Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21070206

Authors: Tingting Liu Joon Koh

With the rapid advancement of digital technology, the self-service model has emerged, introducing a new work model known as digital shadow work (DSW). In this model, consumers perform tasks traditionally performed by employees, such as item scanning and self-checkout, without compensation. While this optimizes service processes and reduces business costs, it raises concerns about consumer rights, work value, and business sustainability. This study explores the psychological factors that affect consumer participation in DSW within self-service environments. Using a grounded theory approach and semi-structured interviews, the study reveals key psychological drivers under the dual-system framework. This study’s findings indicate that habitual behavior, impulsivity, time pressure, technological dependence, social identification, and delayed gratification significantly affect participation in DSW. Notably, the intuitive system (System 1) plays a dominant role in decision-making, leading consumers to make quick, automatic choices, often leaving them unaware of the work involved. By identifying these psychological factors, this research increases consumer awareness of DSW, promoting self-protection in self-service contexts. Additionally, understanding decision-making psychology provides essential insights for companies in non-face-to-face self-service technologies, supporting sustainable business practices.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21070205

Authors: Kai Liu Zhibin Xing Haizhang Chen

Digital game consumption increasingly unfolds across video platforms, comment sections, and community discussions, where platform visibility, creator-mediated information, interaction metrics, and commercialization signals shape users’ expectations. In platform-mediated digital commerce, visible interaction may indicate information use, cultural resonance, payment concern, or consumption-related complaint rather than uniformly positive engagement. Using self-determination theory as a motivational lens within a platform-mediated consumer-behavior framework, this study examines whether platform content cues, public comment responses, and user perceptions provide convergent evidence on differentiated engagement meanings. The empirical setting is Bilibili content related to the Chinese wuxia role-playing game Where Winds Meet. The analysis combines 1164 public videos, 19,919 hot comments, and a content-exposure-anchored survey of 564 valid respondents. The results show differentiated patterns: functional information cues correspond to saving-oriented engagement and useful responses; cultural-aesthetic cues correspond to supportive interaction and cultural responses; and payment-mechanism and experience-problem cues correspond to payment concerns and complaints. The survey further shows that perceived information value, cultural/experiential connection, perceived monetization fairness, consumer autonomy in spending decisions, and perceived monetization risk are associated with continued engagement intention. These findings suggest that engagement quality should be interpreted through platform-mediated consumer relationships rather than interaction volume alone, while recognizing that hot-comment evidence reflects a platform-visible layer of user response rather than the full distribution of comments or player attitudes.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21070204

Authors: Ming-Hsuan Wu

Drawing on signaling theory and a relational perspective, this study examines how perceived influencer credibility is associated with e-loyalty intentions in influencer-mediated social commerce. Rather than claiming that each individual path is theoretically unexpected, this study positions its contribution in specifying a conditional signal-to-relationship process. Specifically, perceived influencer credibility is conceptualized as a credibility-based digital promotional signal, brand trust and customer engagement are examined as sequential relational mechanisms, and perceived brand authenticity is positioned as an identity-consistency boundary condition in the customer engagement–e-loyalty intention relationship. Using survey data from 372 consumers with influencer-mediated social commerce experience, the data were analyzed using partial least squares structural equation modeling (PLS-SEM). The results show that perceived influencer credibility is positively associated with brand trust, brand trust is positively associated with customer engagement, and customer engagement is positively associated with e-loyalty intentions. The bootstrapped serial indirect association through brand trust and customer engagement is significant, indicating a trust–engagement pathway linking influencer-mediated promotional credibility to e-loyalty intentions. Perceived brand authenticity also positively moderates the customer engagement–e-loyalty intention relationship. Descriptive conditional indirect estimates further suggest that the indirect association through brand trust and customer engagement is stronger at higher levels of perceived brand authenticity; however, this conditional indirect pattern is interpreted conservatively because bootstrapped confidence intervals for the low and high conditional estimates were not directly available. These findings extend influencer marketing research by shifting attention from isolated credibility effects to a theory-driven process explaining how influencer credibility is associated with e-loyalty intentions through trust, engagement, and authenticity-based boundary conditions.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21070203

Authors: Mengqi Sun Haitao Chen Hao Chen

Social interaction plays an increasingly important role in facilitating consumption, and many e-commerce platforms have incorporated peer information into product interface design. Given the limited attention paid to action-based information cues, this study proposes repeat purchase action as an information cue and examines its impact on user purchase intention. Drawing on social learning theory, we developed a research model and conducted two online experiments on Credamo, a professional online survey platform in China. The research model was empirically tested using bootstrapping-based mediation analysis. The results showed that both purchase action and repeat purchase action significantly increased user purchase intention. In addition, the impact of repeat purchase action on purchase intention was mediated by trust expectation, whereas purchase action did not elicit users’ trust expectation. These findings add to the literature on information cues in e-commerce and extend the theoretical explanatory power of social learning theory. This study also provides managerial implications for e-commerce platforms and sellers in implementing effective product interface information design and selection strategies.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21070202

Authors: Jinjiang Yan Usama Khaliq Nosherwan Khaliq Anita Tangl

Purpose: This study explores the nonlinear influences of three organizational capabilities, including Cultural Adaptability (CA), Service Efficiency (SE), and Brand Commitment (BC), on Perceived Fairness (PF) and their subsequent effects on Customer Retention (CR) and Purchase Decision (PD). It also analyses the moderating effect of Perceived Social Norms (PSN) in this context. Design/Methodology/Approach: A two-wave time-lagged design was used to increase temporal precedence and reduce common-method bias, and 500 consumers in China and Pakistan were sampled. The hypothesized curvilinear associations were tested using Structural Equation Modeling (SEM). Findings: CA, SE, and BC have a positive influence on PF, though their relationships follow an inverted U-shaped pattern. PF shows positive correlations with CR and PD, and PSN enhances the relationship between PF and customer outcomes. Originality: The research adds value to Social Exchange Theory and Commitment–Trust Theory by demonstrating that organizational capabilities may yield diminishing returns of fairness and thus disproves the more-is-better linear relationships in customer relationship management.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21070201

Authors: Jiaxiang Hu Caoyu Fan Lukai Zhang

This study examines how live-streaming cues influence impulsive purchase intention in fresh-fruit e-commerce, where consumers face substantial quality uncertainty and limited opportunities for pre-purchase inspection. Drawing on the Stimulus–Organism–Response (S-O-R) framework, we examine five stimuli—anchor professionalism, anchor interactivity, visual attractiveness, price discount, and scarcity—and test whether perceived value (cognitive) and positive emotions (affective) operate as parallel mediators. Based on survey data from 353 Chinese consumers, the results show that anchor professionalism, anchor interactivity, price discount, and scarcity are positively associated with impulsive purchase intention both directly and indirectly through perceived value and positive emotions, whereas visual presentation follows a different pattern. Contrary to the common assumption that vividness primarily triggers emotional impulse, visual attractiveness does not exhibit a robust direct effect on purchase intention; instead, its influence is transmitted dominantly through cognitive perceived value rather than affective positive emotions. This finding suggests that, in high-uncertainty perishable categories, vivid presentation is more consequential when it helps consumers evaluate product value than when it merely stimulates affective reactions. The study offers targeted implications for S-O-R theory and provides practical guidance for platform design and promotional disclosure in real-time e-commerce.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21070200

Authors: Xue Pan Xin Xia Lei Hou

Short videos have become a dominant format in digital commerce, enabling brands to engage consumers and drive purchases through dynamic and visually rich content. This highlights the need for a more nuanced understanding of visual framing strategies, that is, what elements are shown and how they are presented. Drawing on Cognitive Load Theory, this study explores the impact of visual compositional framing strategies and their dynamics on consumer engagement and sales. Applying a CNN-based deep learning model, 249,043 images (video frames) extracted from 3426 book-related short sales videos on Douyin are classified into one of three categories: functional, contextual, or social, according to the visual composition of the frame. Further econometric modeling reveals distinct effects of such framing categories: functional framing is positively associated with both engagement and sales, contextual framing relates to higher sales only, while social framing relates positively to engagement but negatively to sales. From a dynamic perspective, frequent transitions between framing types within a short video increase visual complexity, which reduces both engagement and sales and moderates the effects of specific framing strategies. These findings advance theoretical understanding of visual framing in dynamic media environments and offer practical insights for designing more effective short video content.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21070199

Authors: Montchai Pinitjitsamut

This study examines motivational and capability barriers to internet non-adoption in Thailand’s near-saturated digital economy. Using the 2025 Q4 ICT Household Survey conducted by Thailand’s National Statistical Office, the analysis focuses on 20,633 adult non-adopters who report either motivational or capability-related barriers. The dependent variable distinguishes capability non-adoption, defined as lack of skill or awareness, from motivational non-adoption, defined as lack of perceived need or privacy/security concerns. Weighted logistic regression with normalised population weights, PSU-clustered robust standard errors, and average marginal effects is used to estimate associations between household ICT access, age, education, employment, smartphone access, and barrier type. Motivational barriers account for 56.2% of the two-category non-adopter population and capability barriers for 43.8%. Although motivational reasons are the more common, household ICT access is positively—if modestly—associated with capability rather than motivational barriers (average marginal effect +1.7 percentage points): capability-constrained non-adopters are concentrated in connected households, the compositional signature predicted by the second-level digital divide. Age does not significantly moderate this association. Among older non-adopters, education, employment, and smartphone access are negatively associated with capability barriers, while household ICT access is not. The findings suggest that in post-access digital economies, household connectivity is insufficient for digital market inclusion; individual-level skills and device access become central to expanding effective digital market reach.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21070198

Authors: Yiming Li Mingyao Sun Fang Wang Giri Kumar Tayi

Global retail e-commerce sales have surged, yet product fit uncertainty remains a significant challenge, leading to rising product return rates. To address consumer concerns about return shipping costs, major Chinese online retail platforms have introduced return shipping insurance (RSI). Retailers can choose between Retailer-RSI (RRSI), which is provided by the retailer, and Customer-RSI (CRSI), which is purchased by consumers. Despite these options, information asymmetry causes insurers to assess return rates with bias—referred to as managerial confidence bias. Consequently, platforms are increasingly partnering with insurers to enhance their RSI offerings. This study develops a game-theoretical model to examine the dynamics between a platform and an insurer, as well as the impact of managerial confidence bias on RSI strategies. Our analysis reveals that the platform–insurer relationship is crucial in determining the optimal RSI strategy. Under an independent insurer, RSI is viable only if the insurer underestimates product return rates (i.e., exhibits overconfidence bias); RRSI is preferred if the bias is sufficiently strong, whereas CRSI is chosen otherwise. In contrast, under a dependent insurer, CRSI is favored by the retailer only when its return handling costs are substantially high; otherwise, RRSI is preferred. Furthermore, RSI consistently increases consumer surplus by reducing return hassle costs while only mildly raising the product price. However, the independent insurer’s bias leads to its own profit loss, resulting in a “loss–win–win–win” scenario across stakeholders. In contrast, the dependent insurer, supported by platform subsidies, can yield a “win–win–win–win” outcome that aligns stakeholder interests and enhances long-term platform benefits.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21070197

Authors: Omar Munther Nusir Che Aniza Che Wel Siti Ngayesah Ab Hamid

This study examines how consumers respond to personalized advertisements that appear to be derived from prior conversations with generative AI assistants in social commerce settings. Drawing on the Privacy Calculus Theory, Trust Theory, and the Stimulus–Organism–Response framework, the study investigates whether perceived GenAI-based advertising personalization simultaneously creates perceived personalization value and privacy concerns, and how these evaluations shape algorithmic trust and social commerce purchase intention. A scenario-based survey was conducted with 435 social commerce users in Jordan. Respondents evaluated a situation in which a product advertisement appeared to reflect a previous conversation with a generative AI assistant. The data were analyzed using partial least squares structural equation modeling with SmartPLS 4. The findings show that perceived GenAI-based advertising personalization increases both perceived personalization value and privacy concerns. Personalization value strengthens algorithmic trust, whereas privacy concerns weaken it. Algorithmic trust, in turn, strongly enhances social commerce purchase intention. The mediation results show that personalization value and privacy concerns transmit the dual effect of perceived GenAI-based advertising personalization to algorithmic trust. In contrast, algorithmic trust transmits these effects to purchase intention. Perceived transparency disclosure does not significantly reduce privacy concerns, but it strengthens the positive relationship between personalization value and algorithmic trust. This study contributes to digital marketing and social commerce research by showing that GenAI-personalized advertising can be perceived as both useful and intrusive and that perceived transparency disclosure may support trust formation without necessarily eliminating privacy concerns.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060196

Authors: Thabit Atobishi Saeed Nosratabadi

While the operational benefits of Artificial Intelligence (AI) are well-documented, the mechanisms through which firms leverage AI for strategic exploration and radical innovation remain under-theorized. This study addresses the “black box” of AI value creation by integrating the Technology–Organization–Environment (TOE) framework with the Dynamic Capabilities View (DCV). We propose that AI adoption is not a direct antecedent to performance but a multi-stage process wherein technological, organizational, and environmental factors enable the development of sensing capability, which in turn fosters a novel capability we term “AI-Enabled Exploration.” Analyzing survey data from 245 senior executives in Saudi Arabia, a high-growth economy undergoing state-led digital transformation, we employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to test the model. The results confirm a serial mediation chain: organizational readiness and technology compatibility drive sensing capability, which subsequently powers AI-enabled exploration to enhance innovation performance. Contrary to expectations, government support was not a significant predictor of sensing capability, suggesting that in resource-rich environments, external incentives are necessary but insufficient for capability building. Furthermore, competitive pressure was found to positively moderate the relationship between organizational readiness and exploration, acting as a critical catalyst that converts latent resources into active experimentation. These findings offer a theoretical roadmap for firms attempting to transition from AI-driven efficiency to AI-driven ambidexterity.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060195

Authors: Yao Lu Guangming Li

Live streaming commerce is increasingly relying on high-intensity persuasive tactics, yet such tactics may activate consumers’ persuasion knowledge and trigger defensive processing. This research examines whether AI streamers mitigate this defense more effectively than human streamers. Drawing on the Persuasion Knowledge Model, two experiments reveal that, under conditions of high persuasive intensity, consumers perceive lower persuasive intent from AI streamers than from human streamers, which, in turn, reduces consumer suspicion and increases purchase intention. Moreover, this serial mediating effect is stronger for independent accounts than for brand official accounts. These findings provide evidence for a PKM-based mechanism of AI-mediated persuasion and suggest that platforms should consider using AI streamers in high-pressure promotional contexts.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060194

Authors: Emre Yıldırım Faruk Dursun

The growing use of artificial intelligence (AI) in social media marketing has accelerated the emergence of AI-generated virtual influencers. While these influencers offer brands advantages such as scalability and message control, they also raise concerns regarding manipulation and ethical persuasion. Grounded in the Persuasion Knowledge Model (PKM), this study examines how different AI disclosure conditions influence perceived manipulation, perceived ethics, and purchase intention in AI influencer marketing. A three-condition between-subjects experimental design was employed to compare a human influencer, a disclosed AI influencer, and an undisclosed AI influencer using identical Instagram stimuli. Data were collected from 762 Generation Z female consumers in Türkiye. Structural equation modeling (SEM) was used to test the proposed relationships. The findings revealed that both disclosed and undisclosed AI influencer conditions significantly increased perceived manipulation. Perceived manipulation negatively affected perceived ethics, whereas perceived ethics positively influenced purchase intention. In addition, AI literacy positively affected perceived manipulation and perceived ethics while negatively affecting purchase intention. The findings further demonstrated that disclosure conditions indirectly influenced purchase intention through sequential cognitive and ethical evaluation processes. The study contributes to the AI influencer and digital persuasion literature by demonstrating that disclosure cues shape consumer responses through interconnected psychological mechanisms.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060193

