food and beverage services research paper

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• v.15(Suppl 1); 2021 Dec

Food service industry in the era of COVID-19: trends and research implications

1 School of Hospitality Management, The Pennsylvania State University, State College, PA 16802, USA.

2 Department of Food and Nutrition, Yonsei University, Seoul 03722, Korea.

Coronavirus disease 2019 (COVID-19) is a new type of respiratory disease that has been announced as a pandemic. The COVID-19 outbreak has changed the way we live. It has also changed the food service industry. This study aimed to identify trends in the food and food service industry after the COVID-19 outbreak and suggest research themes induced by industry trends. This study investigated the industry and academic information on the food and food service industry and societal trends resulting from the COVID-19 outbreak. The most noticeable changes in the food industry include the explosive increase in home meal replacement, meal-kit consumption, online orders, take-out, and drive-through. The adoption of technologies, including robots and artificial intelligence, has also been noted. Such industry trends are discussed in this paper from a research perspective, including consumer, employee, and organizational strategy perspectives. This study reviews the changes in the food service industry after COVID-19 and the implications that these changes have rendered to academia. The paper concludes with future expectations that would come in the era of COVID-19.

INTRODUCTION

Coronavirus disease 2019 (COVID-19) captured public attention as a new type of respiratory disease. The World Health Organization (WHO) announced it as a pandemic on March 11, 2020 [ 1 ]. Although most people heard “corona virus” for the first time, humans have experienced seven types of coronaviruses, including severe acute respiratory syndrome (SARS) in 2003 and Middle East respiratory syndrome (MERS) in 2015. COVID-19, like SARS and MERS, is a respiratory disease with similar symptoms. Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the virus that causes COVID-19, is genetically 80% similar to SARS-CoV, the virus that causes SARS [ 2 ]. The viruses for COVID-19, SARS, and MERS are stable and active at 4 °C [ 3 ]; they become inactive as the temperature increases to 65–70°C [ 4 ]. As COVID-19 is transmitted via droplets, aerosols, and direct contact, wearing masks and washing hands with disinfectants are the foremost defensive methods. The COVID-19 virus also come out of human activities like breathing, speaking, coughing, and sneezing [ 5 ]. As a major route of COVID-19 transmission is droplets, human contact should be avoided to prevent infection. Furthermore, eating food together, such as Korean soup and side dishes, should be avoided, because the droplets can transmit the COVID-19 virus [ 6 ]. Therefore, foodservice operations have been one of the primary sources of COVID-19 transmission. During the COVID-19 era, people look for healthy foods and adopt behaviors to prevent virus transmission. The COVID-19 outbreak has resulted in novel trends in the foodservice industry.

FOOD SERVICE INDUSTRY TRENDS

Emergence of covid-19 new normal era.

The COVID-19 outbreak brought a situation that people have never experienced. A new word, “a new normal era after COVID-19,” was coined. The era of Before Corona (B.C.) was separated from that of After Corona (A.C.) because people can never get back the days before the pandemic struck. The word “new normal” was used at the time of the global economic crises initiated by the US sub-prime mortgage during 2007–2008 [ 7 ]. A new normal indicates a new norm for the economic standards. The new normal After Corona described the situation as H (healthcare), O (Online), M (manless), and E (economy at home): healthcare as heightened public interest in health and safety; online as a core essence of digital economies with the advantages of artificial intelligence, big data, and 5G; manless as a proven safety and efficiency during the course of prevention from coronavirus transmission; economic activities at home while staying long hours at home [ 7 ]. Such “new normal” also took place in the food service industry.

Non-human contact (untact) purchasing

Most of all, an explosive increase has been observed in the foodservice purchasing using untact methods. Contrary to the dramatic decrease in the sales of restaurants and institutional foodservices, Starbucks Korea experienced a sales increase of 32% from January to February 2020, compared to the same months in 2019 [ 8 ]. In fact, the orders made via Siren contributed to a 25% increase in terms of the purchase number, compared to the previous year [ 9 ]. The outcome explains consumers’ intention to use untact services to minimize human contact, which will be expanded in the future. Since the order could be made online, the drive-through pick-up of the ordered products increased, from café, bakery, and fast foods to all kinds of restaurants, including even Sish-shop [ 10 ]. McDonalds expanded drive-through stores in the US and China, which resulted in a double-digit increase in sales in September 2020, compared to the same month of 2019 [ 11 ].

