns). These articles address food tourism related to social media use by means of content analysis, semi-structured interviews, and literature review, among others. The articles analyzed social media content, as well as antecedents and contingencies regarding social media and food tourism.

The use of social media to increase destination image or to promote a food destination is the main focus of this research stream. Over the past two decades, the key themes regarding food tourism were authenticity through food experiences, the offer of unique food experiences, food tourism and sustainability, as well as the use of food destination in marketing; nevertheless, Okumus ( 2021 ) suggests that future studies should focus on the role of social media in promoting food tourism experiences, among others. In this regard, Filieri et al. ( 2021 ) found that on Instagram, users communicate their destination brand love through photographs of some destination attributes (e.g. people, food, weather, etc.) accompanied by specific positive emotions (e.g. attractiveness, pleasure, amazement, etc.) or providing emotional support during a destination crisis. Besides, Ramirez-Gutierrez et al. ( 2021 ) concluded that in TripAdvisor, tourists’ communications of gastronomic experiences contain both aesthetic and personal values.

Other studies in this research stream reveal social media strategies and how specific online tools can help to promote food destinations. While memories influence positively the loyalty for a food destination (Bachman et al. 2021 ), the description of food on TikTok brings an effect of intention to travel and to obtain information, impacting the affective image of a destination and increasing potential tourists’ attention (Li et al. 2020 ). As a tool to advertise food-based cities, Yu and Sun ( 2019 ) recommend the use of Instagram to attract the attention of consumers including hashtags to reach more users and to generate interactivity. Moreover, the endorsement of celebrity chefs on social media can help to promote cities as culinary destinations by giving provocativeness (i.e. attractiveness and customer engagement), credibility (i.e. trustworthiness, leading, and reliability), and supportiveness (i.e. localism and match-up) (Demirkol and Cifci 2020 ). Besides, Vrontis et al. ( 2021 ) suggest that the support interactions between destination managers and stakeholders by using online technology; can be transformed into a word-of-mouth source that could affect perceptions and sustainable development of the territory producing the place brand.

Finally, by conducting a content analysis of 600 Instagram images containing the hashtag #fitspiration, Tiggemann and Zaccardo ( 2018 ) found that most images of women contained objectifying elements, and only one body type: thin and toned. Authors point out that although ‘fitspiration’ images may be inspirational for viewers, they contain elements that could affect negatively the viewer’s body image.

This research stream analyzed the role of social media in food tourism on Instagram, TikTok, and Tripadvisor. Further research might explore the use of further social media tools in order to enrich this research stream with comparisons among tools and countries.

3.3 Broader communication issues

This research cluster analyses online communications regarding Alternative Food Networks (AFN), online communication, and eating disorders, as well as the analysis of online food related data by means of novel tools. This cluster includes the research streams “sustainable food communication online,” “analysis of online food related data,” and “online communication and eating disorders.”

3.3.1 Research stream on “sustainable food communication online” (Factor 6)

Explaining the 2.66% of the variance of keyword relationships, this research stream of sixth-highest distinction was best represented (in terms of factor loadings) by the keyword sustainability (FL = 0.727) , followed by agriculture, although network and sustainability were the most often listed keywords (68 and 60 mentions) . The remainders of the top ten keywords, were the words innovation , system, economy, chain, alternative, supply, and farmer . The remaining 24 keywords confirm the focus on sustainable food communication. Thus, this research stream clearly addresses the topic “sustainable food communication online.”

The most representative articles of this research stream (see Table 8 ) were selected by the highest number of keywords referenced, in this case, each more than 6 keywords of factor 5. Without a leading theory, most of the articles rely on the concept of AFN, and local food networks or systems. They address the topic of sustainable food and online communication, linked both by means of content analysis, data mining, semi-structured interviews, surveys, and participant observation, among others. Media content is investigated, as well as antecedents and contingencies regarding sustainable food communication online.