Authors: Wushuang Li Chin Fei Goh Yuping Wu Owee Kowang Tan

Although generative artificial intelligence (AI) has increasingly been used to create destination marketing images, tourists’ responses to such images remain unclear. Prior research has often attributed negative reactions to the visual characteristics of AI-generated images. However, limited attention has been paid to how tourists interpret these images within broader cultural contexts. Drawing on authenticity theory and cultural learning theory, this research examines the effect of image type (AI vs. human) on tourists’ perceived authenticity and visit intention, as well as the moderating roles of cultural learning cues in this process. Using three experiments, the results show that AI-generated images reduce perceived authenticity and visit intention compared with images taken by humans. Notably, while salient cultural learning cues enhance tourists’ perceived authenticity and visit intentions, different types of cues produce distinct outcomes: commodified cultural cues mitigate tourists’ negative responses to AI-generated images, whereas heritage cultural cues amplify authenticity concerns. These findings provide strategic insights for destination marketers on how to deploy AI-generated images effectively in tourism destination marketing.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060192

Authors: Kexin Ding Tianjian Yang

Product mismatch, arising from consumers’ inability to physically experience products before purchase, is a major cause of returns in e-commerce, eroding e-tailer profits and intensifying consumers’ concerns about returns. To alleviate these concerns, e-tailers have increasingly adopted return insurance (RI), which reduces consumers’ return freight costs. However, RI may encourage consumers to defer product selection from the pre-purchase search stage to the post-purchase evaluation stage, thereby exacerbating mismatch and increasing return rates. As a countermeasure in live-streaming commerce, augmented reality (AR) provides an immersive product experience that can reduce mismatch and returns. This study develops a game-theoretic model to analyze the strategic interplay between an e-tailer’s RI decision and a live streamer’s AR decision while incorporating consumer search effort. The results show that consumer search effort changes the relationship between the two strategies. When search effort is low, RI and AR function as strategic substitutes; when search effort is high, they function as strategic complements. These findings indicate that the value of a return-management strategy depends on consumer behavior and on the presence of the partner’s AR strategy. The study contributes to the literature on interdependent return-management strategies and provides actionable insights for e-commerce practitioners.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060191

Authors: Ahmed S. Ajina

Rapid digital transformation has accelerated the frequency with which firms introduce product updates, platform enhancements, and feature innovations in e-commerce environments. While continuous innovation is typically associated with improved functionality and customer value, limited research has examined its potential psychological costs for consumers. This study introduces the concept of consumer innovation fatigue (CIF), defined as a psychological state of exhaustion arising from repeated exposure to ongoing innovation-related changes in digital products and online platforms. Following established scale development procedures, this research develops and validates a measurement scale for CIF. Item generation combined insights from prior literature with qualitative evidence from consumer interviews, followed by expert evaluation to ensure content validity. Using survey data from two independent samples of digital consumers in Saudi Arabia, exploratory factor analysis (n = 225) identified a unidimensional six-item scale. The scale was subsequently validated using partial least squares structural equation modeling (n = 361), confirming its reliability, convergent validity, and discriminant validity. The findings further demonstrate nomological validity by showing that exposure to continuous digital innovation significantly increases CIF, which in turn leads to innovation avoidance in online consumption contexts. By conceptualizing and empirically validating CIF, this study contributes to electronic commerce research by highlighting a previously underexplored psychological consequence of rapid innovation cycles in digital environments. The validated scale provides a useful instrument for future research examining consumer responses to ongoing technological change in e-commerce ecosystems.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060190

Authors: Emre Özsalman Alptekin Ulutaş Halime Ünver

The significant growth in e-commerce has brought intense competition to the business sector. Businesses seeking to stand out in this competition are evaluated by customers not only by the quality of the products they sell, but also by their performance on digital platforms. To measure this evaluation, this study analyzed the website performance of 25 e-commerce companies in Türkiye using Multi-Criteria Decision Making (MCDM) methods with eleven technical and user-oriented performance criteria. MAXC (Maximum Criterion) and Skewness Impact Through Distributional Evaluation (SITDE) methods were used to determine the criterion weights of the websites, while CORASO (COmpromise Ranking from Alternative SOlutions) was used to rank the alternatives. According to the results, “total number of visitors” had the highest weight, while “bounce rate” had the lowest weight. According to the CORASO method, the top three performing e-commerce sites were EC1, EC2, and EC3, while the bottom three performing sites were EC11, EC14, and EC20.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060189

Authors: Zheng-Jun Jin Kwang-Su Lee Chang-Hyun Jin Jungyong Lee

Despite rapid growth in the AI endorser market, the psychological mechanisms governing their effectiveness remain theoretically fragmented. This study proposes the AHICC (AI–Human Interface in Consumer Cognition) model—integrating the Stereotype Content Model, Uncanny Valley hypothesis, anthropomorphism theory, Source Credibility Model, and Parasocial Interaction theory—to explain consumer responses to AI endorsers. A fully crossed 3 (endorser type: AI vs. hybrid vs. human) × 3 (anthropomorphism level: low vs. moderate vs. high) × 2 (technological transparency: low vs. high) between-subjects factorial experiment (n = 252) was conducted. Twenty-one sub-hypotheses were tested using MANOVA, polynomial regression, SEM, and bootstrap mediation analysis. All 21 sub-hypotheses were supported. AI endorsers outperformed human counterparts on brand attitude and purchase intention. Polynomial regression confirmed an inverted U-shaped Uncanny Valley effect with an optimal anthropomorphism level of 4.7 (7-point scale). High technological transparency attenuated the Uncanny Valley effect by approximately 60%. Dual-pathway mediation through cognitive and affective routes was confirmed, and TRI and product complexity emerged as significant boundary conditions. The AHICC model offers the first comprehensive framework for the AI endorser context, providing theoretically grounded guidance on anthropomorphism calibration, transparency strategy, and product-category-specific endorser selection.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060188

Authors: Hajin Shin Sulim Kim Hee-Dong Yang Yong-Young Kim

In the crowded landscape of social media, hashtags serve not only as navigational tools but also as strategic signals of meaning and intent. This study examines how hashtag strategies—specifically semantic similarity with post content and usage frequency—affect sales outcomes in influencer-driven electronic commerce. Drawing on self-presentation theory, we analyze panel data from Instagram posts to explore how these hashtag dimensions interact with influencers’ self-presentation styles. The results show that hashtag–posting similarity significantly enhances sales, particularly among influencers exhibiting a Judging (J)-type self-presentation marked by structured and purposeful communication. In contrast, hashtag frequency alone does not increase sales performance and may even diminish it, indicating that excessive use can be counterproductive. However, for J-type influencers, an increase in hashtag frequency yields positive effects when it is deployed within a coherent and structured self-presentation framework, strengthening trust and ultimately enhancing conversion rates. These findings highlight that both what is said (semantic content) and how much is said (frequency) matter, but their effects depend on influencers’ expressive styles. The study provides actionable insights for marketers and brands, suggesting that effective hashtag strategies should align with influencers’ self-presentation tendencies rather than follow standardized or quantitative rules.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060186

Authors: Zichao Jia Junfeng Tian Chenyu Tian Yong Liu

In a duopoly market comprising an e-tailer and a physical retailer, we develop analytical models to explore the e-tailer’s strategy of introducing a virtual showroom to alleviate consumers’ fit uncertainty. While a virtual showroom can increase online consumer traffic, consumers may instead purchase from physical stores (i.e., webrooming) or reduce offline browsing before buying online (i.e., showrooming). Our findings indicate that consumers with a moderate online hassle cost tend to showroom when offline travel cost is not high, whereas those with a high online hassle cost rely on the virtual showroom for webrooming. Therefore, we identify the conditions under which a virtual showroom should be introduced. Specifically, when the cost of travel to the store is relatively high, the e-tailer can profit from introducing a virtual showroom if its return-handling cost is not too low. Under moderate travel cost, the e-tailer can leverage a virtual showroom to weaken competition if the return-handling cost is not too high, enabling both retailers to benefit. Notably, the impact of product fit probability on virtual showroom strategy decisions reverses between high and moderate travel costs. Under specific conditions, the virtual showroom can achieve a “win-win-win” situation for the e-tailer, the physical retailer, and consumers.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060187

Authors: Ying Xie Dan Zhou Tingting Wang Hanyu Sun

With frequent exposures of influencer false advertising and persona fabrication, “authenticity” has become an increasingly critical consumer demand. However, existing research employs inconsistent perspectives on “authenticity” (encompassing both consumer-perceived authenticity and influencer strategic authenticity) and remains fragmented, focusing narrowly on specific experiential dimensions such as positive emotions and social identity without systematic integration across the full customer journey. Therefore, this study adopts meta-analysis, systematically searching Chinese and English databases including Web of Science, Google Scholar and CNKI (2015–2026), and incorporates 170 effect sizes from 56 studies with 63 samples (n = 22,563) to systematically examine the effects of strategic authenticity (SA) and perceived authenticity (PA) on the customer experience journey (affective experience, cognitive experience, physical experience, and social-identity experience). Publication bias tests (fail-safe N > 5k + 10) indicated no significant bias. The results reveal that affective experience is more driven by strategic authenticity (ρ = 0.535), whereas cognitive experience (ρ = 0.591), physical experience (ρ = 0.355), and social-identity experience (ρ = 0.515) are more significantly influenced by perceived authenticity. Regarding influencer type moderation, virtual influencer SA exerts a stronger effect on social-identity experience (ρ = 0.574) than human influencer SA (ρ = 0.170, QB = 3.980, p = 0.046); conversely, human influencer PA shows a stronger effect on social-identity experience (ρ = 0.571) than virtual influencer PA (ρ = 0.016, QB = 8.189, p = 0.004). Regarding cultural differences, individualistic cultures exhibit stronger PA effects on physical experience (ρ = 0.419) and social-identity experience (ρ = 0.742); long-term orientation cultures show stronger SA effects on social-identity experience (ρ = 0.574). These findings contribute to the authenticity literature and offer actionable insights for influencer marketing practices.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060185

Authors: Min Qin Zhensong Jiang Zhao Pan

Live streaming e-commerce has emerged as a dominant force in electronic commerce. Although extensive research has examined service failures and recovery in conventional e-commerce environments, there is limited understanding of how buyers interpret and respond to service recovery information provided by streamers in live streaming contexts, where streamers fulfill dual roles as both idols and sellers. This study, grounded in signaling theory, investigates the relationships among buyers’ observation, interpretation, and feedback of service recovery information. Specifically, it aims to assess how buyers’ perceived justice regarding service recovery information affects their repeat purchase intentions following live streaming e-commerce failures. Meanwhile, this study elucidates the mediating role of trust in the streamer (idol role and seller role) and verifies whether responsibility attribution and product involvement have moderating effects on the effect of perceived justice. Employing PLS-SEM analysis, the study analyzes data from 401 buyers who have experienced service failures in live streaming e-commerce. The findings reveal that perceived justice positively influences repeat purchase intentions to a certain extent. Trust in the streamer mediates the link between perceived justice and repeat purchase intentions. The inhibiting moderation effect of responsibility attribution and product involvement is generally significant. This study contributes to the theoretical understanding of signaling theory by expanding the signaling model to encompass service recovery information in live streaming e-commerce. Furthermore, it provides practical guidance for live streaming e-commerce practitioners on managing service recovery information, including recommendations for the sequence of sending such information, enhancing its transmission, and improving its overall effectiveness.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060184

Authors: Bi Li Chaoshan Wang Yan Wu Boyu Chen Zhifeng Hao

With the rapid development of e-commerce, data-driven models have significantly enhanced service experience. We can obtain the optimal values for the price but have also intensified consumer privacy concerns. Among various privacy protection policies, which are more effective? Is there a governance framework that balances commercial efficiency with privacy safety? To address this, we develop a duopoly game-theory model that analyzes consumer behavior characterized by heterogeneous privacy costs and preferences, aiming to evaluate the impact of differentiated privacy protection policies within digital ecosystems. We analyze whether opt-in requirement or inference regulation is more advantageous for consumer and firm competition. We find that, in a competitive environment, imposing opt-in requirement on one party can yield competitive advantages and profit increases, whereas imposing inference regulation on the other may result in a competitive disadvantage. Such differentiated policies create an asymmetric competitive landscape, effectively avoiding a prisoner’s dilemma and, under certain conditions, increasing both consumer and total surplus. Furthermore, our study reveals significant differences in the impact of these policies on data-driven and usage-driven firms. Based on these findings, we recommend that regulators carefully tailor privacy protection policies according to industry-specific data characteristics, adopting differentiated regulatory strategies when appropriate and providing compensation mechanisms for disadvantaged firms to optimize total welfare.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060183

Authors: Qing Gu Xintao Yu Ding Yuan Qiang Yang

Although existing studies have shown that AI recommendation systems have potential in enhancing consumers’ purchase intention, there remains a lack of systematic research. This study aims to explore how the interaction between information presentation formats and AI role types influences consumers’ purchase intention. Based on metacognitive experience theory, two experiments are designed to analyze processing fluency as a mediator and consumers’ AI knowledge as a moderator. The results reveal that the interaction between information presentation format and AI role type significantly affects consumers’ purchase intention, while their separate effects are insignificant. Different from existing studies on separate factors, this study demonstrates that AI interactive marketing performance hinges on the matching of design and role positioning. This study extends the application of the theory of metacognitive experiences in the field of human–AI interaction and provides targeted recommendations for the interface design of AI recommendation systems.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060182

Authors: Xiao Fu Hao Tan

This study addresses supply uncertainty in the transportation and production of agricultural products within e-commerce-driven supply chains by developing a stochastic supply chain framework. By embedding an endogenous trust-based punishment mechanism, we characterize the strategic interplay between relational governance and operational decisions. In the single-period setting, higher retailer trust leads to larger order quantities while reducing the supplier’s optimal supply effort. This occurs because increased trust lowers the minimum delivery commitment ratio, allowing the retailer to voluntarily share more supply risk in exchange for lower-cost products. This creates a mutually beneficial risk-sharing arrangement between the retailer and supplier. When extending the framework to a dual-channel setting with a reliable backup option, the retailer consistently leverages trust and risk-sharing to lower sourcing costs. Concurrently, fluctuations in trust prompt the retailer to strategically shift order allocations between channels based on the primary supplier’s maximum effort capacity. Multi-period analysis shows a positive relationship between trust and the supplier’s expected profit, with optimal maximum supply effort stabilizing under repeated cooperation. Numerical experiments demonstrate that dual-channel decentralized decision-making achieves bullwhip effect mitigation quantitatively comparable to the centralized benchmark, while also alleviating moral hazard issues and benefiting retailers. These results indicate that the proposed mechanism effectively curbs opportunistic behavior and promotes sustainable, mutually advantageous supply chain collaboration.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060181

Authors: Calvin Steve Nyagudi Wenbing Wu

Technology-driven content is increasingly reshaping how tourists perceive and evaluate destinations, yet the underlying content evaluative processes remain insufficiently investigated. This study, therefore, integrates the Stimulus–Organism–Response (S–O–R) framework with Anthropomorphism Theory to examine how destination anthropomorphic content (DAC) relates to destination image (DI) and destination visitation intention (DVI) in digitally mediated environments. Using a cross-sectional survey design and multi-group Structural Equation Modeling, the study compares relationships across two information sources: AI- and social media influencer-generated content. The results show that DAC is positively associated with both DI and DVI across groups. Permutation-based multi-group analysis indicates that the differences in structural paths between AI and influencer groups are not statistically significant. This finding provides the basis for interpreting group comparisons, suggesting that the observed relationships do not differ meaningfully across content sources. While bootstrapping and effect size (f2) results indicate relatively stronger coefficients in the influencer group, these results are interpreted as descriptive tendencies rather than statistically confirmed differences. These findings suggest that tourists may respond positively to both human and technologically mediated agents’ content when human-like social cues are perceived. This study contributes to the growing discourse on AI and digital content in tourism by unveiling the critical concern of whether the content source matters in anthropomorphic perception. The study further extends the application of S–O–R in AI-mediated marketing contexts. The findings offer practical insights for destination marketers seeking to leverage both AI and influencer-based strategies in shaping tourist perceptions and intentions.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060180

