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Volume 21
Issue 6
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J. Theor. Appl. Electron. Commer. Res., Volume 21, Issue 6 (June 2026) – 37 articles

Cover Story (view full-size image): E-commerce recommender systems do more than predict what consumers may buy: they shape choice, visibility, and market opportunity. Drawing on a bibliometric and topic-modelling analysis of 163 studies published between 2012 and 2025, this article shows how the field has shifted from usability-focused explanations toward fairness, accountability, and governance. It introduces the Acceptance Triangle, which connects trust calibration at the interface, exposure equity in the marketplace, and accountability by design. The framework is operationalized through a nine-lever Trust UX Playbook and an exploratory Composite Acceptability Score, offering practical guidance for designing recommender systems that are not only accurate but also transparent, fair, and legitimate. View this paper
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25 pages, 1528 KB  
Article
Dynamic Capabilities for AI-Enabled Exploration: Antecedents, Mechanisms, and Innovation Outcomes
by Thabit Atobishi and Saeed Nosratabadi
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 196; https://doi.org/10.3390/jtaer21060196 - 22 Jun 2026
Cited by 1 | Viewed by 824
Abstract
While the operational benefits of Artificial Intelligence (AI) are well-documented, the mechanisms through which firms leverage AI for strategic exploration and radical innovation remain under-theorized. This study addresses the “black box” of AI value creation by integrating the Technology–Organization–Environment (TOE) framework with the [...] Read more.
While the operational benefits of Artificial Intelligence (AI) are well-documented, the mechanisms through which firms leverage AI for strategic exploration and radical innovation remain under-theorized. This study addresses the “black box” of AI value creation by integrating the Technology–Organization–Environment (TOE) framework with the Dynamic Capabilities View (DCV). We propose that AI adoption is not a direct antecedent to performance but a multi-stage process wherein technological, organizational, and environmental factors enable the development of sensing capability, which in turn fosters a novel capability we term “AI-Enabled Exploration.” Analyzing survey data from 245 senior executives in Saudi Arabia, a high-growth economy undergoing state-led digital transformation, we employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to test the model. The results confirm a serial mediation chain: organizational readiness and technology compatibility drive sensing capability, which subsequently powers AI-enabled exploration to enhance innovation performance. Contrary to expectations, government support was not a significant predictor of sensing capability, suggesting that in resource-rich environments, external incentives are necessary but insufficient for capability building. Furthermore, competitive pressure was found to positively moderate the relationship between organizational readiness and exploration, acting as a critical catalyst that converts latent resources into active experimentation. These findings offer a theoretical roadmap for firms attempting to transition from AI-driven efficiency to AI-driven ambidexterity. Full article
(This article belongs to the Special Issue Artificial Management—The Influence of Artificial Intelligence on Digital Business and Digital Entrepreneurship)
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24 pages, 756 KB  
Article
AI vs. Human Streamers: How Digital Agents Shape Consumer Persuasion Processing in Live Streaming Commerce
by Yao Lu and Guangming Li
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 195; https://doi.org/10.3390/jtaer21060195 - 21 Jun 2026
Viewed by 1025
Abstract
Live streaming commerce is increasingly relying on high-intensity persuasive tactics, yet such tactics may activate consumers’ persuasion knowledge and trigger defensive processing. This research examines whether AI streamers mitigate this defense more effectively than human streamers. Drawing on the Persuasion Knowledge Model, two [...] Read more.
Live streaming commerce is increasingly relying on high-intensity persuasive tactics, yet such tactics may activate consumers’ persuasion knowledge and trigger defensive processing. This research examines whether AI streamers mitigate this defense more effectively than human streamers. Drawing on the Persuasion Knowledge Model, two experiments reveal that, under conditions of high persuasive intensity, consumers perceive lower persuasive intent from AI streamers than from human streamers, which, in turn, reduces consumer suspicion and increases purchase intention. Moreover, this serial mediating effect is stronger for independent accounts than for brand official accounts. These findings provide evidence for a PKM-based mechanism of AI-mediated persuasion and suggest that platforms should consider using AI streamers in high-pressure promotional contexts. Full article
(This article belongs to the Special Issue Human–Technology Synergies in AI-Driven E-Commerce Environments)
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24 pages, 1579 KB  
Article
Disclosure Matters: Perceived Manipulation, Perceived Ethics, and Purchase Intention Toward AI Influencers in Social Media Marketing
by Emre Yıldırım and Faruk Dursun
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 194; https://doi.org/10.3390/jtaer21060194 - 21 Jun 2026
Viewed by 1406
Abstract
The growing use of artificial intelligence (AI) in social media marketing has accelerated the emergence of AI-generated virtual influencers. While these influencers offer brands advantages such as scalability and message control, they also raise concerns regarding manipulation and ethical persuasion. Grounded in the [...] Read more.
The growing use of artificial intelligence (AI) in social media marketing has accelerated the emergence of AI-generated virtual influencers. While these influencers offer brands advantages such as scalability and message control, they also raise concerns regarding manipulation and ethical persuasion. Grounded in the Persuasion Knowledge Model (PKM), this study examines how different AI disclosure conditions influence perceived manipulation, perceived ethics, and purchase intention in AI influencer marketing. A three-condition between-subjects experimental design was employed to compare a human influencer, a disclosed AI influencer, and an undisclosed AI influencer using identical Instagram stimuli. Data were collected from 762 Generation Z female consumers in Türkiye. Structural equation modeling (SEM) was used to test the proposed relationships. The findings revealed that both disclosed and undisclosed AI influencer conditions significantly increased perceived manipulation. Perceived manipulation negatively affected perceived ethics, whereas perceived ethics positively influenced purchase intention. In addition, AI literacy positively affected perceived manipulation and perceived ethics while negatively affecting purchase intention. The findings further demonstrated that disclosure conditions indirectly influenced purchase intention through sequential cognitive and ethical evaluation processes. The study contributes to the AI influencer and digital persuasion literature by demonstrating that disclosure cues shape consumer responses through interconnected psychological mechanisms. Full article
(This article belongs to the Section Digital Marketing and the Evolving Consumer Experience)
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21 pages, 914 KB  
Article
Why AI Looks Less Real: The Role of Cultural Learning Cues in Tourism Destination Imagery
by Wushuang Li, Chin Fei Goh, Yuping Wu and Owee Kowang Tan
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 193; https://doi.org/10.3390/jtaer21060193 - 19 Jun 2026
Viewed by 816
Abstract
Although generative artificial intelligence (AI) has increasingly been used to create destination marketing images, tourists’ responses to such images remain unclear. Prior research has often attributed negative reactions to the visual characteristics of AI-generated images. However, limited attention has been paid to how [...] Read more.
