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Artificial Intelligence (AI) has revolutionised the tourism industry, offering personalised experiences and streamlining operations. AI provides customised recommendations for travellers through data analysis and machine learning, making their journeys more meaningful. It has also improved efficiency through automated processes, chatbots and enhanced security measures. AI's ability to analyse large volumes of data enables tourism organisations to make data-driven decisions and target their marketing strategies effectively. One of the most notable contributions of AI in tourism is its ability to offer personalised recommendations. By analysing vast travel history, preferences and online behaviour, AI systems can provide tailored suggestions for destinations, accommodations, activities and dining options. This level of customisation enhances the overall travel experience, making it more relevant and satisfying for individual travellers. AI has also greatly improved operational efficiency within the tourism sector. Chatbots, powered by natural language processing, are increasingly being deployed by hotels, airlines and travel agencies to provide instant customer support and assistance. These chatbots can answer queries, offer recommendations and handle booking processes, reducing waiting times and enhancing customer satisfaction. In addition, facial recognition technology allows for quick and accurate identity verification at airports, hotels and other travel-related facilities. This improves security and provides travellers with a seamless and efficient experience. As technology advances, we expect AI to play a more prominent role in augmented reality, voice recognition and virtual assistants, further enhancing the travel experience and facilitating seamless interactions. In conclusion, AI has transformed the tourism industry by providing personalised recommendations, improving operational efficiency, enhancing security measures and enabling data-driven destination management.

The purpose of this study is to provide insights and guidance for practitioners in terms of ensuring rigorous ethical and moral conduct in artificial intelligence (AI) hiring and implementation.

The research employed two experimental designs and one pilot study to investigate the ethical and moral implications of different levels of AI implementation in the hospitality industry, the intersection of self-congruency and ethical considerations when AI replaces human service providers and the impact of psychological distance associated with AI on individuals' ethical and moral considerations. These research methods included surveys and experimental manipulations to gather and analyze relevant data.

Findings provide valuable insights into the ethical and moral dimensions of AI implementation, the influence of self-congruency on ethical considerations and the role of psychological distance in individuals’ ethical evaluations. They contribute to the development of guidelines and practices for the responsible and ethical implementation of AI in various industries, including the hospitality sector.

The study highlights the importance of exercising rigorous ethical-moral AI hiring and implementation practices to ensure AI principles and enforcement operations in the restaurant industry. It provides practitioners with useful insights into how AI-robotization can improve ethical and moral standards.

The study contributes to the literature by providing insights into the ethical and moral implications of AI service robots in the hospitality industry. Additionally, the study explores the relationship between psychological distance and acceptance of AI-intervened service, which has not been extensively studied in the literature.

This study investigates how artificial intelligence (AI) chatbots persuade customers to accept their recommendations in the online shopping context.

Drawing on the elaboration likelihood model, this study establishes a research model to reveal the antecedents and internal mechanisms of customers' adoption of AI chatbot recommendations. The authors tested the model with survey data from 530 AI chatbot users.

The results show that in the AI chatbot recommendation adoption process, central and peripheral cues significantly affected a customer's intention to adopt an AI chatbot's recommendation, and a customer's cognitive and emotional trust in the AI chatbot mediated the relationships. Moreover, a customer's mind perception of the AI chatbot, including perceived agency and perceived experience, moderated the central and peripheral paths, respectively.

This study has theoretical and practical implications for AI chatbot designers and provides management insights for practitioners to enhance a customer's intention to adopt an AI chatbot's recommendation.

1. The study investigates customers' adoption of AI chatbots' recommendation.

2. The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

3. The central and peripheral cues are generalized according to cooperative principle theory.

4. Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

5. Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

6. Customers' mind perception positively moderates the central and peripheral paths.

The study investigates customers' adoption of AI chatbots' recommendation.

The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

The central and peripheral cues are generalized according to cooperative principle theory.

Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

Customers' mind perception positively moderates the central and peripheral paths.

Innovation originally meant ‘change’ or ‘renewal’. Over time, it became associated with creating new products, methods, materials, markets, and forms of organisation. Today, in everyday language, innovation is used as a much broader term that encompasses non-materialistic, non-economical ideas such as social, educational, philosophical, political, environmental, or spiritual innovations. What makes something innovative is subjective and depends not only on the perceived novelty of the content but also on the co-constructed meaning of what is possible or what it changes in our lives. Therefore, innovation leaders must also become experts in co-constructing meanings with their teams. In this chapter, a structured solution-focused framework will be introduced with the intent to support innovative teams in maintaining effective team dialogue, foster more innovative team collaboration, better innovations, or an improved innovation process. In fostering an interactive and dynamic team process, solution-focused leaders engage in deliberate interactions that often initiate a positive dynamic leading into an even more innovative future.

Psychological ownership has been a topic of intense debate for several decades, especially in the digital era. In addition, as part of the digital public domain, virtual communities shape our digital lives. Unfortunately, few studies have examined the communication process in virtual communities from the perspective of psychological ownership. Moreover, information and organization are key aspects of virtual communities. This research aimed to explore the impact of psychological ownership on communication satisfaction from these two perspectives.

I collected 471 responses using a questionnaire. In terms of empirical methods, I developed a structural equation model (SEM) to examine the relationship between psychological ownership and communication satisfaction as well as the mechanism underlying this relationship – namely, information behavior. Specifically, I first examined the relationship between psychological ownership and information behavior. I then developed a comprehensive framework for the double-edged impact of psychological ownership in virtual communities on communication satisfaction.

I found that psychological ownership has a double-edged effect on communication satisfaction based on two types of information behavior in virtual communities. Specifically, organization-based psychological ownership (OPO) positively influences communication satisfaction through information exchange. In contrast, information-based psychological ownership (IPO) negatively impacts communication satisfaction through information-hiding.

The findings of this research demonstrate that psychological ownership has a double-edged effect on communication satisfaction. First, the findings of this study reveal the downsides of psychological ownership, which are not consistent with its beneficial role. Second, the negative effect of psychological ownership with regard to communication in virtual communities also helps explain communication failure in virtual communities. Finally, despite the downsides of psychological ownership in the context of a virtual community revealed by this study, this factor has an overall beneficial effect.