Technological Disruptions in Restaurant Services: Impact of Innovations and Delivery Services

Abstract

This qualitative exploratory study assesses the technological disruptions in restaurant services caused by innovations in food delivery. A systematic review of the restaurant classification for the past two decades showed that the use of the term “restaurant delivery service” increased significantly since 2014 and is now used as often as “fast food service.” An improved typology of services as affected by technology is presented. A hypothetical model was developed to show the hierarchical progression of restaurant services as affected by technological innovations. Technological disruptions were categorized at different stages. The theory of disruptive innovation was assessed, and a hypothesis is presented to relate the impact on delivery services. Major disruptions identified are in the restaurant terminology/classification, widening of the distance between the service provider and customer contact points, and the potential collateral disruption to the service quality. Opportunities and challenges related to disruptions are identified.

Keywords

technological disruptions restaurant delivery services services typology third-party delivery services theory of disruptive innovation

Introduction

The velocity of technological advancements has noticeably affected the business world, affecting the traditional ways of manufacturing products and providing services. Restaurant business with a multitude of complex processes is also availing of the smart technologies that provide pervasive applications. Service providers and customers are both taking advantage of the availability and accessibility of emerging platforms in delivered services. In a race to benefit from technology in this competitive environment, there is a stark possibility of disruptions, particularly within the restaurant industry, which traditionally resists changes or is slower to adapt changes. Internet Connectivity, Big Data, and the Internet of Everything are revolutionizing production and consumption (Buhalis et al., 2019). These technological advancements affect service firms, customer engagement strategies, as well as their expectations (Helkkula et al., 2018).

According to the National Restaurant Association’s report, some of the most likely developments by the year 2030 include (a) vast majority of takeout and delivery orders will be placed digitally, (b) packaging designed for delivery and carryout will be more sophisticated, (c) more restaurant areas will have dedicated space for delivery and carryout, (d) the use of kiosks in limited-service restaurants will be common, (e) technology will be more effectively used to control costs and to increase management efficiency, and (f) the federal government will enact more data-privacy rules to regulate business and handle customer data. All the above predictions point to the increased use of delivery services by restaurants (National Restaurant Association, 2019).

Disruptions occur when an agent is disrupted to the extent that the agent has to redesign its strategy to survive a change in the environment. Christensen’s theory of disruption is the most often quoted theory for technological disruptions. According to Denning (2016), Christensen’s theory of disruption is a theory of competitive response. Actually, disruption is a process, not an event, and innovations can only be disruptive relative to something else. From the perspective of a system, a disruption is an event in which a substantial share of agents belonging to the system are disrupted (Lähteenmäki et al., 2017). According to Buhalis et al. (2019), disruptive innovation occurs when new entrants and conditions challenge and alter industry structures and behavior of actors. Airbnb is an example of technology-led disruption (Guttentag & Smith, 2017), where a platform enabled hosts and guests to connect and cocreate value. In this case, Airbnb represents an innovative accommodation product that has shifted perceptions of hospitality throughout the hotel industry. Although not in the same way, third-party delivery services use innovative technology (primarily using apps and GPS) that has shifted perceptions of a dining experience, honoring personal preferences, and providing convenience and privacy.

Paradoxically, disruptions are often interpreted negatively, while they also provide opportunities for development, correcting mistakes, expanding market, shaping strategies, and introducing new ideas. The analyses in this study consider both positive and negative disruptions. The disruptors predicted by the National Restaurant Association for the coming decade include (a) information technology will permeate restaurants, (b) emergence of more “cloud kitchens” and “virtual restaurants,” (c) consumers may grow increasingly loyal to third-party delivery apps, (d) autonomous vehicles will change how people on the road get their food, and what they eat and drink in cars, (e) nonfood companies could add food and prepared meals to their offerings as an added service, (f) automation and robotics will have a more significant role in food preparation, and (g) the decline of shopping malls and “brick-and-mortar” retail will lead to restaurants becoming even more critical for public outings, community engagement, and socializing. The report also predicts that over the next decade, technology and data will become a greater focus for restaurants. Guests will expect a seamless digital experience and want their preferences known at each interaction. On the other hand, with accelerated sales growth due to off-premise traffic, consumers will place heightened importance on experiential dining on on-premises occasions as a result of accelerated sales.