Although generative artificial intelligence (AI) has increasingly been used to create destination marketing images, tourists’ responses to such images remain unclear. Prior research has often attributed negative reactions to the visual characteristics of AI-generated images. However, limited attention has been paid to how tourists interpret these images within broader cultural contexts. Drawing on authenticity theory and cultural learning theory, this research examines the effect of image type (AI vs. human) on tourists’ perceived authenticity and visit intention, as well as the moderating roles of cultural learning cues in this process. Using three experiments, the results show that AI-generated images reduce perceived authenticity and visit intention compared with images taken by humans. Notably, while salient cultural learning cues enhance tourists’ perceived authenticity and visit intentions, different types of cues produce distinct outcomes: commodified cultural cues mitigate tourists’ negative responses to AI-generated images, whereas heritage cultural cues amplify authenticity concerns. These findings provide strategic insights for destination marketers on how to deploy AI-generated images effectively in tourism destination marketing. Full article
(This article belongs to the Section Digital Marketing and the Evolving Consumer Experience)
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30 pages, 3727 KB  
Article
The Strategic Interplay Between Return Insurance and Augmented Reality in Live-Streaming Commerce Considering Consumer Search Effort
by Kexin Ding and Tianjian Yang
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 192; https://doi.org/10.3390/jtaer21060192 - 19 Jun 2026
Viewed by 298
Abstract
Product mismatch, arising from consumers’ inability to physically experience products before purchase, is a major cause of returns in e-commerce, eroding e-tailer profits and intensifying consumers’ concerns about returns. To alleviate these concerns, e-tailers have increasingly adopted return insurance (RI), which reduces consumers’ [...] Read more.
Product mismatch, arising from consumers’ inability to physically experience products before purchase, is a major cause of returns in e-commerce, eroding e-tailer profits and intensifying consumers’ concerns about returns. To alleviate these concerns, e-tailers have increasingly adopted return insurance (RI), which reduces consumers’ return freight costs. However, RI may encourage consumers to defer product selection from the pre-purchase search stage to the post-purchase evaluation stage, thereby exacerbating mismatch and increasing return rates. As a countermeasure in live-streaming commerce, augmented reality (AR) provides an immersive product experience that can reduce mismatch and returns. This study develops a game-theoretic model to analyze the strategic interplay between an e-tailer’s RI decision and a live streamer’s AR decision while incorporating consumer search effort. The results show that consumer search effort changes the relationship between the two strategies. When search effort is low, RI and AR function as strategic substitutes; when search effort is high, they function as strategic complements. These findings indicate that the value of a return-management strategy depends on consumer behavior and on the presence of the partner’s AR strategy. The study contributes to the literature on interdependent return-management strategies and provides actionable insights for e-commerce practitioners. Full article
(This article belongs to the Section Immersive Commerce and Emerging Technologies)
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30 pages, 368 KB  
Article
Consumer Innovation Fatigue in Digital Commerce: Scale Development and Validation
by Ahmed S. Ajina
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 191; https://doi.org/10.3390/jtaer21060191 - 17 Jun 2026
Viewed by 507
Abstract
Rapid digital transformation has accelerated the frequency with which firms introduce product updates, platform enhancements, and feature innovations in e-commerce environments. While continuous innovation is typically associated with improved functionality and customer value, limited research has examined its potential psychological costs for consumers. [...] Read more.
Rapid digital transformation has accelerated the frequency with which firms introduce product updates, platform enhancements, and feature innovations in e-commerce environments. While continuous innovation is typically associated with improved functionality and customer value, limited research has examined its potential psychological costs for consumers. This study introduces the concept of consumer innovation fatigue (CIF), defined as a psychological state of exhaustion arising from repeated exposure to ongoing innovation-related changes in digital products and online platforms. Following established scale development procedures, this research develops and validates a measurement scale for CIF. Item generation combined insights from prior literature with qualitative evidence from consumer interviews, followed by expert evaluation to ensure content validity. Using survey data from two independent samples of digital consumers in Saudi Arabia, exploratory factor analysis (n = 225) identified a unidimensional six-item scale. The scale was subsequently validated using partial least squares structural equation modeling (n = 361), confirming its reliability, convergent validity, and discriminant validity. The findings further demonstrate nomological validity by showing that exposure to continuous digital innovation significantly increases CIF, which in turn leads to innovation avoidance in online consumption contexts. By conceptualizing and empirically validating CIF, this study contributes to electronic commerce research by highlighting a previously underexplored psychological consequence of rapid innovation cycles in digital environments. The validated scale provides a useful instrument for future research examining consumer responses to ongoing technological change in e-commerce ecosystems. Full article
(This article belongs to the Section Digital Business, Governance, and Sustainability)
22 pages, 422 KB  
Article
Performance Evaluation of E-Commerce Websites Based on Multi-Criteria Decision-Making Methods
by Emre Özsalman, Alptekin Ulutaş and Halime Ünver
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 190; https://doi.org/10.3390/jtaer21060190 - 17 Jun 2026
Viewed by 599
Abstract
The significant growth in e-commerce has brought intense competition to the business sector. Businesses seeking to stand out in this competition are evaluated by customers not only by the quality of the products they sell, but also by their performance on digital platforms. [...] Read more.
The significant growth in e-commerce has brought intense competition to the business sector. Businesses seeking to stand out in this competition are evaluated by customers not only by the quality of the products they sell, but also by their performance on digital platforms. To measure this evaluation, this study analyzed the website performance of 25 e-commerce companies in Türkiye using Multi-Criteria Decision Making (MCDM) methods with eleven technical and user-oriented performance criteria. MAXC (Maximum Criterion) and Skewness Impact Through Distributional Evaluation (SITDE) methods were used to determine the criterion weights of the websites, while CORASO (COmpromise Ranking from Alternative SOlutions) was used to rank the alternatives. According to the results, “total number of visitors” had the highest weight, while “bounce rate” had the lowest weight. According to the CORASO method, the top three performing e-commerce sites were EC1, EC2, and EC3, while the bottom three performing sites were EC11, EC14, and EC20. Full article
(This article belongs to the Special Issue Digital Marketing in Emerging Economies)
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29 pages, 727 KB  
Article
Artificial Minds as Brand Advocates: Developing and Testing the AHICC Model of Consumer Cognitive Processing for AI Endorsers in Digital Marketing
by Zheng-Jun Jin, Kwang-Su Lee, Chang-Hyun Jin and Jungyong Lee
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 189; https://doi.org/10.3390/jtaer21060189 - 16 Jun 2026
Viewed by 539
Abstract
Despite rapid growth in the AI endorser market, the psychological mechanisms governing their effectiveness remain theoretically fragmented. This study proposes the AHICC (AI–Human Interface in Consumer Cognition) model—integrating the Stereotype Content Model, Uncanny Valley hypothesis, anthropomorphism theory, Source Credibility Model, and Parasocial Interaction [...] Read more.
