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Web 2.0 applications enable travelers to evaluate several services and assessment attributes. Constructed websites in several languages trigger a new way of data collections resulting in data streams leading to the accumulation of vast amounts of data, called big data. The need for analysis is in high demand. This study aims to construct a model to investigate which single attribute or interrelated ones having an impact on the performances of hotels.

The total number of 1,137 observations collected from the website HolidayCheck.de are used from the hotels in the Bavaria region in 2016. Bavaria is a region where both domestic and foreign travelers mostly prefer to visit. Fuzzy rule-based systems, which is a combination of fuzzy set theory (FST) and fuzzy logic, are used. Although the FST is used to convert linguistically expressed perceptions by travelers into mathematically usable data, fuzzy logic is used to construct a model between service attributes and price-performance (PP) to attain the set of single and interrelated attributes on the assessment of PP.

No single attribute plays a key role in PP assessment. However, two or more interrelated combinations have different impacts on PP. For example, when “Food—Drink” and “Room” moves together from average to good level, PP reaches the highest level of assessment.

Accessibility to too much data is difficult.

A model can be continuously run so that any changes can be observed during the incoming of data.

As the consumer reviews and ratings are the crucial source of information for other travelers, hoteliers must monitor and respond them on time in order to deal with the complaints.

Travelers’ perceptions or evaluations are treated with a FST that measures the impression of human beings. New modeling enables researchers to observe not only any single attribute but also interrelated ones on the PP.

The purpose of this theme issue is to explore the enduring changes and innovations shaping the future of the event industry in the post-pandemic world. While much of the existing literature focuses on the immediate impacts of COVID-19, this issue aims to provide a comprehensive analysis of the broader transformations, including the integration of sustainability, emerging technologies, and evolving event formats.

The theme issue encompasses a range of methodologies, including systematic reviews, bibliometric analyses, and in-depth case studies. The papers examine various aspects of the event industry, such as the adoption of hybrid event formats, the role of new technologies, and the importance of sustainability in event planning. Each paper contributes unique insights into the future direction of the industry by analyzing trends, technologies, and practices that are defining the next era of event management.

The findings highlight a significant shift in the event industry towards sustainability, with an increasing emphasis on eco-friendly practices, waste reduction, and the use of sustainable materials. Emerging technologies are also transforming the landscape, enabling more personalized and immersive event experiences. The rise of hybrid and micro-events is identified as a key trend, providing flexibility and inclusivity while maintaining the benefits of in-person interactions. These developments suggest a permanent change in consumer expectations and engagement strategies within the event industry.

This theme issue offers a holistic analysis of the innovative practices, technologies, and trends that are defining the future of the event industry. By bridging the gap between immediate pandemic responses and long-term industry transformations, it provides valuable insights for academics, practitioners, and policymakers looking to navigate the next era of event management.

This study aims to investigate the effects of smart tourism technology experience (STTE) on tourist satisfaction and happiness in Bordeaux, with a focus on understanding the mediating role of self-gratification. By examining these relationships, the study seeks to provide insights into how smart tourism technologies can enhance tourist experiences.

The study uses partial least squares-structural equation modeling (PLS-SEM) to analyze data collected from 380 tourists who visited Bordeaux. The measurement model assesses reliability and validity, while the structural model evaluates the proposed hypotheses and the mediation effects of self-gratification.

The results confirm that STTE positively impacts tourist satisfaction, with accessibility, informativeness and personalization significantly enhancing tourist satisfaction, while interactivity does not. Tourist satisfaction, in turn, positively affects tourist happiness. Furthermore, self-gratification partially mediates the relationship between tourist satisfaction and happiness, highlighting its importance in the smart tourism context.

This research extends the understanding of STTE by demonstrating its effects on tourist satisfaction and happiness. It introduces the mediating role of self-gratification, providing a novel perspective on how personalized smart tourism experiences contribute to overall tourist happiness.

This theme issue aims to explore the depth and breadth of automation and artificial intelligence’s (AI’s) impact on the hospitality and tourism industry.

The thematic examination of the articles presented in this theme issue highlights the central results concerning the strategic inquiry, especially regarding their addition to knowledge, which is vital for fostering idea creation and theoretical research beneficial to various stakeholders in the tourism and hospitality sector. Given the swift evolution of these technologies, grasping their utilization, advantages and obstacles is essential for industry experts, decision-makers and scholars.

This theme issue encapsulates the transformative impact of automation and AI in the tourism and hospitality industry, highlighting the juxtaposition of enhanced operational efficiency against employment security concerns. It emphasizes the need for ethical governance to address AI’s ethical dilemmas and security vulnerabilities. The exploration of consumer attitudes towards AI, particularly in service robots and facial emotion recognition technologies, is deemed crucial for leveraging AI’s full potential in service delivery. Furthermore, AI’s entry into gastronomy prompts a reevaluation of traditional culinary practices, advocating for a balance between technological innovation and the preservation of cultural heritage.

