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International Journal of Contemporary Hospitality Management

ISSN : 0959-6119

Article publication date: 26 May 2022

Issue publication date: 26 July 2022

Online food delivery (OFD) has witnessed momentous consumer adoption in the past few years, and COVID-19, if anything, is only accelerating its growth. This paper captures numerous intricate issues arising from the complex relationship among the stakeholders because of the enhanced scale of the OFD business. The purpose of this paper is to highlight publication trends in OFD and identify potential future research themes.

Design/methodology/approach

The authors conducted a tri-method study – systematic literature review, bibliometric and thematic content analysis – of 43 articles on OFD published in 24 journals from 2015 to 2021 (March). The authors used VOSviewer to perform citation analysis.

Systematic literature review of the existing OFD research resulted in six potential research themes. Further, thematic content analysis synthesized and categorized the literature into four knowledge clusters, namely, (i) digital mediation in OFD, (ii) dynamic OFD operations, (iii) OFD adoption by consumers and (iv) risk and trust issues in OFD. The authors also present the emerging trends in terms of the most influential articles, authors and journals.

Practical implications

This paper captures the different facets of interactions among various OFD stakeholders and highlights the intricate issues and challenges that require immediate attention from researchers and practitioners.

Originality/value

This is one of the few studies to synthesize OFD literature that sheds light on unexplored aspects of complex relationships among OFD stakeholders through four clusters and six research themes through a conceptual framework.

• Online food delivery
• Sharing economy
• Systematic literature review
• Bibliometric analysis
• Content analysis

Acknowledgements

The authors thank three anonymous reviewers, the guest editor, and the editor-in-chief for their critical and valuable comments in developing the manuscript in stages.

Shroff, A. , Shah, B.J. and Gajjar, H. (2022), "Online food delivery research: a systematic literature review", International Journal of Contemporary Hospitality Management , Vol. 34 No. 8, pp. 2852-2883. https://doi.org/10.1108/IJCHM-10-2021-1273

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CONCEPTUAL ANALYSIS article

Online food shopping: a conceptual analysis for research propositions.

• Department of Business Administration, Cheng Shiu University, Kaohsiung, Taiwan

Shopping foods online is different from shopping other things online. To stimulate more thinking and enrich potential future research imagination, this paper reviews for online food shopping features, offers a commentary, and proposes future research directions. The propositions include the following: (1) The design and implementation of online food shopping (eco)systems should engage the consumers and other stakeholders to co-create collective and social values; (2) A better fit between technologies’ and food businesses’ natures could generate better applications for online food shopping; (3) A business model with sound finance systems becomes the core of a healthy online food ecosystem; (4) The interaction and transformation between online (virtual) and offline (virtual) food businesses determines the dynamic development of future food shopping.

Introduction

Most studies on online shopping focus on the implications and benefits of e-commerce. This focus is expected to increase as more people are pushed toward shopping online in a bid to avoid crowded shopping malls for fear of contracting the dreaded COVID-19 virus. A gap in the literature, however, is that while the topic is rife with studies detailing how online shopping works, there is limited research on shopping foods online, which is inherently with very different characteristics from buying other kinds of commodities via the World Wide Web. Nonetheless, food is one of the most common products for the mankind, and so are with great impact for human’s online shopping life. A critical analysis for in-depth understanding of the special attributes that online food shopping has can facilitate the construction of a precise (for stakeholders’ needs) and high-quality (for stakeholders’ safety and satisfactions) online food shopping ecosystem. This paper presents a conceptual analysis aimed at explicating the significant themes within the current literature. The review will conduct critical propositions reflected from these studies to propose future research directions. The academic review is significant to both researchers and online food stores as people across the world start embracing online shopping more than ever before.

Background Descriptions

Before beginning the conceptual analysis with literature review, a broader background discussion is needed. Practically, the broader background constitutes: e-commerce platforms, consumer preferences and attitudes, marketing approaches, and packaging and delivery considerations.

E-Commerce Platforms

Silva et al. (2017) define e-commerce platforms as the set of technologies designed to help online businesses to manage their marketing, sales, and operations. Wei’s et al. (2018) study sought to examine the purchase intention of fruits among online shoppers. The authors argue that the past few years have seen the emergence of online purchase platforms for fruits, a trend that has significantly advanced e-commerce development and improved the quality of human life. Although their study sought to investigate consumers’ purchase intention, the results reveal that compared to other products, the e-commerce platforms for fruits did not play a major role in influencing a buyers’ purchase decision. On the contrary, the success of fashion products and electronics is dependent on how online customers perceive their e-commerce platforms ( Huete-Alcocer, 2017 ). For example, customers are less likely to purchase luxury fashion products from a poorly designed website ( Kang et al., 2020 ) and ( Buckley, 2016 ). Thus, while there are limited studies on the differences between buying food and other products online, at least the current studies evidence that e-commerce platforms do not play a significant role in influencing buyers’ purchase decisions.

Consumer Preferences and Attitudes

Kim Dang et al. (2018) study on consumer preference and attitudes regarding online food products examines how the Internet has changed people’s food-buying behaviors. The study is significant because it establishes the underlying consumers’ concerns with regards to food safety information, especially for online food products. Compared to other products, consumer preferences and attitudes toward buying food online differs in that the perceived risks and information quality do not play major roles in influencing their buying behavior ( Li and Bautista, 2019 ; Sanchez-Sabate and Sabaté, 2019 ; Zieliñska et al., 2020 ). Kim Dang et al. (2018) study relies on a cross-sectional study conducted in Hanoi, Vietnam. The findings are reliable as they are based on responses gathered from over 1736 customers through face-to-face interviews. While the preferences and attitudes toward buying food online differ from buying other commodities, Kim Dang et al. (2018) note that the laws governing e-commerce in Vietnam are the same. As such, the findings provide practical advice to online food retailers and the Vietnam government on how to implement appropriate legislation with regards to trading online food products.

Martínez-Ruiz and Gómez-Cantó’s (2016) study emphasizes that using the Internet to seek food service information has now become a common practice among people today. More people than ever before have positive attitudes toward finding information about food online ( Martínez-Ruiz and Gómez-Cantó, 2016 ; Maison et al., 2018 ). Also, people are more likely to search information about food on the Internet than any other product or service ( Hidalgo-Baz et al., 2017 ; Whiley et al., 2017 ; Wong et al., 2018 ). However, Kim Dang et al. (2018) study found that a significant number of consumers were unconcerned about the accuracy of the evidence regarding food safety they found online in selecting food products on the Internet. The conclusions drawn from the current article review produces practical pieces of advice to consumers buying food online as well as the food retailers selling food over the Internet.

Marketing Approaches

Rummo et al. (2020) examine the relationship between youth-targeted food marketing expenditures and the demographics of social media followers. The authors sought to establish the extent to which teenagers follow food brands on Twitter and Instagram by examining the relationships between brands’ youth-targeted marketing practices and the overall percentages of adolescent followers. The study provides evidence showing that unhealthy food brands, especially fast food and sugary drink have more adolescent followers on social media ( Rummo et al., 2020 ). These study results are consistent with Salinas et al. (2014) findings which show that unhealthy food products enjoy a higher market base than the healthy ones. The high percentage of teenage followers is concerning among health experts mainly because most of the advertisements from these companies are biased and do not highlight the unhealthy consequences associated with eating these foods. Compared to other products, food companies are often not required by regulations to highlight their negative consequences ( Salinas et al., 2014 ). For example, cigarette and alcohol companies are mandated to disclose their effects of use on all marketing materials ( Gravely et al., 2014 ). Consequently, with the ubiquitous use of social media by teenagers, young people are more exposed to food and beverage advertising which occurs across multiple digital channels.

The failure to address digital advertising when formulating policies makes it harder to governed youth-targeted food marketing. Food products are often marketed using the general techniques and approaches applied in other products and services. Juaneda-Ayensa et al. (2016) note that food marketing topics such as market segmentation, strategic positioning, test marketing, branding, consumer research, targeting, and market entry strategy are highly relevant. Moreover, food marketing is affected by the major challenges that affect conventional markets such as dealing with perishable products whose availability and quality varies as a function of the current harvest conditions ( Hongyan and Zhankui, 2017 ). However, Topolinski et al. (2015) note that the value chain in food marketing is particularly important because it highlights the extent to which sequential parties within the marketing channel add value to the final product. According to Linder et al. (2018) processing new distribution options often provides additional opportunities available to food marketers to provide the final consumer with convenience. However, when overhead costs such as marketing and processing are added they result in significantly higher costs ( Lou and Kim, 2019 ).

Demographics play an essential role in food marketing almost more than any other product. According to Qobadi and Payton (2017) , food companies must utilize statistical demographics to understand the inherent characteristics of a population. For food marketing purposes, such knowledge can help firms develop a better understanding of the current market place as well as predict future trends ( Isselmann DiSantis et al., 2017 ). For example, with regards to the current market, food companies interested in entering a new market with sports drinks might first study the overall number of people between the ages of 15 and 35, who would constitute a particularly significant market. In such cases, most food companies often prefer shifting their resources toward products consumed by a growing population. As such, the success of the marketing strategy employed by a food company is contingent on how good it studies the demographical makeup of its target market.

Packaging and Delivery Consideration

One of the primary consideration food consumers take into account when making a purchase decision online involves packaging and delivery. According to Chen et al. (2019) , the modern consumer is more interested in food products that utilize sustainable packaging and delivery systems. Hu et al. (2019) add that most customers today are more focused on recyclable packaging systems. Grace (2015) further notes that sustainability is one of the primary sustainability attributes online shoppers look for. For example, over 33% of online consumers believe that packaging and recyclability are more important to them when ordering food items online ( Gutberlet et al., 2013 ). Additionally, 13% of online shoppers cite a lack of packaging information available online, which suggests that there is an existing opportunity for e-retailers to increase their sustainability information ( Quartey et al., 2015 ).

As the world continue grappling with the COVID-19 pandemic, online purchases for fresh food is gradually becoming the norm across the world. As such, food producers must be able to adapt accordingly to take advantage of the emerging market. However, the majority of consumers are still concerned about freshness and food waste ( Yu et al., 2020 ). Unlike in a brick-and-mortar store where shoppers can visibly check the freshness of their produce, this is more difficult with home delivery ( Song et al., 2016 ). Thus, brands must try and opt for packaging that can keep food safe and fresh during transit and displays its freshness to re-assure customers. Moreover, to meet sustainability goals, fresh food brands need to balance the use of more sustainable, recyclable materials, with packaging that continues to extend shelf life and avoid food waste.

Conceptual Analysis for Future Research Propositions

The article review shows that sufficient studies have been conducted on online food shopping. As more people start shopping online, the number of articles on online food shopping is expected to increase. However, despite studies on online food shopping and business models remain rife, there are key gaps in research. These gaps are a result of the majorities of the researchers’ focus on highlighting their perspectives and largely ignore those of the consumers and businesses. Moreover, these studies do not consider crisis (e.g., COVID-19 pandemic) when making these future predictions. The forecasts made about future help in developing a better understanding of the various implications of ordering via mobile apps. Also, it provides a background for examining the emerging technologies in online food ordering. As such, the critical propositions reflected in the literature review propose the following four future research directions.

Value Co-creation With Stakeholders

From a business perspective, getting partners and investors on board is not easy and most restaurants tend to stay away from technology. Thus, the preposition made involves conducting research aimed at developing a better understanding of the customer and business’ perspectives. According to Chen et al. (2018) , setting the commission rates with restaurants is a major problem within the online food industry. Moreover, the majority of startups are depended on restaurants to deliver food at the customer’s doorstep ( Onyeneho and Hedberg, 2013 ). Hwang et al. (2020) argue that relying on technology is not the main focus of a restaurant because preparing food is its main core business. As such, even if an investor trusts a food startup, integrating technology within its business process will always be perceived as a high risk. The lack of sufficient evidence on the business’ perspective toward technology and online platforms make it more difficult for rescuers to tailor their studies to generate crucial insights that help in making better business decisions.

One of the problems identified from the consumer’s perspective is that most of the things mentioned in the online food menus are often not available. Instead, they act as click baits designed to entice online users to continue interacting with their platform and marketing content ( Lara-Navarra et al., 2020 ). In rare cases, some clickbait links often forward online users to pages that require them to make payments, register, or even fill in their payment details. Consequently, a significant communication gap exists between consumers and restaurants while shopping on phone and online. While numerous studies examine the purchase intention of food among online shoppers, few highlight the inherent challenges experienced by consumers as they go about their day.

While it is crucial to investigate both perspectives, more studies need to be conducted on the customer ones. This is because most online businesses often find it difficult to deal with customers, but Ho et al. (2014) note that this is usually because they do not see things from the buyers’ point of view. The authors, however, refutes the popular phrase that “customer is always right” and notes that even when they are completely wrong, they can always win. For example, customers can criticize a business online or even refuse to pay their bills. As such, failing to grasp a customer’s perspective can result in a meltdown with them which is always bad business. It is also essential for future businesses to take into consideration the fact that work is much more enjoyable and profitable when people work alongside the customer rather than against them. Thus, conducting more studies aimed at understanding customers can help develop the necessary recommendations to help businesses see things from their point of view.

One of the ways future studies can explore to better understand the customer’s perspective involves exploring the issues related to empathy. Charles et al. (2018) note that empathy does note naturally to most people but it reinforces one’s ability to understand and share the feelings of a customer by placing themselves in their shoes. Future studies should highlight how online businesses can ask questions about how their current and potential customers would feel in different circumstances. Also, future studies must examine how well online businesses can listen to their customers. Afshar Jahanshahi and Brem (2018) notes that the first step in customer relations involves actively listen to them. Finally, future studies must be able to provide recommendations on how online food businesses can grow trust and show respect to their customers. The prepositions made with regards to the business and customers’ perspective provides the background information for future studies. Also, bridging the current research gaps will help business adopt a more effective online model that maximizes customer satisfaction when purchasing foods. Based on the discussions above, this article suggests the following proposition to both identify the gap in the literature and the corresponding future research directions.

Proposition 1: the design and implementation of online food shopping (eco)systems should engage the consumers and other stakeholders to co-create collective and social values.

