Consumers’ intentions to use online food delivery systems in the USA

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Consumers’intentions to use

online food delivery systems

in the USA

Nefike Gunden,Cristian Morosan and Agnes DeFranco

Conrad N. Hilton College of Hotel and Restaurant Management,

University of Houston, Houston, Texas, USA

Abstract

Purpose –The recent development of online food delivery systems (OFDS) consolidated the restaurant

industry’s representation in the electronic distribution landscape. The purpose of this study is to examine

consumers’intentions to use OFDS.

Design/methodology/approach –A comprehensive structural model was developed based on

UTAUT2 and extended the model with three additional constructs: impulse buying tendency, congruity with

self-image and mindfulness. Data were collected from 605 US respondents. Conﬁrmatory factor analysis and

structural equation modeling were used to test the model.

Findings –Performance expectancy was the strongest predictor of intentions to use OFDS, followed by

congruity with self-image. Low-magnitude predictors included habit and mindfulness, while impulse buying

tendency had a negative impact on intentions to use OFDS.

Research limitations/implications –The study validates a comprehensive yet parsimonious

conceptual model that explains consumers’intentions to use OFDS. The model brings together constructs that

capture the essence of the online food ordering tasks and the consumers’cognitive processes that inform such

tasks.

Practical implications –This study offers substantial practical implications for two types of

practitioners: OFDS developers and restaurants and provides a mapping of the factors inﬂuencing consumers’

intentions to use OFDS.

Originality/value –This study provides a ﬁrst theoretical perspective on consumers’intentions to use

OFDS, which have not been studied so far. Studying such intentions provides insight into consumers’

adoption behaviors, which are critical to the success of OFDS.

Keywords Mindfulness, Restaurants, Electronic commerce, Technology adoption, Delivery systems

Paper type Research paper

Introduction

Conforming to a predominant 2010’s trend, distribution using Online Foodservice Delivery

Systems (OFDS) is becoming a signiﬁcant part of restaurant industry distribution (Muller,

2018). In 2018, online ordering was the most liked method for ordering restaurant food for 45

per cent of the US population (Morning Consult, 2018). The OFDS market is growing with

estimated revenues of $715m in 2019 and a forecast exceeding $950m by 2023 in the USA

(Statista, 2019a) and $82bn globally (Statista, 2019b). While initial efforts to develop OFDS

have emerged in mid 2010s (Grubhub Holdings Inc, 2019a), the recent advancements in

integration/middleware have created opportunities for restaurants to integrate their point-

of-sale software with today’s OFDS (Grubhub Holdings Inc, 2019b). The resulting

This research has been conducted with the support of Hospitality Financial and Technology

Professionals (HFTP).

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intentions

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Received 30 June 2019

Revised 12 September 2019

5 December 2019

27 February 2020

Accepted 6 March 2020

International Journal of

Contemporary Hospitality

Management

Vol. 32 No. 3, 2020

pp. 1325-1345

0959-6119

DOI 10.1108/IJCHM-06-2019-0595

The current issue and full text archive of this journal is available on Emerald Insight at:

https://www.emerald.com/insight/0959-6119.htm

integration facilitated the aggregation of supply into OFDS that offer consumers various

choices in terms of platforms, restaurants and product customization. Such features give

OFDS the unique potential of radically disrupting the restaurant industry, illustrated by

OFDS revenues that are expected to surpass the revenues from restaurants’direct-to-

consumer deliveries in 2020 (Statista, 2019b).

Characterized by user interfaces that are grounded on the same generic retail principles

as websites (Suhartanto et al., 2019), the user experience that OFDS offer and the way the

primary consumer task of food ordering is carried out require unique consumer behaviors

that are substantially different from those used on typical retail websites. While general

consumer behavior on retail websites has been explained in prior research, consumers’

behavior relative to OFDS remains unknown to date. Understanding such behaviors helps

to explain how OFDS can become successful permanent hospitality actors. Most

importantly, as OFDS are generally commission-based, their success is entirely dependent

on consumers’adoption. However, despite the potential ramiﬁcations of the mass adoption

of OFDS and the meritorious ﬁndings of the scarce previous research (Cho et al., 2019;

Suhartanto et al., 2019;Yeo et al., 2017), there is no systematic program of research or study

that has examined consumers’adoption of OFDS in the USA to date, marking a critical

lacuna.