Explosive increase in home meal replacement (HMR) and meal-kit

One of the segments that has benefitted most from the COVID-19 outbreak is the meal-kit and HMR products [ 12 ]. While people stay at home, they care more about health and have time to cook. In the US, the sales of meal-kit products in 2020 became 2 times higher than in the previous year [ 13 ]. The major players in the meal-kit industry, Blue Apron, HelloFresh, and Home Chef, experienced a 49% increase in the number of customers. The meal-kit products satisfy the needs of a variety of customers, including vegan, gluten-free, children, and patients with diabetes [ 14 ]. In Korea, since the COVID-19 outbreak, the sales of meal-kit brands have rapidly increased, while offline retail brands rushed into the meal-kit segments with the names of Simply Cook (GS Retail), ChefBox (Hyundai Department Store), Yorihada (Lotte Mart), Gourmet 494 (Galleria), and Peacock Meal Kit (E-mart) [ 14 ]. The delivery of online order food and HMR food services increased by 77.5% in 2020, compared to the previous year [ 15 ]. Further, people are more concerned about health and look for healthy foods. Consumers purchased more high-protein salads with low calories, health-protection HMR, and fresh ingredient meal-kit [ 16 ].

Acceleration of food tech

COVID-19 resulted in the acceleration of food technology. Robotics in foodservice operations has been expanded significantly. Manless cafés, such as Briggo in USA, Lounge X in Korea, and Chowbotics in California, are its good examples [ 17 , 18 , 19 ]. Chowbotics is the first manless café to purchase fresh produce. Cooking robots work at various positions, such as making hamburgers in a fast-food chain (Miso Robotics in White Castle Burger in California), working at a pasta kitchen (DaVinci Kitchen, Germany), and serving in chicken restaurants (Robert Chicken, Korea) [ 20 , 21 , 22 ]. Moley is the first robot to cook gourmet cuisines using artificial intelligence techniques [ 23 ]. Robotics has also been applied to serving (Royal Palace, Netherlands) and deliveries (PepsiCo's, USA) [ 24 , 25 ]. TUG, as a delivery robot for patient meals at the Reading HealthPlex in Pennsylvania, reduced labor costs by 80% [ 26 ]. The UVD Robotics Techniques have been utilized to prevent COVID-19 transmission, while Blue Ocean Robotics played a role in disinfection at the Heathrow International Airport, UK [ 27 ].

New government project

In Korea, the Ministry of Agriculture, Food and Rural Affairs (MAFRA) launched a new project called “Korean Eating Culture Improvement” in May 2020 [ 6 ]. The project aimed to change Koreans' eating behavior of sharing cuisines, which can cause diseases that are transmitted via droplets [ 28 ]. Thus, COVID-19 can be transmitted through such food-sharing behavior. To accomplish this change, MAFRA proposed three activities: one-person portion meal setting, sanitary management of spoons and chopsticks, and employees wearing masks. The project spread all over the country. Authorities of respective provinces supported the restaurants that abided by the above-mentioned activities by rendering certification to the restaurants. The project is expected to construct a safe eating culture with a high level of safety among Koreans.

RESEARCH IMPLICATIONS

COVID-19 has drastically changed the world, and many believe that some of those changes may last even after the pandemic is over [ 29 , 30 ]. This reality and future expectations certainly apply to the food service industry as well. This study discusses the kinds of research implications that can be drawn from these changes and future expectations. Such changes can be related to the behaviors and perceptions of consumers and employees, as well as the strategic responses of food service businesses. Considering these primary constituencies of the food service industry, this study attempts to provide meaningful research implications related to COVID-19.

Consumer perspectives

Consumer confidence in dining-in.

Consumers of food service businesses have been through and will continue to undergo tremendous changes due to COVID-19. First, due to lockdown or heavy restrictions on in-dining food services during the pandemic, consumers have been unable to enjoy in-dining experiences, either in a complete or at least a partial manner [ 31 , 32 ]. Even in the absence of government restrictions on the in-dining food service, many consumers were and are reluctant to dine out in a confined food service setting, because of the possibility of COVID-19 transmission [ 33 ]. Moreover, although the vaccination rate is significantly increasing, some consumers either refuse inoculation, thus avoiding dining out, or do not feel safe to dine out in a confined place even after getting vaccinated [ 34 , 35 ]. This lingering concern is understandable because of the high level of uncertainty regarding COVID-19 and its vaccines, especially among the general public [ 36 ]. Accordingly, it is important to understand the real consumer confidence in dining in food service establishments as the COVID-19 development continues and how such confidence can be boosted from the perspective of food service management.

