Int. Journal of Business Science and Applied Management, Volume 17, Issue 3, 2022
Impact of Consumer Inertia on Mobile Commerce Adoption
under the Influence of Market Isomorphism Effects
Tiu Chai Hui
Faculty of Economics and Business, Universiti Malaysia Sarawak, Jalan Datuk Mohammad Musa
93400 Kota Samarahan, Sarawak, Malaysia
Tel: +60123480145
Email: elinatiu@yahoo.com
Dayang Affizzah binti Awang Marikan
Faculty of Economics and Business, Universiti Malaysia Sarawak, Jalan Datuk Mohammad Musa
93400 Kota Samarahan, Sarawak, Malaysia
Tel: +6082584492
Email: amdaffizah@unimas.my
Abstract
This study examines consumer mobile commerce adoption through consumer adoption behaviour from
intention to use into adoption under the influence of consumer inertia and market isomorphism. The
presence of inertia elements could naturally act as an inhibiting agent in adopting consumer
technological systems. With increasing social networking media, which resulted in increasing social
interactions, these surrounding social forces could spur change behaviour that could subsequently
influence consumers’ adoption decisions, for example, market isomorphic forces. This study uses
partial least squares structural equation modelling (PLS-SEM) to analyse 403 collected questionnaires
from individuals above 20 years old and who own at least one smartphone. The derived results show
behavioural intention to use positively influenced consumer inertia. The natural inhibiting role of
consumer inertia is weakened by two market isomorphism forces (i.e., coercive pressures and
normative pressures), thus leading to positivity toward mobile commerce channel adoption. However,
mimetic pressures were statistically insignificant. Empirical findings confirm the intercorrelation of
consumer inertia 1st order dimensions, and market isomorphism discriminant validity. This study also
highlights the importance of inertial factors and market isomorphic forces that retailers or service
providers need to consider before implementing mobile commerce app systems.
Keywords: market isomorphism, mobile commerce adoption, omnichannel, institutional theory,
consumer inertia
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1. INTRODUCTION
With widespread digitisation with disruptive technologies (i.e., mobile commerce) included in the
revolutionised omnichannel retailing paradigm, retailers and consumers simultaneously took advantage
of these great potentials for business growth and shopping convenience respectively. The introduction
of Web 2.0 smart technologies has created exponential growth in smartphones and the use of internet-
enabled mobile devices through supporting interactivity, social connectivity, and user-generated
content, which empowered consumers to perform online activities with a certain degree of
independence. The developments have greatly expanded online interactivity and utility, such as online
shopping, retrieving information, comparing alternatives, and sharing, online review blogs (Carlson et
al., 2019; Holmes et al., 2014; Wang et al., 2015; Yang et al., 2017). However, mobility inclusion
could affect consumer habits together with expectations are changing alongside increasing
technological advancements, where consumers are required to learn, re-learn, and adapt to these
changes. Some consumers are willingly accepting this digitisation, while others treat it as unwanted
proximity that is intrusive, resulting in a refusal acceptance and maintaining the status quo.
Statistical evidence has shown incremental internet user penetration and high smartphone usage
rates among Malaysians. A high e-commerce awareness presence is detected (MCMC, 2019). But
non-adopter bystanders exist and revealed their preference to deal with banknotes (cash) or debit/credit
cards remain the dominant forms of retail transaction in Malaysia (Muller, 2022). Malaysians are
inclined to perceive a high degree of threat (MCMC, 2019). Extant studies relating to Malaysia’s
mobile commerce outlooks also specified that even with the apparent benefits that mobile shopping
could provide, adoptions occasionally are obstructed by fear and anxiety, which resulted in an
unwillingness to switch away from their incumbent systems. At the same time, empirical findings have
highlighted that mobile commerce is still at an early stage of adoption in Malaysia, where the attitude
toward mobile commerce adoption is still ambiguous (Balakrishnan & Shuib, 2021; Chan et al., 2022;
Jin et al., 2020; Lui et al., 2021; Moghavvemi et al., 2021; Tew et al., 2021; Yan et al., 2021). The
awareness among consumers regarding Fintech in Malaysia is also relatively low (Aziz & Bakri, 2021).
Similar circumstances applied to Sarawak (the 13th state in Malaysia, located in East Malaysia).
Serojai et al. (2021) have identified extant studies usually focused on Malaysia, where few studies
were on determining consumer readiness for the adoption of mobile commerce-related services.
Sarawak is ranked 3rd lowest in-terms of e-commerce and broadband penetration rates (MCMC, 2021).
Consumers' non-adoptive nature could be from consumer inertia, which formed the attitude to the
status quo, with a preference for familiar incumbent channels over emerging mobile commerce
channels. Retailers must understand consumer behaviour, which shapes expectations. It is the
consumer expectations that lead to adoption. However, successful consumer adoption is affected by
numerous factors besides social norms and the need for new technological adaptations. This gives
retailers greater challenges as there is an urgent need to close the practical gap between the offered
retailing system's capabilities and delivering consumer expectations before attaining a higher adoption
rate among consumers. Retailers need to lead consumers into adoption and understand consumer
adoption behaviour.
Malaysian consumer readiness is questionable even though e-commerce awareness is high
(MCMC, 2021). The ambiguous consumer attitudes are due to various issues such as the lack of
confidence and skills, the high perceived threat (creating trust issues), frauds, products lost in transit,
receipt of damaged products, and products received not matching the ordered specifications. All of
these tend to lead consumers to prefer physical retail stores and dealing in cash among consumers over
online transactions (MCMC, 2021). Social factors are specified to have direct effects on consumer
behaviour, for example, the buying behaviour of consumers (Qazzafi, 2020) and consumer preference
choices in the electric appliances market (Furaiji et al., 2012). This study focuses on market
isomorphism, which is a type of social force adapted from the institutional theory concept where
consumers are pressured into adopting rules and social norms to increase social legitimacy and
conformity to standards and linkages to society (DiMaggio & Powell, 1983; Hwang & Um, 2021).
Hence, there is a high likelihood of consumers either mimicking, complying, or compelling into
adopting actions for their channel preference choice for linkages into the community (Hwang & Um,
2021).
Investigating consumer inertia and market isomorphic forces that could affect mobile commerce
channel adoption in Malaysia would provide a comprehensive understanding of consumer adoption
behaviour. The presence of inertial elements could naturally inhibit adoption as market isomorphic
forces could be the sources that weaken this inhibiting nature of consumer inertia and lead to mobile
commerce channel adoption. Past studies that addressed technology adoption issues identified
individual unique behaviour effects on innovative technologies by focusing on instrumental beliefs like
perceived ease of use and perceived usefulness as drivers of usage intention (Bendary & Al-Sahouly,
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2018; Davis, 1989; Kim et al., 2017). Juaneda-Ayensa et al. (2016) addressed adoption issues
differently, focusing on the technological and management context by examining how consumers
derive and use the information before and during the processing process. Technology adoption studies
commonly study the technology and management factors with minimal emphasis on the effects of
social processes or human factors (i.e., social norms, consumer inertia, market isomorphic forces)
except for some studies incorporating selective human, environmental, and social elements.