Indubitably, OFDS are poised to cause substantial disruption to the distribution system

of US restaurants (Cho et al.,2019) and other industries (Statista, 2019b). By design, OFDS

deprive consumers of a legacy element of foodservice consumption: dining in a public

environment of the restaurant (Jeong and Jang, 2016). Yet, as more than 80 per cent of the

orders are placed from home (Hirschberg et al., 2016), OFDS facilitate the reconstruction of

this experience within consumers’residences where the success of a dining episode is no

longer conditioned by the legacy elements of restaurant service (e.g. atmospherics, server

interactions and appearance), but rather by a combination of familiar home-related elements

(e.g. socialization, combination of food and beverages from multiple vendors). While the

general adoption literature provides insight into the factors inﬂuencing consumers’

intentions to purchase such digitized experiential products such as customizable hotel stay

experiences (Morosan and DeFranco, 2019), it does not offer insight into purchasing

hospitality products that can be digitized on the web while being reconstructed at the

consumer’s residence (Correa et al.,2019), marking a second research lacuna.

The types of products being sold using OFDS are unique: highly perishable and

heterogeneous (Kotler et al., 2016), thus adding a layer of complexity to consumers’

purchasing decisions and the purchasing environment. First, OFDS aggregate supply from

a large variety of restaurants with different degrees of brand equity and awareness among

consumers (Duncan, 2019), which requires consumers to undergo learning processes that

inform their purchasing behaviors (Suhartanto et al.,2019). Second, fulﬁllment time causes

the degradation of certain organoleptic properties of the purchased products. However, such

degradation is different from one type of product to another (e.g. a salad may lose its

properties faster than a pizza during a relatively long delivery during the rush hour). Thus,

consumers are likely to undergo highly involving cognitive processes that require a state of

permanent awareness throughout their purchasing experience. Yet, there is no evidence in

the literature that documents the adoption of systems delivering products where consumers

have to go through such highly involving and complex decisions (Bujisic et al.,2014),

marking a third research lacuna.

Addressing the three research lacunae simultaneously, the goal of this study is to

examine US restaurant consumers’intentions to use OFDS based on antecedents that fully

capture the nature of consumers’food ordering task. To this end, this study validates a

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conceptual model built on the classic technology adoption theory that provided system

perception constructs (i.e. performance expectancy) and consumer inherent characteristics

associated with adoption (e.g. habit) (Venkatesh et al.,2012). This theoretical foundation was

augmented with constructs describing the state of mind facilitated by the characteristics of

the purchasing environment (Rook, 1987) or consumer characteristics (e.g. impulse buying

tendency) (Wells et al., 2011), congruity with self-image (Jeong and Jang, 2018) and

constructs describing the cognitive processes necessary to make a risk-free decision when

buying a product such as a food item (i.e. mindfulness) (Sun et al., 2016). To accomplish its

goal, this study follows two speciﬁc objectives:

(1) to examine the differential role of perceptions and consumer characteristics in

inﬂuencing intentions; and

(2) to ascertain the multidimensional role of mindfulness in stimulating intentions.

Review of literature

Theoretical foundations

The study’s conceptual model was designed to fulﬁll three important criteria:

(1) provide a theoretical base that comprehensively captures the unique context of the

food ordering task;

(2) provide a sufﬁciently broad scope by including constructs that captures the unique

nature of products sold via OFDS while addressing the three aforementioned

research lacunae; and

(3) retain parsimony.

According to the ﬁrst criterion, this study developed a conceptual model that revisited the

legacy adoption theory – Uniﬁed Theory of Acceptance and Use of Technology (UTAUT2)

(Venkatesh et al.,2012). UTAUT2 was revisited by retaining two original constructs –

performance expectancy and habit – and adding three constructs (impulse buying tendency,

congruity with self-image and mindfulness) to investigate consumers’intentions to use

OFDS. UTAUT2 was the preferred theoretical framework for three reasons:

(1) it has been validated as a strong framework for predicting behavioral intentions in

multiple service contexts (Morosan and DeFranco, 2016a);

(2) it captures the speciﬁc task-technology environment of consumer-oriented tasks

(Morosan and DeFranco, 2016a); and

(3) it lends itself to extension via constructs capable of providing comprehensive yet

parsimonious illustrations of system adoption.

