Adult obesity is a significant health problem, with nearly a quarter of Hungarian citizens aged 15 years and older being obese in 2019 (KSH, 2019a). The use of mobile devices for health purposes is increasing, and many m-health apps target weight-related behaviours. This study uniquely examines the effectiveness and user satisfaction of health-oriented apps among Hungarian adults, with a focus on health improvement. Using a mixed-methods approach, the study identifies six key determinants of health improvement and refines measurement tools by modifying existing parameters and introducing new constructs. The principal objective was to develop a measurement instrument for the usability of nutrition, relaxation and health promotion applications. The research comprised three phases: (1) qualitative content analysis of 13 app reviews conducted in June 2022; (2) focus group interviews involving 32 students from the fields of business, economics and health management; and (3) an online survey (n = 348 users) conducted in December 2023 that included Strava (105 users), Yazio (109 users) and Calm (134 users). Six factors were identified as determinants of health improvement: physical activity, diet, weight loss, general well-being, progress, and body knowledge. The LAUQ (Lifestyle Application Usability Questionnaire) scale was validated, including ‘ease of use’ (5 items), ‘interface and satisfaction’ (7 items) and ‘modified usefulness and effectiveness’ (9 items), with modifications based on qualitative findings. This research offers valuable insights into the factors influencing health improvement and user satisfaction with healthy lifestyle-oriented applications. It also contributes to the refinement of measurement tools such as the LAUQ, which will inform future studies in health psychology, digital health, and behavioural economics.

Tourism plays a crucial role in driving economic development, and there is a growing demand to integrate sustainability into the sector, particularly in the financial practices of governments. This study introduces the Quintessence Sustainable Tourism Public Finances (QSustainableTPF) model, which combines five established financial models commonly used in the tourism industry. The research aims to identify statistically significant relationships between these models and assess their impact on sustainability and financial performance in tourism. A quantitative methodology was employed, with data collected from financial reports and budget documents of both local and central governments, along with a survey of 2099 citizens and visitors conducted during the 2023–2024 period. Statistical analysis was performed using SPSS and AMOS, incorporating exploratory factor analysis (EFA), reliability testing using Cronbach’s alpha, and confirmatory factor analysis (CFA). The findings underscore the essential role of public finance in supporting tourism sustainability, particularly through transparent budgetary practices, efficient allocation of resources, and targeted investment in local tourism initiatives. The analysis reveals key insights into the benefits of financial transparency, citizen-centred budgeting, and the promotion of innovation in tourism finance. The interconnectedness of the five models highlights the importance of responsible public financial management in fostering tourism growth, enhancing investment, and ensuring long-term financial sustainability in the sector. The study offers practical implications for policymakers, advocating for the adoption of transparent and innovative financial practices to boost tourism development. It also recommends further research to broaden the scope across different regions, integrating additional public finance dimensions to strengthen sustainable tourism growth.

This study investigates the interaction between audit firms and key audit matters (KAMs) to measure their impact on financial reporting quality in Palestine, thereby enriching the discourse on financial reporting. A descriptive statistical method was used to analyze the audit reports of listed Palestinian firms from 2018 to 2022. A methodology that scrutinizes the clarity and informativeness of KAMs across different audit firms and KAM types, the research investigates how audit procedures and risk assessments contribute to the comprehensibility of KAM disclosures. The findings highlight a significant disparity in the readability of KAMs attributable to audit firm selection, with the non-Big Four firms exhibiting distinct approaches. This understanding, gathered through multivariate analysis, offers valuable contributions to the ongoing discourse on financial reporting quality, emphasizing the essential role of audit firms in shaping the effectiveness of audit reports and KAM disclosures.

This paper investigates the transformative role of Artificial Intelligence (AI) in enhancing infrastructure governance and economic outcomes. Through a bibliometric analysis spanning more than two decades of research from 2000 to 2024, the study examines global trends in AI applications within infrastructure projects. The analysis reveals significant research themes across diverse sectors, including urban development, healthcare, and environmental management, highlighting the broad relevance of AI technologies. In urban development, the integration of AI and Internet of Things (IoT) technologies is advancing smart city initiatives by improving infrastructure systems through enhanced data-driven decision-making. In healthcare, AI is revolutionizing patient care, improving diagnostic accuracy, and optimizing treatment strategies. Environmental management is benefiting from AI’s potential to monitor and conserve natural resources, contributing to sustainability and crisis management efforts. The study also explores the synergy between AI and blockchain technology, emphasizing its role in ensuring data security, transparency, and efficiency in various applications. The findings underscore the importance of a multidisciplinary approach in AI research and implementation, advocating for ethical considerations and strong governance frameworks to harness AI’s full potential responsibly.