Journal Description
Journal of Theoretical and Applied Electronic Commerce Research
Journal of Theoretical and Applied Electronic Commerce Research
(JTAER) is an international, peer-reviewed, open access journal of electronic commerce, published monthly online by MDPI (from Volume 16, Issue 3 - 2021).
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SSCI (Web of Science), dblp, and other databases.
- Journal Rank: JCR - Q2 (Business) / CiteScore - Q1 (General Business, Management and Accounting )
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 27.9 days after submission; acceptance to publication is undertaken in 10.9 days (median values for papers published in this journal in the second half of 2025).
- Recognition of Reviewers: APC discount vouchers, optional signed peer review, and reviewer names published annually in the journal.
Impact Factor:
4.6 (2024);
5-Year Impact Factor:
5.1 (2024)
Latest Articles
The Impact of Integrated AI and AR in E-Commerce: The Roles of Personalization, Immersion, and Trust in Influencing Continued Use
J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 33; https://doi.org/10.3390/jtaer21010033 (registering DOI) - 10 Jan 2026
Abstract
Digital retail is undergoing a paradigm shift driven by the deep integration of artificial intelligence (AI) and augmented reality (AR). Although prior studies have examined the independent effects of AI-based personalized recommendation (cognitive path) and AR-enabled immersion (experiential path), how their integration systematically
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Digital retail is undergoing a paradigm shift driven by the deep integration of artificial intelligence (AI) and augmented reality (AR). Although prior studies have examined the independent effects of AI-based personalized recommendation (cognitive path) and AR-enabled immersion (experiential path), how their integration systematically shapes user behavior through internal psychological mechanisms remains an important unresolved theoretical gap. To address this gap, this study develops an integrated model grounded in the stimulus–organism–response (S-O-R) framework and trust transfer theory. Specifically, the model examines how personalized recommendation, as a dynamic external stimulus, influences users’ cognitive state (perceived usefulness) and experiential state (immersion); how the overall trust of users in the integrated platform can be used as a key boundary condition to adjust the transformation efficiency from the above stimulus to the internal state; and how the above cognitive and experiential states can ultimately drive the continued usage intention through the mediation of positive emotional response. Based on survey data from 400 Chinese consumers with AR shopping experience on Taobao, analyzed using structural equation modeling (SEM), the results indicate that (1) personalized recommendation positively affects both immersion and perceived usefulness; (2) platform trust significantly and positively moderates the effects of personalized recommendation on both immersion and perceived usefulness; (3) both cognitive and experiential states stimulate positive emotions, which in turn enhance continued usage intention, with perceived usefulness exerting a stronger effect; (4) a key theoretical finding is that there is a significant positive correlation between perceived usefulness and immersion, revealing the coupling of psychological paths in an integrated environment; however, immersion does not moderate the effect of personalized recommendation on emotional responses, suggesting that the current integration mode emphasizes the formation of a stable psychological structure rather than real-time interaction. This study makes three contributions to the existing literature. First, it extends the application of S–O–R theory in a complex technological environment by analyzing the “organism” as a parallel and related cognitive-experience dual path and confirming its coupling relationship. Second, it elucidates the enabling role of trust as a moderating mechanism rather than a direct antecedent, thereby enriching micro-level evidence for trust transfer theory in the context of technology integration. Finally, by contrasting path coupling with process regulation, this study provides a more detailed distinction for understanding the theoretical connotations and boundaries of AI–AR technology integration, which may mainly be a kind of structural integration.
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(This article belongs to the Section Digital Marketing and Consumer Experience)
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Open AccessEditorial
JTAER: Evolving Aims, Sections, and Development Strategies
by
Ting Chi
J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 32; https://doi.org/10.3390/jtaer21010032 - 9 Jan 2026
Abstract
The field of electronic commerce has entered a new phase of accelerated transformation [...]
