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.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040106

Authors: Xiaochen Liu Tianyang Ma Qianqian Han Qiang Yang

Live-streaming commerce has become a routine channel for merchants, and streamers’ nonverbal cues are closely associated with consumer responses and conversion. Drawing on real live-streaming settings, this study examined the relationship between streamers’ nonverbal cues and consumer purchase behavior, and further tested whether immersion, as reflected by average watch time, helped explain this relationship. Building on Social Cognitive Theory, we constructed a multimodal dataset of 4600 product-presentation segments from 546 live sessions. Using an automated computer-vision-based framework, we measured segment-level nonverbal behaviors, including nodding frequency, gesture intensity, postural movement intensity, forward lean, and camera proximity. We then examined how these nonverbal cues were associated with consumer purchase behavior and through what mechanisms in live-streaming settings. The results showed that each nonverbal cue was positively and significantly associated with consumer purchase behavior. Mediation tests further indicated that immersion significantly helped explain the relationships between nonverbal cues and consumer purchase behavior. From a process perspective, this study extends the range of constructs examined in live-streaming commerce and clarifies how nonverbal communication is associated with outcomes, offering practical implications for streamer training, camera setup, and content design.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040105

Authors: Ahmed Saif Abu-Alhaija Mahmoud Mohamed Elsawy

Social media influencers (SMIs) have become effective intermediaries that influence consumer perceptions, attitudes, and behavioral intentions through their online presence and persuasion skills; this has made it imperative to comprehend how buyer-related variables contribute to brand loyalty within contemporary marketing research. This study, therefore, examines the effect of social media influencer capability on brand loyalty in Saudi Arabia, using brand trust as a mediating variable and authentic leadership as a moderating variable. Utilizing Social Exchange Theory and Authentic Leadership Theory, the study applied a quantitative cross-sectional survey design. Data were purposively collected from 476 active social media users in three major commercial hubs in Saudi Arabia (Riyadh, Jeddah, and Dammam). The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that authenticity and communication skills have a positive and significant influence on brand trust and brand loyalty, but expertise and influence only have a significant and positive influence on brand trust, not on brand loyalty directly, which means that the two constructs are indirectly influencing brand loyalty. The study also finds that authentic leadership significantly moderates the relationship between expertise, influence, and communication skills and brand loyalty, while the interaction with authenticity is not significant. Moreover, the mediation analysis shows that brand trust plays a significant mediating role in the relationships between communication skills, expertise and influence and brand loyalty, implying that the antecedents play a leading role in fostering loyalty by first developing trust. The study contributes to theory by offering a process-based perspective on the concept of brand loyalty that positions brand trust as a fundamental mechanism and authentic leadership as a vital enabling context. The findings have practical implications for organizations that want to strengthen brand loyalty through authentic communication, trust-building strategies, and leadership practices in social media-based contexts.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040104

Authors: Fanyong Meng Yincan Jia

The rapid expansion of mobile healthcare (mHealth) applications has transformed health-related e-commerce, creating new challenges for understanding and responding to user needs. This study proposes a data-driven framework to systematically identify and prioritize unmet user requirements from negative reviews of Chinese mHealth applications. Using a dataset of 31,124 user reviews collected between 2019 and 2025, the framework integrates sentiment analysis, topic modeling, and machine learning regression to uncover six key areas of user concern and examine their temporal evolution. Among several predictive models linking user concerns to app ratings, the k-nearest neighbors (KNN) model demonstrated superior performance. Subsequent SHAP-based interpretability analysis reveals that account authentication, system accessibility, and application stability have the most significant impact on user ratings, highlighting the critical roles of trust and technical reliability in health e-commerce. This research not only provides actionable insights for platform governance but also contributes a generalizable methodology for leveraging user-generated content to inform evidence-based management and policy decisions in mobile digital services.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040103

Authors: Ahmad Haidar

The rapid integration of artificial intelligence (AI) into digital platforms has raised critical questions about how AI’s ethical declarations influence this sector. This study adopts a mixed-methods approach. First, a descriptive content analysis examined 54 declarations, including 45 national declarations across Africa, Asia, Europe, and the Americas, and 9 from major global actors (MGAs) such as the OECD, G7, and the EU. Ethical principle frequency was examined, and a benchmarking index was developed to compare “dominant principles” cited in over 50% of regional declarations with those cited in over 50% of MGA declarations. The analysis reveals universal adoption of societal well-being, fairness, accountability, and privacy (100%), while transparency and security show regional variation (75%). Second, a semi-systematic literature review following PRISMA guidelines identified four opportunities (e.g., global participation) and seven limitations (e.g., lack of standard frameworks, definitional ambiguities, implementation challenges, and legal enforcement difficulties). The implications of these limitations for digital platforms are then examined, leading to the identification of two dimensions for responsible platform governance: assessment mechanisms (e.g., UNESCO’s Ethical Impact Assessment) and governance implementation structures. The study further distinguishes three tiers of enforceability: declarative, procedural, and institutionalized ethics, bridging normative declarations and operational practice in platform governance.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040102

Authors: Yushun Han Bing He

In the digital economy era, digital marketing has become a key strategy for firms seeking competitive advantage. However, its reliance on data has heightened exposure to cybersecurity risks. While existing research highlights the importance of digital transformation, less is known about how cybersecurity governance influences firms’ digital marketing activities. Drawing on signalling theory and the resource-based view, this study uses panel data from Chinese A-share listed firms during 2012–2023 to examine the impact of cybersecurity governance on digital marketing and its underlying mechanisms. The results show that effective cybersecurity governance significantly enhances firms’ digital marketing engagement. Mechanism analyses identify three channels. First, by preventing data breaches and negative incidents, firms enhance corporate reputation. Second, by creating a secure operating environment, cybersecurity governance strengthens risk-taking capacity and encourages marketing innovation. Third, by improving information disclosure and stakeholder communication, it alleviates information asymmetry. Heterogeneity analyses indicate that the positive effect is more pronounced for non-state-owned enterprises, firms in eastern regions, and high-tech firms. This study fills a gap in the literature by linking cybersecurity governance path to digital marketing and contributes to research on its economic consequences. The findings also offer practical implications for strengthening internal governance to support external market activities.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040101

Authors: Usama Khaliq Jinjiang Yan Nosherwan Khaliq

This study investigates the influence of Product Transparency (PT) and Pricing Strategy (PS) on customer behavior, specifically examining Market Competition (MC) as a moderating factor. Grounded in Signal Theory, the Theory of Planned Behavior (TPB), and Social Exchange Theory (SET), we propose a model where customer trust and perceived value mediate the impact of firm strategies on purchase decisions and customer retention. Using a two-wave time-lagged design with anonymous respondent matching, data were analyzed from e-commerce consumers in China and Pakistan using PLS-SEM multi-group analysis. The findings reveal that market competition undermines the positive relationships in the model, with a greater impact in China than in Pakistan. In general, the results suggest that market competition negatively influences the efficiency of product transparency and pricing strategies in shaping customer trust, perceived value, customer retention, and purchase decisions, which is why firms should be able to adjust these strategies to the levels of market competition and country context. This research provides critical theoretical insights into signal translation and offers practical guidance for international e-commerce managers to refine their customer relationship strategies in highly competitive digital environments.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040100

Authors: Jung Hwan Kim Soyoung Kim

This study identifies the psychological factors that influence consumers’ pre-order decisions and the underlying mechanism. Building on the literature on value congruence in consumer behavior and cognitive consistency theory, we examine how value congruence affects information-seeking engagement and pre-order intentions in the context of information technology (IT) products. Using partial least squares structural equation modeling (PLS-SEM), we find that when consumers perceive value congruence with IT products, they are more likely to seek additional product information, which in turn increases their pre-order intentions. Contrary to prior research that has primarily focused on the operational factors or consumers’ individual aspects in pre-order decisions, our study highlights the importance of value alignment between consumers and products in affecting pre-order decisions. Given the increasing prevalence of IT product pre-order phenomenon in e-commerce, this study contributes to the literature on pre-ordering behavior and consumer judgment and decision-making. It also provides valuable insights for effectively promoting and developing pre-order strategies when launching new products.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040099

