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Article Factors Affecting Dentists' Intention To Adopt Artificial Intelligence: An Extension of the Unified Theory of Acceptance and Use of Technology (UTAUT) Model(Emerald Group Publishing Ltd, 2025) Alqaifi, Faten; Tengilimoglu, DilaverPurposeAdvancements in science and technology have integrated artificial intelligence (AI) into dentistry, improving treatment processes, operational efficiency, and clinical outcomes. However, AI adoption among dentists remains underexplored, hindering progress in oral healthcare. This study aims to identify key barriers to AI adoption and examine factors influencing dentists' intention to use AI.Design/methodology/approachA quantitative cross-sectional approach was employed, utilizing self-administered questionnaires distributed online and across various dental clinics and hospitals in Ankara, Turkey. A total of 440 dentists participated in the study. Data analysis was conducted using SPSS and SmartPLS.FindingsThe study found that AI-anxiety negatively affects the intention to adopt AI in dentistry, showing a medium (almost large) effect that is stronger than other UTAUT factors such as performance expectancy, effort expectancy, and social influence, which demonstrated only small effects. Dentists with higher anxiety about learning and sociotechnical blindness are less likely to adopt AI, while concerns about job replacement and AI-configuration have less but still significant impact.Research limitations/implicationsThese results contribute to the growing body of knowledge on technology adoption in oral healthcare and provide practical implications for technology developers, policymakers, and other stakeholders seeking to facilitate AI integration in dentistry.Originality/valueThis study provides novel insights into AI adoption in dentistry, offering guidance for future development and integration, and addressing a critical research gap in a growing field-particularly in Turkey, where implementation is still in its early stages.Article Mapping the Literature on Thermal Tourism: A Bibliometric and Content Analysis(Conscientia Beam, 2025) Alqaifi, Faten; Tengilimoglu, Dilaver; Aras, Ilknur ArslanThis study explores and maps the existing literature on thermal tourism to provide comprehensive insights and inform future research directions. The research design is based on a bibliometric analysis of 48 documents published between 2013 and 2023 and indexed in the Web of Science database. Data were processed and visualized using Microsoft Excel and Bibliometrix, followed by a content analysis of 42 English-language articles to capture thematic developments in the field. The findings indicate that, despite a temporary decline during the COVID-19 pandemic, publications on thermal tourism have shown strong growth and recovery, with an annual growth rate of 46.65%. The most significant contributions originated from Portugal, China, Spain, Taiwan, Turkey, and Japan, with research disseminated across 37 journals. Four central themes were identified: (1) tourist behaviors and satisfaction, (2) demand and motivations, (3) quality and resource management, and (4) strategic and sustainable development. Among these, tourist behaviors and satisfaction emerged as the most prominent research area, representing 38.10% of the analyzed literature. This paper addresses a gap in the literature by mapping the knowledge landscape in the relatively underexplored field of thermal tourism, highlighting its growth potential and proposing a future research agenda. The practical implications suggest that recognizing these trends and themes can help policymakers, industry stakeholders, and academics develop strategies to enhance sustainable practices and expand opportunities in thermal tourism.