Many technological adoption-related studies adapted the UTAUT2 (Unified Theory of Acceptance
and Use of Technology) model (Venkatesh et al., 2012) as a fundamental theory because of its high
predictive power (Mosquera et al., 2018; Venkatesh et al., 2012). However, most studies did not
include the whole model dimension and selectively included a few specific dimensions. Some studies
integrated into the conceptual framework with other factors from social and human aspects for the
verification of the model’s predictive capabilities on intention to use or the adoption of technology
(Khan et al., 2017; Rondan-Cataluna et al., 2015; Tak & Panwar, 2017; Wu & Lee, 2017). The
complexity of human internal states under the influence of social and external norms is crucial as it
impacts the consumer's decision behaviour for carrying out actions to complete the tasks. The
reviewed articles claim that isomorphic forces influence technology adoption within organisations as
stakeholders seek social legitimacy and conformity to standards and linkage to society. Same
circumstances applied to consumers as the norms established through organisational actions, public
opinion, professional bodies, and government enforcement will create similar standards for consumers
and organisations.
Somehow consumer behaviour will constantly evolve while attempting to meet the demands
created by external factors that seek specific behaviours. The majority of the related adoption articles
focus on the impact of isomorphism but from the organisational lens (Ahmad et al., 2020; Bozan et al.,
2015; Sadoughi et al., 2019). According to Mesquita & Urdan (2019), the influence of market
isomorphism on consumer adoption decisions is a new concept. Isomorphic forces could influence
adoption decisions that possibly led to intention to use, then to actual technology adoption behaviour.
Therefore, studying the underlying effects of market isomorphism forces would provide a
comprehensive understanding of the impacts of social forces, which could spur behaviour change that
affects adoption decisions. This study conducts an empirical analysis for the investigation of consumer
mobile commerce adoption through consumer adoption behaviour, from intention to use to the
subsequent adoption of the mobile commerce channel under the influence of consumer inertia and the
indirect moderating interaction effects of market isomorphic forces between the relationship of
consumer inertia and mobile commerce channel adoption.
The rest of this study is outlined as follows. Section 2 reviews the related literature, Section 3
explains the research methodology, and the results, and interprets the findings using PLS-SEM.
Section 4 discusses the findings, and Section 5 concludes by identifying the theoretical and practical
implications and offers suggestions for future research.
2. LITERATURE REVIEW
2.1. Behavioural intention to use and adoption of mobile commerce channel
In this revolutionised digitisation era, technology and information systems adoption is an actively
discussed topic among scholars and practitioners alike for the purpose of a better understanding of use
and adoption decision behaviour. Earlier studies mostly focused on technological issues and gradually
moved towards technology services management matters and the identification of the factors that
influenced adoption. Various technology adoption theories were adapted. However, most studies were
inclined towards technological and management aspects, thus lacking in the human and social change
areas. At a later stage social dimensions were identified as an important antecedent. With this, the
popular unified theory of acceptance and use of technology model (UTAUT) (Venkatesh et al., 2003)
was formed through the unification of the social cognitive theory (Bandura, 1986) and several
prominent adoption theories such as the technology acceptance model (TAM) (Davis et al., 1989),
theory of planned behaviour (TPB) (Ajzen, 1991, Schifter & Ajzen,1985), theory of reason action
(TRA) (Fishbein & Ajzen, 1975), motivational model (MM) (Davis et al., 1992), and innovation
diffusion theory (DOI) (Moore & Benbasat, 1991). It was argued that the UTAUT model had higher
predictive power as compared to other technology acceptance theories, like the Technology Acceptance
Model (TAM), which lack human and social factors (Venkatesh et al., 2003; Srivastava & Bajaj, 2022).
The UTAUT model was further extended into the UTAUT2 model with the addition of
dimensions such as hedonic motivation, price value and habit (Venkatesh et al., 2012). One of the
objectives of this unification is for the investigation of acceptance and use of technology from the
consumer perspective (Alalwan et al., 2017; Bendary & Al-Sahouly, 2018; Gupta et al., 2018;
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Venkatesh et al., 2012). The UTAUT2 model has been extensively applied to different contexts and
was posited to have high predictive capabilities (Mosquera et al., 2018; Venkatesh et al., 2012).
However, the majority of these studies were integrated with other factors such as from the social and
human dimensions for the strengthening of the model’s predictive capabilities especially relating to
information systems or technology adoption (Alalwan et al., 2017; Gupta et al., 2018; Liu & Yi, 2017;
Mosquera et al., 2018; Phang et al., 2018; Shaw & Sergueeva, 2019; Tak & Panwar, 2017). Empirical
findings revealed some inconsistencies in the derived results (Liu & Yi, 2017; Mosquera et al., 2018),
thus highlighting the possibility of missing factors that could have influenced adoption decisions. This
had the implication that technology adoption theory alone might not be sufficient to investigate
adoption.
There are past consumer studies that identified isomorphic forces (ie mimetic, normative and
coercive) as having an influence on individuals’ behaviour that affected their decision outcomes for the
completion of their tasks (DiMaggio & Powell, 1983; Mesquita & Urdan, 2019). Hence, it is
anticipated that besides the technological and management factors, the behavioural and social factors
like social and external norms under the influence of market isomorphic forces could also impact
consumer technology adoption decisions.
2.1.2 Mobile commerce in the omnichannel environment
Several scholars have claimed that a socially integrated mobilised communication platform is
relatively more efficient and productive than conventional tools of communication in assisting
consumers’ shopping journeys (Waheed et al., 2021; Howard et al., 2014). Shopping within the
omnichannel environment makes it possible to intermingle between consumer touchpoints (eg app,
website, sales counter, etc), provides mobility besides convenience, and gives consumers a seamless
information-rich shopping experience (Rigby, 2011; Shen et al., 2018). These technological advances
differentiated traditional stand-alone purchasing channels from omnichannel ones. Omni-shoppers
may utilise any of the integrated multichannel seamlessly and interchangeably irrespective of the stage
of the purchasing activities (Park & Kim, 2021; Verhoef et al., 2015). This omnichannel uniqueness
enabled the dynamic convergence of e-commerce and mobility features, resulting in enhanced
mobilised communication platform that empowered consumers to take control over their shopping
journey (Verhoef et al., 2015).
Behavioural inertial elements could make consumers maintain and support their familiar
incumbent systems and resist a new or alternative system like a mobile commerce channel although it
could potentially be a superior system (Polites & Karahanna, 2012; Kim & Kankanhalli, 2009). This is
because resistance to innovative adoption could be a natural individual inclination, such as active
resistance, like attitude. Past studies examined more active resistance elements (i.e., the most negative
reaction to a proposed change attempt) than passive resistance (i.e., defensive resistance). Both were
developed unconsciously without considering adoption intrinsic value (Ghazali et al., 2020). Thus, the
mobile commerce channel in the omnichannel environment could have been perceived to be similar or
to have marginal differences or involve hassle to change (Branstad & Solem, 2020; Gong et al., 2020;
Kim et al., 2017; Park et al., 2017). This is because mobile commerce, compared to other purchasing
channels, delivers the same shopping outcomes, and represents an alternative shopping channel.
Investigating mobile commerce channel adoption from the social and consumer behavioural
transformations viewpoint would be fruitful since consumers’ adoption decision behaviour requires
adapting and accepting changes in terms of routines, learning and re-learning, which are impacted by
human inertia, habits, and traditions as consumers are constantly under the influence of social and
external norms.
The failure rate for new technology adoption is usually high due to user resistance since
consumers tend to perceive higher potential losses than potential gains, although the actual losses could
be insignificant as compared to the benefits gained.
