This study employed a deductive approach to examine external HRM factors influencing job satisfaction in the post-pandemic hybrid work environment. Explores the intermediary functions of age, gender, and work experience in this particular environment. The data-gathering procedure consisted of conducting semi-structured interviews with carefully chosen 50 managers representing various sectors, industries, organizations, and professions. The applied approach was adopted to allow a systematic and unbiased investigation of the mediating variables. The study used SPSS 25 and Smart PLS 4 to analyze the model, enhancing understanding of HRM challenges in a constantly evolving workplace. The findings offer valuable insights for HR experts and businesses, highlighting the value of comprehending what methods HRM components influence job satisfaction to optimize employee well-being and productivity. The study provides applied recommendations designed for enhancing employee contentment in the AI-evolving professional atmosphere, shedding light on the importance of supportive leadership strategies, particularly during AI-triggered downsizing. Additionally, we welcome a new era to push forward in integrating and managing AI tools and technologies to automate decision-making and data processing. Results propose that Exogenous influences of human resource management (HRM) influence manager job satisfaction considerably. Specifically, downsizing caused by AI was found to have negative consequences, whereas diversity and restructuring have favorable effects. Gender was recognized as a crucial factor that influences outcomes, then age and years of experience have the most visible effect.

Infrastructure decision-making has traditionally been focused on the use of cost-benefit analysis (CBA) and multicriteria decision analysis (MCDA). Nevertheless, there remains no consensus in the infrastructure sector regarding a favored approach that comprehensively integrates resilience principles with those tools. This review focuses on how resilience has been evaluated in infrastructure projects. Initially, 400 papers were sourced from Web of Science and Scopus. After a preliminary review, 103 papers were selected, and ultimately, the focus was narrowed down to 56 papers. The primary aim was to uncover limitations in both CBA and MCDA, exploring various strategies for amalgamating them and enhancing their potential to foster resilience, sustainability, and other infrastructure performance aspects. Results were classified based on different rationalities: i) objectivist, ii) conformist, iii) adjustive, and iv) reflexive. The analysis revealed that while both CBA and MCDA contribute to decision-making, their perceived strengths and weaknesses differ depending on the chosen rationality. Nonetheless, embracing a broader perspective, fostering participatory methods, and potentially integrating both approaches seem to offer more promising avenues for assessing the resilience of infrastructures. The goal of this research proposal is to devise an integrated approach for evaluating the long-term sustainability and resilience of infrastructure projects and constructed assets.

This paper conducts a bibliometric visual analysis of the application of the Unified Theory of Acceptance and Use of Technology (UTAUT) in education, using CiteSpace software. Drawing on data from the Web of Science, the study explores research trends and influential works related to UTAUT from 2008 to 2023. It highlights the growing use of educational technologies such as mobile learning and virtual reality tools. The analysis reveals the most cited articles, journals, and key institutions involved in UTAUT research. Furthermore, keyword analysis identifies research hot spots, such as artificial intelligence and behavioral intentions. This study contributes to the understanding of how UTAUT has been used to predict technology adoption in education and provides recommendations for future research directions based on emerging trends in the digital learning environment.

In today’s fast-moving, disrupted business environment, supply chain risk management is crucial. More critically, Industry 4.0 has conferred competitive advantages on supply chains through the integration of digital technologies into manufacturing and logistics, but it also implies several challenges and opportunities regarding the management of these risks. This paper looks at some ways emerging technologies, especially Artificial Intelligence (AI), help address pressing concerns about the management of risk and sustainability in logistics and supply chains. The study, using a systemic literature review (SLR) backed by a mapping study based on the Scopus database, reveals the main themes and gaps of prior studies. The findings indicate that AI can substantially enhance resilience through early risk identification, optimizing operations, enriching decision-making, and ensuring transparency throughout the value chain. The key message from the study is to bring out what technology contributes to rendering supply chains resilient against today’s uncertainties.

5G technology is transforming healthcare by enhancing precision, efficiency, and connectivity in diagnostics, treatments, and remote monitoring. Its integration with AI and IoT is set to revolutionize healthcare standards. This study aims to establish the state of the art in research on 5G technology and its impact on healthcare innovation. A systematic review of 79 papers from digital libraries such as IEEE Xplore, Scopus, Springer, ScienceDirect, and ResearchGate was conducted, covering publications from 2018 to 2024. Among the reviewed papers, China and India emerge as leaders in 5G health-related publications. Scopus, Springer Link, and IEEE Xplore house the majority of first-quartile (Q1) papers, whereas Science Direct and other sources show a higher proportion in the second quartile (Q2) and lower rankings. The predominance of Q1 papers in Scopus, Springer Link, and IEEE Xplore underscores these platforms’ influence and recognition, reflecting significant advancements in both practice and theory, and highlighting the expanding application of 5G technology in healthcare.

The integration of chatbots in the financial sector has significantly improved customer service processes, providing efficient solutions for query management and problem resolution. These automated systems have proven to be valuable tools in enhancing operational efficiency and customer satisfaction in financial institutions. This study aims to conduct a systematic literature review on the impact of chatbots in customer service within the financial sector. A review of 61 relevant publications from 2018 to 2024 was conducted. Articles were selected from databases such as Scopus, IEEE Xplore, ARDI, Web of Science, and ProQuest. The findings highlight that efficiency and customer satisfaction are central to the perception of service quality, aligning with the automation of the user experience. The bibliometric analysis reveals a predominance of publications from countries such as India, Germany, and Australia, underscoring the academic and practical relevance of the topic. Additionally, essential thematic terms such as “artificial intelligence” and “advanced automation” were identified, reflecting technological evolution in this field. This study provides significant insights for future theoretical, practical, and managerial developments, offering a framework to optimize chatbot implementation in highly regulated environments.