Regarding the antecedents of the use of internet communications, in this research stream, it was found that initiators and participants of AFN are individual shoppers and nascent activists that organize strategies, build networks, and use internet communications to extend their reach, and expand linkages to emancipatory spaces of global and social justice movements (Schumilas and Scott 2016 ). Online spaces (e.g. websites and social media platforms) supplement the socio-material connections in AFNs’ offline spaces providing a ‘virtual reconnection’ or an additional real for reconnection (Bos and Owen 2016 ). By using social media, participants in citizen-drive initiatives (e.g. for waste-prevention) create collaborative local networks to develop green/sustainable consumption practices (Campos and Zapata 2017 ). Exploring communications with the hashtag #sustainability on Twitter, Pilar et al. ( 2019 ) discovered six communities (i.e. Environmental Sustainability, Sustainability Awareness, Renewable Energy and Climate Change, Innovative Technology, Green Architecture, and Food Sustainability), and 6 hashtags related to sustainability (i.e. innovation, environment, climate change, corporate social responsibility, technology, and energy).

Regarding the use of online communications by producers and intermediaries, it was found that producers establish consumers’ trust by satisfying the consumer´s desire for safe food, and that they use social media to construct food materiality and the perception of this materiality in order to fit the consumer´s ideal of freshness (Martindale 2021 ). Besides, Kummer and Milestad ( 2020 ) discovered that social media is used as an advertising tool in the growing practice of box schemes (i.e. a type of locally oriented distribution system used by community supported agriculture (CSA) farms or enterprises) in Europe. Other works in this research stream studied the motivations for buying sustainable agricultural products (e.g. Ashtab and Campbell 2021 ).

Further research could explore not just the use of social media for communication, but also how these communications influence behavior-change and sustainable food consumption among their participants.

3.3.2 Research stream on “analysis of online food related data” (Factor 7)

The seventh-highest distinction research stream explains 2.14% of the variance of keyword relationships. In terms of factor loadings, the keywords (sentiment) analysis (FL = 0.74) , and tweet are the main keyword representing this research stream . The top ten keywords were led by twitter with 102 mentions, followed by (sentiment) analysis and datum with 35 mentions each. Halal, detection, topic , mining, classification, and sentiment are the remainders of the top ten keywords. Analyzing all keywords, it can be confirmed the use of words related to methods for the analysis of online data. Therefore, this research stream addresses the topic of “analysis of online food related data.”

Although the representative publications (see Table 9 ), with more than 5 keywords of factor 7, do not share a leading theory, they share a research discourse by analyzing Twitter communications. With three articles led by the same author, articles in this research stream address the analysis of online data related to food by means of social network analysis, data mining, and sentiment analysis. Media content, antecedents, and contingencies regarding the analysis of online food related data are analyzed.

Many studies in this research stream emphasize the use of different methods and tools to analyze online communication data. By using opinion mining techniques, Mostafa ( 2019 ) analyzed food sentiments regarding halal food expressed on Twitter detecting a generally positive sentiment toward halal food, as well as a heterogeneous group of halal food consumers divisible by concern for food authenticity, self-identity, animal welfare attitudes, and level of religiosity. By using social network analysis Mostafa ( 2021 ) examined the structure, dynamics, and influencers in halal food networks, founding that few social mediators or “influencers” control the diffusion of information through a small world preferential attachment network that links digital halal food consumers. The same author analyzed Wikipedia’s clickstream data in order to study users’ halal food navigation strategies on Wikipedia servers discovering that only a few articles or “influencers” within close-knot communities control the flow of halal food information (Mostafa 2022 ).

As well the use of geocoding has an important place in this research stream. By using geocoding, Rimjhim et al. ( 2020 ) analyzed data from Twitter and Wikipedia, to know how the conversational discourse on online social networks vary semantically and geographically over time finding that although there is a significant homogenization in online discussion topics, despite geographical distance, it is not similar across all topics of discussion and location. Zhang et al. ( 2020 ) explored individuals’ emotions and cognition of cultural food differences among people from South and North China by using the machine learning method of natural language processing (NLP) by posting on the Zhihu Q&A platform the question “What are the differences between South and North China that you ever know?” They found that food culture is the most popular difference among people from North and South China and that individuals tend to have a negative attitude toward food cultures that differ from their own. Analyzing geo-located and reciprocal user mention and reply tweets over the course of the 2016 primary and presidential elections in the United States, Koylu ( 2019 ) found that the discourse was divided between election-related discussions of the political campaigns and candidates, and civil rights, being the last the more dominant. Ullah et al. ( 2021 ) propose an architecture to store data to accelerate the development process of the machine learning classifiers using rule-based and logistic regression.

