Article

How Does Anxiety Affect the Relationship between the

Customer and the Omnichannel Systems?
Bui Thanh Khoa 1,2, * and Tran Trong Huynh 3

1 Finance, Economics, and Management Research Group, Ho Chi Minh City Open University,
Ho Chi Minh 70000, Vietnam
2 Faculty of Commerce and Tourism, Industrial University of Ho Chi Minh City, Ho Chi Minh 70000, Vietnam
3 Department of Mathematics, FPT University, Ha Noi 100000, Vietnam
* Correspondence: khoa.bt@ou.edu.vn or buithanhkhoa@iuh.edu.vn; Tel.: +84-908091402

Abstract: Omnichannel is not just a marketing, e-commerce, or customer support buzzword. This
future customer engagement platform helps businesses communicate with customers through cen-
tralized channels on a smart interface. It is difficult to achieve customer loyalty when the risk in
online transactions, which creates anxiety, exists in all transaction processes in an omnichannel
system. Hence, the purpose of this research was to analyze the influence of anxiety on relationships
when clients purchase from an omnichannel platform using the stimulus–organism–response (SOR)
paradigm. To fulfill study aims, qualitative and quantitative research approaches were used. In-depth
interviews and focus group discussions were used to acquire qualitative data, while survey responses
from 485 participants were used to collect quantitative data. This study’s results revealed relation-
ships between consumer psychology factors such as perceived mental benefits, hedonic value, and
anxiety. Moreover, customer anxiety in omnichannel can be measured as a novel and exact concept
in marketing science and have a moderating role in the effect of perceived mental benefits on elec-
tronic loyalty and perceived mental benefits on hedonic value in omnichannel systems. As a result,
enterprises were also offered various managerial implications to develop their omnichannel system.

Citation: Khoa, B.T.; Huynh, T.T. Keywords: perceived mental benefits; hedonic value; electronic loyalty; anxiety; omnichannel system
How Does Anxiety Affect the
Relationship between the Customer
and the Omnichannel Systems? J.
Theor. Appl. Electron. Commer. Res. 1. Introduction
2023, 18, 130–149. https://doi.org/
The fast change in consumer lives and their interactions with brands and retailers
10.3390/jtaer18010007
through these digital technologies have increased the complexity of the market environment
Academic Editors: that businesses must navigate in recent years. Keeping brand values, attributes, and overall
Santiago Iglesias-Pradas and image consistent across services, experiences, and channels [1], and developing seamless
Emiliano Acquila-Natale customer experiences are two of the many challenges that have prompted many businesses
to begin developing omnichannel strategies. This process requires the integration and
Received: 16 October 2022
Revised: 2 January 2023
adaptation of resources [2]. The notion of omnichannel retailing reflects the development
Accepted: 5 January 2023
of retail tactics, which have shifted from a singular focus on one channel to a more holistic
Published: 9 January 2023 use of several channels and places of customer interaction. The evolution of the concept
of “Omnichannel” from its precursors “Multichannel” and “Cross-channel” is reflected
in the name itself. Galipoglu et al. [3] say that these phrases are interchangeable in the
literature. Omnichannel retailing, as defined by Levy et al. [4], “offers a unified shopping
Copyright: © 2023 by the authors. experience across all of a retailer’s sales channels.” Some writers have proposed theoretical
Licensee MDPI, Basel, Switzerland. distinctions to help make clearer the differences between these methods. Omnichannel is
This article is an open access article viewed as an extension of multichannel retailing [5], although with the latter, “clients travel
distributed under the terms and freely across channels, all inside a single transaction process”. In the following section,
conditions of the Creative Commons Beck and Rygl [6] suggested a conceptualization that adopts two variables—the degree
Attribution (CC BY) license (https:// of channel integration and the degree of channel interaction—to include the viewpoints
creativecommons.org/licenses/by/
of both retailers and customers. The term “omnichannel” refers to a scenario in which
4.0/).

J. Theor. Appl. Electron. Commer. Res. 2023, 18, 130–149. https://doi.org/10.3390/jtaer18010007 https://www.mdpi.com/journal/jtaer
J. Theor. Appl. Electron. Commer. Res. 2023, 18 131

consumers initiate multichannel interactions with a business or brand via any supported
channels, and merchants exercise some authority over the channels’ integration.
Risk, a crucial basis of consumer concern in conventional commerce and e-commerce,
is always present in transactions between sellers and buyers, particularly in online mar-
ketplaces. Customers who feel vulnerable or unsure are more likely to transfer between
online and offline channels, as suggested by theories of uncertainty reduction [7]. Some
of the factors that contribute to shoppers’ unease while browsing in a physical store or
online store are the following: too much information, which leads to confusion and anxiety;
limited opportunities to engage with the products or other shoppers; and the potential for
a breach of their personal information’s privacy [8,9]. Customers in the age of omnichannel
retailing tend to be more tech-savvy and well-informed, making it even more crucial to
study how they experience uncertainty in this setting. Consumers’ channel preferences
have also been heavily impacted by customers’ anticipation of regret [10]. Customers may
get around this by gathering more data, which can be used in online and offline investiga-
tions [11]. Buyers’ worry becomes a negative incentive for restricting or not purchasing
online, even though sellers provide several advantages and value. Furthermore, anxiety
causes a consumer’s purchase on an omnichannel system to be abandoned and diminishes
their loyalty to a firm if it continues across several channels. Negative emotions hinder
long-term business-consumer connections [12,13]. Researchers have viewed anxiety as
a negative emotional construct [14,15]. However, previous anxiety studies focused on
system anxiety [16]; or technical risk anxiety, such as computer anxiety [17,18] or Internet
anxiety [19,20]; but did not pay much attention to anxiety as the psychological symptom
construct to the omnichannel system [21]. At the same time, studies on the role of anxiety
primarily focused on the role of independent variables or moderators are common [22];
several studies focused on the regulatory effect of anxiety on purchasing factors and in-
tentions [23], and electronic satisfaction [24]. This limitation creates a gap for research in
assessing the effect of anxiety on customer relationship management in all stages of the
customer journey in omnichannel systems (pre-purchase, purchase, post-purchase).
In developed countries, omnichannel systems have been developed long before, and
the legal related to transactions were established and controlled strictly [25,26]. However,
in contrast to the investment and development of omnichannel in developed countries,
consumers in developing countries have been limited in online shopping via websites
or mobile devices [27–29]. Consumers’ habits of buying brick-and-mortar shops cannot
be changed quickly. The perceived risk describes an individual’s subjective evaluation
of his or her risk of an illness or an adverse outcome, often about performing a certain
risky behavior [30]. However, when we say anxiety, we mean experiencing negative
feelings or emotions while engaging in a certain activity. People may wish to stay away
from electronics depending on how anxious they are [31]. Anxiety develops when people
attempt to carry out activities in which they lack confidence [32]. If consumers do not
feel comfortable using omnichannel services, they may experience anxiety while making
purchases across channels [33]. Lessening the burden on the consumer is an important
part of providing a satisfying experience. Customers want to be able to communicate
with a company via their chosen methods on the devices they want to provide the best
possible experience. Customers feel pushed out of their comfort zones, which may lead
to anxiety, irritation, and an unpleasant experience if they comply with preset support
and communication channels. In addition, it may be challenging to concentrate on the
correct media for the right clients since a customer’s favorite channels may change based
on time, location, and urgency. The fear of buying counterfeit, fake, inferior products is
online consumers’ collective psychology [34]. In addition to product quality, many stores
launch deceptive promotions to attract users [35]. Furthermore, personal information is
the customer’s biggest privacy issue when used legally for selling and advertising. The
above risks increase customers’ anxiety when making transactions in omnichannel systems,
resulting in no intention to buy online or discontinue trading with an omnichannel system
J. Theor. Appl. Electron. Commer. Res. 2023, 18 132