Technological Innovation in Services

A modified definition of innovation based on the nature of services states,

services innovation is the intentional introduction and application within a role, group, or organization of ideas, processes, procedures, or products related to services, designed to significantly benefit the individual, the group, organization, or region; considering the distinguished characteristics of services and consumer satisfaction. (M. Khan & Khan, 2009, pp. 510-511)

Service innovation has significant effects on behavioral intention and customer experience. Hospitality services innovations are very different from any industry ones since they include consideration of attributes such as intangibility, heterogeneity, simultaneous production and service, and perishability. It was concluded in a study that the service delivery methods are undergoing changes based on technological advancements, and service providers should consider those changes and utilize them in providing efficient services (Su, 2011).

The Popularity of Delivered Foods

There seems to be a rush to get into the food delivery service by restaurants, either by having their own delivery service or in combination with third-party delivery services. Some of the examples are provided to show a snapshot of the current race to embrace delivery services. Chipotle added direct delivery service through Alexa apps, which reached seven million enrollments. In more than 2,500 units, Chipotle’s loyalty members can add their profile to the app and can reorder their favorite to-go meal by saying: “Alexa, tell Chipotle to reorder my favorite for delivery.” The feature is available only for reordering and cannot be used to create new orders. It is also offering AI (artificial intelligence)-powered voice assistants to all restaurants, which are designed to let the customers have the option of going through the entire order effortlessly, whereas employees can focus on providing a unique guest experience. The voice automation offers the option of paying ahead, skipping the lines and going straight to the digital pickup shelves or driving through the Chipotlanes, which are pick-up only car lanes that are being pilot tested, eventually to be added to the newly constructed restaurants. Other chains, including Domino’s and Good Times Burgers & Frozen Custard, are also testing the conversational AI (Luna, 2019a, 2019b, 2019c).

It was reported by DoorDash that their customers are exploring more diverse flavors when ordering food since 30% of the customers reported that they typically eat 5 to 10 different cuisines per month. Of particular note is the increase in Thai foods, new cuisines with side dishes, and desserts. Apple pie had an increase of 1,550% in 2019 orders by DoorDash customers. Also, 96% of the customers customize their orders with do-it-yourself, with pizza being on top of the orders. Make-your-own sushi rolls increased by 902%, while soups and sandwiches were also popular in orders (Fantozzi, 2019). Other well-recognizable delivery services include GrubHub, Seamless, UberEats, Postmates, DoorDash, Caviar, Bitesquad, Eatstreet, Zomato, and Beyond Menu, to name a few. Many more services are expected to join the delivery service business.

While there is a relatively large number of studies on technological disruptions in other areas, limited studies are in the hospitality industry. In this study, disruptions due to technological innovations were evaluated using the case of restaurant delivery services. Therefore, the following objectives were selected that describe the intent of this study: (a) to examine the impact of technological disturbance(s) to the traditional services classification/terminology; (b) to present a readjusted typology of services, considering the technological disruptions; (c) to assess the impact of disruptions on the relationship between the service provider and the customer; (d) to examine disruptions in light of the theory of disruptive innovation and assess its relevance to the restaurant industry; and (e) to present a theoretical proposition based on the changes due to the technological disruptions.

Theoretical Implications

The most often used and significant model is the technology acceptance model (Davis et al., 1989). It explains an individual’s acceptance of information technology and determines user attitude and the role of perceived ease of use and perceived usefulness. One of the criticisms of this theory is that it does not fully reflect the nature of consumer adoption (Min et al., 2019). It is used jointly with other theories, such as the diffusion of innovative theory, which aims to help predict how people make decisions to adopt a new innovation (Min et al., 2019). Although this theory deals with decision making, it does not focus on postdecision activities.

Interpretative hierarchy theory dealing with self-reflective processes, particularly observation and description, is used to analyze complex and dynamic relationships at different levels. This takes into account ongoing innovations and their rapid technological changes among commercial firms. This theory was used in medical practice to adequately describe the transformation of observed technological hierarchies over time (Galbrun & Kijima, 2010). It also helps in situations where complex relationships are involved.

