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Purpose: The purpose of this chapter is to elaborate on the major conceptual and practical considerations of the use of robots, artificial intelligence and service automation (RAISA) in travel, tourism, and hospitality companies (TTH).

Design/methodology/approach: The chapter develops a conceptual framework of the major issues related to the use of RAISA in the travel, tourism and hospitality context.

Findings: The findings indicate that while there is a creeping incursion of RAISA into TTH, there are major concerns that the TTH industry has to consider in regard to automating TTH services.

Practical implications: In a practical sense, the chapter identifies the decisions that TTH industry professionals need to take when dealing with RAISA technologies. Furthermore, the chapter elaborates on the impacts RAISA have on business operations, marketing management, human resources and financial management of TTH companies. The TTH industry has to adjust its practices and communicate with its workforce in ways as not to increase Luddite tendencies and resistance among employees.

Social implications: The analysis shows that there is an upcoming era in which automation of services will be so advanced that wealthy countries may not need to import labour to make up with its own aging workforce, suggesting that RAISA and its further development has the potential for disrupting society and international relations.

Originality/value: This chapter provides a comprehensive review of the issues related to the use of RAISA in the TTH industry, including the drivers of RAISA adoption in tourism, advantages and disadvantages of RAISA technologies compared to human employees, decisions that managers need to take, and the impacts of RAISA on business processes. It shows how macroenvironmental pressures shape the microeconomic decisions to use RAISA in a TTH context.

The advancement of technology and increased sales of service robots have led to discussions about their usage. Recently, the use of service robots in accommodation businesses has become a topic of examination. This study aims to explore the behavioural intentions of accommodation business managers towards using service robots from the perspective of the technology acceptance model. As part of this project-supported study, the ‘Sanbot Elf’ service robot was rented for 14 days and demonstrated in six accommodation businesses in Kastamonu. Semi-structured interviews were conducted with managers and unit supervisors after the demonstration, and the process was also monitored through participant observation. The data were analysed using content analysis and participant observation methods. It was determined that participants' opinions on service robots were generally positive. Participants stated that personalised service presentations could be provided with service robots and that these robots could be used in different departments and marketing processes. The study concluded that service robots could positively impact service quality, are an exciting technology for accommodation businesses and the use of service robots could increase in the future. Participants' attitudes towards using service robots in accommodation businesses were positive in this context.

Purpose: The research investigates the presence of technology ideologies in consumer discourse on tourism and hospitality robots.

Design/methodology/approach: Using a netnographic approach, the research involved immersion in online discourses and collection of consumer posts from a variety of social media platforms. Data was subjected to a thematic analysis informed by the technology ideology framework described in the literature review.

Findings: Online consumer narratives about tourism and hospitality robots are dynamic and varied and reveal a multitude of technology ideology-related positions. The research confirms the applicability of the technology ideology framework to online discourses on service robots and finds that anthropomorphism triggers additional concerns.

Research implications: The findings suggest that future research on the acceptance and use of service robots should go beyond psychological concepts.

Practical implications: Without uncovering and understanding technology sensemaking processes with respect to service robots, the introduction of service robots in hospitality and tourism might trigger consumer resistance or lead to inferior service experiences.

Social implications: The research suggests that sensemaking of technology, specifically service robots, is complex and colored by pertinent ideologies. Policies and regulations regarding service robot adoption and implementation should consider these various positions.

Originality/value: The paper introduces technology sensemaking and technology ideology as important theoretical frameworks to understand consumer perceptions, attitudes, uses and relationships in regard to service robots in hospitality and tourism contexts.

Purpose: The goal of the chapter is to define customer attitudes towards robots in travel, tourism and hospitality (TTH) and to analyse their most significant characteristics.

Design/methodology/approach: The book chapter develops a conceptual framework of attitudes towards robots in travel, tourism and hospitality, based on critical analysis of relevant publications.

Findings: The chapter provides a definition and discussion of the characteristics of customer attitudes towards robots in TTH. It elaborates the structural elements of attitudes towards robots, and the links and interactions between the elements.

