The growing attention paid to industrial tourism can be seen as one of the major trends in cultural tourism and marketing and has given currency to the proposition that customer experience of industrial tourism acts as a direct personal source of information about their perceptions of companies visited and is essential for customer relationship management of companies. This study applies the service theater theory and proposes a model to explore the structural relationships among theatrical elements of industrial tourism (including setting, performance, and actor), the dimensions of customer experience (enjoyment, learning, and escape), and customers’ behavior intentions. A survey of 500 industrial tourists in a transparent factory in the health food industry was conducted in Zhuhai, Guangdong, China. The results of structural equation modeling indicate that two theatrical factors (setting and performance) relate positively to all dimensions of customer experiences. In contrast, the theatrical factor “actor” only relates positively to the learning experience. Furthermore, all dimensions of customer experience, in turn, positively affect customers’ behavioral intentions. This study will be helpful for corporate managers and tourism organizers who aim to develop and implement marketing strategies based on the service theatre theory to improve their services.

In recent times, there has been a surge of interest in the transformative potential of artificial intelligence (AI), particularly within the realm of online advertising. This research focuses on the critical examination of AI’s role in enhancing customer experience (CX) across diverse business applications. The aim is to identify key themes, assess the impact of AI-powered CX initiatives, and highlight directions for future research. Employing a systematic and comprehensive approach, the study analyzes academic publications, industry reports, and case studies to extract theoretical frameworks, empirical findings, and practical insights. The findings underscore a significant transformation catalyzed by AI integration into Customer Relationship Management (CRM). AI enables personalized interactions, fortifies customer engagement through interactive agents, provides data-driven insights, and empowers informed decision-making throughout the customer journey. Four central themes emerge: personalized service, enhanced engagement, data-driven strategy, and intelligent decision-making. However, challenges such as data privacy concerns, ethical considerations, and potential negative experiences with poorly implemented AI persist. This article contributes significantly to the discourse on AI in CRM by synthesizing the current state, exploring key themes, and suggesting research avenues. It advocates for responsible AI implementation, emphasizing ethical considerations and guiding organizations in navigating opportunities and challenges.

The emerging growth digital application has driven ecosystems integrating digital banks and e-commerce platforms, enabling seamless, efficient transactions. This study examines the impact of user experience and satisfaction on reuse intention in this integrated environment. Using a mixed-method approach, data were collected through surveys of 471 respondents and interviews with 30 participants. Quantitative data were analyzed using structural equation modeling, while qualitative data were processed through content analysis. Results show that perceived ease of use, usefulness, reliability, value, and risk significantly affect user experience, while perceived security does not. These findings aim to help digital banks and e-commerce platforms design effective CRM strategies to enhance satisfaction and reuse intention.