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Open AccessArticle
Mere Virtual Presence Experiences (MVPE) Drive Online Brand Community Members’ Purchasing Behavior: Moderating Roles of Consumers’ Need for Uniqueness (CNFU) and Product Type
by
Ching-Jui Keng, Ming-Yiin Hu and Min-Cyun Jiang
J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 31; https://doi.org/10.3390/jtaer21010031 - 9 Jan 2026
Abstract
Grounded in Social Impact Theory, this study examines the effects of virtual experiences generated by Mere Virtual Presence (MVP), Mere Virtual Presence with Product Experience (MVPE), and pure brand websites on consumers’ brand attitudes and purchase intentions. Additionally, it explores the moderating roles
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Grounded in Social Impact Theory, this study examines the effects of virtual experiences generated by Mere Virtual Presence (MVP), Mere Virtual Presence with Product Experience (MVPE), and pure brand websites on consumers’ brand attitudes and purchase intentions. Additionally, it explores the moderating roles of Consumers’ Need for Uniqueness (CNFU) and product type (search vs. experience products). This study adopts an experimental design with three brand website types (MVP brand communities, MVPE brand communities, and pure brand websites) and two product types to examine the hypothesis. Specifically, a 3 (brand website type) × 2 (product type) experimental design was implemented to examine the influence of brand website types across different scenarios of online marketing. The findings reveal significant insights into consumer brand marketing. Specifically, consumers with low CNFU exhibited higher brand attitudes and purchase intentions compared to those with high CNFU when engaging with search products in MVPE brand communities Furthermore, fan avatars within a virtual brand community can still influence consumer perceptions even without direct interaction. These insights contribute to the growing body of research on personalized marketing and offer practical strategies for leveraging eWOM to enhance consumer engagement and influence decision-making in the digital landscape.
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(This article belongs to the Topic Digital Marketing Dynamics: From Browsing to Buying)
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Driving Service Stickiness in the AI Subscription Economy: The Roles of Algorithmic Curation, Technological Fluidity, and Cognitive Efficiency
by
Bokyung Kim and Joonyong Park
J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 30; https://doi.org/10.3390/jtaer21010030 - 9 Jan 2026
Abstract
This study examines the psychological mechanisms underlying service stickiness during the mature phase of the AI subscription economy, with particular attention to the paradox of subscription fatigue. To enhance conceptual clarity, AI-driven stimuli—specifically Algorithmic Curation and Technological Fluidity—are defined as perceived attributes at
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This study examines the psychological mechanisms underlying service stickiness during the mature phase of the AI subscription economy, with particular attention to the paradox of subscription fatigue. To enhance conceptual clarity, AI-driven stimuli—specifically Algorithmic Curation and Technological Fluidity—are defined as perceived attributes at the individual level. Employing the Stimulus–Organism–Response (S-O-R) framework, the research explores how these perceived stimuli influence consumers’ internal states (Cognitive Efficiency and Serendipity) and subsequent behavioral responses (Service Stickiness). Empirical analysis using partial least squares structural equation modeling (PLS-SEM) on data from U.S. subscription service users yields several theoretical insights. Cognitive Efficiency is identified as the primary driver of stickiness, indicating that, in the context of subscription fatigue, the utilitarian benefit of reduced cognitive effort surpasses hedonic enjoyment. Additionally, the study identifies a “Frictionless Trap,” in which excessive Technological Fluidity negatively affects Serendipity (β = −0.195), suggesting that an entirely seamless experience may create a filter bubble that limits unexpected discovery. As a result, Serendipity does not significantly affect stickiness in the aggregate model. However, post hoc analysis demonstrates that Serendipity remains significant for high-income users, while Cognitive Efficiency is most influential in high-frequency utilitarian contexts, such as food services. These findings indicate that sustainable retention depends on reducing cognitive load while intentionally introducing friction to preserve opportunities for discovery.
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(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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Open AccessEditorial
Transforming E-Commerce with AI: Navigating Innovation, Personalization, and Ethical Challenges
by
Xiaofei Zhang, Kai Li, Yi Wu, Sai Liang and Mengli Yu
J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 29; https://doi.org/10.3390/jtaer21010029 - 8 Jan 2026
Abstract
Artificial Intelligence (AI) has become a primary agent of change in the contemporary e-commerce landscape [...]
