The Fourth Industrial Revolution has brought advanced technologies such as augmented reality (AR) and virtual reality (VR), transforming consumer behavior in retailing and arousing the interest of scholars in studying customer responses to these technologies in retail settings. However, owing to variations in specific contextual factors, the results of related research have been mixed, which impedes retailers’ capacity to gain a systematic understanding of the formulation of well-informed marketing decisions in the context of AR and VR retailing. To address these gaps, this systematic review synthesizes extant empirical evidence with 1099 effect sizes from 111 published studies with 136 datasets and 547,415 sample sizes. This study is based on well-established theories, including the technology acceptance model, the customer journey theory, and the unified theory of acceptance and use of technology, which are extended to create a more comprehensive framework that is adapted for the customer journey in AR and VR retailing. Our findings reveal significant and positive correlations for all the proposed constructs, including the experience; intrinsic, extrinsic, hedonic, and utilitarian factors; and customer experience, attitude, intention, and loyalty, and verify the significant moderating effects for technology and product types. From a management perspective, our findings provide a systematic understanding of enhancing retailers’ integrated sustainable marketing strategies in the context of AR and VR retail and propose a forward-looking research agenda.

Purpose: This investigation explores the increasingly prevalent role of data-driven approaches in hospitality and tourism research, which predominantly relies on expansive datasets from singular sources of social media data. The focus of this study is on uncovering distinct variations across different online travel agencies (OTAs) regarding key analytical metrics, including review topics, sentiment and review length on consumer ratings and their implications for research and practice.Design/methodology/approach: Employing a comparative analysis method, this study analyzed over 11,000 user reviews from a premier boutique hotel in China, gathered from three leading Chinese OTAs. It integrated diverse social media analytics techniques, such as Word Cloud analysis, latent Dirichlet allocation (LDA), traditional regression and PLS structural equation modeling multi-group analysis (MGA) to evaluate review characteristics among the OTAs.Findings: The results reveal significant discrepancies in review topics, sentiments, review lengths and their effects on consumer ratings across the OTAs examined. These findings highlight the risks of relying on a solitary data source for making generalizations. To improve the data-driven research’s validity and reliability in hospitality and tourism, the study advises the adoption of multi-source data for a more holistic understanding of consumer sentiments and behaviors.Originality/value: By pointing out the methodological limitations of present hospitality and tourism research, this paper emphasizes the challenges of a single-source data-driven analytical approach. It suggests several avenues for enhancing the reliability and validity of future research in the field, marking a significant contribution to methodological advancements in hospitality and tourism studies.

Metaverse retailing encapsulates commercial endeavors conducted within virtual reality environments online, facilitating comprehensive trading and experiential processes. This definition spans a spectrum of retail activities within the virtual realm, presenting an extension of established e-commerce and social commerce channels. Its potential to profoundly influence metaverse market segmentation, positioning strategies, and target market selection warrants a thorough examination. This chapter endeavors to prospectively explore the realms of branding, channels, and consumer journeys within the landscape of metaverse retailing.

■ Global publications on new retail and new logistics are increasing, highlighting their growing importance, especially in Chinese literature. ■ Collaboration networks among authors and institutions are limited in both Chinese and English literature. ■ Key research areas include innovative sales and logistics strategies, with Chinese literature focusing on technology applications and English literature emphasizing customer satisfaction. ■ Future research should explore green logistics, metaverse-related innovations, and training programs for professionals in new retail and new logistics.