Despite rapid growth in the AI endorser market, the psychological mechanisms governing their effectiveness remain theoretically fragmented. This study proposes the AHICC (AI–Human Interface in Consumer Cognition) model—integrating the Stereotype Content Model, Uncanny Valley hypothesis, anthropomorphism theory, Source Credibility Model, and Parasocial Interaction theory—to explain consumer responses to AI endorsers. A fully crossed 3 (endorser type: AI vs. hybrid vs. human) × 3 (anthropomorphism level: low vs. moderate vs. high) × 2 (technological transparency: low vs. high) between-subjects factorial experiment (n = 252) was conducted. Twenty-one sub-hypotheses were tested using MANOVA, polynomial regression, SEM, and bootstrap mediation analysis. All 21 sub-hypotheses were supported. AI endorsers outperformed human counterparts on brand attitude and purchase intention. Polynomial regression confirmed an inverted U-shaped Uncanny Valley effect with an optimal anthropomorphism level of 4.7 (7-point scale). High technological transparency attenuated the Uncanny Valley effect by approximately 60%. Dual-pathway mediation through cognitive and affective routes was confirmed, and TRI and product complexity emerged as significant boundary conditions. The AHICC model offers the first comprehensive framework for the AI endorser context, providing theoretically grounded guidance on anthropomorphism calibration, transparency strategy, and product-category-specific endorser selection. Full article
(This article belongs to the Topic Livestreaming and Influencer Marketing)
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26 pages, 1733 KB  
Article
To Boost Sales in E-Commerce: More or More Aligned? Dual Dimensions of Hashtag Strategy and the Moderating Role of Influencers’ Adaptive Self-Presentation
by Hajin Shin, Sulim Kim, Hee-Dong Yang and Yong-Young Kim
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 188; https://doi.org/10.3390/jtaer21060188 - 15 Jun 2026
Viewed by 813
Abstract
In the crowded landscape of social media, hashtags serve not only as navigational tools but also as strategic signals of meaning and intent. This study examines how hashtag strategies—specifically semantic similarity with post content and usage frequency—affect sales outcomes in influencer-driven electronic commerce. [...] Read more.
In the crowded landscape of social media, hashtags serve not only as navigational tools but also as strategic signals of meaning and intent. This study examines how hashtag strategies—specifically semantic similarity with post content and usage frequency—affect sales outcomes in influencer-driven electronic commerce. Drawing on self-presentation theory, we analyze panel data from Instagram posts to explore how these hashtag dimensions interact with influencers’ self-presentation styles. The results show that hashtag–posting similarity significantly enhances sales, particularly among influencers exhibiting a Judging (J)-type self-presentation marked by structured and purposeful communication. In contrast, hashtag frequency alone does not increase sales performance and may even diminish it, indicating that excessive use can be counterproductive. However, for J-type influencers, an increase in hashtag frequency yields positive effects when it is deployed within a coherent and structured self-presentation framework, strengthening trust and ultimately enhancing conversion rates. These findings highlight that both what is said (semantic content) and how much is said (frequency) matter, but their effects depend on influencers’ expressive styles. The study provides actionable insights for marketers and brands, suggesting that effective hashtag strategies should align with influencers’ self-presentation tendencies rather than follow standardized or quantitative rules. Full article
(This article belongs to the Section Digital Marketing and the Evolving Consumer Experience)
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30 pages, 767 KB  
Systematic Review
The Relationship Between Influencer Authenticity and Customer Experience: Evidence from a Meta-Analysis
by Ying Xie, Dan Zhou, Tingting Wang and Hanyu Sun
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 187; https://doi.org/10.3390/jtaer21060187 - 11 Jun 2026
Viewed by 1038
Abstract
With frequent exposures of influencer false advertising and persona fabrication, “authenticity” has become an increasingly critical consumer demand. However, existing research employs inconsistent perspectives on “authenticity” (encompassing both consumer-perceived authenticity and influencer strategic authenticity) and remains fragmented, focusing narrowly on specific experiential dimensions [...] Read more.
With frequent exposures of influencer false advertising and persona fabrication, “authenticity” has become an increasingly critical consumer demand. However, existing research employs inconsistent perspectives on “authenticity” (encompassing both consumer-perceived authenticity and influencer strategic authenticity) and remains fragmented, focusing narrowly on specific experiential dimensions such as positive emotions and social identity without systematic integration across the full customer journey. Therefore, this study adopts meta-analysis, systematically searching Chinese and English databases including Web of Science, Google Scholar and CNKI (2015–2026), and incorporates 170 effect sizes from 56 studies with 63 samples (n = 22,563) to systematically examine the effects of strategic authenticity (SA) and perceived authenticity (PA) on the customer experience journey (affective experience, cognitive experience, physical experience, and social-identity experience). Publication bias tests (fail-safe N > 5k + 10) indicated no significant bias. The results reveal that affective experience is more driven by strategic authenticity (ρ = 0.535), whereas cognitive experience (ρ = 0.591), physical experience (ρ = 0.355), and social-identity experience (ρ = 0.515) are more significantly influenced by perceived authenticity. Regarding influencer type moderation, virtual influencer SA exerts a stronger effect on social-identity experience (ρ = 0.574) than human influencer SA (ρ = 0.170, QB = 3.980, p = 0.046); conversely, human influencer PA shows a stronger effect on social-identity experience (ρ = 0.571) than virtual influencer PA (ρ = 0.016, QB = 8.189, p = 0.004). Regarding cultural differences, individualistic cultures exhibit stronger PA effects on physical experience (ρ = 0.419) and social-identity experience (ρ = 0.742); long-term orientation cultures show stronger SA effects on social-identity experience (ρ = 0.574). These findings contribute to the authenticity literature and offer actionable insights for influencer marketing practices. Full article
(This article belongs to the Special Issue Human–Technology Synergies in AI-Driven E-Commerce Environments)
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24 pages, 2001 KB  
Article
Virtual Showroom Strategies for E-Tailers Towards Cross-Channel Purchasing Behavior of Consumers
by Zichao Jia, Junfeng Tian, Chenyu Tian and Yong Liu
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 186; https://doi.org/10.3390/jtaer21060186 - 11 Jun 2026
Viewed by 306
Abstract
In a duopoly market comprising an e-tailer and a physical retailer, we develop analytical models to explore the e-tailer’s strategy of introducing a virtual showroom to alleviate consumers’ fit uncertainty. While a virtual showroom can increase online consumer traffic, consumers may instead purchase [...] Read more.