The contribution of this research stream to the social sciences lies, without doubt, in the novel approaches to analyzing online data. Further research could extend the use of these tools in their research or propose new ones. And, since most studies analyze text, it is recommended the development of tools to analyze images.

3.3.3 Research stream on “online communication and eating disorders” (Factor 9)

The ninth research stream explains 1.76% of the variance of keyword relationships. Blog and site were the most often listed keywords (62 and 38 mentions), but in terms of factor loadings, the stream was best represented by the keywords discourse (FL = 0.557) , followed by blog. An inspection of the remaining seventeen keywords, confirms the eating disorders approach. Hence, this research stream studies the topic of “online communication and eating disorders.”

Without a leading theory, representative publications of this research stream (see Table 10 ) analyze online communication related to eating disorders, sharing the same discourse. Articles address online communication related to eating disorders by means of virtual ethnography, netnography, and interpretative phenomenological analysis, among others. They analyze web and social media content as well as antecedents and contingencies regarding online communication and eating disorders.

Some studies in this research stream explore online narratives, experiences, and discussions regarding eating disorders (ED) online. By using content analysis of ‘food porn’ websites and blogs, as well as participant observation and interviews regarding ‘pro-anorexia’ websites, Lavis ( 2017 ) found that participants “eat” in, and through cyberspace, beyond and among bodies. Cinquegrani and Brown ( 2018 ) explored narratives of experiences and conceptualizations through online social media forums regarding the eating disorder Orthorexia Nervosa (ON), a fixation on eating proper food accompanied by excessive exercise. The authors found three main narratives: pursuit (i.e. the individuals are on a quest to ‘better’ themselves), resistance to the illness narrative, and the recovery (i.e. after accepting the ‘illness narrative’). The authors suggest considering ON a lifestyle syndrome embodied in social and cultural processes. By analyzing TikTok posts containing the hashtag (#) EDrecovery, Herrick et al. ( 2021 ) concluded that creators share their personal experiences with recovery by using popular (or viral) video formats, succinct storytelling, and the production of educational content.

Other studies explored online conversations in order to understand how individuals confer value and meaning to ‘healthy’ eating behaviors. Consumers are active co-producers of value and meaning regarding the impact of green products on their health and the environment, and their understanding of health and sustainability is affected by cultural meanings and pleasure, which lead them to attribute additional unsubstantiated traits to certain products ascribed as virtuous (Yeo 2014 ). Examining the visual and textual framings of ‘superfoods’ on social media, it was found that superfoods are a marker of idealized identity mobilized by using postfeminist, neoliberal, and food justice discourses (Sikka 2019 ), the healing potential of veganism is derived from a passionate investment of the self that redefines young women’s ways of being in the world (Costa et al. 2019 ).

In sum, this research contributes to the understanding of the complexity of eating disorders by uncovering the processes and meanings of eating disorders and how they are portraited online. Some studies in this research stream also discloses how individuals confer meaning to healthy eating behaviors and how an idealized identity ascribes virtuous attributes to some foods. Further research could explore if this initially idealized identity of healthy foods leads to future eating disorders.

3.4 Service industry discourse on “food online reviews in the service industry” (Factor 2)

One research stream was found in this cluster, which possesses an integrative discourse: “food online reviews in the service industry.” This research stream explains 9.87% of the variance of keyword relationships, indicating a research stream of second-highest distinction. While word-of-mouth and satisfaction were the most often listed keywords (77 and 60 mentions), the research stream was best represented (in terms of factor loadings) by the keywords hotel (FL = 0.868) , followed by ( online) reviews. Performance and (consumer) satisfaction related to restaurant, service, hospitality constitute the remainders of the top ten keywords. An inspection of the remaining 49 keywords confirms this focus on application-oriented topics from the perspective of the service industry. Thus, this research stream addresses the topic “food online reviews in the service industry.”