Therefore, food service researchers should pay close attention to the status of consumers' confidence in dining at food service establishments. An important aspect of this examination would be a constant or timely update because since everyone is experiencing this type of pandemic for the first time, how people psychologically recover from and respond to this event is unknown. In particular, as vaccination rate accelerates globally, consumer confidence may recover quickly in a non-linear fashion, or it may first recover quickly but later possibly stall at a certain level due to a particular group of consumers who are either too concerned about the possibility of full recovery or skeptical of vaccination programs, which raise legitimate empirical questions for the food service industry.

Next, the food service business should have a better understanding of how they can improve consumer confidence in in-dining food services. There are various ways that can be implemented to boost consumer confidence in this matter, such as cleaning and sanitizing, restructuring the dining table layout to ensure social distancing, requiring employees and customers to wear face masks, installing transparent plastic panels at the counter and/or between tables, and minimizing human interactions (e.g., use of an electronic tablet for menu ordering or even robots to take orders). Restaurant businesses need to understand which practices to prioritize or emphasize because they do not have unlimited resources to implement them all. An efficient allocation of resources is essential for the food service industry to achieve a more desirable level of profitability because they have a tight profit margin. Furthermore, even when all or most of the possible implementations are feasible and can be done, proper prioritization of these implementations can go a long way to enhance consumer confidence in in-dining services more effectively, which can directly or indirectly impact the establishment's or brand's image, and consumer loyalty and revisit intention eventually.

Accordingly, researchers in the food service literature are recommended to explore, first, the practices that restaurant businesses should consider implementing to improve consumer confidence in in-dining services. In addition, it would be interesting to investigate differing degrees of consumers' perceptions of the importance of such practices to assist the food service business to prioritize relevant practices more efficiently and effectively, especially in terms of resource allocation. It would also be critical to study how to disseminate the information of those practices to the target markets (i.e., a marketing strategy). Some potential questions to answer in this matter may include which marketing media should be used, which practices or messages should be emphasized, and how these messages should be delivered (e.g., with more detailed information in an educational format or with more visual representations of actual practices). To accomplish these research goals, researchers should seek responses from consumers as primary data by utilizing a survey method in an observational or experimental manner. Laboratory experiments and follow-up field studies are desirable. In addition to examining the main effects of the aforementioned factors, researchers would be encouraged to test potential moderating factors such as gender, age, perceptions of COVID-19, having children, pre-existing health conditions, tendency to general risks, and so on in relation to some characteristics of consumers, but also food service types (e.g., fast food, full-service, etc.), franchised vs. independent, size of the food service establishment, managerial abilities, location of the business, and so on in relation to the business characteristics. Understanding these contingent boundaries will help untangle the proposed main relationships among the mentioned factors in a more detailed and comprehensive way.

Untact service

Another interesting topic is the contact-free service, which can be represented by the marketing term “untact service” in the recent literature (from 2017 to be precise) [ 37 ]. The untact service for the food service business includes drive-through, curbside pickup, and delivery. All these forms of untact services have become a norm in the food service industry during the current pandemic and they have helped many businesses in the industry survive the global health and economic crisis [ 38 , 39 ]. It would be important to reveal, first, how untact services have been helped the industry, for example, its impact on sales and profits, and second, how such positive impacts have been heterogeneous contingent on various factors from both consumer (e.g., gender and age) and business perspectives (e.g., location and type of food service).

Post-pandemic change

Lastly, food service researchers should pay attention to which mentioned factors would stick around even after the pandemic is over. Many believe that these new norms during the pandemic, such as the popularity of untact services, fewer interactions with service providers (e.g., service by robotics), and some cleaning and sanitization practices will continue even after the pandemic. However, it is clearly an empirical question that needs to be examined and verified with actual data and rigorous analyses. Even when consumers may anticipate that these practices will still be important and influence their decisions even after the pandemic, their perceptions can certainly change once the pandemic is over. Although we strongly believe that some of these practices will still be important even after the pandemic, which practices will be significant remains to be answered empirically. Understanding the matter will help the food service business to develop more appropriate and timely strategies.

Employee perspectives

Employee turnover.

Similar to consumers of the food service business, employees of the food service business have been experiencing tremendous changes and hardships. For example, the current pandemic has revealed a high level of risk embedded in the food service industry regarding job security from an employee's perspective. Due to the lockdowns and rigid restrictions on food service operations due to COVID-19, countless food service employees have been laid off or furloughed or have experienced a reduced number of working hours. In fact, the food service industry has been one of the hardest hits in the economy by the pandemic [ 33 ]. Since the food service industry is known for a high turnover rate of employees, the added hardship on employees in the industry has been devastating for both employees and employers. Some employees are considering switching to a new career in a different industry because of this hardship, which requires the business to decide what it needs to do to retain and recruit talented employees during and after the pandemic. This is a critical issue even for those employees who stay with their company because they have witnessed a high level of risk and uncertainty in the food service business, which is volatile to external forces such as the pandemic. The industry needs to convince its employees that the industry is still viable and has great potential to grow in the future, especially after the crisis.