Technological Nature

Although smartphone apps provide an efficient way to replace the conventional methods of ordering food through a phone call, there lacks sufficient evidence on the implications of placing orders through them. A partial but potentially important reason is the lack of in-depth and broader understanding of the technology per se . Mobile ordering apps have caused a significant change in food delivery and pickup business ( Onyeneho and Hedberg, 2013 ). With more and more retailers and restaurants adopting these technologies, the modern consumer is willing to place fewer delivery and pickup orders through their phones. Instead, they are now opting to utilize mobile apps. Studies aimed at exploring the implications of food delivery apps help in establishing whether it is hurting or assisting the business. Thus, as a restaurant owner, one has to be careful with regards to utilizing third-party services to do business. For instance, apps such as Uber Eats have endless possibilities as they make delivery faster, for both the customers and the business. However, future studies must examine the potential disadvantages to using such third-party services. Firstly, the added cost of a food delivery app may be prohibitive to most customers. For example, the cost of using services like Uber Eats changes how businesses price their meals. In the end, customers are likely to end up paying more. Thus, future studies have to consider this fact when developing recommendations on how businesses can use food delivery apps without undermining their financial positions. Also, these studies will help show how customers are likely to react to a price surges.

Subsequent studies on the implications of ordering food through mobile apps should also focus on the issues relating to control and accountability. Cecchi and Cavinato (2019) note that some customers have complained about being unable to control the food ordering process. For example, once the customer’s food is in the possession of the Uber driver, there is little left for them to do, which is perceived as a bad thing. Also, Isoni Auad et al. (2018) note that customers lack control over how their drivers handle their food. One of the consequences of being unable to control the process is that when a customer’s food is mishandled or ends up late, the restaurant is the one that is held accountable. Finally, with regards to the implications, future studies must monitor their third party service to safeguard their brand’s reputation. As such, subsequent studies need to ensure that they highlight the importance of maintaining an effective brand image. Mao et al. (2018) recommend online food businesses to monitor how long it takes their delivery people to transport their customers’ food to establish whether it is being handled with the necessary care it deserves. However, more studies are required to highlight the customer’s grievance which can easily fall on the businesses when the delivery issues are ignored.

Despite the various implications of using mobile apps to order food online, there are numerous benefits associated with online models. As such, as the growth of online applications continues, the subsequent studies need to add to the existing literature on the benefits businesses are likely to accrue from adopting such technologies. According to Li et al. (2020) , this trend is a result of the numerous benefits associated with using the apps compared to the conventional methods of shopping over the phone or waiting in line. These benefits are 2-fold, they include benefits to the consumer and the restaurants. Firstly, there are numerous consumer benefits of using mobile ordering apps to purchase food.

Consumers across the world are downloading mobile ordering apps at lightning speed. For example, When Chick-fil-A, one of the largest American fast food restaurant chains, released its first official app, it reached first place in the app store in only 3 days after it was launched. Mayordomo-Martínez et al. (2019) note that these apps are popular for four main reasons. Firstly, customers feel that no one is waiting in line or getting put on hold. Secondly, customers can pick up food on the go. Thirdly, customers get the whole menu right at their fingertips, including items they may not have known existed. Finally, most restaurants award patrons’ loyalty reward points. In most cases, these points are easy to track directly through applications and lead to big savings if the customer order frequently.

The restaurant benefits from the mobile ordering apps too. While these apps may be created for the customer, they achieve some important objectives that can greatly help out the restaurant or retail store as well ( Ferguson and Solo-Gabriele, 2016 ). For example, they can handle more orders as is the case with Chipotle, an American chain of fast-casual restaurants, which claims that it is capable of processing six additional orders every hour when placed through a mobile app ( Ferguson and Solo-Gabriele, 2016 ). Moreover, customers are more likely to spend more through an ordering app than in person because they have more time to decide since the entire menu is in front of them and they typically want to score more reward points. Based on the discussion above, this article made the propositions as follow.

Proposition 2: A better fit between technologies’ and food businesses’ natures could generate better applications for online food shopping.

New Business Models and Finance Systems

Although numerous studies have highlighted the various emerging trends in buying food online, most were conducted before the COVID-19 pandemic. As such, future studies need to capture how the pandemic has affected the online ordering industry. Such studies will provide the insights necessary to help the business withstand emerging competition as well as keep up with the ever-changing customer demands and the latest trends and technological advancements. Wang et al. (2020) note that the various responses to the COVID-19 global pandemic will shape the online food delivery industry in 2020 and beyond. Thus, future studies need to identify and critically examine the top online food shopping trends that customers and businesses must remain aware of.

For the better part of the year 2020, global cities have become deserted and shopping malls closed. The restaurant sector is one of the most affected as people are recommended to maintain social distancing and remain at home. As the Coronavirus continue spreading across the world, the pandemic is projected to have more economic implications than undermine global health. Thus, future studies must offer people a glimpse of how lockdowns will affect the online food industry, which is hailed as the future in the restaurant sector. However, even at the current stage of the Covid-19 pandemic lifecycle, several lessons are already emerging from China with regards to how people can cope with the commercial and social disruptions. For example, the pandemic is a key driver for digital technologies.

There are three areas that future studies need to focus on. They include the emergence of digitally enabled delivery systems and consumer comfort with the online food sector. Firstly, the prevalence of digitally enabled delivery systems is expected to grow in the coming years. As such, studies are needed to develop a better understanding of how these online delivery systems will affect the food industry. For example, since the COVID-19 pandemic began, more people than ever before purchase their groceries and other food items online ( Hua and Shaw, 2020 ; Zhang and Ma, 2020 ). This is mainly a result of the growing deployment of digital technologies across the country in an attempt to limit interactions among people and mitigate the spread of the virus. Secondly, subsequent studies must examine the factors affecting consumer comfort within the online world. It is projected that in the next decade, online platforms will transform people’s purchasing behaviors, especially with regards to acquiring food items. Thus, studies are needed to help businesses identify the existing opportunities and mitigate the main threats likely to undermine growth within the online food ordering business. Last but not least, more detailed academic investigation and practical development of payment mechanisms are needed. By its nature, payment mechanisms deal with technological development of payment methods and techniques that constantly try to improve user convenience and experiences of payments. Hence, existing discussions/examinations relied heavily on technical aspects of payment mechanisms (or schemes). However, technologies in business world can generate implications beyond technical dimension, but also in the social, cultural, psychological, and/or even political dimensions (e.g., Yang et al., 2012 ; Koenig-Lewis et al., 2015 ; Nelms et al., 2017 ; Verhoef et al., 2019 ). Hence, interdisciplinary works, either conceptual or empirical, can contribute to the literature for analyzing on more complex dynamics of online payment – not just about the technology/system per se , but also about the ecosystem composed of human, system, and knowledge in it. In sum, the discussions in this section emphasize the importance of business models with high-quality finance (e.g., payment) systems. This article makes the following proposition.

Proposition 3: A business model with sound finance systems becomes the core of a healthy online food ecosystem.

Online-Offline Interactions and Transformations

Shopping food online is viewed by most researchers as one of the biggest disruptions in the supermarket and grocery business models. From smaller stores to fewer discounts and more service and robots, these are just a few of the changes brought about by online platforms ( Kuss and Griffiths, 2011 ). The problem is that few studies are examining whether new disruptions will continue emerging or whether the online food sector has reached maturity. Such studies are necessary because they will help manufacturers and retailers react accordingly. These studies can focus on trying to understand how consumers can purchase food in the future, which can be online or in physical stores or from larger or smaller stores. Some of the research questions can focus on establishing whether future customers will continue buying to take dine at home or consume right on the spot.

Despite the numerous uncertainties, with regards to brick-and-mortar stores, Burgoine et al. (2017) note that they may survive even with the growth and prevalence of online businesses. As such, future studies must explore how changes in e-commerce will affect shoppers and online businesses. Such studies are essential because the current findings on consumer behavior seem to suggest that customers prefer interacting at a physical store by seeing, smelling, and even touching products they find there. Moreover, there is an immediate satisfaction when a customer picks up something. The insights generated from such studies can help retailers establish the inherent need to focus their attention on emotional elements as well as create unique experiences.

Studies focused on making future forecasting will help in understanding how online food platforms can achieve the social roles enjoyed by supermarkets. Otten et al. (2017) note that supermarkets increasingly place their shopper firsts and tap into their individual needs in an attempt to mitigate the rising competition from online shopping. As such, studies must thoroughly analyze the existing demographic data to make future predictions on whether the online food ordering platforms can ever enjoy the same social roles which are currently the precincts of supermarkets. Finally, a sufficient number of studies have predicted that artificial intelligence and robots are likely to take over the responsibilities of human beings within the online food sector. However, while most of these studies make future predictions, they do not take into account how automation and artificial intelligence will help online supermarkets to become more efficient. Thus, subsequent studies should establish a balance between human interaction and automation. This article makes the following proposition according to the discussions here.

Proposition 4: The interaction and transformation between online (virtual) and offline (virtual) food businesses determines the dynamic development of future food shopping.

The majority of studies examining online food shopping have provided sufficient evidence highlighting both the implications and benefits of e-commerce. However, most of these studies generalize all forms of online shopping and ignore the fact that shopping foods online is inherently different from buying other commodities. As such, the comprehensive academic review conducted helps at explicating the significant themes within the current literature. Hence, the critical propositions that reflected from these studies help in proposing the following four future research directions. They include conducting studies to highlight the customer and business’ perspectives, making future predictions, understanding the implications of ordering via mobile apps, and examining the emerging technologies in online food ordering. The academic review and prepositions made are significant to both researchers and online food stores as people across the world start embracing online shopping more than ever before.

Theoretical Implications

To generate theoretical implications in a more holistic and comprehensive level, this article focuses on the inter-relationships between the four propositions derived after our conceptual analysis. To recall, the four propositions are inherently about: engaging stakeholders to co-create values, in-depth understanding of technological natures, well-designed business models and finance systems, and online-offline dynamics. One suggestion for future research directions is to develop a holistic-view, often qualitative investigation of a online food shopping ecosystem that composes of interested stakeholders operating with diverse technological sets embedded in well-designed business models that simultaneously incorporate concerns of both online and offline developments of food shopping. Complexity is a point to be explored but is often oversimplified if we could not take a eco-systematic perspective and analyze for both qualitative-quantitative data sources. For a better theoretical development and practical design, the complexity of a food shopping ecosystem can help identify research questions, sketch phenomenon structures and elements, as well as specify heterogeneous interests for policy making. Following this point, another suggestion for future research directions is to address established issues/research questions through cross-disciplinary explorations. As has been discussed, complexity characterizes modern food shopping system, especially the online one. To explore in-depth knowledge of complexity, single disciplinary system of thoughts might limit the imaginations one can create. A cross-discipline approach for studies on online food shopping can both offer fresh explanations for unanswered questions or that in tension, and also help identifying unnoticed phenomenon for further exploration.

Practical Implications

For online retailers, conceptual analyses and the four resulting propositions can generate practical implications too. First, when designing a online food shopping business/system, practitioners need to adopt an ecosystem viewpoint to prevent incomplete thinking and ignorance of any stakeholder’s opinion. Second, practitioners need to take care of the interfaces between the virtual and physical sub-systems even if it is an online food shopping ecosystem. By considering the interfaces between the sub-systems, not just connection and coordination works would be cared about, but also transformation work should be articulated. For example, the transformation of values in the process flows between material (e.g., food products), informational/technological (safety labels; blockchain applications in supply chain communications; human-machines interface in online purchase procedures, etc.), financial (budgeting; pricing; payment, etc.), human (i.e., stakeholders), and other sub-systems should be implemented with a fully consistent and engaging logic.

Limitations

In nature, a conceptual analysis is done without empirical and original data collection. However, this article has tried to avoid such inherent limitation by conducting the conceptual analysis with as many practical examples as possible. Additionally, our analysis focuses on the online shopping for foods only. Future studies can also take a similar approach but discuss other characterized industries, such as online shopping for precious metals, intangible services, and so on. Also, our focus on food is limited to foods in general. Future studies can be more detailed, by characterizing more for different food categories (e.g., organic vs. non-organic foods).

Author Contributions

C-FL was the major author of this article. C-HL reviewed and revised the manuscript. Both authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords : online food shopping, conceptual analysis, future research, propositions, theory and practice

Citation: Liu C-F and Lin C-H (2020) Online Food Shopping: A Conceptual Analysis for Research Propositions. Front. Psychol. 11:583768. doi: 10.3389/fpsyg.2020.583768

Received: 15 July 2020; Accepted: 26 August 2020; Published: 16 September 2020.

Reviewed by:

Copyright © 2020 Liu and Lin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Chi-Fang Liu, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

• Open access
• Published: 16 July 2022

Investigating experiences of frequent online food delivery service use: a qualitative study in UK adults

• Matthew Keeble 1 ,
• Jean Adams 1 &
• Thomas Burgoine 1  

BMC Public Health volume  22 , Article number:  1365 ( 2022 ) Cite this article

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Food prepared out-of-home is typically energy-dense and nutrient-poor. This food can be purchased from multiple types of retailer, including restaurants and takeaway food outlets. Using online food delivery services to purchase food prepared out-of-home is increasing in popularity. This may lead to more frequent unhealthy food consumption, which is positively associated with poor diet and living with obesity. Understanding possible reasons for using online food delivery services might contribute to the development of future public health interventions, if deemed necessary. This knowledge would be best obtained by engaging with individuals who use online food delivery services as part of established routines. Therefore, we aimed to investigate customer experiences of using online food delivery services to understand their reasons for using them, including any advantages and drawbacks.

Methods and results

In 2020, we conducted telephone interviews with 22 adults living in the UK who had used online food delivery services on at least a monthly basis over the previous year. Through codebook thematic analysis, we generated five themes: ‘The importance of takeaway food’, ‘Less effort for more convenience’, ‘Saving money and reallocating time’, ‘Online food delivery service normalisation’ and ‘Maintained home food practices’. Two concepts were overarching throughout: ‘Place. Time. Situation.’ and ‘Perceived advantages outweigh recognised drawbacks’.