Authors: Zhenyu Zhang Xueji Wang

Drawing on the uncanny valley framework, trust theory, and similarity attraction theory, this study examines how customers’ multidimensional perceptions of humanoid service robots shape their approach and avoidance behaviors through two relational states: trust and rapport. Subsequently, structural equation modeling and mediation analysis were employed for testing. The results indicate that customers’ overall perceptions of service robots not only encourage approach behaviors but may simultaneously intensify avoidance tendencies, reflecting the ambivalent nature of human–robot interactions. We interpret this dual activation through the uncanny valley framework, in which humanlike robots simultaneously elicit attraction and aversion. Trust and rapport play critical mediating roles in this process, effectively reducing avoidance responses while strengthening customers’ approaches. Further analyses reveal that different perceptual dimensions operate through distinct mechanisms in the formation of trust and rapport. This study aims to deepen the comprehension of customer response mechanisms to humanoid service robots through a relational perspective, and offers practical insights for hotels seeking to balance operational efficiency with emotional experience in robot design and management.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060179

Authors: Nermin Yildirim Bora Gündüzyeli

Artificial intelligence (AI) has transformed programmatic advertising (PA) by enabling automated, data-driven personalization within digital marketing ecosystems. However, this transformation has also intensified concerns regarding privacy, consumer trust, and the long-term sustainability of these ecosystems. In this study, sustainability is conceptualized as the capacity of digital marketing systems to maintain long-term functionality without eroding consumer trust or amplifying privacy-related tensions that may undermine system stability over time. This study addresses the research question: How does AI-driven PA affect the sustainability of digital marketing ecosystems through the personalization–privacy paradox? A systematic literature review, conducted in line with PRISMA guidelines, synthesizes prior research across four interrelated clusters: AI-driven personalization, privacy concerns, consumer trust, and consumer attitudes and behavior. The findings indicate that consumer responses to AI-driven personalization are not linear and are shaped by factors such as transparency, perceived control, and the perceived legitimacy of data practices. The review further shows that the paradox of personalization and privacy operates as a persistent condition within AI-driven advertising ecosystems, where the benefits of personalization coexist with ongoing privacy-related tensions. This study contributes to the literature by synthesizing fragmented research on AI-driven PA and by highlighting the central role of trust and transparency in understanding how personalization and privacy tensions shape consumer responses in digital marketing ecosystems.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060178

Authors: Yunbo Chen Jing Huang Yin Zhang Yixiang Zhang

Personalized advertising is now routine in digital commerce and new media, but relevance does not always translate into acceptance. When consumers read tailored messages as signs of tracking or inference rather than as useful assistance, they may feel exposed and avoid the advertising. Drawing on advertising avoidance theory, privacy calculus theory, and control agency theory, this study examines a privacy-risk account of personalized advertising avoidance. Survey data from 502 consumers and structural equation modeling show that privacy concern, privacy fatigue, and prior negative experiences are directly associated with advertising avoidance. Privacy concern, prior negative experiences, and perceived personalization are also positively associated with perceived risk; perceived industry self-regulation is negatively but non-significantly associated with perceived risk; and perceived risk is positively associated with advertising avoidance. These results position perceived risk as a close downstream appraisal through which consumers make sense of data-driven targeting. The study contributes to digital commerce and interactive marketing research by showing that consumers evaluate personalized advertising not only as a cue of relevance, but also as a possible source of privacy vulnerability. It also offers implications for transparent targeting, visible user control, platform governance, and less intrusive personalization.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060177

Authors: Muhammad Mohiuddin Meryem Ourhalouch Slimane Ed-Dafali Md. Samim Al-Azad

Digital transformation is contributing to changes in how both production processes and transactions take place among firms within global value chains (GVCs). Firms navigate rapid advancements in digital technologies, such as Industry 4.0-embodied technologies that are translating into the reconfiguration of their value chains. In an era of rapid growth in digital technologies, firms are in a position to reconsider their responsibilities within GVCs and reevaluate the strategic opportunities that come with digital transformation in the global market. Advanced technologies help firms in the GVC to streamline their cross-border production networks and enable real-time transactions between the firms. However, the impact of digitalization on the GVC has not been given much attention in earlier studies. This article presents a systematic literature review (SLR) based on the analysis of 43 articles on GVCs published between 2018 and 2024 and retrieved from the Scopus, Web of Science, and ProQuest databases. The study contributes in two ways: first, to elucidate the association between digital transformation and business-to-business (B2B) transactions within GVCs, and second, to propose future research directions aimed at enriching the literature on GVCs and suggesting theoretical and managerial implications.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060176

Authors: Wenna Wang Jifan Ren Guanhua Wang

This study investigates how different types of service failures in peer-to-peer accommodation influence guests’ negative review intentions. It explores the underlying psychological mechanisms and how the recovery agent’s identity (platform vs. host) shapes recovery effectiveness. Adopting a mixed-methods research design, an initial qualitative study (N = 52) explored key themes related to service failure and psychological contract violation, followed by three scenario-based experiments that empirically tested the proposed theoretical model and the moderating role of the recovery agent. Specifically, Study 1 (N = 236) and Study 2 (N = 297) employed 3 × 1 between-subjects designs comparing informational service failure, social service failure, and a control condition, while Study 3 (N = 352) adopted a 2 × 2 between-subjects design crossing service failure type (informational vs. social failure) and recovery agent identity (platform vs. host recovery). The findings reveal that both informational and social service failures significantly increase negative review intentions, with distinct mediating mechanisms: informational psychological contract violation mediates the impact of informational failures, whereas relational psychological contract violation mediates the effect of social failures. Importantly, a “recovery-agent matching” effect emerges, whereby platform recovery more effectively mitigates informational violations, while host recovery is more effective in repairing relational violations. By applying psychological contract theory to the dual service-provider structure of the sharing economy, this study extends the service recovery literature and shifts the focus from what recovery is delivered to who delivers it. The findings also provide practical guidance for managers, highlighting the need to move beyond one-size-fits-all recovery strategies.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060175

Authors: Tao Zhou Zexuan Zhang

As an emerging application, AI shopping has received increasing attention from both enterprises and users. Based on the push–pull–mooring (PPM) model, this research examined user switching intention from traditional online shopping to AI shopping. We conducted an online survey to collect 422 valid responses and adopted a mixed method of structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA). The results show that choice overload and perceived inefficiency lead to online shopping fatigue, while perceived convenience, perceived anthropomorphism, and perceived coolness affect AI shopping attractiveness. Online shopping fatigue, AI shopping attractiveness, and inertia determine user switching intention. These results provide a comprehensive understanding of the mechanism underlying user switching from traditional online shopping to emerging AI shopping. They also imply that e-commerce platforms need to mitigate online shopping fatigue and increase AI shopping attractiveness in order to expand their user base and maintain a competitive advantage.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060174

Authors: Moritz Lackner Siegfried Pöchtrager

Online grocery retailing remains effort-intensive because consumers must coordinate many item-level decisions, making basket construction and correction a key barrier to more frequent use. This study examines consumer acceptance of an AI-pre-filled basket in Austrian online grocery retailing and links Technology Acceptance Model (TAM) mechanisms to objective interaction performance. Using a field-proximate one-group pre–post design, participants edited an AI-pre-filled basket in a standardized online shop and completed pre- and post-task surveys using 0–100 slider scales; log data captured processing time and edit actions. Analyses are based on n = 297 valid cases. Results show a substantial and statistically significant within-person increase in online grocery usage intention after the AI-basket interaction, rising from 39.17 to 59.78. The TAM results support the core mechanism: perceived ease of use is positively associated with perceived usefulness, and perceived usefulness strongly predicts behavioral intention, whereas a direct ease-of-use effect on intention is not supported. Linking perceptions to log data shows that acceptance is more strongly associated with correction demand than with processing time. AI-basket acceptance depends less on speed than on reducing rework while preserving user control; retailers should therefore design AI baskets as controllable, editable, low-rework systems rather than speed-oriented automation tools.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060173

Authors: Lijun Chen Rui Sun Lele Fan Lei Zhuang

The increasing complexity of artificial intelligence systems and algorithms can negatively affect individual attitudes and prompt them to adopt coping behaviors. Based on the technology threat avoidance theory, this study explores the mechanisms through which the supervisibility of recommendation algorithm throughput influences the coping behaviors of targeted advertising audiences using scenario-based online experiments conducted between August 2022 and January 2023. In particular, we examine the mediating effect of perceived threat and the moderating effects of privacy concerns and self-efficacy. The results reveal that perceived threat arising from the characteristics of recommendation algorithm throughput determines the possible coping behaviors of targeted advertising audiences. Moreover, perceived threat mediates the impact of the supervisibility of algorithm throughput on audiences’ coping behaviors. Furthermore, users’ privacy concerns and self-efficacy positively moderate the influence of the supervisibility of algorithm throughput on perceived threat and the relationship between perceived threat and audiences’ coping behaviors, respectively. The results help to explain the black box of the relationship between the characteristics of recommendation algorithms and audience responses from an algorithm throughput perspective. The findings offer implications for improving the effectiveness of personalized recommendations and provide a new perspective for studying the transparency of algorithmic recommendations in consumer behavior.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060172

Authors: Yu Mi Banggang Wu Yong Wang Yuqi Du

Conversational AI agents are now a routine touchpoint in e-commerce customer service, and AI empathy has emerged as the headline humanization strategy for repairing relational damage during service failures. A growing evidence base reports that empathic AI often backfires, because consumers cannot reconcile felt warmth with their lay model of what an artificial agent is. This research asks under what conditions AI empathy can be made credible to consumers. We propose that mechanistic interpretability, operationalized in the present studies as a consumer-facing visualization of an AI agent’s internal emotion-vector activations designed in the style of mechanistic-interpretability research, operates as a costly authenticity signal that rehabilitates empathic AI by enabling an attributional shift along the experience dimension of mind perception. Signaling Theory carries the antecedent stage of the causal chain, where mechanistic interpretability serves as a verifiable cue of computational authenticity. Mind Perception Theory carries the downstream stage, where the authenticated empathy is converted into consumer-brand intimacy. Two between-subjects experiments preceded by a feasibility pilot tested the account on Mainland Chinese consumers recruited via the Credamo online panel. Study 1 used a single-factor design contrasting high versus low AI empathy. Study 2 used a two (AI empathy) by two (mechanistic interpretability) full factorial. Study 1 showed a pattern consistent with high (versus low) AI empathy lowering brand intimacy through reduced perceived authenticity. Study 2 replicated the AI-empathy backfire when interpretability was absent, reversed the sign of the AI-empathy slope on the perceived-authenticity mediator when interpretability was present, and neutralized the negative conditional indirect effect on brand intimacy through perceived authenticity. The findings introduce mechanistic interpretability to consumer-marketing scholarship as a manipulable signaling channel, document a structural reversal in the mediator-stage slope coupled with neutralization of the indirect effect on the relational outcome, and prescribe pairing empathic AI phrasing with mechanistic-transparency design rather than deploying empathy without an accompanying transparency cue.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060171

Authors: Hyejin Cho Juhee Kim

As digital creators increasingly operate through organized business structures rather than as individual content producers, understanding organizational characteristics associated with digital creator organizations’ performance has become an important research question. This study examines how content production scale, revenue model diversification, and workforce structure are related to the performance of digital creator organizations. Using survey data on the Korean digital creator media industry, we analyze organizational performance in terms of sales volume and sales per employee. The results indicate that content production scale and revenue model diversification are positively associated with organizational performance. The findings also indicate that workforce structure is relevant: the share of permanent employees is positively related to efficiency, whereas the share of production and development employees is negatively associated with performance. Overall, this study suggests that organizational performance in digital creator organizations is associated not only with content production itself, but also with revenue model breadth and workforce structure. This study contributes to the literature by providing an organizational perspective on performance in the creator economy and offers practical implications for the sustainable growth of digital creator organizations.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060170

Authors: Wenna Wang Jifan Ren Muhammad Zahid Nawaz Maroua Ben Maaouia

Negative online reviews play a critical role in shaping consumer decision-making in the hospitality sector. Drawing on cue utilization theory and signaling theory, this study examines how different types of negative reviews and host responses affect potential guests’ booking intentions, as well as the underlying mechanisms and boundary conditions. Across three scenario experiments, the proposed framework was tested. Study 1 reveals a significant interaction between the type of negative reviews (informational vs. social) and host response strategies (problem-focused vs. emotion-focused), highlighting that aligning response strategies with review types is critical for effective negative review management. Study 2 demonstrates that perceptions of host competence and attitude mediate these effects, indicating that potential guests make decisions through psychological inference. Study 3 finds that platform-endorsed credibility signals, such as host badges (Superhost vs. non-Superhost), significantly moderate these relationships. When hosts are Superhosts, informational negative reviews paired with problem-focused responses further enhance competence perceptions and booking intentions; for non-Superhosts, social negative reviews paired with emotion-focused responses improve attitude perceptions and booking intentions. The findings advance theoretical understanding of how signaling mechanisms shape consumer behavior in home-sharing hospitality platforms, and offer practical guidance for hosts and platforms to manage online reputations strategically and effectively.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060169

Authors: Zhexu Zhong Angela C. Chao

The era of zero-sum competition calls for e-commerce platforms to shift focus toward micro-market resilience. Existing research has split into two traditions: diagnostic studies offer detailed analyses of market failure but lack systemic application, while engineering studies develop deployable tools yet suffer from opaque mechanisms and hidden risks. This paper proposes the Signal–Belief–Decision (SBD) framework to bridge this divide, with the Signal layer transforming private information into verifiable public knowledge, the Belief layer aggregating dispersed signals into shared consensus, and the Decision layer encoding enforceable rules for incentive compatibility. Using an extended signaling game, we diagnose six vulnerability dimensions (VD1–VD6) that destabilize markets. Agent-based modeling then allows us to distill four design principles (DP1–DP4) that inform governance configuration. The SBD framework provides a middle-range theoretical architecture that reorients platform governance from reactive tooling to proactive, consumer-centric design.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060168

Authors: Shu Pei Shao Xinyu Bie Jong Min Kim

This study examines the relationships among digitalization awareness, perceived risk, platform trust, and consumer outcomes in e-commerce platforms. Consumer outcomes are conceptualized as a higher-order construct comprising perceived value, engagement, purchase intention, and loyalty. Drawing on technology readiness and trust-based exchange theories, we test a mediation model using survey data collected from 370 online shoppers in China and structural equation modeling. The results show that digitalization awareness is negatively associated with perceived risk and positively associated with platform trust. Platform trust positively predicts consumer outcomes and serves as the dominant mediator. Although perceived risk is negatively related to platform trust, it unexpectedly shows a positive direct association with consumer outcomes, indicating a theoretically nuanced role of risk as both a source of vulnerability and a possible trigger of evaluative engagement. Digitalization awareness also retains a significant direct association with consumer outcomes, supporting a partial mediation framework. These findings highlight observed relationships among digitalization awareness, risk appraisal, platform trust, and multidimensional consumer outcomes in the Chinese e-commerce context.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060167

