Research Paper

What factors determining customer continuingly using food delivery apps

during 2019 novel coronavirus pandemic period?

Yuyang Zhao *, Fernando Bacao

NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Campus de Campolide, 1070-312, Lisboa, Portugal

ECM

TTF

Food delivery apps (FDAs) as an emerging online-to-offline mobile technology, have been widely adopted by

catering businesses and customers. Especially, as they have provided two-way beneficial catering delivery ser-

vices in rescuing catering enterprises and satisfying customers’ technological and mental exceptions under the

COVID-19 global pandemic condition. This study proposes a comprehensive model integrating UTAUT, ECM and

TTF with the trust factor and examines 532 valid FDA users’ continuance intention of using FDAs during the

COVID-19 pandemic period in China. The statistical results and discussions show that satisfaction is the most

significant factor, and perceived task-technology fit, trust, performance expectancy, social influence and

confirmation have direct or indirect positive impacts on users’ continuance usage intention of FDAs during the

of Mobile Operators, global mobile phone users exceeded 5.1 billion in

2020, among them, over 1.2 billion users are accounted for in China

(GSMA, 2020). Meanwhile, various mobile services are significantly

developed and implemented in different industries. Food delivery apps

(FDAs) as online-to-offline mobile services have recently gained popu-

larity offering two-way benefits for catering enterprises and customers

by providing convenient and efficient online order and offline delivery

services. Statista Reports (2019) illustrated that FDAs revenue in China

(38.4 billion US dollar (USD)) generated more than one-third of global

FDAs revenue (95.4 billion USD) in 2018. Moreover, global FDAs rev-

et al., 2020). According to a report from the World Health Organization

(WHO), until 21 May 2020, there were a total of 4,904,413 globally

2020a). During the COVID-19 crisis, wearing a mask in public, social

contacts among people to reduce the risk of COVID-19 transmission

(Wilder-Smith and Freedman, 2020; Tang et al., 2020). Moreover,

because fewer customers intend to use public services, the traditional

catering industry has suffered dramatically during the COVID-19

pandemic. According to the data of iiMedia Research (2020), in China,

the revenue of the catering industry was 419.4 billion yuan (59.2 billion

USD) during January to February 2020, which decreased 43.1 % year on

year. 95.0 % of the interviewed catering businesses’ revenue of the

stores decreased significantly during COVID-19 epidemic period (iiMe-

dia Research, 2020).

tuan research institute (2020), there were 71.7 % of 15,263 participants

using FDAs from the end of February to beginning of March 2020, and

* Corresponding author.

E-mail addresses: d2015046@novaims.unl.pt (Y. Zhao), bacao@novaims.unl.pt (F. Bacao).

Contents lists available at ScienceDirect

https://doi.org/10.1016/j.ijhm.2020.102683

Received 24 May 2020; Received in revised form 11 August 2020; Accepted 3 September 2020

third-party FDAs (Ele.me, Meituan Waimai and Baidu Waimai).

Compared to before the COVID-19 pandemic outbreak, the catering

enterprises registered on FDAs have dramatically increased 63.1 % in

China, and 70 % of the surveyed restaurants will continue to operate and

increase investment in FDAs after the COVID-19 epidemic. Moreover,

according to the business registration data from Tianyancha (2020),

there were 106,000 new enterprise registrations related to food delivery

services from January to May 2020, up 766 % from the same period in

2019. The estimated scale of the Chinese online food delivery market

will exceed 91.8 billion USD in 2020 (iiMedia Research, 2020). There-

stakeholders to understand customers’ requirements and expectations.

In terms of FDA adoption, customers consider performance expectancy

as the main determinator to adopt a relevant service (Yeo et al., 2017;

Roh and Park, 2019). Moreover, easiness and quality of service, con-

venience, social influence and satisfaction are also considerable ante-

cedents of intention to adopt FDAs (Yeo et al., 2017; Cho et al., 2019;

Correa et al., 2019; Ray et al., 2019; Roh and Park, 2019). Meanwhile, in

terms of continuance usage of information technology, performance

expectancy, effort expectance, social influence and satisfaction are

important for formulating users’ continuance usage intention (Gao et al.,

has a significant impact on users’ continuance usage intention.

Meanwhile, Yuan et al. (2016) combined ECM with the Technology

Acceptance Model (TAM) and the Task-Technology Fit model to explain

that users’ continuance usage intention is determined by perceived

task-technology fit and confirmation. However, few prior investigations

have focused on factors affecting FDAs’ continuance usage, especially

under pandemic condition. Consequently, the purposes of this study are

to fulfil the gap of factors determining users’ intention to use FDAs

during the COVID-19 period continuously and support FDA relevant

stakeholders to understand customers’ perceptions and behaviours for

COVID-19 pandemic.

2. Theoretical background and hypotheses development

2.1. Food delivery apps (FDAs)

FDAs, as an emerging online-to-offline mobile technology, provide a

channel between catering enterprises and customers by integrating on-

line order and offline delivery services. FDAs can be categorised into two

patterns (Ray et al., 2019). First, the restaurants themselves, such as

KFC, Domino’s and Pizzahut etc. Second, the third-party intermediary

platforms, such as, Uber Eats, Zomato, Ele.me Meituan Waimai and

Baidu Waimai, which are more popular and have been widely adopted in

benefits in efficiently maintaining social distancing during the

COVID-19 pandemic, enriching service range and reducing the

spatio-temporal interval of sales and consumptions processes (Liu and

Wang, 2016). Therefore, the quality of FDA services significantly im-

pacts on users’ perceptions. Several previous studies have focused on

various factors affecting users’ intentions to adopt FDAs. Yeo et al.