after the first transaction, although they received many benefits and values from online
transactions, including utilitarian and hedonic benefits/values.
Retail is required to take continuous action to respond to changes in consumer behavior
and new government-supported business models related to mass media restrictions. The
pandemic has prompted the emergence of a new multichannel and mixed-store model
called omnichannel [36]. This model continues to grow with the restructuring of operations
from physical stores and warehouses to back-office headquarters. In Vietnam, survey
results from Deloitte [37] show that nearly 52% of customers will shop online as often
as during the pandemic, and more than 45% of customers think they will shop online
less than during the pandemic but more often than before the pandemic. In addition,
the top 4/6 factors driving customers to multichannel shopping are related to logistics,
including door-to-door delivery and delivery speed (89.22%); products are diversified and
abundant (52.94%); easy ordering method (50.98%); save shopping time (49.02%); many
promotions (49.02%); do not have to wait in crowded queues and contact many customers
(34.31%). Thus, creating a more responsive network is important for retailers to build to
stay competitive in omnichannel. The report confirmed that pure e-commerce would not
be able to replace physical stores in Vietnam [38]. However, stores are no longer merely
a place to display items but have a role in integrating into the online purchasing process
as the online–merge–offline model trend. The headquarters office supporting shops and
supermarkets will also be majorly reformed. As remote working becomes more common,
retail businesses need to radically improve operational efficiency and shift towards digital
working styles.
The stimulus–organism–response (hereafter SOR) model, which Mehrabian and Rus-
sell [39] proposed, is a well-known model for reflecting the buyer–seller interaction and
may be used in consumer behavior research [40]. Furthermore, the SOR model has been
used to examine user behavior in information technology, media, and online services such
as mobile user auctions [41]. The SOR model describes the relationship between inputs
(stimulus), processes (organism), and outputs (response) and assumes an individual’s
perception of the environment (context) [39]. The SOR framework has concretized the idea
of the “create value and capture value” process presented by Kotler et al. [42]; however, this
study considers SOR in the customer journey of transactions in omnichannel systems. The
omnichannel systems bring many benefits to customers who buy the product or service;
hence, they can value their advantages. Finally, customers anticipate long-term connections
such as customer loyalty or repurchase behavior from their transactions in omnichannel
systems [43,44]. Because this study focuses on the links between perceived mental bene-
fits, hedonic value, and e-loyalty in omnichannel systems, the SOR model is used as the
overarching framework. The following research questions led the systematic literature
review:
RQ1. How are the relationships between perceived mental benefits, hedonic value,
and e-loyalty in omnichannel systems?
RQ2. How does anxiety negatively moderate the relationship between buyers and
sellers in business omnichannel?
This research sought to overcome the theoretical gap by examining two key interac-
tions. To begin, this study was founded on the SOR model, which includes three constructs
in the omnichannel systems: perceived mental benefit, hedonic value, and electronic loyalty,
in which the “stimulus” in the context studied here is perceived mental benefits, hedonic
value in online transactions represents the “organism,” and electronic loyalty is the “re-
sponse.” Second, the influence of anxiety as a moderating variable on correlations between
research components in the SOR model for the omnichannel systems was investigated. The
research findings provided a strong framework for scholarly contributions and a platform
for providing managerial implications for firms in the context of risky transactions over
omnichannel systems.
The remainder of the paper is structured as follows: First, the literature review and
the goals of this study are summarized in two research questions. The search and selection
J. Theor. Appl. Electron. Commer. Res. 2023, 18 133

procedures used in the technique are then outlined. The study’s conclusions, as well as
their implications and caveats, are discussed in the last part.

2. Literature Review
2.1. Stimulus–Organism–Response (SOR) Model
Many studies have shown that the retail environment influences customer behav-
ior. The most widely used hypothesis is the SOR model (stimulus–organism–response),
which was created by Mehrabian and Russell [39] and confirmed in the retail shop environ-
ment [45]. This model indicates that human responses exhibit emotion and behavior for
stimuli in the external environment [39].
The term “marketing stimulus” refers to the influence of a product, price, location,
promotion, people, procedure, physical evidence, and the “external environment” (eco-
nomic, technological, social, and cultural). They are all determined by the SOR model’s
stimulus [46]. The organism’s state of the customer, such as the buyer’s characteristics
and the buyer’s decision process in the SOR model, represents the customer’s emotional
response to exposure to the stimulus from the seller [46]. These factors comprise three
primary emotional states, PAD (pleasure, arousal, and dominance), each independent of the
other [39]. In most studies, the “reaction” from the SOR model relates to consumer behavior,
such as spending longer time in the shop and more money; if the ambiance at the busi-
ness is pleasant, the customer plans to return and promote others to the store [47]. Many
researchers have proposed and appreciated the SOR model to design online consumer
behavioral models [48–50]. Based on the SOR model, Vergura et al. [51] show that emotional
reactions are critical in the link between stimulus and behavior. Empirical research has also
established the relevance of emotion-based attitudes in mediating the impacts of stimuli on
consumption behavior [52].
Wu et al. [53] pointed out that the hedonic-related website is a stimulus factor and
impacts customers’ emotions in online shopping. In online shopping, customers can look for
practical and mental benefits. Utilitarian benefits relate to pricing, convenience, and product
quality, while mental benefits relate to the enjoyment of design, psychology, and shopping
experience [54]. Khoa and Nguyen [55] measured perceived mental benefits in the online
Vietnamese market, including shopping enjoyment, social engagement, personal buying,
and perceived control. Duong and Liaw [56] predicted that technological advantages in e-
commerce would serve as a stimulus. Moreover, perceived benefits describe the advantages
customers believe they will receive from making purchases on a certain e-commerce site or
the advantages users anticipate receiving; hence, perceived benefits were used as a stimulus
in the SOR model in the research of Zhou et al. [57]. Furthermore, omnichannel systems are
meant to improve communication between consumers, customers, and the company and
provide quick assistance and information resources about goods of interest. These benefits
provide rapid pleasure or respite from bad sensations, which greatly impact customers’
views about online purchasing [58] and online shopping behavior [59]. Consumers are
becoming more concerned with perceived mental advantages [60]. Therefore, the perceived
mental benefit can be considered the SOR model’s stimulus. The SOR model of omnichannel
systems is shown in Figure 1.
2023, 18, FOR PEER REVIEW 5
J. Theor. Appl. Electron. Commer. Res. 2023, 18 134

Figure 1. The conceptual

Figure 1. model.
The conceptual model.