Employee attitudes

Understanding the factors during the pandemic that significantly influence employees' various perceptions, such as satisfaction, commitment, and loyalty, is critical for food service management. Employee perceptions play an important role in shaping employees' intention to remain with the company at the end [ 40 , 41 ]. Despite the extreme operational hardships faced by food service employers during the pandemic, they still need to ensure that they show their employees that they care for them and are trying their best to provide them with job security during the pandemic. Such practices can go a long way, possibly making significantly positive impacts on employees' satisfaction with and commitment to their organization because employees also understand how challenging those practices can be during the current pandemic. This kind of positive impact may eventually have an aftereffect on organizational culture and its long-term success. Accordingly, it is suggested that researchers may explore how employers' caring and transparency in their communication influence employees' perceptions and behaviors during the pandemic.

Human resources allocation

Another important issue that needs to be considered regarding employees in the food service business during the pandemic is human resource allocation. As discussed earlier, the food service business had to adapt to a new business environment during the pandemic by extensively implementing untact services, such as drive-through, curbside pickup, and delivery. In doing so, many food service businesses had to deviate from their traditional in-dining services. Such a dramatic transition requires reallocation of human resources to different tasks and related new training. It would be interesting to research how this reallocation impacted the food service business and, in particular, employees' various perceptions about their job and productivity. Additionally, an extension of this research to the post-pandemic period should be encouraged because such investigations may reveal possible lasting benefits (e.g., improved human capital with multiple capabilities) and/or drawbacks (e.g., dissatisfied employees with too many or less focused job responsibilities) in a long-term manner.

Organizational strategy perspectives

Corporate social responsibility strategy and more.

In addition to the customer and employee perspectives, there are potential research topics from an organizational strategy perspective that need attention. Food service businesses can implement or might have implemented certain organizational strategies to cope with the pandemic. Accordingly, it is important for researchers to investigate which business strategies (e.g., corporate social responsibility [CSR], franchising, internationalization, and diversification) generate positive benefits during the pandemic. For example, previous studies found that a firm's engagement in CSR activities can enhance employees' commitment to and satisfaction with their organization, improve their productivity, and reduce turnover intention [ 42 , 43 ]. Furthermore, many previous studies have found that CSR positively impacts consumers [ 44 ] and firm performance [ 45 ]. Hence, it can be interesting to see whether the food service business's CSR investment during the pandemic has the same positive impact (e.g., on customers, employees, and/or business performance). Interestingly, some may argue that an investment in CSR activities during the pandemic has an opposite impact (i.e., a negative impact) on employees, customers, and performance because such investments will cause the cash flow of the business to become even tighter in an extremely difficult time, thus making the probability of its survival slimmer.

It would also be interesting to explore whether a company's pre-existing reputation of being socially responsible can generate business benefits during the pandemic. The pre-existing reputation is not about the company's investment in CSR during the pandemic, but rather the reputation that had already been built before the pandemic, which does not put any burden on the company during the pandemic. In such a case, the pre-existing reputation of CSR may be more likely to provide benefits because it does not cost the company anything during the pandemic, and CSR investment has been found to provide insurance-like protection during a crisis [ 46 ]. All these CSR issues can be viewed as part of or equivalent to environmental, social, and governance (ESG) issues, which have gained considerable attention from the corporate world and public. Although the ESG concept was created and has been used more in the investment context, due to its extensive popularity in the contemporary corporate world, the term is now used more interchangeably with a broader concept, such as CSR. Accordingly, the suggested research topics are timely, even in the context of ESG. However, since all these suggested research issues are empirical questions, they require empirical verification.

Furthermore, similar research studies apply to other business strategies, such as franchising, internationalization, and various diversification strategies. In particular, since the food service industry employs the franchising strategy the most in the U.S. economy [ 47 ], significant implications of implementing the strategy may exist in relation to the pandemic. Researchers are encouraged to find such implications.

Unit-level analysis

The organizational strategies mentioned above are mainly at the firm level and not at the individual unit level. A majority of the food service business consists of independent and small businesses. Hence, inspecting the effects of the characteristics of the food service business at an individual unit level during the pandemic can provide meaningful and practical implications for food service business owners and operators. An example of such characteristics can be the type of financing. In contrast with large corporations, small food service businesses rely heavily on personal connections to finance (e.g., raising capital from family members and friends) in addition to formal financing (i.e., loans from financial institutions). These different types of financing may imply certain capabilities or lack of them in owners and consequently suggest some anticipatory outcomes during the pandemic, such as a high likelihood of suffering from poor performance and business failure. Thus, these issues should be researched to gain a better understanding of the food service business during the COVID-19 pandemic.

