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This paper aims to determine the knowledge and attitudes of the physicians regarding human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS), to emphasize that these patients exist and they will exist in the future and to raise awareness so as to prevent that their rights to treatment are revoked.

The survey was conducted via a link sent through an online system. Random physicians from 81 cities of the country were invited to the survey. The survey has 41 questions regarding knowledge and attitudes in total, including epidemiological information such as age, gender and title.

A total of 3,107 physicians has voluntarily participated in the study. In total, 2,195 (70.7%) are internal physicians and 912 (29.3%) are surgical physicians among the participant physicians. In total, 1,452 (46.7%) of the participants are specialist physicians, 608 (19.6%) of the participants are practising physician and the rest of it is physician assistants, academicians and dentists, respectively.

In this study, it has been found out that the physicians have a lack of knowledge on HIV/AIDS and they adopt a discriminatory attitude towards HIV-positive persons. HIV-positive patients who are exposed to discrimination and scared of being uncovered refrain from applying to hospitals for treatment, which puts public health into jeopardy due to the high viral load and these patients are faced with difficulties in coping with both medical and emotional load of the disease.

Building on previous historical works, this study aims to develop a framework to represent chambers as meta-organizations and present the case of Dersaadet Chamber of Commerce (DCC), based on this framework, during its emergence and evolution in the late 19th and early 20th centuries.

In the study, a historical narrative was constructed from primary and secondary data. To complement data collected from the archives a systematic content analysis was used to explore the discourse of the chamber within its serial magazine.

It was found that the first chamber of the Ottoman Empire, DCC, was established according to the public law model as an extension of the economic context and the guild order, and it was observed that it increasingly conformed to this model between 1882 and 1929.

In this study, chamber models are examined for the first time according to the designated features of meta-organizational forms, built on the historical work on chambers. The case of DCC suggested that it adopted a public law model and displayed much continuity, even when significant transitions were observed during the modernization process from Ottoman Empire to Turkish Republic.

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。

This paper aims to find the numerical solution of planar and non-planar Burgers’ equation and analysis of the shock behave.

First, the authors discritize the time-dependent term using Crank–Nicholson finite difference approximation and use quasilinearization to linearize the nonlinear term then apply Scale-2 Haar wavelets for space integration. After applying this scheme on partial differential, the equation transforms into a system of algebraic equation. Then, the system of equation is solved using Gauss elimination method.

Present method is the extension of the method (Jiwari, 2012). The numerical solutions using Scale-2 Haar wavelets prove that the proposed method is reliable for planar and non-planar nonlinear Burgers’ equation and yields results better than other methods and compatible with the exact solutions.

The numerical results for non-planar Burgers’ equation are very sparse. In the present paper, the authors identify where the shock wave and discontinuity occur in planar and non-planar Burgers’' equation.

This research aims to explore the role of technology in the future of restaurant labor. It focused on the opinions of restaurant employees, including managers, regarding technological trends such as service robots, self-service kiosks, robot chefs and automated cooking systems and how these may affect the future of restaurant labor.

A qualitative research approach was adopted, and interviews were conducted with restaurant employees in the USA.

The findings uncovered that the benefits, impacts and shortcomings of technological trends in the restaurant industry differ depending on employees’ perspectives. Also, the findings of the shortcomings of each technological trend support the need for human labor as some aspects of technological trends cannot address the requirements of some tasks.

This research proposed a conceptual framework explaining the role of technological trends in the future of restaurant labor. It is one of the first studies to examine the role of technology in the future of hospitality labor, specifically restaurant labor, after the pandemic.

本研究旨在探讨技术在餐厅劳动力未来中的角色。研究聚焦于餐厅员工（包括管理人员）对服务机器人、自助服务终端、机器人厨师和自动烹饪系统等技术趋势的看法, 以及这些趋势可能对餐厅劳动力未来产生的影响。

本研究采用定性研究方法, 在美国对餐厅员工进行了访谈。

研究发现, 不同技术趋势在餐饮行业中的优点、影响及局限性因员工视角而异。此外, 各技术趋势的局限性也表明, 某些任务的需求无法完全由技术解决, 仍然需要人力参与。

本研究提出了一个概念框架, 用以解释技术趋势在餐厅劳动力未来中的作用。这是疫情后首批专门研究技术在酒店业劳动力（尤其是餐厅劳动力）未来角色的研究之一。

The purpose of this paper is to explore how GenAI can help companies achieve a higher level of hyper-segmentation and hyper-personalization in the tourism industry, as well as show the importance of this disruptive tool for tourism marketing.

This paper used the Web of Science and Google Scholar databases to provide updated studies and expert authors to explore GenAI in the tourism industry. Analysing hyper-segmentation and hyper-personalization modalities through GenAI and their new challenges for tourists, tourism cities and companies.

Findings reveal that GenAI technology exponentially improves consumers’ segmentation and personalization of products and services, allowing tourism cities and organizations to create tailored content in real-time. That is why the concept of hyper-segmentation is substantially focused on the customer (understood as a segment of one) and his or her preferences, needs, personal motivations and purchase antecedents, and it encourages companies to design tailored products and services with a high level of individual scalability and performance called hyper-personalization, never before seen in the tourism industry. Indeed, contextualizing the experience through GenAI is an important way to enhance personalization.

This paper also contributes to enhancing and bootstrapping the literature on GenAI in the tourism industry because it is a new field of study, and its functional operability is in an incubation stage. Moreover, this viewpoint can facilitate researchers and companies to successfully integrate GenAI into different tourism and travel activities without expecting utopian results. Recently, there have been no studies that tackle hyper-segmentation and hyper-personalization methodologies through GenAI in the tourism industry.

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.