The most frequently used theory of disruptive technology has two characteristics; first, it tends to underperform the established company’s products by its inability to serve mainstream customers’ needs, even if it is attractive to a segment of customers that are underserved by the established companies, thereby providing an opening. Second, the disruptive technology’s products can become a threat by improving rapidly along the dimensions that are important to mainstream customers. Gans (2016) describes the strategy of dealing with disruptions as (a) beat them, (b) join them, and (c) wait them out. Briefly stated, these strategies suggest companies avoid potential disruption and tackle them by (a) investing in the new disruptive technology, (b) cooperating with or acquire the market entrant, or (c) having critical assets that entrants lack for buying time (Gans, 2016).

King and Baatartogtokh (2015) identified four key elements of the theory of disruptive innovation: (a) incumbents in a market are improving along a trajectory of sustaining innovation, (b) they overshoot customer needs, (c) they possess the capability to respond to disruptive threats, and (d) incumbents end up floundering as a result of the disruption. They questioned the usefulness of the theory and how well it describes what actually happens in business. The reasons for their reservation include that the theory’s essential validity and generalizability have seldom been tested in academic literature, and the theory’s exemplary cases did not fit all its conditions and predictions well.

During any service encounter, the customer can be considered as a coproducer, cocreator of value, or as a collaborator (Bendapudi & Leone, 2003; Vargo & Lusch, 2008); thus the customer contributes to the quality of service and their own satisfaction, as well as creates value during their interactions with the physical and social elements of the service. Accordingly, it seems crucial to integrate the client’s role as a new collaborator in the organization and to facilitate the customer’s understanding of their role (Montargot, 2016). An earlier study (Ottenbacher & Gnoth, 2005) based on a survey of German hoteliers identified factors that promote successful service innovations. The nature of the innovation was described as far less important than the effectiveness of a hotel’s human resources management and employee training, empowerment, and commitment to the service. Montargot (2016) concluded that a new hospitality concept gives more autonomy to the clients and mobility to front-line employees.

In delivery service, the online platform plays an important role. In developing an online platform, it was recommended (Sharma & Kumar, 2019) that emphasis should be on appeal, the appearance of website, timely orders, error-free transactions, interest in customer problems, confidence, and dependability for customers. Customer feedback about service received and customer evaluation and complaints should be taken into consideration. Customer satisfaction was reported to be positively and significantly related to the likelihood of repeat patronage and positive recommendations. Also, an increase in service quality components increases a consumer’s intention to revisit and recommend.

Methodology

This qualitative exploratory study is based on a systemic evaluation of technological development and consequent disruptions in the services provided by restaurants. First of all, a systematic review of the literature using Hospitality & Tourism Complete from the EBSCOhost database was conducted to see the frequency of the use of the “delivery service” term in publications from the years 1998 to 2019. This exercise intended to know the frequency of the use of the term for the past two decades in comparison with the other terms used in the classification of restaurant foodservices, eventually to assess any potential disruptions in the traditional typology due to the innovative technologies. In the second phase, an extensive review of the relevant literature was conducted on innovations and technology disruptions and related theories. On the basis of a comprehensive review of the innovation and technology theories, a hypothetical model was created, delineating different stages of disruptions due to technology. The model was also used to predict a hypothesis for a possible theory that is related to the impact of technological disruptions on the relationship between the service provider and the customer.

Discussions

Typology and Terminology Disruptions

The first objective was to examine the impact of technological disturbance(s) to the traditional terminology/classification of services. It was evident that the current and predicted use of technology in restaurant operations and services markedly affects the conventional classification of the restaurants based on the services. According to a 10-year outlook report published by the National Restaurant Association, in partnership with American Express and Nestle Professional, the restaurant industry sales are expected to reach $1.2 trillion by 2030. Interestingly the prediction indicates that the definition of “restaurant” will change as the digital world and evolving consumer preferences are resulting in restaurant models that are based on giving customers what they want, when, and where they want it. Off-premise opportunities will drive the industry’s growth (National Restaurant Association, 2019).