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(This article belongs to the Special Issue ICEC 2025: Transforming E-Commerce with AI: Navigating Innovation, Personalization, and Ethical Challenges)
Open AccessArticle
Crowdfunding as an E-Commerce Mechanism: A Deep Learning Approach to Predicting Success Using Reduced Generative AI Embeddings
by
Hakan Gunduz, Muge Klein and Ela Sibel Bayrak Meydanoglu
J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 28; https://doi.org/10.3390/jtaer21010028 - 8 Jan 2026
Abstract
Crowdfunding platforms like Kickstarter have reshaped early-stage financing by allowing entrepreneurs to connect directly with potential supporters. As a fast-expanding part of digital commerce, crowdfunding offers significant opportunities but also substantial risks for both entrepreneurs and platform operators, making predictive analytics an essential
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Crowdfunding platforms like Kickstarter have reshaped early-stage financing by allowing entrepreneurs to connect directly with potential supporters. As a fast-expanding part of digital commerce, crowdfunding offers significant opportunities but also substantial risks for both entrepreneurs and platform operators, making predictive analytics an essential capability. Although crowdfunding shares some operational features with traditional e-commerce, its mix of financial uncertainty, emotionally charged storytelling, and fast-evolving social interactions makes it a distinct and more challenging forecasting problem. Accurately predicting campaign outcomes is especially difficult because of the high-dimensionality and diversity of the underlying textual and behavioral data. These factors highlight the need for scalable, intelligent data science methods that can jointly exploit structured and unstructured information. To address these issues, this study proposes a novel AI-based predictive framework that integrates a Convolutional Block Attention Module (CBAM)-enhanced symmetric autoencoder for compressing high-dimensional Generative AI (GenAI) BERT embeddings with meta-heuristic feature selection and advanced classification models. The framework systematically couples attention-driven feature compression with optimization techniques—Genetic Algorithm (GA), Jaya, and Artificial Rabbit Optimization (ARO)—and then applies Long Short-Term Memory (LSTM) and Gradient Boosting Machine (GBM) classifiers. Experiments on a large-scale Kickstarter dataset demonstrate that the proposed approach attains 77.8% accuracy while reducing feature dimensionality by more than 95%, surpassing standard baseline methods. In addition to its technical merits, the study yields practical insights for platform managers and campaign creators, enabling more informed choices in campaign design, promotional tactics, and backer targeting. Overall, this work illustrates how advanced AI methodologies can strengthen predictive analytics in digital commerce, thereby enhancing the strategic impact and long-term sustainability of crowdfunding ecosystems.
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(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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Open AccessArticle
Interactive Effects of Live Streaming Modes and Return Policies: A Game-Theoretic Analysis of Manufacturers’ Pre-Sale Decisions
by
Dandan Dong, Guoqu Deng, Xinxin Qie, Dan Ralescu and Ersen Miao
J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 27; https://doi.org/10.3390/jtaer21010027 - 7 Jan 2026
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This paper investigates the interactive effects of live streaming pre-sale modes and return policies within a manufacturer’s two-stage supply chain. On the one hand, in addition to traditional pre-sales, manufacturers can adopt merchant live streaming or commission influencer live streaming to stimulate demand,
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This paper investigates the interactive effects of live streaming pre-sale modes and return policies within a manufacturer’s two-stage supply chain. On the one hand, in addition to traditional pre-sales, manufacturers can adopt merchant live streaming or commission influencer live streaming to stimulate demand, enhance consumer engagement, and generate social influence. On the other hand, a “Money-back guarantee (MBG)” policy can be implemented to mitigate consumers’ valuation uncertainty. Using a game-theoretic model, we examine the manufacturer’s optimal joint decisions across six scenarios, determining the optimal conditions for activating each pre-sale mode and the MBG policy. Our findings reveal that the effectiveness of an MBG in promoting pre-sales is not universal but highly contingent on factors such as return costs, product satisfaction, and the social influence generated through live streaming. Specifically, traditional pre-sales tend to adopt an MBG only when return costs are low, whereas merchant live streaming pre-sales consistently adopt it under weak social influence. In contrast, influencer live streaming pre-sales are more likely to adopt MBGs when return costs are low; however, with high return costs, the manufacturer’s profit may fall below that of not conducting pre-sales, leading to the abandonment of this mode. Regarding mode selection, under a no-return policy, manufacturers prefer influencer live streaming when social influence is weak but switch to merchant live streaming when it is strong. When offering an MBG, manufacturers tend to commission influencer live streaming when product satisfaction and return costs are low but revert to traditional pre-sales when satisfaction is high. Conversely, with high return costs, manufacturers prefer merchant live streaming under low satisfaction but favor influencer live streaming when satisfaction is high. These findings offer valuable theoretical insights and practical guidance for manufacturers to optimize their pre-sales and return strategies under diverse market conditions.