Authors: Xue Liu Xiaoling Hao Zhiliang Pang Xing Fan

Crowdsourcing contest platforms provide enterprises with opportunities to seek external resources at a lower cost. Increasing the participation of solvers is the key to improving the success of crowdsourcing contests. Many previous studies attempt to use participation intention as a proxy for exploring participation behavior, using surveys to examine participation intention or continued participation intention. However, participation intention and participation behavior differ significantly, and the dynamic nature of influencing factors has a more complex effect on solvers’ participation. Therefore, based on social exchange theory, we use the dynamic data of winvk.com to construct a two-stage model of view and submission. The effect of dynamic competition on participation intention and participation behavior is explored. The results show that external competition has a consistent negative effect on both participation intention and participation behavior. However, the effect of internal competition is different. It has no significant effect on participation intention, but has a significant positive effect on participation behavior. In addition, rewards exacerbate the effect of competition on participation behavior. These findings provide empirical evidence for exploring differences in participation intention and behavior, and offer practical suggestions for enterprises and platforms to improve solvers’ participation in a short time.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21040098

Authors: Jean-Michel Latulippe Riadh Ladhari

Chatbots have spurred keen academic interest in the last decade, with researchers focusing primarily on the factors impacting chatbot adoption by consumers. Based on a systematic literature review (SLR) of 202 selected peer-reviewed papers published from 2015 to 2025, this article aims to achieve the following objectives: (1) describe publication trends, including relevant journals and highly-cited papers; (2) analyze the methodological approaches and theoretical models employed in the field; (3) investigate the drivers and barriers to consumers’ adoption of chatbots; and (4) outline directions for future research. Among the findings, the review reveals that perceived usefulness, perceived ease of use, anthropomorphic characteristics, consumer trust in chatbot applications, and the ability of chatbots to emulate a human-like personality are key drivers of chatbot adoption, whereas perceived risks and anxiety are the most reported barriers. This study offers several future research avenues and highlights the importance of considering the role of emotions and personality traits.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030097

Authors: Shuyuan Bai Xinquan Wang Jun Xia

The rapid integration of AI customer service in e-commerce raises an important managerial question: Can AI effectively reduce product-related information asymmetry and improve sales performance across different product types? While prior research highlights both the uncertainty-reducing benefits of information and the risks of algorithm aversion, little is known about how AI customer service performs under varying levels of product uncertainty and information asymmetry. Using a difference-in-differences design with fixed effects across time, products, shops, and categories, we examine the impact of replacing customer service with AI on sales outcomes, distinguishing between search and experience goods. We further test how the depth and breadth of product information moderate these effects. Our findings indicate that AI customer service reduces sales for experience goods but not for search goods, unless accompanied by sufficient informational depth and breadth. We argue that this effect arises because AI technically inherits and amplifies the information asymmetry inherent in experience products, while greater informational depth and breadth of product information can mitigate this amplified asymmetry. Additionally, we find that this mitigating effect is more pronounced among products with high return rate. These findings clarify when AI-generated information mitigates product uncertainty and when it exacerbates it. Our results provide actionable guidance for firms seeking to deploy AI strategically in digital commerce environments.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030096

Authors: Iván Veas-González Manuel Escobar-Farfán Gabriela Pizarro-Veloso Nelson Carrión-Bosquez Aurora Sánchez Ortiz Catalina Aliaga-Blanco Génesis Rebolledo-Santander

The emergence of social media platforms as commercial environments has necessitated the reconceptualization of service quality frameworks in electronic commerce research. This investigation analyzes and empirically validates social media quality as a multidimensional construct encompassing clarity, attractiveness, interactivity, and relevance dimensions. Grounded in means-end chain theory and uses and gratifications theory, we propose and test a comprehensive nomological network examining customer service and privacy as antecedents and their consequent effects on brand image, electronic word-of-mouth, repurchase intention, and customer satisfaction within Instagram commerce ecosystems. Using structural equation modeling with 258 Chilean Instagram commerce users, we find empirical support for all hypothesized relationships. Results reveal that both customer service and privacy are significant determinants of social media quality perceptions, with privacy demonstrating a substantially stronger effect. Social media quality, in turn, demonstrates considerable predictive power for brand image, customer satisfaction, electronic word of mouth, and repurchase intention. Importantly, customer satisfaction functions as a critical mediating mechanism, translating quality perceptions into behavioral outcomes. This research extends existing service quality literature by delineating a theoretically grounded framework for assessing quality perceptions in social commerce contexts and offering strategic guidance for optimizing social media commerce initiatives.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030095

Authors: Mashael Aldayel Abeer Al-Nafjan Reman Alwadiee Sarah Altammami Abeer Alnafaei Leena Alzahrani

The rapid growth of digital tourism platforms has intensified information overload and decision complexity for both locals and travelers, while operators struggle to differentiate their offerings and sustain profitable, data-driven e-commerce models. This paper presents Doroob, a big data and artificial intelligence (AI)-driven, context-aware recommendation system that integrates traditional recommender techniques with real-time facial emotion recognition (FER) to enable intelligent tourism commerce. Doroob combines three AI-based recommendation strategies: smart adaptive recommendation (SAR) collaborative filtering, a Vowpal Wabbit-based context-aware model, and a LightFM hybrid model. It trained on datasets built from the Google Places API and enriched with ratings adapted from MovieLens. FER, implemented with DeepFace and OpenCV, analyzes short video segments as users browse destination details, converts emotion scores into 1–5 satisfaction ratings, and stores this implicit feedback alongside explicit ratings to support adaptive, emotion-aware personalization. Experimental results show that the context-aware model achieves the strongest top-K ranking performance, the hybrid LightFM model yields the highest AUC of 0.95, and the SAR model provides the most accurate rating predictions, demonstrating that combining contextual modeling and FER-based implicit feedback can enhance personalization, mitigate cold-start, and support data-driven promotion of local tourist services in intelligent e-commerce ecosystems.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030094

Authors: Yizhen Wei David (Jingjun) Xu Kai Li

As artificial intelligence (AI) increasingly engages in managing consumer interactions on e-commerce platforms, an important question arises: how do public AI-generated replies to negative reviews compare with human replies in fostering consumer trust? This study investigates consumer trust in reply source (AI review bots vs. human agents) across three reply strategies, namely, default, thinking, and feeling, in a public review context. AI review bots are defined as automated systems that publicly respond to consumer reviews. Using a controlled laboratory experiment, we find that when using the default strategy, human replies elicit greater trust than AI replies, mediated by higher perceived authenticity and persuasiveness. Conversely, when using the thinking strategy, AI replies outperform human replies in building consumer trust, as they are perceived as more authentic and persuasive. In the feeling strategy, there is a convergence between AI and human replies. These findings demonstrate that the effectiveness of AI versus human replies depends on the strategy adopted. Theoretically, this study extends research on human–AI interaction by introducing a three-strategy framework to systematically compare AI and human communicators in public review contexts. Practically, the results guide e-commerce sellers and platforms on when and how to deploy AI review bots to effectively manage consumer trust in response to negative reviews.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030093

Authors: Saranya Shanmugam Einiyaselvi Elavarasan Narassima Madhavarao Seshadri Dharun Ashokkumar Santhoshkumar Senthilkumar Thenarasu Mohanavelu

