Journal of Open Innovation: Technology, Market, and Complexity 11 (2025) 100635

Contents lists available at ScienceDirect

Journal of Open Innovation: Technology, Market,

and Complexity
journal homepage: www.sciencedirect.com/journal/journal-of-open-innovation-technology-
market-and-complexity

Social commerce attributes, customer engagement and repurchase

intention in social commerce platforms: A stimulus–organism–
response approach
Fadi Herzallah a,1,* , Amer J. Abosamaha a,2 , Salameh Mohammad Salameh b,3 ,
Mahmoud Alhayek c,4
a
Palestine Technical University – Kadoorie, Palestine
b
AL Quds Open University, Palestine
c
Faculty of Business and Low, Curtin University, Perth, Australia

A R T I C L E I N F O A B S T R A C T

Keywords: The integration of social interactions with e-commerce has given rise to social commerce, creating digital en­
Social commerce vironments where consumers engage with each other while shopping. Despite growing research on customer
Customer engagement engagement in social commerce, there remains a limited understanding of how specific platform attributes in­
Repurchase intention
fluence engagement behaviors and subsequent purchasing decisions. This research addresses this gap by
Stimulus-Organism-Response (S-O-R) model
examining the relationship between social commerce attributes and repurchase intention through the lens of the
Stimulus-Organism-Response theoretical framework. Our investigation focuses on four key platform character­
istics, namely, content informativeness, service quality, webpage attractiveness, and traditional word-of-mouth
communication. We hypothesize that these elements act as stimuli that shape customer engagement (the or­
ganism component), ultimately affecting intentions to make repeat purchases (the response component). To test
these relationships, we administered an online questionnaire to 238 social commerce users in Palestine. Data
analysis through structural equation modeling techniques revealed that content informativeness, service quality,
and traditional word-of-mouth significantly enhanced customer engagement, while webpage attractiveness
showed no significant effect. Furthermore, customer engagement demonstrated a strong positive influence on
repurchase intention. These findings contribute to social commerce literature by identifying the relative
importance of different platform attributes in fostering meaningful customer relationships. For practitioners,
especially in emerging markets, our results suggest prioritizing content informativeness, responsive service, and
encouraging traditional word-of-mouth promotion alongside digital strategies to develop more engaging social
commerce platforms that drive customer loyalty.

1. Introduction purchasing processes with community-based interactions on platforms

such as Facebook, Instagram, and specialized social shopping applica­
The emergence of Web 2.0 technologies has fundamentally trans­ tions. Unlike traditional online shopping, s-commerce establishes envi­
formed digital interactions, catalyzing a shift from conventional elec­ ronments where commercial activities occur within social contexts,
tronic commerce toward more socially-oriented platforms worldwide enabling consumers to participate actively in content generation,
(Charles and Kanani, 2025; Dincer and Dincer, 2023). This evolution has knowledge exchange, and peer-to-peer communication (Charles and
given rise to social commerce (s-commerce), which integrates Kanani, 2025; Sohn and Kim, 2020; W. Zhao et al., 2023).

* Corresponding author.
E-mail addresses: f.herzallah@ptuk.edu.ps (F. Herzallah), amer@abosamaha.net (A.J. Abosamaha), smsalamah@qou.edu (S.M. Salameh), mmsh991@live.com
(M. Alhayek).
1
https://orcid.org/0000–0001-8589–7950
2
https://orcid.org/0000–0003-2215–8549
3
https://orcid.org/0000–0001-7046–0166
4
https://orcid.org/0000–0002-4414–7587

https://doi.org/10.1016/j.joitmc.2025.100635
Received 5 July 2025; Received in revised form 1 September 2025; Accepted 9 September 2025
Available online 10 September 2025
2199-8531/© 2025 The Author(s). Published by Elsevier Ltd on behalf of Prof JinHyo Joseph Yun. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
F. Herzallah et al. Journal of Open Innovation: Technology, Market, and Complexity 11 (2025) 100635