Research limitations: Research limitations stem from the small number of studies on customer attitudes towards robots in TTH.

Practical implications: The theoretical analysis can be used as a starting point for empirical studies of customer attitudes towards robots in travel, tourism and hospitality.

Social implication: Combined services, based on human employee-service robot collaboration, are the optimal decision for forming favourable customer attitudes towards robotisation and automation in tourism and hospitality. In that way clients’ needs of high technological convenience, interpersonal communication and socialisation are met simultaneously.

Originality/value: This research is among the few publications that study customer attitudes towards robots in travel, tourism and hospitality. The authors develop a matrix of users’ attitudes and behaviours when using robots in travel, tourism and hospitality.

The gastronomy industry is one of the industries in which consumers use technology most frequently, such as robotics, artificial intelligence and automation systems. Service robots are generally defined as online programs that can act independently or under the control of a human that can carry human characteristics such as speaking, understanding and acting. This study aims to examine and evaluate the studies on service robots in the gastronomy industry regarding quantity or quality, to understand the phenomenon more comprehensively, and to determine a holistic perspective. To this end, a qualitative research approach was adopted. Document technique was used to collect data within a systematic literature review framework, and the data were analysed by descriptive analysis. According to the findings, the papers on service robots in the gastronomy industry are still in their infancy, and these studies have increasingly gained speed in the last five years.

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.

Purpose – The purpose of this chapter is to conduct a critical literature review that examines the origins and development of research on service robots in organizations, as well as the key emotional and cognitive issues between service employees, customers, and robots. This review provides a foundation for future research that leverages the emotional connection between service robots and humans.

Design/Methodology/Approach – A critical literature review that examines robotics, artificial intelligence, emotions, approach/avoid behavior, and cognitive biases is conducted.

Findings – This research provides six key themes that emerge from the current state of research in the field of service robotics with 14 accompanying research questions forming the basis of a research agenda. The themes presented are as follows: Theme 1: Employees have a forgotten “dual role”; Theme 2: The influence of groups is neglected; Theme 3: Opposing emotions lead to uncertain outcomes; Theme 4: We know how robots influence engagement, but not experience; Theme 5: Trust is necessary but poorly understood; and Theme 6: Bias is contagious: if the human mind is irrational…so too are robot minds.

Practical Implications – Practically, this research provides guidance for researchers and practitioners alike regarding the current state of research, gaps, and future directions. Importantly for practitioners, it sheds light on themes in the use of AI and robotics in services, highlighting opportunities to consider the dual role of the employee, examines how incorporating a service robot influences all levels of the organization, addresses motivational conflicts for employees and customers, explores how service robots influence the whole customer experience and how trust is formed, and how we are (often inadvertently) creating biased robots.

Purpose: The information-intensive nature of the tourism and hospitality industry requires regular communication between firms and customers. Yet, customer service personnel’s high contact levels with customers often lead to customer dissatisfaction arising from embarrassment in emotion-inducing service encounters. Accordingly, such companies have been seeking a cost-effective means of maintaining consistency in customer contact. Thus, it seems that the future of chatbots is here.

Design/methodology/approach: This chapter examines chatbots in two ways: the technical composition and its adoption by tourism firms. The technical perspective is represented by a diagram which espouses the functioning of chatbots from inputs query to output reply. On its adoption by tourism firms, two main organizational theories were proposed.

Findings: While chatbots are diffusing rapidly in other areas, their use in the tourism and hospitality industry remains low. We have examined the role of chatbots in various areas of the tourism and hospitality industry and highlighted the barriers to their successful adoption. By applying a conceptual and theoretical approach, our study used a hybrid of institutional theory and organizational learning theory and diagrammatically espouses how the integration of these theories can aid subsequent studies to understand the environmental and organization-specific factors influencing chatbots adoption.

Research limitations/implications: This study is conceptual, consequently, we recommend future studies to empirical test and validate our proposed conceptual framework.

Originality/value: This study is one of the earliest studies that advances firm-level adoption of chatbots by integrating two key organizational theories.