The highly competitive nature of the online food delivery (OFD) market faces a serious retention problem, with acquiring new users typically being much more expensive than retaining existing users. Traditional prediction methods that rely primarily upon static transactional metrics such as recency and frequency are often unable to capture the psychological ‘disconfirmation’ which occurs prior to churn. To fill this gap, this study proposes a framework based on Expectation-Confirmation Theory (ECT). Unsupervised K-Means clustering was employed to classify a simulated and filtered dataset with 1500 customer records containing behaviour, geography, etc. This framework also couples sentiment analysis from BERT, allowing it to identify psychological “silent” attrition. Heterogeneous cohorts, which exhibit different psychological antecedents (utilitarian versus hedonic), were identified. The empirical results of our analyses demonstrated that Random Forest Classifiers with segment-specific features outperform baseline transactional models (F1 = 0.76) with an F1 Score of 0.89. The visual analytic interface developed provides a holistic view of the consumption process than traditional prediction models, including prescriptive, automated segment-based mitigation strategies. Our findings contradict the assumption that the “frequency–loyalty” model applies to all users. High-frequency discretionary users are found to be elastic in terms of retention and will experience significant churn. By utilising the automated action log, managers can plan targeted, highly efficient retention strategies rather than blanket discounting approaches.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030092

Authors: Shizhen Bai Zhui Gui Jiamin Zhou Jiayuan Zhao

Virtual anchor livestreams have rapidly become an efficient e-commerce format, attracting large audiences through distinctive avatars and real-time interactivity. However, technical constraints and the physical limitations of virtual anchors limit the ability to evoke the vicarious proximal sensory perceptions of products. Therefore, it is essential to investigate strategies that compensate for this deficiency and enhance the effectiveness of live streaming to meet consumer demand. This study explores the effect of a virtual anchor’s proximal sensory fit in product descriptions on purchase intention through two experiments. The results show that a higher sensory fit positively affects purchase intention. The chain mediating effect of perceived authenticity and attractiveness is significant. Product display positively moderates the relationship between sensory fit and purchase intention. This study provides new theoretical perspectives and practical guidance for virtual anchor marketing, emphasizing that marketing effectiveness can be enhanced through reasonable product display and sensory descriptions.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030091

Authors: Ru Wang Shugang Li Liqin Zhang

This study is based on the practical context of the livestream e-commerce industry’s shift from “traffic competition” to “quality competition”. Addressing the limitations of existing research that predominantly focuses on streamers’ external traits while overlooking intrinsic qualities and frequently employs linear models that oversimplify the decision-making processes of consumer purchasing behavior (CPB), a theoretical framework grounded in the Elaboration Likelihood Model (ELM) is developed to explain how streamer traits drive consumer trust and identification through dual pathways. This study adopted a mixed-method approach combining structural equation modeling (SEM) and artificial neural networks (ANNs). By analyzing 408 valid questionnaires, it systematically investigated the driving mechanisms through which streamer traits affected consumers’ trust and identification. The study found that streamers’ integrity significantly enhanced perceived trust and perceived identification via the central route. While awareness could strengthen identification, it had no significant effect on trust building, revealing the inherent tension between “traffic” and “quality”. ANN analysis further demonstrated that the nonlinear combination of traits more effectively predicts consumer responses than traits. This study provided empirical support for the “quality transformation” of livestream e-commerce from both theoretical and methodological perspectives, offering important implications for platforms to develop a quality assessment system centered on trust and identification and to optimize the streamer cultivation mechanism.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030090

Authors: Afruza Haque Rasheda Akter Rupa Md. Faisal-E-Alam Most. Sadia Akter Nahida Sultana

In the online shopping context, the proliferation of digital platforms has contributed to an increase in impulsive buying behavior (IBB), which can sometimes lead to regret. This study aims to explore the intrinsic and extrinsic stimuli that influence consumers’ online impulsive buying behavior, which subsequently affects their post-purchase cognitive dissonance, with the moderating role of price consideration (PC). The conceptual framework was formulated using the Stimulus–Organism–Response (S-O-R) model. A total of 813 responses were collected and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings revealed that perceived utilitarian value (PUV), perceived enjoyment (PE), fear of missing out (FOM), and green trust (GT) positively impact online impulsive buying behavior (IBB), which, in turn, positively impacts post-purchase cognitive dissonance (PCD). Moreover, a significant moderating role of PC is found in the relationship between IBB and PCD, suggesting that consumers with low price consideration tend to regret their impulsive buying more. The findings provide insights that guide online retail sellers and digital marketers to develop or implement customized strategies based on the intrinsic and extrinsic stimuli that influence customers’ impulsive buying and subsequent post-purchase cognitive dissonance.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030089

Authors: Yingchao Lu Peng Zou Di Huo Yu Chen Wen Li

Platform-generated default reviews are widespread in e-commerce, yet they are underexamined as a review system design feature. Using 1994 Taobao product snapshots from two windows (January–April 2025, n = 983; December 2025–January 2026, n = 1011) surrounding a gradual interface redesign that folded default reviews from the default view, this study examines how the default review ratio relates to sales and whether reduced visibility moderates the association. Regression results show that higher default review ratios are associated with lower log sales prior to the redesign, while the negative association attenuates once default reviews are de-emphasised; conditional sales levels are also higher post-redesign. Because the rollout was gradual and the data are repeated cross-sectional snapshots, estimates are interpreted as differences in conditional associations across regimes. These patterns are robust to alternative specifications, additional controls, category-specific post shifts, and winsorization. Overall, the market impact of platform-generated review signals depends on interface visibility, highlighting an actionable governance lever for review system design.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030088

Authors: Dam Tri Cuong Bui Huy Khoi

The objective of this study is to conduct a systematic literature review of repurchase intention in social commerce. Specifically, the study examines the current state of research, identifies the key determinants of repurchase intention, and synthesizes background theories and measurement approaches applied in this domain. This research employed the PRISMA procedure for a systematic literature review conducted across two databases: Web of Science and Scopus. A total of 177 papers were identified from databases, with no restrictions on publication year, facilitating the assessment of all pertinent research on the topic. After screening, eligibility for evaluation was based on the study’s objective; ultimately, 27 publications were identified for systematic review and analysis. The results underscore the top five primary determinants of repurchase intention in social commerce: trust, social influences, user experience, perceived value and social commerce attributes. Furthermore, the research identified 16 theoretical foundations for examining repurchase intention in social commerce, with the Stimulus–Organism–Response framework and the Technology Acceptance Model as the primary theories for this systematic review. Furthermore, the findings indicated that partial least squares structural equation modeling remains the predominant measurement technique, but alternative methods continue to be used.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030087

Authors: Xiaoyu Niu Dequan Zheng Yuemei Ding

To examine how digitally empowered rural e-commerce affects the market-oriented allocation of urban–rural factors at the county level and the underlying mechanism, this study treats the National E-commerce into Rural Counties Demonstration Program as a quasi-natural experiment. Using a panel of 1898 Chinese counties from 2000 to 2022, we conduct multi-period DID with staggered adoption and mediation analyses. The results show that rural e-commerce significantly raises the marketization level of factor allocation; the effect grows stronger over time and is most pronounced during the rapid-expansion phase, in agriculture-oriented e-commerce counties, in poverty-stricken counties, and in the Central and Western regions. The impact operates mainly through three channels: enlarging market size, upgrading industrial structure, and deepening digital financial usage. Notably, the digital finance channel exhibits a suppression effect, suggesting a complex role of financial digitalization in the early stages of rural development. To further ensure the robustness of our findings, we also conduct rigorous checks using the CSDID method and alternative proxy variables, consistently reaffirming the policy’s significant positive impact. These findings offer actionable evidence for deepening county-level factor-market reforms and advancing common prosperity, leading to policy recommendations on strengthening county digital infrastructure, tailoring e-commerce support systems, and improving the institutional environment for factor mobility.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030086