Authors: Weiqi Sun Dongkwon Seong

Recycled products have evolved from environmental substitutes to an important development direction in the future consumer market. However, consumers’ active avoidance of recycled product advertisements is still prevalent, which restricts their market acceptance and promotion. This study aims to systematically explore the relationship between recycled product anthropomorphism and consumer advertising avoidance, and reveal the mediating role of perceived risk, as well as the moderating effects of technology readiness and time orientation. A mixed exploratory method combining Smart PLS and fsQCA was adopted to conduct an in-depth analysis of 728 questionnaires. The results show that recycled product anthropomorphism has a significant negative impact on consumer advertising avoidance, and this effect is partially realized through the mediating mechanism of perceived risk, which is regulated by technology readiness and time orientation. The research results not only enrich the application of anthropomorphism theory in the field of sustainable consumption but also provide empirical evidence and practical guidance for companies to formulate effective recycled product advertising strategies and reduce consumer advertising avoidance.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060166

Authors: Marija Gombar Amir Topalović Mirjana Pejić Bach

With the increasing integration of artificial intelligence into e-commerce platforms, trust in algorithmic decision-making has become a critical issue. Recommender systems significantly shape consumer choices and influence visibility within digital marketplaces, yet remain largely opaque. This study aims to bridge the gap between algorithmic accuracy and perceived trustworthiness by conducting a bibliometric and topic modeling analysis of 163 peer-reviewed publications (2012–2025). Results indicate a paradigmatic shift from usability-focused approaches toward governance-aware frameworks encompassing fairness, explainability, and accountability. To capture this transformation, the Acceptance Triangle model is introduced, conceptualising algorithmic acceptability across three interdependent layers: trust calibration at the interface level, exposure fairness at the platform level, and accountability mechanisms at the institutional level. The model is further operationalised through the Trust UX Playbook—nine managerial design levers with associated key performance indicators—and a Composite Acceptability Score integrating accuracy, fairness, and complaint reduction. The findings suggest that trust alone may be insufficient for understanding long-term acceptability in e-commerce recommender systems. Instead, the alignment between user experience, market equity, and governance legitimacy is interpreted as an analytically useful condition for conceptualising algorithmic acceptability. This research contributes a structured framework for assessing and designing acceptable recommender systems, offering actionable guidance for designers, decision-makers, and regulatory stakeholders seeking to improve algorithmic transparency, fairness, and accountability in online commerce.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060162

Authors: Maija Dobele Jelizaveta Prilucka Klaus Solberg Söilen

Family firms are central to global economic stability and employment. Generational transitions, however, involve not only the transfer of leadership but also changes in organizational structures and culture. As digitalization becomes increasingly important for competitiveness, successors are introducing digital marketing practices that may influence organizational culture during leadership transitions. While previous research has examined digital transformation in family businesses, limited attention has been given to the role of digital marketing as a mechanism of cultural change during generational succession. This article addresses the question: How do second-generation successors use digital marketing practices to shape organizational culture during generational transitions in family firms? Drawing on practice theory and Schein’s model of organizational culture, the study explores how cultural change unfolds through everyday practices within organizations. The research employs a qualitative multiple-case study approach based on semi-structured interviews with representatives from 35 family firms in Latvia. The findings identify key digital marketing practices implemented by second-generation successors and illustrate how these practices influence organizational culture during the transition process. The results suggest that digital marketing can both reinforce existing organizational values and selectively reshape organizational identity and legitimacy. The study highlights digital marketing as a culturally legitimate tool through which successors can influence decision-making processes, coordination mechanisms, and authority structures during generational succession.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060165

Authors: Xianfa Shi Miao Su Keun-sik Park

Cross-border e-commerce offers consumers broader product access, yet uncertainty surrounding returns continues to suppress online purchase decisions. This study conceptualizes digital local return services as a digital assurance mechanism in cross-border e-commerce rather than merely a reverse logistics function. Drawing on UTAUT2, perceived risk theory, and trust theory, we develop and test a research model using survey data from South Korean consumers with prior experience of digital local return services (LRS). Structural equation modeling (SEM) is used to test the proposed relationships, and artificial neural networks (ANN) are employed to capture nonlinear effects and compare the relative importance of key predictors. Qualitative interview evidence is further incorporated to enrich the interpretation of the findings. The results show that performance expectancy, effort expectancy, facilitating conditions, and hedonic motivation significantly reduce perceived risk. Perceived risk, in turn, exerts a strong negative effect on purchase intention and weakens consumer trust. Additional ANN results indicate that hedonic motivation and facilitating conditions are particularly influential in lowering perceived risk, while perceived risk is more important than trust in predicting purchase intention. These findings show that digital return service design shapes consumer decisions primarily through risk reduction rather than trust enhancement alone. The study contributes to digital commerce research by explaining how return service design functions as a customer-facing platform assurance mechanism that improves conversion in cross-border online retailing.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060164

Authors: Carmen-María Hervás-Cortina María-Eugenia Ruiz-Molina Irene Gil-Saura Mariia Bordian

This study investigates how user-generated content (UGC) and perceived experience of destination-generated social media content (DGC) shape satisfaction, destination image, and electronic word-of-mouth (eWOM) intention in lesser-explored tourism destinations. A dual-content model grounded in the stimulus-organism-response (SOR) framework is tested using partial least squares structural equation modeling (PLS-SEM) with data from 300 tourists who interact with destinations’ social media. Results reveal that UGC exerts limited influence on satisfaction, destination image, and eWOM intention, which diverges from much prior literature but is consistent with the scarcity and lower trustworthiness of UGC in small destinations. In contrast, perceived experience of DGC strongly enhances destination image and eWOM intention, highlighting the relevance of pre-visit digital experiences. In addition, moderation analysis shows that openness to experience significantly influences selected relationships, with stronger effects observed among tourists who are lower in openness. The findings underscore the importance of integrating pre-visit digital interactions and individual differences into destination marketing models and provide practical insights for destination management organizations (DMOs) in lesser-known destinations, emphasizing the strategic value of high-quality official content to compensate for limited UGC. This research advances destination marketing literature by jointly examining UGC and DGC and by introducing perceived experience of DGC and personality as key explanatory elements.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060163

Authors: Ying Tan Yunqi Zhang Yong Geng Shubo Liu Hongtao Tang

In interactive digital commerce environments, negative electronic word-of-mouth (NeWOM)—particularly negative online reviews—profoundly shapes consumer perceptions and brand relationships. Yet, the underlying mechanisms through which NeWOM influences consumer conformity behavior remain underexplored from a qualitative, process-oriented perspective. This study adopts a grounded theory approach to analyze 1405 authentic negative smartphone reviews from a leading Chinese e-commerce platform. Through systematic open, axial, and selective coding, we develop a processual model that reveals how NeWOM triggers two interconnected yet distinct psychological mechanisms: the formation of generalized negative brand schema, driven by service/product failures and the internalization of psychological expectations, driven by unmet brand expectations and poor service attitudes. These mechanisms jointly shape consumer conformity behavior—the tendency to align one’s judgments and actions with perceived peer consensus reflected in negative reviews. Importantly, enterprises’ responsive improvements based on negative feedback operate as a feedback loop that can sustain or restore consumer–brand congruence. By reconceptualizing NeWOM as a dynamic, dialogic trigger within interactive marketing systems, this study extends electronic commerce theory and provides context-sensitive insight into how consumer conformity emerges and evolves in digital marketplaces.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060161

Authors: Fushuai Guo Haiyang Kong

Using a global panel of bilateral digitally delivered services exports for 192 economies from 2006 to 2022, together with large-scale international news data, this study examines the impact of international media sentiment on digital service exports, with particular attention to the institutional-barrier channel. To address the temporal aggregation mismatch between high-frequency media sentiment and annual trade flows, as well as potential endogeneity concerns, we employ a Mixed Two-Stage Least Squares (M2SLS) approach. The results show that more favorable international media sentiment has a positive and statistically significant effect on digital service exports. This finding remains robust across a range of measurement checks, placebo tests, alternative instrument constructions, subsample analyses, and Bayesian estimation. Further analysis supports an institutional-barrier interpretation by showing that favorable media sentiment is associated with lower bilateral digital service trade policy heterogeneity. The impact is stronger in trust- and reputation-intensive service sectors and in cultural contexts where reputational signals are more salient, while it weakens or reverses in technical service sectors and in highly secular-rational and institutionally asymmetric trading relationships.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21060160

Authors: Wenqiu Guo Yenchen Liu Banggang Wu Xiaoyu Deng

With the rapid development of Artificial Intelligence (AI) technology, human-like AI service agents have been increasingly applied in service marketing. Online travel agency (OTA) platforms provide an important application context for such service agents in consumer-facing service interactions, such as travel planning and related services. Drawing on social cognitive theory and control theory, this study examines the psychological mechanisms underlying consumers’ intentions to adopt AI service agents. One pretest and two experiments involving 521 participants were conducted to investigate the effects of the AI service agent role on consumers’ willingness to use substitute vs. assist AI. The results show that consumers are more willing to use assist AI service agents than substitute AI service agents. This effect is mediated by human identity threat and sense of control. Moreover, higher consumer technology readiness moderates these effects, mitigating the preference for assist over substitute AI service agents. This study extends the conceptual framework of AI service agents in human–computer interaction research and offers practical implications for the effective design and deployment of AI service agents in OTA applications.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050159

Authors: Gulfem Yagmurdur Yan Meng Savas Gayaker

Artificial intelligence (AI) is increasingly being deployed in various sectors of e-commerce. Consequently, it becomes necessary to identify the impact of algorithmic design parameters on buyer behaviour. This study examines the impact of algorithmic anthropomorphism (ANT), algorithmic transparency (TRAN) and perceived algorithmic fairness (FAIR) on consumer purchase intentions (PI) in the Turkish e-commerce market. In addition, this study examines technology acceptance—operationalised through the Technology Acceptance Model (TAM)—as a boundary condition, with particular attention to the differential moderating roles of perceived ease of use (PEOU) and perceived usefulness (PU). A structured questionnaire was distributed among 384 online consumers in Türkiye via Qualtrics. A confirmatory factor analysis (CFA) established the psychometric adequacy of the measurement model (all AVE > 0.50, all CR > 0.87; HTMT < 0.85 across theoretically distinct constructs). The proposed model was tested using the PROCESS macro for sequential mediation and moderation analyses, with bootstrap confidence intervals based on 5000 resamples. The results reveal that: (1) algorithmic anthropomorphism positively affects both algorithmic transparency and perceived algorithmic fairness; (2) algorithmic transparency has a significant positive effect on both perceived fairness and purchase intention; (3) perceived algorithmic fairness mediates the relationships between algorithmic anthropomorphism and purchase intention, as well as between algorithmic transparency and purchase intention; and (4) although the composite technology acceptance level (TAL) measure does not significantly moderate the anthropomorphism–purchase intention path (p = 0.075), disaggregating TAL into its sub-dimensions reveals that PEOU significantly moderates this relationship (p < 0.001), whereas PU does not (p = 0.199). The composite-TAL result is therefore not statistically supported, but the dimension-specific PEOU finding is robust. These findings offer theoretical contributions to AI-driven consumer behaviour research and practical implications for the design of algorithmic e-commerce systems in emerging digital markets.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050158

Authors: Youngju Cho Junyoung Yoo Joon-Woo Yoo Heejun Park

Online reviews are increasingly pivotal in consumer decision-making, with platforms employing mechanisms such as badges to denote reviewer credibility. Although prior research has examined the influence of expert reviewers, it has typically treated badge holders as a homogeneous group, overlooking how variation in tenure within expert tiers shapes the way readers process review content. This article examines how Yelp Elite badge tenure, operationalized as Red (1–4 years), Gold (5–9 years), and Black (10+ years) tiers and treated as a proxy for accumulated platform-recognized expertise, moderates the effects of peripheral cues (Extremity, Length) and central cues (Readability, Subjectivity, and Plutchik’s eight emotions) on perceived helpfulness within an Elaboration Likelihood Model (ELM) framework. The analysis draws on the full population of 324,426 restaurant reviews authored by Yelp Elite badge holders between 2019 and 2021, using a pooled count-model specification with badge tier as a categorical moderator. The primary specification is estimated using Poisson quasi-maximum likelihood with HC1-robust standard errors, and full negative binomial estimation is reported as a robustness check. Wald tests indicate that badge tenure significantly moderates eight of twelve cue–helpfulness relationships (χ2(24)=4938, p<0.001). The effect of readability is monotonically positive and increases sharply with tenure, while the effect of joy varies across tenure groups. These findings suggest that reviewer expertise signals are not monolithic, refining theoretical insights on how tenure-based credibility cues moderate cue processing and offering practical implications for review platform management. The findings also indicate that platforms applying uniform ranking or surfacing rules across all Elite reviewers risk misallocating visibility, and that tenure-conditional weighting of textual cues warrants consideration.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050157

Authors: Chuchu Liu Xin Zhang Mengsi Cai Zheng Han

This study analyzed online review data to examine user requirements for audiovisual products and to compare requirement salience and satisfaction across traditional and emerging product contexts. We collected 86,213 Chinese-language reviews of Skyworth TVs, Xiaomi TVs, and Xiaomi projectors from JD.com. LDA topic modeling was used to identify major user requirement areas, and Logistic Regression, Random Forest, and Support Vector Machine (SVM) models were compared for sentiment classification, with the tuned SVM model retained for downstream analysis. The results show that user discussions primarily concern audiovisual experience, cost performance, service quality, design aesthetics, and intelligent operation. Skyworth TVs receive particularly strong evaluations for picture and sound quality (97.89% positive sentiment), whereas Xiaomi TVs are more strongly associated with cost-effectiveness and smart features (94.05% positive sentiment). Xiaomi projectors attract attention for portability but receive lower satisfaction ratings on core audiovisual performance and intelligent operation. These findings suggest that traditional manufacturers should continue strengthening core performance while improving service responsiveness, whereas emerging brands should build on their technological advantages while further enhancing their product reliability and user experience.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050156

Authors: Ahmed Saif Abu-Alhaija Mahmoud Mohamed Elsawy

This study examines the effects of digital sustainability orientation on consumers’ responses, with a focus on the roles of digital green innovation and consumer environmental consciousness in shaping green brand advocacy in social media marketing. Drawing on the Resource-Based View, Dynamic Capability perspective, and Signaling theory, the study proposes that sustainability-oriented digital strategies are more effective when translated into visible, credible forms of digital green innovation. Using the quantitative research design, data were collected from a sample of 300 Saudi Arabian consumers who interact with eco-friendly brands and sustainability-related content on digital platforms such as Facebook, WhatsApp, Instagram, and TikTok. The study used purposive and convenience sampling to ensure that participants were aware of sustainability communication online. Data analysis was performed using Partial Least Squares-Structural Equation Modeling (PLS-SEM) to test the measurement and structural models and evaluate the hypotheses. The results show that the direct positive effect of digital sustainability orientation on digital green innovation is high, but there is no direct effect on green brand advocacy. However, digital green innovation fully mediates this relationship, making the importance of tangible innovation even greater in turning sustainability intentions into consumer support. Moreover, consumer environmental consciousness plays a significant moderating role in the relationship between digital sustainability orientation and green brand advocacy, suggesting that the more environmentally conscious consumers are, the more responsive they are to sustainability-driven digital strategies. The study contributes to the available literature on digital sustainability and green marketing by showing that being sustainability-oriented is not enough to encourage consumer advocacy without having credible innovation. Practically speaking, the findings show that organizations must pay attention to innovation-based sustainability initiatives and develop genuine digital communication strategies to attract environmentally conscious consumers. Ultimately, the research serves as a great reminder of the importance of integrating digital innovation, sustainability practices, and consumer engagement as key drivers of strong green brand advocacy.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050155