The economic significance of s-commerce is substantial and growing Table 1

rapidly. Currently estimated at approximately $0.7 trillion in global Major Theoretical Approaches in S-commerce Research.
revenue, industry analysts project the market will reach $1 trillion by Study Specific Theory/Model Output Factor
2028 (Statista, 2024). Emerging economies demonstrate particularly
Technology Acceptance and Innovation Diffusion Theories
notable growth trajectories, with the sector currently valued at roughly (Sarker et al., 2025) UTAUT Continuance Intention
$12 billion expected to experience a compound annual growth rate (Rahman et al., UTAUT2 Purchase Intention
exceeding 27 %, potentially reaching $42.5 billion by 2029 (Markets, 2023)
2025). This rapid expansion has transformed passive shoppers into (Jasrotia et al., TAM Usage Intention
2025)
engaged community members who contribute to brand narratives and (Sun et al., 2023) TAM3 Purchase Intention
product evaluations, creating value beyond traditional transactions (Liu, (L. Zhao et al., 2023) DOI + Trust Theory Purchase Intention
2024; Sarker et al., 2025). (Saprikis and UTAUT + DOI Usage Intention
Central to s-commerce success is customer engagement (SCCE), Avlogiaris, 2023)
Post-Adoption Theories
defined as the degree of an individual’s participation and connection
(Aref, 2024) ECT Continuance Intention
with platform offerings and activities. SCCE encompasses cognitive, (Ko and Ho, 2024) ECT Repurchase Intention
emotional, behavioral, and social dimensions that can be initiated by (Yu et al., 2024) ECT + Social Influence Continuance Intention
either customers or organizations, influencing various outcomes Theory
including loyalty, brand community involvement, and repurchase de­ (Leung et al., 2022) Role Theory + ECT Repurchase Intention
(Laradi et al., 2024) Expectancy-Value Theory Purchase Intention
cisions (A. Busalim and Asadi, 2025; S. Sharma and Sharma, 2024). As (EVT)
consumers increasingly rely on social media to obtain product infor­ Social/Cognitive Theories
mation, SCCE plays a significant role in their purchasing behaviors and (Elshaer et al., 2024) SCT Purchase Intention
serves as a crucial variable for businesses aiming to gain competitive (Xu et al., 2024) SLT Impulsive Purchase
(Huwaida et al., SCT Purchase Intention
advantage in s-commerce environments (X. Li et al., 2023; So et al.,
2024)
2024). (A. Y. Liu and Lin, Elaboration likelihood Entrepreneurial Intention
Despite growing research on customer engagement in s-commerce, 2025) model (ELM) + TPB
there remains limited understanding of how specific attributes influence Trust-Based Theories
engagement behaviors and subsequent re-purchasing decisions. While (Al-Adwan et al., ST Trust Enhancement and
2022) Purchase Intention
previous research has identified various factors influencing customer
(Al-Adwan and ST Trust Enhancement
engagement (Busalim and Asadi, 2025; Mohammad et al., 2024), the Yaseen, 2023)
specific impact of seller-level attributes on SCCE and their downstream (Senali et al., 2024) ST Trust Enhancement and
effects on repurchase intentions have remained less clear. This knowl­ Purchase Intention
(F. Herzallah et al., ST Trust Enhancement
edge gap is particularly pronounced in emerging markets, where
2025).
contextual factors may significantly influence the relative importance of
different platform characteristics.
This study addresses these gaps by examining the relationship be­ and innovation frameworks have dominated the field, with researchers
tween social commerce attributes and repurchase intention through the extensively applying UTAUT (Saprikis and Avlogiaris, 2023; Sarker
Stimulus-Organism-Response theoretical framework. Specifically, we et al., 2025), UTAUT2 (Rahman et al., 2023), TAM (Jasrotia et al.,
investigate how four key attributes namely content informativeness, 2025), and TAM3 (Sun et al., 2023) to examine adoption intentions and
service quality, webpage attractiveness, and traditional word-of-mouth usage behaviors. These models primarily emphasize factors such as
communication act as stimuli that shape customer engagement, ulti­ perceived usefulness and ease of use in explaining technology adoption
mately affecting intentions to make repeat purchases. The paper is decisions.
structured as follows: the next section presents the literature review and In contrast, post-adoption theories focus on explaining continued
hypothesis development, followed by the research methodology, find­ engagement after initial adoption. Expectation Confirmation Theory
ings, and their implications. (ECT) has particularly proven valuable for understanding how satisfied
users develop continuance intentions (Aref, 2024; Yu et al., 2024),
2. Literature review repurchase (Laradi et al., 2024), and maintain repurchase behaviors
over time (Ko and Ho, 2024; Leung et al., 2022). Meanwhile, social and
2.1. Theoretical framework comparison and selection cognitive theories have emerged to address the interpersonal di­
mensions of s-commerce, with Social Cognitive Theory (SCT) (Elshaer
The emergence of s-commerce has created unique environments that et al., 2024; Huwaida et al., 2024) and Social Learning Theory (SLT) (Xu
blend transactional and social elements, consequently prompting re­ et al., 2024) providing insights into social influence mechanisms and
searchers to explore various theoretical frameworks to understand learning processes within s-commerce communities.
consumers’ digital behavior in these contexts. However, the selection of Additionally, trust-based approaches have gained attention as re­
an appropriate theoretical foundation significantly influences both the searchers recognize the critical role of uncertainty reduction in online
variables examined and the insights generated, particularly when transactions. Signaling Theory (ST), in particular, has been applied to
investigating repurchase intentions in emerging markets. Traditionally, examine how various platform cues address information asymmetry
prior investigations have predominantly drawn upon established theo­ concerns, ultimately leading to enhanced trust and purchase intentions
retical constructs from information systems research, including the (Al-Adwan et al., 2022; Al-Adwan and Yaseen, 2023; Herzallah and
Technology Acceptance Model (TAM) developed by Davis (1989), Al-Sharafi, 2025; Senali et al., 2024).
Theory of Planned Behavior (TPB) by Ajzen (1991), Innovation Diffu­ While the aforementioned theories have provided valuable insights,
sion Theory (DOI) by Rogers (2003), and the Unified Theory of Accep­ they present notable limitations when applied to s-commerce contexts.
tance and Use of Technology (UTAUT) introduced by Venkatesh et al. These frameworks primarily emphasize cognitive decision processes
(2003). while inadequately addressing the emotional and environmental factors
Table 1 summarizes the growing importance of s-commerce and the that characterize s-commerce platforms (Irimia-Diéguez et al., 2025). In
diverse theoretical lenses applied to investigate various aspects and key contrast, the Stimulus-Organism-Response (SOR) framework has been
outcomes, such as continuance, usage, continuous, trust enhancement widely and successfully applied across numerous fields, including
and repurchase/purchase intentions. Initially, technology acceptance

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F. Herzallah et al. Journal of Open Innovation: Technology, Market, and Complexity 11 (2025) 100635