Authors: Jihye Choi Seunggyu Kang Jonghyeon Moon Soobean Jeon Sesil Lim

Algorithmic transparency is widely considered essential for fostering trust in AI-based financial e-commerce services. However, empirical evidence remains limited on whether transparency benefits all consumers uniformly and how it is evaluated relative to other service attributes in realistic decision contexts. This study examines how consumers trade off transparency, personalization, and user control in robo-advisor (RA) services across different consumer segments. Through a discrete choice experiment and latent class logit modeling, two distinct segments are identified: selective high-expertise investors, who prioritize personalization and user control over transparency, and receptive general consumers, who respond strongly to enhanced explainability. These findings indicate that algorithmic transparency does not serve as a universal design solution but operates conditionally based on consumer expertise and attribute interactions. Simulation results further show that while a regulation-compliant, uniform service design may facilitate market entry, it constraints long-term expansion in heterogeneous markets. In contrast, a segment-based service portfolio calibrated to the distinct preferences of each group significantly increases overall adoption under the same regulatory constraints. These results suggest that sustainable AI diffusion in financial e-commerce requires a nuanced approach that balances disclosure with functional autonomy to address the diverse needs of both sophisticated and novice users.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030085

Authors: Tingting Zhu Yu Zhang

The revitalization of time-honored brands has been identified as a strategic priority in China’s national development agenda, yet many long-established brands continue to face declining market share and limited engagement with younger consumers. E-commerce livestreaming, characterized by real-time interaction and broad digital reach, has emerged as a potentially powerful channel for reversing this trend. However, the mechanisms through which livestreaming strengthens brand identification with time-honored brands among young consumers remain poorly understood. Drawing on the stimulus–organism–response (SOR) framework, social presence theory (SPT) and parasocial interaction theory (PSI), this study investigates how streamer characteristics—popularity, professionalism, and interactivity—shape brand identification with time-honored brands in livestreaming environments. Survey data were collected from 434 young consumers aged 18–40 who had viewed time-honored-brand livestreams within the previous six months. Structural equation modelling was used to test a model incorporating social presence, perceived authenticity of time-honored brands, and trust in time-honored brands as sequential mediators and consumer–streamer relationship strength as a moderator. The results show that streamer popularity and professionalism significantly enhance both social presence and perceived brand authenticity, whereas streamer interactivity primarily strengthens social presence. Social presence and perceived authenticity both increase trust in time-honored brands, which in turn predicts brand identification with time-honored brands. Streamer popularity and professionalism influence brand identification through two serial mediation pathways—via social presence and trust, and via authenticity and trust—while streamer interactivity operates mainly through the social presence–trust pathway. In addition, consumer–streamer relationship strength amplifies the effect of social presence on trust but attenuates the effect of authenticity on trust. By integrating SOR with SPT and PSI in a moderated serial mediation framework, this study provides new insight into how livestreaming transforms external cues into durable brand identification with time-honored brands among young consumers. The findings extend time-honored branding theory into digitally mediated commerce and offer evidence-based guidance for the strategic renewal of time-honored brands in the platform economy.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030084

Authors: Yawen Yang Qiang Yang Xiaochen Liu

With the rapid growth of e-commerce platforms, consumers increasingly make purchase decisions without direct physical interaction, particularly for tactile-dependent categories such as furniture and home décor. Drawing on embodied cognition, this study investigates how visual-based tactile cues influence consumers’ purchase intention on e-commerce platforms. Using experimental methods, two studies manipulate the level of visual-based tactile cues (high vs. low) and examine their effects on purchase intention. The results show that richer visual-based tactile cues significantly increase purchase intention. Contrary to traditional information overload assumptions that additional visual detail may hinder decision-making, this effect occurs through enhanced immersion rather than increased cognitive burden, suggesting that visual-based tactile cues operate as embodied sensory triggers instead of purely informational inputs. Furthermore, cross-modal mental imagery moderates this process in a counterintuitive way: the indirect effect of visual-based tactile cues on purchase intention via immersion is stronger when consumers’ imagery ability is lower, indicating a compensatory role of external sensory cues. By conceptualizing visual-based tactile cues as an innovation in interactive marketing within new media environments, this research offers actionable design implications for e-commerce platforms in enhancing tactile perception through visual presentation and improving conversion effectiveness.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030083

Authors: Abhishek Sharma

With the growing integration of AR/VR/Metaverse technologies across luxury brands, advertising has shifted to providing consumers with a personalised experience in which they can engage with brands via digital avatars. Given the considerable success of Metaverse advertising, it is apparent that organisations need to reinvent their advertising strategies to enhance consumer experience and brand engagement over digital platforms. However, this reinvention would require organisations to develop an advertising strategy that creates a coherent brand experience for consumers and provides them with an immersive brand experience on Metaverse platforms. As a result, this study undertakes a bibliometric approach to provide a comprehensive understanding of how integrating Metaverse platforms with advertising strategies can enhance brand engagement among consumers. More precisely, a keyword search strategy is formulated, and a multi-database search is performed across key databases, including Scopus, EBSCOhost, and ProQuest. In doing so, results from Scopus databases are visualised through network and overlay visualisation maps to understand how key themes/knowledge structures are associated with Metaverse advertising and brand engagement. Besides this, the study also showcases the key theoretical perspectives (i.e., psychological perspectives, value-based perspectives, technology/innovation perspectives, and social interaction perspectives) across these studies to understand how brands have well-infused Metaverse advertising to enhance brand engagement among consumers. Lastly, the study also provides a deeper understanding of the key challenges that are associated with the widespread implementation of Metaverse advertising.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030082

Authors: Ghaith Al-Abdallah Nadine Khair Paiman Jatto

This study examines how followers’ social identity dimensions—cognitive, evaluative, and affective—affect their purchase intention for fashion products promoted by Instagram influencers. It also explores the mediating role of source credibility factors, including trustworthiness, expertise, and attractiveness, in strengthening this relationship. Targeting millennial females, a key fashion consumer group, the study applies social identity theory, source credibility theory, and influencer marketing literature to develop its conceptual framework. A quantitative, correlational approach was used, employing a self-administered questionnaire distributed via a convenience snowball sample of millennial females in Erbil, Kurdistan. Data from 421 respondents collected between were analyzed using SPSS AMOS version 24. Findings reveal that all social identity dimensions significantly influence purchase intention, and source credibility factors play a direct mediating role in this relationship. These insights offer practical implications for marketers and influencers, helping them understand the impact of followers’ social identity on purchasing behavior and refining influencer marketing strategies. This research expands influencer marketing literature by demonstrating the mediating effect of source credibility on the link between social identity and purchase intention. This research provides practical implications for enhancing millennial consumers’ purchase intentions by leveraging social identity mechanisms. The findings offer valuable insights for both social media influencers and brands seeking to employ influencer marketing strategies effectively in fashion promotion.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030081

Authors: Dayun Jeong

The rapid evolution of technology characteristics has significantly influenced various sectors, including fashion, in which technology-enabled platforms have increasingly been utilized to enhance personalization and consumer engagement. This study investigates the effect of these characteristics on consumer behavior within fashion curation platforms. Integrating the task–technology fit and the unified theory of acceptance and use of technology models, this study examines key constructs using structural equation modeling. Data were collected via a week-long survey of 300 Korean consumers using fashion curation platforms. The findings reveal that technology characteristics exert a significant influence on task–technology fit and effort expectancy. Additionally, hedonic motivation, social influence, and facilitating conditions were pivotal in shaping behavioral intention. The novelty of this work lies in the fact that it extends the integrated model framework to a fashion curation context to offer a more nuanced understanding. Moreover, the findings provide practical insights for optimizing technology-enabled fashion platforms to boost user adoption and engagement.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030080

