Int. Journal of Business Science and Applied Management, Volume 19, Issue 2, 2024

Connecting the Dots: Haptic Imagery's Sequential Impact

via Serial Mediation in Social Commerce Applications

Sin-Er Chong

School of Business and Economics, Universiti Putra Malaysia

Jalan Universiti 1, Serdang, 43400, Malaysia

Tel: +603-97697609

Email: sinerchong@gmail.com

Siew-Imm Ng

School of Business and Economics, Universiti Putra Malaysia

Jalan Universiti 1, Serdang, 43400, Malaysia

Tel: +603-97697573

Email: imm_ns@upm.edu.my

Norazlyn Kamal Basha

School of Business and Economics, Universiti Putra Malaysia

Jalan Universiti 1, Serdang, 43400, Malaysia

Tel: +603-97697675

Email: norazlyn@upm.edu.my

Xin-Jean Lim

Business School, Sun Yat-Sen University

Shenzhen Campus, 518107, Shenzhen, China

School of Business and Economics, Universiti Putra Malaysia

Jalan Universiti 1, Serdang, 43400, Malaysia

Tel: +603-97697675

Email: lim.xinjean@yahoo.com

Abstract

By integrating the Theory of Interactive Media Effects (TIME) and flow theory, this research

investigates the influence of haptic imagery on users' experiences and behavioural intentions within the

context of Social Commerce Applications (SCAs). This research delves into the mediating role of

immersion and the intricate serial mediation dynamics involving immersion and social media fatigue,

elucidating their role in the link between haptic imagery and users' continuance intention. A purposive

sampling technique was employed to gather data from 410 users of SCAs in Malaysia via offline and

online data collection methods. The collected data underwent analyses using partial least squares-

structural equation modelling (PLS-SEM). The findings revealed that haptic imagery was positively

associated with immersion, negatively associated with social media fatigue, and positively associated

with continuance intention among users of SCAs. Immersion emerges as a crucial mediator,

sequentially linking haptic imagery to social media fatigue and subsequently to continuance intention.

The study pioneers research into the influence of haptic imagery in the context of SCAs, contributing to

the underexplored research gaps in social commerce continuance literature. The study unravels the

intricate relationships between haptic imagery, user experiences, and behavioural intentions, shedding

light on the serial mediation mechanisms in shaping users' continuance intention. This pioneering

approach facilitates a novel understanding of technology-mediated user behaviour.

Keywords: haptic imagery, immersion, social media fatigue, continuance intention, social commerce,

theory of interactive media effects, flow theory

Int. Journal of Business Science and Applied Management / Business-and-Management.org

Acknowledgements: The authors would like to express their appreciation to the Research Management

Centre of Universiti Putra Malaysia (GPB/2021/9696700) for financially supporting this research.

and Applied Management under a Creative Commons Attribution 4.0 International Licence. Our

journal is an open access resource which means that all content is freely available without charge.

Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the

articles, or use them for any other lawful purpose, without asking prior permission from the publisher

or the author. For more information about this paper and our journal visit our website.

Submitted: 2024-03-25 / Accepted: 2024-07-07 / Published: 2024-07-23

Sin-Er Chong, Siew-Imm Ng, Norazlyn Kamal Basha and Xin-Jean Lim

1 INTRODUCTION

Social commerce applications (SCAs), at the intersection of social media and e-commerce, have

witnessed substantial growth and transformation in recent years (Chiu et al., 2022). Amidst the surge of

advanced technology and the prevalence of mobile gadgets, the landscape of online commerce has

rapidly moved from computers to mobile applications. This shift has energized the growth of mobile

commerce, leading numerous internet firms to pivot toward SCAs in response to the growing impact of

social media (Wang et al., 2023). The impact of social media is profound, extending across various

domains such as supply chains and logistics (Papagiannidis et al., 2019), in addition to its significant

role in social commerce. The rapid rise of SCAs in Southeast Asia, particularly in Malaysia, is

exemplified by TikTok Shop's emergence as a competitive force challenging established e-commerce

players like Shopee and Lazada (Tech Wire Asia, 2023). Given the challenges encountered by e-

commerce players, it is imperative for SCAs to proactively strategize to ensure sustained user

continuance. From a business standpoint, comprehending ways to incentivize consumers' desire to use

SCA represents a crucial strategy to gain a competitive edge and unlock economic potential (Liu et al.,

2019).

The surge in online shopping driven by the COVID-19 pandemic has spurred researchers to

investigate online consumer behaviours, aiming to provide insights for retailers seeking to attract a

larger consumer base and elevate their sales strategies (Tan et al., 2023). Moreover, the continuance

intention to utilize SCAs remains understudied even though scholars have been emphasizing the point

that the sustained usage intention in social commerce serves as a strong indicator of social commerce

sustainability (Hu et al., 2022; Osatuyi & Qin, 2018). Chiu et al. (2022) also emphasized the need for

further research to explore the factors driving continuance intention using an integrated framework.

Hence, there arises a necessity to investigate various factors influencing consumers' continuance

intention in SCAs. In this setting, integrating interactive elements within these platforms has

revolutionized consumer behaviour, offering novel avenues for engagement and transactions (Nandi et

al., 2021). The role of sensory experiences, particularly haptics, has emerged as a pivotal determinant

shaping user perceptions and interactions within SCAs (Racat & Plotkina, 2023). Haptic imagery,

characterized by its tactile and sensory attributes, goes beyond the visual realm, offering users an

immersive and tangible experience (Huang & Liao, 2017). It refers to the mental visualization of touch.

Haptic technologies represent pioneering sensory tools capable of enhancing consumers' online

shopping journeys. For instance, haptic technologies in fashion and luxury redefine online tactile

experiences, employing computational systems to emulate the sense of touch (Ornati & Kalbaska,

2022).

These innovational technologies address the lack of physical interaction in online shopping by

integrating haptically enriched content, virtual prototyping, and multisensory brand promotions in

mixed or virtual reality. By integrating haptic data across the value chain, from design to

merchandising, they add valuable layers to online commerce (Silva et al., 2021). One application

involves integrating haptic feedback to simulate touch-enabled product exploration (Hadi &

Valenzuela, 2020). For instance, in an electronics-focused SCA, users can virtually interact with

gadgets, feeling the textures, buttons, and features through haptic feedback. This immersive experience

not only allows users to explore products in detail but also increases their confidence in making

informed purchase decisions. Another application lies in incorporating haptic feedback to facilitate

sensory-enhanced communication (Racat & Plotkina, 2023). Through haptic-enabled messaging

features, users can convey emotions and sensations beyond text, fostering richer interpersonal

interactions and strengthening bonds. These examples highlight how haptic imagery can revolutionize

the SCA landscape, offering users engaging and sensory-rich experiences while navigating and

interacting within the platform.

Yet, the impact of integrating haptics on user behaviour during SCA usage remains largely

unexplored (Racat & Plotkina, 2023). While numerous studies delve into purchase behavioural

intentions (Tian & Lee, 2022; Vazquez et al., 2023; Wang & Huang, 2023), there remains a scarcity of

research conducted specifically within the context of sustained usage within SCAs. A research gap

persists when it comes to elucidating how haptic imagery can effectively stimulate user engagement

and contribute to sustained intention within SCAs. Drawing on Park and Ha's (2021) argument that

consumer engagement is a pivotal element for brand loyalty, our research emphasizes the significance

of enhancing user involvement in the context of SCAs. To achieve this, one potential avenue is to

augment user immersion, as this has been identified as a key factor influencing continued app usage in

this research.

Beyond spotlighting the direct impact of haptic imagery on continuance intention, understanding

the potential enhancement of immersion via haptic imagery and the consequential alleviation of social

Int. Journal of Business Science and Applied Management / Business-and-Management.org

media fatigue have emerged as crucial considerations. In the context of SCAs, the coalescence of

immersion and social media fatigue represent pivotal factors shaping user experiences. Immersion,

renowned for its capacity to engage users through multisensory stimuli, catalyzes enriched interactions

(Huang & Liao, 2017; Tian & Lee, 2022). Based on flow theory, an earlier study exposes significant

psychological processes, like immersion, through which the communication style impacts customer

behaviour in live-streaming commerce (Liao et al., 2023). However, the looming challenge of social

media fatigue poses a potential impediment, impacting user retention and sustained engagement within

these platforms (Sunil et al., 2022). Researchers have also discovered that immersive experiences result

from various stimuli (Bao & Yang, 2022; Zhou, 2020), can mitigate social media fatigue, a factor that

exhibits a correlation with discontinuance intention (Lin et al., 2020). These findings recommend the

notion of a serial mediation effect, wherein immersion and social media fatigue sequentially mediate

continuance intention, stemming from the influence of haptic imagery. This research pioneers the

investigation into the mediating role of immersion and the sequential mediation of immersion coupled

with social media fatigue, marking a novel exploration within SCA studies.

To address the gaps aforementioned, this study aims to achieve several objectives. Firstly,

leveraging the Theory of Interactive Media Effects (TIME) by Sundar et al. (2015), the research seeks

to examine how haptic imagery influences immersion, social media fatigue, and continuance intention.