Of the seven independent variables of the original UTAUT2, only two were retained.

Performance expectancy was retained because it remains the most fundamental antecedent

of adoption (Venkatesh et al.,2003). Habit was retained because of its ability to explain

adoption of IS where the consumers are familiar with the task from other contexts (e.g.

ordering food from restaurants, shopping online for other products) (Okumus et al.,2018).

Five variables that were originally included in UTAUT2 were not retained in this study

because they could not capture the motivational fabric of using OFDS while preserving

parsimony. Speciﬁcally, effort expectancy was not retained as generally OFDS are designed

with intuitive interfaces, which guide the consumers through the purchasing task in ways

that are similar to other retail environments. Social inﬂuence was not retained as generally

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intentions

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ordering via OFDS is already inﬂuenced by the social interactions that naturally occur

within the consumption party (e.g. couple/family/friends, coworkers), regardless of which

member of the group places the order. Facilitating conditions was not retained because of

the ubiquity of the OFDS and restaurant products in the US market. Hedonic motivation

was not retained as the current model includes the concept of congruity with self-image,

which provides a more comprehensive basis of a consumer’s self-image evaluations (Stets

and Burke, 2005). Finally, price value was not retained because there is no cost associated

with the use of OFDS, as intended in the original model (Venkatesh et al., 2012).

While keeping two independent variables from the UTAUT2 represents a substantial

modiﬁcation of the original model, this new theoretical foundation retains the same

perception-behavior path that has characterized this model since inception and allows it to

explain adoption behavior based on users’perceptions and consumer characteristics

(Benbasat and Barki, 2007). The retained path between performance expectancy and

intentions remains fundamental to IS adoption because it is present in one form or another in

a variety of theoretical models, beyond the UTAUT (Jahanmir and Cavadas, 2018). In

particular, this path reﬂects the primary cognitive processes that evaluate the ability of a

system to facilitate the task (Venkatesh et al., 2003) and stimulate users’evaluations of

systems when facing a task (Venkatesh et al.,2012). However, habit reﬂects the users’

automatic behavior tendency that impact IS use (Lymayem et al., 2007) and explains

motivations that are not necessarily thoroughly elaborated by users but rather

automatically evoked in certain familiar contexts (Escobar-Rodríguez and Carvajal-Trujillo,

2014) (e.g. when sufﬁcient similarity exist with other routine tasks). Thus, based on the

contrasting nature of the two variables, performance expectancy and habit were used as a

core UTAUT-based foundation without compromising parsimony; therefore, this model

allows to address the ﬁrst research lacuna.

In line with the second and third criteria, this study incorporated additional constructs to

address the three lacunae while retaining parsimony. UTAUT2 was reconstructed by the

addition of three concepts based on the thesis that this particular extension from UTAUT2

must comprehensively and parsimoniously capture the task-technology environment of

OFDS. While the literature offers a rich variety of constructs that could inﬂuence intentions

to use a new system, the unique environment of OFDS called for three types of constructs.

First, as OFDS are geared toward persuading consumers to engage in target behaviors in

the absence of face-to-face communication (Cho et al.,2019), this model needs a construct

that reﬂects consumers’constant mind-changing as a result of discovering new information

available about or on OFDS. To capture this critical aspect, impulse buying tendency (Wang

and Tsai, 2017) was added to theoretical foundation. Impulse buying reﬂects consumers’

buying behaviors that occur suddenly (Piron, 1991). As restaurants have begun to shift their

focus to online delivery options (Morgan Stanley Research, 2017), OFDS started to offer

various options such as multiple product selections, different time ranges for delivery,

personalization and online payments (Hirschberg et al.,2016). Simultaneously, their

advertising power has increased. As a result, the way consumers make their decisions to

purchase using OFDS is different than in other online retail environments. For example, a

critical aspect is the state of relative hunger or consumers’anticipation of the meal. This

may precipitate the decision-making process, thus creating situations when consumers may

spontaneously purchase food.