Authors: Nyoman Sri Subawa Ni Putu Chantika Aprilia Nariswari Made Maenita Dewi Anak Agung Gede Wiranata Caren Angellina Mimaki Made Srinitha Millinia Utami

The adoption of immersive technologies, such as Virtual Try-On (VTO), has transformed how consumers evaluate products, interact digitally, and engage with brands. This study investigates the effects of experiential value, flow, perceived enjoyment, customer trust, and customer satisfaction on customer engagement behavior, within the Stimulus–Organism–Response (S–O–R) framework. Experiential value serves as the stimulus, flow and psychological states as the organism, and engagement as the response. Data were collected from 320 Indonesian e-commerce using a purposive sampling technique, targeting respondents with prior experience using Virtual Try-On (VTO) features through an online questionnaire distributed via Google Forms, and were subsequently analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that experiential value and flow are fundamental drivers of immersive experiences. Interestingly, although flow significantly increased perceived enjoyment, these affective responses did not independently mediate the relationship with engagement behavior. Instead, customer trust and satisfaction acted as significant primary mediators, indicating a pragmatic immersion profile in which Indonesian consumers prioritize functional validation and system reliability over mere digital entertainment. These findings underscore that in markets with high uncertainty, evaluative and relational mechanisms are more important for sustained engagement than short-term hedonic responses. Practically, this research suggests that brands should prioritize photorealistic accuracy and biometric data security to foster long-term trust, while using enjoyment as a secondary engagement stimulus.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050154

Authors: Dariia Drozd Klaus Solberg Söilen

With growing interest in the effects of AI disclosure on user-generated content, empirical studies have produced mixed results. While some studies report negative consequences of disclosure, others suggest that transparent AI use does not necessarily reduce perceived authenticity or product evaluations. There is still limited knowledge about how AI disclosure in online reviews influences consumer perceptions when AI is presented as a support tool rather than a replacement for human input. To address this gap, the present study examines how AI disclosure and AI-related review cues influence consumer trust. The study compares three labeled review scenarios—reviews without AI-related information, AI-assisted labeled reviews, and AI-generated labeled reviews. The textual content of the reviews remained constant across conditions, while only AI-related labels and images were varied. This study also examines how these labeled scenarios relate to perceived authenticity and whether perceived authenticity mediates the relationship between labeled review scenarios and consumer trust. Based on survey data from 370 users of digital marketplaces in Latvia, analyzed using repeated-measures ANOVA, pairwise comparisons, and mediation analysis, this study found that: (1) reviews labeled as AI-generated showed the lowest levels of consumer trust and perceived authenticity, whereas AI-assisted labeled reviews were evaluated more favorably than AI-generated labeled reviews; (2) differences across the three scenarios were statistically significant for both consumer trust and perceived authenticity; and (3) perceived authenticity significantly mediated the relationship between labeled review scenarios and consumer trust. This study contributes to the literature by providing a more nuanced understanding of how AI disclosure and AI-related review cues shape consumer trust. It suggests that the key issue is not AI disclosure alone, but how AI-related cues shape perceived authenticity and, in turn, consumer trust.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050153

Authors: Ionica Oncioiu

The growing reliance on artificial intelligence (AI)-based recommendation systems is transforming e-commerce into a space where decision-making is increasingly co-constructed between users and intelligent systems. However, it remains insufficiently understood how the transparency of these systems influences users’ trust and purchasing decisions within human–AI collaboration contexts. Addressing this gap, the study develops a conceptual model that explains the role of cognitive mechanisms in the relationship between AI transparency and consumer behavior. Specifically, algorithmic understanding and fairness perception are conceptualized as cognitive processes through which users evaluate AI-generated recommendations, while perceived control is positioned as a key link between these evaluations and trust formation. The model is empirically tested using partial least squares structural equation modeling (PLS-SEM) based on data collected from 312 users of recommender systems. The results highlight the role of cognitive mechanisms and perceived control in explaining the effects of AI transparency on trust and, indirectly, on purchase intention. AI literacy also shapes how users interpret the information provided by the system. The present research provides an integrated perspective on human–AI collaboration in e-commerce, with relevant implications for the design of recommender systems and the optimization of user experience.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050152

Authors: Ciprian Adrian Păun Nicolae Păun Dragoș Păun

The transition from cash to digital payment instruments is reshaping retail commerce across Europe unevenly, with Central and Eastern European (CEE) countries exhibiting both some of the fastest growth and some of the lowest baseline levels in online shopping participation. This study examines whether the development of digital payment infrastructure proxied by the share of individuals using internet banking (NetBank) is associated with e-commerce adoption across eleven CEE EU member states over the period 2014–2023, yielding a balanced panel of 110 country-year observations. Drawing on harmonised data from Eurostat, the World Bank, and the ITU, we estimate a two-way fixed-effects model with kernel-robust standard errors and a dynamic specification with a lagged dependent variable. The results indicate that a one-standard-deviation improvement in internet banking penetration is associated with a 6.2 percentage point increase in the share of online shoppers once country and year fixed effects are controlled for, a finding that is precisely estimated under kernel standard errors (p < 0.001). Income-group heterogeneity analysis suggests that this association may be substantially larger in lower-income CEE countries (β = 6.9, p = 0.006) compared to higher-income ones (β = 2.3, p = 0.554), consistent with the hypothesis that payment infrastructure improvements generate the highest marginal returns where baseline access is lowest. Romania, despite recording the steepest absolute growth in online shopping in the EU over the sample period (+33 percentage points), remains persistently below the CEE median, illustrating how payment infrastructure constraints can slow convergence even during periods of rapid digitisation. The findings should be interpreted as robust conditional associations rather than causal effects, given the limitations of macro-panel identification.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050151

Authors: Jingxian Wang Ge Tian Joohan Ryoo

Although the entrepreneurial incubation performance of the platform-led entrepreneurial ecosystem is remarkable, existing research lacks insights into how to empower startups and how to effectively improve their performance as important ecosystem participants. To address this gap, this study analyzed the questionnaire data from 368 employees of startups associated with platform enterprises established for less than 8 years. Research findings indicate that within these ecosystems, the coupling relationship between startups and platform ecosystem participants facilitates the formation of interest communities within the platform ecosystem’s inner circles. Crucially, this study reveals that formal platform governance significantly moderates these relationships, acting as an institutional safeguard that curbs opportunistic behavior and amplifies the performance-enhancing effects of coupling. This synergistic interplay between coupling and formal governance mechanisms drives collective value creation across the entire platform, and thus improves startup performance. Finally, based on the coupling intensity and governance maturity, this study has built a practical decision-making matrix, which provides clear strategic rules for startups, large enterprises and policymakers, so as to enhance sustainable collaboration and resource allocation among all ecosystem participants.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050150

Authors: Jindarat Peemanee Thanithaporn Udomlarp Ploychompoo Weber Ranitha Weerarathna

This study examines how human (HI) and virtual influencers (VI) shape consumer responses among Thai Generation Z users (Gen Z) on TikTok. Drawing on Source Credibility Theory (SCT), Parasocial Interaction Theory (PSI), and the Technology Acceptance Model (TAM), the study develops a comparative framework to explain how influencer characteristics affect attitude and purchase-related responses. Data were collected from 400 Generation Z TikTok users in Thailand and analyzed using Govariance-Based Structural Equation Modeling (CB-SEM). The results indicate that both human and virtual influencer characteristics positively influence influencer attitude (IA), which in turn significantly affects purchase decision (PD). However, the total effect of human influencer characteristics on purchase decision is substantially stronger than that of virtual influencers. These findings suggest that while virtual influencers contribute to favorable evaluations through innovation and visual consistency, human influencers remain more effective in translating attitudes into purchase-related outcomes. This study provides comparative evidence from a non-Western context and integrates credibility, relational, and technology-based perspectives into an integrated analytical framework.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050149

Authors: Shang Gao Junjie Kuang Licai Lei Hai Liu

The optimization of regulatory strategies for live-streaming e-commerce is essential for tackling misleading marketing behaviors (MMBs) and protecting stakeholders’ rights. This is fundamental to building a healthy and sustainable live-streaming e-commerce ecosystem. To address governance challenges and regulatory inefficiencies, this paper adopts a behavioral perspective and constructs a tripartite evolutionary game model involving platforms, live streamers, and consumers. It unveils the interactive mechanism between dual herd mentality and overconfidence in shaping regulatory strategy evolution, with numerical simulations validating the dynamic regulatory pathway. The findings indicate: (1) The severity of platform penalties is the linchpin of collaborative governance. Under low penalties, herd mentality may spur consumers to report live streamers who choose the MMB strategy, but the absence of deterrence traps the market in a “more reports, more MMBs” vicious circle. Moderate-to-high penalties align herd behavior with non-MMBs by live streamers, but risk unleashing irrational herd conduct among consumers. A dynamic matching mechanism that adapts penalty intensity to prevailing herd levels is therefore essential. Once a critical threshold is crossed, it enables synergistic benefits through joint supervision by consumers and platforms. (2) Overconfidence on the live streamer’s side magnifies the illusion of inflated returns. At low levels, the herd mentality from consumers can correct this psychological bias, but once overconfidence becomes pronounced, only large-scale supervising can outweigh the expected gains from MMBs. (3) These two behavioral traits jointly shape the equilibrium of the live-streaming e-commerce system and should therefore be treated as key considerations when designing dynamic regulatory strategies.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050147

Authors: Pavithra S S Chitrakala S

Social media platforms such as X (formerly Twitter) increasingly shape attention formation, market visibility, and value signaling in electronic commerce, particularly in emerging digital asset markets such as Non-Fungible Tokens (NFTs). Prior work shows that social engagement correlates with NFT prices, suggesting its potential for valuation support. However, open social platforms exhibit heterogeneous user credibility, automated activity, and coordinated promotion, which can distort engagement-based inference. To address these challenges, we propose NFT-TRUST, a trust-aware social signal modeling framework that transforms raw engagement into credibility- and integrity-aware indicators for robust valuation support under manipulation-prone conditions. The framework integrates three components: (i) Credibility-Weighted Social Signal Aggregation (CW-SSA), (ii) Engagement Disproportionality Detection (EDD), and (iii) Integrity-Aware Signal Attenuation (IASA), which jointly reduce the influence of unreliable or manipulated signals while preserving informative engagement. Rather than estimating intrinsic NFT value from social signals alone, NFT-TRUST evaluates the reliability of social attention and converts it into trust-aware features. An XGBoost-based model is used to capture non-linear interactions among these features. Robustness is assessed through stress testing with RL-TweetGen-ST, a reinforcement learning–based synthetic tweet generator that simulates controlled engagement inflation. Experimental results show that NFT-TRUST achieves competitive predictive performance while demonstrating improved stability under simulated manipulation. Ablation analysis indicates that credibility and integrity components are complementary and jointly enhance the reliability of social-signal-based inference. Overall, this work advances trust-aware analytics in electronic commerce and supports more reliable social-driven valuation in emerging digital markets.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050148

Authors: Guang Yu SangHee Park

With the growing commercial prominence of virtual idol livestreaming, this study examines how gaze strategies employed by virtual idols in livestreaming contexts are associated with viewers’ online interaction intention and tests the mediating roles of social presence and trust. Drawing on the SOR model, this study conceptualizes gaze strategies through a two-layer stimulus structure that integrates virtual idol behavioral cues and viewers’ perceptual responses. A 3 × 3 experimental design was employed, manipulating gaze intensity and gaze dynamics at the behavioral layer using virtual idol livestream clips as stimuli, while participants’ perceived gaze was treated as a stimulus variable at the perceptual layer. Data from 398 participants were analyzed using partial least squares structural equation modelling and multivariate analysis of variance. Results indicate that gaze intensity is positively associated with perceived gaze, which in turn is linked to higher levels of social presence and trust. By contrast, the overall effect of gaze dynamics appears more limited, although high-dynamics conditions are associated with lower levels of trust and online interaction intention. The structural model provides evidence that gaze strategies are indirectly associated with online interaction intention through the mediating roles of social presence and trust. The contributions of this study are twofold. First, it provides an empirical basis for subsequent research on virtual character behavior in livestreaming contexts. Second, it offers context-specific insight into a potential pathway through which gaze-related cues may be associated with online interaction intention.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050146

Authors: Aungkana Jattamart Paingruthai Nusawat Achaporn Kwangsawad

The extensive implementation of AI-driven chatbots in e-commerce has generated both acceptance and objection; however, previous studies have predominantly analyzed these responses separately. This study examines the mechanisms that drive dual customer responses to AI chatbots in the pre-purchase phase of the online shopping customer journey. The study integrates the Artificially Intelligent Device Use Acceptance (AIDUA) model with the Stimulus–Organism–Response (SOR) framework to explain how consumers develop both positive and negative behavioral responses to AI chatbot usage and to derive design-relevant implications for AI chatbot systems in online shopping. Data were collected from active or recent chatbot users in online shopping and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results demonstrate that social influence and chatbot anthropomorphism significantly affect consumers’ attitudes toward AI chatbot usage, whereas novelty value does not show a significant effect. Attitude toward using serves as a significant psychological mechanism that increases willingness to accept AI chatbots and purchase intention, while also being positively associated with objection to use among active or recent chatbot users. The findings extend understanding of AI-enabled interactive marketing and provide applied implications for AI chatbot system design, particularly with respect to interface anthropomorphism, transparent pre-purchase support, objection-sensitive escalation, and adaptive interaction strategies.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050145

Authors: Yeamduan Narangajavana-Kaosiri Yeamdao Narangajavana Silvia Sanz-Blas Fernando J. Garrigos-Simon

In hospitality contexts where customer experience is a key source of competitive advantage, its role in fostering brand evangelism remains insufficiently understood. Despite growing interest in customer experience, the existing literature has largely overlooked the cognitive dimension, particularly outcome expectations, and its role in linking tourist experiences to brand evangelism on social media. This study examines how customer experience influences brand evangelism through the mediating role of outcome expectations in the hospitality context. Data were collected from 452 tourists in Koh Samui, Thailand, and PLS-SEM was applied. The results indicate that customer experience, conceptualized through the dimensions of education, entertainment, esthetics, and escapism, has a significant positive effect on both self-centered and community-related outcome expectations. These outcome expectations act as key drivers of brand evangelism, reflected in customers’ willingness to share positive experiences on social media and actively promote the brand. These findings suggest that outcome expectations act as a key cognitive mechanism transforming experience into brand evangelism, particularly in digital environments where social visibility and sharing intensify consumer engagement with the brand.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050144

Authors: Nikola Draskovic Tomislav Kristof Romana Sabljic

This study investigates whether consumers’ hedonic and eudaimonic well-being orientations predict symbolic gift preferences in an online gift-choice setting. Building on evidence that hedonic and eudaimonic motives are distinct yet can co-occur, the framework predicts that congruent orientation–gift links will be stronger than cross-domain spillovers when both orientations are modeled simultaneously. Data were collected via a cross-sectional online survey with an embedded simulated online store task in which participants evaluated ten pretested gift options (five relatively hedonic; five relatively eudaimonic) as potential gifts for a close other (n = 574). Stimuli were calibrated in a pilot pretest (n = 100) to ensure separation on a hedonic–eudaimonic continuum. Hypotheses were tested using PLS-SEM with reflective measures for orientations and composite/formative outcomes for gift preferences, using nonparametric bootstrapping (5000 resamples) for inference. Results support congruent effects: eudaimonic orientation predicts eudaimonic gift preference and hedonic orientation predicts hedonic gift preference, whereas cross-domain paths are weak. Comparative tests indicate a robust hedonic congruence advantage, whereas the eudaimonic congruence advantage is directionally consistent but not statistically stable under bootstrap resampling. Gender shows a strong main effect on hedonic gift preference, while income exhibits a small positive association with hedonic gift preference. Implications for digital gift discovery and recommendation interfaces are discussed.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050143