TIME posits that the features of a communication medium, alongside the source and content of

messages, significantly influence user experience and interaction. Specifically, the characteristics of the

media interface or its affordances act as cues that trigger various psychological responses, leading to

cognitive or affective reactions from users (Ivanov et al., 2023). Given this framework, TIME is

particularly suited for this study as it provides a comprehensive understanding of how interactive

elements, such as haptic imagery, enhance user experiences and shape behaviours within SCAs.

Secondly, the study aims to explore the effects of immersion on social media fatigue and continuance

intention as well as the mediating role of immersion in this context based on flow theory. Flow theory,

pioneered by Csikszentmihalyi (1975), is highly relevant to understanding the underlying mechanism

of immersion. It is particularly well-suited to explaining immersion in this study because it provides a

framework for understanding the psychological processes underlying user experience. It posits that

individuals experience a state of optimal psychological functioning when they are fully absorbed in an

activity. In the context of SCAs, immersion can be seen as a manifestation of flow, where users become

deeply engaged in the online shopping experience, leading to enhanced continuance intention.

Lastly, this study attempts to examine the serially mediated relationship of immersion and social

media fatigue between haptic imagery and continuance intention. This investigation aims to uncover

the underlying mechanisms inherent in this unique model from fresh vantage points by integrating

TIME and flow theory, representing the inaugural endeavour to integrate the two theories within the

realm of SCAs. This effort also responds to the call by Chiu et al. (2022) to examine the factors

affecting continuance intention from an integrated perspective. By examining the interplay between

media features and user responses, the integration of TIME and flow theory helps elucidate the

mechanisms through which haptic imagery fosters user immersion, reduces social media fatigue and

ultimately influences continuance intention. Through a deeper exploration of these interconnected

factors, this study not only contributes to the theoretical foundations of sensory marketing and user

behaviour within social commerce but also offers practical insights for platform design and marketing

strategies. Understanding how haptic imagery engenders continued user engagement and mitigates

potential fatigue in SCAs involves substantial implications for businesses, marketers, and platform

developers seeking to optimize user experiences and sustain user participation.

2. LITERATURE REVIEW AND THEORETICAL BACKGROUND

2.1 Overview of Social Commerce Continuance Research

Studies into social commerce commenced in the previous decade, witnessing a significant surge in

research articles as technological advances unfolded (Zhao et al., 2023). Researchers have placed

significant emphasis on understanding factors that drive social commerce behavioural intentions such

as purchase intention (Akram et al., 2021; Busalim et al., 2023; Chen et al., 2018; Doha et al., 2019;

Lin & Wang, 2022; Liu et al., 2016; Molinillo et al., 2021), social commerce intention (Cheng et al.,

2019; Liang et al., 2011; Molinillo et al., 2018; Tuncer, 2021; Zhang et al., 2014), and positive

electronic word-of-mouth intention (Busalim et al., 2023; Herrando et al., 2018; Mikalef et al., 2017;

Molinillo et al., 2020, 2021). However, the continuance intention of consumers within the social

commerce context has been relatively overlooked by researchers (Osatuyi and Qin, 2018). On top of

that, researchers have highlighted the importance of users' continuance intention as a crucial indicator

of success and sustainability in the social commerce landscape (Hu et al., 2022). Consequently, it is

Sin-Er Chong, Siew-Imm Ng, Norazlyn Kamal Basha and Xin-Jean Lim

imperative to explore the underlying factors that drive users' continuance intention to engage with

social commerce platforms (Chiu et al., 2022).

As shown in Table 1, we conducted a review of past and current research within the context of

social commerce continuance. From there, we noticed four significant research gaps that this research

attempted to address. First, numerous studies have mostly employed the theoretical lens of social-based

theories such as Social Support Theory, motivation-based theories, the Expectation Confirmation

Model and the Stimulus-Organism-Response Model. Hence, a notable gap remains in leveraging

theoretical frameworks from a technological perspective to elucidate the factors influencing users'

sustained engagement with these platforms. Recognizing the vital role of technology in delivering

optimal user experiences in the context of social commerce, as argued by Leong et al. (2023),

employing a technology-based theoretical framework has become imperative to comprehensively

understand the factors driving users' continuance intention on these platforms. Therefore, the current

study employs TIME as the primary underpinning theory as it explains how interactive technological

media actively engages users and influences their experiences and behaviours.

Second, past studies have predominantly investigated social-related factors, such as social support,

social gratification, and social interaction. Additionally, researchers have explored informational-

related factors, including informational support, information privacy, information quality, information

usefulness and adoption, and informational influence. Furthermore, general technological-related

factors, such as website quality, perceived usefulness, perceived ease of use, service quality, and

customization have been investigated. However, specific technological factors have been overlooked,

especially interactive-related factors like haptic imagery. Haptic imagery involves integrating tactile

sensations into digital interfaces, allowing users to virtually feel and interact with on-screen elements

as if they were physical objects. By providing touch-based feedback, this technology enhances the

sense of realism and immersion in digital experiences, enabling users to perceive textures, vibrations,

and physical sensations when interacting with virtual elements (Ivanov et al., 2023). Recently, Chong

et al. (2024) emphasized the need to explore the impact of haptic imagery, as a technological factor, on

users' immersive experience and continuance intention. Hence, there persists a gap to address as

researchers have highlighted the relevance and influence of interactive technological factors on social

commerce behavioural intention (Lim et al., 2022). Despite the effective integration of these

technologies in mobile apps (Racat & Plotkina, 2023), their effectiveness and relevance in social

commerce studies remain relatively underexplored. Addressing this gap would benefit SCAs and

revolutionize the broader landscape of interactive technologies, influencing user engagement and

interaction in various online platforms.

Third, while scholars have generally focused on factors that can positively drive continuance

intention in social commerce, an aspect that has been neglected is the investigation of factors that can

negatively influence user experience and continuance intention. Notably, only Rashid et al. (2017)

examined the negative effect of perceived risk on perceived enjoyment, attitude towards use, and social

commerce continuance intention. It is evident that in the context of social commerce continuance

research, factors that can drive negative impact have been largely overlooked. To address this research

gap, we identified social media fatigue as a relevant yet understudied factor in the social commerce

context. Social media fatigue, also known as social media exhaustion, is a subjective perception of

tiredness from social media use, widely believed to drive discontinuous usage intention within social

media contexts (Fu et al., 2020; Lin et al., 2020). Given the integration of SCAs within social media

platforms (Leong et al., 2023), examining the impact of social media fatigue on continuance intention

becomes crucial. Yu et al. (2024) have also pointed out that there is only limited research conducted on

how the antecedents of social media participation affect social commerce continuous usage intention.

Hence, we attempted to explore the impact of social media fatigue on SCAs’ continuance intention.

Fourth, previous studies have often overlooked the underlying mechanisms through which

technological factors influence user behaviour in social commerce (Ornati and Kalbaska, 2022). The

existing research has primarily centered on investigating the direct relationship between antecedents

and social commerce intentions, disregarding the potential enhancement in predictive capacity if the

underlying mechanisms guiding continuance intention were considered (Tian and Lee, 2022; Hu et al.,

2022; Chong et al., 2023). While researchers have widely examined the mediating role of satisfaction,

the mediating role of immersion has been understudied in the context of social commerce continuance

research. Based on flow theory, immersion (also known as flow experience) has been found to

significantly mediate the effect of external stimuli on social commerce intention (Tuncer, 2021).

Hence, there is a distinct need to uncover the underlying mediating role of immersion between the

antecedents and continuance intention to enhance our understanding of the mechanisms contributing to

the intention to continue using SCAs.

Note: The evidence from the relevant literature is presented in Table 1.

Int. Journal of Business Science and Applied Management / Business-and-Management.org

Table 1: Overview of social commerce continuance research

Authors &

Timeline

Independent Variables Mediator

Dependent

Variables

Theory

Liang et al.

(2011)

Social support (Informational

and emotional support), and

website quality (system and

service quality)

Relationship quality

(trust, satisfaction, and

commitment)

Social commerce

intention and

continuance

intention

Social Support

Theory

Hajli et al.

(2015)

Perceived value, social

support, subjective norms,

attitude, perceived behavioural

control

Continuance

participation

intention and

behaviour

Theory of Planned

Behaviour and

Social

Support Theory

Hew et al.

(2016)

Concern for social media

information privacy, perceived

usefulness, and confirmation

Continuance intention

to use mobile social

commerce and

satisfaction

Brand loyalty

Expectation

Confirmation

Model

Rashid et al.

(2017)

Perceived trust, perceived

usefulness, perceived ease of

use, perceived

enjoyment, and perceived risk

Attitude towards use

Continuance

intention

Technology

Acceptance

Model

Osatuyi & Qin

(2018)

Social, hedonic, and utilitarian

gratifications

Satisfaction

Continuance

intention and

addictive use

Uses and

Gratifications

Theory and

Motivational

Models

Osatuyi & Turel

(2018)

Subjective and collective norm

Continuance use

intention

Social Identity

Theory and Social

Impact Theory

Osatuyi et al.