2.2. Research Hypotheses

2.2. Research Hypotheses
The customer’sThe customer’s
return return
to the shop, or to
thethe shop,
offer or the offerisofa incentives,
of incentives, behavior that is ashows
behavior that shows
engagement with the online seller [61]. Customers’ favorable attitude and dedication toand dedication
engagement with the online seller [61]. Customers’ favorable attitude
the omnichannel to the omnichannel
systems systems result
result in repurchase in repurchase
behavior and do not behavior
transferand do not
to other buy-transfer to other
buyers. Loyal clients promote omnichannel systems
ers. Loyal clients promote omnichannel systems and urge others to do the same [62,63]. and urge others to do the same [62,63].
Electronic customer loyalty is considered the best response that businesses expect. The expect. The
Electronic customer loyalty is considered the best response that businesses
customer’s
customer’s values mediatevaluesbetween mediate between the
the business’s business’s
stimulus stimulus program
or marketing or marketing and program and
customer loyalty response through the transaction.
customer loyalty response through the transaction. Kotler, Keller, Goodman, Brady, and Kotler, Keller, Goodman, Brady, and
Hansen [46] proposed creating consumer-driven
Hansen [46] proposed creating consumer-driven marketing programs to create superior marketing programs to create superior
value and capture customers’ value. Hedonic value relates to senses, pleasures, feelings,
value and capture customers’ value. Hedonic value relates to senses, pleasures, feelings,
and emotions [64]. The customer can obtain the hedonic value via the fun and playfulness
and emotions [64]. The customer can obtain the hedonic value via the fun and playfulness
of the subject’s experience [65]. Therefore, the researchers confirm hedonic value as the
of the subject’s experience [65]. Therefore, the researchers confirm hedonic value as the
SOR model organism within this study’s scope.
SOR model organism within this study’s scope.
Electronic loyalty transfers brand loyalty from conventional to online commerce [66].
Electronic loyalty transfers brand loyalty from conventional to online commerce [66].
Electronic loyalty is a positive attitude toward an online company, leading to frequent
Electronic loyalty is a positive attitude toward an online company, leading to frequent
purchases on that enterprise’s sales page [67,68]. Online loyalty improves the profitability
purchases on that enterprise’s sales page [67,68]. Online loyalty improves the profitability
of online companies by establishing long-term connections with consumers and lowering
of online companies by establishing long-term connections with consumers and lowering
the cost of acquiring new clients in an online environment [69]. Online corporate profits
the cost of acquiring new clients in an online environment [69]. Online corporate profits
increase by encouraging customers to repeat buying behavior [70]. In the growth of social
increase by encouraging customers to repeat buying behavior [70]. In the growth of social
networking sites, consumers’ loyalty behavior is also reflected in their interactions with
networking sites, consumers’
corporate socialloyalty
mediabehavior
sites, such is also reflected
as liking, in their
sharing, or interactions
following pages.with When firms’
corporate social media sites, such as liking, sharing, or following pages. When
competitive strategies depend on the amount of information customers provide to the firms’ com-
petitive strategies depend
business, on the amount
exposure to personal of information
informationcustomers provide to
is also considered anthe busi- of electronic
indicator
ness, exposureloyalty
to personal information
with online businesses. is also considered an indicator of electronic loyalty
with online businesses.
Traditional procurement may be influenced by functional and non-functional fac-
Traditional procurement
tors may be influenced
[71]. Non-functional incentives by include
functional andand
social non-functional factors
emotional requirements to have
[71]. Non-functional incentives
interesting shoppinginclude social andwhereas
experiences, emotional requirements
functional to haveinclude
motivations inter- convenience,
esting shopping experiences,
product variety,whereas
quality of functional
items, and motivations
costs [72]. include convenience,
All of these motivations prod-
are also beneficial
uct variety, quality of items, and costs [72]. All of these motivations are also
factors for consumers to shop online. Most people seek consumption that affords them beneficial
factors for consumers
feelings,tofantasies,
shop online. and Most people seek
joys, including consumption
playful that activities,
recreational affords them sensory pleasure,
feelings, fantasies, and joys, including playful recreational activities,
daydreaming, enjoyment, and emotional response [73]. Consequently, sensory pleasure, the consumer’s
daydreaming, perceived
enjoyment,mental and emotional
benefit is response [73]. Consequently,
tied to entertainment, peace of themind,
consumer’s
ease, personal fit, or
perceived mental benefit iswith
interaction tiedother
to entertainment, peace ofPerceived
individuals online. mind, ease, personal
benefit fit, oridentified
has been in- as an es-
teraction with other
sentialindividuals
premise of online.
consumer Perceived
loyalty.benefit
Trust andhas social
been identified as an
interests are essen-
significantly associated
tial premise ofwith
consumer
loyaltyloyalty. Trust and
[74]. Customers aresocial
loyalinterests are significantly
to the omnichannel systems associated
when they feel special
with loyalty [74]. Customers are loyal to the omnichannel systems when
treatment or have a social benefit [75]. In addition, entertainment benefits they feel specialare essential for
customers to continue using the service, followed by loyalty to the omnichannel systems.
J. Theor. Appl. Electron. Commer. Res. 2023, 18 135

Additionally, a loyalty program motivates customers to participate in loyalty programs