2.1.3 Consumers’ internal states that led to behavioural intention to use the mobile
commerce channel
Consumers’ backgrounds (eg work experience, education, professional profile, socio-cultural
background and so on) might subconsciously influence the decision behaviour, in addition to the rules,
policies, and standard practises within the community or society. Consumers may choose to mimic
decisions of the society or community because of the influence of the perceived social pressure from
friends or family (Al-Maghrabi et al., 2011) because through consumers’ perception of the social
pressures, they could be directed to perform the adoption behaviour in question (Ajzen, 1985; Al-
Maghrabi et al., 2011). It has been reported that Malaysians have a high perceived threat nature
towards online transactions (MCMC, 2019) and this may cause Malaysian consumers to feel that it is
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less risky to mimic actions of members within the society (mimetic pressures) or follow the decisions
of professional bodies/associations they are associated with (normative pressures) or regulative rules
and polices (coercive pressures). According to Walden & Browne (2009), who studied individuals
from the observational learning perspective, if others are adopting something, then the individual will
conclude it to be of higher inherent value. This is mimicking action, also known as mimetic
isomorphism (DiMaggio & Powell, 1983). DiMaggio & Powell (1983) argued that factors like the
isomorphic forces influenced consumers (eg behavioural emotion, affective, and cognitive matters),
leading them to change behaviour.
This change behaviour will lead to behavioural intention to use and subsequently to adoption
(Mesquita & Urdan, 2019). According to the theory of planned behaviour (Ajzen, 1991), the
individual’s behaviour will directly affect behavioural intention to use, which will subsequently lead to
technology adoption. With the rise of social media networking, the social related dimensions could
also act as a change agent that influences consumers’ behaviour, spurring consumers’ internal states to
trigger behavioural change with the aim of obtaining compliance and social legitimacy due to social
and external norms (Bell & Cox, 2015). Social responses and consumer-to-consumer interactions
through various social media networking platforms (eg Facebook, Instagram, WeChat, WhatsApp, etc)
were found to have increased substantially (Souiden et al., 2018). These perceived social forces
formed through the presence and usage of social media networking platforms influence the
isomorphism forces (DiMaggio & Powell, 1983; Mesquita & Urdan, 2019) and affect consumers’
expectations evaluation. Subsequently, consumers' adoption decision outcomes could be affected (Kim
& Kankanhalli, 2009).
These consumers’ reactions are often theorised as behavioural intention to use, which will
eventually be transformed into actual behaviour (Fishbein & Ajzen, 1975; Kim & Forsythe, 2008), or
technology use and acceptance (Davis, 1989; Rogers, 2003; Venkatesh et al., 2012). The behavioural
change could either be positive or negative towards adoption (Kleijnen et al., 2009) as consumers'
reactions may be postponed depending on the surrounding social and external norms, as well as the
human, technological, management aspects. Previous studies have identified behavioural intention to
use as the main antecedent of use behaviour, and it directly impacted on consumers’ actual use of a
given technology or system (Chopdar et al., 2018). Past studies in different contexts have also
confirmed the relationship between intention to perform a behaviour and actual behaviour (Aldas-
Manzano et al., 2009; GroB, 2015). Thus, the following hypothesis is proposed:
H1 Behavioural intention to use will positively impact mobile commerce channel adoption.
However, consumer adoption behaviour under the impact of consumer inertia will provide an
understanding of consumers’ affective, cognitive, and behavioural states that could trigger adoption
behaviour change. The behavioural intention to use could positively influence the consumers’
behaviour (Fishbein & Ajzen, 1975) initially although subject to the negativity of consumer inertia
before adoption. Thus, the following hypothesis is proposed:
H2 Behavioural intention to use will positively impact consumer inertia.
2.2. Consumer inertia
2.2.1 Concept of consumer inertia
Past studies pointed out that new technological systems are likely to be subject to user resistance
(Kim, Lee et al., 2017; Lee & Joshi, 2017; Lin et al., 2015; Polites & Karahanna, 2012). This
consumer resistance is said to have relevance to consumer inertia, and both are important adoption
behaviours that are manifested in consumer behaviour (Seth et al., 2020). Consumer resistance can be
described as resistance towards innovations, and it is usually caused by functional and psychological
barriers (Heidenreich & Kraemer, 2015; Ram & Seth, 1989) that lead consumers to maintain the status
quo. Consumer inertia was conceptualised from the status quo bias theory (Samuelson & Zeckhauser,
1988), which referred to consumers adhering to their existing habits or actions to resist change by
maintaining the status quo even though a superior alternative is available (Mesquita & Urdan, 2019;
Samuelson & Zeckhauser, 1988). Consumer inertia is considered highly relevant to consumer
behaviour studies about intention to use and the adoption of technological systems. Inertia can be
manifested when using emerging payment technology that involves switching from the incumbent
payment channel to an e-banking payment channel (Lu et al., 2011; Lu, Yang, et al., 2011).
Therefore, consumer inertia will be a relevant concept for many studies on human phenomena as it
has usually been taken as a metaphor that is associated with resistance to change, and it is applicable in
this study as well. Individuals' attitudes and beliefs about themselves and their surroundings could
cause inertia (Asamoah et al., 2019; Polites & Karahanna, 2012; Samuelson & Zeckhauser, 1988).
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There are multiple factors that could create resistance to change, such as uncertainties, habits, and loss
aversion. These factors could further strengthen the inertia effects on intention to use and the adoption
of technology (Lee & Joshi, 2017). Consumers facing new or alternative technological systems could
either choose to adopt or refuse. Past studies revealed consumer behaviour to be an important agent
that influenced consumer decision behaviour, especially for consumer adoption decisions where inertia
was argued to be an attitudinal propensity to maintain the status quo even if superior alternatives are
available (Lee & Neale, 2012; Lin & Huang, 2014; Polites & Karahanna, 2012; Tsai et al., 2019).
Consumer inertia would influence behavioural intention to use and continue with the status quo
because inertia will naturally act as an adoption inhibitor of technological systems (Polites &
Karahanna, 2012). This is due to uncertainty avoidance, habits, emotional attachment with incumbent
systems or perceived insignificant differences between the incumbent and new or alternative
technological systems, whereby consumers do not want to spend extra time and effort learning the new
technology or systems (Anderson & Swaninthan, 2011; Kim & Kang, 2016; Polites & Karahanna,
2012). According to Polites & Karahanna (2012) and Lee & Neale (2012), as consumer inertia
increases, consumers do not consciously evaluate the costs and benefits any more, but they will
automatically support the incumbent systems. According to Greenfield (2005), it was believed that it is
the individual’s habit that creates this tendency to continue doing what one has been doing, and
together with the individual’s sensitivity to external pressures or norms this formed the concept of
consumer inertia.
2.2.2 Consumer Inertia will influence consumer adoption behaviour
Several studies have examined the effects of consumer inertia on different aspects of consumer
behaviour, e.g. the transition from the web to mobile payment services (Gong et al., 2020), the
homogenisation of phone services (Mesquita & Urdan, 2019), the continuing use of technology (Kim &
Kang, 2016; Park et al., 2017), resistance to adoption (Seth et al., 2020), switching costs, habits, and
inertia on new systems acceptance (Polites & Karahanna, 2012), switching intention (Lin & Huang,
2014), IT loyalty (Lin et al., 2015) and consumer adoption resistance (Seth et al., 2020). Polites &
Karahanna (2012) developed and validated a multi-dimensional scale to measure consumer inertia like
affective-based inertia, cognitive-based inertia, and behavioural-based inertia. A higher order construct
was established formatively, with each dimension representing a unique feature of consumer inertia
(Gong et al., 2020; Lin & Huang, 2014; Lin et al., 2015; Polites & Karahanna, 2012), which this study
also adapts. This study aims to examine the effects of consumer inertia on consumer behaviour
towards adoption decisions.