(2020)

Confirmation

Perceived usefulness

and satisfaction

Continuance

intention

Expectation

Confirmation

Theory

Molinillo et al.

(2021)

Information quality, service

quality,

rewards and recognition, and

customization

Perceived value

Repurchase

intention,

positive eWOM

intention, and

customer

engagement

behaviour

intention

Stimulus-

Organism-

Response Model

Chiu et al.

(2022)

Confirmation, argument

quality, and source credibility

Satisfaction,

information

usefulness, and

information adoption

Continuance

intention

Expectation

Confirmation

Model and

Information

Adoption Model

Hu et al. (2022)

Source credibility and social

interaction

Perceived enjoyment,

perceived usefulness,

informational and

emotional social

support

Continued social

commerce intention

Motivation

Theory and Social

Support Theory

Qu et al. (2023)

Perceived ease of use,

perceived usefulness, and

social interactivity

Utilitarian and hedonic

shopping value

User stickiness

Stimulus-

Organism-

Response Model

Yu et al. (2024)

Informational

influence factor, interpersonal

trust,

perceptions of friends’

knowledge

Confirmation,

perceived

usefulness, and

satisfaction

Continuance

intention

Expectation

Confirmation

Model

Source: Authors’ compilation

Sin-Er Chong, Siew-Imm Ng, Norazlyn Kamal Basha and Xin-Jean Lim

2.2 Theory of Interactive Media Effects (TIME) and Flow Theory

To unravel the role of haptic imagery in this context, we leveraged a comprehensive research

framework by integrating the perspectives of TIME into the domain of flow theory. TIME, introduced

by Sundar et al. (2015), serves as a fundamental theoretical framework shaping research endeavours

aimed at comprehending the interplay between interactive media and user behaviour, specifically

focusing on how particular technological aspects prompt shifts in human psychology and behaviours. It

goes beyond the traditional notion of media being solely channels for communication. Instead, it

highlights how interactive media actively engages users and influences their experiences and

behaviours. In essence, the attributes embedded within the media interface act as cues triggering

diverse psychological responses in consumers, encompassing both cognitive and affective reactions

(Ivanov et al., 2023). TIME's profound emphasis on interactivity resonates powerfully with our

exploration of the effects of haptic imagery within SCAs. It illuminates a transformative landscape

where digital interfaces cease to be mere channels and instead become dynamic tools shaping user

experiences (Sundar et al., 2015). Just as TIME redefines the notion of media by accentuating

interactivity's pivotal role, our study on haptic imagery in social commerce ventures beyond

conventional paradigms. This synergy between TIME's focus on interactive media effects and our

inquiry into haptic imagery's impact fortifies our quest to decipher how sensory stimulation shapes user

behaviour and perceptions in the vibrant context of SCAs.

TIME also posits that the nature of user engagement hinges on the mediator involved in a given

interaction, emphasizing how various predictors influence user engagement and subsequent outcome

behaviours (Sundar et al., 2015). Drawing on TIME, Lee et al. (2020) discovered that telepresence,

signifying the immersion state, mediated the connection between media attributes and favourable

consumer attitudes, subsequently influencing the adoption intention of AR-based mobile applications.

It is essential to recognize the substantial intermediary function of consumers’ immersive experiences.

For instance, Javornik (2016) agreed that users' psychological reactions stemming from affordances can

be manifested as immersive experiences, subsequently influencing emotional, cognitive, and

behavioural responses toward these applications. TIME suggests that the way individuals respond to

media is impacted by the technological aspects of the source, specifically through users' immersive

experiences that represent user absorption. Hence, our research delves into the concept of immersion as

a mediator—a psychological state characterized by deep involvement and absorption within an activity

or environment. This mediator, supported by flow theory, serves as a crucial link between haptic

imagery and user intentions, reflecting TIME's assertion that user engagement depends on the mediator

present during interactions.

Flow theory, grounded in psychology, elucidates the concept of immersion as a mental state

characterized by intense focus and complete engagement in an activity. This theory, proposed by

Csikszentmihalyi (1975), explores optimal human experiences that foster a state of heightened

concentration and enjoyment. Javornik (2016) believed that immersion is impactful as it reflects the

depth of the involvement and absorption users feel during interactions. For instance, Zhou (2020)

demonstrated that immersion acts as a mediator between stimuli and outcomes like social purchase and

sharing intentions within social commerce environments. Bao and Yang (2022) expanded on this and

highlighted how an immersive experience similarly mediates the relationship between stimuli and the

urge to impulsively buy during online shopping. Additionally, Liao et al. (2023) shed light on the

mediating role of immersion between communication styles and user behavioural outcomes,

particularly in the context of purchase intention during live-streaming shopping events. Lin et al.

(2020) contributed to this discourse by highlighting the role of flow experience in mitigating social

media fatigue and discontinuance intentions, hinting at the sequential mediation via immersion.

The integration of TIME and flow theory offers an apt theoretical framework for this study,

allowing for an exploration of haptic imagery as a predictive factor. This framework models how haptic

imagery influences consumers' experiences and perceptions within SCAs, consequently shaping their

intentions to continue engaging with these platforms. The aforementioned findings collectively

emphasize the centrality of immersion as a mediator between various stimuli and consequential

consumer behaviours, aligning with our study's focus on understanding how immersion interacts with

haptic imagery in shaping continuance intention within SCAs. This includes examining its effects on

social media fatigue in delineating the sequential mediation pathway between haptic imagery and

continuance intention. This aims to bridge the research gap by emphasizing its role in shaping user

experiences within SCAs, aligning with TIME's overarching principles regarding user engagement in

interactive media contexts.

Int. Journal of Business Science and Applied Management / Business-and-Management.org

3. HYPOTHESIS DEVELOPMENT AND RESEARCH FRAMEWORK

3.1 Effects of Haptic Imagery

Deciphering individuals' tactile preferences in everyday situations has been a focal point in the

realms of haptic science, engineering, and marketing (Brakus et al., 2009; Ujitoko et al., 2022). Haptic

technologies are advanced computational applications crafted to mimic the sense of touch artificially

because touch plays a profound role in shaping our emotions, thoughts, and actions, even influencing

decisions like purchasing apparel online (Ornati & Kalbaska, 2022). In contrast to conventional visual

and auditory cues, haptic imagery introduces a tactile component to the user interface, fostering a

multisensory engagement that emulates the sense of touch (Goncalves et al., 2020). Scholars have

found that advanced virtual try-on apps incorporating haptic imagery features have the potential to

induce user immersion (Ivanov et al., 2023). Commonly defined as the simulation of tactile experiences

in a digital environment, haptic imagery holds significance in improving the overall user experience by

delivering a heightened level of immersion and a more lifelike interaction (Huang & Liao, 2017).

Introducing haptic stimuli into a virtual environment is expected to yield a more immersive, cohesive,

and credible experience, potentially elevating the sense of presence even further (Goncalves et al.,

2020).

It is postulated that haptic imagery, through its integration of tactile feedback and immersive

experiences, will alleviate social media fatigue. Research in smartphone settings has demonstrated that

haptic interactions, such as tilting, swiping, and shaking during mobile app experiences, contribute to

heightened positive affect, increased engagement, and strengthened purchase intentions (Mulcahy &

Riedel, 2018; Shi & Kalyanam, 2018). Additionally, the presence of haptic feedback in the interface

has been associated with a reduction in social media exhaustion by enhancing attitude and experiential

evaluations of the overall interaction (Hadi & Valenzuela, 2020). Incorporating touch in haptic

technology can enhance perceived closeness, as seen in devices enabling remote hugs and tactile

communication, offering positive online user interactions (Petit et al., 2019). Thus, the incorporation of

haptic imagery could potentially mitigate social media fatigue, offering users a more enjoyable

experience, positively influencing their interaction with SCAs.

In line with the TIME by Sundar et al. (2015), haptic features as an interactive tool, with the

potential to elevate social presence and stimulate interaction, fostering prolonged usage of the media.

Moreover, Ivanov et al. (2023) demonstrated that the integration of haptic imagery in online shopping

apps enhances users' performance expectancy, fostering perceptions of convenience and effectiveness,

ultimately instilling confidence in their app usage decisions. These features empower self-discovery, a

crucial factor for the sustained usage by e-shoppers in the future (Huang & Liao, 2017). Technologies

that enable sensory experiences, like haptic feedback, may contribute to sustained usage by fostering

psychological comfort, trust, positive attitudes, and heightened purchase intention (Racat & Plotkina,

2023). Logically, as users are prompted to integrate the authenticity of the pleasurable experience into

their credibility evaluations, they are more likely to continue using the application. Therefore, we

propose the following hypotheses:

H1. Haptic imagery is positively associated with immersion.

H2. Haptic imagery is negatively associated with social media fatigue.

H3. Haptic imagery is positively associated with continuance intention.