After considering each of the accessible food purchasing options within the context of their location and the time of day, participants typically selected online food delivery services. Participants reported that they did not use online food delivery services to purchase healthy food. Participants considered online food delivery service use to be a normal practice that involves little effort due to optimised purchasing processes. As a result, these services were seen to offer convenient access to food aligned with sociocultural expectations. Participants reported that this convenience was often an advantage but could be a drawback. Although participants were price-sensitive, they were willing to pay delivery fees for the opportunity to complete tasks whilst waiting for delivery. Furthermore, participants valued price-promotions and concluded that receiving them justified their online food delivery service use. Despite takeaway food consumption, participants considered home cooking to be irreplaceable.

Conclusions

Future public health interventions might seek to increase the healthiness of food available online whilst maintaining sociocultural values. Extending restrictions adopted in other food environments to online food delivery services could also be explored.

Peer Review reports

Purchasing food that is prepared out-of-home and served ready-to-consume is prevalent across the world [ 1 ]. The neighbourhood food environment includes all physically accessible food outlets where individuals can purchase and consume foods, including food prepared out-of-home (often referred to as ‘takeaway food’) [ 2 ]. An increased number of outlets selling this food in the neighbourhood food environment may have contributed to normalising its consumption [ 3 ]. Purchasing formats represent ways to buy takeaway food. Although the opportunity to purchase this food was once limited to visiting food outlets in person or placing orders directly with food outlets by phone, additional purchasing formats such as online food delivery services now exist [ 4 ]. Unlike physically accessing outlets in the neighbourhood food environment or contacting outlets by telephone before collection or delivery, online food delivery services exist within a digital food environment. On a single online platform, customers receive aggregated information about food outlets that will deliver to them based on their location. Customers then select a food outlet, and place and pay for their order. Orders are forwarded to food outlets where meals are prepared before being delivered to customers [ 5 ]. Online food delivery services have been available in the UK since around 2006. However, widespread internet and smartphone access has increased their use [ 6 ], with global online food delivery service revenue estimated at £2.9 billion in 2021 [ 7 ]. The COVID-19 pandemic may have accelerated and perpetuated market development [ 8 ].

Food sold by takeaway food outlets, and therefore available online, is typically nutrient-poor and served in portion sizes that exceed public health recommendations for energy content [ 9 , 10 ]. More frequent takeaway food consumption has been associated with poorer diet quality and elevated bodyweight over time [ 11 ]. Although it is currently unclear, using online food delivery services might lead to more frequent and higher overall takeaway food consumption. In turn, this could lead to increased risk of elevated bodyweight and associated comorbidities. Since an estimated 67% of men and 60% of women in the UK were already considered overweight or obese in 2019 [ 12 ], the possibility that using online food delivery services increases overall takeaway food consumption is a major public health concern, as recognised by the World Health Organization [ 4 , 13 , 14 ].

With respect to the neighbourhood food environment, food outlet accessibility (number) and proximity (distance to nearest), food availability (presence of variety), and attitudinal dimensions (acceptability) contribute to takeaway food purchasing practices [ 15 ]. Each of these domains apply to takeaway food access through online food delivery services. In 2019, the number of food outlets accessible through the leading online food delivery service in the UK ( Just Eat ) was 50% greater in the most deprived areas compared with the least deprived areas [ 16 ]. Furthermore, adults living in the UK with the highest number of food outlets accessible online had greater odds of any online delivery service use in the previous week compared to those with the lowest number [ 17 ]. To our knowledge, however, attitudinal dimensions of online food delivery service use have not been investigated in the public health literature. Given the complexity of takeaway food purchasing practices, there are likely to be unique and specific reasons for using online food delivery services. Understanding these reasons from the perspective of customers could contribute to more informed public health decision-making and intervention, which is important since public health interventions that include online food delivery services may be increasingly necessary as their growth in popularity continues worldwide [ 13 , 18 ].

In our study, we investigated experiences of using online food delivery services from the perspective of adults living in the UK who use them frequently. We aimed to understand their reasons for using these services, the possible advantages and drawbacks of doing so, and how they coexist with other food-related practices.

Between June and August 2020, we used semi-structured telephone interviews to study experiences of using online food delivery services from the perspective of adults living in the UK. We used the Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist to guide the development and reporting of our study [ 19 ].

The University of Cambridge School of the Humanities and Social Sciences Research Ethics Committee provided ethical approval (Reference: 19/220).

Methodological orientation

We used a qualitative description methodological orientation to investigate our study aims. Qualitative description has been framed as less interpretative than other approaches [ 20 ]. However, it is theoretically and epistemologically flexible and can facilitate a rich description of perspectives [ 21 ], which matched our study aims.

Participants and recruitment

We used convenience sampling to recruit adults that used online food delivery services frequently. For the purpose of our study, we defined frequent customers as those who had used online food delivery services on at least a monthly basis over the previous year. We believed this level of use would make participants well-positioned to provide their experiences of using this purchasing format within established takeaway food purchasing practices. We also based participant recruitment on reported sociodemographic characteristics of online food delivery service customers [ 22 , 23 ]. As data collection progressed, we additionally considered level of education so that our sample included frequent customers who were less highly educated (see Table 1 ).

We used two social media platforms (Twitter and Reddit) to recruit participants. Participant recruitment through social media platforms can be fast and efficient [ 24 , 25 , 26 ]. If targeted advertising is not used (as in our study), participant recruitment in this way is also typically free. In our study, participant recruitment through social media was particularly appropriate, given that our aims were related to understanding experiences of using a digital purchasing format. Twitter users can publish and re-publish information, images, videos, and links to external sites. Reddit users can publish information, images and videos, and discuss topics within focused forums known as ‘Subreddits’. For Twitter, the primary researcher (MK) published recruitment materials using his personal account and relied on existing connections to re-publish them. For Reddit, MK created an alias account (he did not have a personal account at the time of our fieldwork) and published recruitment materials in Subreddits for cities in the UK with large populations according to the 2011 UK census, those related to online food delivery services, and those that discuss topics relevant to the UK [ 27 ]. See Additional file 1 (Box A1) for a complete list of Subreddits.

Recruitment materials asked interested individuals to contact MK by email. When contacted, MK responded by email with screening questions that asked about self-reported frequency of online food delivery service use over the past year, age, and level of education. When eligibility was confirmed, MK provided information about the study by email. This information included the study aims, details about researchers involved, the offer of a £20.00 electronic high street shopping voucher, and a formal invitation to participate. After five business days with no response to the invitation, MK sent a further email. After another five business days, we classified individuals that did not respond as ‘non-respondents’.

Data collection

Before data collection.

Before starting data collection, we planned to complete a maximum of 25 interviews. We did not target data saturation. Food purchasing and consumption are highly individual and influenced by previous experiences, cultural backgrounds, and preferences [ 28 ]. Therefore, we felt that it would be difficult to conclude data saturation was achieved based on the traditional conceptualisation of no new information being reported by participants [ 29 , 30 ]. Instead, we prioritised conceptual depth and information strength. This approach was aligned with the qualitative description methodological orientation of our study [ 30 ].

We wanted to investigate experiences of using online food delivery services from before the COVID-19 pandemic, when there were no restrictions on accessing multiple purchasing formats or consuming food on the premises. Therefore, we pre-specified that we would stop data collection if it became difficult for participants to refer to the time before March 2020, which is when pandemic related travel and food outlet access restrictions were first introduced in the UK. MK piloted an initial protocol with an eligible individual to confirm this would be possible, and made amendments based on their feedback.

Before starting data collection, MK reflected on his position as a population health researcher, and his previous training and experience in qualitative research [ 31 ]. MK also reflected on his own takeaway food consumption and previous use of online food delivery services. As of June 2020, MK consumed takeaway food infrequently and had previously placed one order with an online food delivery service. Although he was not a frequent customer according to our classification, MK was familiar with online food delivery services operating in the UK. MK concluded that despite having a broad understanding about why online food delivery services might be used, he could not use his own experiences to provide detailed reasons for favouring this purchasing format over alternative options.

Throughout data collection

MK completed one-off semi-structured telephone interviews with participants at a convenient time selected by them. At the start of the interview process, MK confirmed the rationale for the study, gave participants the opportunity to ask clarifying questions and asked them to provide verbal consent. MK used a topic guide that was developed based on a priori knowledge, pilot interview feedback and previous research related to takeaway food and online food delivery services [ 22 , 32 , 33 ]. MK amended the topic guide as data collection progressed so that points not initially considered could be discussed in future interviews. Interview questions focused on reasons for using online food delivery services, the perceived advantages and drawbacks of using these services, and how using them coexisted with other purchasing formats and food-related practices (see Box A2 in Additional file 1 for the final topic guide).

Although MK completed interviews during the COVID-19 pandemic, he did not ask questions related to this period of time, and prompted participants to think about the time before March 2020 so that pre-pandemic experiences could be discussed. MK digitally recorded interview audio and made field notes to track points for discussion within the interview.

After data collection

MK immediately reflected on topics discussed, data collection progress, possible links with existing theory, and the ability of participants to think about the time before the COVID-19 pandemic. We used these post-interview reflections to help inform our decision to stop data collection.

Data analysis

A professional company transcribed interview audio verbatim. Whilst listening to the corresponding audio, MK quality assured each transcript and anonymised it. Participants did not review their transcripts.

We used codebook thematic analysis. When using this analytic approach, researchers develop a codebook based on the final topic guide used during data collection and data familiarity that is achieved by reviewing collected data [ 34 , 35 ]. Codebook thematic analysis is aligned with qualitative description methodological orientations as it allows researchers to remain ‘close to the data’ and facilitates an understanding of a topic through the ‘spoken word’ of participants [ 36 ]. In practice, MK developed an initial codebook. MK, JA, and TB then reviewed three transcripts (a 10% sample). This number was manageable and allowed us to discuss a sample of collected data [ 37 ]. After discussion, MK refined the initial codebook to collapse codes that overlapped and to add new codes, which formed the final codebook. MK coded each transcript with the final codebook and reviewed reflections written after each interview. MK then studied the coded data to generate themes that were discussed and finalised with JA and TB. In the context of our study, themes summarise experiences of using online food delivery services from the perspective of participants. After discussion, we also identified that across the themes we generated, there were overarching concepts. For our study, concepts should be seen to offer an overall and consistent structure that capture the common and overlapping elements of each of the generated themes.

MK used NVivo (version 12) to manage the data and facilitate interpretation.

Participant and data overview

MK conducted interviews with 22 frequent online food delivery service customers between June and August 2020. Interviews lasted between 35 and 61 min. There were 12 male participants, 13 participants were aged between 20 and 29 years, and 15 had completed higher education. Since initial adoption, participants had typically used online food delivery services at least fortnightly but as often as daily, and during interviews they consistently referred to using the three most well-established online food delivery services operating in the UK ( Just Eat, Deliveroo, and Uber Eats ) (see Table 2 ).

During the 19 th interview, conducted in August 2020, it was difficult for the participant to think about the time before the onset of the COVID-19 pandemic in March 2020. MK completed three further interviews and then concluded that this difficulty was consistent so stopped data collection. We included data from all interviews in analyses. In addition to those who took part, three interviews were scheduled but cancelled by individuals without providing a reason, and there were nine non-respondents.

Summary and structure

We generated two concepts that were overarching throughout our data: ‘Place. Time. Situation.’ and ‘Perceived advantages outweigh recognised drawbacks’. Within these overarching concepts, we generated five themes: ‘The importance of takeaway food’, ‘Less effort for more convenience’, ‘Saving money and reallocating time’, ‘Online food delivery service normalisation’ and ‘Maintained home food practices’.

In the following sections, we present the findings for each of the overarching concepts, followed by each of the themes. Whilst we discuss each concept and theme in turn, all of their elements were present throughout the data and should be thought of as dynamic, overlapping, and non-hierarchical. For example, participants consistently reflected on features of online food delivery services within the context of their location at a specific time. The conclusion of this process dictated whether a feature was viewed as an advantage or a drawback, and in some cases whether an online food delivery service would be used. We provide examples of this comparison process at the end of our Results (Table 3 ).

Overarching concepts

Place. time. situation..

Participants described how their location and the time of day impacted their ability to access different types of food, including both ‘takeaway’ food and other types of food. When choosing one type of food over another, participants had a multi-factorial thought process that considered their food at home, immediate finances available for food, and the food already eaten that day.

Although data collection focused on takeaway food, participants were clear that this type of food was not always appropriate. As participant 10 (Female: 20–29 years) stated; “ I don’t always just go and get a takeaway; sometimes I’ll walk to the shop, get some food, and make something ”. This view was shared by participant 11 (Male 30–39 years); “ some days I’ll decide that it’s too expensive and I’ll either get something else direct from the restaurant or go to the supermarket and then make food ”.

Nonetheless, participants indicated that purchasing takeaway food was preferable in many situations. For example, when acting spontaneously, when meals had not been planned or if other types of food could not satisfy needs, then takeaway food was appropriate.

“ I think you’re more likely to get delivery and order online when it’s unplanned and you need a pick-me-up, or you need something quick, or you don’t have something and you’re really hungry .” Participant 15 (Male: 40-49 years)

When participants decided to purchase takeaway food, they recognised that their location and the time of day dictated the purchasing formats they could access and potentially use. Access to multiple purchasing formats created a second decision making process. Participants considered the cuisines they wanted, delivery times estimated by online food delivery services versus the time it would take to travel to a food outlet, the weather, their willingness to leave home, and previous experience with accessible food outlets. Alongside these influential factors, choosing one purchasing format over another was often based on what was most convenient.

“ If I’m out and about, on the way home and I’m passing via an outlet, then I’ll pick it up. If I’m at home and just kind of, don’t want to leave the house, then I’ll order via an app or online, just because it’s just convenient .” Participant 2 (Male: 20-29 years)

Despite having apparently decided how they would purchase takeaway food, participants stated that they could change their mind. In the case of online food delivery services, if estimated delivery times failed to meet expectations, this purchasing format would no longer be appropriate and another purchasing format or type of food would be selected. The need for food practices to align with other routines and schedules, and therefore meet expectations, was particularly clear when participant 8 (Female: 40–49 years) described that they used online food delivery services when they could “ relax on a Friday night with the whole evening free ”. However, if they do not have time to select a food outlet, place their order, and then wait for delivery they “ normally just have some spaghetti because that takes 10 min ”.