In a duopoly market comprising an e-tailer and a physical retailer, we develop analytical models to explore the e-tailer’s strategy of introducing a virtual showroom to alleviate consumers’ fit uncertainty. While a virtual showroom can increase online consumer traffic, consumers may instead purchase from physical stores (i.e., webrooming) or reduce offline browsing before buying online (i.e., showrooming). Our findings indicate that consumers with a moderate online hassle cost tend to showroom when offline travel cost is not high, whereas those with a high online hassle cost rely on the virtual showroom for webrooming. Therefore, we identify the conditions under which a virtual showroom should be introduced. Specifically, when the cost of travel to the store is relatively high, the e-tailer can profit from introducing a virtual showroom if its return-handling cost is not too low. Under moderate travel cost, the e-tailer can leverage a virtual showroom to weaken competition if the return-handling cost is not too high, enabling both retailers to benefit. Notably, the impact of product fit probability on virtual showroom strategy decisions reverses between high and moderate travel costs. Under specific conditions, the virtual showroom can achieve a “win-win-win” situation for the e-tailer, the physical retailer, and consumers. Full article
(This article belongs to the Section Immersive Commerce and Emerging Technologies)
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22 pages, 655 KB  
Article
A Signaling Perspective of Recovering Buyers After the Failure of Live Streaming E-Commerce Service: Protocols, Mechanisms, and Recommendations
by Min Qin, Zhensong Jiang and Zhao Pan
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 185; https://doi.org/10.3390/jtaer21060185 - 11 Jun 2026
Viewed by 486
Abstract
Live streaming e-commerce has emerged as a dominant force in electronic commerce. Although extensive research has examined service failures and recovery in conventional e-commerce environments, there is limited understanding of how buyers interpret and respond to service recovery information provided by streamers in [...] Read more.
Live streaming e-commerce has emerged as a dominant force in electronic commerce. Although extensive research has examined service failures and recovery in conventional e-commerce environments, there is limited understanding of how buyers interpret and respond to service recovery information provided by streamers in live streaming contexts, where streamers fulfill dual roles as both idols and sellers. This study, grounded in signaling theory, investigates the relationships among buyers’ observation, interpretation, and feedback of service recovery information. Specifically, it aims to assess how buyers’ perceived justice regarding service recovery information affects their repeat purchase intentions following live streaming e-commerce failures. Meanwhile, this study elucidates the mediating role of trust in the streamer (idol role and seller role) and verifies whether responsibility attribution and product involvement have moderating effects on the effect of perceived justice. Employing PLS-SEM analysis, the study analyzes data from 401 buyers who have experienced service failures in live streaming e-commerce. The findings reveal that perceived justice positively influences repeat purchase intentions to a certain extent. Trust in the streamer mediates the link between perceived justice and repeat purchase intentions. The inhibiting moderation effect of responsibility attribution and product involvement is generally significant. This study contributes to the theoretical understanding of signaling theory by expanding the signaling model to encompass service recovery information in live streaming e-commerce. Furthermore, it provides practical guidance for live streaming e-commerce practitioners on managing service recovery information, including recommendations for the sequence of sending such information, enhancing its transmission, and improving its overall effectiveness. Full article
(This article belongs to the Section Digital Marketing and the Evolving Consumer Experience)
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37 pages, 1964 KB  
Article
Which Privacy Policy Works, Opt-In Requirement or Inference Regulation? A Game-Theoretic Analysis of Privacy Policies in E-Commerce
by Bi Li, Chaoshan Wang, Yan Wu, Boyu Chen and Zhifeng Hao
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 184; https://doi.org/10.3390/jtaer21060184 - 9 Jun 2026
Viewed by 546
Abstract
With the rapid development of e-commerce, data-driven models have significantly enhanced service experience. We can obtain the optimal values for the price but have also intensified consumer privacy concerns. Among various privacy protection policies, which are more effective? Is there a governance framework [...] Read more.
With the rapid development of e-commerce, data-driven models have significantly enhanced service experience. We can obtain the optimal values for the price but have also intensified consumer privacy concerns. Among various privacy protection policies, which are more effective? Is there a governance framework that balances commercial efficiency with privacy safety? To address this, we develop a duopoly game-theory model that analyzes consumer behavior characterized by heterogeneous privacy costs and preferences, aiming to evaluate the impact of differentiated privacy protection policies within digital ecosystems. We analyze whether opt-in requirement or inference regulation is more advantageous for consumer and firm competition. We find that, in a competitive environment, imposing opt-in requirement on one party can yield competitive advantages and profit increases, whereas imposing inference regulation on the other may result in a competitive disadvantage. Such differentiated policies create an asymmetric competitive landscape, effectively avoiding a prisoner’s dilemma and, under certain conditions, increasing both consumer and total surplus. Furthermore, our study reveals significant differences in the impact of these policies on data-driven and usage-driven firms. Based on these findings, we recommend that regulators carefully tailor privacy protection policies according to industry-specific data characteristics, adopting differentiated regulatory strategies when appropriate and providing compensation mechanisms for disadvantaged firms to optimize total welfare. Full article
(This article belongs to the Section Data Science, AI, and e-Commerce Analytics)
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22 pages, 3097 KB  
Article
Metacognitive Experience: How AI Recommendations Shape Purchase Intention
by Qing Gu, Xintao Yu, Ding Yuan and Qiang Yang
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 183; https://doi.org/10.3390/jtaer21060183 - 9 Jun 2026
Viewed by 655
Abstract
Although existing studies have shown that AI recommendation systems have potential in enhancing consumers’ purchase intention, there remains a lack of systematic research. This study aims to explore how the interaction between information presentation formats and AI role types influences consumers’ purchase intention. [...] Read more.
Although existing studies have shown that AI recommendation systems have potential in enhancing consumers’ purchase intention, there remains a lack of systematic research. This study aims to explore how the interaction between information presentation formats and AI role types influences consumers’ purchase intention. Based on metacognitive experience theory, two experiments are designed to analyze processing fluency as a mediator and consumers’ AI knowledge as a moderator. The results reveal that the interaction between information presentation format and AI role type significantly affects consumers’ purchase intention, while their separate effects are insignificant. Different from existing studies on separate factors, this study demonstrates that AI interactive marketing performance hinges on the matching of design and role positioning. This study extends the application of the theory of metacognitive experiences in the field of human–AI interaction and provides targeted recommendations for the interface design of AI recommendation systems. Full article
(This article belongs to the Topic Innovations in New Media: Shaping the Future of Interactive Marketing)
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43 pages, 3535 KB  
Article
Mitigating Supply Uncertainty in Agricultural Supply Chains: A Trust-Based Punishment Mechanism to Reduce the Bullwhip Effect
by Xiao Fu and Hao Tan
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 182; https://doi.org/10.3390/jtaer21060182 - 9 Jun 2026
Viewed by 438
Abstract
This study addresses supply uncertainty in the transportation and production of agricultural products within e-commerce-driven supply chains by developing a stochastic supply chain framework. By embedding an endogenous trust-based punishment mechanism, we characterize the strategic interplay between relational governance and operational decisions. In [...] Read more.