Authors: Horng-Jinh Chang Chen-Hsiu Chen

This study integrates the SOR framework with signalling theory, centring on information disclosure transparency as the core construct, to systematically examine its direct and indirect effects on consumers’ purchase hesitation. It specifically investigates the mediating roles of seller uncertainty and product uncertainty, whilst also testing the moderating effects of product price, type, and attributes. The research employs PLS-SEM in conjunction with the PROCESS Macro for empirical validation, drawing on 814 valid responses collected from online consumers in Taiwan. The principal findings indicate the following: (1) information disclosure transparency exerts a significant negative direct effect on purchase hesitation (B = −0.582, p < 0.001); (2) both seller uncertainty (indirect effect = −0.061) and product uncertainty (indirect effect = −0.060) exhibit partial mediation; (3) the model demonstrates strong predictive relevance for purchase hesitation (Q2 = 0.486), underscoring its robust explanatory power in consumer decision-making processes; and (4) product price, type, and attributes significantly moderate the relationships between information disclosure transparency and the two uncertainty constructs. By extending signalling theory—originally developed in traditional markets—to the digital consumption context, this study provides empirical support for the signalling efficacy of information disclosure. It thereby offers an alternative theoretical lens for analysing consumer behaviour in online environments.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030079

Authors: Yishu Tang Hosung Son

Emerging digital technologies are increasingly embedded in consumer-facing financial services, reshaping how users experience, evaluate, and engage with AI-mediated interactions. This paper investigates how the perceived sociality of AI Digital Human Advisors influences user experience in digital financial services. Sociality—defined as the extent to which users perceive an AI Digital Human Advisor as a socially capable actor (e.g., responsive, relational, and role-embedded) rather than a purely functional tool—was experimentally manipulated across four controlled behavioral experiments simulating interactions on financial platforms. The results from four controlled experimental simulations consistently demonstrate that, under controlled interaction conditions, high-sociality AI advisors significantly enhance both utilitarian and hedonic value. Social presence was found to partially mediate these effects, revealing the psychological mechanism through which social cues embedded in emerging AI technologies are transformed into experiential value. Furthermore, two boundary conditions were identified: communication style and usage context. Communication framed around task completion amplified the influence of sociality on utilitarian value, whereas interaction styles emphasizing social connection strengthened its effect on hedonic value. Likewise, purchase-related scenarios heightened functional perceptions, while browsing situations elicited stronger emotional responses. By situating AI Digital Human Advisors within the broader context of emerging digital technologies, these findings extend Social Response Theory into AI-mediated financial environments and provide insights into how technologically enabled social cues shape consumer experience and behavior in digital finance.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030078

Authors: John Yang

This study explores the effects of algorithmic governance on consumer responses, with a particular focus on the role of territorial psychological ownership (TPO) as a moderator. In increasingly automated digital environments, consumers interact with algorithms that govern content, services, and personalized experiences. This research demonstrates that TPO influences consumer reactions to algorithmic actions, such as the perceived intrusiveness of automated systems, which subsequently affects brand attitude and purchase intention. The findings highlight the importance of understanding how algorithmic governance can be designed to optimize consumer interactions while maintaining consumer satisfaction. By balancing the need for personalized experiences with respect for consumer autonomy, businesses can create more effective and efficient governance systems that avoid negative consumer perceptions. This study offers key insights for companies looking to navigate the delicate balance between providing personalized services and respecting consumer preferences, ultimately ensuring positive interactions with automated systems.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030077

Authors: Hyuk Kwon

This study aims to analyze the effect of individuals’ digital capital on life satisfaction in the digital global marketing environment and to structurally verify the mediating effects of digital self-efficacy and the level of E-commerce utilization in this process. For this purpose, data from the 2023 Digital Divide Survey conducted by Statistics Korea was utilized, and Structural Equation Modeling (SEM) analyses were conducted. The results indicate that the sub-factors of digital capital—digital competence, digital support resources, and social capital—all have significant positive effects on digital self-efficacy. Furthermore, digital self-efficacy exerts a significant positive influence on both the level of E-commerce utilization and life satisfaction. In addition, the level of E-commerce utilization was found to have a modest but statistically significant direct effect on life satisfaction. Mediation analysis based on SEM revealed that digital self-efficacy functions as a key mediating mechanism linking digital capital to life satisfaction. While indirect effects through digital self-efficacy were consistently supported, the sequential mediation pathway involving both digital self-efficacy and E-commerce utilization level appeared relatively weak, suggesting that psychological confidence plays a more central role than behavioral usage alone. Overall, these findings suggest that digital capital extends beyond mere access to technology or frequency of use and forms a structural pathway influencing quality of life primarily through psychological empowerment and, to a lesser extent, digital behavioral engagement. This study contributes to digital divide research by presenting an integrated analytical framework connecting digital capital, digital self-efficacy, E-commerce utilization level, and life satisfaction, and provides empirical evidence supporting the importance of policies and educational interventions that enhance individuals’ digital self-efficacy alongside practical e-commerce-based digital education.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030076

Authors: Emre Yıldırım Sima Nart Osman M. Karatepe

Online customization has become a prominent strategic approach for delivering personalized value. However, prior research has largely examined isolated relationships such as trust and purchase intention, customization and value, or value and loyalty. This study situates the issue within the broader context of digital co-creation and aims to provide an integrated explanation of how trust in an e-vendor and participation in e-customization shape multiple dimensions of customized product value and subsequent repeat purchase intention. Using survey data from 312 customers with prior online customization experience, the proposed relationships were tested through structural equation modeling. The results suggest that trust in an e-vendor increases participation in customization, which in turn enhances utilitarian value, uniqueness value, and self-expressiveness value. These value components positively influence repeat purchase intention, and several mediation effects have emerged. Specifically, participation partly mediates the effect of trust on all three value dimensions, while uniqueness value and self-expressiveness value partly mediate the effect of participation on repeat purchase intention. Overall, the findings provide empirical evidence for a trust–participation–value pathway and highlight the importance of both functional and symbolic value outcomes in sustaining customer engagement in online customization environments.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030075

Authors: Jia-Qi Feng Chao Xu Sung-Eui Cho

This study examines customers’ continuance intention in metaverse services by integrating technological, content, and social-relational dimensions and assessing the role of immersiveness. Six focal antecedents are considered, namely, technological sophistication, security, content creativity, content richness, social interaction, and social presence. Survey data from 231 metaverse users in China show that technological sophistication, content creativity, social interaction, and social presence are positively associated with immersiveness, whereas security and content richness are not. In addition, continuance intention is positively associated with technological sophistication, security, content richness, social interaction, and immersiveness. Despite the absence of clear indirect effects via immersiveness, the results suggest that continuance intention reflects not only immersive experience but also post-adoption evaluations of assurance and usefulness. As metaverse services move toward broader adoption and commercialization, these findings distinguish experience-building drivers from retention-relevant factors and offer implications for service development, content strategy, and community experience design.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21030074

Authors: Yanbo Zhang Chuanlan Liu

Artificial intelligence (AI) has become a transformative force in fashion e-commerce, reshaping how consumers interact with brands across design, marketing, and retail. However, a systematic synthesis of recent empirical research on consumer interactions with AI in fashion remains underexplored. This study utilizes both systematic and bibliometric approaches to review 50 empirical articles published between 2022 and 2025, retrieved from Scopus and Web of Science, to reveal dominant topics and intellectual structures. Guided by the Theme–Theory–Method (TTM) framework, the review employs systematic content analysis complemented by bibliometric mapping to identify key themes, trends, theories, and methods in existing AI-related consumer studies in fashion. AI-powered chatbots and general AI services are most frequently examined, with the Technology Acceptance Model and Stimulus-Organism-Response framework as leading theoretical lenses. Quantitative research designs prevail, though qualitative and mixed-method approaches are emerging. Based on the findings and identified gaps, a TTM-guided future research agenda is proposed to inform theoretically grounded and practically relevant investigations in the fashion domain, meanwhile contributing to the broader advancement of e-commerce scholarship and practice. This study offers the first integrated synthesis of AI-related empirical consumer research in the contemporary fashion context and the Generative AI era.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21020073