Second, recent data show that certain consumers (e.g. younger and urban) are likely to be

attracted more by OFDS (Statista, 2019b). Therefore, recognizing the intrinsic motivations

that can lead to OFDS utilization, this theoretical foundation required a construct reﬂecting

such motivational fabric and added congruity with self-image to the core foundation.

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Congruity with self-image reﬂects the level of match between the consumers’perception of a

brand or experience with their identities (Luna-Cortés et al., 2019). The design of OFDS is in

line with the design of other similar retail platforms, which could be found appealing only

by certain segments of consumers. Thus, it is possible that consumers who view themselves

as typical users of such systems to be attracted by OFDS. Such motivations may originate

in the user interface characteristics (e.g. inherently intuitive) but also in task characteristics

(e.g. desire to try something new). Overall, the inclusion of impulse buying tendency and

congruity with self-image positioned this conceptual model to address the second research

lacuna.

Third, recent consumer behavior insight shows that consumers are not merely passive

users of an IS; instead they like to interact with the system to maximize value in use (Tu

et al.,2018). Important elements of the use of IS include consumers’continuous awareness of

the task and their continuous adaptation of their behavior to make the systems work for

them in accomplishing the tasks (Pickert, 2014). Scholars’attention increased toward the

consumer-oriented tasks in online shopping as a continuous process of using IS (Wang et al.,

2015). This is especially important in context where tasks –such as ordering via OFDS –are

addressing needs that are situated at various levels within a consumers’hierarchy of needs

(i.e. hunger as a physiological needs and customization of an online platform as self-

actualization). Thus, to capture OFDS’interactive environment’sinﬂuence on consumers

intentions (e.g. modifying food items and adding tips for drivers) mindfulness was added to

the core foundation (Thatcher et al.,2018), which allows this conceptual model to address the

third research lacuna.

Hypotheses development

Performance expectancy. Derived from the perceived usefulness construct of the original

technology acceptance model (Davis, 1989), performance expectancy reﬂects the perception

of a user that IS helps the user complete a task better than its rival systems (Venkatesh et al.,

2003). Performance expectancy has been validated as a strong predictor of intentions to use

IS in various contexts, including hospitality (Okumus et al., 2018). OFDS have been designed

to facilitate food ordering task completion in lieu of or addition to traditional systems (e.g.

direct phone or web ordering). Compared to phone ordering, consumers can check the

information about multiple food items on a uniﬁed platform, therefore optimizing the task

(Quevedo-Silva et al.,2016). Compared to restaurants’websites, OFDS allow consumers to

compare offers from multiple restaurants. Moreover, consumers can optimize ordering on

OFDS by browsing information about future purchases without a task being imminent.

This process enhances the information search phase of their purchasing, which can result in

effective task completion. Based on the discussion above and the recent literature (Yeo et al.,

2017), the following hypothesis was developed:

H1. Performance expectancy is positively related to the consumers’intentions to use

OFDS.

Habit. Habit reﬂects a relationship between a person’s past and future behaviors (Kim and

Malhotra, 2005). Habit has been validated as an antecedent of users’behaviors, especially

when repetitive behaviors manifest in IS use (Limayem and Cheung, 2008). Thus, habit

reﬂects consumers’continuous use of IS, in alignment with their satisfaction from previous

purchasing experiences (Khalifa and Liu, 2007). Given the ubiquity of today’s IS devices,

consumers develop habitual use patterns (Jasperson et al.,2005), which facilitates

subsequent use. Most contemporary online retail environments are grounded in the same

principles: guiding consumers through a linear path from information to decision-making,

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purchasing and fulﬁllment. OFDS makes no exception. Consumers ordering a food item are

guided by OFDS through this linear path, which enhances their learning effects and

optimizes subsequent episodes of use. Corroborated with similar processes from other online

retail environments (e.g. software, education and food service) (Correa et al.,2019), the

resulting habit can lead to intentions to use such systems in the future. Thus, it is expected

that consumers’habits inﬂuence their intentions to use OFDS, according to the following

hypothesis:

H2. Habit is positively related to the consumers’intentions to use OFDS.