Authors: Kiyoung Jung Sunmi Kim

Stablecoins are increasingly viewed as interoperable settlement layers within electronic commerce, yet the mechanisms through which they become activated as payment instruments remain underexplored. Extending the Unified Theory of Acceptance and Use of Technology (UTAUT) with platform interoperability and regulatory perception, this study develops a sequential adoption-to-activation framework in which technological evaluation, ecosystem compatibility, and institutional legitimacy jointly shape adoption intention and behavioral activation likelihood (BAL). Survey data from 400 digitally experienced Korean consumers with prior experience in digital payments and/or crypto-asset–related transaction environments were analyzed using hierarchical regression with HC3 robust standard errors and bias-corrected bootstrapped mediation testing. The findings show that platform interoperability exerts the strongest influence on adoption intention and also has a significant direct effect on BAL, while social influence exhibits both direct and indirect effects. By contrast, facilitating conditions and regulatory perception operate primarily through adoption intention, and performance expectancy and effort expectancy show no significant direct or mediated effects once ecosystem-level and institutional determinants are incorporated. These results identify a boundary condition of UTAUT in ecosystem-integrated payment environments: in digitally mature multi-sided commerce ecosystems, ecosystem compatibility and institutional legitimacy can operate as structurally prior conditions of activation, suggesting that stablecoin payment activation is better understood as a sequential process shaped by platform-level coordination than as a conventional intention-to-use decision centered on marginal functional gains.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050142

Authors: Tuncay Ozcan

Customer segmentation is a critical step in the efficient utilization of customer data and maximization of profitability in the e-commerce sector. Segmentation studies can yield economic benefits for firms and provide a range of insights based on customer data. This study proposes an extended RFM framework to address the shortcomings of the traditional RFM model, using customer transaction data from an e-commerce company for the period 1 January 2024–31 December 2025. The proposed framework integrates additional dimensions—campaign share, basket depth, and the standard deviation of inter-order intervals—alongside the conventional recency, frequency, and monetary values to improve segmentation. Subsequently, several clustering techniques employed for segmentation, including K-means, K-medoids, and fuzzy C-means, were considered. To determine the optimal number of clusters and assess the model fit, the results of the algorithms were evaluated using a quality index computed with multiple indices, such as the Silhouette, Dunn, and Davies–Bouldin indices. The proposed extended RFM model extends the traditional RFM framework by integrating additional behavioral dimensions such as price sensitivity, shopping regularity, and basket depth. This enriched representation of customer behavior allows for more discriminative and actionable segmentation, thereby enhancing target customer identification and enabling more precise product recommendation strategies.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050141

Authors: Li Xiong Dan Wei Xiaoliang Long

This study focuses on the transfer of the celebrity effect to live-stream e-commerce. It examines how the effectiveness of persuasion and the underlying mechanisms change when celebrities shift from live human appearances to AI avatars. Integrating Uncanny Valley Theory and Source Credibility Theory, and conducting a PLS-SEM analysis on 391 valid questionnaires collected from October to November 2025, reveals that, compared to live streaming by real celebrities, virtual streamers using celebrity avatars trigger significantly higher levels of perceived eeriness among consumers. This perceived eeriness systematically weakens audience evaluations of the streamer’s credibility, attractiveness, and expertise, ultimately leading to a decline in purchase intention. The findings suggest that, when the celebrity effect relies on an AI avatar, the persuasive pathway is negatively moderated by technological mediation. Among the dimensions of source credibility, trustworthiness is most directly eroded, while expertise remains the core factor driving purchase decisions. From a human-versus-avatar perspective, this study reveals the key psychological mechanisms underlying the digital migration of the celebrity effect. The results have important theoretical implications for understanding the boundaries of source credibility in digital communication and offer practical insights into the development and optimisation of AI avatar endorsement strategies in live-stream e-commerce.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050139

Authors: José Magano Sara Rebelo

This study develops and tests an association-based model explaining how consumers interpret AI-enabled personalization in fashion e-commerce and how these interpretations relate to behavioral intentions. Integrating perspectives from Social Exchange Theory, the Antecedents of Trust Model, Self-Determination Theory, Psychological Contract Breach Theory, and Surveillance Capitalism, we examine the joint associations of perceived personalization, transparency, data control, and privacy concerns with brand trust, perceived surveillance, privacy violation perceptions, and purchase intention. Using PLS-SEM with data from 664 online shoppers, we find that personalization, transparency, and data control are each positively associated with brand trust, while personalization and privacy concerns are positively associated with surveillance perceptions. Brand trust is negatively associated with both surveillance and privacy violation perceptions, and privacy violation is negatively associated with purchase intention. Data control is directly associated with lower surveillance perceptions, whereas transparency operates indirectly through brand trust. Mediation analysis reveals that surveillance is associated with lower purchase intention only indirectly through privacy violation (full mediation), identifying perceived privacy violation as the central psychological pathway in the personalization-privacy paradox. Multi-group analysis identifies segment-level variations by gender and education: personalization is a stronger trust cue for men, while transparency is a stronger trust cue for women; trust buffers violation more strongly for higher-educated consumers. The results highlight a trust-first personalization strategy in which relevance must be paired with meaningful transparency and data-control features to mitigate surveillance and violation appraisals, supporting positive consumer outcomes in fashion e-commerce.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050140

Authors: Inma Rodríguez-Ardura

The digital landscape keeps evolving at an extraordinary pace, prompting profound transformations in marketing schemes and changing how consumers discover, assess, and engage with brands, value propositions, and one another [...]

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050138

Authors: Shanji Yao Feifan Li Dewen Liu Lianlian Song

This research investigates the interactive influence of live-streaming background design and food processing levels on consumer behavior. Our findings reveal that for minimally processed agricultural products, an origin-based background (e.g., broadcasting directly from a farm) significantly enhances purchase intention compared to a standard studio background. We demonstrate that this effect is driven by a heightened perception of freshness. Conversely, for highly processed agricultural goods, the influence of background type is attenuated. Furthermore, we identify rural sentiment as a critical boundary condition, revealing that the positive effect of origin-based backgrounds is amplified among consumers with stronger emotional ties to rural life. These results offer nuanced insights into how digital broadcasting environments can be strategically aligned with product characteristics to optimize marketing outcomes.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050137

Authors: Angelo Leogrande Carlo Drago Alberto Costantiello Massimo Arnone

The research examines regional disparities in the diffusion of e-commerce among enterprises employing at least 10 people in Italy, using an integrated analytical framework that blends econometric modeling, machine learning, and network analysis. Instrumental Variable (IV) panel models overcome endogeneity arising from digital infrastructure, socioeconomic factors, and online business activity, with geographic slope as a suitable instrument for broadband penetration. Machine learning models—regularized regressions, random forests, and boosting—augment causal inference by registering nonlinear effects and sorting variable salience. The results, in all cases, emphasize internet use, household digital connectivity, and the prevalence of remote work as the most important predictors of the diffusion of e-commerce. Cluster analysis identifies regional digital profiles that distinguish northern-central regions from southern-insular regions, characterizing persistently distinct digital divides. The network analysis, in turn, identifies digital inclusion variables—such as internet penetration and ICT infrastructure—that occupy central positions within the entirety of the economic and technological interdependencies’ regime. Innovation and income levels, while practiced, hold peripheral positions, indicating that digital capacity, rather than economic affluence in the singular, drives online business participation. Italy’s case can particularly illustrate this beyond its national borders. Being a high-income economy with significant regional disparities, it reproduces challenges common elsewhere in the world, among which the cases of Spain, Germany, the USA, the Republic of Korea, and Japan come to mind, where regional disparities inhibit inclusive digital development. The Italian case presents, then, a transferable model for the diffusion of digital tools, the reduction in regional disparities, and the encouragement of economic integration. By synthesizing the causal, predictive, and systemic methodologies, the study offers a theoretical and practical response to digital transformation across diverse terrains.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050136

Authors: Lihuan Guo Yenchun Jim Wu

The phenomenon of followership is widely observed in the e-commerce industry. Crowdfunding, as a model of e-commerce entrepreneurship, has attracted many investors. Principal investors function as “leaders” who exert influence on follow-on (subsequent) investors. Accurately identifying principal investors in online entrepreneurial ventures and analyzing their preferences could enhance the success rate of fundraising. Grounded in the BTS (Behavior–Text–Social) framework, this study constructs a multi-dimensional model comprising 15 sub-indicators across three domains: user behavior, textual data, and social connections. A neural network is employed for training and prediction. By integrating the central and peripheral routes elicited from the Elaboration Likelihood Model (ELM), which ranks influence, principal investors are identified. The experiment results indicate that ELM-derived ranking demonstrates the highest consistency (error = 0.15), followed by user behavior (error = 0.30), social metrics (error = 0.71), and textual features (error = 0.95). Weight analysis using SHAP highlights the relative importance of structural holes, out-degree centrality, investment times, and investment moments. Furthermore, principal investors exhibit a preference for local projects and occupy dual roles. This study provides a theoretical foundation and practical guidance for identifying principal investors, thereby improving financing performance and mitigating investment risks for follow-on investors.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050134

Authors: Hee Un Park Suk Kyung Kim Duk Hee Lee Jae Jeung Rho

Digital transformation has become a central strategic priority as organizations increasingly rely on digital technologies to redesign business processes, governance structures, and value creation mechanisms in digitally evolving environments. However, existing approaches to digital transformation readiness often rely on additive maturity models or capability inventories that assume transformation capacity increases through cumulative capability development. Such approaches overlook how strategic emphasis must be distributed across transformation domains under governance and resource constraints. This study addresses this limitation by conceptualizing digital transformation readiness as a problem of strategic prioritization rather than cumulative capability accumulation. To operationalize this perspective, the study develops the Strategic Focus Index (SFI), a governance-aligned diagnostic instrument that evaluates how organizations distribute strategic attention across interdependent transformation domains. The index is constructed through a two-round Delphi study involving 53 experts from industry, academia, and the public sector, followed by statistical validation and an illustrative diagnostic application. The findings demonstrate how domain-level prioritization patterns can be systematically interpreted to identify potential imbalances in transformation efforts. By reframing readiness assessment as a prioritization-based diagnostic rather than a linear maturity measure, this study contributes a structured approach for evaluating digital transformation in digital business and platform-based environments.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050135

Authors: Jing Li Jianglei Wei Hua Pang Yungeng Xie

As Gen-AI shopping chatbots become increasingly prevalent in e-commerce, limited research has examined how consumers’ appraisals of interactive cues shape trust and continued use in privacy-sensitive retail settings. Drawing on Cognitive Appraisal Theory (CAT) and the AIDUA framework, this study investigates how novelty value, anthropomorphic attribute, and social presence influence performance anticipation, effort anticipation, and perceived privacy risk and how these appraisals subsequently shape perceived trust and continued use. Data from 549 experienced users in mainland China were analyzed using partial least squares structural equation modeling (PLS-SEM). The results show that while novelty value enhances performance and effort anticipation, it does not significantly elevate perceived privacy risk. Anthropomorphic attribute positively affects performance anticipation and negatively affects perceived privacy risk, while social presence enhances performance anticipation and effort anticipation and reduces perceived privacy risk. Performance anticipation and effort anticipation positively predict perceived trust, whereas perceived privacy risk negatively predicts perceived trust; perceived trust, in turn, strongly predicts continued use. Mediation analyses further show that cognitive appraisal variables mediate the effects of primary appraisal factors on perceived trust, while perceived trust mediates the effects of cognitive appraisal variables on continued use. Serial mediation results additionally indicate that primary appraisal factors influence continued use through cognitive appraisal and trust formation. These findings deepen understanding of the cognitive and trust-building mechanisms underlying consumer interactions with Gen-AI shopping chatbots and offer practical implications for e-commerce platforms.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050133

Authors: Dongze Zhao Xuxu Jin Wenjing Ren Ke Dong Chang-Hyun Jin

Internet advertising, while enabling unprecedented commercial reach, has become a pervasive vehicle for deceptive practices that inflict measurable harm on consumers. This study empirically investigates the structural relationships between internet advertising falsity and consumer harm by integrating analyses of the mediating role of consumer cognitive processes and the moderating role of consumer vulnerability within a unified structural framework. Survey data were collected from 600 adult consumers with online purchase experience in the Republic of Korea—an advanced digital economy characterized by exceptionally high mobile-commerce penetration, mature e-commerce infrastructure, and evolving digital consumer protection regulation—and analyzed using structural equation modeling (SEM) with AMOS 24.0, supplemented by Hayes’ PROCESS macro Model 59 for conditional process analysis. All 13 hypotheses were supported, although path magnitudes varied substantially across falsity dimensions and mediator pathways—with direct effects ranging from β = 0.156 (false scarcity) to β = 0.224 (performance exaggeration), and indirect effects dominated by the risk assessment distortion pathway. Among the four sub-dimensions of advertising falsity—factual misrepresentation, performance exaggeration, price deception, and false scarcity—performance exaggeration exerted the strongest direct effect on consumer harm. The three cognitive mediators—perceived advertising credibility, risk assessment distortion, and purchase decision pressure—all demonstrated significant partial mediation, with risk assessment distortion emerging as the most powerful indirect pathway. All four consumer vulnerability dimensions—digital literacy level, demographic vulnerability, prior victimization experience, and impulsive buying tendency—significantly moderated the falsity–harm relationship, with low-digital-literacy consumers experiencing approximately 1.7 times the adverse effect of high-literacy counterparts. Moderated mediation analysis revealed that the conditional indirect effect for the high-vulnerability group was approximately 2.3 times that of the low-vulnerability group, confirming that the cognitive harm mechanism intensifies systematically for vulnerable consumers. These findings advance consumer vulnerability theory in the digital context and offer evidence-based implications for consumer protection policy, platform governance, and digital literacy education.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050132

Authors: Anh Viet Tran Bui Thanh Khoa

Generation Z (Gen Z) consumers exhibit a distinctive multi-platform purchase behavior: they habitually discover products through social commerce (S-commerce) stimuli—including influencer content and livestream shopping—yet systematically migrate to e-marketplaces to complete their transactions. Despite the strategic importance of this behavioral pattern for platform operators, brand managers, and policymakers, the underlying mechanisms remain poorly understood. This study advances a Consumer Decision Journey framework comprising five stages—Social Commerce Stimuli, Discovery, Risk Evaluation, Marketplace Evaluation, and Purchase Decision—and integrates Stimulus-Organism-Response theory and the Elaboration Likelihood Model to explain how Gen Z consumers navigate cross-platform purchase decisions. Employing a sequential explanatory mixed-methods design, we conducted a large-scale survey (n = 423 Gen Z respondents) analyzed via Partial Least Squares Structural Equation Modeling, complemented by 18 in-depth qualitative interviews. Results confirm that influencer persuasion, livestream engagement, and perceived product authenticity drive product discovery; price comparison mediates, and price sensitivity moderates the discovery-to-risk pathway. Critically, perceived risk in S-commerce paradoxically accelerates cross-platform migration and elevates trust in e-marketplaces. Trust in e-marketplaces and logistics reliability each moderate the risk-to-purchase relationship. Qualitative analysis reveals that cross-platform behavior is a deliberate, internalized strategy among Gen Z—a platform arbitrage norm. These findings have substantial implications for S-commerce platform design, influencer marketing strategy, and e-marketplace positioning in emerging economies.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050131