Participants also referred to online food delivery service marketing in their day-to-day environments, including branded food outlet signs and equipment used by delivery couriers. Participants stated that these things did not always trigger immediate use of online food delivery services, however, their omnipresence reminded them that these services were available.

“ I don’t know if I ever go onto Just Eat after seeing it advertised, I don’t think that’s ever directly led me to do it. But it certainly keeps it in your mind, it’s certainly at the forefront of your mind whenever you think of takeaway .” Participant 11 (Male: 30-39 years)

Perceived advantages outweigh recognised drawbacks

Throughout the data, participants recognised that a single online food delivery service feature could be an advantage or a drawback based on their location and the time of day. This was clearest when participant 2 (Male: 20–29 years) discussed the number of food outlets accessible online compared with those available through other purchasing formats. There was value in having access to “ 20, 30, 40 food outlets ” through online food delivery services as it meant more options, otherwise “ you’re more limited just by the virtue of where you are or what shops you’re passing ”. However, access to a greater number of food outlets was a drawback when it meant that making a selection was difficult. The constant comparison of advantages and drawbacks prompted MK to ask participants why they kept using online food delivery services. There was a consensus that features of these services were unique, mostly advantageous, and outweighed the instances where they were seen as drawbacks. Since participants continued to use online food delivery services to access unique features, this practice appears to be self-reinforcing, even if this means accepting that the same feature can sometimes be a drawback.

Participants favoured online food delivery services in many situations. Nevertheless, they acknowledged that if the overall balance between advantages and drawbacks changed then they would purchase takeaway food in other ways. This solution emphasises that takeaway food can often be accessed in multiple ways dependent on place and time. As it stands, participants anticipated that they would continue to use online food delivery services indefinitely.

“ I can’t see any reason why I would [stop using online food delivery services] , unless something went wrong with Just Eat, you know, the service had a massive problem, but at the moment I can’t see any reason why I would. ” Participant 16 (Male: 20-29 years)

Analytic themes

We now present each of the five themes generated from our analyses. As described, elements of each theme overlapped within the two overarching concepts presented above.

The importance of takeaway food

Participants emphasised that, ultimately, it was “ the food ” that they valued, and that directed them towards using online food delivery services.

“ It’s the food really, that leads me to use [online food delivery service] apps .” Participant 10 (Female: 20-29 years)

Participants reported that they did not use online food delivery services with the intent of purchasing healthy food. Participants told us that they expected takeaway food to be unhealthy and that online food delivery services facilitated access to this food. This perspective influenced the types of food that participants were willing to purchase through online food delivery services. For example, pizza (seen as unhealthy) was appropriate but a salad (seen as healthy) was not. Moreover, participants recognised that if they wanted to consume healthy food, they would most likely cook for themselves.

Participants stated that takeaway food had social, cultural, and behavioural value. For many, purchasing and consuming takeaway food at the end of the working week signified the start of the weekend, which was seen as a time for relaxation and celebration. This tradition was carried forward from childhood, with Friday night referred to as “ takeaway night ”. For participants, using an online food delivery service allowed them to maintain, yet digitalise, traditions.

“ It’s always a weekend thing, besides it being a convenient, really quick way of accessing food that is filling and tastes nice, for me, it marks the end of a work week .” Participant 4 (Female: 30-39 years)

Participants reported that in some situations consuming takeaway food as a group could be a way to socialise. This was especially the case during life transitions such as leaving home to start university.

“ When you move out you’re concentrating on making friends and getting a takeaway was quite an easy way for everyone to sit down around the table and socialise and to have drinks .” Participant 14 (Female: 20-29 years)

Participants did not value online food delivery services to the same extent that they did takeaway food. This perspective reinforced that online food delivery services were primarily used to satisfy takeaway food purchasing needs.

“ If Just Eat as an entity disappeared, or all online takeaways disappeared, I wouldn’t be upset […] it’s a luxury, it makes life easier .” Participant 9 (Male: 30-39 years)

Less effort for more convenience

Participants reported that it took little effort to use online food delivery services because they receive information about all food outlets that will deliver to them on a single platform. Additionally, participants valued the opportunity to save payment details, previous orders, and favourite food outlets for future use. Participants also informed us that they had a greater number of food outlets and a more diverse range of foods and cuisines to choose from compared with other purchasing formats. Due to the number of accessible food outlets, the selection process was not always fast. Nonetheless, participants indicated that online food delivery services make purchasing takeaway food easier and more convenient than other purchasing formats where information is less readily available.

“Y ou’ve got all of the different options laid out in front of you, it’s like one resource where everything is there and you can choose and make a decision, rather than having to pull out leaflets from a drawer or Google different takeaways in the area. It’s all there and it’s all uniform and it’s in one place .” Participant 3 (Female: 20-29 years) “ I can pick through a whole wide selection rather than being limited to the few takeaways down on my road or having to drive somewhere .” Participant 21 (Male: 20-29 years)

Participants emphasised that smartphone applications had been optimised to enhance this experience.

“ I guess it’s the convenience of just being able to open the app on my phone, and not have to go searching for menus or phone numbers and checking if places are open. So yeah, it’s the convenience .” Participant 15 (Male: 40-49 years) “ For me it’s just the ease of going on, clicking what you want, paying for it and it arriving. You don’t have to move, you don’t have to cook, you don’t have to think, it’s just there ready to go, someone’s doing the hard work for you .” Participant 1 (Female: 20-29 years)

However, greater convenience was not always advantageous. Some participants were concerned that convenient and easy access to takeaway food through online food delivery services might have negative consequences for health and other things.

“ It’s quite addictive in the way that it’s just so convenient to order. I’m not making stuff fresh at home, and I’m eating unhealthier .” Participant 21 (Male: 20-29 years) “ I think it adds to a general kind of laziness that is not good for people really. If you actually got up and went for a walk to go and get this food, at least there’s a slightly positive angle there .” Participant 17 (Male: 30-39 years) “ The convenience is not necessarily a positive thing, these apps can be abused because it’s so easy to access foods .” Participant 10 (Female: 20-29 years)

Saving money and reallocating time

Participants were price-sensitive and valued the opportunity to save money. When discussing financial aspects of online food delivery service use, participants referred to special offers they had received by email or through mobile device push notifications. Participants recognised that direct discounts (e.g. 10% off), free items (e.g. free appetizers on orders over £20.00), free delivery (e.g. on orders over £30.00), or time-limited price-promotions (e.g. 40% off all orders for the next three-hours) can justify takeaway food purchasing and online food delivery service use.

“ Getting a takeaway is always a treat, every time I do it I know I shouldn’t but then basically I’m convinced to treat myself, if there’s a discount I’m much more likely to do it because I don’t feel like it’s such a waste of money .” Participant 18 (Male: 20-29 years)

Participants recognised takeaway food as a distinct food category. Nevertheless, they appreciated that that they could use online food delivery services to purchase ‘restaurant food’. Since this food is usually accompanied by a complete dining experience that online food delivery services cannot replicate, participants expected to spend less on this food purchased online compared to when they dined inside a restaurant.

“ Some restaurants deliver through Deliveroo, [places] where you can sit down and have an experience, a dining experience, well that’s different […] you might go there for the dining experience .” Participant 4 (Female: 30-39 years) “ Sometimes I’m deterred from using Uber Eats because I noticed that the restaurants increase their prices if you buy it through them rather than directly […] I don’t want to pay over £10 for a takeaway dish, whereas I would pay that if I ate at a restaurant .” Participant 3 (Female: 20-29 years)

Although participants considered the price of food when deciding which outlet to order from, they traded money for time. Participants compared the time they would spend cooking or travelling to takeaway food outlets with the time taken to place orders through online food delivery services plus the tasks they could complete whilst waiting for meal delivery. Paying a delivery fee to have the opportunity to use time that would not have otherwise been available was acceptable.

“ Yeah, it costs money but at the same time we’re getting more time with the kids, and more time to do other stuff, so it’s absolutely fine as far as I’m concerned .” Participant 9 (Male: 30-39 years)

However, some participants were unsure about the appropriateness of paying to have food delivered as it might be unfair to delivery couriers.

“ I don’t feel like it’s necessarily right to make a delivery driver drive two minutes up the road just because I can’t be bothered to go and collect something that’s not very far away .” Participant 10 (Female: 20-29 years)

Online food delivery service normalisation

Participants had positive previous experiences of using online food delivery services. These experiences influenced future custom and contributed to an overall sense that using this purchasing format was now a normal part of living in a digital society. Some participants referred to watching television online to exemplify this point.

The normalisation of using online food delivery services was particularly evident when MK prompted participants to think about the term ‘takeaway food’. Participants often referred to online food delivery services in the first instance and saw them as synonymous with takeaway food.

“ If you were to say ‘takeaway food’ I’d pull out my phone and I’d open one of the apps and say ‘okay, what should we order’, I wouldn’t say ‘oh let’s go to this road’, or ‘let’s go to that road’, I’d say ‘yeah, let’s look on the app’ .” Participant 21 (Male: 20-29 years)

For participants in our study, using online food delivery services replaced purchasing takeaway food in other ways. This perspective was linked to habitual takeaway food purchasing and sociocultural values. Participants rarely purchased takeaway food outside of set routines (for example only doing so at the weekend) because they did not think it was appropriate. As a result, participants reported that they had a limited number of opportunities to use multiple purchasing formats and thus increase their existing levels of consumption.

Maintained home food practices

Most participants were responsible for cooking at home, enjoyed doing so, and said they were competent at it. Nonetheless, cooking at home required personal effort and being “ lazy ” or “ tired ” or “ having nothing in the cupboards ” was used as a justification for using online food delivery services.

“ I cook, when I’m not using these apps I cook and prepare food for myself , it’s just on the odd occasion I might be feeling tired or want something different […] the rest of the time, I’m quite happy to cook .” Participant 10 (Female: 20-29 years)

Despite the apparent normalisation of using online food delivery services, participants did not feel that they would ever completely eliminate cooking at home. Most participants consumed home cooked food daily, whereas they consumed takeaway food less frequently. This contributed to the view that these two types of food were different. As a result, participants used online food delivery services to purchase food they could not or would not cook at home; for a break from normality, and as a “ cheat ” or “ treat ”.

Summary of findings

To our knowledge, this is the first published study in the public health literature to investigate experiences of using online food delivery services from the perspective of frequent customers.

Participants recognised that their location and the time of day meant that they could often access different types of food through multiple purchasing formats, at the same time. Participants stated that purchasing takeaway food was appropriate in many situations and typically favoured using online food delivery services. For many participants, using these services was now part of routines in their increasingly digital lives. As such, using online food delivery services appeared to be synonymous with takeaway food purchasing. This meant that participants expected food sold online to be unhealthy and that it was inappropriate to purchase healthy food in this manner. Participants consistently thought about how features of online food delivery services were an advantage or a drawback within the context of their location at any given point in time. This was a complex and dynamic thought process. Participants described how the advantages of these services were a strong enough reason to continue use, overcoming drawbacks such as the acknowledged unhealthfulness of takeaway food. Participants reported that using online food delivery services involved little effort as they were provided with food outlet information, menus, and payment facilities on one platform that had been optimised for use. Moreover, although the cost of food was an important consideration for participants, they were willing to pay a fee in exchange for the opportunity to complete tasks whilst waiting for meal preparation and delivery. Finally, using online food delivery services substituted purchasing takeaway food in other ways. Nevertheless, participants reported that cooking at home was a distinct food practice that occurred more frequently and was irreplaceable.

Interpretations

Participants described sociocultural values assigned to takeaway food. These values are proposed to develop from previous experiences [ 38 , 39 ]. For our participants, purchasing takeaway food at the weekend was a traditional routine that celebrated the end of the working week. In the past, this tradition might have meant visiting food outlets in the neighbourhood food environment. However, online food delivery services are now used and favoured. Since participants reported that it was takeaway food in and of itself that was a fundamental reason for seeking out online food delivery services, it is reasonable to conclude that sociocultural values linked to this food exist, and transfer, across purchasing formats.

Food purchasing has been recognised as situational and made in the context of place and time [ 40 , 41 ], with convenience reported as a consistent consideration [ 42 ]. Participants in our study reported that takeaway food was appropriate in many situations and acknowledged that it could often be accessed through multiple purchasing formats. Using one purchasing format over another came after considering multiple factors, including the level of effort required to find a suitable food outlet and place orders. As using online food delivery services took little effort, this purchasing format was often most convenient. However, participants were clear that although their decision had seemingly been made, it could be changed, especially if an online food delivery service feature that was supposedly an advantage became a drawback. For example, if estimated delivery times were too long or delivery fees were too high an alternative option would be considered. Our findings support that the decision about if and how to purchase takeaway food is dynamic and influenced by place and time [ 32 ].

Food access has previously been summarised within the domains of availability, accessibility, affordability, accommodation, and acceptability [ 15 ]. Although Caspi and colleagues described these domains in the context of physical food access, they are applicable to digital food environments. Broadly speaking, our research investigated the ‘acceptability’ of using online food delivery services, and participants made explicit reference to the domains of food ‘accessibility’ and ‘affordability’.

For example, participants told us that one particularly valuable aspect of using online food delivery services was the ability to access a greater number of food outlets compared with other purchasing formats. This finding speaks to our previous research that found a positive association between having the highest number of food outlets accessible online and any use of online food delivery services in the previous week amongst adults living in the UK [ 17 ]. The experiences of using online food delivery services reported in the current study support the possibility that having more food outlet choice contributes to the decision to adopt, and maintain, use of these services rather than necessarily increasing the frequency in which they are used. Other features of online food delivery services, such as having information about each of the accessible food outlets on one platform, likely amplify the perceived benefit of greater food outlet access. Notably, however, access to an increased number of food outlets was not always advantageous. This finding recognises a general awareness about the negative aspects of takeaway food consumption, previously captured from the perspectives of young adults in Australia and Canada [ 38 , 43 ].