The COVID-19 pandemic has resulted in tremendous changes in the overall economy and society. In the food service industry, the ways people order has shifted mostly to non-human contact or untact methods, such as online orders and drive-through orders. The consumption of particular products, such as HMR and meal-kit, has also increased explosively. Cooking and serving robots have been extensively adopted to prevent human contact and reduce labor costs. The COVID-19 situation has also caused serious issues in environmental protection. In terms of research implications, COVID-19 poses great challenges and provides opportunities. This study discusses these challenges and opportunities from three perspectives: consumer, employee, and organizational strategy perspectives.

Conflict of Interest: The authors declare no potential conflicts of interests.

Author Contributions:

• Conceptualization: Ham S, Lee, S.
• Investigation: Ham S, Lee S.
• Supervision: Ham S, Lee S.
• Writing - original draft: Ham S, Lee S.
• Writing - review & editing: Ham S, Lee S.

• Open access
• 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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MPK designed the study and oversaw the data collection and analysis. JS and ML collected the data. EP carried out the data analysis and wrote the first draft of the manuscript. All authors read and approved the final manuscript.

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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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Restaurants and robots: public preferences for robot food and beverage services

Journal of Tourism Futures

ISSN : 2055-5911

Article publication date: 22 April 2022

Issue publication date: 23 May 2023

The hospitality industry in developed countries is under pressure due to labor shortages and it is likely more food and beverage operations will have to be automated in the future. This research investigates the public’s perceptions of the use of robots in food and beverage operations to learn about how the public perceives automation in food and beverage.

Design/methodology/approach

Data were collected from a survey disseminated online in 12 languages, resulting in a sample of 1,579 respondents. The data were analyzed using factor analysis and OLS regressions.

The data also reveal that generally positive attitudes toward the use of robots in tourism and hospitality is a strong indicator of positive attitudes toward the use of robots in an F&B setting. The data also illustrate that the public’s perception of appropriateness of the use of robots in F&B operations is positively related to robots’ perceived reliability, functionality and advantages compared to human employees.

Research limitations/implications

The implications illustrate that the public seems to be generally accepting robots in food and beverage operations, even considering the public’s understanding and acceptance of the limitations of such technologies.

Practical implications

The research suggests that a critical element in terms of incorporating automation into future food and beverage operations is encouraging consumers to have generally positive attitudes toward the use of robots in hospitality and tourism industries.

Originality/value

This survey is based upon the data gathered in multiple countries to learn about how individuals perceive the use of robots in food and beverage operations, illustrating the attitudes that will assist or hinder the automation of this service industry.

• Attitudes toward robots
• Acceptance of robotic technologies

Ivanov, S. and Webster, C. (2023), "Restaurants and robots: public preferences for robot food and beverage services", Journal of Tourism Futures , Vol. 9 No. 2, pp. 229-239. https://doi.org/10.1108/JTF-12-2021-0264

Emerald Publishing Limited

Copyright © 2022, Stanislav Ivanov and Craig Webster

Published in Journal of Tourism Futures . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode .

Introduction

By 2020, only a century after the invention of the word “robot” ( NPR, 2011 ), robots were responsible for much manufacturing ( Ross et al. , 2018 ) and are increasingly involved in the service economy ( Belanche et al. , 2020 ; Wirtz et al. , 2018 ). However, it has only been in recent years that robots have been increasingly used to provide services to hospitality guests ( Ivanov and Webster, 2019a ). The integration of automation technologies in tourism and hospitality is inevitable because of the advancement of technology ( Mihelj et al. , 2019 ) as well as demographic factors ( Webster, 2021 ) that limit the human labor available for service industries. Here we discuss the use of robots in hospitality and explain several hypotheses with regard to perceptions of the use of robots in food and beverage operations. Then, we explain the data collection on the topic, analyze the data with regard to the hypotheses and conclude explaining how the findings inform the incorporation of robots into food and beverage operations in the future.