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Open AccessArticle
Platform Governance and Digital Sustainability: A Systemic Functional Dependency Perspective
by
Keming Chen and Tingting Li
J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 26; https://doi.org/10.3390/jtaer21010026 - 6 Jan 2026
Abstract
The governance of digital platforms is a key factor in sustainable business development. Nevertheless, the specific governance mechanisms through which platforms reconfigure virtual (e-commerce) and physical (logistics) systems, and whether these outcomes are equitable or sustainable, remain insufficiently examined. This research proposes an
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The governance of digital platforms is a key factor in sustainable business development. Nevertheless, the specific governance mechanisms through which platforms reconfigure virtual (e-commerce) and physical (logistics) systems, and whether these outcomes are equitable or sustainable, remain insufficiently examined. This research proposes an analytical framework, Systemic Functional Dependency, to elucidate how platform governance shapes the co-evolution of digital and physical activities in the platform economy. The analysis of China’s platform economy from 2013 to 2022 reveals a governance-induced bifurcation: Core regions build sustainable, synergistic business models (local e-com coef. = 0.204, p < 0.05). In contrast, peripheral regions face structural decoupling, where digital-led growth (22.63% CAGR) vastly outpaces the expansion of physical business capacity (6.46% CAGR). This imbalance, caused by a functional transition (32.21% CAGR in net-work-serving logistics vs. 2.44% in local-serving logistics), led to a structural breakpoint in 2017–2018. The findings advance digital business theory by linking platform governance to asymmetric outcomes. This leads to a functional lock-in for peripheral regions, which is a big problem for sustainability and shows how important it is to have governance frameworks right away.
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(This article belongs to the Section Digital Business, Governance, and Sustainability)
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Open AccessArticle
Driving Sustainable Consumption Online: The Interplay of Green Digital Marketing and Digital Literacy in Shaping Purchase Intentions for Sustainable Coffee in Urban Ethiopia’s E-Commerce
by
Abdulaziz Hassen Mume and Xixiang Sun
J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 25; https://doi.org/10.3390/jtaer21010025 - 6 Jan 2026
Abstract
The growth of e-commerce in emerging economies presents a critical opportunity to steer digital consumption toward sustainability, yet the mechanisms that drive online green purchases in these contexts remain underexplored. This study examines how green digital marketing signals, specifically eco-labeling and sustainability claims,
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The growth of e-commerce in emerging economies presents a critical opportunity to steer digital consumption toward sustainability, yet the mechanisms that drive online green purchases in these contexts remain underexplored. This study examines how green digital marketing signals, specifically eco-labeling and sustainability claims, influence the online purchase intention for sustainable coffee in urban Ethiopia, introducing digital literacy as a key moderating factor. Grounded in an integrated framework of Signaling Theory and the Theory of Planned Behavior, the research model was tested using Partial Least Squares Structural Equation Modeling (PLS-SEM) on data from 451 urban e-commerce consumers. The results confirm that both eco-labeling and sustainability claims significantly enhance purchase intention, with green trust serving as a significant partial mediator. A pivotal finding is that digital literacy positively and significantly moderates the relationship between green trust and purchase intention, indicating that consumers with higher digital competence are more effective at translating trust into purchase decisions. These findings underscore that the success of online green marketing is contingent not only on signal credibility but also on user capability, offering crucial insights for platform design and policy in emerging digital markets.
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(This article belongs to the Section Digital Business, Governance, and Sustainability)
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Open AccessArticle
What Makes Social Posts Go “Hot”? A Multimodal Analysis of Creator–Content–Timing Signals on a Visual Social Platform
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Yi Wang and Ying Xin
J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 24; https://doi.org/10.3390/jtaer21010024 - 6 Jan 2026
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Visual social commerce platforms now mediate much of brand communication and conversion, yet managers still lack clear guidance on how brands and creators should technically design posts that consistently achieve high user engagement under budget and platform constraints. Prior research explains why users
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Visual social commerce platforms now mediate much of brand communication and conversion, yet managers still lack clear guidance on how brands and creators should technically design posts that consistently achieve high user engagement under budget and platform constraints. Prior research explains why users engage with brands online, but it mainly focuses on individual motives and message features and largely treats the brand–creator–platform relationship and the post-design process as a black box. Drawing on the Technology Affordance Actualization (TAA) framework—which conceptualizes how platform-provided action possibilities (affordances) are selectively enacted through user practices—we develop a Creator–Content–Timing (CCT) perspective on how brands and creators actualize visibility, interactivity, and commercial collaboration affordances into user engagement outcomes. We analyze 138,713 image–text posts from 100 beauty brands on Xiaohongshu using machine learning, text mining, computer vision, and regression and clustering models. The results show that creator tier, brand status, sponsorship, content cues, and posting time have systematic effects on both engagement intensity and a cost-normalized metric, Int_per_cost (interactions per 1000 CNY of estimated advertising cost). Smaller creators and non-sponsored posts achieve higher engagement per impression and higher Int_per_cost than top-tier creators and sponsored posts; moderate text length, non-exclusive brand mentions, human faces, and specific temporal windows are also associated with superior outcomes. The study extends TAA to a creator–brand–platform context by operationalizing affordance actualization as observable CCT configurations at the post level and provides configuration-level guidance on how brands can align creator selection, content design, and scheduling to improve engagement on visual social commerce platforms.