on e-commerce sites [76]. Omnichannel clients utilizing at least two channels throughout
their encounter with the company build their opinion of quality across all channels, not just
one, influencing their total happiness. Furthermore, in the case of omnichannel retail, the
benefit felt via the usage of various service channels was shown to be a decisive element in
the formulation of total customer satisfaction. Otherwise, because it has been established
that customer satisfaction in an omnichannel context is higher when the perceived benefit
of channel integration is high [77,78], this study proposes to test this link for benefits and
loyalty as customers transact via omnichannel systems. Therefore, the proposed hypothesis
H1 is as follows:
H1: Perceived mental benefit has a positive impact on electronic loyalty in omnichannel systems.
Hedonic value is one of the values related to consumers’ entertainment and emotional
needs [79]. Hedonic value is a behavioral component of multicultural, imaginative, and
emotional consumption processes. During the consumption process, customers appreciate
the interesting, inventive, fun, and stimulating experience provided by acquired items or
services [80]. Perceived value influences customer loyalty positively [81]. Brand penetration
is also derived from a customer’s positive perception of the brand after using its products
or services. In Sirdeshmukh et al. (2018)’s study, the perceived value was instrumental in
creating consumer loyalty. Customers tend to switch to another online provider [67]. In
addition to physical perceived values, hedonic perceived value is increasingly important in
building online shoppers’ intent to continue shopping. Hedonic value positively affects
engagement with Groupon sites [82]. Lewis and Soureli [83] corroborated this finding in
the banking industry, demonstrating that the perceived value clients get from their primary
bank is positively associated with customer loyalty. However, Carlson et al. [84], Swaid
and Wigand [85] have proven this conclusion in the multi-channel environment, finding
that a firm’s usage of several channels increases customer loyalty. An omnichannel that
consumers appreciate also boosts loyalty in the omnichannel environment [86]. Thus, in
the instance of omnichannel retail, this study proposes hypothesis H2:
H2: Hedonic value has a positive impact on electronic loyalty in omnichannel systems.
The customer purchases the product or service to achieve the lower-order values
of consumer benefit and sets the stage for the value of life [87]. Mental benefits are
instrumental in the developed social context, while hedonic value is the terminal value
in consumer behavior science. The empirical study of Chen and Hu [88] showed that
perceived benefits directly affect perceived value. Additionally, consumers are willing to
make trade-offs when they perceive the benefits of a service. In e-commerce, receiving
benefits such as entertainment or anonymity creates positive psychology for customers
when trading, which is the entertainment price. More specifically, a high level of multi-
channel integration that demonstrates a high level of channel synergy and a smooth
customer experience raises the perceived value of a consumer multichannel system [89].
This finding has received much attention in the context of omnichannel systems [90]. As a
result, this study proposed testing this relationship in the context of omnichannel systems,
particularly because, with the omnichannel system, firms tend to improve the benefits
of integrating their channels through more personalization of the shopping experience
and a large offering of mobile value-added services [91]. From there, this study proposes
hypothesis H3:
H3: Perceived mental benefit has a positive impact on Hedonic value in omnichannel systems.
The business tries its best to create and bring benefit or value to the customer through
omnichannel systems. The social cognitive theory offers a framework for understanding the
psychology of human cognition, emotions, and behavior [92]. Personal and environmental
variables interact in the model and serve as determinants of one another [93]. Human
behavior is governed by a system of behavioral variables, self-efficacy, and anticipated
J. Theor. Appl. Electron. Commer. Res. 2023, 18 136

consequences (the personal factors), and evaluation of one’s behavior concerning external
conditions (environmental factors). According to social cognitive theory, anxiety is an
emotional response that reduces an individual’s determination to take a specific action
by limiting personal abilities and judgments to generate performance through emotional
stimulation and lowering an individual’s expectations of the desired performance result [94].
Kim and Forsythe [95] have shown that the intangibility of online purchasing increases
uncertainty and perceived risk, contributing to online shopping anxiety. Anxiety is a
succession of unpleasant thoughts about similar or dissimilar themes that lead to potential
bad effects [96]. The current laws and regulations relating to electronic sales are insufficient
to protect customers from the risks associated with virtual suppliers worldwide. There
is considerable fear associated with internet buying, which diminishes their enthusiasm
for utilizing this approach [97]. When customers are anxious, online shopping frequency
decreases, reducing the patronage of electronic shops [98]. Therefore, this study can
consider the moderating role of anxiety based on the hypotheses below:
H4: Anxiety negatively moderates the relationship between perceived mental benefits and
electronic loyalty with omnichannel systems.
H5: Anxiety negatively modifies the relationship between hedonic value and electronic
loyalty in omnichannel systems.
H6: Anxiety negatively influences the relationship between perceived mental benefits and
the hedonic value of omnichannel systems.

3. Research Method
To design and evaluate the conceptual model, this study used a mixed technique,
primarily deductive methods (deducing from theory and empirical investigations) and the
inductive method (building different scales of research construct). Field research techniques
were employed to acquire information, while expert interviews and group discussions were
used to collect data for qualitative methodologies [99]. Two categories were specifically
discussed: Group 1 consists of eight omnichannel specialists, and Group 2 consists of
sixteen MBA students who often purchase omnichannel systems in Vietnam. The goal
of the group discussion is to standardize vocabulary and alter and augment the scale
to fit the Vietnamese context and conditions and, concurrently, clarify the meaning and
comprehensiveness of the questionnaire survey questions [100].
The buyers (including students, white-collar professionals, company owners, lecturers,
laborers, housewives, and government officials) were surveyed using a premade question-
naire to obtain data for quantitative analysis. The participants have occupations with high
exposure to omnichannel purchasing and are early adopters of technology; therefore, they
boldly order from omnichannel operations. However, it is precisely because pioneering
shopping in a new way leads to unexpected results from their purchases, which makes them
anxious, and some respondents consider continuing to buy from omnichannel systems. The
survey respondents were chosen using a sampling technique known as convenience sam-
pling. The survey was created online using Google Forms, and its URL was shared across
several social media platforms. Friends on the author list sent this survey URL to pool their
responses. This study focuses on popular purchasing occupations in Vietnamese omnichan-
nel, such as students, office workers, lecturers, entrepreneurs, housewives, and government
officials [101]. In addition, to ensure the reliability and validity of the survey results, the
study also uses the number of times shopping through the omnichannel in a month as the
control variable. Moreover, the researchers explained the “omnichannel” in the survey, and
the participant must have experience in using omnichannel. Omnichannel systems have
been popular in Vietnam recently; hence, the participants could understand them. Table 1
provides a breakdown of the study’s sample size of 485 and some descriptive statistics.
J. Theor. Appl. Electron. Commer. Res. 2023, 18 137

Table 1. Sample descriptive statistic.

N %
Male 246 50.7
Gender
Female 239 49.3
Student 71 14.6
White-collar
69 14.2
employee
Occupation Business owner 65 13.4
Lecturer 71 14.6
Worker 72 14.8
Housewife 66 13.6
Government official 71 14.6
2–4 times 116 23.9
5–6 times 116 23.9
Times of online shopping/month
7–10 times 122 25.2
>10 times 131 27.0

The scale of all constructs is adapted from the previous research and adjusted in the
qualitative research. Quantitative data collected was processed using SmartPLS software,
version 3.7. All scales of this study were based on prior studies and modified for omnichan-
nel background. The scale of perceived mental benefits (hereafter PMB) includes four
items [102]. The scale of electronic loyalty (hereafter ELOY) includes three items [103]. The
hedonic value scale (hereafter HV) includes four items [104]. PMB, ELOY, and HV scales
were measured using a five-point Likert scale (1 is totally disagree, 5 is totally agree). This
research employed a five-point Likert scale instead of a seven-point one for two reasons.
The first was an online poll, which people could fill out in a few minutes while waiting
for the bus or at their desks. The second factor is that the five-point Likert scale is quite
common in Vietnam. The scale of anxiety (hereafter ANX) included six items, such as
worry, stress, fear, difficulty, distraction, and disinterest [105], which were measured by
the five-point scale (0—none; 1—low; 2—moderate; 3—high; 4—very high). The anxiety
measurement scales (Appendix A), which were adapted from Khoa and Nguyen [55], are
the psychological symptom; hence, they begin with “0” (zero value).

