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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 online quarterly by MDPI since Volume 16, Issue 3, 2021, and online monthly since 2026.

Quartile Ranking JCR - Q2 (Business)

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All Articles (1,419)

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

4 May 2026

Correlation matrix of numeric attributes.

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

30 April 2026

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

30 April 2026

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

30 April 2026

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J. Theor. Appl. Electron. Commer. Res. - ISSN 0718-1876