payment systems (Kumar et al., 2025; Uddin et al., 2025), e-commerce technological features such as personalization and responsiveness, social
(Y. Liu et al., 2024; W. Zhao et al., 2023), live streaming commerce elements including e-WOM credibility and influencer familiarity,
(Ming et al., 2021), tourism live streaming (Liang et al., 2024), and platform-specific features like recommendations and community fo­
importantly s-commerce (Chandraa et al., 2024; Imanuddin and Han­ rums, and experiential factors such as immersion and perceived enjoy­
dayani, 2025; Mohammad et al., 2024; Yang et al., 2025). Recent bib­ ment. Additionally, platform affordances including visibility,
liometric analyses identify SOR as an emerging "driving theme" in metavoicing, and guidance shopping function as stimuli that trigger user
s-commerce research (2019–2022), representing a well-developed and responses.
pivotal theoretical approach for structuring the field (D. Herzallah et al., Second, organism (O) refers to the internal psychological processes
2025; L. Y. Leong et al., 2024). and states that mediate the relationship between external stimuli and
The SOR framework’s three-stage process goes beyond simple input- behavioral outcomes. This component captures both cognitive and
output models by explicitly examining consumers’ internal cognitive emotional dimensions of consumer processing. Recent applications
and emotional states as crucial intermediaries between environmental reveal diverse organism variables across s-commerce studies, including
stimuli and behavioral responses, thereby explaining the "black box" of trust-related constructs (e.g., trust in products, streamers, sellers),
consumer psychology (Haq et al., 2024). Furthermore, SOR’s versatility cognitive states (e.g., perceived usefulness, perceived value, brand
enables simultaneous investigation of diverse stimuli, including tech­ attitude), emotional responses (e.g., parasocial relationships, immersive
nological features, social factors, and platform characteristics, making it experience), and engagement-related outcomes (e.g., customer
particularly suitable for the multi-faceted environment of s-commerce engagement, flow experience). This component represents the "black
(Chandraa et al., 2024; Tuncer, 2021). Additionally, the SOR framework box" of consumer psychology where environmental stimuli are pro­
demonstrates strong integrative capacity, serving as a solid foundation cessed and transformed into psychological states.
that can be integrated with other theories to build more nuanced Third, response (R) encompasses the final behavioral outcomes
models. Studies successfully combine SOR with trust transfer theory, the resulting from the internal processing of stimuli. In s-commerce
theory of planned behavior (TPB), and the IT affordance lens to create research, responses typically manifest as various forms of intentional
richer explanations of consumer behavior (Haq et al., 2024; Tuncer, behaviors, including purchase intention, continuance intention, social
2021). Having established the theoretical rationale for framework se­ commerce intention, and engagement behaviors. These responses
lection, we now turn to a detailed examination of the SOR applications represent observable behavioral manifestations that result from the
in s-commerce and its operationalization within our Palestinian context. complex interplay between environmental stimuli and internal psy­
chological processing.
While previous SOR applications in social commerce have examined
2.2. Stimulus-Organism-Response (SOR) framework
various stimuli such as live streaming affordances (Chandraa et al.,
2024; Yang et al., 2025), platform-wide features (Mohammad et al.,
The Stimulus-Organism-Response (S-O-R) framework, originally
2024), and digital communication characteristics (Haq et al., 2024), our
developed by Mehrabian and Russell (1974), is a psychological model
study focuses on four attributes that represent distinct stimulus (i.e.,
that explains human behavior as a three-stage process. It posits that
content informativeness, service quality, webpage attractiveness, and
external environmental cues (stimulus) influence an individual’s inter­
traditional word-of-mouth). This specific combination has not been
nal cognitive and emotional states (organism), which in turn trigger
examined collectively within the SOR framework, representing a theo­
behavioral reactions (response). This framework has gained prominence
retical gap that our research addresses to enrich both theoretical un­
in consumer behavior research for its ability to explain the mechanisms
derstanding and practical applications in s-commerce.
through which environmental factors shape purchasing decisions by
Content informativeness was selected as it addresses the funda­
explicitly examining the intermediate psychological processes that
mental information asymmetry challenges prevalent in online trans­
traditional input-output models often overlook (Haq et al., 2024; Iri­
actions, particularly critical in emerging markets where consumers rely
mia-Diéguez et al., 2025). As demonstrated in Table 2, the three com­
heavily on available information to reduce perceived risks (Al-Adwan
ponents can be detailed as follows.
and Yaseen, 2023; F. Herzallah and Al-Sharafi, 2025). Service quality,
First, stimulus (S) represents the external environmental factors,
while fundamental to s-commerce success, has been notably absent from
cues, or incentives that individuals encounter in s-commerce platforms.
previous SOR applications. Although Chandraa et al. (2024) examined
As demonstrated in recent applications, these stimuli encompass

Table 2
SOR Model Application in S-Commerce.
Study Theories Stimulus (S) Organism (O) Response (R)

(Imanuddin and SOR, Trust Transfer Theory, - Personalization- Visibility - Susceptibility to - Trust in Products- Trust in - Continuance intention to
Handayani, 2025) and Social Exchange Theory. Informational Influence- Co-creation Behaviour Streamers- Perceived Value use live streaming
(Yang et al., 2025) SOR and Parasocial - Immersion- Social Presence- Telepresence- Perceived - Parasocial Relationship - Trust Purchase Intention
Relationship Theory Enjoyment in Product- Trust in Seller
(Chandraa et al., SOR and IT Affordance theory - Personalization- Responsiveness- Entertainment- - Perceived Usefulness- Purchase Intention
2024) Mutuality- Perceived Control- Visibility- Meta-voicing- Psychological Distance-
Guidance Shopping Immersion
(Haq et al., 2024) SOR, trust transfer theory and - e-WOM credibility - e-WOM Valence- Influencer -Brand Attitude -Perceived - Online Engagement
the Theory of Planned Familiarity Brand Quality Intention - Online Purchase
Behavior. Intention
(Mohammad et al., SOR - Recommendations & Referrals- Forums & - Perceived Brand Image - - Hotel Booking Intentions
2024) Communities- Reviews & Ratings Customer Engagement
(Y. Liu et al., 2023) SOR - Usefulness- Interactivity- Entertainment- Authenticity - Arousal- Pleasure - Impulse buying- Social
participation
(Hewei and SOR -Social Media Interactivity - Perceived Value- Immersive Continuous Purchase
Youngsook, Experience Intention
2022)
(Tuncer, 2021) SOR and IT Affordance theory - Visibility- Metavoicing- Guidance shopping - Trust in seller - Trust in social Social commerce intention
media platform - Flow
experience

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F. Herzallah et al. Journal of Open Innovation: Technology, Market, and Complexity 11 (2025) 100635

responsiveness as a narrow platform affordance, comprehensive service context as illustrated in Fig. 1.