3.2 Effects of Immersion and Social Media Fatigue

Drawing on flow theory by Csikszentmihalyi (1975), immersion can be conceptualized as the state

of deep concentration and engagement experienced during a flow state. It occurs when individuals are

fully absorbed in an activity, experiencing a sense of control, focus, and enjoyment. In the context of

haptic imagery in e-shopping, immersion represents the user's complete involvement and absorption in

the interactive experience (Huang & Liao, 2017). Theoretically, as users become immersed in the

virtual environment, the heightened engagement can divert attention from the potential fatigue

associated with excessive social media use because, when immersion occurs, other negative feelings

seem to disappear (Hoffman & Novak, 1996). Empirically, this immersive experience, acting as a

positive psychological state, counteracts the negative effects of social media fatigue (Lin et al., 2020).

Drawing on the insights from the literature, immersion, often conceptualized as the flow

experience, has emerged as a crucial factor in influencing continuance intention. Based on the findings

of Al-Maghrabi et al. (2011), perceived enjoyment has been found to be positively related to increasing

customer continuance intention in the context of online shopping. This observation carries significant

implications for the proposed hypothesis, as it is essential to note that perceived enjoyment is one of the

key determinants of immersion based on flow theory (Csikszentmihalyi, 1975, 1990). Similarly, Tian

Sin-Er Chong, Siew-Imm Ng, Norazlyn Kamal Basha and Xin-Jean Lim

and Lee (2022) pointed out that individuals who experience immersive experiences are more likely to

engage in activities repeatedly, fostering continuous purchase intention on an SCA. Furthermore,

Rodríguez-Ardura and Meseguer-Artola (2018) found that flow experience not only directly increases

users' engagement with an SCA but also enhances the platform usage intention. This heightened

engagement is attributed to the fact that flow demotivates discontinuance decisions (Lin et al., 2020).

Herrando et al. (2019) pointed out that flow in social commerce also fosters emotional and behavioural

loyalty, driving intentions to return and repurchase. Hence, we propose the following hypotheses:

H4. Immersion is negatively associated with social media fatigue.

H5. Immersion is positively associated with continuance intention.

In the Stressor-Strain-Outcome framework, prolonged exposure to stressors, such as excessive use

and information overload in social media, can lead to strain outcomes (Zhang et al., 2016). Extended

exposure to constant connectivity and overwhelming content can induce psychological and emotional

strain, marked by exhaustion. Social media fatigue, as a manifestation of strain, results in negative

feelings and increased discontinuance intentions (Lin et al., 2020). These detrimental effects contribute

to a decline in users' overall satisfaction and positive experiences, subsequently diminishing their

intention to continue using social media platforms (Fu et al., 2020). Accordingly, we propose:

H6. Social media fatigue is negatively associated with continuance intention.

3.3 Mediating Effects of Immersion

According to flow theory, individuals immersed in an activity lose self-awareness and become

engrossed in the moment, leading to heightened enjoyment and focus (Csikszentmihalyi, 1975). As

individuals experience this state, their concentration intensifies, enabling them to navigate through

challenges effortlessly. Applying this theoretical perspective to the realm of sensory stimulus, haptic

imagery can trigger an immersive state, fostering an absorbing and enjoyable user experience

(Goncalves et al., 2020). Aligning with TIME by Sundar et al. (2015), the immersive quality induced

by sensory cues may divert users' attention from potential stressors and disruptions in the social media

environment through absorbed engagement, consequently reducing social media fatigue. Empirically,

the immersive quality resulting from haptic imagery features contributes to users perceiving the

experience as more authentic, which, in turn, positively impacts their evaluations of credibility (Ivanov

et al., 2023). This study aligns with the broader understanding that immersive experiences contribute to

sustained user participation and favourable perceptions, shaping the users' commitment to ongoing

interaction with the platform (Rodríguez-Ardura & Meseguer-Artola, 2018).

The literature consistently supports the contention that immersion acts as the pivotal link between

stimuli and consequential outcomes. For instance, Zhou (2020) discovered that the immersive

experience serves as the foundational mechanism mediating the relationship between stimuli, such as

social interaction, and ensuing responses, exemplified by social purchase intention and social sharing

intention. Ming et al. (2021) further discovered that this experience acts as a mediator between stimuli

and impulsive buying behaviour in live-streaming commerce. Liao et al. (2023) also found that

immersion plays a mediating role between communication style and customer behaviour in the context

of live-shopping. The body of evidence aligns cohesively to emphasize the fact that immersion serves

as the underlying mechanism orchestrating the relationship between stimuli and outcomes in the user

experience, substantiating its pivotal role in the proposed theoretical framework.

Additionally, Huang and Liao (2017) argued that haptic imagery could potentially induce positive

psychological states, fostering immersive experiences. Building on this, Lin et al. (2020) demonstrated

that immersive experiences, particularly in the context of social platforms, contribute to a reduction in

user fatigue, while this reduced fatigue, as uncovered by Lin et al. (2020), plays an effective role in

mitigating discontinuance intention. Consequently, the findings suggest a sequential impact of haptic

imagery, immersive experiences, reduced fatigue, and ultimately increased continuance intention,

underscoring the interplay between sensory imagery and a series of user experience outcomes in the

social platform landscape. Summarizing the above arguments, we hypothesize that:

H7. Immersion mediates the relationship between haptic imagery and social media fatigue.

H8. Immersion mediates the relationship between haptic imagery and continuance intention.

H9. Immersion and social media fatigue sequentially mediate the relationship between haptic

imagery and continuance intention.

By integrating TIME and flow theory, the proposed research framework is depicted in Figure 1.

Other than the direct impacts of haptic imagery on immersion, social media fatigue, and continuance

Int. Journal of Business Science and Applied Management / Business-and-Management.org

intention, the figure also depicts the mediating effects of immersion, along with the serial mediation

involving social media fatigue. In line with previous literature highlighting the influence of age,

ethnicity, and education as differentiating factors in behavioural intentions (Shiau et al., 2024), we

controlled for these three demographic variables in our study.

Figure 1: Research framework

Source: Authors’ own work

4. METHODOLOGY

4.1 Measurement Items

All items used for this study were drawn from established and validated scales from the existing

literature and adapted to the context of SCA as shown in Table 2. This approach was undertaken to

ensure the rigour of the measurements and the reliability of the scale employed in the research. The

utilization of both five-point and seven-point Likert scales was implemented as a procedural strategy to

minimize common method bias by reducing response set bias and enhancing the precision of the

measurements across diverse constructs (Jordan & Troth, 2020). The items about haptic imagery were

adapted from the works of Brakus et al. (2009) and Huang & Liao (2017); the items about immersion

were adapted from Liao et al. (2023); the items on social media fatigue were adapted from Fu et al.

(2020); the items on continuance intention were adapted from Hu et al. (2022). To improve the logical

coherence and comprehensibility of the questionnaire, we initiated a pre-test involving three marketing

scholars and three marketing practitioners. Subsequently, a pilot study was conducted, engaging 30

SCA users. These steps are to validate the effectiveness of the survey instrument before commencing

the main data collection (Liu et al., 2019).

Table 2: Measurement items of constructs and results of the measurement model assessment

Construct Item Source

Outer

α CR (ρ

)

CR (ρ

)

AVE

Haptic

Imagery

HI1: I find this app interesting in

terms of my haptic sense as it

creates a realistic feeling of

touching products virtually.

Brakus et al.

(2009);

Huang &

Liao (2017)

0.880

0.824 0.830 0.895 0.739

HI2: I find this app handy as I

experience a lifelike sense of touch

while navigating the app.

0.835

HI3: I can freely adjust the size of

the product image on this app by

touching the screen.

0.864

Immersion

IM1: I was deeply engrossed when

using this app.

Liao et al.

(2023)

0.864 0.883 0.884 0.919 0.740

Sin-Er Chong, Siew-Imm Ng, Norazlyn Kamal Basha and Xin-Jean Lim

IM2: My attention was focused

when using this app.

0.866

IM3: While browsing this app, I

feel that time passes quickly.

0.838

IM4: When browsing this app, I

often focus too much and forget

about other things I have to do.

0.873

Social Media

Fatigue

SMF1: I feel tired from this app’s

activities.

Fu et al.

(2020)

0.920

0.939 0.939 0.956 0.844

SMF2: I feel drained from activities

that require me to use the app.

0.934

SMF3: Using this app is a strain for

me.

0.916

SMF4: I feel burned out from this

app’s activities.

0.905

Continuance

Intention

CI1: In the future, I am willing to

provide my experiences and

suggestions when my friends on

this app want my advice on buying

something.

Hu et al.

(2022)

0.859

0.903 0.904 0.928 0.720

CI2: I am willing to continue

sharing my own shopping

experience with my friends on this

app.

0.872

CI3: In the future, I am willing to

recommend products that are worth

buying to my friends on this app.

0.849

CI4: I will consider the shopping

experiences of my friends on this

app when I want to shop.

0.828

CI5: I am willing to continue

buying the products recommended

by my friends on this app.