Currently, there is a growing body of research on robots in tourism and hospitality (see, for example, Murphy et al. , 2017 ; Samala et al. , 2020 ; Tung and Au, 2018 ; Tuomi et al. , 2021 ), including in food and beverage operations (e.g. Berezina et al. , 2019 ; Cha, 2020 ; Lee et al. , 2018 ; Fusté-Forné, 2021 ; Hwang et al. , 2020 ; Omar Parvez and Cobanoglu, 2021 ; Seyitoğlu and Ivanov, 2020 ; Seyitoğlu et al. , 2021 ; Tuomi et al. , 2019 ; Zemke et al. , 2020 ; Zhu and Chang, 2020 ). Previous studies have shown that robots can be used to automate dirty, dull, repetitive and dangerous jobs as well as create entertaining and novel experiences for tourists. Specifically, investigating the use of robots for food and beverage is critical since such operations are labor-intensive, critical to the hospitality industry, and typically suffer from high turnover rates. The automation of the delivery of food and beverage services may alleviate many of the headaches that managers in hospitality face and such automation has already been used in the food industry to reduce labor costs ( Ivanov and Webster, 2019b ) and to provide better services ( Kincaid and Baloglu, 2005 ). While there is a great deal of speculation about issues linked with the incorporation of automation technologies into food and beverage operations (see, for example, Berezina et al. , 2019 ), much of what is known about the perceptions of managers and customers based upon empirical data is from small samples of semi-structured interviews ( Seyitoğlu et al. , 2021 ; Tuomi et al. , 2021 ), case studies ( Seyitoğlu and Ivanov, 2020 ), or single-country surveys ( Cha, 2020 ; Hwang et al. , 2020 ). Thus, understanding the current perceptions of the public with regard to automated hospitality services is necessary to understand how to better implement fuller automation into hospitality operations, something that will be needed in the not-so-distant future due to labor shortages and the increasing effectiveness of the technology.

This research note aims to identify the F&B tasks that customers consider as appropriate for robotization and the drivers of the perceived appropriateness of robot use in F&B operations. More specifically, the paper looks at the role of perceived robot reliability, functionality, advantages and disadvantages compared to human employees, and demographic characteristics of respondents and their impact on the perceived appropriateness of robot use in F&B operations. In this way, the research will help managers address the factors that hinder or facilitate the implementation of the robot in F&B operations. Functionality of a robot shows that it possesses the technical features (e.g. sensors, actuators), software and overall design that allow it to implement its intended tasks (e.g. cook food, make a cocktail, serve dish) while a robot’s reliability shows how well it will perform these tasks. That is why, previous studies have found that the reliability and functionality of robots are significant components of the trust in robots ( Tussyadiah et al. , 2020 ). Additionally, reliability and functionality are positively related to the intentions of tourists to use robots ( Tussyadiah et al. , 2017 ). The perceived advantages and disadvantages of robots compared to humans show how respondents perceive the potential provider of a particular tourism/hospitality service (a robot or a human employee). The perceived advantages of robots compared to human employees are found to have a positive relationship with the attitudes toward the use of robots in a hotel; the perceived disadvantages of robots have a negative effect, but it is washed out when the general attitudes toward robots are included in the regression models ( Ivanov et al. , 2018 ). Positive relationship between the perceived advantages and the perceived appropriateness of robot application in museums was recently reported by Webster and Ivanov (2022) . The same study showed that the respondents who had more positive attitudes toward robots considered that robots are appropriate for implementation in museum context. Attitudes are a significant driver of customer acceptance of service robot as well ( Zhong et al. , 2021 ).

Perceived robot reliability is positively related to the appropriateness of robot use in F&B operations.

Perceived robot functionality is positively related to the appropriateness of robot use in F&B operations.

Perceived robot advantages compared to human employees are positively related to the appropriateness of robot use in F&B operations.

Perceived robot disadvantages compared to human employees are negatively related to the appropriateness of robot use in F&B operations.

The attitude toward service robots in travel, tourism and hospitality is positively related to the appropriateness of robot use in F&B operations.

Methodology

To investigate the public’s perceptions of the use of robots in travel, tourism and hospitality, a global survey was run from March 2018 to October 2019. The survey was developed in English and subsequently translated into 11 other languages to make it accessible to as many people globally as possible. The survey questions were developed with the Technology Acceptance Model ( Venkatesh and Davis, 2000 ) in mind while looking specifically into the question of how technology’s incorporation into the tourism and hospitality ecosystem would be expected to be perceived by consumers of tourism and hospitality services. Questions pertaining to the advantages and disadvantages of robot labor were adapted and expanded from Ivanov et al. (2018) .

To ensure that translations were accurate, native speakers translated the survey based on the original English language version. The survey was sponsored, allowing for researchers to offer incentives for participation in the survey, to ensure higher response rates. The incentive for participation was five gift cards that were given to those who completed the survey and wished to be considered for a drawing enabling each person who had indicated interest to win a 100$ gift card. The funds for the incentive were provided by a research firm that supported the research to learn about consumer perceptions of automation in the industry. Permission was given by a US university’s IRB board, permitting the survey to be launched and it was disseminated via social media and emails globally. The authors’ social media and email contacts were the primary means by which the survey link was disseminated, with colleagues encouraged to forward the link to others.