This study addresses supply uncertainty in the transportation and production of agricultural products within e-commerce-driven supply chains by developing a stochastic supply chain framework. By embedding an endogenous trust-based punishment mechanism, we characterize the strategic interplay between relational governance and operational decisions. In the single-period setting, higher retailer trust leads to larger order quantities while reducing the supplier’s optimal supply effort. This occurs because increased trust lowers the minimum delivery commitment ratio, allowing the retailer to voluntarily share more supply risk in exchange for lower-cost products. This creates a mutually beneficial risk-sharing arrangement between the retailer and supplier. When extending the framework to a dual-channel setting with a reliable backup option, the retailer consistently leverages trust and risk-sharing to lower sourcing costs. Concurrently, fluctuations in trust prompt the retailer to strategically shift order allocations between channels based on the primary supplier’s maximum effort capacity. Multi-period analysis shows a positive relationship between trust and the supplier’s expected profit, with optimal maximum supply effort stabilizing under repeated cooperation. Numerical experiments demonstrate that dual-channel decentralized decision-making achieves bullwhip effect mitigation quantitatively comparable to the centralized benchmark, while also alleviating moral hazard issues and benefiting retailers. These results indicate that the proposed mechanism effectively curbs opportunistic behavior and promotes sustainable, mutually advantageous supply chain collaboration. Full article
(This article belongs to the Special Issue Global Supply Chain Management and Sustainability in E-Commerce)
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20 pages, 445 KB  
Article
Artificial Intelligence vs. Social Media Influencer-Generated Content: A Comparative Study of Anthropomorphism in Shaping Tourist Destination Visitation Intention
by Calvin Steve Nyagudi and Wenbing Wu
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 181; https://doi.org/10.3390/jtaer21060181 - 8 Jun 2026
Viewed by 891
Abstract
Technology-driven content is increasingly reshaping how tourists perceive and evaluate destinations, yet the underlying content evaluative processes remain insufficiently investigated. This study, therefore, integrates the Stimulus–Organism–Response (S–O–R) framework with Anthropomorphism Theory to examine how destination anthropomorphic content (DAC) relates to destination image (DI) [...] Read more.
Technology-driven content is increasingly reshaping how tourists perceive and evaluate destinations, yet the underlying content evaluative processes remain insufficiently investigated. This study, therefore, integrates the Stimulus–Organism–Response (S–O–R) framework with Anthropomorphism Theory to examine how destination anthropomorphic content (DAC) relates to destination image (DI) and destination visitation intention (DVI) in digitally mediated environments. Using a cross-sectional survey design and multi-group Structural Equation Modeling, the study compares relationships across two information sources: AI- and social media influencer-generated content. The results show that DAC is positively associated with both DI and DVI across groups. Permutation-based multi-group analysis indicates that the differences in structural paths between AI and influencer groups are not statistically significant. This finding provides the basis for interpreting group comparisons, suggesting that the observed relationships do not differ meaningfully across content sources. While bootstrapping and effect size (f2) results indicate relatively stronger coefficients in the influencer group, these results are interpreted as descriptive tendencies rather than statistically confirmed differences. These findings suggest that tourists may respond positively to both human and technologically mediated agents’ content when human-like social cues are perceived. This study contributes to the growing discourse on AI and digital content in tourism by unveiling the critical concern of whether the content source matters in anthropomorphic perception. The study further extends the application of S–O–R in AI-mediated marketing contexts. The findings offer practical insights for destination marketers seeking to leverage both AI and influencer-based strategies in shaping tourist perceptions and intentions. Full article
(This article belongs to the Topic Artificial Intelligence and Tourism Transformation)
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15 pages, 681 KB  
Article
Navigating the Robot–Human Paradox: An Integrated Model of Trust, Rapport, and Ambivalent Behavioral Responses to Service Robots
by Zhenyu Zhang and Xueji Wang
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 180; https://doi.org/10.3390/jtaer21060180 - 8 Jun 2026
Viewed by 420
Abstract
Drawing on the uncanny valley framework, trust theory, and similarity attraction theory, this study examines how customers’ multidimensional perceptions of humanoid service robots shape their approach and avoidance behaviors through two relational states: trust and rapport. Subsequently, structural equation modeling and mediation analysis [...] Read more.
Drawing on the uncanny valley framework, trust theory, and similarity attraction theory, this study examines how customers’ multidimensional perceptions of humanoid service robots shape their approach and avoidance behaviors through two relational states: trust and rapport. Subsequently, structural equation modeling and mediation analysis were employed for testing. The results indicate that customers’ overall perceptions of service robots not only encourage approach behaviors but may simultaneously intensify avoidance tendencies, reflecting the ambivalent nature of human–robot interactions. We interpret this dual activation through the uncanny valley framework, in which humanlike robots simultaneously elicit attraction and aversion. Trust and rapport play critical mediating roles in this process, effectively reducing avoidance responses while strengthening customers’ approaches. Further analyses reveal that different perceptual dimensions operate through distinct mechanisms in the formation of trust and rapport. This study aims to deepen the comprehension of customer response mechanisms to humanoid service robots through a relational perspective, and offers practical insights for hotels seeking to balance operational efficiency with emotional experience in robot design and management. Full article
(This article belongs to the Topic Artificial Intelligence and Tourism Transformation)
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18 pages, 698 KB  
Article
The Personalization–Privacy Paradox in AI-Driven Programmatic Advertising: Implications for Digital Marketing Sustainability
by Nermin Yildirim and Bora Gündüzyeli
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 179; https://doi.org/10.3390/jtaer21060179 - 5 Jun 2026
Cited by 1 | Viewed by 1687
Abstract
Artificial intelligence (AI) has transformed programmatic advertising (PA) by enabling automated, data-driven personalization within digital marketing ecosystems. However, this transformation has also intensified concerns regarding privacy, consumer trust, and the long-term sustainability of these ecosystems. In this study, sustainability is conceptualized as the [...] Read more.
Artificial intelligence (AI) has transformed programmatic advertising (PA) by enabling automated, data-driven personalization within digital marketing ecosystems. However, this transformation has also intensified concerns regarding privacy, consumer trust, and the long-term sustainability of these ecosystems. In this study, sustainability is conceptualized as the capacity of digital marketing systems to maintain long-term functionality without eroding consumer trust or amplifying privacy-related tensions that may undermine system stability over time. This study addresses the research question: How does AI-driven PA affect the sustainability of digital marketing ecosystems through the personalization–privacy paradox? A systematic literature review, conducted in line with PRISMA guidelines, synthesizes prior research across four interrelated clusters: AI-driven personalization, privacy concerns, consumer trust, and consumer attitudes and behavior. The findings indicate that consumer responses to AI-driven personalization are not linear and are shaped by factors such as transparency, perceived control, and the perceived legitimacy of data practices. The review further shows that the paradox of personalization and privacy operates as a persistent condition within AI-driven advertising ecosystems, where the benefits of personalization coexist with ongoing privacy-related tensions. This study contributes to the literature by synthesizing fragmented research on AI-driven PA and by highlighting the central role of trust and transparency in understanding how personalization and privacy tensions shape consumer responses in digital marketing ecosystems. Full article
(This article belongs to the Special Issue Digital Market Ecosystems: AI-Driven Intersections of E-Commerce, Branding, and Consumer Behavior)
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16 pages, 418 KB  
Article
When Relevance Feels Risky: Consumer Avoidance of Personalized Advertising in the Digital Age
by Yunbo Chen, Jing Huang, Yin Zhang and Yixiang Zhang
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 178; https://doi.org/10.3390/jtaer21060178 - 4 Jun 2026
Viewed by 844
Abstract
Personalized advertising is now routine in digital commerce and new media, but relevance does not always translate into acceptance. When consumers read tailored messages as signs of tracking or inference rather than as useful assistance, they may feel exposed and avoid the advertising. [...] Read more.