Cognitive-based inertia refers to the understanding and learning of new systems as the individual
will continue to use incumbent systems although consciously knowing that incumbent systems were
not the best systems to provide the most effective or efficient ways of performing their tasks (Polites &
Karahanna, 2012). Affective-based inertia refers to the rational selection decision, which involves
emotions or feeling responses that are rationalised to maintain the status quo because of familiarity and
it being less stressful to maintain the status quo (Polites & Karahanna, 2012; Zhuang et al., 2018).
Conative behavioural-based inertia refers to the outcomes of the actions undertaken like adoption
behaviour that is linked to the individual’s beliefs, where the individual may choose uncertainty
avoidance by continuing to use the incumbent systems without any due considerations because of
familiarity (Kim & Gupta, 2012; Polites & Karahanna, 2012). Choosing to maintain the status quo
may be due to emotional attachment to the incumbent systems (Lee & Joshi, 2017). The formation of
consumer inertia varies depending on the contexts and it is therefore important to understand how
consumers evaluate the purchasing channel “fit” with their expectations.
Past studies that investigated the discordance between individual willingness and behaviour have
indicated research gaps because of external limitations (Adnan et al., 2017; Zhang et al., 2019). Hence,
it can be predicted that there is a discrepancy between consumers’ willingness or intention to switch to
the mobile commerce channel and the actual switching behaviour or adoption because of constraints
arising from the surrounding social dimensions. Explaining the advantages and strengths of new
systems solely for adoption study is insufficient as it will not effectively lead to adoption decisions
because of the inhibiting effects of consumer inertia. Drawing on previous studies that examined the
effects of consumer inertia (Gong et al., 2020; Kim & Kang, 2016; Mesquita & Urdan, 2019; Park et al.,
2017; Polites & Karahanna, 2012; Seth et al., 2020), the following hypothesis is proposed for the
consumer inertia construct:
H3 Consumer inertia will negatively influence the adoption of mobile commerce channels.
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2.3 Market Isomorphism
2.3.1 Market Isomorphism, the linkage between consumer decision behaviour and mobile
commerce adoption behaviour
The convergence of dynamic technological advancement and the internet has changed consumers'
livelihood, leaving some consumers able to adapt to these changes, whereas some are lagging. It has
been argued that institutional isomorphic forces have impacted organisational adoption behaviour
(DiMaggio & Powell, 1983). Since both individuals and organisations seek social legitimacy and
compliance with standards and rules of survival in the marketplace or linkage to the society, market
isomorphic forces could also have the same effect on consumer adoption behaviour because market
isomorphism is an adaptation from the institutional theory concept, which is led by social norms.
Hwang & Um (2021) specified that individual beliefs will have strong effects on individual compliance
to social norms, which subsequently influence adoption decisions. Although past adoption-related
studies commonly used the institutional theory that concludes isomorphic forces effects adoption
decisions (Eid & Agag, 2020; Mignerat & Rivard, 2015; Soares et al., 2021; Wang et al., 2020), these
studies were mainly focusing on the organisational contexts. Therefore, this study adopts the
institutional theory concept through the consumer lens to investigate the relationship between mobile
commerce channel adoption and consumer inertia under the influence of market isomorphic forces
within the current omnichannel shopping trends.
2.3.2 Market Isomorphism from the consumer context, adapted from the concept of
Institutional Theory
Institutional theory states that the isomorphic forces experienced by organisations pressured them
to adopt rules, as well as social and institutional norms, to increase legitimacy and compliance, leading
to organisations within the same sector becoming more similar to each other (DiMaggio & Powell,
1983). This homogenisation process is known as isomorphism and it is categorised into mimetic
(competitive), coercive (regulatory), and normative (market) isomorphism (Delmas & Toffel, 2004;
DiMaggio & Powell, 1983). Institutional theory has been widely adapted im various contexts, for
example environmental practises (Zeng et al., 2017), organisational information systems (Liang et al.,
2007; Soares et al., 2021) and many more. Previous studies have used isomorphic forces to examine
the diffusion and adoption of technology and innovation (Branstad & Solem, 2020; Gholami et al.,
2013; Zhu & Mazaheri, 2020) from the organisational lens. These organisation stakeholders (ie
members, managers, top management, suppliers, etc) in public areas are consumers and information
producers (Hwang & Um, 2021). Since isomorphism affects organisation stakeholders, similarly this
could be applied to consumers as well.
Organisation actions with the objective of achieving social legitimacy have been evaluated as
being consistent with the welfare and expectations of the community (Suchman, 1995), where the same
circumstances happened to consumers (Bendapudi et al., 1996). As an organisation take actions in
adherence with the rules of acceptable social norms, the same applied to consumers, who faced various
normative influences to decide on the appropriate manner of acting (Handelman & Arnold, 1999) as
consumers and organisations both seek social legitimacy and compliance in the same social
environments. In the marketplace, retailers and consumers co-exist within the same social
environmental conditions that shaped the organisational environment, while at the same time shaping
the consumer environment as well, thus subsequently influencing the adoption decision behaviour. The
concept of institutional theory considered the society as a field of social forces where individuals’
actions are led by social norms, and this will directly affect the chance of consumers adopting new or
alternative systems. It has been argued that the adoption of new or alternative systems will not only be
shaped by retailers themselves, but also actively by the consumers (Branstad & Solem, 2020).
This study examines market isomorphism forces on consumer adoption. Most isomorphism
research is organisational (DiMaggio & Powell, 1983). However, organisations and consumers
similarly seek to link themselves within society through the same norms established by public opinion,
organisation actions, and government enforcement (Scott, 2005), justifying market isomorphism in the
consumer context.
2.3.3 Influences of market isomorphic forces on mobile commerce adoption
Bandwagon behaviour studies specify individuals positively herds to enjoy the adopted
technological innovation, and isomorphic forces drove this herd behaviour that impacted the adoption
behaviour (Fiol & O’Conner, 2003). According to Sun (2009), herding behaviour is a part of social
learning. Kraatz & Zajac (2001) suggested that herd behaviour led to following the adoption decisions
of others because facing high uncertainties will make individuals believe other people know better or
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have complete information to make the right decision. So, social norms will affect individual choice,
thus creating a background that leads people to either mimic, comply with or compel and could prohibit
some actions from being made. Examining isomorphism forces are applicable in socially responsible
related research (Hwang & Um, 2021; Sadoughi et al., 2019), where the same concept applies to
consumer mobile commerce adoption. The three isomorphic forces are mimetic, coercive, and
normative pressures (Chen et al., 2011; DiMaggio & Powell, 1983; Mesquita & Urdan, 2019).
Isomorphic forces (i.e., mimetic, normative, and coercive pressures) triggered changes initiated by
service providers and consumers, for example, in co-creation practices through self-service technology
interfaces (Branstad & Solem, 2020; Liang et al., 2007). Mimetic pressures will direct consumers to
follow established standard practises under high uncertainty. These isomorphic forces would influence
someone else to imitate successful practises (Eid & Agag, 2020; Wang et al., 2020). Coercive
pressures will direct consumers away from certain practices to conform to regulations like those
exerted by government or professional bodies. Normative pressures are instilled through socialisation
and learning because consumers will take actions adapted from their profession, experiences, or beliefs
(Eid & Agag, 2020; Wang et al., 2020). Consumers' perceived social pressure would lead them to
imitate the successful actions of influential people or anyone who is important to them (Fishbein &
Ajzen, 1975).
