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 Ebook: EI 475 Taxonomies : Practical Approaches to Developing an By Helen Lippell |  Ebook: EI 476 Internet+ and Electronic Business in China : Innov By Qiongwei Ye and Baojun Ma |  Ebook: EI 477 The Shopify Story : How a Startup Rocketed to e-Co By Larry MacDonald |
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| Articles |
| Brand Trust in AI-Driven E-Commerce Personalization: The Well-Being–Privacy Trade-Off By Samet, Aydin Sustainability; Basel Vol. 18, Iss. 2, (2026): 1073. DOI:10.3390/su18021073 Abstract :The rapid advancement of artificial intelligence (AI) in e-commerce has intensified data-driven personalization, raising important questions about its psychological implications for consumers and its role in shaping sustainable and responsible digital business practices. This study examines how AI-driven personalization affects consumer psychological well-being in the Turkish e-commerce market and investigates the roles of privacy concerns and brand trust in shaping this relationship from a social sustainability and responsible AI perspective. The research develops and empirically tests an integrated model comprising perceived personalization, privacy concerns, psychological well-being, and brand trust. Survey data from 400 active e-commerce customers were analyzed using partial least squares structural equation modeling (PLS-SEM). Findings show that both perceived relevance and perceived specificity significantly enhance psychological well-being by reducing cognitive overload and increasing perceived value. However, these personalization dimensions also increase privacy concerns, with perceived specificity exerting a notably stronger effect. Privacy concerns negatively affect psychological well-being and competitively mediate the relationship between personalization and well-being, reflecting the Personalization–Privacy Paradox in AI-driven e-commerce contexts. Moreover, brand trust significantly moderates this dynamic by weakening the harmful impact of privacy concerns on psychological well-being. Overall, the findings indicate that privacy concerns represent a latent social cost that can undermine the long-term sustainability of data-intensive business models when not governed by trust-based mechanisms. | |||
| From personalization to novelty: AI`s role in elevating e-commerce experience By Anggraeni, Adilla; Hutagaol-Martowidjojo, Yanthi; Meivitawanli, Bryna; Ayupitha Tiara Silalahi; Tohang, Valentina ; et al. Frontiers in Communication; Lausanne Vol. 11, (May 2026): 1801803. DOI:10.3389/fcomm.2026.1801803 Abstract :Artificial intelligence (AI) assists e-commerce users in making transaction decisions through voice, image search, and recommendation features thereby improving shopping efficiency. AI has transformed consumer experience as individuals increasingly rely on it for purchase decisions, resulting in a more personalized shopping experience. However, despite the growing focus on AI and its diverse applications, there has been limited research examining the factors that influence sustained intention to use AI in the e-commerce sector. This study aims to understand the unified online customer experience and identify the many touchpoints through which consumers engage with brands. This study contributes to existing literature by exploring different aspects of AI usage in the e-commerce context while also highlighting the evolving landscape of AI applications in marketing. This research uses quantitative methodology by collecting primary data through the distribution of online questionnaires. The questions measure customer satisfaction, human laziness, novelty seeking, and the intention to continue using AI. | |||
| Advancing rural e-commerce: examining farmers’ behavioral intention toward e-commerce platforms in China By Weng, Wei; Somasundram, Sotheeswari; Ramayah, Malarvilly; Rahman, Rabi’ah Bte Abd; Zhang, Guangbin ; et al. Humanities & Social Sciences Communications; London Vol. 13, Iss. 1, (Dec 2026): 1083. DOI:10.1057/s41599-026-07065-7 Abstract :Although the expansion of e-commerce has demonstrably enhanced rural livelihoods, the behavioral underpinnings and contextual enablers that shape farmers’ adoption decisions remain inadequately theorized and empirically underexplored. This study advances a tailored extension of the Unified Theory of Acceptance and Use of Technology to construct a comprehensive analytical framework. It examines how performance expectancy, effort expectancy, social influence, facilitating conditions, habit, perceived risk, and policy support jointly inform farmers’ behavioral intention. A survey employing purposive sampling was conducted using a self-administered questionnaire, gathering 392 valid responses from farmers in Sichuan Province, China. The data collected was analyzed using partial least squares structural equation modelling (PLS-SEM). The results confirmed significant associations between the constructs—social influence, facilitating conditions, habit, perceived risk, and policy support—and farmers’ behavioral intention. Furthermore, policy support was found to moderate the relationship between habit and behavioral intention, as well as between perceived risk and behavioral intention. Moreover, this study used IPMA to evaluate the importance and efficacy of predictors on the outcome variable, demonstrating that habit, social influence, and facilitating factors significantly influence farmers’ behavioral intention. These results validate UTAUT2 within the context of e-commerce adoption intention in China and contribute to the literature on policy support’s impact on farmers’ behavioral intention. The findings present critical implications for policymakers and platform administrators, furnishing valuable insights to advance e-commerce adoption within the agricultural sector. | |||
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