quality encompassing reliability, efficiency, and customer support has
not been investigated as an SOR stimulus. 2.4.1. Content Informativeness (COIN) and Customer Engagement (SCCE)
Webpage attractiveness, while examined in broader s-commerce Social commerce environments function primarily as specialized
(Marmat, 2023; Ramezani Nia and Shokouhyar, 2020), has not been implementations of broader social media platforms, delivering distinct
specifically investigated within the SOR framework for s-commerce commercial functionality within interactive digital spaces. To effectively
applications. Although previous SOR studies have examined related serve their purpose, these platforms must deliver measurable utility to
constructs such as visibility (Imanuddin and Handayani, 2025; Tuncer, users through their content presentation strategies (Liu, 2024). The
2021), these focused on content findability and discoverability rather COIN concept, encompasses the comprehensive nature of product de­
than aesthetic appeal and visual design attractiveness. Traditional tails provided through seller interfaces, incorporating the depth,
word-of-mouth was selected as a novel stimulus not previously exam­ breadth, and multimedia integration of content elements including
ined in SOR social commerce research. Despite previous investigations textual descriptions, visual assets, and video demonstrations made
of digital word-of-mouth elements such as e-WOM credibility and available to potential customers (Lee et al., 2021).
valence (Haq et al., 2024) and platform-based recommendations and Prior research has confirmed the influence of content informative­
referrals (Mohammad et al., 2024), these studies focused exclusively on ness on Customer engagement (SCCE). For example, Vlachvei et al.
digital communications. Our inclusion of traditional word-of-mouth (2022) investigated the effects of content characteristics on stages of
addresses the gap in understanding how offline interpersonal recom­ SCCE in social media, while Lee and Park (2022) confirmed the influ­
mendations influence online engagement behaviors, particularly rele­ ence of content informativeness on SCCE in an social media setting.
vant in Palestinian culture where strong interpersonal relationships and Furthermore, Moran et al. (2020) show positive relationships for media
community ties significantly impact consumer decisions (Sayyad, 2018). richness content components on increasing consumer-brand engage­
ment outcomes. Building on this empirical evidence, it can be argued
2.3. S-commerce in Palestine that when s-commerce sellers provide rich information on their web­
pages, they are likely to make prospective customers more willing to
Despite growing SOR applications in s-commerce, comprehensive purchase from them. Thus, we propose the following hypothesis
analyses note that this framework remains underutilized in emerging
H1. : There is a positive relationship between COIN and SCCE.
markets where contextual factors may significantly influence consumer
behavior patterns (Singh and Pandey, 2024; W. Zhao et al., 2023).
2.4.2. Service Quality (SERQ) and Customer Engagement (SCCE)
Palestine represents a particularly compelling case for SOR application,
Service quality is a pivotal factor in distinguishing trustworthy
demonstrating significant social media engagement with approximately
sellers from unscrupulous ones in the e-commerce sector. It significantly
2.2 million users representing 40.5 % of the nation’s 5.43 million pop­
influences consumer behavior, enhancing trust and satisfaction, which
ulation (Kemp, 2024). This substantial digital penetration has translated
in turn can lead to increased traffic and sales (Sutisna et al., 2023). The
into growing business utilization of social platforms, with Sayyad (2018)
multidimensional nature of service quality encompasses various aspects
emphasizing the integral role of social media in Palestinian marketing
such as reliability, efficiency, and responsiveness, which are crucial for
practices.
maintaining a competitive edge in the digital marketplace (Çağlar et al.,
However, academic examination of s-commerce within Palestine
2024). Online customers may evaluate the quality of the services offered
remains limited and fragmented, revealing substantial gaps in theory-
by the seller in terms of the scope of functions provided by the s-com­
based investigations (F. Herzallah and Al-Sharafi, 2025). The existing
merce webpage or the level of overall support and services provided
body of Palestinian s-commerce research encompasses only a few
(Charles and Kanani, 2025; Pour et al., 2020). Online business studies
empirical studies spanning 2018–2025, with several studies lacking
regard service quality as a signal that sellers can use (F. Herzallah and
formal theoretical grounding (e.g., Ayyash, 2023; Hamleh, 2020; F.
Al-Sharafi, 2025).
Herzallah and Al Qirim, 2023; Sayyad, 2018). Among the theory-based
In the context of s-commerce, providing high service quality on
investigations, only the Expectation Confirmation Model (F. Herzallah
webpages can significantly enhance customer willingness to purchase
and Ayyash, 2021), Theory of Planned Behavior (D. Herzallah et al.,
(Pour et al., 2020). This is primarily because good service quality re­
2021), and recently Signaling Theory (F. Herzallah and Al-Sharafi,
duces perceived risks and uncertainties, thereby fostering trust and
2025) have been applied, leaving substantial theoretical gaps in un­
confidence in potential buyers (Sutisna et al., 2023). The empirical ev­
derstanding Palestinian s-commerce behavior. Notably, limited studies
idence from various studies supports the notion that service quality is a
have applied the SOR framework within the Palestinian s-commerce
critical determinant of SCCE in online environments (Amro et al., 2025;
context, despite its growing prominence in the broader s-commerce
Fan et al., 2022; Ganie and Bhat, 2023). Therefore, the following hy­
literature.
potheses are proposed:
This convergence of theoretical and contextual gaps presents a
compelling research opportunity. In our research context, we consider H2. : There is a positive relationship between SERQ and SCCE.
specific s-commerce attributes (i.e., content informativeness, service
quality, webpage attractiveness, and traditional word-of-mouth) as 2.4.3. Webpage Attractiveness (WEBA) and Customer Engagement (SCCE)
external environmental stimuli (S) that influence customer engagement The attractiveness of a seller’s webpage in s-commerce is signifi­
as the organism (O), which ultimately affects consumers repurchase cantly influenced by its visual appearance and physical design (Li et al.,
intention as the response component (R) within the Palestinian market 2024). This is because visual aesthetics play a crucial role in shaping
context. This application of the SOR framework allows us to systemat­ consumer perceptions and behaviors, impacting their purchase in­
ically analyze how platform characteristics shape user psychological tentions and overall engagement with the platform (Marmat, 2023;
states and subsequent purchasing behaviors in an understudied market Ramezani Nia and Shokouhyar, 2020). The design elements of a web­
environment, while contributing both theoretical advancement and page can enhance user experience by providing aesthetic pleasure,
empirical insights from an emerging market perspective. which in turn can lead to increased consumer satisfaction and loyalty
(Ramezani Nia and Shokouhyar, 2020). The integration of visual appeal,
2.4. Research model and hypotheses user-friendly navigation, and interactive features can create a more
engaging and satisfying user experience, which in turn can positively
In this section, we present a conceptual model and study hypotheses influence consumer behavior. This relationship is supported by multiple
based on the literature reviewed and a reflection made of the study studies that highlight the importance of website design and social

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F. Herzallah et al. Journal of Open Innovation: Technology, Market, and Complexity 11 (2025) 100635

Fig. 1. Conceptual Model.