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Determinants of Success in Online Travel: Examining the Effect of a Comprehensive Higher-Order Model on e-Service Quality on Loyalty and Customers’ Citizenship Behavior
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Peter O’Connor and Guy Assaker
J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 23; https://doi.org/10.3390/jtaer21010023 - 5 Jan 2026
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This study proposes and validates a comprehensive model of the determinants of online travel company success by establishing the relationships between a properly conceptualized higher-order e-service quality construct, perceived value, and satisfaction on customer loyalty and customers’ citizenship behavior. The model was tested
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This study proposes and validates a comprehensive model of the determinants of online travel company success by establishing the relationships between a properly conceptualized higher-order e-service quality construct, perceived value, and satisfaction on customer loyalty and customers’ citizenship behavior. The model was tested using structural equation modeling and data collected on 257 US travelers. Results reveal that e-service quality positively influences customers’ loyalty and citizenship behavior both directly and indirectly (through perceived value and satisfaction). Perceived value also exerts a direct positive influence on satisfaction. The results provide theoretical and practical implications by helping to demystify the relationships between the tested variables, as well as by increasing our understanding of the determinants of success in online travel websites.
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Open AccessArticle
From Manual Delivery to Autonomous Delivery Robots: A Socio-Technical Push–Pull–Mooring Framework
by
Xueli Tan, Dongphil Chun, Shuxian Zhao and Yanfeng Liu
J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 22; https://doi.org/10.3390/jtaer21010022 - 5 Jan 2026
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Urban delivery demand continues to rise, intensifying last-mile logistics challenges and accelerating the transition from manual delivery to autonomous delivery robots (ADRs). This study investigates the behavioral mechanisms underlying consumers’ migration toward ADRs. Grounded in the socio-technical systems perspective, we integrate the Push–Pull–Mooring
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Urban delivery demand continues to rise, intensifying last-mile logistics challenges and accelerating the transition from manual delivery to autonomous delivery robots (ADRs). This study investigates the behavioral mechanisms underlying consumers’ migration toward ADRs. Grounded in the socio-technical systems perspective, we integrate the Push–Pull–Mooring (PPM) model with Social Cognitive Theory (SCT) to explain how technological and social stimuli shape switching and continuance intentions through cognitive and emotional pathways. Survey data from 786 Chinese consumers, analyzed using second-order structural equation modeling, support the proposed framework. The results indicate that dissatisfaction with manual delivery (push) and perceived benefits of ADRs (pull) significantly enhance both switching and continuance intentions. Outcome expectancy positively predicts switching intention but negatively predicts continuance intention. Technophobia reduces switching intention but does not significantly influence continuance. Moreover, social norms moderate key relationships, highlighting the role of external social influence in technology transition. This study extends PPM research into the smart logistics context, introduces socio-cognitive mechanisms into technology switching analysis, and conceptually distinguishes switching and continuance intentions as separate constructs. The findings offer practical guidance for ADR developers and policymakers by emphasizing strategies to reduce emotional resistance, enhance social endorsement, and promote the sustainable adoption of autonomous delivery technologies.
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Open AccessArticle
The Past Shapes the Present: Competitive Experience and Digital Orientation
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Yanyan Ma, Xiaohong Wang, Yixuan Kang and Linlin Liu
J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 21; https://doi.org/10.3390/jtaer21010021 - 5 Jan 2026
Abstract
As a crucial endogenous resource of firms, history has increasingly been recognized for its role in shaping strategies. However, little is known about how historical competitive experience affects digital orientation (DO), a vital strategic foundation that enables firms to capture value from digital
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As a crucial endogenous resource of firms, history has increasingly been recognized for its role in shaping strategies. However, little is known about how historical competitive experience affects digital orientation (DO), a vital strategic foundation that enables firms to capture value from digital transformation. This study addresses this gap by investigating the impact of competitive experience on firms’ DO and the factors shaping this relationship. Using a panel dataset of 4281 Chinese A-share listed firms from 2012 to 2023, we measure DO through MD&A-based text analysis and test our hypotheses with a two-way fixed-effects model. The results reveal an inverted U-shaped relationship between competitive experience and DO. This indicates that moderate competitive experience stimulates DO, while excessive competitive experience can induce rigidity and constrain DO. Interestingly, market turbulence decreases the positive and increases the negative effect of competitive experience on DO, whereas market competition exerts the opposite moderating effect. Further analysis shows that this positive effect is enhanced within a higher-quality innovation environment. Our findings highlight the importance of history in shaping firms’ digital strategic posture in an emerging market. By treating competitive experience as a strategic resource, managers can transform their competitive legacy into a powerful engine for DO, especially under favorable environments.