Authors: Yitao Chen Zhixi Zhang Li Zhou Zhijie Chen

“Cashback for positive reviews” is a common form of e-commerce manipulation that may undermine consumer trust and distort the market evaluation system. However, there is a lack of systematic research on how it influences consumers’ willingness to provide evaluations through psychological mechanisms. This study, based on the Stimulus–Organism–Response (S-O-R) framework, integrates the theories of psychological contract and cognitive dissonance. An empirical analysis based on 460 valid questionnaire responses was performed using SPSS and AMOS, yielding the following findings. (1) Negative emotions, including disappointment, anger, and regret, significantly triggered psychological contract breach, both transactional and relational. (2) Psychological contract breach reduced consumers’ willingness to provide positive reviews and lowered their store evaluation behavior, fully mediating the relationship between negative emotions and evaluation behavior. (3) Cognitive dissonance partially moderated the pathway from negative emotions through psychological contract breach to review behavior. This study elucidated the influence mechanism of negative emotions in “cashback for positive review” scenarios on consumers’ evaluation behavior, established a “merchant-user” online review relationship model, and provided practical and managerial implications for fostering mutually beneficial outcomes among platforms, merchants, and consumers.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21020072

Authors: Fangfang Ma Shaochuan Fu Yuanyuan Zhang Zhengwei Lyu

Retailers must reevaluate store positioning when implementing omnichannel strategies. This study examines retailers’ strategic preferences toward in-store services, including Buy-Online-Pickup-in-Store (BOPS), Buy-Online-Return-in-Store (BORS), and their combined offering. A stylized model incorporating capacity constraints and strategic consumers’ purchase behavior is developed to analyze omnichannel impacts on brick-and-mortar operations from an inventory perspective. Firstly, profit-maximizing retailers benefit from reducing online channel inventory when handling product returns. Under high online return rates or stringent capacity constraints, retailers prefer maintaining physical-only channels to mitigate returns and capture cross-selling opportunities. Secondly, offering BOPS services remains a strategic advantage during periods of moderate capacity utilization. When the online consumer market expands, spillover effects increase, return rates decrease, and capacity constraints ease, it becomes feasible to consider jointly providing BORS services. Finally, BORS may migrate offline shoppers online, making it unsuitable for high-return-rate products. For omnichannel retailers, this study offers valuable insights into implementing omnichannel strategies under capacity constraints, empowering practitioners to make more informed decisions and optimize operational tactics.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21020071

Authors: Yang Yu Miaomiao Li Honglei Li Kuanwei Wu

In the rapid diffusion of artificial intelligence (AI), firms increasingly rely on AI to reshape user interactions, yet how such interactions translate into sustained innovation remains unclear. Adopting a user–producer interaction perspective, this study examines how AI-Driven User–Producer Interaction (ADUPI) affects User–Producer Interconnected Innovation (UPII), focusing on the mediating roles of User–Producer Knowledge Exchange (UPKE) and User–Producer Knowledge Integration (UPKI), as well as the moderating effect of AI Readiness (AIR). Using survey data from 974 firms and applying regression, mediation, moderation, and bootstrap analyses, the findings show that ADUPI significantly enhances UPII. Moreover, UPKE and UPKI jointly mediate this relationship, forming a dual mediation mechanism in which knowledge integration exerts a stronger effect than knowledge exchange. In addition, AIR positively moderates the effects of ADUPI on both UPKE and UPKI, amplifying innovation outcomes under higher AI readiness. This study advances AI and innovation research by shifting the focus from internal firm capabilities to cross-actor interaction, clarifying differentiated knowledge mechanisms, and highlighting AI readiness as a key condition for value realization. The results also provide actionable insights for firms seeking to convert AI-driven interaction into interconnected innovation through improved AI readiness and knowledge management.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21020070

Authors: Shuxia Sui Yunzhong Yang Xiaogang Ma Ting Li

To address the challenge of complex quality control in shared manufacturing arising from loose “partner” relationships, a quality disclosure mechanism is incorporated into a shared manufacturing supply chain. By developing a platform-led game-theoretic model, it compares four quality disclosure strategies under third-party and self-built shared manufacturing platforms, filling a theoretical gap on how quality disclosure aligns with different platform models. The findings indicate that: (1) Quality disclosure always increases platform profit, providing theoretical support for the economic incentives for platforms to promote quality transparency. (2) Under third-party shared manufacturing platforms, all manufacturers prefer unilateral disclosure by the high-quality manufacturer, indicating that this platform model naturally generates a high-quality-led signaling mechanism and reduces coordination costs. (3) Under self-built shared manufacturing platforms, strategy choice is conditional: when the disclosure level is very high, the high-quality manufacturer counter-intuitively induces the low-quality manufacturer to disclose in order to avoid excessive guarantee risk; when the market quality gap is large, bilateral disclosure is the equilibrium, jointly building market trust; when the quality gap narrows, the equilibrium returns to unilateral disclosure by the high-quality manufacturer to strengthen the quality signal.This study provides a new theoretical framework for understanding quality signaling in multi-actor collaborative settings and offers managerial insights for shared manufacturing platforms to design disclosure mechanisms and for manufacturers to choose cooperation modes.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21020069

Authors: Shoufen Jiang Lingbin Zhao

Drawing upon social presence and perceived value theories, this study examines how time-limited (TL) and quantity-limited (QL) promotions influence consumers’ purchase intention in live-streaming shopping. Through two controlled experiments (using countdown prompts for TL and inventory visualization for QL), the findings reveal distinct mechanisms: TL promotions elevate functional value by fostering a perception of collective synchronicity, whereas QL promotions boost social value identification through the perception of interactive control. Notably, this latter pathway is moderated by social cue sensitivity. Theoretically, this work unveils a “dual social presence–perceived value” framework that overcomes the limitations of single-mediation models and integrates evidence from eye-tracking and neurobehavioral analysis. Practically, it proposes a strategic promotion-matching criterion (recommending TL for high-circulation goods and QL for scarce items) to optimize live-streaming marketing effectiveness.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21020068

Authors: Yonggang Wang Huanchen Tang Jingchun Zhang Yubo Wang Xiaodong Liu

Under the rapid development of live commerce, impulse buying has become a core consumption phenomenon, yet its psychological triggering pathways across different consumer groups remain to be fully elucidated. Drawing on the S–O–R framework, this study conceptualizes live-stream interactivity, novelty, and streamer attractiveness as external “stimuli,” and positions immersive experience as the core “organism” mechanism, thereby constructing and testing an integrated “stimulus–experience–response (impulse buying intention)” model. Using a mixed-method approach that combines structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA), the results show that all three live-stream features significantly enhance impulse buying intention, primarily by strengthening immersive experience, with immersion exerting a significant partial mediating effect. Moreover, consumers’ loneliness significantly amplifies the indirect effect of live-stream features on impulse buying via immersive experience. The fsQCA further uncovers multiple equivalent pathways leading to high impulse buying intention, including a strong-experience pattern centered on “streamer attractiveness + immersive experience,” as well as a social compensation pattern centered on “high interactivity + high loneliness.” This study provides a testable theoretical framework, actionable operational strategies, and sustainable ethical guidance for live commerce, offering a pathway for the industry to achieve a “high experience × high conversion × high well-being” triple-win outcome.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21020067

Authors: Bahri Baran Koçak

Despite the significant potential of AI applications in tourism marketing communication, consumers’ attitudes and behaviors towards the outputs of these applications are still a mystery. To fill this research gap, the current study examines and compares consumer engagement (CE), novelty and attitude perceptions towards tourism destinations and hotel promotional content created by ChatGPT-4o (vs. human) for social media and web pages. According to the results, ChatGPT-generated messages (GPTGMs) play a crucial role on social media compared to human-generated messages (HGMs). Moreover, based on the theory of uses and gratifications (UGT), tourists’ perception significantly varies between platforms (social media vs. web pages). This research provides insights for marketers on optimizing message design and selecting effective platforms based on consumer reactions to GPTGMs.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21020066