commerce attributes in driving SCCE and purchase intention (Busalim to develop a positive platform-related sentiment or a belief that other
et al., 2024; Marmat, 2023; Permell and Pacheco, 2024). Thus, this study customers will help improve their repurchase decisions (Mubdir et al.,
proposes: 2025). Prior research suggests that SCCE positively affects s-commerce
customers’ repurchase intention (Lim et al., 2020; Majeed et al., 2022;
H3. : There is a positive relationship between WEBA and SCCE.
Simbolon and Law, 2022). Building on this empirical evidence, it can be
argued that SCCE in s-commerce has become a focal point for businesses
2.4.4. Traditional word-of-mouth (TWOM) and Customer Engagement
seeking to build long-term consumer relationships. Thus, we propose the
(SCCE)
following hypothesis
When purchasing from online sellers, consumers engage in
information-seeking behavior to reduce uncertainty and make informed H5. : There is a positive relationship between SCCE and REPI.
decisions (Herzallah and Al-Sharafi, 2025; Shah and Paul, 2020). This
behavior is driven by the need to gather comprehensive information
2.5. The dynamics of open innovation in social commerce
about both the product and the seller, which helps mitigate perceived
risks associated with online transactions (Al-Adwan and Yaseen, 2023).
Open innovation represents a paradigm shift from traditional, closed
The process of information seeking is multifaceted, involving various
models, establishing a holistic approach to innovation management that
strategies and sources, both online and offline, to ensure a satisfactory
systematically encourages organizations to investigate opportunities
purchase experience (Shah and Paul, 2020). This information can be
from both internal and external sources (Merritt and Zhao, 2022; Sir­
obtained online from s-commerce webpages because they enable pre­
iwong et al., 2024). Within the contemporary digital landscape, social
vious customers to make recommendations and provide reviews and
commerce (s-commerce) platforms have emerged as critical enablers of
ratings (Laradi et al., 2024).
open innovation dynamics. They function as ecosystems where sellers,
TWOM is recognized as a significant influence on online SCCE and
particularly small and medium enterprises (SMEs), can access external
purchase decisions (Laradi et al., 2024). This influence is attributed to
knowledge, collaborate with customers, and co-create value through
the strength of personal relationships and the perceived trustworthiness
social interactions (Ni and Wang, 2025; Yuana et al., 2021).
of offline interactions (Li and Du, 2017). TWOM, especially from friends
The integration of social interactions with commercial activities
and trusted individuals, can provide a more persuasive and credible
creates unique conditions for these processes. S-commerce platforms
source of information compared to online WOM, which often lacks the
facilitate the flow of external knowledge through customer feedback and
personal connection and trust inherent in face-to-face interactions
peer recommendations, embodying the "outside-in" dimension of open
(Chawdhary and Weber, 2025). This dynamic is crucial in understand­
innovation where enterprises actively absorb external insights to
ing how TWOM can impact online SCCE. From this discussion, it can be
enhance their innovation capabilities (Ni and Wang, 2025). This
argued that the quality of TWOM of friends and trusted people regarding
customer engagement represents a form of collective intelligence,
an online seller can influence s-commerce customers’ engagement.
generating valuable insights for product development and business
Thus, we propose the following hypothesis
model innovation. This aligns with social open innovation principles,
H4. : There is a positive relationship between TWOM and SCCE. where innovation emerges through social networks and
community-driven collaboration rather than formal research and
2.4.5. Customer Engagement (SCCE) and Repurchase Intention (REPI) development processes (Davies et al., 2019).
The consequences of s-commerce-based SCCE include increased Ni and Wang (2025) argue that for SMEs in emerging markets like
customer satisfaction, loyalty, co-creation, electronic word of mouth China, s-commerce platforms provide crucial access to open innovation
(WOM), repurchase intention, feedback and collaboration, and website opportunities that might be unavailable due to resource constraints.
stickiness (Busalim et al., 2024). These outcomes are facilitated by the These platforms help SMEs navigate complex market environments and
unique attributes of s-commerce platforms, such as community inter­ make decisions under conditions of bounded rationality by providing
action, collaboration, and social dynamics, which foster a more accessible information and social validation (Yun et al., 2020). The
engaging and interactive shopping experience (Nadeem et al., 2021). engagement of customers through s-commerce is a form of innovation
One such positive outcome is repurchase intention, which refers to a culture cultivation, where enterprises build innovation-oriented re­
customer’s intention to rebuy a product or service from an s-commerce lationships with their customer base to drive competitive advantage
supplier (Busalim et al., 2024). s-commerce-based SCCE are also likely (Merritt and Zhao, 2022; Yun et al., 2020).

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F. Herzallah et al. Journal of Open Innovation: Technology, Market, and Complexity 11 (2025) 100635

However, adopting open innovation also presents complexity chal­ (2025) and Lin (2024). Service Quality was measured with 3 items from
lenges, particularly for SMEs. Managing the dynamics between tradi­ Chan and Gao (2021) and Charles and Kanani (2025). Webpage
tional business practices and new social commerce approaches requires attractiveness was measured with 3 items adapted from Charles and
a careful balance, as the "cost of open innovation" can overwhelm an Kanani (2025) and Shen et al. (2019). Traditional word-of-mouth was
organization if not properly managed (Yun et al., 2020). The findings of measured with 3 items from the research of Charles and Kanani (2025)
this study, therefore, contribute to understanding how specific platform and Farooq et al. (2024). SCCE was measured with 4 items adapted from
attributes facilitate these open innovation processes, helping B2C SMEs Ho and Chung (2020) and Shah et al. (2024). Finally, Repurchase
in the specific context of Palestine leverage digital channels for sus­ intention was measured with 4 items adapted from Miao et al. (2022)
tainable growth. and Wang and Chu (2020). In all the cases, as shown in Tables 4, 5-point
Likert-type scales were used (1 strongly disagree; 5 strongly agree).
3. Research methodology Given that the original scales were developed in English while the target
population spoke Arabic, all measurement items underwent a rigorous
3.1. Sampling and data collection translation process. First, the questionnaire was translated from English
to Arabic by a certified professional translation service. Subsequently,
Our investigation employed a one-time cross-sectional data gath­ back-translation from Arabic to English was performed by an indepen­
ering strategy to capture relevant variables simultaneously. We focused dent translator to verify semantic equivalence and ensure the preser­
on Palestinian consumers who actively utilize social media platforms for vation of original scale meanings. The back-translated version was
purchasing activities and have reached the age of majority (18 years or compared with the original English scales to identify and resolve any
older), ensuring participants possessed both the legal capacity and discrepancies, ensuring cross-linguistic validity.
technological access necessary for engaging in digital commerce trans­
actions. The participant recruitment process utilized non-probability 3.3. Analytical procedures
convenience sampling techniques through digital channels. Data
collection occurred via a web-based questionnaire developed and To examine causal relationships between theoretical constructs,
distributed using “Microsoft forms”. Table 3 presents the demographic structural equation modeling was selected—a method capable of
characteristics of the respondents. analyzing complex variable interactions (Hair et al., 2022). Within SEM
To address potential systematic response bias concerns, first, we frameworks, two approaches exist: covariance-based (CB-SEM) and
conducted Harman’s single-factor assessment. Results indicated no sig­ partial least squares (PLS-SEM) (Hair et al., 2020; Sarstedt et al., 2022).
nificant common method bias (CMB), as the primary factor explained PLS-SEM was prioritized for its suitability in exploratory theoretical
less than the critical threshold of 50 % variance (Podsakoff et al., 2003). modeling and handling predictive relationships, and has been widely
Second, as recommended by Kock (2015), we employed variance used by previous studies in the field (Al-Adwan et al., 2022; Al-Adwan
inflation factor (VIF) values as an additional statistical remedy for CMB and Yaseen, 2023; Alhumud and Elshaer, 2024; F. Herzallah et al.,
detection. The inner VIF values for all constructs ranged from 1.000 to 2025). Analyses were conducted using Smart-PLS software.
2.208, which are well below the suggested threshold of 3.3 (Hair et al.,
2022), further confirming the absence of CMB in this study. The final 3.4. Model evaluation stages
sample comprised 238 valid and complete responses, substantially
exceeding the minimum required sample size of 136 participants as The PLS-SEM process involved two phases. First, the measurement
determined through statistical power analysis using G-Power software model was validated by testing construct reliability and accuracy. In­
(assuming 80 % power). This sample size satisfies established method­ dicator loadings, composite reliability (CR), cronbach’s alpha (CA), and
ological standards for management research in social sciences, where average variance extracted (AVE) were calculated to verify internal
statistical power of 0.80 is considered the minimum acceptable consistency and convergent validity (Hair et al., 2022). Discriminant
threshold (Hair et al., 2018). validity was assessed using two approaches: the Fornell-Larcker crite­
rion (comparing AVE square roots to construct correlations) and
heterotrait-monotrait (HTMT) ratios (Henseler et al., 2009, 2015).
3.2. Questionnaire design and validation Second, the structural model tested hypothesized relationships.
Collinearity was first examined via variance inflation factors (VIFs),
The constructs of the model were measured through reflective ensuring values remained below recommended thresholds. Predictive
measurement scales validated in previous research. Content informa­ power was evaluated using R² values, with scores ≥ 0.2 deemed
tiveness were measured using 4 items adapted from Charles and Kanani acceptable (Cohen, 1988). Path coefficients, significance levels
(t-values, p-values), and 95 % bias-corrected confidence intervals were
Table 3 calculated through 5000 bootstrap iterations. Model fit was measured
Demographic Characteristics of Respondents. via the standardized root mean square residual (SRMR), quantifying
Characteristic Category Frequency Percentage discrepancies between observed and predicted correlations (Henseler
(%) et al., 2015).
Gender Male 117 49.2
Female 121 50.8 4. Findings
Education Level Diploma or below 71 29.8
Bachelor’s degree 132 55.5
Postgraduate 35 14.7
4.1. Measurement model assessment
studies
Age 18–24 years 63 26.5 Construct validity and reliability were tested using four benchmarks,
24–30 years 89 37.4 which are indicator loadings, AVE, CR, and CA. As shown in Table 5, the
30–40 years 55 23.1
loadings for all items exceeded the recommended value of 0.708, except
Above 40 years 31 13.0
Social Media Less than 1 year 35 14.7 (REPI3), thus meeting recommended thresholds. AVE scores
Experience 1–3 years 66 27.7 (0.816–0.897) surpassed the 0.50 minimum, while CR and CA values
3–5 years 110 46.2 consistently topped 0.70, confirming strong scale reliability (Hair et al.,
More than 5 years 27 11.3 2022). Furthermore, as shown in Table 6, discriminant validity was
N 238
upheld via HTMT ratios below 0.85 (Henseler et al., 2015) As for