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(This article belongs to the Section Digital Business, Governance, and Sustainability)
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How Does the Fear of Missing Out (FOMO) Moderate Reduced SNS Usage Behavior? A Cross-Cultural Study of China and the United States
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Hui-Min Wang, Nuo Jiang, Han Xiao and Kyungtag Lee
J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 20; https://doi.org/10.3390/jtaer21010020 - 4 Jan 2026
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With the ubiquitous connectivity and exposure of social network service (SNS), the stressors it causes have received extensive attention in the academic community. Unlike previous studies, this research focuses on the cross-cultural dimension and explores the different effects of multiple SNS-generated stressors on
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With the ubiquitous connectivity and exposure of social network service (SNS), the stressors it causes have received extensive attention in the academic community. Unlike previous studies, this research focuses on the cross-cultural dimension and explores the different effects of multiple SNS-generated stressors on user behavior outcomes. Based on the “Stressors-Strain-Outcome” (SSO) theoretical framework, we constructed a “technical stressors—exhaustion—reduced SNS usage intention” pathway to systematically investigate five types of technical stressors. These were perceived information overload, perceived social overload, perceived compulsive use, perceived privacy concern, and perceived role conflict. We introduce “fear of missing out” (FOMO) as a moderating variable to explore its moderating role in SNS exhaustion and reduced SNS usage intention. In this study, we took SNS users from China and the United States as the research subjects (338 samples from China and 346 samples from the United States), and conducted empirical tests using structural equation models and multiple comparative analyses. The results show that there are significant cultural differences between Chinese and American users in terms of the perceived intensity of technostress, the path of stress transmission, and the moderating effect of FOMO. Against the background of collectivist culture in China, perceived information overload, privacy concerns, and role conflicts have a significant positive impact on SNS exhaustion, and SNS exhaustion further positively drives the intention to reduce usage of SNS. However, the direct impacts of perceived social overload and perceived compulsive usage are not significant, and FOMO does not play a significant moderating role. In the context of the individualistic culture found in the United States, only perceived information overload and perceived social overload have a significant positive impact on SNS exhaustion, and FOMO significantly negatively moderates the relationship between exhaustion and reduced SNS usage intention, as high FOMO levels will strengthen the driving effect of exhaustion on reduced usage intention. The innovation this study exhibits lies in verifying the applicability of the SSO model in social media behavior research from a cross-cultural perspective, revealing the cultural boundaries of the FOMO moderating effect, and enriching the cross-cultural research system of reduced usage intention of SNS. The research results not only provide empirical support for a deep understanding of the psychological mechanisms of users’ SNS usage behaviors in different cultural backgrounds, but also offer important references that SNS enterprises can use to formulate differentiated operation strategies and optimize cross-cultural user experiences.
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(This article belongs to the Section Digital Marketing and Consumer Experience)
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Open AccessArticle
Customer Requirements Analysis and Product Service Improvement Framework Using Multi-Source User-Generated Content and Dual Importance–Performance Analysis: A Case Study of Fresh E-Ecommerce
by
Zifan Shen, Cuiming Zhao and Yanlai Li
J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 19; https://doi.org/10.3390/jtaer21010019 - 4 Jan 2026
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The growth of e-commerce has led to a rapid increase in user-generated content (UGC), attracting scholars’ attention as a new data source for investigating customer requirements. However, existing requirements analysis methods fail to integrate three critical requirement indicators: stated importance, derived importance, and
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The growth of e-commerce has led to a rapid increase in user-generated content (UGC), attracting scholars’ attention as a new data source for investigating customer requirements. However, existing requirements analysis methods fail to integrate three critical requirement indicators: stated importance, derived importance, and performance. Using only one or two of these indicators inevitably has its limitations. This paper proposes a novel framework for analyzing and prioritizing customer requirements based on multi-source UGC. First, customer requirements are extracted from online reviews and questions & answers using non-negative matrix factorization. Next, aspect-level sentiment analysis and multi-source data fusion are employed to calculate dual importance and performance. Specifically, we developed an improved importance–performance analysis (IPA) model, named dual importance–performance analysis (Du-IPA), which integrates the three indicators to classify requirement types in a 3D cube with corresponding improvement strategies. Finally, by combining the three indicators, an improved prospect value and PROMETHEE-II are proposed using prospect theory to prioritize CRs for product service improvement. The effectiveness of the proposed method is demonstrated through a case study of fresh food in online retail.