0.836

Notes: Respondents were instructed to answer based on their perceptions of their favourite SCA.

Source: Authors’ own work

4.2 Data Collection Method and Descriptive Statistics

This research used purposive sampling to invite Malaysian participants with a recent transaction

history on an SCA within the past six months, ensuring a relevant sample (Lim et al., 2019). The

utilization of a dual-source data collection approach, combining face-to-face surveys and online

surveys, is strategically designed to enhance the robustness and inclusivity of our data by

accommodating diverse participant preferences and ensuring comprehensive coverage across various

demographic segments (Ji et al., 2023). As an appreciation for their participation, the participants

received a voucher valued at RM10, approximately USD 2.15 after completing the questionnaire.

The selection of Malaysia as the research context for this study is justified by several

considerations. Firstly, Malaysia represents a dynamic and growing market for SCAs, making it an

ideal setting to explore user behaviours and experiences in this evolving digital landscape (Data

Reportal, 2023). Additionally, Malaysia's diverse population provides a rich pool of participants,

allowing for a more comprehensive examination of the impact of haptic imagery on user experience

and continuance intention. Furthermore, the country's technological infrastructure and widespread use

of mobile devices make it a relevant context for investigating the role of haptic imagery in the context

of SCAs. Lastly, the decision to focus on Malaysia aligns with the global trend of increasing

digitalization and activities of SCAs, making the findings of this research potentially applicable to

broader contexts beyond the local setting (Data Reportal, 2023). It is anticipated that the findings of

this research will contribute not only to the understanding of Malaysian consumers but also offer

transferable insights that can benefit other Asian countries experiencing similar technological

transformations.

After eliminating cases exhibiting straight-lining, we acquired a total of 410 valid questionnaires.

Consistent with the guidelines suggested by Faul et al. (2009), we argue that this sample size is

sufficient for rigorous statistical analysis as the minimum sample size calculated is 98 based on the

current model. The demographic profile of the participants presented in Table 3 exhibits a diverse and

representative sample. 54.15% identified as male and 45.85% as female. Ethnicity-wise, the participant

composition in this study demonstrates a broad spectrum of representation. 38.29% identified as Malay,

Int. Journal of Business Science and Applied Management / Business-and-Management.org

35.37% as Chinese, 19.27% as Indian, and 7.07% as belonging to other ethnic groups. The age

distribution revealed a majority in the 26-30 age group (37.80%), with a gradual decline in

participation as age increased. Education levels varied, with 60.49% holding an undergraduate degree,

and 11.22% possessing a postgraduate degree. Regarding monthly income, a significant portion

(37.56%) fell within the RM2001-RM4000 range. The descriptive statistics on SCA usage reveal a

diverse landscape of preferences and activities among respondents. Instagram emerges as the

frontrunner, capturing the favour of 16.83% of users, closely pursued by TikTok/DouYin at 15.85%.

WhatsApp and Facebook also hold substantial popularity, securing 15.61% and 13.66%, respectively.

Table 3: Demographic profile (n=410)

Demographics

Category

Frequency

Percent (%)

Gender

Male

222

54.15

Female

188

45.85

Ethnicity

Malay

157

38.29

Chinese

145

35.37

Indian

19.27

Others

7.07

Age

25 years old and below

16.83

26-30 years old

155

37.80

31-35 years old

23.66

36-40 years old

10.24

41-45 years old

8.29

46 years old and above

3.17

Highest Level of Education

Secondary or below

10.00

Diploma

18.29

Undergraduate Degree

248

60.49

Postgraduate Degree

11.22

Monthly Income

Less than RM2000

14.39

RM2001-RM4000

154

37.56

RM4001-RM6000

125

30.49

RM6001-RM8000

10.98

RM8001-RM10000

3.17

Above RM10000

3.41

Favourite SC app

Instagram

16.83

TikTok/DouYin

15.85

15.61

Facebook

13.66

XiaoHongShu

13.17

9.76

WeChat

6.83

Twitter

4.39

YouTube

3.90

Source: Authors’ own work

5. DATA ANALYSIS AND RESULTS

This research employs a variance-based Structural Equation Modelling (SEM) approach,

specifically Partial Least Squares SEM (PLS-SEM), instead of Covariance-Based SEM (CB-SEM).

PLS-SEM is recognized as a variance-based SEM method, emphasizing the utilization of all indicators'

variances to estimate model relationships, with a particular focus on predicting dependent variables

(Hair et al., 2021). In contrast, CB-SEM primarily explains the covariation between indicators and does

not prioritize the prediction of dependent variables. CB-SEM is typically employed for theory testing

and confirmation, which does not align with the main objective of this study. Given that the primary

objective of this study is theory development through the integration of the TIME and flow theory, the

analysis is oriented towards testing a theoretical framework from a prediction perspective. Hair et al.

(2021) advocated the use of variance-based SEM, particularly PLS-SEM, in cases where researchers

aim to explore theoretical extensions of established theories, which aligns with the exploratory nature

of this study focused on theory development. Therefore, variance-based SEM is deemed appropriate for

this research.

PLS-SEM was chosen as the analytical method due to its suitability in analyzing complex

relationships within theoretical models, with a focus on prediction. PLS-SEM is recognized as a widely

acclaimed multivariate data analysis method (Cheah et al., 2023). Moreover, PLS-SEM software, such

Sin-Er Chong, Siew-Imm Ng, Norazlyn Kamal Basha and Xin-Jean Lim

as SmartPLS 4 used in this research, offers advanced capabilities, including the ability to conduct serial

mediation analysis, aligning with the research objective of the current study (Cheah et al., 2023). It also

has the latest PLSpredict feature, which can effectively gauge the predictive relevance of the model

(Shmueli et al., 2019). PLS-SEM provides robust capabilities for handling data without depending on

assumptions about distribution, making it especially advantageous for social science research, where

non-normal data distribution is common (Hair et al., 2021). In this study, the result of the multivariate

normality test revealed a Mardia’s multivariate kurtosis coefficient of 26.108 (p <0.001), surpassing the

threshold limit of 20, indicating non-normal data distribution (Kline, 2023). Given the advice from

scholars and the compatibility of PLS-SEM's features with the goals of this research, PLS-SEM was

selected for analysis.

The study implemented strategies to mitigate CMB, including the use of two types of Likert scale

in the questionnaire design, expert input, and iterative revisions for clarity and precision (Podsakoff et

al., 2024). Harman's single-factor test was applied, and exploratory factor analysis indicated that the

explained variance of the first factor was below the 50% threshold, signifying the absence of significant

CMB. Additionally, a full collinearity test was conducted to assess the presence of CMB. The Variance

Inflation Factors (VIFs) obtained from the test were all lower than 3.3, confirming that the model is

devoid of CMB.

5.1 Measurement Model Evaluation

All assessment criteria utilized to appraise the measurement and structural models adhere to the

guidelines outlined by Hair et al. (2019). As illustrated in Table 2, the loadings for all items exceeded

the recommended threshold of 0.708, aligning with the prescribed criterion. Subsequently, internal

consistency was gauged using Cronbach's alpha (α) and Composite Reliability (CR), encompassing ρa

and ρc. All values surpassed the recommended limit of 0.7, indicating a high degree of reliability.

Furthermore, the constructs exhibited an Average Variance Extracted (AVE) exceeding 0.5, signifying

the establishment of convergent validity. The Heterotrait-Monotrait Ratio (HTMT) values, as shown in

Table 4, were below the 0.90 threshold, thereby refuting concerns about discriminant validity. The

table also provides the results for the Fornell-Larcker Criterion, indicating that the square root of the

AVE for each construct (the diagonal line) was greater than the correlations between that construct and

all other constructs (off-diagonal values). Both the results of the HTMT and the Fornell-Larcker

criterion indicated that discriminant validity has been established (Henseler et al., 2015).

Table 4: Discriminant validity

Heterotrait-Monotrait Ratio of Correlations

1 2 3 4

1. Continuance Intention

(CI)

2. Haptic Imagery (HI)

0.643

[0.565, 0.714]

3. Immersion (IM)

0.866

[0.827, 0.881]

0.649

[0.580, 0.711]

4. Social Media Fatigue

(SMF)

0.738

[0.690, 0.782]

0.709

[0.633, 0.779]

0.741

[0.697, 0.781]

Note: HTMT<0.90, [Confidence interval]

Fornell-Larcker Criterion

1 2 3 4

1. Continuance Intention

(CI)

0.849

2. Haptic Imagery (HI) 0.557 0.860

3. Immersion (IM) 0.774 0.559 0.860

4. Social Media Fatigue

(SMF)

-0.680 -0.625 -0.675 0.919

Note: The values on the diagonal line are higher than the corresponding correlations between constructs (off-

diagonal values)

Source: Authors’ own work

Int. Journal of Business Science and Applied Management / Business-and-Management.org

5.2 Structural Model Analysis

5.2.1 Direct Effects and Control Effects

The analysis results of assessing the structural model are presented in Table 5. All VIF values

remained below 3.3, indicating the absence of significant collinearity among the constructs. The results

revealed that haptic imagery was positively associated with immersion (H1: β=0.559, p<0.001) and

continuance intention (H3: β=0.095, p<0.05), whereas it was negatively associated with social media

fatigue (H2: β=-0.360, p<0.001). As proposed, immersion was found to be negatively associated with

social media fatigue (H4: β=-0.474, p<0.001) and positively associated with continuance intention (H5:

β=0.552, p<0.001). Other than that, social media fatigue was found to be negatively associated with

continuance intention (H6: β=-0.245, p<0.001). Overall, the hypotheses (H1 to H6) garnered support

through the utilization of the bootstrapping technique with 10,000 sub-samples, showcasing statistical

significance (p-value<0.05, t-value>1.645 for one-tailed test, confidence interval did not include a

zero). The results also indicated that none of the control variables (i.e., Age, Education, and Ethnicity)

exerted a significant influence on continuance intention.