Personalized advertising is now routine in digital commerce and new media, but relevance does not always translate into acceptance. When consumers read tailored messages as signs of tracking or inference rather than as useful assistance, they may feel exposed and avoid the advertising. Drawing on advertising avoidance theory, privacy calculus theory, and control agency theory, this study examines a privacy-risk account of personalized advertising avoidance. Survey data from 502 consumers and structural equation modeling show that privacy concern, privacy fatigue, and prior negative experiences are directly associated with advertising avoidance. Privacy concern, prior negative experiences, and perceived personalization are also positively associated with perceived risk; perceived industry self-regulation is negatively but non-significantly associated with perceived risk; and perceived risk is positively associated with advertising avoidance. These results position perceived risk as a close downstream appraisal through which consumers make sense of data-driven targeting. The study contributes to digital commerce and interactive marketing research by showing that consumers evaluate personalized advertising not only as a cue of relevance, but also as a possible source of privacy vulnerability. It also offers implications for transparent targeting, visible user control, platform governance, and less intrusive personalization. Full article
(This article belongs to the Topic Innovations in New Media: Shaping the Future of Interactive Marketing)
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27 pages, 4579 KB  
Systematic Review
Digital Transformations and the Changing Business-to-Business (B2B) Transactions in the Global Value Chains: A Systematic Literature Review
by Muhammad Mohiuddin, Meryem Ourhalouch, Slimane Ed-Dafali and Md. Samim Al-Azad
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 177; https://doi.org/10.3390/jtaer21060177 - 3 Jun 2026
Viewed by 758
Abstract
Digital transformation is contributing to changes in how both production processes and transactions take place among firms within global value chains (GVCs). Firms navigate rapid advancements in digital technologies, such as Industry 4.0-embodied technologies that are translating into the reconfiguration of their value [...] Read more.
Digital transformation is contributing to changes in how both production processes and transactions take place among firms within global value chains (GVCs). Firms navigate rapid advancements in digital technologies, such as Industry 4.0-embodied technologies that are translating into the reconfiguration of their value chains. In an era of rapid growth in digital technologies, firms are in a position to reconsider their responsibilities within GVCs and reevaluate the strategic opportunities that come with digital transformation in the global market. Advanced technologies help firms in the GVC to streamline their cross-border production networks and enable real-time transactions between the firms. However, the impact of digitalization on the GVC has not been given much attention in earlier studies. This article presents a systematic literature review (SLR) based on the analysis of 43 articles on GVCs published between 2018 and 2024 and retrieved from the Scopus, Web of Science, and ProQuest databases. The study contributes in two ways: first, to elucidate the association between digital transformation and business-to-business (B2B) transactions within GVCs, and second, to propose future research directions aimed at enriching the literature on GVCs and suggesting theoretical and managerial implications. Full article
(This article belongs to the Special Issue Global Supply Chain Management and Sustainability in E-Commerce)
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30 pages, 1619 KB  
Article
Platform or Host? Matching Service Recovery to Mitigate Negative Reviews
by Wenna Wang, Jifan Ren and Guanhua Wang
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 176; https://doi.org/10.3390/jtaer21060176 - 3 Jun 2026
Viewed by 415
Abstract
This study investigates how different types of service failures in peer-to-peer accommodation influence guests’ negative review intentions. It explores the underlying psychological mechanisms and how the recovery agent’s identity (platform vs. host) shapes recovery effectiveness. Adopting a mixed-methods research design, an initial qualitative [...] Read more.
This study investigates how different types of service failures in peer-to-peer accommodation influence guests’ negative review intentions. It explores the underlying psychological mechanisms and how the recovery agent’s identity (platform vs. host) shapes recovery effectiveness. Adopting a mixed-methods research design, an initial qualitative study (N = 52) explored key themes related to service failure and psychological contract violation, followed by three scenario-based experiments that empirically tested the proposed theoretical model and the moderating role of the recovery agent. Specifically, Study 1 (N = 236) and Study 2 (N = 297) employed 3 × 1 between-subjects designs comparing informational service failure, social service failure, and a control condition, while Study 3 (N = 352) adopted a 2 × 2 between-subjects design crossing service failure type (informational vs. social failure) and recovery agent identity (platform vs. host recovery). The findings reveal that both informational and social service failures significantly increase negative review intentions, with distinct mediating mechanisms: informational psychological contract violation mediates the impact of informational failures, whereas relational psychological contract violation mediates the effect of social failures. Importantly, a “recovery-agent matching” effect emerges, whereby platform recovery more effectively mitigates informational violations, while host recovery is more effective in repairing relational violations. By applying psychological contract theory to the dual service-provider structure of the sharing economy, this study extends the service recovery literature and shifts the focus from what recovery is delivered to who delivers it. The findings also provide practical guidance for managers, highlighting the need to move beyond one-size-fits-all recovery strategies. Full article
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17 pages, 876 KB  
Article
Examining User Switching from Traditional Online Shopping to AI Shopping
by Tao Zhou and Zexuan Zhang
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 175; https://doi.org/10.3390/jtaer21060175 - 2 Jun 2026
Viewed by 680
Abstract
As an emerging application, AI shopping has received increasing attention from both enterprises and users. Based on the push–pull–mooring (PPM) model, this research examined user switching intention from traditional online shopping to AI shopping. We conducted an online survey to collect 422 valid [...] Read more.
As an emerging application, AI shopping has received increasing attention from both enterprises and users. Based on the push–pull–mooring (PPM) model, this research examined user switching intention from traditional online shopping to AI shopping. We conducted an online survey to collect 422 valid responses and adopted a mixed method of structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA). The results show that choice overload and perceived inefficiency lead to online shopping fatigue, while perceived convenience, perceived anthropomorphism, and perceived coolness affect AI shopping attractiveness. Online shopping fatigue, AI shopping attractiveness, and inertia determine user switching intention. These results provide a comprehensive understanding of the mechanism underlying user switching from traditional online shopping to emerging AI shopping. They also imply that e-commerce platforms need to mitigate online shopping fatigue and increase AI shopping attractiveness in order to expand their user base and maintain a competitive advantage. Full article
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28 pages, 1292 KB  
Article
Technology Acceptance of AI-Pre-Filled Carts in Online Grocery Retailing: Testing TAM Paths and Their Link to Objective Performance
by Moritz Lackner and Siegfried Pöchtrager
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 174; https://doi.org/10.3390/jtaer21060174 - 1 Jun 2026
Viewed by 446
Abstract
Online grocery retailing remains effort-intensive because consumers must coordinate many item-level decisions, making basket construction and correction a key barrier to more frequent use. This study examines consumer acceptance of an AI-pre-filled basket in Austrian online grocery retailing and links Technology Acceptance Model [...] Read more.