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F. Herzallah et al. Journal of Open Innovation: Technology, Market, and Complexity 11 (2025) 100635

Table 4
Questionnaire Items.
Construct Items Source

Content COIN1 Social commerce sellers provide sufficient information about product delivery to customers. (Charles and Kanani, 2025; Lin, 2024)
Informativeness COIN2 Social commerce sellers publish sufficient contact information on their social media pages.
COIN3 Social commerce sellers publish numerous clear pictures of the available products.
COIN4 Overall, the information provided on social commerce sellers’ pages is very helpful in making
purchasing decisions.
Service Quality SERQ1 Social commerce sellers respond quickly to customer inquiries. (Chan and Gao, 2021; Charles and
SERQ2 Social commerce sellers always ensure that customers are informed about all product details. Kanani, 2025)
SERQ3 Social commerce sellers provide additional information if customers are not satisfied.
Webpage Attractiveness WEBA1 It is easy to find the information I need on social commerce sellers’ pages. (Charles and Kanani, 2025; Shen et al.,
WEBA2 Product images on social commerce sellers’ pages are well-organized. 2019)
WEBA3 It is very easy to navigate social commerce sellers’ pages.
Traditional word-of- TWOM1 Most users on social media provide positive opinions about their experience purchasing from (Charles and Kanani, 2025; Farooq
mouth sellers on these platforms. et al., 2024)
TWOM2 Most of my trusted friends provide positive opinions about purchasing from sellers on social
media.
TWOM3 Most of my friends provide positive opinions about the quality of products from sellers on social
media.
Customer Engagement SCCE1 Using social commerce platforms is fun. (Ho and Chung, 2020; Shah et al.,
SCCE2 Anything related to social commerce platforms grabs my attention. 2024)
SCCE3 Social commerce platforms enable sharing information with others.
SCCE4 I enjoy spending time browsing products and seller pages on social media.
Repurchase Intention REPI1 I intend to continue purchasing products from sellers on social media in the future. (Miao et al., 2022; Wang and Chu,
REPI2 I recommend others to purchase from sellers on social media. 2020)
REPI3 I always look forward to learning about new products offered by sellers on social media.
REPI4 I want to receive regular notifications and recommendations from sellers on social media about
new products.

Table 5 Table 6
Measurement Model. Results of discriminant validity.
Variable Indicator Loading AVE CA CR Heterotrait-monotrait ratio (HTMT)

Content Informativeness COIN1 0.755 0.833 0.889 0.667 Constructs COIN TWOM REPI SCCE SERQ WEBA
(COIN) COIN2 0.858 Content ​ ​ ​ ​ ​ ​
COIN3 0.829 Informativeness
COIN4 0.821 (COIN)
Traditional Word-of-mouth TWOM1 0.877 0.859 0.914 0.779 Traditional word-of- 0.774 ​ ​ ​ ​ ​
(TWOM) TWOM2 0.891 mouth (TWOM)
TWOM3 0.880 Repurchase Intention 0.564 0.600 ​ ​ ​ ​
Repurchase Intention (REPI) REPI1 0.870 0.823 0.894 0.738 (REPI)
REPI2 0.860 S-Commerce Customer 0.610 0.565 0.505 ​ ​ ​
REPI4 0.849 Engagement (SCCE)
S-Commerce Customer SCCE1 0.863 0.897 0.928 0.762 Service Quality (SERQ) 0.709 0.774 0.603 0.562 ​ ​
Engagement (SCCE) SCCE2 0.873 Webpage Attractiveness 0.459 0.466 0.646 0.364 0.671 ​
SCCE3 0.896 (WEBA)
SCCE4 0.860 Fornell-Larcker criterion
Service Quality (SERQ) SERQ1 0.855 0.816 0.890 0.730 ​ COIN TWOM REPI SCCE SERQ WEBA
SERQ2 0.866 Content 0.817 ​ ​ ​ ​ ​
SERQ3 0.841 Informativeness
Webpage Attractiveness WEBA1 0.851 0.836 0.901 0.754 (COIN)
(WEBA) WEBA2 0.819 Traditional word-of- 0.658 0.883 ​ ​ ​ ​
WEBA3 0.931 mouth (TWOM)
Repurchase Intention 0.470 0.505 0.859 ​ ​ ​
(REPI)
Fornell-Larcker criteria, the diagonal AVE roots exceeded S-Commerce Customer 0.534 0.504 0.443 0.873 ​ ​
cross-construct correlations (Fornell and Larcker, 1981). Engagement (SCCE)
Service Quality (SERQ) 0.588 0.648 0.498 0.490 0.854 ​
Webpage Attractiveness 0.393 0.400 0.541 0.328 0.553 0.868
4.2. Structural model and hypothesis analysis (WEBA)