Participants also discussed how the price of food influenced their use of online food delivery services. This reflects that food affordability is a fundamental purchasing consideration [ 32 ]. Beyond this, our findings provide insight into actions that food outlets registered to accept orders online might take to attract customers. Given that online food delivery service customers can often select from multiple food outlets at the same time, food outlets might aim to compete with one another by lowering the price of food sold or by introducing price-promotions in an attempt to capitalise on customer demand. Particularly in the case of the latter, participants acknowledged the importance of price-promotions. Previous evidence shows that price-promotions contribute to unhealthy food purchasing practices [ 44 , 45 ]. Access to price-promotions through online food delivery services has not been systematically documented. However, it is possible that their availability is positively associated with the number of food outlets accessible online. Since both price-promotions and the number of food outlets accessible online appear to influence online food delivery service use, the possibility of interaction between them is concerning for overall consumption of food prepared out-of-home, and subsequently, diet quality and health.

In some cases, participants reported that they used online food delivery services because they did not have time to cook at home. A number of tasks, including household chores, work, travel, and childcare, can limit the time available for, and take priority over, home cooking [ 46 ]. Using online food delivery services (and paying associated delivery fees) instead of cooking at home allowed participants in our study to complete non-food related tasks whilst waiting for meal preparation and delivery. Due to sociocultural values and perceived ‘rules’ about how frequently takeaway food 'should' be purchased, participants did not see online food delivery services as a complete replacement for cooking at home. Nevertheless, even partial replacement has implications for diet quality and health, especially since the food available and purchased online was acknowledged as unhealthy by participants in the current study.

Possible implications for public health and future research

Participants reported that using online food delivery services had mostly substituted, not supplemented, their use of other purchasing formats. Given the perspectives of participants in our study, an increasing number of food outlets could be registering to accept orders online to supply an apparent customer demand. Further research is required to understand the extent to which customer demand is driven by food outlet accessibility, and vice versa.

Participants in our study reported that despite using online food delivery services frequently, their overall takeaway food consumption had remained the same. We do not yet know if this perception would be reflected in objective assessment of takeaway food consumption. Further research that quantifies the use of multiple purchasing formats and takeaway food consumption over time is required to understand the potential public health implications as a result of using online food delivery services. Although evidence from Australia suggests that food sold through online food delivery services tends to be energy-dense and nutrient-poor [ 47 ], this has not been established in the UK, to our knowledge. Nor does it necessarily reflect the balance of what food is purchased. Objective assessment of the nutritional quality of foods available, and purchased, through online food delivery services in the UK could be the focus of future research. This evidence will help to better understand the extent to which public health concern is warranted.

With a few exceptions, food sold through online food delivery services is prepared in food outlets that are also physically accessible in the neighbourhood food environment [ 13 ]. From a public health perspective, this reinforces the intrinsic link between neighbourhood and digital food environments [ 48 ]. Therefore, public health interventions adopted in the neighbourhood food environment may also influence the digital food environment. For example, urban planning policies have been adopted to prevent new takeaway food outlets from opening in neighbourhoods [ 49 ]. By extension, this stops new food outlets from becoming accessible online. Other public health interventions that operate synergistically between physical and digital food environments might be increasingly required in the future. It will also be vital for any future interventions to consider how the geographical coverage of online food delivery services expands neighbourhood food outlet access [ 50 ], potentially undermining the effectiveness of interventions adopted in the neighbourhood food environment. Doing so would help address concerns that these services increase access to food prepared out-of-home [ 4 , 13 ]. Interventions of this nature could be particularly important in more deprived areas that have the highest number of accessible food outlets across multiple purchasing formats [ 16 , 51 ].

Participants recognised that online food delivery services provide access to takeaway food that was associated with being unhealthy. Participants were aware that they could purchase healthy food through online food delivery services, but this did not mean that they would . From a public health perspective, this finding indicates that the success of interventions intended to promote healthier takeaway food purchasing through online food delivery services might be limited by existing sociocultural values if they are not taken into consideration. A possible way to navigate this would be to improve the nutritional quality of food available online without necessarily making any changes salient. Interventions of this nature include healthier frying practices and reduced food packaging size [ 52 , 53 ]. Although these interventions were acceptable and feasible when implemented inside takeaway food outlets [ 54 ], further investigation is required to understand the extent to which they are appropriate in the context of online food delivery services. Changing the types of food available to purchase through online food delivery services could also lead to improved food access for those with limited kitchen facilities at home or limited mobility.

Public health interventions intended specifically for online food delivery services could also be developed. Potential approaches include preferential placement of healthy menu items, introducing calorie labelling and offering healthier food swaps. Embedding these approaches within existing online food delivery service infrastructures would allow implementation to be uniform [ 55 ], and their implementation could be optimised to enhance customer awareness and interaction. The potential success of approaches of this nature requires exploration. Nevertheless, in February 2022, the UK Behavioural Insights Team (formerly of the UK Government) published a protocol to investigate approaches to promoting the purchase of lower energy density foods through a simulated online food delivery service platform [ 56 ].

Price-promotions influenced and justified the use of online food delivery services. Legislation to restrict the use of volume-based price-promotions (e.g. buy-one-get-one-free, 50% extra free) on less healthy pre-packaged food sold both in-store and online were due to be introduced in England in October 2022 [ 57 ]. However, the introduction of this legislation has now been delayed. Although hot food served ready-to-consume was due to be excluded, given what is known about the impact of price-promotions on purchasing other food [ 58 ], and our participants’ description of the importance of price-promotions on their purchasing practices, extension of these restrictions to hot food served ready-to-consume might be warranted. Understanding how price-promotions influence food purchased from online food delivery services represents a first step to understand the need for future regulation.

Limitations

We recruited participants through two social media platforms, which means that our study sample was formed from a subset of all social media users. However, online recruitment was appropriate since we wanted to understand experiences of using a digital purchasing format. Moreover, the participants we recruited were mostly highly educated, potentially reflecting reported online food delivery service use amongst this socioeconomic group [ 22 , 23 ]. After 12 telephone interviews we acknowledged this and adjusted our recruitment strategy to ensure a more balanced sample with respect to level of education. Nevertheless, future research should explore the perspectives of frequent online food delivery service customers with lower levels of education, since it is possible that they have different reasons for using these services. Although we did not recruit infrequent online food delivery service customers or non-customers, they would not have been well-positioned to help us investigate our study aims. However, since we have described experiences of using online food delivery services from the perspective of frequent customers, future work should seek to understand perspectives of non-customers, customers who use them less frequently, and customers who use them for specific reasons.

As the first study in the public health literature to investigate frequent customer experiences of using online food delivery services, we chose a descriptive methodological orientation. Our descriptive approach meant that we did not investigate the underlying meaning of the language used by participants, however, this was not aligned with our aims. Furthermore, our descriptive methodological orientation allowed us to use codebook thematic analysis and include multiple researchers in analysis. Coding a 10% sample of interviews transcripts and discussing analytic themes would have been less appropriate with reflexive approaches to thematic analysis [ 34 , 35 , 59 ], but assisted with our interpretations.

We conducted fieldwork during the early stages of the COVID-19 pandemic, which might have altered the recent experiences of online food delivery service use and participant perspectives. However, MK asked participants to think about the time before the COVID-19 pandemic and reflected on their ability to do so. This reflexivity is in line with established practices regarding qualitative rigour [ 20 , 60 ], and allowed us to determine when it would be most appropriate to stop fieldwork. Nonetheless, we acknowledge the possibility that food-related practices have changed during the COVID-19 pandemic. As a result, it is possible that online food delivery services are now used for different reasons, both initially and over time, and by individuals with different sociodemographic characteristics than those in our study.

We used telephone interviews with frequent online food delivery service customers to investigate experiences of using this purchasing format. We found that the context of place and time influenced if and how takeaway food would be purchased. Online food delivery services were often seen as most appropriate. In part, this was due to the opportunity to access advantages not available through other purchasing formats, such as efficient and convenient ordering processes that had been optimised for customers. Fundamentally, however, online food delivery services provide access to takeaway food, which despite being acknowledged as unhealthy, has strong sociocultural value. There was a consistent awareness that some advantages of online food delivery services may also be drawbacks. Despite this, the drawbacks were not sufficiently negative to stop current or future online food delivery service use. Finally, price-promotions justified online food delivery service use and made this practice appealing. Public health interventions that seek to promote healthier food purchasing through online food delivery services may be increasingly warranted in the future. Approaches might include increasing the healthiness of the food available whilst maintaining sociocultural values and expectations, and extending restrictions on price-promotions to hot food prepared out-of-home.

Availability of data and materials

Processed and anonymised qualitative data from this study is available from the corresponding author upon reasonable request. Additional raw data related to this publication cannot be openly released; the raw data contains interview audio containing identifiable information.

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Matthew Keeble was funded by the National Institute for Health and Care Research (NIHR) School for Public Health Research (SPHR) [grant number PD_SPH_2015]. This work was supported by the Medical Research Council [grant number MC_UU_00006/7]. The views expressed are those of the authors and not necessarily those of any of the above named funders. The funders had no role in the design of the study, or collection, analysis and interpretation of the data, or in writing the manuscript. For the purpose of open access. the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising.

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Keeble, M., Adams, J. & Burgoine, T. Investigating experiences of frequent online food delivery service use: a qualitative study in UK adults. BMC Public Health 22 , 1365 (2022). https://doi.org/10.1186/s12889-022-13721-9

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Online food delivery companies' performance and consumers expectations during Covid-19: An investigation using machine learning approach

Purushottam meena.

a Department of Supply Chain & Information Management, School of Business, College of Charleston, Charleston, SC, 29424, USA

Gopal Kumar

b Department of Operations Management, Indian Institute of Management, Raipur, Chhattisgarh, 492015, India

Online food delivery (OFD) businesses flourished during COVID-19; however, OFD companies experienced different challenges and customers' expectations. This paper uses social media data to explore OFD companies' performance and customers' expectations during the COVID-19 pandemic. The most important topics in developed and developing countries are identified using machine learning. Results show that customers in India are more concerned about social responsibility, while financial aspects are more important in the US. Overall, customers in India are more satisfied with OFD companies during the COVID-19 pandemic than the US customers. We further find that factors such as OFD companies' brand, market size, country, and COVID-19 waves play a crucial role in moderating customer sentiment. The results of the study offer several managerial insights.

1. Introduction

The COVID-19 pandemic has caused a profound and severe impact on the global economy. As the COVID-19 pandemic started, many restaurants worldwide lost billions of dollars, and many even faced business closures ( National Restaurant Association, 2020 ). According to the National Restaurant Association (2020) report, the restaurant industry has already lost approximately $240 billion by 2020. Restaurants that remained in business found it essential to adapt to recent changes in the industry and offer online food delivery (OFD) services for their survival ( Brewer and Sebby, 2021 ). Many restaurants started using third-party food delivery providers' services during the pandemic. It resulted in a significant increase in online OFD businesses worldwide. For example, Uber Eats observed a substantial increase in OFD orders following the mandate of no dine-in service ( Raj et al., 2021 ).

The platform economy in the food sector is not more prominent in terms of labor participation in India ( Sundararajan, 2016 ; Pant and Shende, 2020 ). However, with entries of global OFD leading companies such as Uber Eats along with some Indian companies—Zomato and Swiggy—the OFD industry is proliferating with a 25–30 percent annually ( Boston Consulting Group, 2020 ). The overall platform economy in India is expected to be $30 billion by 2025 ( NASSCOM, 2018 ). In 2019, more than 48 million people used OFD platforms in the US, which is likely to be approximately 70 million in 2024. The OFD revenue in the US is expected to grow steadily at 7.26 percent annually and is estimated to be $41,504 million by 2025 ( Statista, 2021 ). As per the 2022 Statista report, the global OFD service market is expected to reach $223.7 billion in 2025 from $115.07 billion in 2020 (Statista, 2022).

In recent years, the number of laborers who work in the platform economy has increased significantly. According to the NITI Aayog (a policy think tank of the India government), the platform economy employs around 15 million workers, and approximately 0.44 million of them work in the food sector ( Tiwari et al., 2019 ). Food delivery workers are not hired as full-time employees like any other sharing economy sector. These workers are primarily considered interchangeable or “gig workers” by food delivery companies ( Sundararajan, 2016 ).

During the first wave of COVID-19, most restaurants in the US were forced to suspend dine-in services and were only allowed to operate via takeout, drive-through, or contactless deliveries. As the COVID-19 outbreak started, restaurants demand started plumbing globally and affected the financial performance of the restaurant industry. In US restaurants, customer demand decreased drastically with increasing COVID-19 cases ( Yang et al., 2020 ). However, more and more people started ordering foods online via food delivery platforms like DoorDash, Grubhub, Uber Eats (in the US), Zomato, and Swiggy (in India) ( Jain, 2020 ; Kim et al., 2021 ). Restaurants that provided OFD and curbside pickup services for contactless delivery experienced a lesser effect on financial performance. Most of these OFD services businesses were in operation during the COVID-19 outbreak as they are considered among the essential services. The OFD service platforms were instrumental for restaurants to remain in business during challenging times ( Puram et al., 2021 ). Compared to March 2019, customer spending on food delivery increased significantly (i.e., 70 percent)—during the first COVID-19 wave in March 2020 ( Chen McCain et al., 2021 ).

On the flip side, OFD service providers (i.e., riders or drivers) and consumers faced several challenges during the ongoing pandemic. For example, Indian OFD workers have faced personal and social risks, ranging from loss of income to exposure to COVID-19 and risking their lives ( Lalvani and Seetharaman, 2020 ). The OFD became crucial and popular as millions of people were quarantined and unquarantined required foods ( Chen McCain et al., 2021 ; Kim et al., 2021 ). While delivering food, OFD companies needed to follow strict COVID-19 appropriate behaviors; otherwise, riders and consumers would be exposed to life-threatening health risks.

Overall, during the COVID-19 pandemic, consumers prioritized expectations from OFD companies, and the challenges faced by OFD companies were different from those of the pre-COVID-19 pandemic ( Gavilan et al., 2021 ). The adaptability of food delivery companies to a situation of a global healthcare crisis, where customers' expectations are entirely different ( Gavilan et al., 2021 ; Nguyen and Vu, 2020 ). It may depend on several factors, such as fear ( Balakrishnan, 2020 ; Mehrolia et al., 2021 ; Ahorsu et al., 2020 ; Lo Coco et al., 2021 ), marketing strategies during COVID-19 waves ( Jia et al., 2021 ), brand perception ( Dsouza and Sharma, 2021 ; Prasetyo et al., 2021 ), market size, region (developing or developed countries) of their operations ( Keeble et al., 2020 ; Zanetta et al., 2021 ), public listing ( Bao and Zhu, 2022 ), and COVID-19 waves ( Kohút et al., 2021 ; Mohan et al., 2022 ), etc. For example, OFD companies with better brand perception, bigger market size, and listed in the stock market should do better in a crisis. They may also improve their performance in the second wave better than in the first wave of the COVID-19 pandemic. Therefore, to have a deeper understanding of the delivery operations of OFD companies and consumers' behaviors/expectations during a global healthcare crisis, it is crucial to understand how OFD companies performed, to what extent consumers' expectations were met, and factors that can explain OFD companies' performance or customers' satisfaction during COVID-19 pandemic.