Authors: Xingqi Wang Yanjie Ren

This study investigates how algorithmic governance, a core feature of modern e-commerce platforms, impacts the consumption behavior of its service providers—specifically, ride-hailing drivers’ preference for high-calorie food. From an e-commerce ecosystem perspective, the dynamic interaction between platforms and their service providers is critical for long-term value co-creation and platform sustainability. By examining how algorithmic control mechanisms spill over into drivers’ off-platform behaviors, this research offers crucial insights for designing more sustainable and human-centric platform business models. Analyzing 710 survey responses from ride-hailing drivers in China via PLS-SEM, our findings reveal that algorithmic tracking evaluation and behavioral constraints are positively associated with high-calorie food consumption, with emotional exhaustion acting as a key mediator. Notably, standard guidance algorithms showed no significant effect. These results contribute to the e-commerce literature by demonstrating how platform-centric control can inadvertently lead to adverse externalities that may undermine service quality and provider well-being, ultimately posing a risk to the platform’s brand reputation and operational stability. We offer practical recommendations for e-commerce platform managers on optimizing algorithmic strategies to foster a healthier and more sustainable gig worker ecosystem.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21020065

Authors: Silvia Ghita-Mitrescu Ionut Antohi Cristina Duhnea Andreea-Daniela Moraru

The digital transformation of financial services has changed how customers interact with banks through electronic channels, yet the factors influencing channel choice between branch-based and digital banking are not entirely understood, especially in emerging European markets. This study investigates banking channel preferences over three consecutive years (2023–2025) in Constanta County, Romania, quantifying how perceived bank technologization and sociodemographic characteristics are associated with the likelihood of digital banking adoption in the e-commerce context. Using repeated cross-sectional survey data from 785 respondents, we applied pooled and year-specific logistic regression models to evaluate temporal effects and estimate the predictive contribution of a composite perception measure (TechScore). Results show that although digital banking usage increased from 87.7% to 92.4%, time alone did not significantly predict adoption. Technologization perceptions consistently increased the odds of digital banking use, with stronger effects in 2025. Age and living environment were significant determinants, while gender and relationship length were not. As digital financial services mature, perceived bank technologization becomes increasingly influential in channel-use decisions. The study contributes to the electronic commerce and technology acceptance literature by demonstrating the importance of perception-based predictors in digital banking contexts and highlights how perception-based evaluation shapes channel choice in digital service platforms, offering insights applicable to electronic commerce contexts where providers compete across physical and digital channels.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21020064

Authors: Jiacheng Wang Qiang Wu

In the era of e-commerce, consumers’ innovative insights are crucial for brands to improve their products and meet consumers’ potential needs. Although user-generated content (UGC) platforms have accumulated a vast amount of consumer voices, brands often face the dilemma of “rich data but scarce insights”: valuable consumer innovation insights are not only scarce but also expressed implicitly. Traditional methods have difficulty reliably identifying such insights in this task. Therefore, this study, for the first time, introduces a large language model (LLM)-augmented Siamese framework, aiming to improve the identification and generalization of consumer innovation insights in multi-platform UGC. Based on four Chinese social media platforms and a dataset of 133,538 comments, we conducted three experiments and performed a systematic comparison under five model configurations. The results show that our approach significantly outperforms traditional benchmarks and strong baselines in most experimental settings, while maintaining stable competitiveness in cross-platform tests. Finally, we showed how the identified innovation insights can be transformed into structured outputs for product planning, thereby facilitating the integration of consumer insights into the brand’s innovation process.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21020063

Authors: John Yang

AI recommendation agents increasingly mediate consumer decision-making in electronic commerce, yet algorithm-based agents often suffer credibility deficits relative to human sources. This research examines how recommendation agent type (human vs. AI) influences behavioral intentions through perceived credibility and how psychological ownership moderates this process. Across two controlled online experiments, consumers evaluated recommendations delivered by human or AI agents. Study 1 shows that baseline AI agents are perceived as less credible than human agents, while AI agents receiving minimal user involvement (naming) exhibit partially improved credibility, and that credibility mediates the effects of agent type on intention to use the system, recommendation acceptance, and purchase intention. Study 2 introduces a stronger psychological ownership manipulation through AI agent customization. Results indicate that customization strengthens psychological ownership, which reduces the credibility gap between AI and human agents and, when ownership is high, even allows AI agents to be evaluated as more credible. Conditional process analyses confirm that psychological ownership moderates both the effect of agent type on credibility and the indirect effects on behavioral intentions. Overall, the findings demonstrate that credibility toward AI recommendation agents is dynamically shaped by user–agent relational experiences. By integrating algorithm aversion, source credibility, and psychological ownership perspectives, this research advances understanding of consumer–AI interaction and provides design insights for AI-enabled recommendation systems in electronic commerce.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21020062

Authors: Na-Eun Cho

This study examines how different types of experienced harm influence trust in sellers and platforms in secondhand, platform-mediated markets. Drawing on attribution theory, we distinguish between fulfillment harm and integrity harm and investigate how these two forms of harm differentially affect seller trust and platform trust. Using data from the Consumer Market Evaluation Index on secondhand marketplaces, we find that both fulfillment and integrity harm are negatively associated with seller trust and platform trust compared to no-harm experiences. When both types of harm occur together, trust deterioration becomes more pronounced. Importantly, fulfillment harm is primarily associated with lower seller trust, whereas integrity harm is more strongly related to platform trust. These findings indicate that trust redistribution depends on attributional evaluations regarding causal locus and controllability. This study contributes to the existing literature by demonstrating how attribution processes allocate trust among multiple market actors and by revealing how different types of failures are attributed to these market actors. Moreover, the findings provide practical guidance for platform governance and seller behavior by highlighting the importance of targeted safeguards in sustaining trust in platform-mediated marketplaces.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21020061

Authors: Mohammad Alsharo Jumana Khwaileh Malik Al-Essa

Consumers are increasingly utilizing their smartphones to pay for goods and services, taking advantage of a variety of mobile payment options. Among these, Peer-to-Peer (P2P) mobile payment systems have gained global momentum, becoming one of consumers’ preferred choices. This study aims to examine the factors influencing consumers’ continuance intention to use CliQ, a P2P mobile payment system in Jordan. Following a thorough literature review, we extend the Theory of Planned Behavior (TPB) by integrating perceived structural assurance, perceived usefulness, and satisfaction. The Partial Least Squares Structural Equation Modeling (PLS-SEM) results indicate that perceived structural assurance significantly affects both consumer attitude and perceived security. The findings also suggest that attitude is the most influential factor in the proposed research model, while perceived usefulness and perceived behavioral control emerged as key drivers of user satisfaction and continuance intention. Furthermore, satisfaction was found to be a strong predictor of consumers’ continuance intention. These findings enrich the literature and provide valued implications for mobile-payment service providers and application developers.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21020060

Authors: Qin Zhang Firdaus Abdullah

This research investigates the impact of augmented and virtual reality (AR/VR) and AI-enabled chatbots, both individually and collectively, on consumer engagement of e-commerce platforms. Moreover, this research examines the mediating effects of perceived utility, ease of use, and enjoyment and the moderating effects of product type and technology readiness, respectively. By applying the theories of Technology Acceptance Model (TAM) and Stimulus–Organism–Response (S-O-R), this research proposed this theoretical framework and adopted a mixed-method research method. This research collected its empirical findings from 486 respondents who had utilized chatbots and AR/VR technology on three of China’s most popular e-commerce platforms, including Taobao, JD.com, and Pinduoduo. Structural equation modeling was utilized for hypothesis testing, and semi-structured interviews on 30 participants were used for validation of empirical findings. Results reveal that both AI chatbot features (β = 0.35, p < 0.001) and AR/VR technologies (β = 0.42, p < 0.001) significantly enhance consumer engagement, with AR/VR demonstrating stronger effects. Perceived enjoyment emerged as the strongest mediator (AI: β = 0.14; AR/VR: β = 0.18), surpassing traditional utilitarian factors. Technology readiness significantly moderated these relationships, with high-readiness consumers showing substantially stronger responses (AI: β = 0.45; AR/VR: β = 0.52). Experience goods amplified technology effects compared to search goods. Multi-group analysis revealed platform-specific variations, while robustness checks identified diminishing returns for AI chatbots but not AR/VR technologies. This research contributes to digital marketing and information systems literature by providing empirical evidence of differential technology impacts on engagement, highlighting the dominance of hedonic over utilitarian pathways in consumer technology adoption. The findings offer practical guidance for e-commerce platforms in optimizing technology investments and designing engagement strategies.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21020059