The assessment of the Structural Model (inner model) was conducted

after the analysis of the outer model was completed. Collinearity was Table 7
examined to ensure that the path coefficients did not produce biased Path Results of Research Model Hypotheses.
results. The variance in the inflation factor (VIF) was calculated to # The Relations O T P Result VIF
examine to check for collinearity. As shown in Table 7, the VIF values
H1 COIN ➡ SCCE 0.296 3.616 0.000 Supported 1.927
ranged from 1 to 2.208 which meets the requirement of being less than 5 H2 SERQ ➡SCCE 0.178 2.603 0.009 Supported 2.208
(Hair et al., 2022). We then proceeded to assess the structural model and H3 WEBA ➡SCCE 0.043 0.693 0.488 Not Supported 1.455
hypothesized relationships. H4 TWOM ➡SCCE 0.177 2.082 0.037 Supported 2.161
Next, the model’s in-sample explanatory power was assessed by H5 SCCE ➡ REPI 0.443 7.759 0.000 Supported 1.000

examining the R2 values of the endogenous variables. According to

Cohen (1988), the R2 values from 0.02 to 0.12 are small, while those
from 0.12 to 0.25 are moderate, and those from 0.25 to 1 are substantial.

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F. Herzallah et al. Journal of Open Innovation: Technology, Market, and Complexity 11 (2025) 100635

Fig. 2. The results of the research model.

As shown in Fig. 2, the S-commerce customer engagement (SCCE) had hypotheses are discussed in more details below.
an R2 value of 0.348, whilst perceived repurchase intention (REPI) had Initially, the significant positive influence of content informativeness
an R2 value of 0.197, which translates into substantial and moderate on customer engagement aligns with previous studies by Lee and Park
explanatory power of the model. (2022). Moran et al. (2020), and Vlachvei et al. (2022), who found that
The analysis of direct effects revealed that 4 out of 5 hypothesized rich, varied, and comprehensive information enhances customer
relationships were statistically significant (p < 0.05), as presented in engagement across digital platforms. In the social commerce context,
Table 7 and Fig. 2. Specifically, SCCE was positively influenced by this finding suggests that customers place high value on detailed product
content informativeness (COIN) (β = 0.296, t = 3.616, p < 0.05), ser­ information, accurate descriptions, and sufficient visual representations
vice quality (SERQ) (β = 0.178, t = 2.603, p < 0.05), and traditional when making purchase decisions. Notably, content informativeness
word-of-mouth (TWOM) (β = 0.177, t = 2.082, p < 0.05). Therefore, emerged as the strongest predictor among the examined attributes,
H1, H2, and H4 are supported. However, webpage attractiveness indicating its critical role in fostering engagement within social com­
(WEBA) (β = 0.043, t = 0.693, p = 0.488) showed no significant effect merce platforms.
on SCCE. Hence, it is considered this hypothesis (H3) is not supported. Furthermore, the positive relationship between service quality and
Furthermore, SCCE demonstrated strong positive effects on repurchase customer engagement corroborates findings from (Amro et al., 2025;
intention (REPI) (β = 0.443, t = 7.759, p = 0.000). Therefore, H5 is Fan et al., 2022; Ganie and Bhat, 2023). This result highlights that
supported. responsive customer service, prompt addressing of inquiries, and pro­
active support significantly enhance user engagement in social com­
5. Discussion merce environments. When sellers demonstrate reliability and
responsiveness, they effectively reduce perceived risks associated with
This study aimed to examine how specific social commerce attributes online transactions, thereby fostering greater trust and willingness to
influence customer engagement and ultimately repurchase intention engage with the platform. Moreover, traditional word-of-mouth also
through the lens of the Stimulus-Organism-Response (SOR) framework. significantly influenced customer engagement, consistent with research
The study’s finding demonstrated that content informativeness, service by Laradi et al. (2024) and Li and Du (2017). This finding underscores
quality, and traditional word-of-mouth all positively and significantly the enduring power of traditional word-of-mouth recommendations in
influenced customer engagement in social commerce platforms, sup­ driving online engagement behaviors. In the Palestinian context, where
porting hypotheses H1, H2, and H4. Additionally, customer engagement community ties are often strong and interpersonal trust is highly valued,
strongly predicted repurchase intention, confirming H5. However, offline recommendations from trusted sources such as family, col­
contrary to our expectations, webpage attractiveness did not signifi­ leagues, and friends appear to substantially impact users’ willingness to
cantly impact customer engagement, leading to the rejection of H3. The engage with social commerce platforms.

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F. Herzallah et al. Journal of Open Innovation: Technology, Market, and Complexity 11 (2025) 100635