Representative publications of this research stream (see Table 11 ) reference each more than 10 keywords of factor 2. Regarding theories and conceptualizations, most of the articles refer to electronic word of mouth (e-WOM) and online review. Thus, an inclusive and shared research discourse can be diagnosed.

A closer look at these articles (selected by maximum number of referenced keywords) provides insights about the methods applied and types of insights gained from this research discourse (Table 11 right columns). These articles address online food reviews as an indicator of service quality, linking both by means of regression analysis or structural equation modeling. Antecedents, consequences as well as contingencies of online food reviews are analyzed.

In a narrow effects perspective, Kim et al. ( 2016 ) found that the number of online reviews correlates with restaurant performance. By analyzing online customer comments on Yelp.com, Bilgihan et al. ( 2018 ) found that a focus on selected menu offerings, food, ambiance, and service can create buzz in social media. Addressing the broader scope of tourism industry, Abrudan et al. ( 2020 ) studied customer review scores on booking.com to analyze the impact of different hotel facilities on customers’ overall ratings, confirming the special relevance of food service for hotel ratings. Another analysis of online reviews from 68 online platforms however did not confirm such a special relevance of food services, with hotel attributes, including quality of rooms, Internet provision, and building to impact hotel performance most (Phillips et al. 2017 ). Altogether, these works highlight the importance of food reviews as drivers of positive consumer feedback primarily in the restaurant industry but less so in the broader hospitality industry.

Other works critically reflect on the antecedents of consumers’ online food reviews. Investigating consumers´ personal drivers to write food reviews, Liu et al. ( 2020 ) found that personal motivation, and especially altruism, influences the posting of negative consumer online reviews. Cambra-Fierro et al. ( 2020 ) discovered that a company’s corporate social responsibility can steer consumers to identify and link themselves to brands generating buy-back and recommendation behaviors. These works thus reveal behavioral drivers on the creation of food reviews both at the consumer and company level. Finally, several works investigate contingencies regarding the effects of food reviews: Zinko et al. ( 2021 ) found that reviewer-submitted (food) images influence consumers’ attitudes only when they are consistent with the review text. This contingency perspective on the effects of food reviews in social media seems the more needed given that previous research, as outlined above, came to divergent conclusions about the impact of online food reviews on consumers’ service ratings.

With most articles in this research stream addressing written food reviews online on different social media, further research might analyze not just the use of written messages, but as well the use of images in online reviews.

3.5 Patterns of the overall research system

The previous analyses were restricted to the level of single research streams. To complement this perspective, the relationship between research streams is analyzed by means of a network analysis. Hereto, a multidimensional scaling of the linkages of the top-ten keywords per factor is calculated and visualized in Fig.  2 . While the size of nodes displays the relative mentioning frequency of each keyword, their positioning within the figure informs about their overall centrality and connectedness. Although the largest nodes or most often mentioned keywords are communication, diet, risk, and obesity , this chart indicates a clear focality on the keyword communication .

Network Visualization of Factors´ Top-10-Keywords Relations

The closeness of single keywords indicates their relationship with each other, and with other research streams. To ease interpretation, each factors’ keywords are marked in different colors. Thus, the distance between keywords stemming from different research streams reveals not only their closeness but as well interconnections between their respective research streams. For example, obesity and diet are closely linked to advertising . This implies close connections between the discourses on “Online Tools for Healthy Diet Intervention Programs” (factor 1, marked in red) and “Online Food Advertising Exposure” (factor 5, marked in dark green). While these two discourses assume a different actor perspective, zooming into consumers’ or marketers’ interest, they nonetheless discuss related topics from a complementary perspective.