Most of the erstwhile work in the literature on OFD is conducted predominantly using primary data with a limited sample size. To the best of our knowledge, no study exists in the literature that considers social media-based big data relating to OFD companies during the pandemic and uses qualitative (machine learning algorithms) as well as quantitative approaches to investigate issues faced by OFD companies, service providers, and customers during the first two waves of the COVID-19 in the US and Indian market. Specifically, this study investigates how do consumers' sentiments vary on OFD companies' services during COVID-19 across different dimensions of consumer expectations, market characteristics, and companies' characteristics?

The following research objectives (RO) are considered to address the research question:

RO1: To identify the broader issues/topics prominently discussed about OFD companies and service providers during the pandemic.

RO2: To investigate consumers' net sentiment and negative sentiment across identified dimensions, OFD companies, and different countries.

RO3: To test the impact of different market characteristics and OFD companies' characteristics on consumers' sentiments.

To address these research objectives, first, we collected data for four OFD companies (i.e., Uber Eats, Grubhub, Zomato, and Swiggy) from Twitter during the first two waves of the COVID-19 pandemic. Second, the text mining approach is used to identify different topics/issues discussed on Twitter about these OFD companies. Third, for each identified topic, positive and negative sentiments of people are computed. Fourth, different regression models are developed to investigate the relationship between the moderating variables and people's sentiments. Finally, the results of both countries' companies are compared to examine the differences among the topics and customers' sentiments. The results offer several important practical insights which are helpful for OFD companies.

The remainder of the paper is organized as follows. Section 2 discusses the analyses of relevant literature. Section 3 presents the research hypotheses. Data collection, research methodology, and results are provided in Section 4 . Section 5 presents discussion and managerial insights. Finally, section 6 concludes the research and offers the scope for future studies.

2. Literature review

There was not much research conducted on the OFD area before the COVID-19 pandemic. Previous studies have mainly focused on issues such as the OFD platform's performance and customer satisfaction ( Seghezzi and Mangiaracina, 2020 ; Gilitwala and Nag, 2019 ), consumers behavior and attitude ( Pigatto et al., 2017 ; Hwang and Choe, 2019 ; Yeo et al., 2021 ), vehicle routing problems ( Liu et al., 2020 ; Correa et al., 2019 ), adoption and acceptance of technology in OFD apps ( Pigatto et al., 2017 ; Gunden et al., 2020 ; Roh and Park, 2019 ), and riders issues related to wages and health ( Bates et al., 2020 ; Correa et al., 2019 ; Kougiannou and Mendonça, 2021 ). For a detailed discussion on these issues, interested readers can refer to Li et al. (2020) and Seghezzi et al. (2021) , who have provided an excellent review of OFD literature published before the COVID-19 period.

Research on the OFD has witnessed significant growth during the last two years. One of the reasons for this rapid growth was the rapid increase in OFD services demand during the COVID-19 pandemic. For safety reasons, more people started ordering their food from home via OFD apps ( Mehrolia et al., 2021 ; Zanetta et al., 2021 ; Hong et al., 2021 , Hong et al., 2021 ), such as Uber Eats, DoorDash, Zomato, and Swiggy. Several researchers ( Hong et al., 2021 , Hong et al., 2021 ; Gani et al., 2021 ) have studied how these new behaviors of people affect the food delivery business during the COVID-19 outbreak.

As per the world health organization (WHO), more than 6.28 million people have already died because of the COVID-19 pandemic. It has affected people's life emotionally, psychologically, and physically ( Ahorsu et al., 2020 ; Conte et al., 2021; Watson and Popescu, 2021 ). People have used several ways to deal with the stress, anxiety, and loneliness caused by the COVID-19 (Kumarand Shah, 2020; Ahorsu et al., 2020 ; Lo Coco et al., 2021 ). Consumers have extensively utilized different social media platforms to share their opinion and remain updated with the public policies and regulations during the COVID-19 ( Rydell and Kucera, 2021 ; Trivedi and Singh, 2021 ). Several researchers studied how the COVID-19 has changed consumers' behavior, habits, and tastes when buying food online ( Watson and Popescu, 2021 ; Birtus and Lăzăroiu, 2021 ; Rydell and Suler, 2021 ; Smith and Machova, 2021 ). Michalikova et al. (2022) have reviewed the literature on customers' judgment, behavior intentions, and purchase decision dynamics during the COVID-19 pandemic in the food delivery sector.

COVID-19 has considerably impacted the financial strength of restaurant firms; however, restaurant firms that used OFD and other contactless delivery services experienced relatively lesser financial glitches ( Kim et al., 2021 ). Before COVID-19, the primary marketing strategies were based on product imagery, links, and sponsorships. While combatting the COVID-19 pandemic, selling social distancing, appropriating frontline workers, and accelerating digitalization were the selling points ( Jia et al., 2021 ). We classify the research conducted on OFD during the COVID-19 outbreak into three categories—customer satisfaction/experience, intention to use OFD apps, and workers/drivers/riders' conditions during operations of OFD.

The first set of studies ( Kumar and Shah, 2021 ; Mehrolia et al., 2021 ; Prasetyo et al., 2021 : Sharma et al., 2021 ) focused on customer experience and OFD companies' performance. Mehrolia et al. (2020) and Sharma et al. (2021) investigated the characteristics of customers who used and did not use online food delivery services (OFDS) during the first wave of COVID-19 in India. Customers who purchased food via OFD platforms have experienced lesser perceived threats and a high purchase pattern, perceived benefits, and product involvement ( Al Amin et al., 2021 ; Mehrolia et al., 2021 ; Sharma et al., 2021 ; Uzir et al., 2021 ). Studies found that during the COVID-19 pandemic, hedonic motivation ( Prasetyo et al., 2021 ; Sharma et al., 2021 ; Shah et al., 2021 ), food quality, variety, and safety ( Dsouza and Sharma, 2021 ; Shah et al., 2021 ), and mobile app information design/features ( Pal et al., 2021 ) significantly affect customers satisfaction and loyalty. Hedonic motivation is also important for price, information quality, and promotion ( Prasetyo et al., 2021 ; Bao and Zhu, 2022 ; Shah et al., 2021 ; Sharma et al., 2021 ; Ramos, 2021 ; Pal et al., 2021 ). Unlike other studies, Zenetta et al. (2021) found that hedonic motivation was not the most crucial factor for the continuance intention.

India is one of the most populated countries and was severely affected by the COVID-19. Several studies ( Dsouza and Sharma, 2021 ; Mehrolia et al., 2021 ; Pal et al., 2021 ) have been conducted to understand OFD companies and customers' purchase behaviors in the Indian market. Trivedi and Singh (2021) found that Zomato received the most positive and less negative customer sentiments than other competitors, such as Swiggy in India. Dsouza and Sharma (2021) found that the food quality and safety measure of OFDAs positively affects customer satisfaction and loyalty in India. Pal et al. (2021) investigate student satisfaction and loyalty to OFDAs. Their findings suggest that satisfaction is the main predictor of loyalty, whereas mobile app information design has the highest impact on satisfaction and loyalty. Chen McCain et al. (2021) assessed customers' satisfaction with Uber Eats on different dimensions—OFD apps performance, food quality, and service quality during the first wave of COVID-19 in the US. They found that service quality was the most important dimension, followed by OFD app performance and food quality.

The second set of studies focused on the continuous usage intention of OFD apps during the COVID-19 outbreak period in different countries, such as India ( Mehrolia et al., 2021 ), the USA ( Hong et al., 2021 , Hong et al., 2021 ), China ( Zhao and Bacao, 2020 ), Brazil ( Zanetta et al., 2021 ), Mexico ( Ramos, 2021 ), Vietnam ( Tran, 2021 ). These and several other studies have found that performance expectancy ( Mehrolia et al., 2021 ; Zanetta et al., 2021 ; Pal et al., 2021 ; Ramos, 2021 ), habit ( Zanetta et al., 2021 ; Rydell and Kucera, 2021 ), effort expectancy ( Kumar and Shah, 2021 ; Ramos, 2021 ; Pal et al., 2021 ), price saving orientation ( van Doorn, 2020 ; Ramos, 2021 ; Pal et al., 2021 ), perceived usefulness, and employee trust ( Gavilan et al., 2021 ; Chakraborty et al., 2022 ; Trivedi and Singh, 2021 ; Uzir et al., 2021 ) affect consumers intention to use OFD services during the COVID-19 period.

Similarly, delivery, hygiene, subjective norms, attitudes, behavioral control, and social isolation ( Al Amin et al., 2021 ; Gani et al., 2021 ; Tran, 2021 ; Sharma et al., 2021 ; Yeo et al., 2021 ; Hopkins and Potcovaru, 2021 ) positively affect the consumers' continuance intention to use Mobile food delivery apps. Further, studies have also found that OFD apps features, ease of use, convenience, price saving, and food variety ( Pigatto et al., 2017 ; van Doorn, 2020 ; Pal et al., 2021 ; Dirsehan and Cankat, 2021 ; Shah et al., 2021 ; Kumar et al., 2021 ; Bao and Zhu, 2022 ) also affect the continued intention to use the FDA. Gavilan et al. (2021) found that customers preferred innovative solutions by OFD companies during COVID-19. Kumar and Shah (2021) observed that the app aesthetics were responsible for customers' pleasure, significantly affecting the customers' continued usage intent.

The third set of studies ( Huang, 2021 ; Parwez & Ranjan, 2021 ; Puram et al., 2021 ) attempted to understand food delivery drivers' conditions during COVID-19 in China and India. The precarity of work among the food delivery workers had aggravated during COVID-19—and it impacted workers' job loss, health risks, and occupational distress ( Huang, 2021 ; Parwez & Ranjan, 2021 ). Among drivers in China, work insecurity, financial distress, health risks, livelihood crisis, and inflamed racism were also observed ( Huang, 2021 ). Puram et al. (2021) analyzed the challenges faced by last-mile food delivery riders working for different OFD platforms in India during the COVID-19 pandemic. They categorize the riders' challenges under operational, customer-related, organizational, and technological categories.

Apart from the variables discussed above, several other variables moderate or affect customers' satisfaction ( Hu et al., 2009 ), sentiments about the food delivery service ( Oliver, 1977 ; Gavilan et al., 2021 ), and intent to use and reuse OFD services ( Mittal et al., 2001 ; Kim et al., 2021 ; Gani et al., 2021 ). A large number of studies show that a firm's brand image ( Fornell, 1992 ; O'Sullivan and McCallig, 2012 ; Peng et al., 2015 ; Chai and Yat, 2019 ; Hwang and Kim, 2020 ; Prasetyo et al., 2021 ) and market value/size (Daniel et al., 2015; Dai et al., 2021 ) positively affect customers satisfaction in different service industries. The customer's expectations about the OFD service performance may vary between different waves of the COVID-19 ( Sv et al., 2021 ; Mohan et al., 2022 ). The geographic location of customers may affect their expectations and purchase intention about the product and service ( Steyn et al., 2010 ; Ng, 2013 ; Leng et al., 2019 ; Punel et al., 2019 ). Rizou et al. (2020) found similar findings in the food delivery sector as well. Studies have explored the difference in people's sentiments during the first and second waves of the COVID-19 ( Lo Coco et al., 2021 ).

None of the above studies utilize secondary data from social media platforms like Twitter, where customers regularly express their concerns, experience, and advice to OFD companies and their businesses. This data can help companies comprehensively understand customers' expectations and measure their performance during the pandemic. This paper addresses this issue by collecting consumer data on the top two Indian and US OFD companies from Twitter and exploring the issues OFD companies face by employing the text mining approach and regression analyses.

3. Research hypotheses development

In addition to the traditional OFD business market factors, several other variables may affect or moderate customers' sentiments about OFD companies' performance and service during the COVID-19. The variables and related hypotheses are discussed in the following sub-sections.

3.1. The COVID-19 waves and people's sentiments

The COVID-19 pandemic brought havoc to everyone's life and affected people in different ways—financially, emotionally, psychologically, and physically ( Trivedi and Singh, 2021 ; Conte e t al., 2021). At the beginning of the COVID-19 outbreak (i.e., in the first wave), it was difficult for OFD companies and restaurants to run their business and serve customers efficiently and safely. In the first COVID-19 wave, most OFD companies were clueless about the customers' expectations of their delivery services and how to meet them. Due to safety reasons ( Zhao and Bacao, 2020 ), customers with self-protective behavior were hesitant to order food online during the first COVID-19 wave ( Ahorsu et al., 2020 ). The primary reasons for their safety concern were lack of information about hygiene, how and who is preparing food, ingredients used in foods, source of ingredients, and safety measures adopted at restaurants ( Gavilan et al., 2021 ).

However, to address these concerns, soon, OFD companies started adopting government regulations, offered contactless delivery, and implemented several measures for customers' safety ( Nguyen and Vu, 2020 ). During the first COVID-19 wave, OFD companies have learned to meet consumers' expectations in the best way possible. As COVID-19 time passed, OFD service providers started offering more information about safety measures adopted by them to consumers (Keeble et al., 2021). Therefore, in the second wave of COVID-19, companies' performance and consumers' sentiment about their performance should improve. Literature suggests a difference in people's sentiments between the first and second wave of the COVID-19 ( Kohút et al., 2021 ; Sv et al., 2021 ; Mohan et al., 2022 ), which also suggests people's psychological adoption of the new normal situation ( Koppehele-Gossel et al., 2022 ) as well satisfaction with improved services of OFD firms. We believe customers' sentiments on the operations of OFD companies ( Kim et al., 2021 ) should vary from COVID-19 first to the second wave. Therefore, we hypothesized:

COVID-19 waves moderate people's sentiments.