Surprisingly, webpage attractiveness did not significantly affect 6.2. Practical implications
customer engagement, contradicting findings from previous studies by
Busalim et al. (2024), Marmat (2023), Ramezani Nia and Shokouhyar Our findings offer valuable insights for social commerce practi­
(2020). This unexpected result might be explained by several contextual tioners, particularly those operating in markets similar to Palestine.
factors. First, in developing markets like Palestine, functional aspects of First, the strong influence of content informativeness suggests that
social commerce platforms (such as information quality and service sellers should prioritize providing comprehensive, accurate, and visu­
responsiveness) may take precedence over aesthetic considerations. ally supported product information. This includes detailed descriptions,
Second, as social commerce predominantly operates through established multiple high-quality images, sizing information, material specifica­
social media platforms (e.g., Facebook, Instagram) that already have tions, and transparent pricing and delivery details. Social commerce
standardized interfaces, the visual differentiation between sellers may sellers should ensure that all essential information is easily accessible on
be limited, reducing the relative importance of webpage attractiveness. their pages, as this significantly impacts customer engagement. Second,
Third, given limited internet infrastructure in some areas, users might the importance of service quality highlights the need for responsive and
prioritize informational content and service quality over visually com­ reliable customer support. Social commerce sellers should establish
plex or aesthetically pleasing interfaces that could potentially slow clear communication channels, respond promptly to inquiries, provide
loading times. Fourth, this prioritization of functional over aesthetic post-purchase support, and address customer concerns efficiently.
attributes may extend beyond market-level characteristics to specific Implementing service quality standards and training staff to maintain
user segments. Users with lower digital literacy may prioritize clear, consistent service levels could significantly enhance customer engage­
information-rich interfaces over visually complex designs that could ment on social commerce platforms.
create navigation confusion. Similarly, users operating devices with Third, the significant effect of traditional word-of-mouth un­
limited processing power or data constraints may favor streamlined, derscores the continued relevance of traditional marketing approaches
fast-loading content over aesthetically elaborate presentations that even in digital contexts. Social commerce businesses should actively
consume bandwidth and processing resources. encourage satisfied customers to share their positive experiences within
Finally, the strong positive relationship between customer engage­ their social circles, potentially through referral programs or community-
ment and repurchase intention aligns with findings from Lim et al. building initiatives. Fourth, the non-significant effect of webpage
(2020), Majeed et al. (2022), Simbolon and Law (2022). This confirms attractiveness suggests that social commerce sellers in contexts similar
the critical role of engagement as a precursor to sustained purchasing to Palestine might benefit more from investing resources in improving
behavior in social commerce contexts. When customers actively engage information quality and service standards rather than focusing exten­
with content, interact with sellers, and immerse themselves in the social sively on visual aesthetics. While maintaining a clean, functional
shopping experience, they develop stronger intentions to return and interface remains important for usability, elaborate visual designs might
make subsequent purchases. not yield proportionate returns in terms of customer engagement in this
specific market context.
6. Implications Finally, the strong relationship between customer engagement and
repurchase intention confirms that fostering engagement is essential for
6.1. Theoretical implications building sustainable business models in social commerce. Practitioners
should implement engagement-focused strategies, such as interactive
This study offers several significant contributions to the social content, community-building features, and personalized communica­
commerce literature, particularly in the context of developing markets. tion, to encourage customers to actively participate in the social shop­
First, by applying the Stimulus-Organism-Response (SOR) framework to ping experience, thereby increasing the likelihood of repeat purchases.
examine specific social commerce attributes, we validate this theoretical
approach in understanding the mechanisms through which platform 7. Limitations and future research directions
attributes influence customer engagement and repurchase intention.
The significant relationships identified in our model affirm the appli­ Despite its contributions, this study has several limitations that
cability of SOR framework in explaining social commerce behavior in provide opportunities for future research. First, our cross-sectional
the Palestinian market. Second, our findings extend the current under­ design captures relationships at a specific point in time, limiting our
standing of customer engagement antecedents in social commerce. ability to observe how these relationships might evolve. Future studies
While previous research has broadly examined social commerce con­ could adopt longitudinal approaches to examine how changes in social
structs and their impact on engagement (Busalim et al., 2024; Moham­ commerce attributes affect engagement and repurchase behaviors over
mad et al., 2024), our study specifically identifies the relative extended periods. Second, our use of convenience sampling and focus on
importance of different attributes. The stronger effect of content infor­ Palestine offers important insights into an understudied context but
mativeness compared to service quality and traditional word-of-mouth limits the statistical and geographical generalizability of findings. While
provides a more nuanced understanding of what drives engagement in convenience sampling enabled access to active social commerce users
social commerce environments, particularly in developing markets. across Palestinian social media platforms and was appropriate for this
Third, our results challenge existing assumptions about the univer­ exploratory investigation, future research should employ probability
sality of visual aesthetics in driving online engagement. The non- sampling methods to enhance representativeness. Additionally, our
significant effect of webpage attractiveness contradicts findings of pre­ single-country focus potentially limits generalizability to other markets.
vious studies (Marmat, 2023; Ramezani Nia and Shokouhyar, 2020), Future research could adopt comparative approaches examining how
suggesting that the importance of design elements may vary across social commerce dynamics might differ across the Middle East and North
different E-commerce types. Finally, our research provides empirical Africa (MENA) countries with varying levels of digital infrastructure,
support for the relationship between customer engagement and economic development, and cultural orientations.
repurchase intention in social commerce, reinforcing the strategic Third, while our model explains a substantial portion of variance in
importance of engagement as a key performance metric. This finding customer engagement (34.8 %), customer engagement explained only a
aligns with the broader literature on customer engagement (Nauen and moderate portion of variance in repurchase intention (19.7 %).
Enke, 2022; So et al., 2024) and provides additional evidence from the Although this falls within Cohen’s (1988) established moderate range,
Palestinian context with potential implications for similar developing we acknowledge that this level of explained variance may be considered
markets where functional attributes may take precedence over aesthetic modest in marketing and behavioral research contexts, indicating that a
considerations. significant proportion of the variance (80.3 %) remains unexplained.

9
F. Herzallah et al. Journal of Open Innovation: Technology, Market, and Complexity 11 (2025) 100635

Furthermore, our focus on customer engagement as the sole organism analysis, Conceptualization. Fadi Herzallah: Writing – original draft,
variable may explain the modest explained variance in repurchase Supervision, Data curation, Conceptualization.
intention. Previous SOR applications as shown Table 2 in social com­
merce have employed diverse organism variables including trust con­ Declaration of generative AI and AI-assisted technologies in the
structs (Imanuddin and Handayani, 2025; Yang et al., 2025), emotional writing process
states (Y. Liu et al., 2023), cognitive processing variables (Chandraa
et al., 2024), and experience-related factors (Hewei and Youngsook, Generative AI was used solely to improve language and grammar.
2022). The inclusion of multiple organism variables in future research, The authors reviewed and edited all content as needed and take full
particularly trust-related constructs which previous studies have shown responsibility for the content of the publication.
to be crucial mediators in social commerce contexts, may substantially
improve the model’s explanatory power
Fourth, our study focused exclusively on seller-level attributes, Declaration of Competing Interest
which limits the comprehensive understanding of all environmental
stimuli that shape customer engagement in social commerce contexts. The authors declare that they have no known competing financial
While our investigation of content informativeness, service quality, interests or personal relationships that could have appeared to influence
webpage attractiveness, and traditional word-of-mouth provides valu­ the work reported in this paper.
able insights for individual sellers, customers also interact extensively
with platform-level features such as interface design, recommendation Acknowledgement
algorithms, security systems, and overall platform aesthetics that vary
significantly across platforms (Facebook, Instagram, TikTok Shop). The The authors would like to thank Palestine Technical Uni­
unexpected non-significance of webpage attractiveness may partially versity—Kadoorie for their financial support in conducting this
reflect this limitation, as consumers may make platform choices based research.
on overall platform design and functionality rather than individual seller
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