Online grocery retailing remains effort-intensive because consumers must coordinate many item-level decisions, making basket construction and correction a key barrier to more frequent use. This study examines consumer acceptance of an AI-pre-filled basket in Austrian online grocery retailing and links Technology Acceptance Model (TAM) mechanisms to objective interaction performance. Using a field-proximate one-group pre–post design, participants edited an AI-pre-filled basket in a standardized online shop and completed pre- and post-task surveys using 0–100 slider scales; log data captured processing time and edit actions. Analyses are based on n = 297 valid cases. Results show a substantial and statistically significant within-person increase in online grocery usage intention after the AI-basket interaction, rising from 39.17 to 59.78. The TAM results support the core mechanism: perceived ease of use is positively associated with perceived usefulness, and perceived usefulness strongly predicts behavioral intention, whereas a direct ease-of-use effect on intention is not supported. Linking perceptions to log data shows that acceptance is more strongly associated with correction demand than with processing time. AI-basket acceptance depends less on speed than on reducing rework while preserving user control; retailers should therefore design AI baskets as controllable, editable, low-rework systems rather than speed-oriented automation tools. Full article
(This article belongs to the Special Issue AI-Based Disruption, Innovations, and New Business Models in E-Commerce: Empirical Research, Case Studies and Current Trends)
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21 pages, 1159 KB  
Article
Cutting Edge or Crystal Clear? How Does the Supervisibility of Algorithm Throughput Influence the Coping Behaviors of Targeted Advertising Audiences?
by Lijun Chen, Rui Sun, Lele Fan and Lei Zhuang
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 173; https://doi.org/10.3390/jtaer21060173 - 30 May 2026
Viewed by 545
Abstract
The increasing complexity of artificial intelligence systems and algorithms can negatively affect individual attitudes and prompt them to adopt coping behaviors. Based on the technology threat avoidance theory, this study explores the mechanisms through which the supervisibility of recommendation algorithm throughput influences the [...] Read more.
The increasing complexity of artificial intelligence systems and algorithms can negatively affect individual attitudes and prompt them to adopt coping behaviors. Based on the technology threat avoidance theory, this study explores the mechanisms through which the supervisibility of recommendation algorithm throughput influences the coping behaviors of targeted advertising audiences using scenario-based online experiments conducted between August 2022 and January 2023. In particular, we examine the mediating effect of perceived threat and the moderating effects of privacy concerns and self-efficacy. The results reveal that perceived threat arising from the characteristics of recommendation algorithm throughput determines the possible coping behaviors of targeted advertising audiences. Moreover, perceived threat mediates the impact of the supervisibility of algorithm throughput on audiences’ coping behaviors. Furthermore, users’ privacy concerns and self-efficacy positively moderate the influence of the supervisibility of algorithm throughput on perceived threat and the relationship between perceived threat and audiences’ coping behaviors, respectively. The results help to explain the black box of the relationship between the characteristics of recommendation algorithms and audience responses from an algorithm throughput perspective. The findings offer implications for improving the effectiveness of personalized recommendations and provide a new perspective for studying the transparency of algorithmic recommendations in consumer behavior. Full article
(This article belongs to the Special Issue Interactive Marketing in Digital Commerce: Consumer Behavior, Engagement and Decision-Making)
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28 pages, 968 KB  
Article
When Algorithms Speak Louder than Empathy: Mechanistic Interpretability as a Costly Authenticity Signal in AI-Mediated E-Commerce Customer Relationships
by Yu Mi, Banggang Wu, Yong Wang and Yuqi Du
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 172; https://doi.org/10.3390/jtaer21060172 - 29 May 2026
Viewed by 567
Abstract
Conversational AI agents are now a routine touchpoint in e-commerce customer service, and AI empathy has emerged as the headline humanization strategy for repairing relational damage during service failures. A growing evidence base reports that empathic AI often backfires, because consumers cannot reconcile [...] Read more.
Conversational AI agents are now a routine touchpoint in e-commerce customer service, and AI empathy has emerged as the headline humanization strategy for repairing relational damage during service failures. A growing evidence base reports that empathic AI often backfires, because consumers cannot reconcile felt warmth with their lay model of what an artificial agent is. This research asks under what conditions AI empathy can be made credible to consumers. We propose that mechanistic interpretability, operationalized in the present studies as a consumer-facing visualization of an AI agent’s internal emotion-vector activations designed in the style of mechanistic-interpretability research, operates as a costly authenticity signal that rehabilitates empathic AI by enabling an attributional shift along the experience dimension of mind perception. Signaling Theory carries the antecedent stage of the causal chain, where mechanistic interpretability serves as a verifiable cue of computational authenticity. Mind Perception Theory carries the downstream stage, where the authenticated empathy is converted into consumer-brand intimacy. Two between-subjects experiments preceded by a feasibility pilot tested the account on Mainland Chinese consumers recruited via the Credamo online panel. Study 1 used a single-factor design contrasting high versus low AI empathy. Study 2 used a two (AI empathy) by two (mechanistic interpretability) full factorial. Study 1 showed a pattern consistent with high (versus low) AI empathy lowering brand intimacy through reduced perceived authenticity. Study 2 replicated the AI-empathy backfire when interpretability was absent, reversed the sign of the AI-empathy slope on the perceived-authenticity mediator when interpretability was present, and neutralized the negative conditional indirect effect on brand intimacy through perceived authenticity. The findings introduce mechanistic interpretability to consumer-marketing scholarship as a manipulable signaling channel, document a structural reversal in the mediator-stage slope coupled with neutralization of the indirect effect on the relational outcome, and prescribe pairing empathic AI phrasing with mechanistic-transparency design rather than deploying empathy without an accompanying transparency cue. Full article
(This article belongs to the Section Digital Marketing and the Evolving Consumer Experience)
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18 pages, 325 KB  
Article
Determinants of Digital Creator Organizations’ Performance: An Organizational Perspective
by Hyejin Cho and Juhee Kim
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 171; https://doi.org/10.3390/jtaer21060171 - 29 May 2026
Viewed by 574
Abstract
As digital creators increasingly operate through organized business structures rather than as individual content producers, understanding organizational characteristics associated with digital creator organizations’ performance has become an important research question. This study examines how content production scale, revenue model diversification, and workforce structure [...] Read more.