The theory of reasoned action (Fishbein & Ajzen, 1975) specified both normative pressures and
social norms would affect behavioural intention to use. Social norms determine consumers’ perceived
social pressures on others, which leads consumers to take calculative actions (Elliot & Fu, 2008).
Normative pressures would impact these actions by guiding the individual to determine whether the
behaviour in question to agree with people important to them should be performed or not (Elliot & Fu,
2008; Krell et al., 2016). According to Mesquita & Urdan (2019), market isomorphism refers to the
homogeneity of service providers. Consumers will assume service providers will offer similar services.
In this study, there is a high likelihood that consumers are unable to distinguish differences among the
available purchasing channels in terms of benefits or values. This is due to the growing similarity
among competing retailers in all areas, such as products, pricing, offerings, or even the type of
purchasing channels offered (where online and offline key similar functionalities). Everything one
retailer did or offered, other retailers are frequently doing the same, as every firm is striving for
competitive advantage by delivering higher levels of valued benefits through digitisation.
Superficially, these circumstances will lead to higher degree of consumers maintaining the status
quo with their familiar purchasing channel. It is unlikely that adoption is solely affected by consumer
inertia. Market isomorphism would surface from social and external norms influence that could affect
human inertia factors resulting in behavioural change that could subsequently lead to the adoption of
the mobile commerce channel. The human inertia effects would naturally drive consumers to maintain
the status quo with incumbent systems (Polites & Karahanna, 2012), but the impactful market
isomorphic forces could create behavioural change that subsequently leads to adoption (Bilgicer et al.,
2015; Mesquita & Urdan, 2019). Hence, it is foreseeable that market isomorphism forces could highly
affect consumers' adoption of the mobile commerce channel by weakening the negativity of consumer
inertial factors. Mesquita & Urdan (2019) stated that studies relating to market isomorphism effects on
technology adoption are limited. Further investigation is encouraged to validate its discriminant
validity and definitions in the consumer context. Previous studies have adapted institutional
isomorphism to examine the diffusion and adoption of innovation and technology (Branstad & Solem,
2020; Gholami et al., 2013; Zhu & Mazaheri, 2020), but most are from the organisational lens.
Especially the normative pressures from social norms or subjective norms that numerous studies
indicated have effects on behavioural intention to use (Elliot & Fu, 2008) besides its relationship to
adoption behaviour (Hung et al., 2003).
Furthermore, empirical evidence from studies exploring market isomorphism from social
dimension viewpoints found social dimension positive effects on consumer inertia. However, it
negatively affects new systems adoption even though scholars specified social dimension having a
positive impact on the adoption of new sales channels (Bilgicer et al., 2015; Islam et al., 2020).
Empirical evidence found inconsistent results on different occasions, where sometimes none of the
three isomorphic forces were significant even when tested separately from the dependent variable.
Therefore, this justifies the complexity claims of market isomorphic forces due to the three different
underlying dimensions (Berrone et al., 2013). These inconsistent empirical findings encourage further
investigation. This study will focus on market isomorphic forces individually (i.e., normative, coercive,
mimetic pressures) by treating each as moderators that impact the relationship between consumer
inertia and mobile commerce channel adoption. Based on this rationale, the following hypotheses are
proposed:
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H4 Coercive pressures will reduce the negative effect of consumer inertia on mobile commerce
channel adoption.
H5 Mimetic pressures will reduce the negative effect of consumer inertia on mobile commerce
channel adoption.
H6 Normative pressures will reduce the negative effect of consumer inertia on mobile commerce
channel adoption.
3. RESEARCH METHODOLOGY
3.1 Data sample design and collection
There was a total of 29 measures in the questionnaire, represented by consumer inertia (three
dimensions), behavioural intention to use (one dimension), mobile commerce channel adoption (one
dimension), and market isomorphism forces (three dimensions). All 29 items are an adaptation from
past studies. 10 items of consumer inertia three dimensions (i.e., cognitive-based, affective-based, and
behavioural-based inertia) are from Polites & Karahann (2012). 11 items of three market isomorphic
forces dimensions (i.e., mimetic, normative, and coercive pressures) are from DiMaggio & Powell
(1983). 4 items of behavioural intention to use mobile commerce are from Venkatesh et al. (2012). 4
items of mobile commerce channel adoption are from Venkatesh et al. (2012). All constructs are
measured using existing established seven-point Likert scale, ranging from “1=strongly disagree” to
“7=strongly agree”. A pilot test of the questionnaire was conducted based on 32 valid respondents,
after which some items were reworded and removed. The pilot data tested were not included in the
final data.
A total of 403 completed questionnaires were collected from both online and offline modes with
respondents over 20 years old, who own at least one smartphone, and who reside in Sarawak, Malaysia.
This study uses a quantitative method to collect primary data using an online survey and print-out
questionnaires distributed via social media, email, face-to-face, and mobile apps. The non-response
bias was not an issue for this study as the data collected were through face-to-face interaction with the
target respondents when necessary. Supporting secondary data were derived from the Department of
Statistics Malaysia (DOS), the Malaysian Communication and Multimedia Commission (MCMC), and
publicly published reports from reputable consultancy firms, agencies, and newspapers. Table 1
provides an overview of respondents' demographic characteristics and preferred shopping methods.
The results show that 44.4% of respondents were male and 55.6% were female. 27.3% of respondents
were between 20-24 years, 21.6% between 25-28 years, 20.6% between 29-39 years, 17.1% between
40-55 years, and 13.4% between 55 years and above. Most respondents (62%) had either a degree, a
master's, or a PhD.
The household income of respondents was below RM 5,000 (50.1%). As for respondents'
shopping preferences, 71% of respondents usually used mixed online and offline shopping. Most
respondents preferred to visit physical retail stores and use banknotes or debit/credit card payment
methods even though sometimes they do online shopping (64.3%). 23.6% of the respondents prefer
shopping at physical retail stores and paying through e-wallet apps even though sometimes they do
online shopping. 9.2% of the respondents prefer online shopping using mobile apps. 3% of the
respondents prefer online shopping through a personal computer to access e-commerce websites.
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Table 1: Profile of respondents
Characteristics
Frequency
(%)
Age (Year)
20 – 24
110
27.3%
25 – 28
87
21.6%
29 – 39
83
20.6%
40 – 55
69
17.1%
55 and above
54
13.4%
Gender
Male
179
44.4%
Female
224
55.6%
Level of education
Primary and Secondary education
85
21.1%
Diploma
68
16.9%
Degree
174
43.2%
Master's
74
18.4%
PhD
2
0.5%
Race
Malay
102
25.3%
Chinese
97
24.1%
Indian
6
1.5%
Iban
69
17.1%
Bidayuh
34
8.4%
Other Malaysian ethnic groups
95
23.6%
Household income
< RM2,500
54
13.4%
RM2,500 - RM4,999
148
36.7%
RM5,000 - RM6,999
127
31.5%
RM7,000 - RM10,999
40
9.9%
RM11,000 & above
34
8.4%
CONSUMER SHOPPING:
Usual shopping method:
Shopping online only
83
20.6%
Shopping offline only
34
8.4%
Mixed online and offline shopping
286
71.0%
Preferred shopping method:
Shopping online using mobile apps
37
9.2%
Shopping online using personal computer
12
3.0%
Sometimes online but prefer going to physical retail
stores using bank notes or debit/credit cards to pay
259
64.3%
Sometimes online but prefer going to physical retail
stores using e-wallet apps to pay
95
23.6%
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3.2 Research Design
Figure 1 represents the proposed conceptual framework.