Barrows and Vieira (2013) provided recommendations for the development of a new operational classification system for the foodservice industry. An extensive comparative study of the existing classification showed that there was no uniform system of classification that would accurately differentiate between different types of foodservice establishments. Based on the average check, their classification of restaurant clusters included quick-service, fine dining, fast-casual, casual/upscale casual, cafeteria/buffet, and casual/delivery/takeout.

The traditional typology of independent restaurants included three segments: quick-service, midscale, and upscale. Considering the prominence of the multiunit environment at that time, two additional segments, moderately upscale (casual) and business (industry dining), were recommended by Muller and Woods (1994). Customer decision attributes for visiting quick service were low price, convenience, speed, and consistency. For midscale, these attributes were a menu, value, comfort, and table/counter service; and for moderate upscale, the customer decision attributes were a fashion statement, ambiance, and flexibility. Style, ambiance, service, and dining experience were the attributes for upscale restaurants. For business dining, these attributes were different and included location, no menu fatigue, price, value, and ease of purchase decision (Muller & Woods, 1994). In short, their typology constituted quick service, midscale, moderate upscale, and upscale. They added business (or industry and contract foodservice) dining to the initial four segments. Historically, the National Restaurant Association has reported five major restaurant industry segments: quick-service restaurants (QSR or fast food), fast-casual, midscale, moderate (or casual), and fine dining (or upscale), and it also distinguishes among independent and multiunit (chain) restaurants. The U.S. Census Bureau, in its North American Industry Classification System (NAICS, 2017), proposes four primary subcategories under code.722, Foodservices and Drinking Places: full-service restaurants; limited-service restaurants; cafeterias, grill buffets, and buffets; and snack and nonalcoholic beverage bars. Descriptive adjectives presented as subcategories of the North American Industry classification system include diners, family dining, fast food, fine dining, pizzerias, steak houses, and takeout/carryout restaurants. This classification is intended for government use in statistical analyses of business establishments; however, it is also used in industry and academia (Canziani et al., 2016). A Chicago-based market research firm, the NPD Group, predicts that over the next 10 years, the very definition of what makes a restaurant will change. They cannot ascertain the future status of the traditional brick-and-mortar restaurant as more serve-yourself kiosks, delivery-only models, and robot-staffed concepts continue to emerge (Glazer, 2019). Based on the latest report outlining projections for restaurants for the next 10 years, there will be a change in the way restaurants are classified. A hybrid model will be adopted by some restaurants offering counter service, full service, takeout and delivery, and meal kits. The delivery-only restaurant will lead to virtual restaurants and “ghost kitchens” (National Restaurant Association, 2019).

Since there are different bases on which restaurants are classified, an attempt was made to evaluate the use of different classes in literature from the year 1998 to 2019. As shown in Figure 1, both peer-reviewed and trade publications indicated the use of different types of terminology for restaurants. Comparing the frequent use of different classifications, it is apparent that the term fast food restaurant was most often used, followed by casual dining service and fine dining service restaurants. The use of fast-casual restaurant was used least frequently. The peak period of use of all the terminologies except for the restaurant delivery was during the years 2005 to 2006. From that period onward, there was a decline in usage of all classifications between the years 2010 and 2019. This decline is indicative of a lack of finite definitions or confusion related to the use of different terms. The noteworthy fact is that although the restaurant delivery service term was used less frequently in earlier years, starting from the year 2014, there was a rapid increase in its use, which is an indication of the popularity of this type of service. By the year 2019, the term delivery service was used as often as fast foodservice. The frequency of the use of the term delivery service reached from 36 to 138, from 2014 to 2019, which is a big jump considering the fact that the frequency of other terms declined during that period. The steep rise and fall of the use of earlier classifications indicated that there is some disruption in its use, and a well-defined method of classification is warranted. Although this disruption may not be related to the use of technology, there is still a need to reform and revise.