Authors: Sıla Çetin Esin Ayşe Zaimoğlu

The rapid expansion of e-commerce has significantly influenced consumer purchasing behavior, making user reviews a critical source of product-related information. However, the large volume of low-quality and superficial reviews limits the ability to obtain reliable insights. This study aims to classify Turkish e-commerce reviews as either useful or useless, thereby highlighting high-quality content to support more informed consumer decisions. A dataset of 15,170 Turkish product reviews collected from major e-commerce platforms was analyzed using traditional machine learning approaches, including Support Vector Machines and Logistic Regression, and transformer-based models such as BERT and RoBERTa. In addition, a novel Multi-Transformer Fusion Framework (MTFF) was proposed by integrating BERT and RoBERTa representations through concatenation, weighted-sum, and attention-based fusion strategies. Experimental results demonstrated that the concatenation-based fusion model achieved the highest performance with an F1-score of 91.75%, outperforming all individual models. Among standalone models, Turkish BERT achieved the best performance (F1: 89.37%), while the BERT + Logistic Regression hybrid approach yielded an F1-score of 88.47%. The findings indicate that multi-transformer architectures substantially enhance classification performance, particularly for agglutinative languages such as Turkish. To improve the interpretability of the proposed framework, SHAP (SHapley Additive exPlanations) was employed to analyze feature contributions and provide transparent explanations for model predictions, revealing that the model primarily relies on experience-oriented and semantically meaningful linguistic cues. The proposed approach can support e-commerce platforms by automatically prioritizing high-quality and informative reviews, thereby improving user experience and decision-making processes.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21020058

Authors: Jongtae Yu

This study examines why privacy concerns do not consistently deter online information disclosure by focusing on internal evaluative dynamics underlying privacy decisions. Drawing on theories of attitudinal ambivalence and cognitive–affective inconsistency, it investigates how internal tensions shape the translation of privacy concerns into disclosure behavior. Using two-phase data comprising a survey, the research distinguishes between threat-based and coping-based evaluative conflicts by operationalizing ambivalence and cognitive–affective inconsistency across privacy risks, perceived benefits, self-efficacy, and response efficacy. Results from Phase 1, based on 540 Amazon Mechanical Turk participants, indicate that while privacy concerns generally reduce disclosure intentions, this effect is significantly weakened when individuals experience higher levels of cognitive–affective inconsistency and ambivalence. Although ambivalence significantly reduces the magnitude of inconsistency, it has a limited influence on the moderating role of inconsistency. Phase 2 findings further show that under conditions of high ambivalence, cognitive–affective inconsistency related to self-efficacy exerts a significant effect in situation-specific disclosure contexts. By elucidating the dynamic interplay of the internal tensions, this study clarifies when and why privacy concerns fail to predict disclosure behavior and highlights the importance of incorporating internal evaluative dynamics into models of digital privacy decision-making.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21020057

Authors: Lingyu Wang Jasmine A. L. Yeap Jiaqi Liu Zongwei Li

This review examines existing research on virtual streamers in live streaming commerce and digital marketing, identifying key factors that shape consumer responses. Based on 41 peer-reviewed studies and following PRISMA 2020 guidelines, the analysis applies the CIMCO to synthesize findings through a systematic review. Results highlight three primary mechanisms—trait-based trust, perceived social presence, and message framing—which collectively constitute an integrative model explaining how virtual streamers influence AI-enabled consumer behavior. These elements shape how consumers engage with virtual streamers across platforms and product types. However, current research is limited by geographic concentration, reliance on self-reports, and a lack of longitudinal or behavioral data, which constrains broader applicability. For retailers and platform operators, aligning avatar traits and communication styles with product categories and consumer expectations is crucial for effective digital service delivery. Transparency about whether a streamer is AI or human-operated is also important for maintaining user trust. This review proposes a triadic integration model and offers a foundation for future research on AI-driven marketing influence.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21020056

Authors: Zhuocheng Lu Song Wang

Market and government are the main bodies in solving the problem of income inequality, especially as both undergo electronic informatization. This study explores the effect of e-commerce and e-government on regional income inequality, along with its impact mechanisms and spatial characteristics. The results show a significant “sword effect” impact: e-commerce exacerbates income inequality, while e-government suppresses it. This conclusion remains valid after endogeneity and robustness tests. Mechanistically, e-commerce widens the gap by promoting industrial agglomeration and worsening resource misallocation, while e-government narrows it by enhancing fiscal transparency and alleviating resource misallocation. Spatially, all three variables exhibit spatial correlation and β-convergence; e-commerce and income inequality show α-divergence, while e-government shows α-convergence. E-commerce presents a negative spatial spillover of “aggravating local inequality but suppressing adjacent regional inequality,” while e-government’s inhibitory effect is limited to local cities. Their impacts show significant heterogeneity across regional gradients and geographical locations, providing a basis for differentiated policy implications.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21020055

Authors: Yanni Liu Liming Wang Bian Chen Dongsheng Liu

The unbridled pursuit of statistical rationality has precipitated a crisis of value rationality in e-commerce ecosystems, leading to algorithmic involution—a dilemma characterized by destructive hyper-competition. To reconcile this theoretical paradox and explore effective governance pathways, this paper constructs a tripartite evolutionary game model involving e-commerce platforms, government regulators, and consumers. Simulation results indicate that high-intensity government deterrence constitutes the necessary stability foundation of hard constraints, while consumer activism acts as the decisive accelerator of the soft environment contingent on high synergistic gains and low information screening costs. Furthermore, a platform’s pivot toward “algorithm for good” is not driven by altruism, but by the rational calibration between short-term extractive gains and long-term benevolent returns. Sensitivity analysis confirms that reducing the ratio of these two factors is the effective lever to speed up system convergence. Finally, effective governance requires restructuring this payoff matrix by establishing dynamic penalty mechanisms and transparent low-cost feedback channels to render ethical algorithmic behavior a dominant strategy in terms of economic rationality. This research aims to guide the e-commerce ecosystem from a zero-sum game of involution toward a sustainable equilibrium of multi-party value co-creation.

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer21020054

Authors: Junmin Zhou Weijun Zeng

Platforms are increasingly adopting membership bundling strategies to strengthen competitiveness. This paper explores how duopoly platforms bundle their membership services (the base products) with those provided by other platforms (add-ons) through a game-theoretic lens. We focus on the competing platforms’ strategic decisions to bundle different add-ons together or separately by examining three key determinants: the quality gap between the base products, the quality of versus consumer preference for the add-ons, and the profit-sharing ratio to partners who offer the add-ons. First, with comparable base-good qualities, symmetric bundling emerges in equilibrium. Specifically, simultaneously bundling add-ons together (or separately) dominates when the add-on quality (or the consumers’ preference) mainly drives purchase. Second, significant quality disparity in the base goods leads to asymmetric equilibria: the high-quality platform strategically selects the bundling mode, together or separately, that minimizes the profit-sharing payouts, forcing the low-quality rival to adopt a different strategy. Finally, when the base goods have similar quality, the platform competition can largely yield optimal welfare outcomes. With a significant quality disparity, however, the equilibrium strategies may deviate from social efficiency. Our study advances understanding of platform competition with membership bundling and offers regulatory insights for social planners to strategically intervene in platforms’ membership bundling decisions.