3.3 Data Analysis
Partial least squares structural equation modelling (PLS-SEM), a popular and powerful method for
measurement and structural model assessment, was applied using SmartPLS 3.3.2 software (Ringle et
al., 2015) to analyse the conceptual framework, the moderators’ interaction effects, and for hypothesis
testing. Both reflective and reflective-formative second-order constructs are included in this
framework, making PLS-SEM a suitable statistical method for this study to analyse the framework
(Hair et al., 2017). A sample size of 403 is adequate for PLS-SEM. Using G*Power software it is
calculated that a minimum of 74 samples is sufficient to get a power of 0.95 for analysis (Faul et al.,
2009). Therefore, the sample size of this study is adequate to perform the analysis.
3.4 Results and Findings
3.4.1 Assessment of measurement model
This study framework involves one second-order reflective-formative construct, i.e., consumer
inertia. The framework also includes five reflective constructs, i.e., behavioural intention to use,
mobile commerce channel adoption, and market isomorphism (i.e., coercive pressures, mimetic
pressures, and normative pressures). The market isomorphism forces are moderators. A two-stage
approach is adopted to establish the second-order constructs as it is necessary to assess the
measurement model of the preliminary framework, which includes three reflective constructs (Ali et
al., 2018; Becker et al., 2012; Rasoolimanesh et al., 2020). Measurement assessment consists of eight
reflective first-order constructs, that is (1) intention to use, (2) affective-based inertia, (3) behavioural-
based inertia, (4) cognitive-based inertia, (5) coercive pressures, (6) mimetic pressures, (7) normative
pressures, and (8) mobile commerce channel adoption with reliability and validity assessment (Hair et
al., 2017). In establishing reliability, the outer loading of items for each reflective construct should be
higher than 0.7, and the composite reliability (CR), Cronbach’s alpha, and rho-A of the constructs
should be greater than 0.7 (Ali et al., 2018; Hair et al., 2017).
Figure 1: Conceptual Framework (Effects of market isomorphism on consumer inertia on
consumer mobile commerce adoption)
H1
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The average variance extracted (AVE) should be higher than 0.5 to establish convergent validity
(Ali et al., 2018; Hair et al., 2017). Table 2 shows that the outer loadings for all items associated with
the constructs are higher than 0.7. The value of CR, Cronbach’s alpha, and rho-A are higher than 0.7.
The AVE is higher than 0.5 for all constructs in the first stage and confirms all constructs meet the
acceptable reliability and convergent validity criteria (Hair et al., 2019).
Table 2: Results of assessment of measurement model for first-order constructs
Construct items
Cronbach's
alpha
CR
Intention to use
0.921
0.944
37BI2
37BI3
37BI4
37BI5
Affective_based inertia
0.904
0.843
41CIA1
41CIA2
41CIA3
Behavioural_based inertia
0.739
0.852
42CIB1
42CIB2
42CIB3
Cognitive_based inertia
0.808
0.886
43CIC1
43CIC2
43CIC3
Coercive pressures
0.767
0.865
51MIC1
51MIC2
51MIC3
Mimetic pressures
0.833
0.889
52MIM1
52MIM2
52MIM3
52MIM4
Normative pressures
0.801
0.883
53MIN1
53MIN2
53MIN3
Mobile commerce channel adoption
0.861
0.905
38MC1
38MC2
38MC4
38MC5
Discriminant validity assessment is established for confirming the distinction between constructs
in the framework with various criteria (Hair et al., 2019). Extant literature has specified two
conservative approaches to assess discriminant validity, i.e., heterotrait-monotrait (HTMT) ratio and
Fornell-Larcker criterion (Henseler et al., 2015; Voorhees et al., 2016), whereby both approaches
applied in this study. The value of HTMT for all constructs should be less than 0.9 to establish
discriminant validity based on the HTMT approach (Henseler et al., 2015). Therefore, in establishing
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discriminant validity based on the Fronell-Larcker criterion, the square root of the AVE of each
construct should be higher than its correlation with other constructs in the model (Hair et al., 2017).
Discriminant validity for market isomorphic forces is derived in this study as well. The results of this
study demonstrated acceptable discriminant validity based on both approaches, as shown in Table 3
and Table 4. Consumer inertia is a second-order formative construct with value derived from the score
of the associated first-order constructs (i.e., affective-based inertia, cognitive-based inertia, and
behavioural-based inertia) (Becker et al., 2012; Md Noor et al., 2019; Rasoolimanesh et al., 2020).
In the second stage, consumer inertia is an add-on to the framework with five other first-order
reflective constructs (i.e., behavioural intention to use, coercive pressures, mimetic pressures,
normative pressures, and mobile commerce channel adoption). The assessment of formative constructs
includes multi-collinearity checking using the variance inflation factor (VIF) and the need to achieve
outer weights significance (Hair et al., 2017). In an acceptable measurement model for formative
constructs, the constructs should have a VIF value of lower than five and attain outer weight
significance (Ali et al., 2018). The results of the assessment of the measurement model in the second
stage show that the VIF value of the items for consumer inertia was between 1.38 and 2.281, thus
indicating acceptable collinearity for the formative construct. The outer weights of the items for the
formative construct are significant. Hence, these results indicate good construct reliability, indicator
reliability, convergence validity, and discriminant validity, ensuring that the constructs are statistically
distinct. These results demonstrate an acceptable measurement model for the first and second stages
and thus can proceed to test the structural model.
3.4.2 Assessment of the structural model
Table 5 and Figure 2 show the acceptable results of the structural model assessment and
hypothesis testing (Hair et al., 2018). The value of R2 for mobile commerce channel adoption is 0.430.
According to Hair et al. (2017), an R2 value of 0.20 is acceptable for consumer behavioural research.
The value of inner VIFs for all constructs involved in the structural model was from 1.00 to 3.99,
indicating the accepted level of multi-collinearity for the constructs in the final model. The results
supported all the direct and indirect effects and hypotheses. Also found behavioural intention to use
direct effects on consumer inertia (H2), behavioural intention to use on mobile commerce channel
adoption (H1), and consumer inertia on mobile commerce channel adoption (H3), with the highest
effects belonging to H1. Empirical findings support the influence of emotional behaviours like inertia
on emotions, mental states, habits, and behavioural responses (Polites & Karahanna, 2012). According
to Sun et al. (2017), individuals' habits positively influence the inertia that strengthens inhibiting effects
of inertia and negatively affects individual switching behaviour to adopt the new mobile instant
messaging apps.
This study derived positive effects of consumer behavioural intention to use over consumer
inertia. H1 stated that behavioural intention to use positively led to actual use behaviour or adoption.
This result is similar to past studies (Aldas-Manzano et. al., 2009; Chopdar et al., 2018; Tak et. al.,
2017). The negative impact of consumer inertia on adoption (H3) is confirmed, and this study has the
same result as Park et al. (2017)’s study, which indicated inertia’s negative impact on continuous use,
thus confirming the adoption inhibiting effects of consumer inertia. H4 to H6 refers to the indirect
interacting effects of market isomorphic forces as moderators (i.e., coercive, normative, and mimetic
pressures) on mobile commerce channel adoption. A two-stage approach is applied to assess these
moderators (Fassott et al., 2016). The results (Table 6) show that this study was only able to support
the moderating role of coercive pressures (H4) and normative pressures (H6). However, the
moderating role of mimetic pressures (H5) is not supported as this is not statistically significant.