In contrast, a large distance among words or factors shows a weak relationship or missing links between research streams; for example, a large distance can be observed among keywords related to “Sustainable Food Communication Online” (factor 6) and to “Social Media and Food Tourism” (factor 10). This shows that these two research streams are not yet strongly related. Future research might contribute by linking those different perspectives together.

Furthermore, the location of keywords related to “Social Media and Mental Disorders” (factor 8) at the outer skirt of the figure reveals that this research stream is a truly peripheral discourse. Finally, the method-driven discourse on “Food Online Reviews in the Service Industry” (factor 2) is clearly more related to the core discourse, to twitter and the different methods of analysis.

4 Conclusions and implications

This study presents a bibliometric analysis of the research conducted regarding food and social media within the social sciences. By using co-word analysis, this study evaluated 413 main Keywords contained in 1356 articles by means of factor and social network analysis. The study shows that the number of studies conducted on this topic has increased rapidly, indicating a growing interest in food and social media. Besides, the results reveal four main research clusters (i.e. Psychological Research Realm, Action-Oriented Research, Broader Communication Issues, and Service Industry Discourse) containing the main topics of research.

The Psychological Research Cluster analyzes online tools for healthy diet intervention programs, the use of apps for service purposes or dietary change, the exposure of children and adolescents to influencer marketing in YouTube videos, as well as the antecedents and consequences of social media use and mental disorders. The Action-Oriented Research cluster analyzes online food risk communication, behavioral intention and buying online, as well as the use of social media for food tourism. The Broader Communication Issues cluster studies sustainable food communication online, online food related data, and the relationship between online communication and eating disorders. Finally, the Service Industry Discourse cluster explores online reviews in the service industry.

Future research could transfer topics in order to have a broad scope of research. For example, the insights gained on the discourse “food and the use of apps” (factor 12), could be transferred to studies regarding “online food risk communication” (factor 3). A further alternative is to transfer the potential of the sophisticated text-mining as method of analysis used in the discourse “analysis of online food related data” (factor 7) enriched by picture mining, in order to address research questions related to how food is perceived and marketed (e.g. factor 6). Another possibility is to intersect, for example, the topic of factor 1, which addresses more positive psychological constructs in detail, and factor 8, which addresses topics more related to clinical psychology. Further integration of theoretical models stemming from psychology (e.g. factor 1 and factor 2) into the practically oriented joint discourse on service industry setting (Factor 2). More theoretical foundations might help to generate broader insights. Other studies could compare target groups (e.g. comparing adults, adolescents, and children), in different countries, regarding the same topics (e.g. fast-food intake while consuming social media). Additionally, the analysis of texts or reviews could be enriched through the analysis images, or by developing tools to analyze images. Other ideas are summarized in Table 12 , and elaborated in the discussion of the single research streams above.

By suggesting future research directions, this study help scholars to find relevant future topics of research in this area of study. The findings presented in this study can be beneficial for marketing and business scholars, as well as companies, and organizations interested in understanding the relationships between food and social media.

Data availability

On request.

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91 Food & Beverage Essay Topic Ideas & Examples

🏆 best food & beverage topic ideas & essay examples, 🔍 good research topics about food & beverage, 📌 interesting topics to write about food & beverage, ❓ food and beverage questions.