Regarding the R

, haptic imagery explained 31.2% of the variance in immersion, while haptic

imagery and immersion collectively accounted for 54.5% of the variance in social media fatigue.

Finally, haptic imagery, immersion, and social media fatigue together explained 65.1% of the variance

in continuance intention. In short, the model exhibits substantial explanatory power (Hair et al., 2019)

by comprehensively considering the impacts of haptic imagery, immersion, and social media fatigue on

continuance intention in SCAs. In assessing the effect sizes, Cohen's (2003) guidelines were followed.

Haptic imagery exerts a large effect size on immersion (f

=0.454), a medium effect size on social

media fatigue (f

=0.196), and a small effect size on continuance intention (f

=0.015). Moreover,

immersion has a medium effect size on social media fatigue (f

=0.339) and a large effect size on

continuance intention (f

=0.445). Lastly, social media fatigue yields a small effect size on continuance

intention (f

=0.076).

Table 5: Results of structural model analysis

Hypotheses VIF β SD t-value p-value CI R

Decision

Direct effects

H1: HI→ IM 1.000 0.559*** 0.035 15.967 0.000 (0.499, 0.614)

0.312

(IM)

0.454 (L) Supported

H2: HI→ SMF 1.454 -0.360*** 0.050 7.259 0.000 (-0.442, -0.279)

0.545

(SMF)

0.196 (M) Supported

H3: HI→ CI 1.776 0.095* 0.045 2.115 0.017 (0.023, 0.171)

0.651

(CI)

0.015 (S) Supported

H4: IM→ SMF 1.454 -0.474*** 0.042 11.258 0.000 (-0.542, -0.403) 0.339 (M) Supported

H5: IM→ CI 1.964 0.552*** 0.044 12.418 0.000 (0.478, 0.624) 0.445 (L) Supported

H6: SMF→ CI 2.278 -0.245*** 0.058 4.258 0.000 (-0.338, -0.150) 0.076 (S) Supported

Control effects

Age→ CI 1.019 0.020ns 0.030 0.680 0.248 (-0.029, 0.070)

Education→ CI 1.014 0.035ns 0.027 1.276 0.101 (-0.010, 0.080)

Ethnicity→ CI 1.034 -0.002ns 0.030 0.081 0.468 (-0.051, 0.046)

Mediation effects

H7: HI→ IM→ SMF -0.265*** 0.026 10.365 0.000 (-0.307, -0.223) 0.070 (S) Supported

H8: HI→ IM→ CI 0.309*** 0.031 10.109 0.000 (0.259, 0.360) 0.096 (M) Supported

H9: HI→ IM→ SMF→ CI 0.065*** 0.016 3.957 0.000 (0.039, 0.092) Supported

Note: β=Path coefficient; SD= Standard deviation; HI=Haptic imagery; IM=Immersion; SMF=Social media

fatigue; CI=Continuance intention; ns=non-significant; *p <0.05; **p < 0.01; ***p < 0.001; S=Small;

M=Medium; L=Large effect size

Source: Authors’ own work

Sin-Er Chong, Siew-Imm Ng, Norazlyn Kamal Basha and Xin-Jean Lim

5.2.2 PLSpredict

PLSpredict results are shown in Table 6. As guided by Shmueli et al. (2019), the Q²predict values

for indicators of continuance intention were greater than zero, signalling that we could proceed to

compare the RMSE values with the naïve LM benchmark. As a result, the majority of indicators yield

smaller prediction errors compared to the LM (the majority of the values in the last column are

negative values), suggesting a medium level of predictive power.

Table 6: PLSpredict results

Q²predict PLS-SEM_RMSE LM_RMSE

PLS-SEM_RMSE-

LM_RMSE

CI1 0.231 1.413 1.410 0.003

CI2 0.231 1.368 1.372 -0.004

CI3 0.236 1.486 1.489 -0.003

CI4 0.172 1.594 1.602 -0.008

CI5 0.233 1.617 1.616 0.001

Note: CI=Continuance Intention; RMSE=Root Mean Squared Error

Source: Authors’ own work

5.2.3 Mediating Effects

As Table 5 presents, immersion plays a significant role as the mediator for three mediation paths.

First, immersion mediates the relationship between haptic imagery and social media fatigue (H7: β=-

0.265, p<0.001, confidence intervals did not contain a zero). According to Cohen (1988), the mediating

effect of immersion between haptic imagery and social media fatigue exhibits a small effect size

=0.070). Second, it mediates the indirect path from haptic imagery to continuance intention (H8:

β=0.309, p<0.001, confidence intervals did not contain a zero). Moreover, a medium effect size

=0.096) is reported for the mediating effect of immersion between haptic imagery and continuance

intention. Third, immersion and social media fatigue sequentially mediate the relationship between

haptic imagery and continuance intention (H9: β=0.065, p<0.001, confidence intervals did not contain a

zero). In summary, the hypotheses proposing the mediation paths (H7 to H9) are supported.

6. DISCUSSION

The connection between haptic imagery and endogenous constructs like immersion, social media

fatigue, and continuance intention has been underexplored in research, especially in the context of

SCAs. Consequently, the present study aimed to fill the research gaps by exploring the link between the

four constructs. To achieve our research objectives, we integrated the TIME and flow theory to further

understand the theoretical backgrounds and we proposed the mediating effects of immersion as well as

the serial mediation effect that chains the relationship between haptic imagery and continuance

intention through immersion and social media fatigue.

The study primarily highlights the favourable impact of haptic imagery as a significant predictor

influencing user immersion, as the effect size was found to be large. Furthermore, we discovered

evidence supporting the dual nature of haptic imagery in alleviating social media fatigue and bolstering

the intention to continue in the context of SCAs. Ivanov et al. (2023) also echoed a similar perspective,

indicating that haptic imagery can enhance performance expectancy, ultimately fostering a sense of

decision comfort among users, which implies that users perceive their choice to use the app as a

positive and informed decision. Our discovery is also consistent with the arguments of Silva et al.

(2021), which emphasized the strategic use of haptic imagery, particularly in the context of online

shopping, to foster positive perceptions of product quality and boost purchase intention. Similarly,

Goncalves et al. (2020) believed that haptic elements play a pivotal role in influencing users' sense of

presence in virtual environments. The engagement of human senses through haptic experiences not

only enhances the overall immersive feeling but also contributes to users perceiving the virtual

experience as more credible, thereby fostering a deeper engagement with the virtual environment.

Moreover, this study confirmed the effect of immersion in reducing social media fatigue and

boosting users’ continuance intention of using SCAs. This finding corresponds with prior research,

which indicated that immersion can alleviate social media fatigue (Lin et al., 2020). It is also consistent

with the principles of flow theory, where immersion displays a positive effect on the repurchase and

return intention in the social commerce context (Herrando et al., 2019). On top of that, we integrated

the theoretical frameworks of TIME and flow theory to delve into the intricate mechanisms governed

by immersion. The outcomes revealed that immersion serves as a crucial mediator, bridging the

Int. Journal of Business Science and Applied Management / Business-and-Management.org

association between haptic imagery and both social media fatigue and continuance intention.

Furthermore, our study uncovered a sequential mediation pathway, confirming that immersion and

social media fatigue collaboratively mediate the relationship between haptic imagery and continuance

intention. This result aligns with the substantial emphasis on the influence of immersion in the context

of mobile apps (Ming et al., 2021; Zhou, 2020), reinforcing the established notion that immersive

experiences significantly contribute to users' intentions to continue using the SCAs.

6.1 Theoretical Implications

The theoretical implications of this study are threefold. Firstly, it extends the existing body of

knowledge by pioneering empirical research into the impact of haptic imagery on user experiences and

continuance intention in the context of SCAs. This novel exploration provides valuable insights into the

underexplored realm of haptic elements in contemporary user interactions with SCAs. This study

significantly contributes to the existing literature by addressing the four research gaps highlighted in

the literature review. Specifically, we integrated the TIME and flow theory to understand the

underlying and uncovered role of haptic imagery in impacting continuance intention. This study makes

a significant theoretical contribution by revealing the impact of specific technological factors—namely,

haptic imagery—within the SCAs landscape, an area previously overlooked by research that focused

only on general technological factors. While prior research has emphasized the importance of haptics in

online shopping contexts (Ivanov et al., 2023; Mulcahy & Riedel, 2018; Silva et al., 2021), our study

uniquely focuses on evaluating the effectiveness of haptic imagery specifically within the realm of

SCAs, in response to the call by Racat and Plotkina (2023) for research specifically targeting mobile

commerce. This contributes to the theoretical foundation of haptic knowledge in the context of social

commerce, offering valuable insights into this relatively unexplored area.