4. Results
Using Cronbach’s alpha (hereafter CA), this study determines whether the scale is
credible; a CA of 0.7 or above indicates a credible scale. Table 2 shows that on the scale
of ELOY, the lowest possible CA is 0.792, and the lowest possible composite reliability
(hereafter CR) is 0.882 (scale of PMB). This means that the study scales may be relied upon
to accurately measure the constructions of interest.

Table 2. Reliability and validity test result.

VIF Value HTMT Value

Construct CA CR AVE Outer Loading
HV ELOY ANX ELOY HV
ANX 0.933 0.946 0.746 0.773–0.958
ELOY 0.792 0.878 0.71 0.786–0.876 0.224
HV 0.893 0.922 0.75 0.775–0.910 1.416 0.140 0.456
PMB 0.83 0.882 0.65 0.730–0.891 1.213 1.492 0.507 0.643 0.428

When the CR of a scale is at least 0.7, the average variance extracted (hereafter AVE)
value is at least 0.5, and outer loadings of the items in the construct are at least 0.708, then
the scale may be said to have convergent validity. Outer loadings for four items ranged
from 0.775 to 0.910; CR for PMB was 0.882; CR for ANX was 0.946; CR for AVE for ANX
was 0.746; CR for CR for ANX was 0.882; CR for AVE for CR for ANX was 0.746; and CR
J. Theor. Appl. Electron. Commer. Res. 2023, 18 138

for CR for AVE for CR for ANX was 0.882 (Table 2). Thus, all study constructs attained
convergent validity.
To evaluate the discriminant validity of two constructs, researchers have begun to use
the Heterotrait–Monotrait correlation ratio (henceforth HTMT). HTMT has a cutoff of 0.850.
Because the highest HTMT value in Table 2 is 0.643, which is lower than the cutoff value of
0.850, it is easy to say that all of the constructs in this research have discriminant validity.
This is known as collinearity when two or more seemingly unrelated factors are
shown to be highly correlated. Due to the regression model’s skewness brought on by the
collinearity phenomena, quantitative analysis will no longer provide any insight. When
evaluating collinearity, the variance inflation factor (VIF) is used. No collinearity exists if
the VIF value is less than three. No collinearity was found since the greatest VIF was 1.492,
as shown in Table 2.
According to F. Hair et al. [106], partial least squares structural equation modeling
(PLS-SEM) research publications have expanded substantially in recent years. Because
PLS-SEM outperforms CB-SEM (covariance-based structural equation modeling) in several
important ways, it is increasingly being used in fields including organizational behavior,
information system management, strategic management, and marketing research. Using
complex research models with many moderators, mediators, latent and observed variables,
in particular, structural equation models; analyzing reflective measurement models and
formative measurement models simultaneously; being fit for predisposition-oriented stud-
ies; accepting small sample size and nonnormal distribution. The PLS-SEM model was
assessed using the bootstrapping technique, with an initial sample size of 485 and 5000
random subsamples. The results indicated that hypotheses 1, 2, and 3 (H1, H2, and H3)
were supported with a 99 percent confidence level (p-value = 0.000 < 0.001).
R2 is an essential indicator in evaluating the degree of interpretation of the independent
variable to the dependent variable and is called the determination coefficient. An R2 value
of 0.2 is considered high [107]. Accordingly, the result pointed out that the R2 value of HV
was 0.231, reflecting the low level of interpretation of PMB to HV, but it could be acceptable.
PMB and HV explained a moderate ELOY change. The effect size f2 is used to consider the
effect of exogenous variables on endogenous variables. The impact level is weak, moderate,
and strong when f2 is at 0.02, 0.15, and 0.35, respectively. Table 3 shows that the effect size
of the relationship between PMB and HV was moderate (f2 = 0.222). In addition, PMB had
a strong effect on ELOY (f2 = 0.395), and HV was affected weakly on ELOY (f2 = 0.026).
Q2 denotes the prediction level through the blindfolding technique, and Q2 indicates the
explanatory power and predictability of the endogenous latent variable. If the value of Q2
is higher than 0, a model has predictive relevance. In Table 3, the values of Q2 confirmed
the predictive relevance when all Q2 is greater than 0 (Q2 HV = 0.134, and Q2 ELOY = 0.308).

Table 3. PLS-SEM result.

Relationship β STDEV p Values Result

PMB -> ELOY 0.554 0.040 0.000 Supported
HV -> ELOY 0.138 0.033 0.000 Supported
PMB -> HV 0.455 0.042 0.000 Supported
PMB -> HV -> ELOY 0.063 0.016 0.000
R2 HV = 0.231, R2 ELOY = 0.479
f2 PMB->HV = 0.222; f2 HV->ELOY = 0.0.026; f2 PMB->ELOY = 0.395
Q2 HV = 0.134, Q2 ELOY = 0.308
Note: STDEV: standard deviation.

Hedonic value was also confirmed to play a partial moderator between perceived
mental benefit and electronic loyalty when satisfying the criteria, including (1) PMB had
a significant impact on HV (β = 0.455, p-value = 0.000), (2) HV had a significant impact
on ELOY (β = 0.138, p-value = 0.000), (3) PMB impact significantly on ELOY (β = 0.554,
 PMB -> ELOY 0.554 0.040 0.000 Supported
HV -> ELOY 0.138 0.033 0.000 Supported
PMB -> HV 0.455 0.042 0.000 Supported
PMB -> HV -> ELOY 0.063 0.016 0.000
R HV = 0.231, R ELOY = 0.479
2 2
J. Theor. Appl. Electron. Commer. Res. 2023, 18 139
f2PMB->HV = 0.222; f2HV->ELOY = 0.0.026; f2PMB->ELOY = 0.395
Q2HV = 0.134, Q2ELOY = 0.308
Note: STDEV: standard deviation.
p-value = 0.000), and (4) the level of PMB’s impact on ELOY through HV was less the direct
impact
ThisPMB
studyonchose
ELOYthe = 0.063, p-value
(βtwo-stage = 0.000).
approach to assess anxiety’s moderating because it is
This study chose the two-stage approach to assesseffect
the most versatile [107]. Table 4 illustrates the moderating anxiety’s moderating
of anxiety because
on the relation-
it is the most versatile [107]. Table 4 illustrates the moderating effect of anxiety on the
ship between perceived mental benefits, hedonic value, and electronic loyalty in e-com-
relationship between perceived mental benefits, hedonic value, and electronic loyalty in
merce.
e-commerce.
Table 4. The impact of anxiety on the relationship between perceived mental benefits, hedonic
Table 4. The impact of anxiety on the relationship between perceived mental benefits, hedonic value,
value, and electronic loyalty.
and electronic loyalty.
Relationship Hypothesis β STDEV p Values Result
Relationship Hypothesis β STDEV p Values Result
PMB*ELOY-> ELOY H4 −0.303 0.043 0.000 Supported
PMB*ELOY-> ELOY
HV*ELOY-> H5 −0.303 0.030 0.0430.027 0.242 Reject
H4 0.000 Supported
ELOY
PMB*HV-> HV
HV*ELOY-> ELOY H5
H6 0.030 −0.176 0.0270.057 0.002
0.242
Supported
Reject
Note:PMB*HV->
STDEV: standard
HV deviation.
H6 −0.176 0.057 0.002 Supported
Note: STDEV: standard deviation.
Table 4 pointed that the interaction term (PMB*ELOY) has the negative impact on
ELOYTable(-0.303), whereasthat
4 pointed thethe
simple effect ofterm
interaction PMB(PMB*ELOY)
on ELOY washas 0.554,
thewhich is animpact
negative average on
ANX effect. For higher ANX levels, by increasing by one standard deviation
ELOY (-0.303), whereas the simple effect of PMB on ELOY was 0.554, which is an average unit, the re-
lationship
ANX effect. between PMB and
For higher ANXELOY decreased
levels, to 0.268
by increasing by (i.e.,
one 0.554–0.303 = 0.251).unit,
standard deviation On the
the
other hand, with
relationship lower PMB
between ANXandlevels by decreased
ELOY decreasedoneto standard
0.268 (i.e.,deviation point,
0.554–0.303 PMB and
= 0.251). On
ELOY’s
the other relationship
hand, withbecame 0.554 levels
lower ANX + 0.303by= 0.857. Moreover,
decreased the p-value
one standard of thepoint,
deviation path link-
PMB
ing
andthe interaction
ELOY’s term and
relationship ELOY0.554
became was +0.000,
0.303and H4 was
= 0.857. supported
Moreover, with a confidence
the p-value of the path
level of 99%
linking (Table 4). Consequently,
the interaction term and ELOY ANX
waswas a moderator
0.000, and H4 wasthat negatively
supported withimpacted the
a confidence
relationship
level of 99%between perceived
(Table 4). mentalANX
Consequently, benefits
wasand electronicthat
a moderator loyalty, as shown
negatively in Figure
impacted the
2.relationship between perceived mental benefits and electronic loyalty, as shown in Figure 2.