• The Food and Beverage Industry Role in the Tourism The essay begins by looking at the food and beverage industry in general, and then proceeds to look at the main sectors of the industry.
• Food and Beverage Management The mission of the department is to provide food and beverage that meets highest standards so that they can keep a competitive edge in the hotel industry. We will write a custom essay specifically for you by our professional experts 808 writers online Learn More
• Hospitality Management: Food & Beverage Service The art of catering goes beyond providing food and beverages and extends to the ambience of the eating place and the quality of service received.
• Eco-Friendly Packaging for Food and Beverage Industry This product was chosen because of the direct impact of the quality of food products on the health of ordinary people regardless of the region of living of country of origin.
• Food and Beverage Development This paper focuses on how food production and food consumption has affected the eating habits and led to the introduction of junk foods because of the production and consumption factors.
• The Food and Beverage Sector There is no doubt that there are many substitutes to this industry and the best investors can do is to try to retain the available market by offering quality services.
• The Supply and Demand for Energy Foods and Beverages One should pay attention to the following issues: 1) the growing demand for energy foods and drinks; 2) willingness of people to pay attention to the health effects of such products; 3) the increasing number […]
• Food and Beverage Server’s Duties and Dependencies As a food and beverage server, my relationship with the facilities department where I work would primarily consist of coordination regarding the disposal of material waste, bringing in the proper types of beverages that customers […]
• Ethical Behavior as to Returned Food and Beverages One of the biggest problems is that the liberalization of the policies related to the return of the food and beverages led to the abundance of the products that should be returned.
• Food and Beverage Services: “Moments of Truth” Dinning experience has a great impact on the perception of service and restaurant brand image, customers’ loyalty, and repeat visitors.”Moments of truth” influence the decision to visit a bar or a restaurant again and customers’ […]
• Food and Beverage Brands’ Expansion and Site Selection In this paper, the researcher focused on investigating and comparing the conventional factors influencing site selection and the innovative indicators used in site selection in the food and beverage brands within the Kingdom of Saudi […]
• Sustainable Business of Food and Beverage Delivery The array of key information includes the adherence of a specific manufacturer to sustainable development goals in the food industry, as well as the work ethics and equality policies.
• Organizational Performance in the Food and Beverage Industry in Nigeria The following is an analysis of the research carried out in Nigeria about the impacts of the exterior atmosphere on the performance of an institute in the food and beverage industry.
• Food and Beverage Control Software In such a way it is possible to find out which items are the most gainful, and if the wastage of food is low enough for managers to reach the profitability targets.
• Starbucks Corporation’s Food and Beverage Management It is a vital, and may well be the vital, resource factor for marketing.the case study suggests hat the term service could cover service industries, as well as in the colloquial use of the term, […]
• Food & Beverage Choices and Health Impacts This written report presents the analysis of my Meal Summary Report, Nutrients Report, and Food Groups and Calories Report to reveal the factors affecting my food and beverage choices, compare the latter with SuperTracker’s Recommended […]
• International Food and Beverage Business in Africa The large population in the country is a source of labor; human resources and natural resources combined has made the country’s economy being the 37th in the world and second in Africa according to 2007 […]
• Chicago Food and Beverage Company: Human Resources This is the case because the targeted workers should be empowered and guided to pursue their roles diligently. This model also guides companies to balance the salaries of their expatriates.
• Careers in Lodging and Food and Beverage Industries Responsibilities of the baker are limited to “bakeshop, which is found within the food service establishment, while banquet manager, on the other hand, plans and oversees parties, banquets, and conventions, which the restaurant s/he works […]
• Food and Beverage Industry Analysis The Coca-Cola Company and Pepsi Cola are among the biggest and most profitable firms in the world. The world head quarter of the Coca-Cola Company is located in Atlanta, Georgia while the head office of […]
• Job Description of a Food and Beverage Manager in Australia It’s the role of the food and beverage manager to ensure that the employees abide to this and others international hotel regulations.
