Research on the influence path of the consumer insightful experience of AI personalized recommendation on online purchase intention DOI
Jiwang Yin, Xiaodong Qiu, Ya Wang

и другие.

Опубликована: Ноя. 8, 2024

Язык: Английский

Discovering how digital attitudes, control, self-efficacy and social norms influence the digital behavior decision-making of leisure and recreation activities participants DOI
Tai‐Yi Yu, Chih‐Hsing Liu, Jeou‐Shyan Horng

и другие.

Current Psychology, Год журнала: 2025, Номер unknown

Опубликована: Янв. 2, 2025

Язык: Английский

Процитировано

1

Unveiling the Factors Influencing U.S. Consumer Adoption of the Apparel Digital Retail Theater DOI Creative Commons

Yi-Ning Tai,

Ting Chi

Journal of theoretical and applied electronic commerce research, Год журнала: 2025, Номер 20(2), С. 60 - 60

Опубликована: Март 31, 2025

In recent years, the fashion industry has undergone a significant transformation driven by digital innovations, particularly with emergence of retail theater (DRT). A DRT integrates augmented reality (AR), virtual (VR), and 3D modeling to create immersive shopping experiences that bridge physical worlds. This study specifically focuses on apparel DRTs investigates key factors influencing U.S. consumers’ intention adopt this technology. Drawing unified theory acceptance use technology (UTAUT) perceived risk theory, we developed tested an integrative research model. Primary data were collected through structured online survey administered via Amazon Mechanical Turk (MTurk). total 400 valid responses obtained from consumers. Data analyzed using multiple regression analysis examine hypothesized relationships. The results indicate effort expectancy (ease use), facilitating conditions (technical infrastructure), (concerns about potential harm), time/convenience loss significantly influence DRTs. Surprisingly, performance social not predictors adoption. These findings provide valuable insights for retailers, emphasizing importance user-friendly designs, robust technical infrastructure, minimizing risks foster

Язык: Английский

Процитировано

0

The Impact of AI-Personalized Recommendations on Clicking Intentions: Evidence from Chinese E-Commerce DOI Creative Commons
Jiwang Yin, Xiaodong Qiu, Ya Wang

и другие.

Journal of theoretical and applied electronic commerce research, Год журнала: 2025, Номер 20(1), С. 21 - 21

Опубликована: Фев. 5, 2025

AI-personalized recommendation technology offers more accurate and diverse choices to consumers increases click-through rates sales on e-commerce platforms. Yet, data consumers’ experiences of recommendations their impact path clicking intention are scarce. This article addressed these issues through three studies. In study 1, we adopted the Grounded Theory approach conduct in-depth interviews with 30 Chinese constructed a scale measure consumer experience click intention. 2, empirical research method reliability validity tests 347 valid questionnaires finalize officially. 3, based SOR theory, model formulated hypotheses then conducted analysis using 1097 questionnaires. We found that relevance, inspiration, insightful can significantly promote Moreover, immersive mediates between former factors intention, acceptance When perceive high degree information privacy infringement, experience’s positive will be weakened. Meanwhile, promoting effect also inhibited. quality improves, enhanced. fills gap in literature clarifies how affect It valuable insights for platforms continuously optimize personalized algorithms boost conversion rate online shopping.

Язык: Английский

Процитировано

0

Understanding customer loyalty-aware recommender systems in E-commerce: an analytical perspective DOI Creative Commons
Ramazan Esmeli, Ali Selçuk Can,

A. Y. Awad

и другие.

Electronic Commerce Research, Год журнала: 2025, Номер unknown

Опубликована: Фев. 20, 2025

Язык: Английский

Процитировано

0

Transforming E-Commerce with Intelligent Recommendation Systems: A Review of Current Trends in Machine Learning and Deep Learning DOI Open Access
P. Chinnasamy

International Journal of Computational and Experimental Science and Engineering, Год журнала: 2025, Номер 11(2)

Опубликована: Март 17, 2025

In the ever-changing realm of E-Commerce, it is essential for online businesses to comprehend and adjust shifting consumer behaviour in order achieve long-term success. which, Intelligent Recommendation System (IRS) has gained familiarity by suggesting personalized information based on user preference behaviours. Hence, review paper primarily aims analyse significance intelligent recommendation system transform ecommerce field, specifically enrich personalisation satisfaction, enhance revenue business. Accordingly, proposed survey discussed traditional AI-powered personalization ecommerce. utilize sophisticated algorithms extensive data, allowing provision highly customized relevant content, product recommendation, satisfaction. Besides, examines future trends AI integration within e-commerce, particularly advancements Natural Language Processing (NLP) visual search technologies, which are poised further The concludes with a look toward directions technologies anticipating NLP capabilities, promise shopping experience. Overall, findings article underscores transformative impact IRS e-commerce sector, advocating their continued development response evolving market demands.

Язык: Английский

Процитировано

0

Sustained use of generative AI for shopping: a PLS-ANN analysis DOI
Behzad Foroughi, Morteza Ghobakhloo, Jun Wen

и другие.

Service Industries Journal, Год журнала: 2025, Номер unknown, С. 1 - 34

Опубликована: Апрель 3, 2025

Язык: Английский

Процитировано

0

Key Enablers of Marketing 6.0 in the Metaverse DOI
Rhytheema Dulloo, Mario Silić, Andrea Appolloni

и другие.

IGI Global eBooks, Год журнала: 2025, Номер unknown, С. 441 - 468

Опубликована: Апрель 18, 2025

This study investigates the key enablers of Marketing 6.0 within metaverse environments, examining how technological integration, human-centric approaches, sustainability practices, and seamless phygital experiences drive marketing performance outcomes. As evolves beyond technology-driven personalization toward more meaningful consumer relationships, offers unprecedented opportunities for immersive brand experiences. Using a mixed-methods approach combining surveys 412 professionals 843 consumers, in-depth interviews with 28 executives 12 technology experts, industry-diverse case studies, this research develops comprehensive conceptual framework. The framework identifies four implementation approaches demonstrates influence loyalty purchase intention, engagement acting as mediating mechanism. Structural equation modeling revealed strong support hypothesized emerging particularly influential across all metrics.

Язык: Английский

Процитировано

0

Exploring the Link between Positive Online Shopping Experiences and Online Shopping Frequency: Insights for Mobile Marketing Strategies DOI
Jakub Horváth, Richard Fedorko, Radovan Bačík

и другие.

Deleted Journal, Год журнала: 2024, Номер unknown, С. 262 - 268

Опубликована: Янв. 1, 2024

Mobile marketing is nowadays one of the most popular ways not only to search for information about goods and services, reviews, experiences other customers, but also make actual purchase. The main objective paper identify whether there are statistically significant associations between positive with online shopping via smartphone frequency shopping. Artificial intelligence (AI) bringing revolutionary innovations e-commerce by enabling personalization experience, automation processes, more accurate demand predictions. questionnaire survey included 194 respondents Generation Y (Millennials). Data was collected over course first half 2024. Based on results, it can be concluded that have smartphone. Spearman correlation test confirmed association above variables. COVID-19 pandemic brought changes buying behaviour people. findings our add overall picture share mobile in e-commerce, which a real game changer companies offer their products services online.

Язык: Английский

Процитировано

0

Research on the influence path of the consumer insightful experience of AI personalized recommendation on online purchase intention DOI
Jiwang Yin, Xiaodong Qiu, Ya Wang

и другие.

Опубликована: Ноя. 8, 2024

Язык: Английский

Процитировано

0