Search results

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 aim of the paper is to discuss the contribution of tourism technologies to Sustainable Development Goal 5 (SDG5), gender equality.

Following a review of the literature on tourism technologies and a consideration of the goals of SDG5, we provide a discussion of the ways in which tourism technologies can support gender equality.

While the tourism industry has potential for the promotion of gender equality, there are policies and research agendas that can be followed that will enable tourism technologies to better support the SDG5 goal.

Tourism, as an industry, can play a vital role in supporting SDG5 by ensuring that women’s voices are present in the management of tourism technologies.

This paper represents a viewpoint of how automation technology applications in tourism can progress towards the SDGs, specifically in regard to gender equality. This analysis shows that there is potential at this point to incorporate women’s perspectives into automation technology applications in tourism in ways to ensure that meaningful contribution is made towards progress in gender equality.

As the Journal of Tourism Futures celebrates its 10th anniversary, Dr. Albert Postma (NHL Stenden University) interviews Professor Ian Yeoman (NHL Stenden University) as co-editor of the Journal of Tourism Futures and expert on scenario planning in tourism and hospitality.

A personal interview.

Yeoman shares his expertise on the establishment and evolution of the Journal of Tourism Futures, in the context of the growth of futures thinking in tourism within a science and industry context.

The interview provides insights in the evolution of futures thinking in tourism, reflected in the growth and growing reputation of the Journal of Tourism Futures.

The paper aims to reveal the intellectual structure of studies on artificial intelligence (AI) in the fields of tourism and hospitality. Evaluations regarding the intellectual structure have been made based on co-author, co-word and citation.

The study is exploratory in nature. The study, using bibliometric analysis, provides a Web of Sciences (WOS) overview. The data has been obtained from the WOS database by coding as “artificial intelligence” and “tourism” and “hospitality.” VOSviewer program has been used to obtain and analyze the data.

The findings of the research show that studies on the use of AI in tourism and hospitality have become very popular, especially in the last 4 years. The authors of the study are working in the tourism and hospitality fields and have a high h-index. Generally, in current AI studies in tourism, topics such as robot, automation, ChatGPT, technology adoption and mechanical learning are studied. It has also been determined that topics related to the future of destinations and literature reviews are also discussed.

Although this paper examines all studies identified as a result of filtering, the analysis is limited to 195 studies. However, due to the widespread use of AI in tourism-related studies recently, bibliometric analysis has been made with extensive filtering. As studies on the subject become more widespread in the coming years, it would be useful to repeat similar studies by filtering with more specific quotas.

There are a few similar studies on the subject in the field. However, these studies need to be repeated at certain periods. This paper contributes to monitoring the literature of AI studies, which are new to use in tourism and hospitality, and to the formation of a theoretical framework on the subject.

The purpose of this study is to reveal the research trends in guest experiences of service robots in the hospitality industry.

In this study, a review was carried out on the Web of Science (WoS) database with the assistance of bibliometric analysis techniques. Cluster analysis was also employed for this to group important data to determine the relationships and to visualize the areas in which the studies are concentrated. The thematic content analysis method was used to reveal on which customer experiences and on which methods the focuses were.

On the subject of experiences of service robots, the greatest number of publications was in 2021. In terms of country, China has come to the fore in the distribution of publications. As a result of thematic content analysis, it was determined that the leading factor was the main dimension of emotional experience. In terms of sub-dimensions, social interactions attracted more attention. Most of the studies discussed were not based on any theory. Apart from these, the Technology Acceptance Model (TAM), the Service Quality Model (SERVQUAL) and Perceived Value Theory (PVT) were featured more prominently among other studies.

In this study, only the WoS database was reviewed. In future studies, it would be possible to make contextual comparisons by scanning other databases. In addition to quantitative research designs, social dimensions may be examined in depth following qualitative research methods. Thus, various comparisons can be made on the subject with mixed-method research designs. Experimental research designs can also be applied to where customers have experienced human-robot interactions (HRIs).