Authors: Sofiane Laradi Omar Younes Ahmed H. Alsharif Md Billal Hossain

The literature emphasizes the importance of perceived social media marketing activities (SMMAs) in shaping various brand-related outcomes. However, their importance in brand attachment formation remains underexplored. Grounded in the Stimulus–Organism–Response (S-O-R) framework and Attachment Theory, this study examines the relationship between SMMAs and brand attachment, and the impact of brand attachment on brand loyalty and consumer engagement with brand social media (CEBSM). A questionnaire survey was conducted with 502 consumers of outdoor and sports brands in Algeria. Data analysis was performed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings unveil that SMMAs, including interactivity, informativeness, personalization, trendiness, and WOM, are positively associated with brand attachment. Furthermore, brand attachment is significantly associated with both brand loyalty and CEBSM. This study makes several theoretical contributions by being among the early studies to examine the individual effects of social media marketing dimensions, the role of SMMA in brand attachment formation, and brand-related outcomes alongside in-platform outcomes. This study offers recommendations to guide community managers and brand managers in clarifying the roles and capabilities of social media marketing in evoking and reinforcing brand attachment.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050130

Authors: Xiaoyu Xu Huan Sun Shuowei Jia

Despite the popularity of AI-powered virtual streamers in live streaming commerce as persistent and customizable digital intermediaries, the dynamic role of virtual streamer features across the decision journey remains unclear. Grounded in the integrated AIDA-HSM framework, this study aims to systematically investigate the multi-stage mechanism through which virtual streamer features guide consumers from attention to action in virtual live streaming commerce (VLSC) marketing. We adopt a three-stage hybrid research approach, integrating a systematic literature review, structural equation modeling (SEM), and fuzzy-set qualitative comparative analysis (fsQCA). The SEM results reveal the differential impact of distinct virtual streamer features across various stages of the consumer journey. Furthermore, the fsQCA indicates that every sufficient configuration must draw upon factors from each of the AIDA stages. This study not only pioneers the validation and contextualization of the AIDA-HSM framework in VLSC marketing, but also offers actionable guidance for practitioners to optimize their virtual streamer strategies.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050129

Authors: Elena Druică Ionela-Andreea Puiu Călin Vâlsan Irena Munteanu

The Technology Acceptance Model (TAM) has been widely used to explain e-banking and digital technology adoption. Existing literature supports the robustness of its core relationships, but the magnitude of the effects varies considerably across studies, raising questions about their stability and generalizability in new contexts. Existing meta-analysis studies focus primarily on pooled effect sizes, providing limited insight into the temporal stability of relationships, their sensitivity to individual studies, and the extent to which observed heterogeneity reflects contextual variation. This study contributes by reinterpreting heterogeneity not as a problem to be reduced, but as a feature that defines the limits of generalizability. We advance the TAM literature by moving beyond average effects and rethinking empirical evidence through the joint lens of robustness, stability, and dispersion. We conduct a random-effects meta-analysis on 44 effect sizes (correlation coefficients) coming from 43 research papers indexed in Web of Science and Scopus. In addition to pooled correlations, the analysis employed cumulative meta-analysis, leave-one-out influence diagnostics, prediction intervals, and publication bias assessments to evaluate the evolution, consistency, and variability of TAM relationships across contexts. The findings show that core TAM relationships are consistently positive and stable at the aggregate level yet display substantial variation across empirical settings. While some relationships remain robust across contexts, others exhibit prediction intervals that include zero, indicating that their strength and even direction may depend on contextual conditions. As prior TAM meta-analyses have not systematically incorporated prediction intervals, this study provides new evidence to the extent to which TAM relationships generalize beyond average effects. The results further show that although TAM offers a reliable structural framework, interventions and policies based on its core relationships must be context-sensitive, because relying on average effects alone may lead to ineffective or inconsistent adoption outcomes.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21050128

Authors: Adambarage Hansaka Methmal De Alwis Adambarage Chamaru De Alwis Marko Šostar

Business-to-consumer (B2C) e-commerce firms operate in fast-changing digital markets, where timely interpretation of external signals may strengthen organisational agility. This study examines how four dimensions of competitive intelligence—market, technological, social, and competitor intelligence—relate to organisational agility in Croatian B2C e-commerce firms. The study adopted a pragmatic explanatory sequential mixed-methods design. Quantitative data were collected through an online survey, and 208 valid responses were analysed using reliability testing, construct-validity assessment, correlation analysis, and multiple regression. Qualitative follow-up evidence was used to support the interpretation of the quantitative results. The findings show that the effects of competitive intelligence dimensions on organisational agility are not uniform. In the final validated model, social intelligence emerged as the only significant positive predictor of organisational agility, while market intelligence, technological intelligence, and competitor intelligence did not show statistically significant effects. The study therefore suggests that, in this context, systematic attention to customer conversations, online feedback, and socially visible market signals may play a more decisive role in supporting agile organisational responses than other intelligence domains. The study contributes to the competitive intelligence and agility literature by showing that intelligence dimensions should be examined separately rather than treated as a single undifferentiated capability in digital commerce settings.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040127

Authors: Hongmei Duan Ahmad Yahya Dawod Guochao Wan

AI-driven personalization (AIP) has become a core mechanism of digital commerce platforms, yet its psychological consequences remain theoretically fragmented. Drawing on the Stimulus–Organism–Response (SOR) framework and Psychological Reactance Theory (PRT), this study proposes a Threat-Substitution Mechanism (TSM) to explain how AIP shapes continuance intention in high-involvement online travel decisions. Using survey data from 488 Generation Y and Z users of Chinese online travel agencies and analyzing the model via PLS-SEM, results show that AIP significantly increases usage intention (UI) and reduces psychological reactance. Psychological reactance partially mediates the relationship between AIP and UI, indicating the presence of underlying psychological friction alongside dominant utilitarian benefits. Furthermore, privacy concerns amplify the negative relationship between AIP and reactance, suggesting that privacy-sensitive users exhibit heightened appraisal sensitivity rather than uniform resistance to personalization. By reconceptualizing the personalization paradox as a context-contingent threat appraisal process, this study advances electronic commerce research beyond parallel dual-effect models and clarifies the boundary conditions under which AIP enhances or constrains user continuance. Practical implications highlight the importance of algorithmic precision and autonomy-supportive design in AI-enabled commerce platforms.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040126

Authors: Jin-Myong Lee Sowon Kim

This study examines how mandatory digital service environments, in which human-assisted alternatives are systematically withdrawn, shape older consumers’ avoidance of self-service technologies (SSTs). We conceptualize perceived coercion as consumers’ subjective awareness of structurally constrained choice. Drawing on cognitive appraisal theory and psychological reactance theory, we propose a dual-pathway framework in which perceived coercion activates both perceived loss of autonomy and negative affect. Survey data from 389 older consumers in South Korea were analyzed using structural equation modeling. The results support a parallel mediation model, showing that perceived coercion significantly increases both mediators, each of which independently predicts avoidance intention, with negative affect showing a relatively stronger association. By conceptualizing coercion as a structural condition rather than an individual disposition, this study extends research on mandatory SST use and technology-mediated service encounters. The findings highlight the importance of autonomy-preserving and emotionally inclusive digital service systems in aging societies.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040125

Authors: Manh-Hoang Do Yung-Fu Huang Thi-Them Hoang

In the original publication [...]

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040124

Authors: Ba Phong Nguyen Weishen Wu

In recent years, virtual influencers (VIs) have been increasingly used in digital commerce. Despite the rise in VI research, past studies have yet to comprehensively examine the effectiveness of VIs, often focusing only on isolated partial models rather than an integrated framework and boundary conditions that drive consumer responses. This meta-analysis fills this gap by synthesizing 186 effect sizes from 76 studies (N = 64,545) to examine the mechanisms and moderators of purchase intention in VI marketing. The results indicate that human-likeness is a central antecedent that directly and indirectly affects purchase intention through source credibility, customer engagement, and attitude. More importantly, this study challenges prior social proof assumptions by showing that follower size has no significant impact on purchase intention in VI marketing. In addition, purchase intention is independent of a nation’s AI readiness, suggesting a borderless potential for commerce regardless of a country’s technological maturity. This study also examined the moderating effects of product type, consumer age, and uncertainty avoidance culture. Although these moderators showed initial significance, none remained significant after the Benjamini–Hochberg false discovery rate (FDR) correction. Therefore, these effects were viewed as exploratory rather than confirmatory, providing directions for future research. These findings offer new insights for e-commerce managers: success in the metaverse era depends on anthropomorphism and targeted alignment rather than metrics such as follower counts or a nation’s AI readiness.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040123

Authors: Chien-Chih Wang Yu-Teng Hsu Hsuan-Yu Kuo

Upstream textile small and medium-sized enterprises (SMEs) frequently exhibit constrained supply chain resilience owing to persistent information latency and structural dependence on downstream orders. To address these challenges, this study develops and validates a customer-to-manufacturer (C2M) intelligence framework that enables data-driven production planning using publicly available e-commerce data. The framework incorporates ethically compliant acquisition of consumer demand signals, semantic translation of unstructured market data into textile engineering attributes, machine-learning-based demand forecasting, and human-centric decision support. Utilizing 3.87 million consumer comments from 127,846 product listings, a Neural Boosted Tree model with entity embeddings for textile attributes was constructed. This model achieved a mean R2 of 0.921 in cross-validation, surpassing benchmark methods. Consumer comment volume was validated as a proxy for sales activity, facilitating demand estimation. Forecasts were translated into production guidance using Monte Carlo simulation and a decision dashboard. In a 12-month field study at a Taiwanese dyeing SME, implementation resulted in a 28% reduction in inventory value, a 31% decrease in dye lot changeovers, and a 16% increase in capacity utilization. This research extends the C2M paradigm from downstream retail contexts to upstream textile SMEs, proposes an integrated and operationally feasible intelligence framework for resource-constrained manufacturers, and demonstrates how digital intelligence can enhance supply chain resilience while supporting, rather than replacing, human decision-making. The results indicate that upstream textile SMEs can leverage publicly visible e-commerce signals to enhance production planning responsiveness, minimize inventory exposure and dye-lot disruptions, and strengthen resilience to demand uncertainty through planner-centered digital decision support.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040122

Authors: Mutlu Yüksel Avcılar Gülhan Yenilmez

This study investigates how two key characteristics of AI-enabled chatbots in mobile banking applications—perceived intelligence and perceived anthropomorphism—influence users’ cognitive and hedonic evaluations, namely perceived usefulness, confirmation, and perceived enjoyment, and how these evaluations subsequently shape user satisfaction and continuance intention. Grounded in the Expectation–Confirmation Model (ECM), the study also examines the moderating role of users’ need for interaction with service employees in these relationships. Using a quantitative research design, data were collected through a structured survey from 402 users of AI-enabled mobile banking applications in Türkiye. The proposed model was tested using partial least squares structural equation modeling (PLS-SEM), and moderated mediation effects were analyzed using Hayes’ PROCESS Macro (Model 58). The results reveal that perceived intelligence positively affects perceived anthropomorphism, perceived usefulness, perceived enjoyment, and confirmation, while perceived anthropomorphism further reinforces these effects. Cognitive and emotional evaluations significantly enhance user satisfaction, which in turn strongly predicts continuance intention toward chatbot usage. Moreover, the need for interaction with service employees significantly moderates the indirect effects of perceived usefulness, perceived enjoyment, and confirmation on satisfaction and continuance intention. By extending the expectation–confirmation model with both cognitive and emotional dimensions, this study offers novel insights into user-centered chatbot design in mobile banking and highlights the importance of individual differences in shaping sustained technology use.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040121

Authors: Ye Wang Jinye Li Minggang Yang

While existing research has established that air pollution-induced “avoidance behavior” significantly drives the growth of online food delivery volumes, the Average Order Value (AOV) remains unexplored. This study utilizes micro-transactional data provided by the store owner and employs machine learning algorithms to detect the impact of air quality (measured by the AQI) on online food delivery AOV and analyze the underlying consumer behavior. The findings indicate that: (1) Air quality deterioration significantly drives up the AOV. The global average response coefficient is 0.0053, showing a 2.4-fold acceleration effect once the AQI crosses the median (66). (2) Crucially, this growth stems from a directional divergence in consumer decision-making. Air pollution leads to the simultaneous occurrence of a reduction in average item quantity (impact coefficient: −0.0014) and a surge in Average Item Price (AIP) (impact coefficient: 0.0066). (3) Causal analysis further identifies a “substitution mechanism.” Specifically, every one-unit decrease in average item quantity induces a CNY 1.098 jump in average item price. These findings suggest a plausible behavioral logic where environmental stress may induce psychological fatigue but does not necessarily trigger “defensive frugality.” Instead, the observed pattern is consistent with a “decision avoidance” mode where consumers streamline item quantities; simultaneously, to hedge against potential experience risks resulting from simplified choices, they appear to utilize saved cognitive resources to target high-value “signature” items. Theoretically, this study fills the gap in environmental stress research regarding the price dimension of online consumption and reveals a behavioral evolution from “pure avoidance” to “value-oriented selection.” Practically, it provides empirical support for online food delivery merchants to optimize product selection, differentiate pricing, and implement precision marketing in dynamic environments.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040120

Authors: Ahmed S. M. Almamy Sufyan Habib Layla K. Nasser Nawaf N. Hamadneh

This study examines the impact of explainable artificial intelligence (XAI) features on user satisfaction and purchase intention in Saudi mobile shopping applications, utilising the stimulus–organism–response (S–O–R) framework. With the increasing reliance on AI-driven decision support in e-commerce, enhancing transparency, fairness, trustworthiness, and interpretability has become crucial for shaping consumer perceptions and behavioural responses. The research employed a quantitative methodology using partial least squares structural equation modelling (PLS-SEM) to examine the relationships among stimulus factors, cognitive and affective states, consumer satisfaction, and purchase intention. In a survey of 597 respondents from Jeddah and Makkah, Saudi Arabia, the findings highlight that fairness and bias detection, trustworthiness, and transparency significantly influence consumers’ cognitive and affective states, which in turn enhance satisfaction and intention to purchase. Consumer satisfaction emerged as a critical mediator, reinforcing the role of positive emotional and cognitive experiences in driving purchase behaviours. However, interpretability showed limited impact, suggesting that consumers may prioritise fairness and trustworthiness over technical clarity of explanations. Theoretically, this study contributes to advancing knowledge on the role of XAI in consumer behaviour by integrating fairness, transparency, and affective responses into the S–O–R paradigm. From a managerial perspective, the results underscore the importance for mobile shopping platforms to design AI systems that foster trust, reduce perceived bias, and ensure transparency, thereby improving consumer engagement and purchase outcomes. By addressing gaps in interpretability and transparency, businesses can strengthen user trust and loyalty, ultimately enhancing competitive advantage in Saudi Arabia’s rapidly growing e-commerce sector.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040119

Authors: Ovidiu-Iulian Bunea Răzvan-Andrei Corboș

Artificial intelligence (AI) is reshaping electronic retailing, yet many firms struggle to translate AI adoption into a sustainable competitive advantage, and research still lacks an integrative explanation of how digital maturity, AI implementation, AI-enabled benefits, customer experience, and competitive outcomes are linked in this context. This study develops and tests a capability-to-advantage framework proposing that digital maturity is associated with AI implementation, that AI implementation is associated with qualitative and quantitative AI benefits, and that these benefit streams are linked to digitally mediated customer experience and to differentiation and cost-based competitive advantage. Using survey data from retail employees and managers, we estimated the model with PLS-SEM and applied cIPMA to identify actionable priorities by combining importance-performance evidence with necessity-oriented insights. We triangulated the proposed mechanisms through NVivo-based sentiment and thematic analysis of open-ended comments. Results support all hypothesized relationships. Digital maturity strongly predicts AI implementation, which increases both benefit streams and directly improves the customer experience. Customer experience was the strongest downstream driver of both competitive advantage dimensions and partially mediated the effects of AI-enabled benefits. cIPMA identified customer experience and AI implementation as the primary improvement priorities; qualitative evidence was predominantly positive and highlights efficiency/cost gains and decision support alongside the capability constraints. The study integrates capability-based and customer-experience perspectives to offer a theory-guided explanation of how digital maturity and AI implementation are associated with competitive outcomes in electronic retailing while also offering guidance for managers seeking AI-driven advantage.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040118