This paper’s sample includes 1,579 respondents who answered the questions related to the application of robots in food and beverage operations and had answered all questions asked in the survey. Since it was disseminated online, it would be impossible to estimate how many people saw the link but refused to take the survey, although there was a significant number who took part in the survey and terminated the survey at some point. Those that did not answer the relevant questions for this analysis were removed from the sample for this particular analysis. Table 1 illustrates the major characteristics of the sample.

To learn about perceptions toward the use of robots in food and beverage operations, several questions were asked, with responses being recorded with a seven-point scale. Respondents to the survey were asked, “ Please indicate which activities do you personally consider as appropriate to be performed by service robots in travel, tourism, and hospitality ,” with responses of different activities in the food and beverage operations of hospitality. Table 2 illustrates the questions asked and the mean responses to the questions, based upon the seven-point scale. The scale consisted of one extreme “1 = Extremely inappropriate” and the other extreme “7 = Extremely appropriate.” Several questions were also asked with regard to the reliability and functionality of robots as well as questions with regard to the advantages and disadvantages of robots relative to human employees, using a seven-point Likert scale.

In regressions, demographic data were added in the hopes that they would give insight into the perceptions of the appropriateness of using robots in food and beverage operations. The gender, age and education levels of the respondents were used as independent variables. However, in addition, the respondents perceived economic well-being and reported that frequency of travel was also added to the regressions. The respondent’s subjective perception of economic well-being was added instead of a measure for their income levels, as income levels are a sensitive issue tending to lead to a refusal to answer. Such monetary data are hard to compare against respondents from many different countries. In addition, travel frequency was added, as it was suspected that frequent travelers may have a different relationship with hospitality industries than those who travel less frequently.

Table 2 illustrates that respondents were most receptive to robots taking orders for room service ( m  = 5.37), followed by cleaning the table ( m  = 5.19), delivering food and drinks in room service ( m  = 5.16), and providing information about the menu ( m  = 5.14). The respondents were least receptive to robots cooking food ( m  = 3.77). These data show that respondents see some differences between the various tasks that they feel are appropriate for robots to do concerning food and beverage. The paired samples’ t -test values showed that the differences between the mean responses to taking orders for room service, cooking food and the other tasks were statistically significant at p  < 0.001. The data illustrate that the respondents generally seem to believe that cooking food is the task that is best left to humans while taking orders, cleaning tables, supplying information, and delivering food to guests could be delegated to robots.

Exploratory factor analysis was also employed and the results are shown in Table 2 , illustrating that the data could be condensed into five meaningful factors. Table 3 presents the discriminant validity matrix. The results show that the constructs have high internal consistency and discriminant validity.

For a full analysis of the perceived appropriateness of robot application in the food and beverage industries, multiple OLS regressions were performed and the results are reported in Table 4 . The first model used two independent variables – reliability and functionality of robots. The model seems to have relatively high levels of predictability, with an adjusted R-squared of 0.324, as Table 4 illustrates. Also, perceptions toward the reliability and functionality of robots are systematically and positively related to the perceived appropriateness of using robots in food and beverage operations, regardless of the control variables added.

The other regressions are also insightful, illustrating the additional power of the regressions given the added independent variables. The second model illustrates that the addition of two independent variables that indicate perceptions of the advantages and disadvantages of robots compared to human employees is also positively related to the dependent variable. The subsequent models demonstrate some interesting findings, showing that the addition of the variable to measure a general attitude toward robots seems to have two substantial impacts. First, the independent variable that indicates a generally positive attitude toward robots increases the adjusted R-squared value to 0.41 (Models 3 and 4). Another interesting finding is that the addition of the demographic data suggests that only the age of respondents is associated with the dependent variables (Model 4). Most of the demographic variables failed to show any relationship with the dependent variable, apart from the age of respondents, showing that the younger respondents were more accepting of the use of robots in food and beverage operations.

In general, the regressions illustrate that the perceived functionality and reliability of robots are positively associated with the perceived appropriateness of the use of robots for food and beverage operations, providing support to hypotheses H1 and H2 . Furthermore, the findings show that the perceived advantages of robots compared to employees are strongly and positively related to the perceived appropriateness of their application in the F&B context in all three models with that variable, while the perceived disadvantages are negatively related (the variable was reverse coded); thus supporting H3 and H4 . Moreover, the attitude toward the use of robots in travel, tourism and hospitality is positively related to the perceived appropriateness of robot use in F&B, hence supporting H5 . Therefore, the respondents accept the use of robots in F&B operations when they trust the reliability and functionality of the robots, their advantages over human employees, and when they have generally positive attitudes toward robots in tourism, while the perceived disadvantages of robots decrease respondents’ acceptance of service robots in F&B.

