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The present study assesses the impact resistance of the shear thickening fluids-filled (STFs-filled) foam through drop-hammer impact tests.

The maximum residual impact load and specific impact energy absorption rate of STF-filled foam are studied with varying thickness (4–14 mm), densities (0.35–0.6 g/cm3) and hardness (40–50 Rockwell Hardness C Scale (HRC)) under different ambient temperatures (−20−20 °C) and impact energies (25–75 J).

The following conclusions are obtained from this study: (1) the higher the impact energy, the greater the maximum residual impact force and energy absorption efficiency of the material; (2) the impact resistance of STF-filled foam can be improved with the decrease of ambient temperature, achieving the highest energy absorption rate at −10?. (3) STF-filled foam substrate has the highest impact resistance, the lowest maximum residual impact force and the highest energy absorption coefficient when the density is 0.35  g/cm3, the hardness is 45HC and the thickness is 10 mm.

This is the first paper to analyze the impact of both environmental factors and material properties on the impact resistance of STF-filled foam. The results show that the decrease in temperature and the increase in hardness can enhance the impact resistance of STF-filled foam.

The purpose of this research is to investigate the importance and status of conditional accounting conservatism indicators and financial flexibility for the management of legal claims of the company during the outbreak of Corona.

The research method was implemented using statistical analysis in the SPSS environment. The participants of this research can be experts and specialists working in companies admitted to the stock exchange and expert professors in accounting fields; auditing; economy; financial engineering and financial management, categorized. The data related to the localization tool of research variables were collected by snowball sampling method in the summer of 2022.

One of the main results of the research is that based on the opinions and professional experience of experts and professionals working in companies admitted to the stock exchange and academic experts, within a range of seven, “The number of legal claims of the company with electronic businesses” under the title of the main indicator in the legal claims of the company in the outbreak of Corona from the importance dimension; “Exchange rate fluctuations in financial resilience” under the title of the main indicator in financial resilience in the Corona outbreak from the functional dimension; “The number of legal claims of the company with government institutions” under the title of the main indicator in the company’s legal claims in the Corona outbreak from the functional dimension; “The company’s conservatism score” under the title of the main indicator in the conditional conservatism of accounting in the Corona outbreak from the functional dimension; “oil price fluctuations in financial resilience” under the title of the main indicator in financial resilience in the Corona outbreak from the importance dimension; and “type of industry based on total assets” under the title of the main indicator in the conditional conservatism of accounting in the Corona outbreak was calculated from the importance dimension.

Although the previous literature has studied the direct correlation between accounting conservatism and financial flexibility, this work focuses on examining the direct association between accounting conservatism and financial flexibility in the post-Corona era and is carried out to resolve legal claims.

The growth of sustainable tourism has emerged as a major topic of discussion on a global scale, and the hospitality industry is playing a crucial part in the achievement of this goal. The hospitality industry in China is experiencing rapid growth, and with the assistance of artificial intelligence (AI), the country may be able to realize sustainable growth in the tourism sector. Within the context of the Chinese hospitality industry, this chapter investigated the role AI plays in promoting sustainable tourism and how the Chinese government is supporting the hospitality industry in doing so. Sustainable tourism practices increase travellers' trip experiences while protecting the environment and local people; however, China could invest more in AI technology to promote sustainable tourism, which might benefit the economy, environment and society. This chapter examines AI deployment in the Chinese hotel industry and its challenges and benefits. AI technology can increase service quality, operational efficiency and hospitality operators' competitiveness, according to the authors. AI application requires careful consideration of employee training, ethics and customer privacy.

The usage of AI-powered chatbots and virtual assistants facilitates seamless communication, offering instant responses to inquiries and enhancing customer satisfaction. In Japan, the hospitality industry is at the forefront of this AI-driven transformation and through collaborations with technology companies, hotels are deploying AI-powered concierge services, smart room automation, and language translation systems to cater to diverse guest needs. The integration of AI in Japan's tourism sector not only enhances operational efficiency but also showcases the country's commitment to innovation and delivering exceptional customer experiences. As Japan embraces AI in its hospitality industry, it navigates the delicate balance between leveraging technology and preserving human interaction and by combining the efficiency and accuracy of AI with the warmth and personal touch of human hospitality, Japan aims to redefine the future of tourism. Moreover, AI streamlines operations by automating repetitive tasks, optimising resource allocation, and improving efficiency in areas such as reservation management, inventory control, and demand forecasting. However, along with these benefits, there are significant challenges to consider. Privacy concerns arise as AI systems collect and process personal data, necessitating robust security measures to protect sensitive information. Ethical considerations must also be addressed, as the use of AI raises questions about transparency, bias, and accountability. Furthermore, while AI enhances efficiency, there is a concern about losing the human touch that has long been a hallmark of the hospitality industry. Balancing the benefits of AI with maintaining personalised and authentic guest experiences becomes a crucial challenge.

As the tourism industry continues to evolve and adapt to changing consumer demands, automated systems and artificial intelligence have gained significant attention. However, concerns related to ethical, social and environmental aspects have arisen alongside the benefits offered by these technologies. This chapter explores the emerging challenges surrounding the integration of robots and self-service technology in responsible and creative tourism.

The aim of this article is to produce alternative solution suggestions at a conceptual level, by utilizing technologies in the field of Augmented Reality (AR) and Artificial Intelligence (AI), to address the increasing personnel shortages encountered in the tourism and hospitality industry. The discussion is based on a review of the literature.

This article presents a qualitative study investigating the impact of Artificial Intelligence (AI) and Augmented Reality (AR) technologies on the workforce turnover rate in the tourism and hospitality industry in general.

