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This paper aims to investigate travelers’ intentions to use ChatGPT and the influential factors affecting their decision-making.

Four studies were conducted to test three hypotheses. Four groups of respondents totaling 593 (Study 1), 337 (Study 2), 374 (Study 3) and 385 (Study 4) survey participants were used for data analyses.

Overall, the findings confirmed the impacts of technology usage experience and ChatGPT’s mistakes and provided additional information on travelers’ intentions to use ChatGPT. The four hypotheses were supported.

The findings can help researchers and industry to understand travelers’ intentions to use ChatGPT and their responses to its functions.

这项研究调查了旅行者使用ChatGPT的意图, 以及影响其决策的重要因素。

通过进行四项研究来验证三个假设。四组受访者总共593名（研究1）、337名（研究2）、374名（研究3）和385名（研究4）参与了数据分析。

总体而言, 研究结果证实了技术使用经验的影响、ChatGPT的错误并提供了有关旅行者使用ChatGPT意图的更多信息。四个假设均得到了支持。

研究结果可以帮助研究人员和业界了解旅行者使用ChatGPT的意图, 以及他们对其功能的反应。

Este trabajo investiga la intención de los viajeros en el uso de ChatGPT y su influencia en el proceso de decisión de viaje de los viajeros.

Se han desarrollado cuatro estudios para probar tres hipótesis. Cuatro grupos de participantes: 593 (Estudio 1), 337 (Estudio 2), 374 (Estudio 3), y 385 (Estudio 4) participantes respondieron la encuesta y sus respuestas utilizadas para el análisis de datos.

En resumen, los resultados confirman el impacto de la experiencia de uso de la tecnología, los errores de ChatGPT, proveyendo información adicional sobre la intención de uso de ChatGPT por los viajeros. Las cuatro hipótesis de investigación fueron aceptadas.

Los resultados pueden ser útiles para la academia y la industria sobre la comprensión en la intención de uso de ChatGPT, tanto por los viajeros, como sus respuestas sobre su función.

While there was heightened awareness on the technologies of the fourth industrial revolution (IR 4.0) prior to COVID-19, studies have shown that the adoption of these advanced technologies (e.g. Big Data, robotics, Internet of Things, etc.) continues to remain low across global industries. This qualitative study sought to explore the reasons for the low rate of adoption of these technologies and appropriate measures to enhance their adoption at hotels, through the lens of hotel executives.

Based on interpretivist's ideals, this study follows a case study design and adopts a qualitative method of enquiry. The heterogenous purposive sampling technique was employed to gather data for the study, using semi-structured interviews.

Grounded on the technology-organisation-environment (TOE) framework, the thematic analysis revealed technology, organisation and environment-related reasons for the low rate of IR 4.0 technologies adoption at hotels in Malaysia. Also, the study uncovered some interesting measures that will enhance the adoption of these advanced technologies at hotels.

This study unearths technology, organisation and environment-related reasons for low adoption, and measures to enhance the adoption of IR 4.0 technologies in hotels. This study also enlightens hotel owners and technology providers about practical issues that will ensure the successful adoption of such technologies to enhance hotel business. In line with SDG 9, this study also seeks to promote sustainable innovation in the hospitality industry. Practical and theoretical implications have also been discussed in this study.

The aim of this mixed methods study sought to investigate the preferences and challenges towards fourth industrial revolution (FIR) technologies adoption at hotels in Malaysia.

The study adopted partially-mixed concurrent quantitative-dominant mixed methods. The quantitative part of the study examined the preferred FIR technologies for hotels; whiles the qualitative part explored the challenges towards their adoption.

The results revealed that Internet of things, big data, cloud computing, artificial intelligence and cyber physical systems were the preferred FIR technologies for hotels. The findings revealed significant relationships between respondents' socio-demographic characteristics (age, gender, working experience, etc.) and preferred FIR technologies. Penultimately, challenges that affect the adoption of FIR technologies including investment cost, migration cost, trust, etc., were discussed.

In effect, findings from this study provide valuable information for policy makers (i.e. hotel owners, management, technology providers and future researchers). Most especially, the study unearths specific FIR technologies preferred by the hospitality and tourism industry. Also, the significant interplay of these preferences vis a vis respondents' socio-demographic characteristics, as well as challenges influencing their adoption also have major implications for policy makers. Another valuable contribution of this study lies in the research method utilised, since most studies on technology adoption either use quantitative or qualitative. These contributions for theory and practice have been thoroughly discussed.

Business model innovation (BMI) plays a key role in accelerating the transition toward greater environmental sustainability in the agri-food industry. However, knowledge of the mechanisms that activate BMI in agri-food firms remains scarce. This study aims to clarify the interdependencies between environmental sustainability and new technologies as drivers of BMI. It explores the relationships between these drivers and the locus (i.e. internal and/or external to the firm) of the stimulus activating BMI.