Discussion and conclusion

The findings illustrate a great deal in regard to the perceptions of the use of robots in food and beverage operations. The results show that one of the hardest things to sell to the public will be that cooking will be done by robots. While previous research has researched scenarios in which robots were involved in food production and delivery ( Seo and Jee, 2021 ), any concerns about specific tasks done by robots in the scenarios were not explored. Thus, the findings in this current research illustrate a hesitancy of the public to accept robots doing the specific task of cooking, since the methodology allowed for an assessment of the consumers’ acceptance of using technology for specific tasks in a food and beverage ecosystem. This also stands in contrast with previous research that was based upon the viewpoints of scholars and robot manufacturers, as Berezina et al. ’s (2019) exploration of the topic. It may be noted that there may be a commonly held belief among the public that the cooking of food requires not just the human’s ability to mechanically manipulate and create foods but some sort of spiritual/artistic element. Overcoming this may be easier than one would expect if the cooking of food is presented as something that is fun to watch and can result in a tasty result. Demystifying the cult of the celebrity chef will face an uphill battle, though, as it may be that the public has a love for their celebrity chefs, seeing them as entertainment ( Caraher et al. , 2000 ; Demirkol and Cifci, 2020 ), so it may be that robotic chefs may also be used as entertainment. This feeds into a larger issue with regard to automation versus authenticity in service industries ( Seyitoğlu, 2021 ), with different markets and different consumers demanding automation or authentic service provision by humans.

Consistent with previous studies, the general attitudes toward robots are associated with the particular use of robots in service industries (see, for example, Malchus et al. , 2013 ; Ivanov et al. , 2018 ). This suggests that to understand whether a person accepts the application of robots in a specific context (e.g. in F&B operations), it is necessary to learn about a person’s general attitude toward robots.

Additionally, the results show that gender does not play a role in influencing attitudes toward the use of robots in food and beverage operations. While much of the research (see, for example, Hudson et al. , 2017 ; Katz and Halpern, 2014 ; Pochwatko et al. , 2015 ) suggests that gender conditions attitudes toward robots, the findings in this research suggest that food and beverage operations may be quite different from many other applications of robots, without having substantial gender differences in perceptions. The data also suggest that there is a generational rift, illustrating that younger people are more accepting of robotic technologies in F&B operations. As such, this research fits neatly into the current research that looks into how different age groups perceive automation technologies (see, for example, Ezer et al. , 2009 ; Xu et al. , 2015 ), although some findings contend that age differences may not account for many of the differences in perception of robots ( Backonja et al. , 2018 ). At any rate, it seems that the generational rift and perceptions of people of different ages warrant further investigation.

The main limitation of this research is that data collection was finalized just before the outbreak of the COVID-19 pandemic. It may be that the global pandemic has changed the public’s perceptions of service robots in F&B operations. That is why future research needs to reassess the perceptions to check whether they have changed. Future research should explore a great deal more regarding the use of automation technologies in food and beverage since there is a predictable shortage of available labor in developed countries ( Webster, 2021 ). Future research may focus on the willingness to pay for robot-delivered F&B services and the role of robots in creating memorable F&B experiences.

All-in-all, this research note illustrates that the further automation of food and beverage will occur upon the foundation of a population that seems to recognize the strengths and weaknesses of more automated operations. In terms of theory and methodology, the findings illustrate the value of breaking down operations into tasks that may be automated. Such a methodology illustrates that some specific tasks are deemed by the public as being more acceptable for robots to do. This suggests that future research should investigate tasks, rather than scenarios with robots involved, as the public seems to have a somewhat different view of the use of robots based upon tasks, rather than grand scenarios in which a person has to imagine being served food. What is especially interesting is that the findings highlight that the public seems to recognize the disadvantages of robots in such operations but it does not seem to undermine the general attitude toward the appropriateness of the use of such technology. In terms of actionable elements from the research, it seems that cultivating a population that has generally positive attitudes toward service robots will play a helpful role in terms of allowing for robots to become more integrated into food and beverage operations. However, there is also an indication that the public, in general, will be willing to accept greater automation of food and beverage services depending upon what the task is, meaning that some tasks will not just be easier to automate but will also have less consumer resistance to the use of robots for such tasks.

Sample’s characteristics

Exploratory factor analysis