• Food and Beverage Industry: Supply Chain Management
• Challenges to Scale for Food and Beverage Makers in the USA
• Case Analysis: Forecasting Food and Beverage Sales
• Food and Beverage Sector in the Consumption Service
• Challenges and Trends Facing Food and Beverage Industry
• Factors That Affect the Food and Beverage Offer in Food Outlets
• Food and Beverage Television Advertising Exposure and Youth Consumption
• Corporate Social Responsibility: Food and Beverage Industry
• Linder Effect Hold for Differentiated Agri-Food and Beverage Product Trade
• Error Management Culture Among Food and Beverage Employees in Deluxe Hotels
• Examining CSR Disclosure Strategies Within the Australian Food and Beverage Industry
• Expanding Food and Beverage Industry to Drive Global Carboxymethyl Cellulose Market
• Environmental Management Beyond the Firm Boundaries: Dutch Food and Beverage Firms
• Analysis of the Food and Beverage Companies in Singapore
• Reasons for Food and Beverage Cans Market Grow
• Analysis of the Food and Beverage Consumption Characteristics
• Food and Beverage Industry: Competitor Analysis
• Link Between Food and Beverage Management and Operation Performance Monitoring
• Relations Between Food and Beverage Policies and Purchasing Practices
• Food and Beverage Product Reformulation as a Corporate Political Strategy
• Forecasting Food and Beverage Sales: The Vintage Restaurant
• Global Antioxidants Market Advances in Food and Beverage Industry
• How Roger Enrico Transformed the PepsiCo Into a Food and Beverage Giant
• Industry-Specific Social and Environmental Reporting: Australian Food and Beverage Industry
• Sources of Strategic Human Capital for Multinational Food and Beverage Firms
• The Role of the International Food and Beverage Management
• Food and Beverage Multinationals in a Peripheral European Country
• Multinational Firms, Investment, and Trade-In Canada’s Food and Beverage Industry
• Nestle, the World’s Largest Food and Beverage Company
• Analysis of the Reasons for Singapore’s Food and Beverage Growth
• Strategic Human Resource Management: Lion Food and Beverage Company
• Structure, Costs, and Performance in Canadian Food and Beverage Industries
• Control and Generation of Technology in European Food and Beverage Multinationals
• Analysis of the Food and Beverage Manufacturing Industry
• Three Trends That Have Affected the Food and Beverage Industry
• Understanding Different Food and Beverage Production and Service Systems
• Work-Based Learning Experience: Analysis Food and Beverage Sector
• Depiction of the Purpose of Food and Beverage Cost Control
• Applying the Rea Diagram for Food and Beverage Company
• Resistance to Change in Food and Beverage Department
• What Challenges and Trends Does the Food and Beverage Industry Face?
• What Are the Food and Beverage Service Standards?
• What Are the Responsibilities of the Director of Food and Beverage?
• What Is Food and Beverage Reverse Logistics?
• What Are the Characteristics of the Food and Beverage Industry?
• What Is the Future of the Food and Beverage Industry?
• What Is the Reach of Food and Beverage Television Advertising?
• How Is the Food and Beverage Market Changing?
• Who Is the Largest Food and Beverage Company in THE US?
• Do Trends in the Food and Beverage Industry Affect Body Mass Index and Obesity?
• What Are the Trends in Food and Beverage Industry?
• What Is the Responsibility of the Food and Beverage Department?
• What Are Your Suggestions for Improving Food and Beverage Management?
• What Is Forecasting in Food and Beverage Management?
• How Is the Performance of the Food and Beverage Industry Monitored?
• What Are the Skills Required in Food and Beverage Management?
• What Is the Role of Food and Beverages in Tourism?
• What Is the Main Role of Human Resources in the Food & Beverage Industry?
• How Is the Metal Food and Beverage Cans Market Developing?
• What Are the Innovations in Food and Beverage Packaging?
• What Is the Demand for Peracetic Acid From the Food and Beverage Industry?
• What Are the Basic Managerial Functions in Food & Beverage Service Management?
• What Is the Classification of Food and Beverage?
• What Are the Duties and Responsibilities of Food and Beverage Server?
• How Is Food and Beverage Cost Control at the Hotel Done?
• What Are the Objectives of a Food and Beverage Management Business Report?
• What Are the Achievements of the Global Food and Beverage Antioxidants Market?
• Which Organization Deals With Food and Beverage Control?
• What Is the Role of the Food and Beverage Service Industry?
• How Can the Food and Beverage Control System Be Improved?
• Chicago (A-D)
• Chicago (N-B)

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• Dining out in China is experiential, with restaurants thriving by catering to diverse consumer needs and leveraging technology, social media, and exclusivity to expand.
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Daxue group

• Daxens - sensory research
• Doxaganda - branding in China
• DaxLr - growth acceleration
• Sinonym - chinese brand naming
• China business podcast