The
Figure2.2.The
Figure moderator
moderator of anxiety
of anxiety in relationship
in the the relationship between
between perceived
perceived mental
mental benefits
benefits and
and elec-
tronic loyalty.
electronic loyalty.

The interaction term (HV*ELOY) positively impacts ELOY (+0.03) in Table 4, whereas
the simple effect of HV on ELOY is 0.138, which is an average ANX effect. For higher ANX
levels, by increasing by one standard deviation unit, the relationship between HV and
ELOY decreased to 0.135 (i.e., 0.138–0.03). Conversely, the relationship between HV and
ELOY was 0.135 (0.138–0.003) for lower ANX levels by decreasing one standard deviation
point. Following the result in Table 4, the p-value of the path linking the interaction term
and HV was 0.242, which means H5 was rejected. Therefore, ANX was not a moderator in
the relationship between hedonic value and electronic loyalty, as shown in Figure 3.
 the simple effect of HV on ELOY is 0.138, which is an average ANX effect. For higher ANX
ELOYby
levels, decreased to 0.135
increasing by one(i.e., 0.138–0.03).
standard Conversely,
deviation unit, thetherelationship
relationshipbetween
betweenHV HVand
and
ELOYdecreased
ELOY was 0.135to(0.138–0.003) for lower ANX
0.135 (i.e., 0.138–0.03). levels by the
Conversely, decreasing one standard
relationship between deviation
HV and
point. Following the result in Table 4, the p-value of the path linking the
ELOY was 0.135 (0.138–0.003) for lower ANX levels by decreasing one standard deviation interaction term
and HV was 0.242, which means H5 was rejected. Therefore, ANX was not
point. Following the result in Table 4, the p-value of the path linking the interaction term a moderator
in the
J. Theor. Appl. Electron. Commer. Res.and
2023, 18 relationship
HV between
was 0.242, which hedonic
means valuerejected.
H5 was and electronic loyalty,
Therefore, ANXaswasshown
not in Figure 3.140
a moderator
in the relationship between hedonic value and electronic loyalty, as shown in Figure 3.

Figure 3. The moderator of anxiety in the relationship between hedonic value and electronic loy-
alty. Themoderator
Figure3.3.The moderatorofofanxiety
anxietyininthe
therelationship
relationshipbetween
betweenhedonic
hedonicvalue
valueand
andelectronic
electronicloy-
loyalty.
Figure
alty.
Table 4 pointed that the the interaction
interaction termterm (PMB*HV)
(PMB*HV) hurts hurts HV −0.176), whereas
HV ((−0.176), whereas the
simple effect
effect of
ofPMB
PMB ononHVHVis 0.445,
is which
0.445, whichis an isaverage
an level
average
Table 4 pointed that the interaction term (PMB*HV) hurts HV (−0.176), whereas of the
level ofANXthe effect.
ANX For higher
effect. For
the
levels
higher of ANX,
levels ofby increasing
ANX, by by one
increasing standard
by one deviation
standard unit,
deviationthe
simple effect of PMB on HV is 0.445, which is an average level of the ANX effect. For relationship
unit, the between
relationship PMBbe-
and
higherHV
tweenlevelsdecreased
PMB of and to 0.268 (i.e.,
HV decreased
ANX, by increasing0.445–0.176
to 0.268
by one =
(i.e., 0.269). On
0.445–0.176
standard the other
= 0.269).
deviation hand,
On
unit, the by
the decreasing
other hand,be-
relationship one
by
standard
decreasing deviation
one point
standard for lower
deviation levels
point forof ANX,
lower the
levelsrelationship
of ANX,
tween PMB and HV decreased to 0.268 (i.e., 0.445–0.176 = 0.269). On the other hand, by thebetween PMB
relationship and HV
between
becomes
PMB and0.445
HV + 0.176 =0.445
0.621. The p-value of thep-value
path linking thethe interaction term and HV
decreasing onebecomes
standard + 0.176
deviation = 0.621.
point The
for lower levels ofofANX, path
the linking the
relationship interaction
between
was 0.002, and H60.002,
was supported with a confidence level of 95% level
in Table 4. Hence, as a
PMB and HV becomes 0.445 + 0.176 = 0.621. The p-value of the path linking the interaction4.
term and HV was and H6 was supported with a confidence of 95% in Table
moderator,
Hence, as aANX negatively
moderator, ANX impacted
negativelythe relationship
impacted thebetween perceived
relationship mental
between benefits
perceived
term and HV was 0.002, and H6 was supported with a confidence level of 95% in Table 4.
and hedonic
mental benefitsvalue,
andas shownvalue,
hedonic in Figure 4.
as shown in Figure
Hence, as a moderator, ANX negatively impacted the 4.relationship between perceived
mental benefits and hedonic value, as shown in Figure 4.

