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By focusing on Sustainable Development Goal 12 (SDG 12) and tourism automation, this perspective paper aims to investigate how tourism and automation will work to create a world in which tourism has more sustainable production and consumption patterns.

This perspective paper reviews the past developments of automation in tourism in the context of sustainable production and consumption patterns, the lessons learned from the COVID-19 pandemic and looks at the future of tourism and how automation will help it be more sustainable in terms of consumption and production patterns.

The insights from this analysis suggest that automation technologies will play a major role in both the supply and demand sides of the tourism and hospitality industry, encouraging increased tourism sustainability. While automation technologies will have the greatest impact on the supply side in the near future, as such technologies will be used to minimise waste and energy usage, creating large gains for environmental protection, the technologies will also benefit responsible consumption. Big data and analytical technologies will work in ways to ensure that consumers are nudged into consumer practices that are increasingly sustainable.

This perspective paper synthesises the literature on the subjects, namely, automation and SDG 12 in tourism, and points to important new future research agenda. This is one of the first papers in tourism to blend automation and SDG 12 literature to shed light on the use of automation in sustainable consumption and production in tourism.

通过聚焦于可持续发展目标12和旅游自动化, 本前瞻性文章旨在探讨旅游业和自动化如何共同创造一个让旅游产业拥有更可持续的生产和消费模式的世界。

本文回顾了旅游自动化在可持续生产和消费模式背景下的发展, 从COVID-19大流行中学到的教训, 并展望旅游业的未来以及自动化如何帮助其在消费和生产模式方面变得更加可持续。

根据分析, 自动化技术将在旅游和酒店业的供求两侧发挥重要作用, 促进旅游业的可持续性发展。虽然自动化技术在近期内将对供应侧产生最大影响, 因为这些技术将被用来最小化废物和能源使用, 为环境保护创造巨大收益, 但这些技术也将惠及负责任消费。大数据和分析技术将以确保消费者被引导向越来越可持续的消费实践。

本前瞻性论文综合了关于旅游中的自动化和可持续发展目标12的文献, 并指出了重要的新的未来研究议程。这是旅游业中第一批结合自动化和可持终发展目标12文献以阐明旅游中可持续消费和生产的自动化使用的论文之一。

Al centrarse en el ODS12 y la automatización del turismo, este artículo de perspectiva pretende investigar cómo el turismo y la automatización trabajarán para crear un mundo en el que el turismo tenga unos patrones de producción y consumo más sostenibles.

Este artículo de perspectiva revisa los desarrollos pasados de la automatización en el turismo en el contexto de los patrones de producción y consumo sostenibles, las lecciones aprendidas de la pandemia COVID-19, y examina el futuro del turismo y cómo la automatización le ayudará a ser más sostenible en términos de patrones de consumo y producción.

Las conclusiones de este análisis sugieren que las tecnologías de automatización desempeñarán un papel importante tanto en la oferta como en la demanda de la industria del turismo y la hotelería, fomentando una mayor sostenibilidad del turismo. Mientras que las tecnologías de automatización tendrán el mayor impacto en el lado de la oferta en un futuro próximo, ya que dichas tecnologías se utilizarán para minimizar los residuos y el uso de energía, creando grandes ganancias para la protección del medio ambiente, las tecnologías también beneficiarán al consumo responsable. Los macrodatos y las tecnologías analíticas funcionarán de manera que se incite a los consumidores a adoptar prácticas de consumo cada vez más sostenibles.

Este documento de perspectiva sintetiza la bibliografía sobre los temas, a saber, la automatización y el ODS12 en el turismo, y apunta a una nueva e importante agenda de investigación futura. Se trata de uno de los primeros trabajos sobre turismo que combina la literatura sobre automatización y ODS12 para arrojar luz sobre el uso de la automatización en el consumo y la producción sostenibles en el turismo.

The rapid growth of artificial intelligence is disrupting various industries, including the tourism sector. This paper aims to outline the applications, benefits and risks of ChatGPT and large language models in general on tourism. It also aims to establish a research agenda for investigating the implications of these models in tourism.

Drawing on the available literature on ChatGPT, large language models and artificial intelligence, the paper identifies areas of application of ChatGPT for several tourism stakeholders. Potential benefits and risks are then considered.

ChatGPT and other similar models are likely to have a profound impact on several tourism processes. They will contribute to further streamline customer service in front-of-house operations and increase productivity and efficiency in back-of-house operations. Although negative consequences for human resources are expected, this technology mostly enhances tourism employees.