3.2. Market size and public listing impact on people's sentiments

From the expectancy theory perspective ( Oliver, 1977 ), customers will have specific expectations from a firm based on their previous experiences, influencing their behaviors to achieve specific goals. Before the COVID-19 outbreak, OFD companies with a bigger market size and listed publicly may have provided better customer experiences. Customers would be expecting similar services during the COVID-19 period as well. Some OFD companies (e.g., Zomato and Groubhub) are publicly listed and have a better brand value than others ( Savitri et al., 2020 ; Yao et al., 2021 ). OFD companies with more resources can invest liberally to bring innovation to delivery operations to handle the COVID-19 healthcare crisis and market them to the consumers. Different innovative OFD options are discussed in the literature ( Keeble et al., 2020 ; Richardson, 2020 ; Shah et al., 2021 ; Sharma et al., 2021 ; Bao and Zhu, 2022 ), which helps in reducing customers' fear of safety concerns and increases their experiential value ( Gavilan et al., 2021 ) during COVID-19. Such companies can be more successful in conveying their safety-related measures to consumers.

Numerous studies ( O'Sullivan and McCallig, 2012 ; Peng et al., 2015 ) have investigated how a firm's value affects customer satisfaction. Bolton et al. (2004) and Luo et al. (2010) found that customer satisfaction significantly affects the firm's value in the stock market and vice-versa. It is established in the literature that high firm value not only helps increase customer satisfaction ( Hu et al., 2009 ) but also enhances its brand image ( Prasetyo et al., 2021 ), purchase and repurchase intention ( Bao and Zhu, 2022 ), customer retention ( Mittal et al., 2001 ), and reduces complaints ( Fornell, 1992 ). Dai et al. (2021) studied the impact of the COVID-19 outbreak on small and medium-sized enterprises (SMEs) across different industries during the first and second waves. They found that during the second wave, companies were more prepared based on their learning from the first wave. Daniel et al. (2005) find a higher correlation between a firm's market values and customers' confidence in the firm. Based on the above studies, one can conclude that if a firm has a higher market size or value and is listed publicly, it leads to high customer confidence or sentiments in the firm.

The market size of OFD companies moderates people's sentiments .

Public listing of OFD companies moderates people's sentiments.

3.3. The brand image and people's sentiments

The brand image of a food company is crucial for customers to use their OFD service ( Prasetyo et al., 2021 ). In the restaurant industry, brand image is defined as “emotions, ideas or attitudes that customers associate with full-service dining restaurants” ( Jin et al., 2012 ). It is established in the literature that customers prefer to purchase products or services from well-known brands as they offer high-quality food ( Aaker and Equity, 1991 ). During the COVID-19 outbreak, several restaurants have increased their presence on OFD platforms to increase brand awareness ( Chai and Yat, 2019 ; Hwang and Kim, 2020 ). In general, a better brand image helps increasing consumer trust, purchase intention ( Erdem and Swait, 2004 ), and customer satisfaction with a better service and quality ( Baek et al., 2010 ). Aureliano-Silva et al. (2022) argued that brand love and service recovery are important for purchase intention and brand trust in food delivery platforms. Studies show that brand love is instrumental to customer satisfaction and intentions for future purchases ( Han et al., 2011 ; Erkmen and Hancer, 2019 ; Bao and Zhu, 2022 ).

Ibrahim et al. (2017) found a positive relationship between consumer sentiments on Twitter and the company's brand image. A positive brand image creates a good reputation for the company in customers' minds for a long time, and it increases customer loyalty toward a high brand image company ( Pitta and Katsanis, 1995 ). Customers heavily rely on a company's brand image when they are concerned about uncertain product or service quality ( Berry, 2000 ; Erdem and Swait, 2004 ), food safety, and quality under uncertain times like the COVID-19 outbreak ( Kim et al., 2021 ). A company's brand image positively affects customer loyalty and is a significant predictor of customer satisfaction in the restaurant ( Hwang and Kim, 2020 ) and other industries ( Jin et al., 2012 ; Ryu et al., 2012 ; Faullant et al., 2008 ). The high brand image of a food delivery firm positively affects the customer's behavioral intention to use OFD service ( Hwang and Choe, 2019 ; Gani et al., 2021 ). Therefore, we hypothesized:s.

The brand image of OFD companies moderates people's sentiments.

3.4. Operating regions and people's sentiments

The customers' expectations about the same products and services may vary between different regions based on different factors such as behaviors, loyalty, attitudes, and cultural influence ( Steyn et al., 2010 ). Punel et al. (2019) found that customers' experiences and expectations about the same airline service vary based on customers' geographical region. The authors find a difference in the Noth American and Asian passengers' expectations of the ticket price and in-flight service. Some studies show that cultural regions moderate online purchase intention ( Ng, 2013 ). Leng et al. (2019) observed differences in the US and Japanese people's choices and expectations about food products and services.

Twitter is a popular social media platform where people freely express their feelings. People's reactions on Twitter to the COVID-19 varied in different regions. For example, the US people's sentiment score was more negative than the UK people toward the COVD-19 ( Zou et al., 2020 ). Similarly, the fear and awareness of the COVID-19 safety measures vary from country to country Rizou et al. (2020) ; Lo Coco et al. (2021) . Consumers' expectations and sentiments about the OFD service providers may also vary according to their country ( Keeble et al., 2020 ), as consumers in developed countries would be more educated and aware and, hence, have more expectations. In India, the OFD services business is growing exponentially. However, it is still new compared to the US market. Thus, OFD companies may focus more on consumer-centric service delivery in developed countries than in developing countries. Variation in the above factors should change customer sentiment. Therefore, we hypothesize that:

Operating regions (i.e., countries) of OFD companies moderate people's sentiments .

4. Research methodology and results

We have collected consumer data for four popular OFD companies from India (e.g., Zomato and Swiggy) and from the US (e.g., Uber Eats and Grubhub). The consumer-level data were extracted from Twitter —a social networking site—on which billions of users express their ideas and experiences. Each post by a user is known as a “tweet”. The customer-level data were collected between February 01, 2020 to November 30, 2021 covering the first two COVID-19 waves.

As shown in Fig. 1 , in India, the first COVID-19 wave is considered from March 01, 2020 to February 28, 2021 and the second wave is considered from March 01, 2021 to November 30, 2021. For the US, the first wave is considered from February 01, 2020 to June 30, 2021 and the second wave is considered from July 01, 2021 to November 30, 2021. The second wave in India brought more negative impacts as the number of new daily cases and fatality rate were significantly higher than the first wave. The second wave inflicted more fear on people's minds as the number of people hospitalized, and the load on medical infrastructure were significantly higher than the first wave of COVID-19.

COVID-19 cases and deaths in India and US.

Fig. 2 summarizes the research methodology adopted in this paper. Primarily, a four steps method was utilized for: (i) data collection, (ii) topic extraction, (iii) sentiment analysis, and (iv) moderation variable analysis. We used the company name, their Twitter handle, and related hashtags as keywords to extract the data. We extracted a total sample of 11,134 for Zomato, 14,355 for Swiggy, 15,583 for Uber Eats, and 2030 for Grubhub. The data were preprocessed by employing language identification, cleaning, tokenization, lemmatization, and removing stopwords. We kept data in English for further analysis, leading to a useful sample of 9447 for Zomato, 13,160 for Swiggy, 12,536 for Uber Eats, and 1951 for Grubhub. The remaining three steps are described in subsections 4.1, 4.2, and 4.3.

The proposed research methodology framework.

4.1. Text analytics and topic extraction

We employed the latent Dirichlet allocation (LDA) tool ( Blei et al., 2003 ) to identify hidden topics discussed in the large volume of unstructured data, as it does not assume any structure of grammar properties. The model was trained to identify the number of topics in unstructured documents. The extant literature ( Nikolenko et al., 2017 ; Lee, 2022) suggests a coherence score as a more reliable measure to discover the most prominent number of topics in a large volume of documents. Fig. 3 shows the variation of coherence score over topics 2 to 40 for each OFD company.

Coherence score of each OFD company.

We found the highest coherence score for each OFD company when the number of topics extracted was 13 for Zomato, 6 for Swiggy, 2 for Uber Eats, and 11 for Grubhub. We believe that there must be more than two topics related to Uber Eats discussed by customers, so we preferred to extract topics that correspond to the next highest coherence score. It results in 7 topics for Uber Eats. Topics and their associated 10 most important keywords of Zomato, Swiggy, Uber Eats, and Grubhub are presented in Table 1 , Table 2 , Table 3 , Table 4 , respectively.

Keywords, topics, and dimensions of Zomato and their statistics.

Keywords, topics, and dimensions of Swiggy and their statistics.

Keywords, topics, and dimensions of Ubereats and their statistics.

Keywords, topics, and dimensions of Grubhub and their statistics.

Topics extraction results are analyzed in three steps: (i) an expert team reviewed keywords of each topic and gave an appropriate name, as shown in Table 1 , Table 2 , Table 3 , Table 4 , (ii) each topic was then reviewed and higher dimensions which were a collection of topics were formed (see Table 1 , Table 2 , Table 3 , Table 4 ), keeping literature in mind, and (iii) based on percent tweets related to the dimensions (see Table 5 ), most prominent dimensions of each food delivery company and regions were identified and discussed in Section 5 . To label topics, the keywords of each topic were discussed and reviewed carefully by experts from academics. Further, we observed that a set of topics represents a higher-level dimension. Thus, we identified sets of topics representing higher-level dimensions. These dimensions are also shown in Table 1 , Table 2 , Table 3 , Table 4 .

Performance of delivery companies across different dimensions.

Further, we also extracted topics based on the COVID-19 waves to check if there is any difference in topics. The results show that in India, people discussed more regarding help and support for drivers and restaurants, vaccination requests, customized orders, and food quality in the second COVID-19 wave. In the first wave, we observed more discussion about consumers' perceived responsibility, perceived solutions, and companies' social responsibility. On the other hand, US people discussed more about coupons and promocode during the first COVID-19 wave. Whereas in the second wave, people emphasize more about vaccination, money spending, and delivery operations in the US market.

4.2. Sentiment analysis

Sentiment analysis is a procedure to quantify customers' experiences or emotions based on the subjective text data expressed by the customers (Lee, 2022). The sentiment was labeled based on the python package, Gensim/VADER. We preferred the VADER-based model as they provide a parsimonious rule -or lexicon-based model specially designed for social media text sentiment analysis. Social media text, especially tweets data, is characterized as short sentences/descriptions with emoji, copious use of question marks and exclamation marks, and repetitive words. This technique of unsupervised sentiment computation does not require features and is widely used in the literature ( Ibrahim and Wang, 2019 ; Lee, 2022; Mehta et al., 2021 ).

Customer sentiment may include positive, negative, or neutral (Lee, 2022; Liu et al., 2021), depending upon VADER based compound score that varies from −1 to +1. If the compound score was ≤ −0.05, between −0.05 and +0.05, and ≥ +0.05, the sentiment was labeled as negative, neutral, and positive (Lee, 2022). Lexicon-based sentiment computation approach matches words with a dictionary of words. First, we assessed the sentiment score of each tweet. Subsequently, we assessed topic-level and dimension-level sentiments using dictionaries or a pre-defined list of words approach. The topic- and dimension-level sentiment was determined by averaging the tweet- and topic-level sentiments, respectively. Dimension-level positive and negative sentiments of delivery companies are shown in Table 5 . Based on the mean score of positive and negative sentiment, the results are further discussed in section 5 .

4.3. Moderating variables

To test hypotheses, we considered two types of sentiment: net sentiment and negative sentiment, as response variables. Five important variables—COVID-19 wave, brand, market size, country, and listed, may influence customers' both types of sentiment/satisfaction. We employ the ordinal least square (OLS) regressions to estimate response variables, net sentiment, and negative sentiment. The relationship between the response variable and explanatory variables takes the form of equations (1) , (2) .

The COVID-19 wave, country, and “listed” are binary variables. The COVID-19 wave has two labels —the first and the second wave. The country has two labels—India and US. Similarly, listed has labels yes and no, where yes implies a company is listed in the stock market, and no for otherwise. Zomato and Grubhub are publicly listed OFD companies, while Uber Eats and Swiggy are not. The brand and market size are categorical variables, where the brand has four labels—Zomato, Swiggy, Uber Eats, and Grubhub. The market size has three labels: small, medium, and large. With a nearly $80.53 billion market cap, Uber Eats is considered a large-market size company. Zomato, Swiggy, and Grubhub, with a market cap of nearly $13.82 billion, $5 billion, and $10.55 billion, are considered medium, small, and medium market sizes, respectively.

The ordinary least squares (OLS) regression results are presented in Table 6 . The results show that there is a significant relationship between net sentiment and explanatory variable, the COVID waves (p < 0.05), brand (p < 0.05), market size (p < 0.05), country (p < 0.05), and listed (p < 0.10). Thus, the hypotheses H1 , H2 , H3 , H4 , and H5 are supported for the net sentiment. For the negative sentiment, we found that all the explanatory variables are significant (p < 0.05) except the country (p > 0.10). Therefore, hypotheses H1 , H2 , H3 , and H4 are supported for the negative sentiment; hypothesis H5 is rejected.

OLS regression results for hypotheses.

To identify specific pairs of groups that differ from each other, we conducted the Post-Hoc test of multiple comparisons of means—Tukey Honestly Significant Difference (Tukey HSD). The results are shown in Table 7 and discussed in the Discussion section.

Multiple comparison test results.

5. Discussions and managerial implications

The topic modeling results (from Table 1 , Table 2 , Table 3 , Table 4 ) convey the prominence of 13 topics for Zomato, 6 topics for Swiggy, 7 for Uber Eats, and 11 for Grubhub. These topics are further used to form higher-level dimensions that resulted—6 dimensions for Zomato, 4 dimensions for Swiggy, 5 dimensions for Uber Eats, and 4 dimensions for Grubhub. We find a wide range of topics (and dimensions) relating to OFD companies were expressed and discussed during the COVID-19 pandemic. Delivery operations, social responsibility, perceived consumers responsibility, the financial impact of COVID-19 on consumers, consumers perceived behaviors, perceived solutions, perceived negative impact of OFD, promocode and food delivery, free delivery, adapting to pickup/takeout service, and appreciation for drivers/restaurants are dimensions that emerged from our analysis.