Figure 1

Restaurant Types

A distinct impact of disruptions due to technology is in the generation of new terminology. With the simultaneous growth in demand for carryout and delivery services, unique terminology is emerging for use in operations and food delivery. Some terms are in use without verifiable definitions of the terms or an established industry conversation language or vocabulary. Some of the terms for food preparation areas are dark kitchens, ghost kitchens, virtual kitchens, shadow kitchens, and cloud kitchen/commissary. Although there are no clear definitions for these terms, an effort is made to highlight some of the essential features in the following paragraphs. Apparently, the restaurant industry is struggling with the variety and opaqueness of the vocabulary. One standard feature for kitchens described by these terms is that the kitchens are not housed in the restaurants but in rented spaces, shared commissary, or spaces removed from the typical brick-and-mortar restaurant kitchen areas, without a dining room or serving space.

When shared commissary spaces are used for kitchens, focusing on the delivery of foods, they are referred to as central kitchens, rent-a-kitchen, ghost kitchen, dark kitchen, virtual kitchen, or even a high-tech term, “cloud commissary.” For example, DoorDash Kitchens are shared ghost kitchen spaces in Northern California that have rental spaces for other restaurant brands striving to expand their off-premise sales in the pricy Silicon Valley area (Anonymous, 2019). Chick-fil-A launched a delivery-only operation from DoorDash Kitchens that also houses four other Bay Area restaurants. DoorDash Kitchens is a part of a growing network of rent-a-kitchen facilities (Luna, 2019a, 2019b, 2019c). Terms such as virtual restaurant, delivery-only restaurant, or cloud restaurant refer to restaurants that are housed in an established traditional restaurant. Associated with the use of different types of kitchens, new terminology being used includes “delivery-only” restaurant or “digital” restaurant.

The physical servicescape refers to the overall environment, including the ambiance of a restaurant. On the other hand, social servicescape refers to the sharing of space with others. Some types of restaurants, such as bars or fine-dining establishments, have relatively well-defined service delivery models, whereas with restaurants, such as casual or family restaurants, service norms are more ambiguous (Hanks et al., 2017).

Terminology can also be based on customer contact with the service provider. Much of the emphasis is currently placed on having effective customer contact or touchpoints in services. These contact points will be subjected to disruptions since they will be changed, altered, or eliminated. Lee (2018) and Lee & Lee (2019) used the term, “untact,” as a portmanteau term created in South Korea by adding the prefix “un,” which has the meaning of “no,” to the word, “contact,” to refer service that is provided without face-to-face encounters between employees and customers through the use of digital technologies. According to the author, this term reflects the shift in consumption trends to noncontact services based on untact technology that in essence reflects the generational and social changes. Kim et al. (2019) suggested four significant avenues of value creation offered by the untact technology: (a) quick service at any time, due to customers dislike for complicated procedures or waiting to receive services at any time; (b) convenience and in one go, due to the dislike having to visit multiple destinations to purchase goods and services; (c) privacy and secrecy due to reluctance to expose one’s personal information; and (d) receiving customized services tailored to customers’ preferences.

The earlier studies mentioned are based on a variety of services providing goods and materials; however, in the case of food delivery service where customers have limited or no contact with the service provider, the term “untact” can be altered to “de-tact,” or detached contact, since there will still be some attachment, albeit limited, at least to the brand name of the original supplier or the third-party delivery service. The reason for the detact technology use in foodservices can be predicted to be due to (a) convenience, (b) individual preferences, (c) accessibility, and (d) customized services. The diffusion of disrupting innovations can bring in significant market changes, modifying the dominant logic, and affecting the strategic positioning of companies. The disruptive changes affect several aspects as well as relationships between players and their changing roles (Viglia et al., 2016). In this digital age, customers demand customized services that support their tastes, needs, and lifestyles (Lee, 2018) that is made possible by the technology-enabled innovation systems. Technology-supported innovation can shift specific transaction task responsibilities from workers to customers. Although many business firms have offered self-service, do-it-yourself, cafeteria-style services, and information kiosks as a result of the technology-supported innovation, in the digital age the degree of transference has gone far higher than the traditional encounters.

Services Typology and Technological Disruption Stages

The second objective of the study was to present a readjusted typology of services, considering the technological disruptions. With the growing use of technology, there is a need for a services typology that identifies the way technology is used. Lee (2018) classified the technology-based forms of contact during the service encounter into three types. The first is a technology-facilitated service, in which the customer and service provider complete the service together using robots or machines. The second is a technology-mediated service, where the customer interacts only with a screen using robots or machines without direct contact with the service provider. The third type is a technology-generated service, in which the customer voluntarily creates and completes the service using robots or machines. According to the author, technology can be used to gradually reduce the interaction between the customer and the service provider.