Second, our study enriches the literature by examining immersion and social media fatigue within

the context of SCAs, offering a deeper understanding of user experiences and outcomes. By confirming

the impact of immersion on reducing social media fatigue and increasing continuance intention, our

study adds depth to the existing literature and empirical support to flow theory. Third, our study

advances the integration of TIME and flow theory by unveiling the mediating role of immersion in the

influential paths. Additionally, we proposed and tested the serial mediation by connecting the dots,

demonstrating that haptic imagery's positive effect leads to immersion, reducing social media fatigue,

and ultimately influencing continuance intention. This novel approach expands our understanding of

the intricate relationships between technological advancement and user experiences of continuing the

usage of SCAs.

6.2 Practical Implications

The research findings have substantial implications for the social commerce context, especially

considering the vast potential of SCAs in the economic landscape of Asian markets (WARC, 2023).

From a practical standpoint, this study provides valuable insights for developers of SCAs seeking to

enhance user retention. The positive impact identified regarding haptic imagery, specifically its

influence on immersion, the reduction of social media fatigue, and continuance intention, suggests a

strategic opportunity for integrating haptic features into the design of these apps. By prioritizing the

creation of immersive and engaging experiences through haptic elements, developers can not only

attract users but also contribute to a more positive user journey, catering to the preferences and

behaviours of the Southeast Asian market. Understanding the sequential mediation effects, particularly

the role of immersion as a bridge between haptic imagery and user behaviour, offers developers a

nuanced approach to optimizing the user experience within the social commerce landscape. This

knowledge empowers them to make informed decisions, allowing them to tailor the design of SCAs to

foster a sense of immersion, alleviate fatigue, and ultimately encourage users in the social commerce

market to continue engaging with these platforms.

To leverage these findings, developers and designers of SCAs catering to the Southeast Asian

market could contemplate incorporating specific haptic imagery features. For example, introducing

tactile product reviews with associated haptic feedback could be an innovative approach. Users would

then be able to access reviews and feel the emotions or sentiments expressed in them through haptic

cues, creating a more immersive and emotionally engaging environment. Social interactions within the

app can also benefit from haptic elements, with the integration of haptic gestures or virtual touches

during social engagements, fostering a more immersed and interactive experience for social commerce

users. Additionally, strategically placing haptic interactions at key points in the user journey, such as

during product exploration or purchasing processes, can enhance the overall experience for users in the

social commerce context. Furthermore, the study's focus on the TIME and flow theory contributes to a

deeper understanding of the underlying mechanisms influencing users' experiences in SCAs.

Sin-Er Chong, Siew-Imm Ng, Norazlyn Kamal Basha and Xin-Jean Lim

Businesses can draw upon these theoretical frameworks to inform their strategies, ensuring a more

nuanced and culturally relevant approach to user interaction and retention.

Addressing social media fatigue has become crucial, and developers may focus on refining content

curation algorithms to reduce information overload. Utilizing haptic features to guide users through the

platform, providing a more relaxed and enjoyable social commerce experience, is one way to achieve

this. Implementing haptic feedback to signal positive interactions or nudges within the app could

contribute to a less exhausting and more engaging environment, aligning with preferences in the social

commerce market. Moreover, the understanding of sequential mediation effects suggests an

opportunity for developers to design features that capture users' attention through haptic imagery,

guiding them seamlessly through an immersive journey and ultimately reducing social media fatigue

within the social commerce business landscape.

Continuous user education about the practical usage of haptic imagery and gathering feedback on

specific haptic elements that resonate positively or negatively can inform iterative design processes for

SCAs, targeting more users. Through these practical examples, SCAs can unlock the full potential of

haptic imagery, offering users a richer and more immersive shopping journey to encourage continued

usage. The potential benefits extend from heightened engagement and emotional connection to a more

personalized and interactive user journey, shaping a new paradigm for the future of social commerce in

the Asian and global business context. In conclusion, this research provides actionable insights for

businesses operating in the dynamic realm of SCAs, guiding them in harnessing the potential of haptic

imagery, optimizing user experiences, and fostering continued user engagement. These implications

pave the way for businesses to navigate the evolving landscape of social commerce in diverse markets.

7. LIMITATIONS AND FUTURE RESEARCH

While this study contributes valuable insights, it is not without limitations. One notable limitation

is the cross-sectional nature of the research design. Future research could adopt a longitudinal approach

to better understand the temporal dynamics and causal connections between haptic imagery,

immersion, social media fatigue, and continuance intention. Additionally, the study focused on users

within a specific geographical context (Malaysia), and the findings may not be universally applicable.

Extending the research to diverse cultural contexts could provide a more comprehensive understanding

of the generalizability of the results. Next, the reliance on self-reported data introduces the possibility

of response bias and social desirability effects. Employing objective measures or combining self-

reports with behavioural data could enhance the robustness of the findings. Moreover, the study

concentrated on a set of demographic control variables, namely age, education, and ethnicity. Future

research could explore a broader range of demographic factors or incorporate individual differences,

such as technology readiness or personality traits, to uncover nuanced insights. Lastly, the study

generally focused on haptic imagery. Future investigations could delve into the distinct effects of

various haptic modalities, such as touch feedback or force feedback, to discern their unique

contributions to user experiences.

REFERENCES

Akram, U., Junaid, M., Zafar, A. U., Li, Z., & Fan, M. (2021). Online purchase intention in Chinese

social commerce platforms: Being emotional or rational? Journal of Retailing and Consumer

Services, 63, 102669.

Al-maghrabi, T., Dennis, C., Halliday, S. V., & BinAli, A. (2011). Determinants of customer

continuance intention of online shopping. International Journal of Business Science & Applied

Management, 6(1), 41–66.

Bao, Z., & Yang, J. (2022). Why online consumers have the urge to buy impulsively: Roles of

serendipity, trust and flow experience. Management Decision, 60(12), 3350–3365.

Brakus, J. J., Schmitt, B. H., & Zarantonello, L. (2009). Brand Experience: What Is It? How Is It

Measured? Does It Affect Loyalty? Journal of Marketing, 73(3), 52–68.

Busalim, A., Hollebeek, L. D., & Lynn, T. (2023). The effect of social commerce attributes on

customer engagement: An empirical investigation. Internet Research. (ahead-of-print).

Cheah (Jacky), J.-H., Magno, F., & Cassia, F. (2023). Reviewing the SmartPLS 4 software: The latest

features and enhancements. Journal of Marketing Analytics, 12, 97-107 (2024).

Int. Journal of Business Science and Applied Management / Business-and-Management.org

Chen, C., Hsiao, K., & Wu, S. (2018). Purchase intention in social commerce An empirical

examination of perceived value and social awareness. Library Hi Tech, 36(4), 583–604.

Cheng, X., Gu, Y., & Shen, J. (2019). An integrated view of particularized trust in social commerce:

An empirical investigation. International Journal of Information Management, 45, 1–12.

Chiu, W., Oh, G.-E. (Grace), & Cho, H. (2022). An integrated model of consumers’ decision-making

process in social commerce: A cross-cultural study of the United States and China. Asia Pacific

Journal of Marketing and Logistics, 35(7), 1682–1698.

Chong, S. E., Ng, S.-I., & Norazlyn, K. B. (2023). A Systematic Review of Studies on Flow

Experience from 2010-2022. Insights and Directions for Future Research. NUST Business

Review, 4(2), 1–21.

Chong, S. E., Ng, S. I., Kamal Basha, N., & Lim, X. J. (2024). Social Commerce in the Social Media

Age: Understanding How Interactive Commerce Enhancements Navigate App Continuance

Intention. Journal of Research in Interactive Marketing. (ahead-of-print).

Cohen, J. (2003). A power primer (p. 436). American Psychological Association.

Csikszentmihalyi, M. (1975). Beyond boredom and anxiety: Experiencing Flow in Work and Play.

Jossey-Bass.

Csikszentmihalyi, M. (1990). Flow: The Psychology of Optimal Experience. Harper and Row.

Data Reportal. (2023, February 13). Digital 2023: Malaysia. DataReportal – Global Digital Insights.

https://datareportal.com/reports/digital-2023-malaysia

Doha, A., Elnahla, N., & McShane, L. (2019). Social commerce as social networking. Journal of

Retailing and Consumer Services, 47, 307–321.

Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical power analyses using G*Power

3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160.