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Open AccessArticle
Beyond Aesthetics: Functional Categorization and the Impact of Review Image Composition on Purchase Decisions
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Minchen Wang and Yu Tong
J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 18; https://doi.org/10.3390/jtaer21010018 - 4 Jan 2026
Abstract
Online review images shape consumer perceptions by offering visual cues of product quality and use. Existing studies focus on aesthetics or object presence but overlook the functional balance among image types. This study introduces the Holistic Image Proportion (HIP)—the ratio of holistic to
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Online review images shape consumer perceptions by offering visual cues of product quality and use. Existing studies focus on aesthetics or object presence but overlook the functional balance among image types. This study introduces the Holistic Image Proportion (HIP)—the ratio of holistic to detailed review images—as a key determinant of visual information completeness. Using deep learning (ResNet-101) to classify over 240,000 images from 4450 clothing products, we find an inverted U-shaped relationship between HIP and sales: a balanced mix (HIP ≈ 0.5) maximizes performance. A follow-up experiment confirms that balanced image composition enhances perceived completeness, which fully mediates its effect on purchase intention. Review sentiment further moderates this relationship, amplifying the effect under positive sentiment. This research extends information completeness theory to visual data, highlighting that completeness emerges from functional image composition rather than quantity or aesthetics, offering new insights for multimodal persuasion and e-commerce design.
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(This article belongs to the Section Data Science, AI, and e-Commerce Analytics)
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Open AccessArticle
The Effect of Homophonic Puns on Green Purchase Intention: The Mediating Role of Affiliative Humor and the Moderation of Visual Salience
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Jianguo Wang, Xixiang Sun, Wei Zhang, Liang Gao, Jing Lu and Ziqing Guo
J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 17; https://doi.org/10.3390/jtaer21010017 - 4 Jan 2026
Abstract
Green brands are increasingly leveraging electronic commerce and interactive marketing to enhance persuasive efforts in new media environments. However, empirical research on the role of linguistic rhetoric in these interactive settings remains limited. This study examines whether the use of homophonic puns in
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Green brands are increasingly leveraging electronic commerce and interactive marketing to enhance persuasive efforts in new media environments. However, empirical research on the role of linguistic rhetoric in these interactive settings remains limited. This study examines whether the use of homophonic puns in green brand advertising increases green purchase intention on digital platforms, and how visual salience moderates this effect. Across four online experiments (total N = 1382), using stimuli modeled on social media feeds and mobile commerce interfaces, we manipulated advertising copy to include either homophonic puns or non-pun alternatives and varied the level of interface salience. The results indicate that homophonic puns significantly increase green purchase intention, primarily through the mechanism of affiliative humor, which proved stronger than alternative humor pathways. Moreover, visual salience moderates this effect: high-salience layouts amplify humor perception and purchase intention, while low-salience conditions yield no significant effects. This study advances the field of interactive marketing by proposing a language–emotion–behavior framework and introducing a cross-modal synergy mechanism that links linguistic rhetoric with visual attention in digital media contexts. The findings provide both theoretical insights and practical implications for e-commerce platforms, particularly in optimizing advertising copy, attention design, and message placement strategies to align pun-based messages with high-salience executions, thereby enhancing green brand engagement.