As count or percent contribution is shown in Table 5 , overall, perceived consumer responsibility, delivery operations, social responsibility, perceived negative impact, free delivery, etc., are the most prominent dimensions related to OFD companies across emerging and developed countries. These findings differ from the previous literature ( Chen McCain et al., 2021 ; Dsouza and Sharma, 2021 ; Shah et al., 2021 ; Trivedi and Singh, 2021 ) that observed food quality and safety measures, socialization, and marketing are the main themes for OFD companies during COVID-19. Our topics seem more enlightening and COVID-19 pandemic-oriented rather than topics related to the usual expectations from OFD companies. Reasons for the difference may be due to the fact that this study is more comprehensive in terms of the number of companies included, the sample size considered, and the time period during which the sample was collected.

Table 5 further conveys that the mean score of the positive sentiment of most dimensions is more than the mean score of a negative sentiment of most dimensions of all OFD companies. Exceptions to this are financial impact and consumers' perceived behaviors of Zomato; delivery operations of Swiggy; promocode and food delivery of Uber Eats. These findings are different from the findings of Chen McCain et al. (2021) in the sense that they found that negative sentiment is more than positive sentiment.

Most of the identified topics for Indian firms Zomato and Swiggy belong to delivery operations, social responsibility, and perceived consumer responsibility dimensions (see Table 1 ). However, most of the topics of Uber Eats operating in the US belong to promocode/coupon on food delivery orders and free delivery. In contrast, for Grubhub, most topics belong to the appreciation of drivers/restaurants for delivery service and food delivery operations. Interestingly, a closer look at the topics and dimensions of Zomato and Swiggy conveys that people in India are more concerned about society, such as the social responsibility of OFD companies and the responsibility of consumers to society in such a hard time. People are more inclined toward spreading awareness and highlighting the responsibility of both consumers and delivery companies. As expected for OFD companies, we also found people discussing delivery operations dimension concerning to responsiveness of OFD companies and customized orders by following COVID-19 appropriate behaviors. Results in Table 5 show that perceived customer responsibility, delivery operations, and social responsibility are the three most prominent dimensions in the Indian market. On the other hand, delivery operations, fee delivery, and perceived customer responsibility are the three most prominent dimensions in the US.

Table 8 shows our identified dimensions and compares them with dimensions discussed in the literature. We observe that most of the existing studies ( Kim et al., 2021 ; Pal et al., 2021 ) deal with the operational aspect of delivery, while a few studies ( Li et al., 2020 ; Yeo et al., 2021 ) highlight the sustainability aspect of OFD companies, discount and promotion ( Kim et al., 2021 ), and concerned for drivers ( Huang, 2021 ; Ramos, 2021 ). However, we find perceived customer responsibility (contributing 28.27 percent) is the most important dimension, followed by delivery operations (contributing 25.9 percent) during the COVID-19 (see Table 5 ). Interestingly, compared to the existing literature, this study finds perceived consumers' responsibility, COVID-19 impacts on delivery business, benefits of competition, free food delivery service, and pickup/takeout services as unique concerns expressed and discussed by customers during the COVID-19 pandemic. During the COVID-19 pandemic, customers in India want OFD companies to be more socially sensitive, while US customers are concerned about discounts, coupons, free food delivery, etc.

Identified dimensions in this study and comparison with dimensions in literature.

We further observed that the net sentiment (i.e., positive-negative ) differs across COVID-19 waves, brands, market sizes, countries, and listed (see Table 6 , Table 7 ). Net sentiment during the second COVID-19 wave is significantly higher than that of the first COVID-19 wave. However, we also found that negative sentiment in the second wave (0.0761) was higher than in the first wave (0.0696) and significantly different (p < 0.05). It conveys that even though negative sentiment increased in the second wave, OFD companies have used their learning and experiences from the first wave and therefore could improve net sentiment during the second wave of COVID-19. Our findings are different from the literature ( Hong et al., 2021 , Hong et al., 2021 ) that finds no moderation effect of COVID-19 on the relationship between explanatory variables and intention to use OFD apps. We find that COVID-19 waves significantly influence customer sentiment, which aligns with the literature ( Birtus and Lăzăroiu, 2021 ; Mehrolia et al., 2021 ; Watson and Popescu, 2021 ), that observed that COVID-19 reshaped customers behaviors, attitude, and expectations.

Analyzing net sentiment across brands, we find that except for Grubhub and Swiggy (p > 0.05), all other pairs of brands are significantly different based on the net sentiment. Grubhub's mean net sentiment (0.0398) is significantly higher (p < 0.05) than Uber Eats (0.0175) and Zomato (0.0274). It shows that Grubhub performed better than other OFD companies. Swiggy received the second-highest mean net sentiment score (0.035), which is significantly higher (p < 0.05) than the net sentiment of Uber Eats and Zomato (see Table 7 ). Finally, Zomato's net sentiment is significantly higher (p < 0.05) than Uber Eats. Overall, Grubhub received the highest net sentiment, which is significantly higher than all other OFD companies. In India, Swiggy performed better than Zomato, whereas Grubhub did better than Uber Eats in the US. Grubhub also received the highest negative sentiment (0.07489), followed by Zomato (0.0729), Uber Eats (0.0710), and Swiggy (0.0683).

Table 7 further conveys that Grubhub's and Zomato's negative sentiments are significantly (p < 0.05) higher than Swiggy's negative sentiments. The negative sentiment of the remaining pair of companies does not differ significantly. Our findings indicate that brands play an important role in driving customer sentiment. This finding is aligned with previous literature ( Gani et al., 2021 ) that observed that restaurant reputation influences OFD apps' usefulness during the COVID-19 pandemic. These findings are different from the literature ( Prasetyo et al., 2021 ) that discovers restaurant credibility does not impact the intention to use OFD apps. It also differs from Trivedi and Singh (2021) , who observed more positive and less negative sentiment for Zomato than Swiggy.

Observing the importance of market size, we found that OFD companies with low, medium, and large market sizes received a mean net sentiment score of 0.0350, 0.0295, and 0.0175, respectively. Further, Table 7 clearly shows that low and medium market size companies have significantly higher (p < 0.05) mean net sentiment scores than large market size companies. This interesting finding conveys that low or medium market size companies can do better and receive better customer appreciation if they perform better during a crisis or on special customer demands.

We further observed that the medium market size company received the highest negative sentiment (0.0732), followed by large (0.071) and small market share (0.068). The negative sentiment of medium and large companies is significantly (p < 0.05) higher than those with small market sizes. It conveys that smaller companies may satisfy customers more in odd times than bigger companies. It may be because smaller companies might be delivering more customer-friendly services as they may be determined to increase their market share by satisfying customers. Challenging times like the COVID-19 pandemic can be used as an opportunity to create more customer-based value. Our findings are different from the literature ( De Mendonca and Zhou, 2019 ) that says larger companies can generate higher profit and customer satisfaction. Our results are more contextual and complex than the literature that says companies with higher market value may positively influence customers' perception ( Hu et al., 2009 ) and repurchase intention ( Bao and Zhu, 2022 ).

Analyzing results at the country level, we noticed that the mean net customer sentiment scores in India and the US are 0.0318 and 0.0205, respectively. Table 7 further confirms that India's net sentiment score is significantly higher (p < 0.05) than the US. As the US is a developed country with excellent infrastructure and customer-based operations are more prevalent—one may expect better customer satisfaction and customer experience from OFD companies in the US. However, interestingly, we find customers are more satisfied with OFD companies in India than in the US. These findings are in line with previous studies ( Charm et al., 2020 ; Steyn et al., 2010 ) that found customer sentiments vary greatly across different countries. Consumers in India, China, and Indonesia display more optimism than in the US (and the rest of the world) ( Charm et al., 2020 ). As far as negative sentiment is concerned, we find no significant difference (p > 0.10). OFD companies in India and US attract similar negative sentiments. It may be because the challenges faced by the companies are almost the same, and the reasons for customers to get discontent are identical, especially in terms of sanitization and COVID-19 appropriate behaviors.

Further, we found mean net sentiment score of the publicly listed companies (0.0295) is significantly higher (p < 0.10) than those of not listed companies (0.0264). Listed companies may have better perceptions and brand names that may positively influence customers' net sentiment. It is also possible that listed companies may adopt a more stakeholder-oriented approach ( Hickman, 2019 ), bringing better customer experiences. These findings align with the literature ( De Mendonca and Zhou, 2019 ; Hickman, 2019 ), highlighting that customers may be more loyal to publicly traded companies as they are more likely to be responsible to the environment and society. The negative sentiment of listed OFD companies (0.07325) also differs significantly (p < 0.05) from unlisted companies (0.06964). Noticeably, the negative sentiment of listed companies is higher than that of unlisted companies. It is possibly because customers have more expectations from listed companies ( Hickman, 2019 ) during the COVID-19 pandemic. Service delivery below the expectation may generate more negative sentiment. Our observations in terms of negative sentiment are different from the literature ( Hickman, 2019 ).

6. Conclusions and future scopes

This study brings a deeper understanding of customers' experience of OFD companies operating in the COVID-19 pandemic, a worse health crisis globally. During the pandemic, thousands of people were quarantined, and the remaining people could not go out to have food in restaurants because of strict lockdowns. During this time, OFD companies delivered food to people who had different expectations from the companies than expectations during the normal time. Especially, sanitization, COVID-19 appropriate behaviors, and social responsibility were among the most important expectations of customers. The central theme of this paper is to explore how OFD companies performed during the COVID-19 pandemic and whether they performed up to the expectations. It also analyzed whether OFD companies' performance differs across emerging and developed countries and different COVID-19 waves. We collected consumer data from Twitter, conducted a qualitative and quantitative analysis to understand several intricacies of OFD companies' operations during the COVID-19 pandemic, and compared our findings with existing literature. This study throws several exciting findings.

The most talked-about topics were social responsibility, delivery operations, perceived consumer responsibility, financial impacts of COVID-19, etc. People in India and the US think differently regarding OFD service during such a hard time. People in India are more concerned about the responsibility of OFD and consumers towards society, but in the US, people discuss more about discounts, coupons, free food delivery, etc. Therefore, managers of OFD companies in India and the US should prioritize their services accordingly. Our findings convey to managers of OFD companies that customer expectations during a crisis are not usual expectations (such as prompt service, good taste, etc.); they expect something beyond. Therefore, managers must understand expectations first and deliver experience accordingly. A few previous studies demonstrated more generic expectations. Theoretically, we observe that dimensions of customer expectations during the COVID-19 crisis differ from normal times.

We further offer important theoretical contributions that the net sentiment of people differs across different COVID-19 waves, brands, market size, countries, and publicly listed (or unlisted) companies. OFD companies improved net sentiment in the second wave of COVID-19, perhaps by using their learnings from the first wave. Overall, Grubhub received the highest net sentiment as well as the negative sentiment. Hence, to minimize negative sentiment, managers of Grubhub should align their service operations as per customer expectations. In India, Swiggy did better than Zomato. Managers of OFD companies should see the events like COVID-19 as opportunities where OFD companies with smaller market sizes also can do better than medium and large-market size companies. Customers are more satisfied in India than in the US; however, negative sentiment is almost equal in the two countries. The publicly listed OFD companies generate higher net sentiment as well as negative sentiment than those of unlisted companies. Hence, managers of listed OFD companies should control negative sentiment as per the performance on different topics identified. Interactions of COVID-19 waves, brands, market size, countries, and publicly listed (or unlisted) companies with net and negative sentiment of customers of OFD companies and its intricacies are interesting theoretical implications of this research.

This paper compares and contrasts OFD companies' consumer service and operations across emerging and developed countries and during the first and second waves of the COVID-19. By studying OFD during the COVID-19 pandemic, this study significantly and uniquely contributes to the existing literature ( Huang, 2021 ; Kim et al., 2021 ; Yeo et al., 2021 ) on retailers and consumers. We identified new topics of importance during a hard time of the COVID-19 pandemic, which are entirely different from topics discussed before the COVID-19 outbreak. We further identified different variables which are significantly influencing customers' sentiment.

Like any other study, this paper also has some limitations. We mainly studied OFD companies operating in India and US by collecting customers' data from Twitter. Future studies can extend the scope of this study further. In addition to the US and Indian markets, it would be interesting to study people's sentiments and identify concerning dimensions about OFD companies' performance in the European and South American markets. Further, the inclusion of financial variables, such as revenue and profit for OFD companies' delivery performance, would be another exciting study. Nonetheless, this study documents the service and operations performance of OFD companies during the COVID-19 health crisis on a large scale which can be used for a future contingency plan. Finally, another promising problem for future studies is investigating how people's sentiment affects the OFD companies' performance in the stock market during the COVID-19 period.

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Adoption of Online Grocery Shopping: A Systematic Review of the Literature

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• Kirti Prashar   ORCID: orcid.org/0000-0001-7439-7846 9 , 10 &
• Anil Kalotra 9  

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 2051))

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• International Conference on Applied Technologies

This article provides an SLR, or systematic review of the field of study known as “e-grocery adoption.’’ It suggests using grocery apps or online buying groceries to enhance marketing research. The purpose of this study is to critically revise and produce an essay about the adoption of grocery applications. 38 studies were produced by the SLR and presented concurrently to the adoption of grocery apps. Results from ahead descriptive analytics show the most important research questions around the adoption of grocery applications as well as diverse strategies that link researchers and participants in various research methods. The essay looks into the factors that led to the acceptance of grocery applications. The writers emphasized how the subject has evolved over time and noted the prospective potential future research topics. The study eventually provides references for further research on adoption of grocery applications.

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Prashar, K., Kalotra, A. (2024). Adoption of Online Grocery Shopping: A Systematic Review of the Literature. In: Botto-Tobar, M., Zambrano Vizuete, M., Montes León, S., Torres-Carrión, P., Durakovic, B. (eds) International Conference on Applied Technologies. ICAT 2023. Communications in Computer and Information Science, vol 2051. Springer, Cham. https://doi.org/10.1007/978-3-031-58950-8_2

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