Themoderator
4. The
Figure 4. moderatorofofanxiety
anxiety
in in
thethe relationship
relationship between
between perceived
perceived mental
mental benefits
benefits and and
he-
donic value.
hedonic value.
Figure 4. The moderator of anxiety in the relationship between perceived mental benefits and he-
donic value.
5. Discussion
The research tested the relationship of variables in the study based on the SOR model
of Mehrabian and Russell [39]. The research results confirm the SOR theory with perceived
mental benefit, hedonic value, and electronic loyalty in the omnichannel platform context.
This research was carried out in Vietnam, where the economy and consumer life will
continue to thrive over the coming decade. Economic growth and consumer vitality will
accelerate, setting a new benchmark for fast-growing economies and opening up incredible
possibilities for business owners and investors. Before discussing the research results, this
study summarized some contexts of Vietnam.
J. Theor. Appl. Electron. Commer. Res. 2023, 18 141

A large percentage of Vietnam’s young population accounts for half of the country’s
population. Since economic reforms were implemented in 1986, Vietnam has gone from one
of the world’s poorest countries to a lower middle-income economy with rapid GDP growth
per capita [108]. Due to this, more people can try out cutting-edge forms of shopping [109].
Forty percent of Vietnamese people use social media regularly, placing them eighth on
a list of countries with the most Facebook users [110]. Of the total population, 70% now
has access to the internet [111]. Little is known about omnichannels as a recreational
activity in the nation yet [38], despite its globalization and the fact that individuals of all
socioeconomic backgrounds participate in it. Most Vietnamese individuals have doubts
about the authenticity of goods bought online, which makes them reluctant to make
payments or shop from a new method such as an omnichannel in this manner.
Meanwhile, many companies have failed to earn consumers’ confidence at a level
that would prompt them to alter their buying patterns. However, after the COVID-19
pandemic, online shopping in Vietnam is to grow by 54% in 2020, thanks to the success
of online shopping platforms that have increased their market share, transaction volume,
and average order value [112]. Thus, with the aid of COVID, the channel has gained in
popularity, trustworthiness, and current dependence among its target audience. Ninja
Van Group and DPD Group conducted research in 2022 on cross-border e-commerce in
six ASEAN nations and found that Vietnamese customers place an average of 104 annual
online purchases, much more than their counterparts in Thailand (75 orders), Singapore, or
the Philippines (58 orders each) [113]. There are typically only around 66 annual orders in
other southeast Asian nations. However, there are some negative effects on the Vietnamese
due to the uncertainty avoidance aspect; the mental health issues of sadness, anxiety, and
personality disorders have all been linked to compulsive shopping, according to much
research [114]. Hence, Vietnamese customers are easily persuaded by the benefit or value
of omnichannel systems, which can make them loyal to a business. However, they also
experience stress and anxiety from innovative technology as shopping.
Hypothesis H1 was accepted, meaning that the perceived mental benefit positively
affects electronic loyalty (β1 = 0.554, p-value = 0.000). Previous studies have also shown a
relationship between benefits and customer loyalty. The benefits that business brings to cus-
tomers are proven to be the premise of loyalty intention, word of mouth, and commitment
to the organization. Adamson et al. [115], Friman et al. [116] demonstrated that benefits
can increase commitment and customer loyalty. Customer loyalty and the commitment to
purchase increases as it provides additional exclusive benefits to its customers [117,118].
Social and unique treatment benefits are essential in increasing customer commitment
to the business [74,119]. As technology develops, the ability to customize products and
services is a benefit that positively affects electronic customer loyalty. Ju Rebecca Yen and
Gwinner [120] pointed out that loyalty increases when customers positively perceive a
business’s benefit. Customers shopping online in developing countries often appreciate
the benefits that business brings. Therefore, the perceived mental benefits are essential
in building electronic loyalty on an omnichannel platform. Recent studies have pointed
out that the benefit of omnichannel platforms makes the customer disclose their personal
information to improve the quality of the relationship [36].
This study showed that hedonic value positively affected electronic loyalty with
a confidence level of 99%; hence, hypothesis H2 was accepted with β2 = 0.138. These
findings support Carpenter et al. [121], suggesting that hedonic shopping value significantly
contributes to customer loyalty and word-of-mouth. The product value positively impacts
satisfaction by increasing customer loyalty [122]. Customer loyalty is created by product
value [123]. The utilitarian value affects customer satisfaction, but the hedonic value
directly impacts loyalty to Airbnb’s service [124]. Thus, in addition to utilitarian values,
a business should provide customers with entertainment and enjoyment values when
shopping on an omnichannel platform. The customer’s best hedonic values were games
or news on omnichannel systems, especially from the social media marketing activities of
businesses [125–127].
J. Theor. Appl. Electron. Commer. Res. 2023, 18 142

Moreover, hypothesis H3 was also accepted (β3 = 0.455, p-value = 0.000). Thereby, the
perceived mental benefit positively affects hedonic value. The trade-off theory has shown
that benefit and cost are two prerequisites of perceived value [118,128]. Hann et al. [129]
also provide evidence that money is a financial benefit the business brings to its customers,
leading to positive behavior. Sweeney and Soutar [130] defined value as a positive assess-
ment of the benefits customers receive from the business. The hedonic value begins with
mental benefits such as fun and enjoyment of transactions from the omnichannel platform;
consequently, the more mental benefits are created, the more hedonic value is received.
Hypotheses H4 and H6 are supported, respectively, β4 = −0.303, p-value = 0.000, and
β6 = −0.176, p-value = 0.002. Anxiety negatively moderates the perceived mental benefit
of electronic loyalty and the impact on hedonic value [55]. The moderating effect on the
relationship between PMB and ELOY is greater, meaning that the anxiety change leads
to a large negative change in this relationship. Increased anxiety about an omnichannel
platform reduces customers shopping on the site even though it benefits the customer.
Vietnam is accustomed to media shopping with a “touch-and-see” mentality. Additionally,
anxiety is also a factor that reduces online shopping value, although it has many benefits.
Feeling enjoyment, social interaction, discreetness, and control cannot fill the risks when
dealing online.

6. Conclusions
The omnichannel platform has received consumers’ attention due to the benefits sur-
passing traditional commerce. Purchasing omnichannel platform products or services
brings enjoyment, social interaction, discreetness, and control; hence, the omnichannel
system creates a hedonic value for consumers as they shop on an omnichannel platform.
Simultaneously, these benefits and values create customers’ electronic loyalty to an om-
nichannel system. However, this study’s results also point out the adverse effects of anxiety
on the relationship between benefits, loyalty, and hedonic value. Therefore, businesses
need solutions to reduce customer anxiety to maintain customer preference, patronage, and
premium for an omnichannel system. This research’s results have theoretical contributions
and managerial implications for businesses.