This theme issue stands out for its focused exploration of the transformative effects of automation and AI within the hospitality and tourism industry. Unlike broader discussions on technology in business, it delves into specific AI-driven innovations, operational changes and the resultant shifts in consumer behavior and industry standards. By curating a collection of empirical research, theoretical analyses and content analyses, this issue is providing important insights into how automation and AI are reshaping service delivery, management practices and strategic decision-making in an industry characterized by its intense customer focus and reliance on human-to-human interaction.

The purpose of this study was to explore the relative importance of various attributes (i.e. the total cost of attending, conference organizer, publishing opportunities for an academic career and personal development, reputation as measured by the number of conferences held, location and size) in terms of their ability to impact the decision of attendees in their selection of which academic conference to attend.

Conjoint analysis was used to examine the relative importance of various attributes to impact an attendee’s decision to select an academic conference (i.e. the total cost of attending, conference organizer, publishing opportunities for an academic career and personal development, reputation as measured by the number of conferences held, location and size).

The choice-based conjoint analysis revealed that the most crucial attributes for attending an academic conference were the total cost of attending the conference (28% of relative importance) and the conference organizer (28%).

Since the total cost of attending a conference is one of the top two attributes, conference organizers should reduce the costs as much as possible. Recommendations include choosing a university venue instead of a hotel or conference center and offering multiple options for registration passes (i.e. one-day pass). However, organizers should be careful about meals provided during the conference program, as meals have a positive effect on attendees’ decisions.

This study introduces to the literature a new indicator for selecting an academic conference – the reputation of the conference as measured by the number of times it had been held. In previous studies, this variable was not considered in the context of selecting an academic conference.

Fuzzy rule-based system (FRBS), a soft computing method used for big data analysis, is used to determine which single hotel attribute or interrelated hotel attributes used in Travel 2.0 data play a role on price–performance (PP).

FRBS, based on fuzzy set theory, is used using the data set of four- and five-star hotels in the Alanya destination in Turkey collected from HolidayCheck.de website for the period between 2009 and 2016.

Single attributes do not have an impact on PP. At least two or more attributes are necessary to have an impact on PP. Compensations among attributes that are observed to be leading to PP not to change from their current level. Instead of assuming a linear relationship between hotel attributes and PP, non-linearity should often be assumed. In addition, some hotel attributes do not have an impact on PP until some other attribute reaches a certain level.

The limitations of this research can be grouped under two topics. While the first is related to data, which is German-speaking tourists staying at four- and five-star hotels between 2009 and 2016, the second is the limitation on generalizability. By implementing other types of data related to hotel attributes, new insights can be generated to shed light on different aspects of the relationship between hotel attributes and PP or other measures such as overall evaluation.

A data-driven model called FRBS is constructed using original verbal statements. Novel insights pertinent to relations between hotel attributes and PP have been extracted.

乏晰规则为本系统（FRBS）作为大数据分析的软计算方法, 接用旅游2.0数据来分析出哪个酒店属性或者相关酒店属性对于价格-效益（PP）有直接作用。

本论文采用FRBS以Fuzzy Set理论为基础, 采集2009年至2016年之间的HolidayCheck.de网站上的土耳其阿拉尼亚目的地的四星和五星酒店数据作为样本, 进行分析计算。

酒店个别属性并不对PP具有直接影响。至少两个或者以上属性加和对PP有直接影响。酒店属性与PP的关系并不是预想的那样线性关系, 而是非线性的。此外, 一些酒店属性起初并不对PP有影响, 而是直到其他属性达到一定的水平后才起反应。

本论文使用原始文本数据来构建以数据导向的FRBS模型。本论文给出了对于酒店属性和PP的关系相关的新型建议。

Grounded in the cognitive appraisal theory, this paper aims to investigate how employees cognitively evaluate and respond to the introduction of service robots, with a particular focus on generational differences.

Data was collected from hospitality employees across different generations in the USA, and 279 responses were analyzed using partial least squares structural equation modeling.

The results indicate negative service robot awareness and perceived risk significantly contribute to increased turnover intentions, with job insecurity mediating these associations. Notably, Generation Z employees exhibit distinct attitudes toward service robots compared to older generations, indicating a varying response pattern across different generational cohorts.

Organizations operating in the hospitality industry can use these findings to tailor interventions aimed at addressing concerns related to job insecurity and turnover intentions arising from the integration of service robots. Recognizing the diverse perspectives among different generational groups, organizations can implement targeted approaches to ensure a smoother transition and enhance employee acceptance of service robot technologies.