Considering the earlier typology by Lee (2018) and based on an extensive study of the impact of technology innovation and using foodservice delivery as a case, a typology using six distinct types of services is proposed. These types describe the hierarchical process from traditional restaurant services to technology-assisted delivery services to remote sites. They also represent the intensity of possible disruptions subsequent to the introduction of supporting technology. The suggested typology includes (a) limited technology-services, (b) technology-facilitated services, (c) technology-mediated services, (d) technology-generated services, (e) technology-enabled services, and (f) technology-dependent services. These types also coincide with the states of technological disruptions that are described below. A summary of these types of services and the stages of disruption are presented in Table 1.

Stage 1: At this stage, there is limited use of technology that is confined to use in equipment or operations, such as using the conventional POS (Point of Sales) system. Restaurants that can be included at this stage are traditional restaurants with all different types of services, including fast foods (QSR), fast-casual dining, casual dining, and fine dining restaurants. Customers visit these restaurants for experience, entertainment, socializing, and/or fulfillment. Providing convenience and/or efficient service with good customer contact is practiced in line with the type of service offered. Face-to-face interaction takes place between the service provider and customers. This stage also serves as a primary point for comparing the technological disruptions in other types of services. Responsibility for the quality of food and services rests with the service provider. These restaurants can offer unlimited varieties of menu items. The disruptions are proportional to the extent of technology used, hence classified as limited technology use services.

Stage 2: This stage comprises process improvements in services using technology, such as ordering kiosks in restaurants. This is common in fast food operations where a customer can order foods either using an app or by individual machines provided within the restaurant. This is referred to as the technology-facilitated services, where the customer and service provider both complete the service together. The interaction is somewhat limited, and the consumer plays a role in the performance of services as a participant assisting the service provider. There is no limitation on the number of menu items offered, and the customer uses technology only on placing the order. From this point onwards, the service satisfaction splits between the actions of the customer versus the service provider, as seen in the following stages.

Stage 3: Mainly comprised of pick-up service and is classified as technology-mediated service, where the customer interacts only with a screen using Internet/mobile phones with minimal direct contact with the service provider. The consumer has a choice of selection of the options and does not have to interact with the service provider. Both parties fulfill their part contributing to service satisfaction, convenience, and smooth operation. The menu choices are limited since the food quality of the delivered food may get affected until it is consumed.

Stage 4: This stage consists of own and third-party delivery services classified as technology-generated service, in which the customer voluntarily initiates the service process resulting in food delivery provided by the restaurant using its own delivery service or using a third-party service. In the completion of service, the customer has a bigger role in selecting service and menu items. The responsibility for the quality of food rests with the service provider and/or third-party deliverer. Also, there is a legal liability related to food safety. Menu choices are reasonably limited since only those menu items can be used that can withstand delivery and retain quality until consumed.

Stage 5: Freestanding delivery service only, is a hybrid between other technology-enabled services, where the restaurant serves only as an outlet for pick-up with no additional services provided. This is based primarily on the convenience of the customer. The use of technology is limited since there is mainly customer pickup from a central kitchen. There is no seating or any other interaction with the service provider. This type of service is classified as the technology-enabled services, where the customer primarily handles the technology component.

Stage 6: This stage is composed of the drone delivery service, which is a highly technology-dependent delivery service in which there is no face-to-face interaction with the customer and service provider. This arrangement facilitates both convenience for the customer and extends the reach of the service provider with expanded market and span of service. The responsibility for the food quality rests with the provider, but the quality of service is dependent on the technology. Menu choices are extremely limited. This technology is still under the experimental stage, although some restaurants are already using it on a limited basis.