6.1. Theoretical Contributions

This research’s results bring many theoretical contributions to consumer behavior or
electronic commerce.
Firstly, instead of studying the general perceived benefits and the perceived value of
consumers like previous studies [88,131,132], this study focused on building relationships
between consumer psychology factors such as perceived mental benefits, hedonic value,
and anxiety. The perceived mental benefits of online shopping included perceived enjoy-
ment, perceived social interaction, perceived discreet shopping, and perceived control. The
positive relationship between the research constructs in the omnichannel system context
will contribute to further research in the same or different context as mobile commerce or
social commerce.
Secondly, consumer anxiety symptoms are prevalent and are interested in psychologi-
cal research; however, it has limited online consumer behavior science. Most studies have
measured anxiety via technology anxiety (computer anxiety [18,133,134] or internet anxi-
ety [19,20]), reflecting a part of anxiety. This research expanded anxiety as the psychological
factor with six states of feeling based on Hamilton’s study: worry, stress, fear, difficulty,
distraction, and disinterest. From this study’s result, customer anxiety in omnichannel
systems can be measured as a novel and exact concept in marketing science.
Finally, the moderating role of anxiety symptoms in the relationship between research
constructs is also an academic contribution. Very few studies evaluate anxiety as a modera-
tor; for example, Yang and Forney [23] showed that technological anxiety moderates the
impact of facilitating conditions on utilitarian and hedonic performance expectancy and the
relationship between social influences and behavioral intention. In contrast, most previous
J. Theor. Appl. Electron. Commer. Res. 2023, 18 143

studies looked at the effects of anxiety as an independent variable, which harms some
other concepts: perceived cognitive effort [135], perceived ease of use [136,137], patronage
intentions [21], and behavioral intentions. This study demonstrated the moderating role of
anxiety in the effect of perceived mental benefits on electronic loyalty and perceived mental
benefits on hedonic value in omnichannel systems.

6.2. Managerial Implications

The positive impact of perceived mental benefits on hedonic value and electronic
loyalty showed its importance; therefore, businesses need to focus on providing appropriate
solutions to generate benefits related to mental benefits in the four aspects outlined in the
research: enjoyment, social interaction, discreet shopping, and perceived control. Firstly,
the omnichannel system should concentrate on image quality and instruction posts to make
valuable information for customers’ evaluation in the search stage. The gamification in
mobile applications for special events needs to hold to create the customer’s relaxation.
Secondly, online businesses can increase customer social interaction through the customer
forum or the customer feedback system. The omnichannel system should be added to the
rating function of each product or service for customers. Privacy policies, as well as careful
packaging, increase perceived discreet shopping. The information in the package is enough
to ship the product or service. Finally, businesses can use cookies to collect online users’
habits or establish retarget marketing strategies to enhance customers’ perceived control.
Anxiety negatively affects the relationship between perceived mental benefits and
electronic loyalty and between perceived mental benefits and hedonic value. Hence, the
business should try to reduce the anxiety of buyers as some solutions below.
(a) This study’s first implication concerns customers’ digital literacy, which, if inadequate,
might stymie businesses’ attempts to implement omnichannel strategies. Managers
can educate consumers to increase their digital literacy, or they may make omnichan-
nel experiences as straightforward as possible.
(b) The features of the product are the subject of the second managerial implication.
According to our findings, online shoppers may feel uneasy about purchasing per-
ishable or delicate goods from a distant vendor. Thus, managers working with such
products should aim to (1) provide the infrastructure to prevent the product from
spoiling or breaking and (2) alleviate customers’ anxiety related to such infrastructure
by providing a transparent and comprehensive communication policy on delivery
modes and return options. The refund and product/service return policies should be
clear and published on the channels.
(c) The tracking system should establish customers to check the transaction process;
therefore, they will not worry about its goods/services. There is a strict collaboration
between businesses and logistics companies to ensure on-time shipping. Furthermore,
it is ideal for the shop to charge shipping when they promise a quicker delivery
time, which may lessen customers’ perceived uncertainty and boost satisfaction. This
means that free delivery is not always preferable. Online stores that cannot send items
quickly may choose to provide free delivery instead, which means they include the
shipping cost in the item’s price. This practice is thought to boost customer satisfaction
and subsequent purchases.
(d) The significance of a purchase affects online shopping hedonic value. When making
a significant purchase, shoppers are more appreciative of expedited shipping. Cus-
tomers may decide not to buy anything online because they feel it is too important to
risk losing money. They are more inclined to buy key items in-store with visual and
tactile contact. The door is now open for omnichannel merchants to provide “You may
place an order and pick it up in store today” services. Customers may still buy the
goods online; however, in certain cases, urgent orders can be fulfilled the same day or
within a few days. This guarantees on-time delivery of essential goods to clients.
J. Theor. Appl. Electron. Commer. Res. 2023, 18 144

6.3. Limitations and Further Research

Despite great research efforts, some limitations still need to be improved in further
studies. First, the conceptual model is tested in the field of omnichannel systems. It
is more beneficial to replicate this study in another specific online area, such as mobile
commerce and social commerce. Second, this study assessed the relationship between
perceived mental benefit, hedonic value, and electronic loyalty. The following studies can
increase research construct by adding utilitarian benefits and value. Finally, this study only
examines the general effect of anxiety on the relationship in the model; however, there are
different anxiety levels, so examining the moderating effects of anxiety levels is a concern.

Author Contributions: Conceptualization, B.T.K.; methodology, B.T.K.; software, T.T.H.; validation,

B.T.K.; formal analysis, T.T.H.; data curation, T.T.H.; writing—original draft preparation, B.T.K.;
writing—review and editing, B.T.K.; visualization, T.T.H. All authors have read and agreed to the
published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.
Data Availability Statement: Data available on request due to restrictions, e.g., privacy or ethical.
Conflicts of Interest: The authors declare no conflict of interest.

Appendix A Measurement Scales

Perceived Mental Benefits (PMB)
• I have had the pleasure of making my purchase using an omnichannel platform.
• When I purchase anything via an omnichannel system, it seems like I am engaging in
some social engagement.
• I may purchase the goods or service in private with an omnichannel system.
• I feel in charge when I make a purchase using an omnichannel platform.
Hedonic value (HV)
• Concerning my budget, omnichannel shopping is a source of immense joy.
• I cannot complain about the price of what I get out of omnichannel shopping.
• When compared to traditional malls, omnichannel shopping provides me with more
fun for my money.
• I find that omnichannel shopping is more convenient than traditional buying methods.
Electronic Loyalty (ELOY)
• My preference was communicated through an omnichannel platform, which was my
top choice.
• I found engaging with others by enjoying and spreading the word about an omnichan-
nel system exciting.
• Because of its superiority, however, my investment in an omnichannel platform has
not been wasted.
Customer anxiety (ANX)
• I’m worry that the goods will not match the description on the omnichannel systems.
• When I order new things from the omnichannel systems, I am stressed.
• I fear that the omnichannel systems may misuse my data.
• Waiting for the stuff to come from omnichannel systems is preventing me from getting
any rest.
• When I was waiting for the merchandise from omnichannel systems, I could not focus
on my job.
• After receiving the incorrect item or waiting too long for its delivery, I stopped caring
about omnichannel systems.
J. Theor. Appl. Electron. Commer. Res. 2023, 18 145

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