Impulse buying tendency. Impulse buying reﬂects the tendency that leads consumers to

spontaneously purchase a product (Chan et al.,2017). In online shopping, various IS

attributes (e.g. website quality) (Wells et al.,2011) and value retained by shoppers (Chung

et al.,2017) were found to inﬂuence consumers’impulse buying tendencies, which can

inﬂuence their intentions to purchase (Chung et al., 2017). The value that consumers could

retain can be assessed based on persuasive information/advertising in the retail

environment. As advertising stimulates impulse purchasing (Madhavaram and Laverie,

2004), consumers who are impulse buyers may be tempted to use OFDS. Such behaviors

may be exacerbated by the innate appetizing presentation of food items in retail and the

urgency to eat. Moreover, impulsive consumers may purchase using OFDS based on

browsing because OFDS offer intangible beneﬁts that can stimulate purchasing (e.g.

removing certain ingredients and creating a product bundle) (Sharma et al., 2010). Therefore,

characterized by persuasive information OFDS are environments where impulsive buyers

can determine stimuli that can guide them from information to purchasing, therefore

suggesting a relationship between impulse buying tendency and intentions to use OFDS:

H3. Consumers’impulse buying tendency is positively related to their intentions to use

OFDS.

Congruity with self-image. Congruity with self-image reﬂects the match between the

consumers’self-image and a brand or product image referencing the purchasing motivation

(Sirgy and Su, 2000). Self-image congruity is important to OFDS as both the food service

(Jeong and Jang, 2018) and IS literature (Carter and Grover, 2015) have recognized its role in

inﬂuencing consumers’intentions. Speciﬁcally, an individual can attach himself/herself to

an IS, which eventually integrates into his/her identity (Schwarz and Chin, 2007). OFDS

reﬂect marketing strategies designed to attract speciﬁc segments of consumers, stimulating

them to recognize the match between their self-image and the OFDS. Most importantly, the

cognitive evaluation of the match between a consumer’s perceived image of himself/herself

and that of the OFDS that is characterized by novelty (e.g. new technology, disruptive

business model, creating an identity with a third-party company that is not part of the

legacy hospitality industry) could reﬂect a high level of match, which could result in

intentions (Sirgy, 1982). Thus, consumers high in self-image congruity with OFDS could

display high intentions to use OFDS:

H4. Consumers’congruity with self-image is positively related to their intentions to use

OFDS.

Mindfulness. Mindfulness refers to individuals’awareness about the context and content of

information (Langer, 1997). It is a condition of being open to use IS where individuals

consider both details and features (Thatcher et al., 2018). When being mindful, users are

likely to consider various uses of IS (Roberts et al.,2007), which is fundamental to

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stimulating intentions to use IS (Sun et al., 2016). Mindful users continuously scan the task

environment to determine the best opportunities to interact with an IS (Thatcher et al.,2018).

Moreover, consumers’cognition when immersed in a task may inﬂuence their level of

performance in task completion (Butler and Gray, 2006) because they adapt to new

situations for accomplishing tasks (Teo et al.,2017). Accordingly, consumers are likely

to acknowledge the details and features of OFDS, which range from system design features

(e.g. shopping cart management), to the mix of hard products (e.g. customization) and soft

product features (e.g. rewards, coupons). For example, a consumer using an OFDS may see

an option for a food item made from local ingredients. Changing the consumer’s initial

choice may result in an optimized task completion because the new choice can be more

beneﬁcial. The consumer can further optimize his or her purchasing task by applying

coupons found on the OFDS. Thus, OFDS-mindful consumers are likely to develop

intentions to use OFDS:

H5. Consumers’mindfulness toward OFDS is positively related to consumers’intention

to use OFDS.

Mindfulness comprises four dimensions:

(1) alertness to distinction;

(2) awareness of multiple perspectives;

(3) openness to novelty; and

(4) orientation in the present (Thatcher et al., 2018).

Alertness reﬂects the users’tendency to be aware of the differences between the way they

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