These results revealed that coercive pressures moderated the relationship between consumer
inertia and adoption (Std Beta = -0.158, t = 1.723), p < 0.05) (see Figure 3), but consumer inertia
negative impact on adoption weakened at higher coercive pressures. They also revealed that normative
pressures moderated the relationship between consumer inertia and adoption (Std Beta = -.296, t =
3.363), p < 0.01) (see Figure 4), but consumer inertia negative impact on adoption weakened at higher
normative pressures. According to Mesquita & Urdan (2019), market isomorphism negatively impacts
customer inertia. This study found market isomorphism has a negative effect on adoption. However,
only two market isomorphic forces (i.e., coercive and normative pressures) have a significant impact
but not mimetic pressures. The reason for mimetic pressures having a different result could be related
to the high perceived threat nature of consumers in this region. Consumers in this region might refrain
from dealing with online financial-related transactions unless reinforced by policies, statutory bodies,
or influenced by the professional-related background of consumers themselves.
Moderators’ interactive effects are obtained from comparison of the two R2 values i.e., before and
after including these moderators using the two-stage approach (Henseler & Chin, 2010). The result of
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79
0.07 (Table 7) reveals the effect of the underlying moderating interactions of the market isomorphic
forces on the relationship between consumer inertia and mobile commerce channel adoption to be
strong and significant (Cohen, 1988; Kenny, 2016). The product of the coefficient approach using the
bootstrapping resampling method is applied to assess the mediator in this study (Hayes & Scharkow,
2013; Nitzl et al., 2016; Rasoolimanesh et al., 2020). This study demonstrated a significant mediating
role of consumer inertia on the relationship between behavioural intention to use and mobile commerce
channel adoption (Table 8). Derived results revealed a negative path coefficient (Std Beta -0.284) for
the relationship between consumer inertia and adoption. This indicates the inhibiting effects of
consumer inertia on adoption by comparing this to the direct effect path that derived a positive path
coefficient (Std. Bega 0.520) for the relationship between behavioural intention to use and adoption
(Figure 2).
Tiu Chai Hui and Dayang Affizzah binti Awang Marikan
Table 3: Results of Discriminant validity (HTMT)
Affective-
based Inertia
Behavioural-
based Inertia
Cognitive-
based Inertia
Intention to
use
Coercive
pressures
Mimetic
pressures
Normative
pressuers
Mobile
Commerce
Channel
Adoption
Affective-based Inertia
Behavioural-based Inertia
0.619
Cognitive-based Inertia
0.888
0.631
Intention to use
0.453
0.348
0.448
MI-Coercive
0.449
0.269
0.438
0.564
MI-Mimetic
0.442
0.334
0.380
0.581
0.766
MI-Normative
0.416
0.291
0.401
0.551
0.744
0.876
Mobile Commerce Channel Adoption
0.072
0.084
0.100
0.569
0.330
0.372
0.430
Table 4: Results of Discriminant validity (Fornell-Larcker criterion)
Affective-
based Inertia
Behavioural-
based Inertia
Cognitive-
based Inertia
Intention to
use
MI-
Coercive
MI-Mimetic
MI-
Normative
Mobile
Commerce
Channel
Adoption
Affective-based Inertia
0.871
Behavioural-based Inertia
0.490
0.811
Cognitive-based Inertia
0.735
0.488
0.850
Intention to use
0.400
0.289
0.390
0.900
MI-Coercive
0.358
0.200
0.339
0.474
0.826
MI-Mimetic
0.369
0.261
0.313
0.511
0.618
0.816
MI-Normative
0.341
0.224
0.323
0.471
0.582
0.717
0.846
Mobile Commerce Channel Adoption
-0.001
-0.060
-0.054
0.499
0.269
0.317
0.358
0.840
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Table 5: Results of hypothesis testing
Hypothesis
Relationships
Std
Beta
p-value
Confident
interval (95%)
bias corrected
Supported
H1
Behavioural Intention to use
→ Mobile Commerce
Channel Adoption
0.52
<0.01
[0.427, 0.609]
Yes
H2
Behavioural Intention to use
→ Consumer Inertia
0.431
<0.01
[0.342, 0.499]
Yes
H3
Consumer Inertia → Mobile
Commerce Channel
Adoption
-0.161
<0.05
[-0.259, -0.075]
Yes
Table 6: Results of moderators’ interaction effects
Hypothesis
Moderating
interaction effect
Std.
Beta
Std
Error
t-
value
Confident
interval
(95%) bias
corrected
Supported
H4
Coercive*CI →
Mobile Commerce
Channel Adoption
-0.158
0.094
1.679*
[-0.309, -
0.005]
Yes
H5
Mimetic*CI →
Mobile Commerce
Channel Adoption
0.136
0.090
1.505
[-0.001,
0.289]
No
H6
Normative*CI →
Mobile Commerce
Channel Adoption
-0.296
0.086
3.451*
[-0.448, -
0.159]
Yes
Note: **p<0.01, *P<0.05 (one-tailed test)
Table 7: Comparison of R
2
included and excluded moderator
Included
Excluded
f
2
Effect size
Citation
R
2
0.441
0.371
0.07
large effect size
Kenny, 2016
Table 8: Results of mediating interaction effects
Mediating effect
Std.
Beta
Std
Error
t-value
p-value
Confidence
interval (95%)
bias corrected
Supported
Behavioural intention to use
→ Consumer Inertia →
Mobile Commerce Channel
Adoption
-0.069
0.024
2.939*
0.002
[-0.112, -0.035]
Yes
Note: **p<0.01, *P<0.05
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Figure 2: Results of assessment of structural model
Figure 3: Moderator Simple Slope Analysis (H4)
Figure 4: Moderator Simple Slope Analysis (H6)
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4. DISCUSSION
Previous studies have identified practical gaps between consumer expectations and omnichannel
systems capabilities (Shi et al., 2019). This indicates a need to be addressed by retailers before any
systems implementation as its crucial for retailers to understand consumer technological systems
adoption behaviour. Exploring behavioural intention to use and adoption of the mobile commerce
channel from the market isomorphism lens would provide a deeper insight into consumer adoption
behaviour. For this purpose, this study investigated and found a positive significant direct effect of
behavioural intention to use on mobile commerce adoption and has similar results to past adoption
studies (Alalwan et al., 2017; Bendary & Al-Sahouly, 2018; Venkatesh et al., 2012). This indicates
that if consumers have behavioural intention to use, there will be a high likelihood of leading to actual
adoption. Consumer inertia inhibiting effects were confirmed. Past studies also found consumer
inertia inhibiting effects on adoption (Chopdar et al., 2018; Polites & Karahanna, 2012; Tak et al.,
2017), thus leading to the conclusion that the natural inhibiting effects of consumer inertia negatively
affect consumers’ behavioural outcomes, irrespective of the nature of the adoption.
Referring to the mediation assessment, the bulk of the effects of affective-based inertia, cognitive-
based inertia, and behavioural-based inertia have transferred through the higher order consumer inertia
onto mobile commerce channel adoption is confirmed. These results indicated that consumer inertia
increases consumer resistance toward adoption and would lead to a high likelihood of consumers
deciding to maintain the status quo with their incumbent purchasing channel. However, in the
marketplace reality, not only consumer inertia other factors like the market isomorphic forces would
affect consumer adoption decisions. The revelation of market isomorphism effects could weaken the
negativity of consumer inertia on adoption, indicating that inertial elements can also affect surrounding
social factors even though only coercive pressures and normative pressures have a positive significant
interaction effect. The insignificance of mimetic pressures is due to the high perceived threat attitudes
of Malaysian consumers towards online transactions, which deters consumers from mimicking the
adoption decisions (mimetic pressures) of the public. Derived results indicated that adoption reinforced
policies or statutory bodies' regulations (i.e., coercive pressures) besides consumer professional
backgrounds like profession, experience, etc (normative pressures).