(2017) emphasised post-usage usefulness and perceived convenience

motivation as significantly affecting customer’s behavioural intentions

to adopt online food delivery services. Moreover, Roh and Park (2019)

modified TAM with the moral obligation moderator and found that

attributes affecting the intention of using online food delivery services.

Furthermore, Ray et al. (2019) implemented the uses and gratifications

theory and validated that customer experience, ease-of-use and tech-

nological characteristic had significant impacts on behavioural intention

to use FDAs. Likewise, Cho et al. (2019) associated multi-dimensional

perceived values with attitude to investigate continuance intention of

FDAs. They presented that trustworthiness has the most significant

positive effect on perceived value towards formulating users’ attitudes

to continue using FDAs.

Therefore, according to previous relevant researches and character-

influence (Roh and Park, 2019) from UTAUT, satisfaction (He et al.,

2018) and confirmation (Yeo et al., 2017) from ECM, perceived tech-

nology task fit (Elvandari et al., 2018) from the Task-Technology Fit

model and trust (Cho et al., 2019). Furthermore, the following parts

introduce the theoretical foundations that contribute to the con-

ceptualisation of the research model.

tems. Specifically, the UTAUT model has been modified with other

variables and widely implemented on mobile technology adoption. For

example, Khalilzadeh et al. (2017) modified UTAUT to verify that trust

is associated with security and risk, and significantly affects customers’

intentions to use mobile payment technology. Min et al. (2008) com-

bined UTAUT with satisfaction to analyse mobile commerce adoption in

China. Moreover, UTAUT has also been integrated with other models for

investigating mobile technology adoption. For example, Zhou et al.

(2010) integrated the Task-Technology Fit model with UTAUT and

found that performance expectancy, task-technology fit, social influ-

ence, and facilitating conditions had significant effects on mobile

banking adoption in China. Afterwards, Oliveira et al. (2014) integrated

UTAUT with the Task-Technology Fit model and the Initial Trust Model

(ITM) and validated that initial trust, performance expectancy, tech-

nology characteristics, and task-technology fit are important predictors

to formulate users’ intention to adopt mobile banking. Furthermore,

Y. Zhao and F. Bacao

intention of mobile technology (Chopdar and Sivakumar, 2019; Mar-

ECM was proposed by Bhattacherjee (2001) and is rooted in the

expectation–confirmation theory (ECT) (Oliver, 1980). It consists of

three dimensions, including performance expectancy, confirmation and

satisfaction for evaluating continuance usage intention of information

systems. ECM has been widely implemented in various continuance

adoptions of mobile technology. Such as Hung et al. (2012) who

modified ECM with the trust factor and proved that consumers’ satis-

faction and trust had a significant impact on continuance usage inten-

tion of mobile shopping. Chong (2013) extended ECM with perceived

ease of use, perceived enjoyment, trust and perceived cost to analyse

Tam et al., 2020 ECM

UTAUT2

expectancy

Y. Zhao and F. Bacao

2.3. Development of hypotheses

2.3.1. Revisiting the UTAUT model

2.3.1.1. Performance expectancy (PE). According to UTAUT, perfor-

mance expectancy (PE) is defined as the degree to which the user be-

lieves that using a particular technology will facilitate his or her

performance in a certain activity (Venkatesh et al., 2003). PE is a sig-

nificant predictor to determine a user’s intention to adopt new tech-

networking apps (Lai and Shi, 2015), mobile banking (Yuan et al., 2016)

and mobile shopping applications (Chopdar and Sivakumar, 2019).

Moreover, PE also has a significant effect on consumers’ satisfaction

towards affecting the continuance intention of using mobile technology

(Tam et al., 2018). In terms of UTAUT, studies by Marinkovi´

c et al.

(2020) and Chong (2013) verified that PE is a significant predictor

affecting the satisfaction of users’ continuance usage of mobile com-

merce. Furthermore, the ECM posits that PE significantly influences the

satisfaction and continuance intention of using mobile technology (Yuan

et al., 2016; Susanto et al., 2016). Accordingly, PE is considered as a

H5: Effort expectancy (EE) positively affects satisfaction (SA) to-

wards continuously using FDAs during the COVID-19 pandemic.

2.3.1.3. Social inuence (SI). According to UTAUT, social influence (SI)

is defined as the degree that users gain willingness from others’ (e.g.

families, friends and colleagues) encouragement that they should use a

angle has been supported in various aspects, such as mobile social

network sites (Zhou and Li, 2014), shopping apps (Chopdar and Siva-

kumar, 2019) and mobile payment systems (Zhu et al., 2017).

Furthermore, SI not only directly determines users’ continuance inten-

tion, but also indirectly formulates users’ intention to continuously use

mobile technology by affecting their satisfaction (Hsiao et al., 2016).

Marinkovi´

c et al. (2020) revised UTAUT to confirm that SI has a sig-

nificant effect on users’ satisfaction towards continuance intention of

using mobile technology. Therefore, the following hypotheses are pro-

posed in this study:

behaviour of integrity and ability (Gefen, 2000; Grazioli and Jarvenpaa,

Y. Zhao and F. Bacao