Fu, S., Li, H., Liu, Y., Pirkkalainen, H., & Salo, M. (2020). Social media overload, exhaustion, and use

discontinuance: Examining the effects of information overload, system feature overload, and

social overload. Information Processing & Management, 57(6), 102307.

Goncalves, G., Melo, M., Vasconcelos-Raposo, J., & Bessa, M. (2020). Impact of Different Sensory

Stimuli on Presence in Credible Virtual Environments. Ieee Transactions on Visualization and

Computer Graphics, 26(11), 3231–3240.

Hadi, R., & Valenzuela, A. (2020). Good Vibrations: Consumer Responses to Technology-Mediated

Haptic Feedback. Journal of Consumer Research, 47(2), 256–271.

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results

of PLS-SEM. European Business Review, 31(1), 2–24.

Hair, J., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2021). A Primer on Partial Least Squares Structural

Equation Modeling (PLS-SEM) (Third Edition). SAGE Publications, Inc.

Hajli, N., Shanmugam, M., Powell, P., & Love, P. E. D. (2015). A study on the continuance

participation in on-line communities with social commerce perspective. Technological Forecasting

and Social Change, 96, 232–241.

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity

in variance-based structural equation modeling. Journal of the Academy of Marketing Science,

43(1), 115–135.

Herrando, C., Jimenez-Martinez, J., & De Hoyos, M. (2018). From sPassion to sWOM: the role of

flow. Online Information Review, 42(2), 191–204.

Herrando, C., Jimenez-Martinez, J., & Martin-De Hoyos, M. (2019). Social Commerce Users’ Optimal

Experience: Stimuli, Response and Culture. Journal of Electronic Commerce Research, 20(4),

199–218.

Hew, J.-J., Lee, V.-H., Ooi, K.-B., & Lin, B. (2016). Mobile social commerce: The booster for brand

loyalty? Computers in Human Behavior, 59, 142–154.

Hoffman, D. L., & Novak, T. P. (1996). Marketing in hypermedia computer-mediated environments:

Conceptual foundations. Journal of Marketing, 60(3), 50–68.

Hu, X., Chen, Z., Davison, R. M., & Liu, Y. (2022). Charting consumers’ continued social commerce

intention. Internet Research, 32(1), 120–149.

Huang, T.-L., & Liao, S.-L. (2017). Creating e-shopping multisensory flow experience through

augmented-reality interactive technology. Internet Research, 27(2), 449–475.

Sin-Er Chong, Siew-Imm Ng, Norazlyn Kamal Basha and Xin-Jean Lim

Ivanov, A., Head, M., & Biela, C. (2023). Mobile shopping decision comfort using augmented reality:

The effects of perceived augmentation and haptic imagery. Asia Pacific Journal of Marketing and

Logistics, 35(8), 1917–1934.

Javornik, A. (2016). ‘It’s an illusion, but it looks real!’ Consumer affective, cognitive and behavioural

responses to augmented reality applications. Journal of Marketing Management, 32(9–10), 987–

1011.

Ji, F., Wang, F., & Wu, B. (2023). How does virtual tourism involvement impact the social education

effect of cultural heritage? Journal of Destination Marketing & Management, 28, 100779.

Jordan, P. J., & Troth, A. C. (2020). Common method bias in applied settings: The dilemma of

researching in organizations. Australian Journal of Management, 45(1), 3–14.

Kline, R. B. (2023). Principles and Practice of Structural Equation Modeling (Fifth). Guilford

Publications.

Lee, H., Xu, Y., & Porterfield, A. (2020). Consumers’ adoption of AR-based virtual fitting rooms:

From the perspective of theory of interactive media effects. Journal of Fashion Marketing and

Management: An International Journal, 25(1), 45–62.

Leong, L.-Y., Hew, T. S., Ooi, K.-B., Hajli, N., & Tan, G. W.-H. (2023). Revisiting the social

commerce paradigm: The social commerce (SC) framework and a research agenda. Internet

Research. (ahead-of-print).

Liao, J., Chen, K., Qi, J., Li, J., & Yu, I. (2023). Creating immersive and parasocial live shopping

experience for viewers: The role of streamers’ interactional communication style. Journal of

Research In Interactive Marketing, 17(1), 140–155.

Liang, T.-P., Ho, Y.-T., Li, Y.-W., & Turban, E. (2011). What Drives Social Commerce: The Role of

Social Support and Relationship Quality. International Journal of Electronic Commerce, 16(2),

69–90.

Lim, W. M., Kumar, S., Pandey, N., Rasul, T., & Gaur, V. (2022). From direct marketing to interactive

marketing: A retrospective review of the Journal of Research in Interactive Marketing. Journal of

Research in Interactive Marketing, 17(2), 232–256.

Lim, X.-J., Cheah, J.-H., Waller, D. S., Ting, H., & Ng, S. I. (2019). What s-commerce implies?

Repurchase intention and its antecedents. Marketing Intelligence & Planning, 38(6), 760–776.

Lin, J., Lin, S., Turel, O., & Xu, F. (2020). The buffering effect of flow experience on the relationship

between overload and social media users’ discontinuance intentions. Telematics and Informatics,

49, 101374.

Lin, X., & Wang, X. (2022). Towards a model of social commerce: Improving the effectiveness of e-

commerce through leveraging social media tools based on consumers’ dual roles. European

Journal of Information Systems, 32(5), 782–799.

Liu, C., Bao, Z., & Zheng, C. (2019). Exploring consumers’ purchase intention in social commerce An

empirical study based on trust, argument quality, and social presence. Asia Pacific Journal of

Marketing and Logistics, 31(2), 378–397.

Liu, H., Chu, H., Huang, Q., & Chen, X. (2016). Enhancing the flow experience of consumers in China

through interpersonal interaction in social commerce. Computers in Human Behavior, 58, 306–

314.

Mikalef, P., Giannakos, M. N., & Pappas, I. O. (2017). Designing social commerce platforms based on

consumers’ intentions. Behaviour & Information Technology, 36(12), 1308–1327.

Ming, J., Zeng, J., Bilal, M., Akram, U., & Fan, M. (2021). How social presence influences impulse

buying behavior in live streaming commerce? The role of S-O-R theory. International Journal of

Web Information Systems, 17(4), 300–320.

Molinillo, S., Aguilar-Illescas, R., Anaya-Sanchez, R., & Liebana-Cabanillas, F. (2021). Social

commerce website design, perceived value and loyalty behavior intentions: The moderating roles

of gender, age and frequency of use. Journal of Retailing and Consumer Services, 63, 102404.

Molinillo, S., Anaya-Sanchez, R., & Liebana-Cabanillas, F. (2020). Analyzing the effect of social

support and community factors on customer engagement and its impact on loyalty behaviors

toward social commerce websites. Computers in Human Behavior, 108, 105980.

Molinillo, S., Liebana-Cabanillas, F., & Anaya-Sanchez, R. (2018). A Social Commerce Intention

Model for Traditional E-Commerce Sites. Journal of Theoretical and Applied Electronic

Commerce Research, 13(2), 80–93.

Int. Journal of Business Science and Applied Management / Business-and-Management.org

Mulcahy, R., & Riedel, A. (2018). ‘Touch it, swipe it, shake it’: Does the emergence of haptic touch in

mobile retailing advertising improve its effectiveness? Journal of Retailing and Consumer

Services, 54.

Nandi, S., Nandi, M., & Khandker, V. (2021). Impact of perceived interactivity and perceived value on

mobile app stickiness: An emerging economy perspective. Journal of Consumer Marketing, 38(6),

721–737.

Ornati, M., & Kalbaska, N. (2022). Looking for haptics. Touch digitalization business strategies in

luxury and fashion during COVID-19 and beyond. Digital Business, 2(2), 100035.

Osatuyi, B., & Qin, H. (2018). How vital is the role of affect on post-adoption behaviors? An

examination of social commerce users. International Journal of Information Management, 40,

175–185.

Osatuyi, B., Qin, H., Osatuyi, T., & Turel, O. (2020). When it comes to Satisfaction … It depends: An

empirical examination of social commerce users. Computers in Human Behavior, 111, 106413.

Osatuyi, B., & Turel, O. (2018). Social motivation for the use of social technologies: An empirical

examination of social commerce site users. Internet Research, 29(1), 24–45.

Papagiannidis, S., Bourlakis, M., & See-To, E. (2019). Social media in supply chains and logistics:

Contemporary trends and themes. International Journal of Business Science and Applied

Management, 14, 17–34.

Park, J., & Ha, S. (2021). Developing Brand Loyalty through Consumer Engagement with Brand

Communities in Social Media. Asian Journal of Business Research, 11(1), 83–102.

Petit, O., Velasco, C., & Spence, C. (2019). Digital Sensory Marketing: Integrating New Technologies

Into Multisensory Online Experience. Journal of Interactive Marketing, 45, 42–61.

Podsakoff, P. M., Podsakoff, N. P., Williams, L. J., Huang, C., & Yang, J. (2024). Common Method

Bias: It’s Bad, It’s Complex, It’s Widespread, and It’s Not Easy to Fix. Annual Review of