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(This article belongs to the Topic Innovations in New Media: Shaping the Future of Interactive Marketing)
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Open AccessArticle
Factors Influencing Sponsorship Disclosure and Attitudes Toward Problematic Digital Marketing Practices of Social Media Influencers Worldwide
by
Louisa Ha, Halima Lul Ali, Kelsey Zook, Arnab Biswas, Osama Bahassan, Man Luo, Yang Yang and Mohammad Abuljadail
J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 16; https://doi.org/10.3390/jtaer21010016 - 4 Jan 2026
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This mixed-methods study investigates ethical practices among 500 social media influencers spanning across 44 countries and eight languages using surveys and in-depth interviews. Contrary to the study’s assumptions of demographic and cultural influence, most structural factors and individual characteristics showed little influence towards
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This mixed-methods study investigates ethical practices among 500 social media influencers spanning across 44 countries and eight languages using surveys and in-depth interviews. Contrary to the study’s assumptions of demographic and cultural influence, most structural factors and individual characteristics showed little influence towards sponsorship disclosure practices and attitudes toward problematic digital marketing. Findings show that cultural context (high or low) had no relationship to disclosure practices, while linguistic culture significantly affected disclosure methods, with French-speaking creators being the most likely to directly disclose sponsorships while Chinese creators are the least likely to do so. Follower size was the strongest predictor, with creators with 10 K+ followers being twice as likely to disclose sponsorships directly compared to nano-influencers. Qualitative interviews revealed that contingency factors, such as including personal values alignment with brands, influencer confidence in audience trust, brand type, and client expectations, affect disclosure practices. The study shows the complexity of ethical decisions on sponsorship disclosure practices and the need for an ethical theory-based standard to provide guidance for influencers to optimize disclosure of sponsored product recommendations.
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Open AccessArticle
Navigating the Digital Landscape: The Impact of Social Media Agility on Customer-Based Brand Equity, Customer Engagement and Customer Motivation
by
Chinedu Felix Ikoko, Figen Yeşilada and Iman Aghaei
J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 15; https://doi.org/10.3390/jtaer21010015 - 4 Jan 2026
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Despite the increasing number of social media users and the advantages linked to agility in other areas, the implementation of agility within a social media framework remains unexamined. This study aims to examine how perceived social media agility influences customer-based brand equity through
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Despite the increasing number of social media users and the advantages linked to agility in other areas, the implementation of agility within a social media framework remains unexamined. This study aims to examine how perceived social media agility influences customer-based brand equity through the mediating roles of customer engagement and customer motivation. A quantitative method was utilized. Data was collected from 420 Social Networking Site users in Turkey using a questionnaire. The study utilised convenience sampling method to gather the data. Structural equation modelling was used to analyse the data, employing SmartPLS 4. The results show that perceived social media agility has a positive impact on customer-based brand equity, customer engagement, and customer motivation. Customer engagement and customer motivation were found to impact customer-based brand equity significantly. Furthermore, customer motivation has no significant impact on customer engagement. Change-seeking has a positive influence on customer engagement and customer motivation. Customer engagement and customer motivation were found to significantly mediate the link between perceived social media agility and customer-based brand equity. The study contributes to the literature by integrating social media agility into established frameworks of brand equity and consumer behaviour. Practically, the results suggest that firms should develop agile and responsive social media strategies to enhance customer engagement and strengthen brand equity.
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Open AccessArticle
Human and AI Reviews Coexist: How Hybrid Review Systems Enhance Trust and Decision Confidence in E-Commerce
by
Yunzhe Li and Hong-Youl Ha
J. Theor. Appl. Electron. Commer. Res. 2026, 21(1), 14; https://doi.org/10.3390/jtaer21010014 - 4 Jan 2026
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This research investigates how hybrid review systems integrating human-generated reviews and AI-generated summaries shape consumer trust and decision-related confidence. Across three controlled experiments conducted in simulated e-commerce environments, when and how hybrid reviews enhance consumer evaluations were examined. Study 1 demonstrates that hybrid
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This research investigates how hybrid review systems integrating human-generated reviews and AI-generated summaries shape consumer trust and decision-related confidence. Across three controlled experiments conducted in simulated e-commerce environments, when and how hybrid reviews enhance consumer evaluations were examined. Study 1 demonstrates that hybrid reviews, which combine the emotional authenticity of human input with the analytical objectivity of AI, elicit greater levels of review trust and decision confidence than single-source reviews. Study 2 employs an experimental manipulation of presentation order and demonstrates that decision confidence increases when human reviews are presented before AI summaries, because this sequencing facilitates more effective cognitive integration. Finally, Study 3 shows that AI literacy strengthens the positive effect of perceived diagnosticity on confidence, while information overload mitigates it. By explicitly testing these processes across three experiments, this research clarifies the mechanisms through which hybrid reviews operate, identifying authenticity and objectivity as dual mediators, and sequencing, literacy, and cognitive load as critical contextual moderators. This research advances current theories on human–AI complementarity, information diagnosticity, and dual-process cognition by demonstrating that emotional and analytical cues can jointly foster trust in AI-mediated communications. This integrative evidence contributes to a nuanced understanding of how hybrid intelligence systems shape consumer decision-making within digital marketplaces.
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