Authors: Jaeyoung Park Sewon Eom Eugene Choi Jinho Park Seongcheol Kim

Creative expression is no longer separate from monetization. It is increasingly structured by the business models that platforms provide. Content monetization has evolved rapidly: early models focused on advertising revenue, followed by brand partnerships, and most recently, the integration of commerce-oriented features at the platform level. YouTube, for example, launched its YouTube Shopping service in South Korea in June 2024, enabling creators to sell products directly through their content. This development demonstrates that commerciality has become intrinsic to the creator economy. While prior research has emphasized factors such as authenticity, less focus has been placed on commerciality itself. This study addresses this gap by analyzing how varying levels of content commerciality affect performance, using real-world data from a Korean YouTube beauty creator agency (N = 286 short-form videos). The analysis tests the effects of three revenue models (organic, sponsored, and content-driven commerce) and two content types (context-focused and product-focused) through multiple regression. Results reveal a trade-off between engagement and revenue, as while content-driven commerce generates significantly higher engagement than sponsored content, it yields lower immediate revenue. Regarding content strategy, contrary to expectations, product-focused content consistently outperforms context-focused content in driving engagement, except within sponsored videos where a context-focused approach effectively mitigates the negative impact of overt commercial intent. These findings demonstrate the divergent efficacy of monetization models and content strategies in the short-form ecosystem. By empirically validating the relationship between commerciality and performance, this study advances theoretical discussions on the platform-driven creator economy and offers practical insights for creators, brands, and platforms navigating this evolving environment.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040117

Authors: Yachu Wang Renyong Hou Lu Xiang

Against the backdrop of a technological revolution centered on green and low-carbon development, the deep integration of digitalization and greening has become a core engine for high-quality progress. Moving beyond linear perspectives of environmental governance, this study constructs tripartite evolutionary game models to dissect the strategic interactions among government, enterprises, and consumers. Focusing on the institutional context of e-commerce, we examine how platform-enabled transparency mechanisms (e.g., blockchain traceability and carbon labeling) shape these interactions through key parameters: greenwashing detection (θ), premium loss coefficient (η), and information screening cost (CD). The analysis reveals that the long-term trajectory is fundamentally determined by the intrinsic economic viability of corporate transformation. Government intervention acts as an equilibrium selector, influencing the speed of convergence, while product value (consumer utility and premium) and platform transparency determine the sustainability of the equilibrium. Critically, the tripartite model shows that the optimal outcome—full enterprise transformation and consumer adoption—can be achieved without sustained government intervention when product fundamentals are sufficiently attractive. This demonstrates the potential for market self-regulation to sustain digital–green synergy. The study makes three contributions: it captures the full tripartite feedback loop, reveals the saturation effect of policy intensity, and embeds platform transparency mechanisms into an evolutionary framework. The findings reframe the government’s role as a temporary enabler and position e-commerce platforms as key governance intermediaries, offering a theoretical basis for adaptive governance strategies in digital commerce.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040116

Authors: Munise Hayrun Sağlam

Automated customer service and algorithmic governance are common in digital marketplaces, yet trust can erode when logistics, refunds, and escalation fail. Complaint-based risk and trust narratives in Turkey’s e-commerce marketplaces are analyzed for January 2019–December 2025 using 118,173 de-identified Turkish and English texts from Şikayetvar, a leading Turkish online consumer-complaint portal, and reviews of official marketplace apps on Google Play and the Apple App Store. BERTopic is implemented in Python with multilingual transformer embeddings, UMAP, HDBSCAN, and c-TF-IDF representations. The selected model identifies 35 micro-topics grouped into five macro-themes: fulfillment disruptions, remediation frictions, product-integrity risks, escalation failures, and governance threats. Monthly probability-weighted prevalence is estimated, and marketplace differences are evaluated with divergence measures, permutation tests, and multinomial regression controlling for time and language. Changepoint tests indicate a shift toward fulfillment grievances in April 2020, rising governance threats from June 2022, and increasing escalation failures linked to automated support from February 2023. These patterns suggest that barriers to human escalation convert operational incidents into platform-level trust judgments, offering monitoring signals for service recovery, marketplace governance, and AI oversight. By isolating escalation failures as a distinct complaint domain, the study links service automation to procedural justice mechanisms that translate operational breakdowns into platform-level trust and risk judgments.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040115

Authors: Costel-Iliuță Negricea Cristina Coculescu Ana Maria Mihaela Iordache Laura Daniela Roșca Alexandru Dan Smedescu

In recent years, the e-commerce sector has undergone continuous adaptation to both consumer needs and the economic context. This adaptation is driven by technological advances and the development of new software products. The present study aimed at achieving two primary objectives. First, it sought to assess the current state of e-commerce development in Romania within the broader European context. Second, it identified the use of AI-driven automation as a potential strategy for improving e-commerce in the country. To this end, e-commerce indicators were extracted from the questionnaire “ICT Usage and E-commerce in Enterprises,” which was conducted by National Statistical Authorities and centralized at the level of the European Commission. The questionnaire was carried out on a sample of 157,000 companies. A range of sophisticated techniques were employed to these indicators with the aim of reducing their dimensionality and classification error, with the objective of achieving a robust classification with the lowest possible error rate. We then proceeded to analyze Romania’s position in this ranking and, given the structure of e-commerce companies in the country, proposed the use of AI-driven automation as a potential strategy for enhancing activity in this sector.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040114

Authors: Nada Sarkis Nada Jabbour Al Maalouf Ella Abou Jaoude Tarek Azzi

Interactive digital commerce environments increasingly rely on influencers as algorithmically amplified intermediaries between brands and consumers. However, the process through which influencer attributes translate into brand trust remains theoretically underdeveloped. Drawing on Social Influence Theory and Source Credibility Theory, this study develops a process-based model in which consumer engagement operates as a psychological mechanism linking influencer characteristics, namely credibility, brand alignment, interactivity, and authenticity, to brand trust. Using survey data from 400 active social media users in Lebanon and partial least squares structural equation modeling (PLS-SEM), the findings reveal that all four influencer attributes significantly enhance consumer engagement, which in turn strongly predicts brand trust. Influencer–brand alignment emerges as the strongest driver of engagement, suggesting that value congruence functions as a heuristic cue in interactive digital commerce contexts. By conceptualizing engagement as a trust-internalization mechanism within platform-mediated environments, this study advances electronic commerce theory and provides context-sensitive insight into digital trust formation in emerging markets.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040113

Authors: Sven Kottmann Jürgen Seitz

This study investigates the acceptance of an AI-powered decision-support chatbot among professionals in a marketing and sales context, addressing a gap in technology acceptance research by examining data-intensive decision environments that remain underexplored. Building on the Unified Theory of Acceptance and Use of Technology (UTAUT), the study proposes an extended model incorporating Behavioral Intention, Performance Expectancy, Effort Expectancy, Social Influence, Output Quality, Time Saving, Source Trustworthiness, Cognitive Load, and Chatbot Self-Efficacy. An experimental study was conducted with 106 professionals using a chatbot-enhanced business analytics platform to complete marketing KPI analysis tasks. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results demonstrate that Behavioral Intention to use decision-support chatbots is significantly influenced by Performance Expectancy, Effort Expectancy, and Social Influence. Performance Expectancy is strongly driven by Output Quality, Time Saving, and Source Trustworthiness, while Effort Expectancy is significantly shaped by reduced Cognitive Load and higher Chatbot Self-Efficacy. The findings suggest that chatbot acceptance in professional decision-making depends not only on usability and performance beliefs but also on cognitive relief, trust in information sources, and efficiency gains, highlighting important implications for both theory and the design of AI-based decision-support systems.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040112

Authors: Abdalfatah Damaj Reema Nofal

Social media influencers (SMIs) are becoming increasingly powerful in shaping customers’ perceptions and behaviors regarding the products they purchase and the brands within digital marketing environments. This research proposes to assess the extent to which social media platforms, particularly Instagram and TikTok, affect SMIs’ capacity to persuade their followers concerning brand credibility and purchase intention. Using an online survey of 701 active users of both platforms in Palestine, the data were analyzed using structural equation modeling (SEM) through SmartPLS 4.0 for the simultaneous evaluation of both the measurement models and the structural models. The research findings indicate that follower involvement, interactivity, and emotional attachment positively influence the persuasive outcomes through the creation of parasocial relationships (PSRs) between followers and SMIs, and that these influences are different for each platform. Results show that Instagram had a larger overall influence compared to TikTok, whereas there were no differences between platforms regarding how PSRs shape follower perceptions of brand credibility and emotional attachment to SMIs; both of these perceptions are strongly linked to PSRs. Therefore, these findings underscore the importance of platform-specific engagement mechanisms in shaping PSRs and offer theoretical and practical implications for influencer marketing strategies. The findings further suggest that platform affordances may condition not only overall engagement levels but also the relative strength of persuasion mechanisms underlying PSRs and their behavioral consequences. By situating the analysis within a non-Western digital market, this study provides context-specific insights and highlights avenues for future research in comparable digital consumption environments.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040111

Authors: Hua Pang Chenyang Jin Zihan Zhou

The advancement in artificial intelligence (AI)-powered automation has accelerated the integration of AI-powered chatbots into our daily routines, opening novel channels for dynamic information flow and participatory dialogue. Whilst prior studies have examined chatbot interactivity and related outcomes, the mechanism through which information interactivity is translated into relational and advocacy outcomes remains insufficiently theorized, and its conceptual demarcation from active involvement remains underdeveloped. Grounded in Uses and Gratifications (U&G) theory, this study develops and tests a process model of AI-powered chatbot use. In this model, information interactivity is treated as an AI-powered communicative affordance, perceived value represents the mechanism through which gratifications are realized, and active involvement is conceptualized as a situational psychological state that influences customer trustiness and positive word-of-mouth (WOM). Using structural equation modeling on survey data from 588 AI-powered chatbot users, the study finds that information interactivity positively predicts functional, psychosocial, and hedonic value, all of which significantly enhance active involvement. Active involvement, in turn, exerts a significant positive effect on customer trustiness, and customer trustiness significantly promotes positive WOM. By contrast, the direct effect of active involvement on positive WOM is not significant, suggesting that trustiness functions as the more proximal mechanism through which involvement is translated into advocacy. These findings contribute to research grounded in U&G theory by demonstrating how functional, psychosocial, and hedonic value link chatbot interactivity to relational and advocacy outcomes. They also suggest several practical considerations for the development of chatbot services that are more responsive to users’ expectations and trustiness formation.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040110

Authors: Lifei Luo Jiajun Xu Rui Li

This study investigates how digital transformation influences corporate breakthrough innovation through supply chain spillovers. Using data from Chinese listed companies between 2006 and 2023, we find that upstream digital transformation significantly promotes downstream breakthrough innovation via three mechanisms: knowledge spillover, digital peer effects, and information synergy, the latter helping to mitigate the bullwhip effect. Robustness checks confirm the reliability of these results. Heterogeneity analyses reveal that the effect is stronger for firms with high absorptive capacity, operating in highly competitive industries, or with concentrated supplier bases. In contrast, downstream digital transformation also affects upstream firms, but the spillover is weaker, asymmetric, and operates only through peer effects. These findings enrich the literature on supply chain dynamics and innovation, offering practical insights for firms to harness digital synergy to expand their innovative capabilities.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040109

Authors: Pei Wang Yiwen Li Sindy Chapa Zeyuan Jing

The rise of digital platforms has transformed marketing landscapes, with live-streaming emerging as a powerful tool for engaging audiences and shaping consumer behavior. While live-streaming e-commerce is rapidly expanding in Chinese and North American markets, empirical research comparing live-streaming impulse buying (LSIB) across cultural contexts remains limited. This study examined how atmospheric cues (ACs) are associated with LSIB in China and the United States through hedonic value (HV) and utilitarian value (UV), while also considering cultural value boundary conditions. Data were collected from 396 Chinese and 408 American consumers through online survey platforms. The measurement structure was first assessed using multi-group confirmatory factor analysis, and the main structural relationships were then tested using controlled multi-group latent structural equation modeling (SEM). Composite score path models were estimated as robustness checks, and moderation hypotheses were examined using interaction regressions on composite scores. In both countries, AC was positively associated with HV and UV, and HV was positively associated with LSIB. In the U.S. sample, UV was negatively associated with LSIB, whereas the corresponding association was not significant in China. Formal Wald tests did not indicate statistically significant cross-country differences in the focal structural paths. On the HV pathway, collectivism strengthened the relationship between AC and HV in China, and long-term orientation strengthened the relationship between AC and HV in the U.S. The findings suggested that the core stimulus–organism–response (S-O-R) mechanism replicated across two market contexts, while cultural orientations mainly condition the hedonic route. The study contributed to cross-context understanding of live-streaming consumption and provides evidence-based implications for digital marketing strategy.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040108

Authors: Abdelhalem Mahmoud Shahen Mesbah Fathy Sharaf

This study offers an integrative and systematic examination of the relationship between the COVID-19 pandemic, digital payment systems, and financial inclusion. To achieve this, it adopts a dual methodological approach that combines a PRISMA 2020-based systematic literature review with bibliometric analysis. The analysis covers a set of peer-reviewed journal articles published between 2020 and 2025, using bibliometric mapping to explore the conceptual structure of the field, its main thematic clusters, and its temporal evolution. The findings indicate that COVID-19 acted as an external shock that accelerated the adoption of digital payment technologies. However, this acceleration did not automatically or uniformly lead to sustainable financial inclusion. Instead, digital payments emerge in the literature as an intermediate pathway linking the pandemic to financial inclusion outcomes under specific conditions. The strength and direction of this process depend on factors such as structural readiness, regulatory quality, digital infrastructure, levels of trust, and financial and digital literacy. Bibliometric results reveal strong conceptual convergence around three core themes—COVID-19, Digital Payments, and Financial Inclusion—forming a cohesive knowledge structure. Over time, the literature progresses from describing the crisis itself, to analyzing digital operational responses and finally to assessing longer-term inclusion and development outcomes. Overall, the study clarifies the interactive nature of the digital payments–financial inclusion nexus and proposes an integrative interpretive framework that can guide future research and support the design of more inclusive and resilient digital financial policies in post-crisis contexts.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040107

Authors: Ramazan Topdemir Gülşen Akman

The development of digital supply chains has significantly changed traditional supplier selection models that focus on static and cost-driven criteria. In addition to price, operational standards, service excellence, and contribution to the platform should be taken into account when evaluating sellers operating on dynamic, performance-oriented e-commerce platforms. This study addresses this gap by developing a comprehensive multi-criteria decision-making (MCDM) framework through a systematic literature review according to PRISMA methodology. Searches conducted in Web of Science, ScienceDirect, IEEE Xplore, Google Scholar, and Taylor & Francis yielded 4630 records from 2014 to 2025, of which 123 were analyzed using bibliometric mapping and thematic synthesis. The findings indicate a progressive diversification of evaluation criteria over time: while quality, delivery, and cost remain foundational, recent studies increasingly address customer service, search volume, and refined financial indicators such as profit and markup rate, pointing toward more multidimensional seller evaluation models. Through thematic synthesis of the indicators identified across the reviewed studies, we propose a four-dimensional framework encompassing financial sustainability, operational efficiency, quality and service standards, and market positioning. The study also discusses the implications of integrating artificial intelligence with multi-criteria and hybrid decision-making approaches for developing adaptive seller ranking systems. By synthesizing fragmented research, our framework offers strategic guidance for platform managers designing seller evaluation and allocation mechanisms.