As digital creators increasingly operate through organized business structures rather than as individual content producers, understanding organizational characteristics associated with digital creator organizations’ performance has become an important research question. This study examines how content production scale, revenue model diversification, and workforce structure are related to the performance of digital creator organizations. Using survey data on the Korean digital creator media industry, we analyze organizational performance in terms of sales volume and sales per employee. The results indicate that content production scale and revenue model diversification are positively associated with organizational performance. The findings also indicate that workforce structure is relevant: the share of permanent employees is positively related to efficiency, whereas the share of production and development employees is negatively associated with performance. Overall, this study suggests that organizational performance in digital creator organizations is associated not only with content production itself, but also with revenue model breadth and workforce structure. This study contributes to the literature by providing an organizational perspective on performance in the creator economy and offers practical implications for the sustainable growth of digital creator organizations. Full article
(This article belongs to the Section Entrepreneurship, Innovation, and Digital Business Models)
29 pages, 4552 KB  
Article
Don’t Just Say Sorry—Say It Right: How Semantic Congruence and Credibility Cues Turn Negative Reviews into Potential Guests’ Booking Intentions
by Wenna Wang, Jifan Ren, Muhammad Zahid Nawaz and Maroua Ben Maaouia
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 170; https://doi.org/10.3390/jtaer21060170 - 29 May 2026
Viewed by 406
Abstract
Negative online reviews play a critical role in shaping consumer decision-making in the hospitality sector. Drawing on cue utilization theory and signaling theory, this study examines how different types of negative reviews and host responses affect potential guests’ booking intentions, as well as [...] Read more.
Negative online reviews play a critical role in shaping consumer decision-making in the hospitality sector. Drawing on cue utilization theory and signaling theory, this study examines how different types of negative reviews and host responses affect potential guests’ booking intentions, as well as the underlying mechanisms and boundary conditions. Across three scenario experiments, the proposed framework was tested. Study 1 reveals a significant interaction between the type of negative reviews (informational vs. social) and host response strategies (problem-focused vs. emotion-focused), highlighting that aligning response strategies with review types is critical for effective negative review management. Study 2 demonstrates that perceptions of host competence and attitude mediate these effects, indicating that potential guests make decisions through psychological inference. Study 3 finds that platform-endorsed credibility signals, such as host badges (Superhost vs. non-Superhost), significantly moderate these relationships. When hosts are Superhosts, informational negative reviews paired with problem-focused responses further enhance competence perceptions and booking intentions; for non-Superhosts, social negative reviews paired with emotion-focused responses improve attitude perceptions and booking intentions. The findings advance theoretical understanding of how signaling mechanisms shape consumer behavior in home-sharing hospitality platforms, and offer practical guidance for hosts and platforms to manage online reputations strategically and effectively. Full article
(This article belongs to the Topic Digital Marketing Dynamics: From Browsing to Buying)
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23 pages, 1674 KB  
Article
Architecting Micro-Market Resilience: A Signal–Belief–Decision Framework for E-Commerce Platforms
by Zhexu Zhong and Angela C. Chao
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 169; https://doi.org/10.3390/jtaer21060169 - 28 May 2026
Viewed by 564
Abstract
The era of zero-sum competition calls for e-commerce platforms to shift focus toward micro-market resilience. Existing research has split into two traditions: diagnostic studies offer detailed analyses of market failure but lack systemic application, while engineering studies develop deployable tools yet suffer from [...] Read more.
The era of zero-sum competition calls for e-commerce platforms to shift focus toward micro-market resilience. Existing research has split into two traditions: diagnostic studies offer detailed analyses of market failure but lack systemic application, while engineering studies develop deployable tools yet suffer from opaque mechanisms and hidden risks. This paper proposes the Signal–Belief–Decision (SBD) framework to bridge this divide, with the Signal layer transforming private information into verifiable public knowledge, the Belief layer aggregating dispersed signals into shared consensus, and the Decision layer encoding enforceable rules for incentive compatibility. Using an extended signaling game, we diagnose six vulnerability dimensions (VD1–VD6) that destabilize markets. Agent-based modeling then allows us to distill four design principles (DP1–DP4) that inform governance configuration. The SBD framework provides a middle-range theoretical architecture that reorients platform governance from reactive tooling to proactive, consumer-centric design. Full article
(This article belongs to the Section Digital Business, Governance, and Sustainability)
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34 pages, 729 KB  
Article
From Digitalization Awareness to Consumer Outcomes: The Sequential Roles of Risk Appraisal and Platform Trust in the Chinese E-Commerce Context
by Shu Pei Shao, Xinyu Bie and Jong Min Kim
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 168; https://doi.org/10.3390/jtaer21060168 - 28 May 2026
Viewed by 811
Abstract
This study examines the relationships among digitalization awareness, perceived risk, platform trust, and consumer outcomes in e-commerce platforms. Consumer outcomes are conceptualized as a higher-order construct comprising perceived value, engagement, purchase intention, and loyalty. Drawing on technology readiness and trust-based exchange theories, we [...] Read more.
This study examines the relationships among digitalization awareness, perceived risk, platform trust, and consumer outcomes in e-commerce platforms. Consumer outcomes are conceptualized as a higher-order construct comprising perceived value, engagement, purchase intention, and loyalty. Drawing on technology readiness and trust-based exchange theories, we test a mediation model using survey data collected from 370 online shoppers in China and structural equation modeling. The results show that digitalization awareness is negatively associated with perceived risk and positively associated with platform trust. Platform trust positively predicts consumer outcomes and serves as the dominant mediator. Although perceived risk is negatively related to platform trust, it unexpectedly shows a positive direct association with consumer outcomes, indicating a theoretically nuanced role of risk as both a source of vulnerability and a possible trigger of evaluative engagement. Digitalization awareness also retains a significant direct association with consumer outcomes, supporting a partial mediation framework. These findings highlight observed relationships among digitalization awareness, risk appraisal, platform trust, and multidimensional consumer outcomes in the Chinese e-commerce context. Full article
(This article belongs to the Section Digital Marketing and the Evolving Consumer Experience)
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28 pages, 1377 KB  
Article
Please Don’t Refuse Me: The Impact of Recycled Product Anthropomorphism on Consumer Advertising Avoidance
by Weiqi Sun and Dongkwon Seong
J. Theor. Appl. Electron. Commer. Res. 2026, 21(6), 167; https://doi.org/10.3390/jtaer21060167 - 28 May 2026
Cited by 1 | Viewed by 852
Abstract
Recycled products have evolved from environmental substitutes to an important development direction in the future consumer market. However, consumers’ active avoidance of recycled product advertisements is still prevalent, which restricts their market acceptance and promotion. This study aims to systematically explore the relationship [...] Read more.
Recycled products have evolved from environmental substitutes to an important development direction in the future consumer market. However, consumers’ active avoidance of recycled product advertisements is still prevalent, which restricts their market acceptance and promotion. This study aims to systematically explore the relationship between recycled product anthropomorphism and consumer advertising avoidance, and reveal the mediating role of perceived risk, as well as the moderating effects of technology readiness and time orientation. A mixed exploratory method combining Smart PLS and fsQCA was adopted to conduct an in-depth analysis of 728 questionnaires. The results show that recycled product anthropomorphism has a significant negative impact on consumer advertising avoidance, and this effect is partially realized through the mediating mechanism of perceived risk, which is regulated by technology readiness and time orientation. The research results not only enrich the application of anthropomorphism theory in the field of sustainable consumption but also provide empirical evidence and practical guidance for companies to formulate effective recycled product advertising strategies and reduce consumer advertising avoidance. Full article
(This article belongs to the Topic Artificial Intelligence and Sustainable Development)
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