Consumers would only consider using mobile commerce channel when necessary or because of
guided behavioural patterns that lead them to be incompliant. There are past studies relating to
isomorphic forces deriving different results. For example, Ramayah et al. (2013), investigating
coercive and mimetic pressures, found that only coercive pressures positively affect adoption of green
information systems. Islam et al. (2020) found that only normative pressures have a significant effect
on the adoption propensity of green ICT in Malaysia and some more studies revealed that coercive and
mimetic pressures have insignificant influences on the adoption propensity of green ICT (Amores-
Salvado et al., 2014; Gholami et al., 2013). Past studies claimed that normative pressures consist of
soft constraints (ie moral standards and social norms), which help people to adhere to the respective
regulations and standards (Krell et al., 2016; Zhu, 2016). Mesquita & Urdan (2019) has found a
negative effect of market isomorphism on customer inertia. Market isomorphism is unidimensional in
Mesquita & Urdan's (2019) study. The disadvantage of a unidimensional construct is the failure to
provide comprehensive information. Market isomorphism is multidimensional, conceptualised through
three types of pressures i.e., coercive, normative, and mimetic.
Normative pressures' significant positive effects were from consumer backgrounds (ie profession,
education, etc) or professional practises (ie experience, professional standards, professional networks)
that developed into norms. The coercive pressures' significant positive effects referred to government
and statutory bodies' standards settings and society's cultural expectations.
5. CONCLUSION
5.1 Theoretical implications
There are several theoretical contributions to this study. Firstly, although behavioural intention to
use and technology adoption is an active study area, mobile commerce channel adoption through the
market isomorphism lens has not been well investigated. Studying market isomorphism from a
consumer context has been identified as a new concept by Mesquita & Urdan (2019). User resistance
usually challenges technology acceptance, where human inertia is the most common. Consumer
inertia that acted as a natural inhibitor would trigger users to maintain the status quo. This study will
evaluate the relationship between consumer inertia and mobile commerce channel adoption under the
indirect interacting effects of market isomorphism. Derived results would significantly contribute to
the literature by detailing the intercorrelation between the sub-dimensions of consumer inertia and also
the indirect interactive effect of each key component of market isomorphism forces effects on the
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84
relationship between consumer inertia and mobile commerce channel adoption. Secondly, previous
studies have treated consumer inertia as both multidimensional and unidimensional.
This study examines the effects of behavioural intention to use on consumer inertia sub-
dimensions through the interrelationships between cognitive-based inertia, behavioural-based inertia,
and affective-based inertia. Evaluating the mediating role of consumer inertia on the relationship
between behavioural intention to use and consumer inertia and mobile commerce channel adoption
concluded the positive effect of behavioural intention to use on consumer inertia as well as consumer
inertia plays a mediating role in these relationships. Thirdly, although institutional theory is commonly
in information systems adoption research, most of these studies were conducted through the
organisational lens. Within the organisations, all technological systems adoption is mandatory and is
governed by corporate policies and rules, whereas within the consumer context, technology systems
adoption is voluntary. This study specifically focuses on the consumer context and derived results
confirmed that market isomorphism abilities in weakening the relationship between consumer inertia
and mobile commerce channel adoption. This study statistically tests market isomorphic forces (i.e.,
coercive, normative, and mimetic) individually and found discriminant validity for all the market
isomorphism forces.
5.2 Practical implications
This study also contributes a few practical implications for managerial recommendations. Firstly,
the results indicate consumer inertia (i.e., behavioural-based inertia, cognitive-based inertia, and
affective-based inertia) would significantly affect mobile commerce channel adoption, confirming
consumer inertia inhibiting characteristics. It is crucial for retailers and service providers to understand
consumer behaviour needs and to address the cognitive, affective, and behavioural elements before any
technological systems are implementation. Statistical findings indicated consumers' preference for
continued dealing with physical banknotes and debit/credit cards (MCMC, 2019). This is the
foreseeable reality unless retailers take the lead role and build initiatives to encourage consumers to
adopt the mobile commerce channel through their marketing initiatives. Secondly, retailers need to
consider the social dimensions, eg social norms, faced by consumers and address them through their
marketing plans as an encouragement to adoption. This is because adoption realisation is achievable by
addressing consumer expectations and taking measures to tackle the social dimension simultaneously
can lead to improvement of consumer confidence in adopting mobile commerce channel.
With a high perceived threat attitude among consumers, it is anticipated that consumers of this
region would not follow the actions of others unless adoption is directly reinforced through rules and
policies by regulative or statutory bodies or from their background through their experience or
profession. Bad past experiences with online transactions or shopping, online fraud cases, and
financial losses experienced from online transactions would deter consumers from adopting the mobile
commerce channel unless retailers and service providers could earn consumers' confidence through
privacy and security protection. Consumers may still search for information about products and
services and make comparisons among products and services online even though they are deterred from
performing online transactions. Therefore, retailers are challenged to take the lead role in educating
consumers on the security protection and privacy aspects of their mobile commerce apps and not only
putting efforts to highlight convenience and benefits. Benefits like online offers and incentives alone
are not convincing enough to get consumers into adopting the mobile commerce channel.
In the long term, with these highlighted efforts enforced, the mobile commerce channel will also
benefit retailers and service providers as well as consumers because mobile shopping could potentially
stimulate spontaneous consumer buying behaviour, followed by better sales margins for goods and
services, which could potentially increase their business performance. Thirdly, these empirical
findings highlight the importance of inertia elements and reaping the benefits of the market isomorphic
forces, as this determines consumers' readiness level for mobile commerce adoption. Retailers are
encouraged to consider this empirical evidence in their business strategies and marketing initiatives
such as incentives, rewards systems, or customer loyalty programmes through mobile commerce apps.
The ability to lock in existing customers and draw new customers to their businesses is the key aim of
retailers in justifying mobile commerce implementation in their business.
5.3. Limitation and future research
The focus of this study is on Sarawak consumers in Malaysia. Sarawak is the largest state in terms
of geographical coverage area. In the e-commerce usage survey and broadband penetration survey
conducted by the Malaysian Communications and Multimedia Commission (MCMC, 2019, 2021),
Sarawak ranked 3rd lowest in Malaysia, with an e-commerce usage rate of 24% and broadband
penetration rate of 103.1% as compared to the top-ranked (Kuala Lumpur) having 70.5% and 227.5%
Tiu Chai Hui and Dayang Affizzah binti Awang Marikan
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respectively. However, caution needs to be exercised before generalising the derived results to the
whole of Malaysia’s consumers because the environmental differences of Sarawak as compared to
Kuala Lumpur, Selangor, and other states need to be taken into consideration. Future research adopting
the same framework should compare the results by focusing on the states with different broadband
penetration rates to obtain a more comprehensive understanding of the effects of consumer inertia and
market isomorphic forces on mobile commerce channel adoption by Malaysian consumers.
In addition, future studies might look to focus on exploring market isomorphism influences on
other variables, like perceived threats and perceived controllability between consumer inertia sub-
dimensions and consumer mobile commerce channel adoption.
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