An in-depth analysis of 13 cases of small- and medium-sized agri-food firms that have successfully introduced BMI is performed, drawing on information collected through interviews with these firms’ decision-makers.

The analysis unveils the mechanisms behind the activation of BMI in agri-food firms. A framework combining the drivers and the locus of BMI is proposed, highlighting BMI paths in agri-food firms.

This study proposes an original framework that outlines three main paths to BMI in agri-food businesses: purpose-driven BMI, technology-exploration-driven BMI and compliance-driven BMI.

In the tourism sector, fully unmanned and partially unmanned hotel models serving customer segments from different income groups are increasing. Analyzing examples of unmanned hotels worldwide and their practices is crucial for understanding the automation systems used, the smart technologies employed, and the opportunities and challenges these hotels present, as well as for gaining insights into their impacts on the tourism sector.

The data used in this research were obtained from secondary sources. One of the qualitative research methods, document analysis, was used for the analysis of these sources. The content analysis technique was used in the analysis of the data. A seven-stage systematic review process was used in the research. This seven-stage review process consists of the following stages: (1) determining the review objectives and formulating research questions; (2) identifying search terms and selection criteria; (3) conducting a search for unmanned hotel applications before clarifying exclusion and inclusion criteria; (4) evaluating the quality and relevance of unmanned hotel applications; (5) identifying content analysis review variables; (6) conducting content analysis; and (7) analyzing and reporting the findings.

In traditional hotel management, the innovations brought by digitalization and automation are transforming the guest experience and increasing operational efficiency. Unmanned smart hotels are equipped with various technological solutions, such as voice-controlled AI assistants, smart room control systems, AI-based concierge services, and robotic room service. These hotels are redefining roles and expectations within traditional hotel management, while simultaneously reducing costs and enhancing efficiency. Analyses indicate that unmanned smart hotels particularly appeal to specific customer segments, such as business travelers, and are becoming increasingly popular. These hotels offer advantages such as allowing guests to perform self-check-in, control their rooms, and receive necessary services via robots.

The universe of the research consists of all currently operating unmanned hotels worldwide. As a result of the research, 18 examples of unmanned smart hotels were identified. Hotels within the same chain with identical applications and processes were considered as a single example. Therefore, the research sample consists of 18 hotels.

By integrating these technological advancements, the hospitality and tourism industries can mitigate the impact of staff shortages, maintain high service standards, and improve operational efficiency. This approach allows businesses to adapt to changing workforce dynamics while continuing to deliver exceptional guest experiences. In conclusion, the significance and impact of unmanned smart hotels in the travel industry are growing. These hotels have the potential to shape the role of technology in the hospitality sector and influence future trends. Therefore, the adoption and development of unmanned smart hotels are important considerations for hotel operators and industry experts.

This study aims to focus on publications that jointly address robots in the tourism field and the technology acceptance model (TAM).

This study adopts bibliometric analysis. Publications listed in the Web of Science database constitute the scope of this research. 51 publications were analyzed within the scope of the research.

Between the years 2017 and 2023, an upward trend in the number and citations of publications was identified. It has been observed that article studies are more prevalent compared to other types of publications. When considering the indexes of the publications, a significant majority were found to be in Social Sciences Citation Index (SSCI) and Science Citation Index (SCI)-EXPANDED. The status of the keywords identified within the scope of the research in the abstracts of the publications has been presented. The keyword “robot” was found to be the most frequently occurring in the abstracts. The abstracts were also analyzed, and the publications were accordingly clustered into five distinct themes.

This study offers a comprehensive evaluation of publications concerning the use of robots in the tourism sector, framed within the context of the TAM. Within the scope of the study, the findings were interpreted using bibliometric analysis. The publications have been categorized into themes. The results presented provide insights into the necessity for further publications in this field.

The study and analysis of airport marketing strategies and the diversification of its activities through strategic alliances are essential for airports, and these should be a priority to plan and develop marketing plans in these times of uncertain economic and pandemic, because the future of the aviation and tourism industries lies in stressing the value of unity between the two sectors. This chapter shows real examples of airport marketing strategies around the world to help airport and airline operators, marketers and destination marketing organisations (DMOs) improve their marketing strategies in a competitive and environmentally sustainable market, as is the case with aviation and tourism activities. Opportunities to develop mutually beneficial relationships in cities between DMOs and airports are plentiful but often largely untapped by both parties due to miscommunication and the common interests of business operators. The marketing strategy of diversification is critical to reviving in times of economic downturn.