Although Artificial Intelligence (AI) and Augmented Reality (AR) technologies have both positive and negative aspects for the hospitality and tourism industry and its employees, these technologies can be used to reduce the factors that cause employee turnover. In particular, it leads to improvements in job satisfaction, job commitment and career opportunities of sector employees, reduction of job stress, and selection and retention of the right employees.

This study examines the factors that tourism sector employees encounter in the sector and that cause the workforce turnover rate to increase, and emphasizes the importance of the possible benefits of the use of Artificial Intelligence (AI) and Augmented Reality (AR) technologies in reducing these factors that cause the workforce turnover rate.

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.

Service robots are increasingly prevalent in the hospitality industry. While studies have explored the concept of service robot risk awareness (SRRA) – an employee’s perception of service robots posing a threat to human labor – the impact of SRRA on robot abuse and its emotional mechanism through which it affects employees remains unclear. This research leverages emotional appraisal theory to investigate the mediating role of fear of robots in the relationship between SRRA and robot abuse. Additionally, considering the influential role of leadership in shaping emotional appraisal, this study aims to examine the moderating impact of transformational leadership.

To test the proposed model, time-lagged survey data were collected from 283 employees working under 54 leaders in 18 hotels in China. The model was analyzed using multilevel modeling in Mplus 7.3.

At the individual level, SRRA indirectly increases robot abuse through the mediation of fear of robots. However, there is a cross-level moderation: the indirect relationship is alleviated when leaders exhibit high levels of transformational leadership.

This study pioneers the concept of robot abuse in hospitality and tourism settings. It extends emotional appraisal theory by highlighting the significant mediating role played by fear of robots. Furthermore, demonstrating how transformational leadership can mitigate the effects of SRRA offers valuable insights for leadership selection and training to facilitate the successful implementation of service robots.

服务机器人在酒店业中日益普及。虽然研究已探讨了服务机器人风险意识（SRRA）的概念——即员工对服务机器人构成对人力劳动的威胁感知, 但SRRA对辱虐机器人及其对员工的情绪机制的影响仍不清楚。本研究利用情绪评估理论调查了恐惧对SRRA与机器人滥用之间关系的中介作用。此外, 考虑到领导在塑造情绪评估中的重要作用, 本研究还考察了变革型领导力的调节影响。

为了测试提出的模型, 收集了来自中国18家酒店中54位领导下的283名员工的时滞调查数据。该模型使用Mplus 7.3中的多层建模进行分析。

在个体水平上, SRRA通过恐惧对机器人的中介作用间接增加了辱虐机器人。然而, 研究发现跨层次调节变量：当领导展现出较高水平的变革型领导力时, 间接关系得到缓解。

本研究首创了服务在酒店和旅游领域的辱虐机器人行为概念。它通过突出恐惧对机器人的重要中介作用, 扩展了情绪评估理论。此外, 展示了变革型领导如何缓解SRRA的影响, 为领导选聘和培训提供了有价值的见解, 促进了服务机器人的成功实施。

At the forefront of current research is the investigation of how big data analytics capability (BDAC) and artificial intelligence capability (AIC) can enhance performance in concert. Therefore, current study intended to conduct more deep research into emerging phenomena and attempts to cover the gap by exploring how entrepreneurial orientations (EO) emphasize the use of two emerging capabilities under the moderating role of environmental dynamism which in turn augment co-innovation and hotel performance.

Data were collected from four-star and five-star hotels located in Kula Lumpur and Langkawi in Malaysia. A total of 260 responses were obtained from IT staff and senior managers with the assistance of a Manpower agency for data analysis. The hypotheses were examined by analyzing the data using PLS-SEM technique through Smart PLS 3 software.

The result revealed that EO has a positive and significant effect on co-innovation (CIN). Additionally, the BDAC and AIC have been tested and proven to be potential mediators between EO and CIN. Also, environmental dynamism as moderator has positive and significant effect on BDAC and co-innovation performance, however, not significant impact on AIC and co-innovation performance. Lastly, findings displayed positive and significant moderated mediation impact of environmental dynamics on BDAC and CIN with hotel performance, but not significant influence on AIC and co-innovation with hotel performance. For theoretical corroboration of the research findings, the current study integrated EO, resource-based view theory and contingent dynamic capabilities (CDC), because neither single stance can explicate an extant research framework.

This study anticipated the several implications for the entrepreneurs of hospitality industry. Managers are recommended to invest in the entrepreneurial traits of the employees/organizations and make strategic readjustment of their capabilities for sustained business performance.

The study goes beyond the normal inquiry by investigating moderated mediation impact of environmental dynamism between two emerging capabilities, co-innovation and hotel performance relationships. Another novelty of this study is to culminate the exploitation and adoption of emerging IT-based capabilities in cross domains of management, entrepreneurship, information systems management within the hotel industry.

The purpose of this study is to explore whether five factors drawn from the unified theory of acceptance and use of technology (UTAUT) and UTAUT2 significantly influence customers' intention to use hotel in-room voice assistants (VAs). It further examined culture as a moderator of the relationships between the five factors and customers' intention to use.

The authors collected data from US and Singapore to examine cultural differences in customer acceptance of in-room VAs. All hypotheses were tested via structural equation modeling and multi-group analysis.

The results showed that performance expectancy, social influence and hedonic motivation significantly affected customers' intentions to use in-room VAs, while effort expectancy and facilitating conditions did not. The results confirmed that culture did not play a substantial role in moderating the relationships between these factors and intentions to use.

This study established that the instrument and structural paths in the research model were equivalent across two samples from different countries. The findings may not generalize to other countries as the data arises from customers in the US and Singapore.

The findings provide important implications for hotel operators and vendors seeking to enhance customer acceptance of in-room voice technology.

This study addresses the gaps of extant research by developing and testing a research model to better understand the influential factors of in-room VA adoption within the hotel domain.