To the best of the authors’ knowledge, this is one of the first studies that explore the potential implications of ChatGPT in tourism and hospitality.

人工智能的快速发展正在颠覆包括旅游业在内的各个行业。 本文旨在概述ChatGPT和大型语言模型在旅游业中的应用、好处和风险。同时, 旨在建立一个研究议程, 以调查这些模型在旅游业中的影响。

本文借鉴了关于ChatGPT、大型语言模型和人工智能的现有文献, 确定了ChatGPT在几个旅游利益相关者中的应用范围, 然后考虑了潜在的好处和风险。

ChatGPT和其他类似的模型可能会对一些旅游过程产生深远的影响。它们将有助于进一步简化前台业务的客户服务, 并提高后台业务的生产力和效率。虽然对人力资源的负面影响是可以预见的, 但这项技术主要是增强旅游业的员工能力。

这是首批探索ChatGPT在旅游业和酒店业潜在影响的研究之一。

A partir de la bibliografía disponible sobre ChatGPT, grandes modelos lingüísticos e inteligencia artificial, este artículo identifica las posibles áreas de aplicación de ChatGPT y actores que se pueden beneficiar. De igual forma, se examinan los posibles beneficios y riesgos.

El rápido crecimiento de la inteligencia artificial está afectando diversas industrias, incluyendo la del turismo. Este artículo pretende esbozar las aplicaciones, ventajas y riesgos de ChatGPT, así como los grandes modelos lingüísticos, en turismo. También pretende establecer una agenda de investigación para estudiar las implicaciones de estos modelos en el turismo.

Es probable que ChatGPT y otros modelos similares tengan un profundo impacto en varios procesos turísticos, contribuyendo a racionalizar, aún más, el servicio al cliente en las operaciones de front-of-the-house y aumentando la productividad y eficiencia en el back-of-the-house. Aunque se prevén consecuencias negativas para los recursos humanos, esta tecnología servirá sobre todo para potenciarlos.

Éste es uno de los primeros estudios que exploran las implicaciones potenciales de ChatGPT en el turismo y la hostelería.

Despite ongoing reports of insider-driven leakage of confidential data, both academic scholars and practitioners tend to focus on external threats and favour information technology (IT)-centric solutions to secure and strengthen their information security ecosystem. Unfortunately, they pay little attention to human resource management (HRM) solutions. This paper aims to address this gap and proposes an actionable human resource (HR)-centric and artificial intelligence (AI)-driven framework.

The paper highlights the dangers posed by insider threats and presents key findings from a Leximancer-based analysis of a rapid literature review on the role, nature and contribution of HRM for information security, especially in addressing insider threats. The study also discusses the limitations of these solutions and proposes an HR-in-the-loop model, driven by AI and machine learning to mitigate these limitations.

The paper argues that AI promises to offer many HRM-centric opportunities to fortify the information security architecture if used strategically and intelligently. The HR-in-the-loop model can ensure that the human factors are considered when designing information security solutions. By combining AI and machine learning with human expertise, this model can provide an effective and comprehensive approach to addressing insider threats.

The paper fills the research gap on the critical role of HR in securing and strengthening information security. It makes further contribution in identifying the limitations of HRM solutions in info security and how AI and machine learning can be leveraged to address these limitations to some extent.

Drawing on person–environment fit theory, this study aims to investigate how the relationships between service task types (i.e. utilitarian and hedonic service tasks) and perceived authenticity (i.e. service and brand authenticity) differ under different conditions of service providers (human employee vs service robot). This study further examines whether customers’ stereotypes toward service robots (competence vs warmth) moderate the relationship between service types and perceived authenticity.

Using a 2 × 2 between-subjects experimental design, Study 1 examines a casual restaurant, whereas Study 2 assesses a theme park restaurant. Analysis of covariance and PROCESS are used to analyze the data.

Both studies reveal that human service providers in hedonic services positively affect service and brand authenticity more than robotic employees. Additionally, the robot competence stereotype moderates the relationship between hedonic services, service and brand authenticity, whereas the robot warmth stereotype moderates the relationship between hedonic services and brand authenticity in Study 2.

Restaurant managers need to understand which functions and types of service outlets are best suited for service robots in different service contexts. Robot–environment fit should be considered when developers design and managers select robots for their restaurants.

This study blazes a new theoretical trail of service robot research to systematically propose customer experiences with different service types by drawing upon person–environment fit theory and examining the moderating role of customers’ stereotypes toward service robots.