Table 1

Stages and Impact of Technological Disruptions

Disruption Stage	Technology Use	Interactions Between Provider and Customer	Responsibility for the Quality of		Menu Choices	Examples	Disruption Impact
Disruption Stage	Technology Use	Interactions Between Provider and Customer	Food	Service	Menu Choices	Examples	Disruption Impact
Stage 1	Limited technology use services	Face-to-face	Provider	Provider	Unlimited	All types of restaurants	Confined to limited technology use
Stage 2	Technology-facilitated service	Slightly limited	Provider	Customer + Provider	Unlimited	Service Kiosks in fast food restaurants	The customer uses technology to order only
Stage 3	Technology-mediated services	Very limited	Provider	Provider	Slightly limited	Pick-up services in casual dining restaurants	The customer uses technology to order and picks up food
Stage 4	Technology-generated services	Limited with the service provider/full interaction with the deliverer	Provider + Deliverer	Deliverer	Fairly limited	Third-party delivery service or restaurant’s own delivery service	The customer has a choice of selection of service. Liability of the quality is on the delivery service
Stage 5	Technology-enabled services	Extremely limited	Provider	Pick-up service provider	Fairly limited	Free-standing delivery only service	Customer orders and picks up from an outlet
Stage 6	Technology dependent services	None	Provider	Technology	Extremely limited	Drone food delivery service	Customer orders and food delivered by drones

Hypothetical Model

Analyses of the recent trends related to the use of technology predict disruptions to the operational and service aspects in the restaurant industry. With the rapid increase of the Internet-enabled services and social media, consumers are more involved in securing information as well as purchasing after a value comparison. This change in the purchasing environment has become a driving force in nudging consumers toward more value-oriented behaviors (Kim et al., 2019). It is predicted that the future consumption culture and customers’ lifestyles will become more fragmented and reflect the influence of digital devices (Lee, 2018).

The third objective of the study was to assess the impact of disruptions on the relationship between the service provider and the customer. Using the different stages of disruption, a hypothetical model was created, as shown in Figure 2. One axis shows the direct/indirect contact with the customer, while the other axis shows the distance with the service provider. As clearly evident, with each addition of innovative technology, there is disruption taking place, resulting in reduced contact with the customer and increasing distance between the service provider and the customer. Each disruption causes a change in the operational parameters and the type of service provided. An analytical view, as seen in the figure, shows a distinct trace showing an upward hierarchical and latent move progressively separating the user from the service provider. Therefore, with the intensity of technology use, a wedge is created between the service provider and the customer. Although intentional, this apparently disrupts the traditional ways in which restaurants have operated and provided service. In fact, it disrupts the very social inclination to visit a restaurant as a place of enjoyment, recreation, and fulfillment.

Figure 2

Hypothetical Model Showing the Hierarchical Progression of Restaurant Services and the Impact of Technology

Theoretical Underpinning

The fourth objective of the study was to examine disruptions in light of the theory of disruptive innovation and assess its relevance to the restaurant industry. King and Baatartogtokh (2015) questioned the usefulness of the theory of disruptive innovation and how well it describes what actually happens in business. The reasons for the authors’ reservations included that the theory’s essential validity and generalizability have seldom been tested in academic literature, and the theory’s exemplary cases did not fit all its conditions and predictions well. One of their observations was based on the laws of probability, such as new infrastructure and changing demographics caused an expansion of business opportunities creating a “gold rush.” They mentioned that although many of the old chains such as Howard Johnson’s and Dairy Queen managed to survive, some of the new companies such as McDonald’s and Burger King proved to have selected better buying models and eventually emerged as the biggest winners. If the sheer numbers of the new entrants are large, the incumbent companies cannot claim as many claims. Findings in this study agree with the author’s analogy of the “gold rush” as evident with the rapid use of the third-party delivery services by prominent chains. As shown in the graph in Figure 1, even the term “delivery service” is being used as much as the term “fast food” in restaurant classification. Companies that had delivery service in their concepts are opting for additional services from third-party services, intending to gain markets as well as get access to online subscribers. Little Caesars pizza chain announced a deal with DoorDash to provide delivery as it gets ready to move the traditional pickup pizza chain to compete even more directly with rivals Domino’s, Papa John’s, and Pizza Hut. Chains do not want to be left behind in the “gold rush” taking place when other chains are using third-party delivery services, although pizza chains traditionally depended on their own delivery service. Similarly, Panera Bread and Outback had their delivery join the third-party services.