In the hospitality industry, it is critical to uncover every dimension of guests' robot acceptance. This study, which presents the current situation on this basis, guides future projections for the development of guest experiences regarding service robots in the hospitality industry.

This chapter investigates the experiences of doctoral students and supervisors in the doctoral process, focusing on the potential impact of imbalances in the distribution of power. In this respect, there are troublesome manifestations of excessive faculty entitlement that appear to be a source of inequality and injustice. These phenomena call into question the crucial relationship of support expected of doctoral students, as thesis supervisors have a fundamental role to play in guiding them towards the doctorate and ensuring their successful entry into the research community. Looking at the issue from the angle of the theory of social fields, I examine instances of dysfunction in supervisory experiences. Such problematic practices tend to conform to the relationships and traditions that sustain and (re)produce the practices of the academy, constraining the establishment of what Bakhtin describes as a dialogical relationship, between doctoral students and supervisors. I examine this problem from my own experience, both as a doctoral student and as a supervisor. I approach the question by combining self-study and narrative inquiry to make use of the data from my experience to analyse the issues raised during the supervision of doctoral programmes. I connect accounts drawn from literature, real-life testimonies and a corpus of discussions and notes to explore the manifestations of excessive faculty entitlement in the form of asymmetries and difficulties that can negatively impact the quality of supervision.

The multiplicity of the late-night television offer is a recent phenomenon. In the late 1940s, TV was still in its experimental stage and programming was limited to certain hours of the day. How then did late-night evolve from one dominant program to the cornucopia that exists today? To what extent did the progressive fragmentation of the media environment contribute to this exponential growth in late-night programs? To answer these questions, this chapter will look closely at three phases of late-night history: the ascendance of The Tonight Show during the Johnny Carson era, Johnny's succession when two princes vied for his late-night throne, and then finally the latest developments where a new generation of late-night royalty, which I refer to as The House of Stewart, would emerge with a plethora of shows. Simultaneously, this chapter will also delve into the media context during each phase which became increasingly fragmented leading to an explosion of new ways of experiencing television.

The role of customers has moved from reactive to proactive, and they require more control over digital touchpoints. The quest for authenticity is their response to the dark side of interactive marketing – forms of faking, manipulation and exploitation. Authenticity becomes a key topic in interactive marketing as it reflects how customers assess digital touchpoints. However, there is a lack of comprehensive knowledge of authenticity in the interactive environment.

This article consolidates the authenticity studies in various digital touchpoints using the entity-referent correspondence framework. This research employs bibliometric analysis and thematic analysis of 103 articles in the last 15 years.

Five research clusters are identified: (1) human, (2) brand-generated content, (3) user-generated content, (4) branded platforms and (5) new technologies-based touchpoints (artificial intelligence, augmented reality and virtual reality). Most interactive marketing studies focus on human and content authenticity, and new technologies-based touchpoints lack comprehensive conceptualization. The review synthesizes the types of authenticity used in each touchpoint and highlights the importance of true-to-creator-self and true-to-customer-self in customer evaluation. We further propose a research framework with four antecedent groups and outcomes.

Our research supports managers by highlighting the type of authenticity prioritized in each touchpoint's development.

To answer the call from interactive marketing researchers, this research highlights the distinct definitions of authenticity at various digital touchpoints rather than looking at the overall brand. Trends, gaps and future research agenda of the authenticity concept in technology adoption and customer behavior are discussed.

This chapter shifts focus from the underlying causes of offending to current rehabilitation approaches and models. It begins with an overview of the rehabilitation movement, emphasising the principle of ‘what works’ in offender reform. The discussion then moves on to explore two major frameworks: the Risk-Need-Responsivity (RNR) model and the Good Lives Model (GLM). Each model will be briefly outlined and critically evaluated for its effectiveness in preventing re-offending and supporting desistance. The chapter concludes with a rationale for introducing a new approach to rehabilitation, the Compassionate Positive Applied Strengths-based Solutions (COMPASS) model, summarising its potential benefits for enhancing desistance support.