This study investigates how anthropomorphic language and chatbot schema (a customer’s cognitive framework for understanding and interacting with a chatbot) jointly influence customer electronic word-of-mouth (eWOM). Across two experiments, we examine how anthropomorphic language (such as empathetic language and emojis) impacts customers’ engagement with chatbots. Study 1 provides directional evidence suggesting that anthropomorphic language is associated with greater eWOM when a chatbot schema was active, but not when it is inactive. Study 2 demonstrates that the effects of anthropomorphic language on authenticity and eWOM are contingent on the chatbot’s competence. Together, these findings suggest that linguistic cues may improve chatbot interactions, beyond their visual appearance. This research has implications for marketing practitioners, helping them to formulate effective strategies based on chatbot disclosure and competence.
This study examines how 360-degree (vs. traditional) videos influence social media word-of-mouth (WOM) intention in the luxury hospitality sector. Across four studies, results show that 360-degree videos outperform traditional formats, with telepresence and luxury experience explaining this effect through a sequential process. Drawing on the Stimulus-Organism-Response (S-O-R) framework and Feelings-as-Information Theory, the study provides a clearer theoretical explanation of how 360-degree video formats influence social media WOM intention in the luxury hospitality context through consumers’ psychological responses. Further, it reveals how the presence or absence of haptic instructions, together with hedonic value, shapes social media WOM intention. The findings reveal that hedonic value and haptic instructions strengthen the indirect relationship between 360-degree video and social media WOM intention, via luxury experience only. The findings provide several actionable insights for luxury hotel managers and digital marketers aiming to enhance social media WOM intention through 360-degree content strategies.
The rapid digitalization of organizations has transformed how knowledge is created, shared, and leveraged to enhance both customer experience (CX) and employee experience (EX). Advances in artificial intelligence (AI), analytics, automation, and digital platforms have increased opportunities for a technologically-mediated knowledge exchange, creating new pathways for value creation while simultaneously introducing challenges for organizations seeking to balance employee and customer needs. Despite growing scholarly interest in CX, EX, knowledge management, and digital transformation, these streams of research have largely developed in parallel, resulting in limited understanding of their interrelationships. This research paper introduces the Special Issue on Enhancing Customer and Employee Experience in Digital Enterprises through Technologically Mediated Knowledge Exchange. To contextualize the contributions of the Special Issue, we conduct a bibliometric review and analysis of 1,132 publications published between 1988 and 2025. The analysis identifies six major research themes: (1) organizational knowledge and performance, (2) AI-enabled learning and knowledge systems, (3) information systems and customer-centric applications, (4) digital transformation in enterprises, (5) customer relationships and social analytics, and (6) human and workplace factors. The findings reveal a significant shift from traditional knowledge management and information systems perspectives towards AI-enabled, AI-mediated, data-driven, and experience-oriented research. However, the field remains fragmented, with limited integration across technological, organizational, employee, and customer perspectives. Building on these insights, we synthesize existing research to develop an integrated framework linking technologically mediated knowledge dynamics, EX, and CX. We also introduce the articles included in this Special Issue and highlight their contributions to advancing our understanding of how technologically-mediated knowledge exchange shapes customer and employee outcomes in digital enterprises, including CX and EX, a core focus of the SI. This paper conclude by proposing a future research agenda that encourages greater theoretical integration and interdisciplinary collaboration to advance research on CX, EX, and knowledge exchange in the era of artificial intelligence.
As firms increasingly deploy artificial intelligence (AI) to navigate complex market environments, understanding how AI-powered data capabilities shape outside-in marketing processes has become theoretically consequential. Employing a qualitative design with in-depth interviews across diverse industries, organizational sizes, and geographic contexts, this study addresses the knowledge gap. Grounded on the Resource-Based View, Dynamic Capabilities perspective, and Relational View, we develop an integrative framework of AI-powered data capabilities with two core dimensions (AI intelligence and AI action). Research findings clarify how these capabilities enable market sensing, customer profiling, customer linking, and partner bonding. Based on this framework, AI-powered data capabilities are adaptive, relational, and ecosystem-enabling dynamic capabilities, rather than static strategic resources. The study also reveals four boundary conditions that moderate the impacts of AI-powered data capabilities: regulatory constraints, the ripple effects of privacy initiatives, social privacy sentiments, and AI interoperability. These findings offer both theoretical advancement and practical guidance for AI-powered marketing strategy.
E-commerce is critical for managing increased customer demand and maintaining operational efficiency during disruptions such as natural disasters, health crises, and political instability. Despite this, little is known about how crisis-driven market changes influence dynamic capabilities, technology adoption, and customer experience (CX). This study provides insights into how e-tailers can leverage technology to enhance the CX for first-time online shoppers (FTOS). Given the limited literature on FTOS, which differs from repurchasers, three studies were conducted using a multi-method approach. Study 1 involved an environmental scan of 109 news articles and journal papers for practical insights. Study 2 consisted of in-depth interviews (IDIs) with senior managers working full-time for e-tailers, while Study 3 involved IDIs with FTOS. Findings reveal that e-tailers adapt to crises by leveraging technology to bridge demand–supply gaps through dynamic demand forecasting and improved last-mile delivery. They also use advanced technologies to provide personalised and immersive experiences, helping narrow the gap between offline and online shopping for FTOS. This study contributes to theory with a conceptual framework, with empirically grounded, theory-informed propositions linked to the Resource-Based Theory (RBT) and CXM frameworks, to explore how e-tailers leverage crisis-led capabilities to enhance FTOS experience. It conceptualises a new understanding of how e-tailers adapt to enhance FTOS CX amidst crises which can serve as a springboard for future research. The insights from an empirically grounded conceptual framework and propositions, offer managerial implications for e-tailers and other service providers.