Hypothesis Development

The last objective of the study was to present a theoretical proposition based on the changes due to technological disruptions. It is accurate, as stated earlier, that the theory of disruptive innovation is not tested in all academic circles, mainly the ones related to the restaurant and foodservice industries. Considering the impact of technology on the relationship between the service provider and the customer, as shown in Figure 2, the most evident factor was the wedge that is created by technology. This disruption creates an interruption in the services by either technology or third-party service provider or both.

Consequently, a hypothesis was initiated based on the phenomena observed in the hypothetical model. Specialized theories that focus on hospitality services are nonexistent, and most of the theories are borrowed from other disciplines. A framework for theory in applied hospitality discipline should be based on a phenomenon backed by research, and applicable to practice (M. A. Khan, 2019). Based on this definition and all observations in this study, a hypothesis or a theoretical proposition is suggested that can be stated as “With each hierarchical technological innovation in restaurant services, the distance between the service provider and the customer increases, resulting in either positive or negative implications for service provider and the customer.” As with all theories and hypotheses, this statement is subject to changes and additions. This hypothesis is primarily floated for criticism and modifications as necessary.

Conclusions

The use of technology has a disruptive impact on services, considering the current growth of demand for food delivery. How long this trend will last is difficult to say since there are still unknown parameters to judge the success of third-party deliveries. Facts may reveal that the deliveries are not as big a profit maker as expected and carry liability related to service quality and food safety. Maybe the chains will realize that jumping into the third-party deliveries was not a good idea and may consider their own delivery service.

Also, in agreement is our observation that established companies such as McDonald’s and Burger King have better capability to survive disruptions due to their numbers and their well-established business status. Time will show how the number of new entrants will affect the incumbent companies. Existing theories related to technological disruptions do not focus on the disruptive impact on food delivery services. One of the significant disruptions is the apparent wedge being created between the service provider and the customer. The attributes of services being intangible, heterogeneous, simultaneous production and service, as well as the dimensions of empathy and courtesy, are subjected to the “collateral” disruptions due to the application of technological innovations. In fact, the most applicable ServQual measure of service quality needs to be reevaluated in light of the delivery services, particularly involving third-party delivery services. The contacts or touchpoints, which are so crucial in services, also become detached or, as mentioned earlier, get “de-tact,” thereby creating problems for the service providers.

Technological disruptions can have both positive and negative impacts, some of which are worth mentioning and considering. According to Dawson (2019), the New York City council’s Small Business Committee is conducting a comprehensive legislative inquiry into the impact of third-party delivery platforms on the restaurant sector. According to one council member, there is a concern that a third-party delivery system will trap restaurant owners in an unstable, unsuitable business model that does not add to the bottom line but could eat at their profits. The delivery business is a lot of work at low margins, and so is the restaurant business. Low profitability and charges of third-party delivery are bound to become discussions in the future.

The most significant impact will be on the quality of food and food safety since menu items do not retain quality after some time and withstanding the transportation rigor. Ingredients like sauces do not keep well during delivery. Another issue is related to liability related to accidents and food safety. The responsibility of any potential foodborne outbreak is still not clear. Similar to the “transfer of ownership” in transport, it is not clear as to which point the liability will transfer from the service provider to the third-party delivery service. The charges for delivery services and their impact on profitability still need to be figured out, although the tech-savvy customers may not mind adding costs in place of convenience. Yet unknown is the impact on the franchising and franchisee’s reactions to the use of technology and possible changes in service.

On the positive side, restaurants can benefit from the increased market size and customer reach. Savings can also result from reduced seating and equipment requirements. It may also provide opportunities to focus on customers who enjoy eating at the restaurant and redesigning services to keep and develop loyal customers. New modes of marketing are possible using technology, such as introducing innovative apps. Even the free delivery service will add to the promotional tactics. Overall there is a need for changing strategies to either adapt or resist technological disruptions.

Footnotes

ORCID iD

Mahmood A. Khan

Mahmood A. Khan, PhD (e-mail: mahmood@vt.edu), is a professor and director, MSBA program in Hospitality & Tourism Management, Pamplin College of Business at Virginia Tech, Greater Washington DC Metro Campus, Falls Church, VA.

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