This study contributes to the literature by shedding light on the nuanced interplay between employees’ cognitive evaluations, generational differences and the introduction of service robots in the hospitality sector. The insights generated offer valuable guidance for both academics and industry practitioners, facilitating the development of strategies to foster a mutually beneficial integration of service robots into the workforce.

本研究基于认知评估理论, 探讨员工如何对引入服务机器人进行认知评估和响应, 特别关注世代差异。

采集了来自美国不同世代的酒店员工的数据, 分析了279份回应, 采用了部分最小二乘结构方程建模（PLS-SEM）分析方法。

研究结果显示, 对服务机器人的负面认知和感知风险显著增加了员工的离职意向, 工作不安全感在这些关系中起到了中介作用。值得注意的是, 与老一辈相比, Z世代员工对服务机器人表现出明显不同的态度, 显示出不同世代群体对服务机器人的响应模式各异。

本研究通过揭示员工认知评估、世代差异和服务机器人引入在酒店业中的微妙互动, 对文献做出了贡献。所得的洞见为学术界和行业从业者提供了宝贵指导, 有助于制定策略, 促进服务机器人与工作人员的互利融合。

在酒店业运营的组织可以利用这些发现来定制干预措施, 解决由引入服务机器人引发的工作不安全感和离职意向问题。认识到不同世代群体的多样化观点, 组织可以实施有针对性的方法, 确保服务机器人技术的平稳过渡, 增强员工对其的接受度。

Environmentally Responsible Behavior (ERB) refers to actions and practices aimed at minimizing negative environmental impact through conservation, waste reduction and sustainable practices driven by concern for environmental well-being. This study aims to explain the effect of environmental attitudes of hotel guests visiting green and non-green hotels on their ERB. In the research, hotels with different concepts were handled separately and a comparative analysis was made between both customer types.

The study was assessed using two separate models: one for green hotel guests and another for non-green hotel guests. Data were collected from 205 participants from green hotel guests in Turkiye and 206 participants from hotel guests visiting non-green hotels in Turkiye, using a survey form with a convenience sampling method. The hypotheses were analyzed with the structural equation model and multi-group analysis (MGA) in the Smart PLS statistical program.

The ecocentric attitude positively affects political and community activism but does not impact recycling, educational behavior, green consumerism or overall ERB. The technocentric attitude negatively influences recycling, educational behavior, green consumerism, community activism and ERB but does not negatively affect political activism. The dualcentric attitude positively impacts all ERB sub-dimensions. The multi-group analysis (MGA) revealed that dualcentric attitudes have a stronger influence on green consumerism, political activism and recycling behavior among green hotel guests compared to non-green hotel guests.

These findings directly impact hotel managers, underscoring the strategic significance of adopting and advocating green practices. Implementing environmentally friendly initiatives not only appeals to environmentally conscious consumers but also holds the potential to cultivate ERB among all guests. By integrating sustainability into marketing strategies, hotels can communicate their commitment to environmental stewardship, positively influencing guests’ environmental attitudes and behaviors.

The paper’s key contribution is its comparative analysis of ERB between guests at green and non-green hotels. It reveals how tourists’ environmental attitudes influence their hotel choices and behaviors, offering insights into sustainable tourism. Additionally, it explores the differences between ecocentric, technocentric and dualcentric attitudes, enhancing our understanding of how varying environmental concerns shape tourists’ behaviors and choices and contributing to the broader discussion on environmental psychology in tourism.

This paper aims to address the critical labor shortage in the food industry by exploring the potential of 3D food printing technology as a strategic solution. The study investigates how 3D food printing can enhance productivity, reduce labor costs, and offer innovative applications in various sectors of the food industry.

The research employs a comprehensive review of existing literature and case studies to analyze the current state of labor scarcity in the food industry and the technological advancements in 3D food printing. The paper also assesses the technical, operational, regulatory, and ethical challenges of 3D food printing and provides strategic recommendations for stakeholders.

3D food printing technology presents a viable solution by automating labor-intensive tasks, enhancing labor efficiency, and enabling customized food production. The technology’s potential benefits include improved productivity, reduced operational costs, and the ability to meet personalized nutritional needs. However, the adoption of 3D food printing faces challenges such as high initial costs, maintenance requirements, and scalability issues. Additionally, regulatory and consumer acceptance hurdles need to be addressed.

Policymakers are encouraged to support the development and adoption of 3D food printing through funding and clear regulatory frameworks. Business leaders should consider strategic investments in 3D printing technology and training programs to harness its benefits. Technology developers must focus on advancing the capabilities and user-friendliness of 3D food printers. Addressing these aspects can help the food industry overcome labor scarcity and achieve long-term sustainability and efficiency.

This paper provides a comprehensive analysis of 3D food printing technology as a strategic response to labor scarcity in the food industry. It contributes to the existing body of knowledge by highlighting the potential of 3D food printing to revolutionize food production and offering practical recommendations for its adoption and integration.