Recently, Agile project management has received significant academic and industry attention from due to its advantages, such as decreased costs and time, increased effectiveness, and adaptiveness towards challenging business environments. This study primarily aims to investigate the relationship between the success factors and Agile project management methodology adoption and examine the moderating effect of perceived compatibility. The technology-organization-environment (TOE) framework and technology acceptance theories (UTAUT, IDT, and TAM) were applied as the theoretical foundation of the current study. A survey questionnaire method was employed to achieve the study objectives, while quantitative primary data were gathered using a carefully designed methodological approach focusing on Omani oil and gas industry. The PLS-SEM technique and SmartPLS software were used for hypotheses testing and data analysis. Resultantly, readiness, technology utilization, organizational factors, and perceived compatibility were the significant factors that promoted Agile methodology adoption in the oil and gas industry. Perceived compatibility moderated the relationship between success factors and Agile methodology. The findings suggested that people, technology, and organizational factors facilitate the Agile methodology under the technology acceptance theories and frameworks. Relevant stakeholders should adopt the study outcomes to improve Agile methodology adoption.

The construction industry is responsible for over 40% of global energy consumption and one-third of global greenhouse gas emissions. Generally, 10%–20% of energy is consumed in the manufacturing and transportation stages of materials, construction, maintenance, and demolition. The way the construction industry to deal with these impacts is to intensify sustainable development through green building. The author uses the latest Green Building Certification Standard in Indonesia as the Green Building Guidelines under the Ministry of Public Works and People’s Housing (PUPR) Regulation No. 01/SE/M/2022, as a basis for evaluating existing office buildings or what is often referred to as green retrofit. Structural Equation Modeling-Partial Least Squares (SEM-PLS) is used by the authors to detail the factors influencing the application of green building by analyzing several variables related to the problem studied, which are used to build and test statistical models of causal models. From this study, it is concluded that the most influential factors in the implementation of green retrofitting on office buildings are energy savings, water efficiency, renewable energy use, the presence of green building socialization programs, cost planning, design planning, project feasibility studies, material cost, use of the latest technology applications, and price fluctuations. With the results of this research, there is expected to be shared awareness and concern about implementing green buildings and green offices as an initiative to present a more energy-efficient office environment, save operating costs, and provide comfort to customers.

Resisting the adoption of medical artificial intelligence (AI), it is suggested that this opposition can be overcome by combining AI awareness, AI risks, and responsibility displacement. Through effective integration of public AI dangers and displacement of responsibility, some of these major concerns can be alleviated. The United Kingdom’s National Health Service has adopted the use of chatbots to provide medical advice, whereas heart disease diagnoses can be made by IBM’s Watson. This has the ability to improve healthcare by increasing accuracy, efficiency, and patient outcomes. The resistance may be due to concerns about losing jobs, anxieties about misdiagnosis or medical mistakes, and the consciousness of AI systems drifting more responsibility away from medical professionals. There is hesitancy among healthcare professionals and the general public about the deployment of AI, despite the fact that healthcare is being revolutionised by AI, its uses are pervasive. Participants’ awareness of AI in healthcare, AI risk, resistance to AI, responsibility displacement and ethical considerations were gathered through questionnaires. Descriptive statistics, chi-square tests and correlation analyses were used to establish the relationship between resistance and medical AI. The study’s objective seeks to collect data on primary and public AI awareness, perceptions of risk and feelings of displacement that the professionals have regarding medical AI. Some of these concerns can be resolved when AI awareness is effectively integrated and patients, healthcare providers, as well as the general public are well informed about AI’s potential advantages. Trust is built when, AI related issues such as bias, transparency, and data privacy are critically addressed. Another objective is to develop a seamless integration of risk management, communication and awareness of AI. Lastly to assess how this comprehensive approach has affected hospital settings’ ambitions to use medical AI. Fusing AI awareness, risk management, and effective communication can be used as a comprehensive strategy to address and promote the application of medical AI in hospital settings. An argument made by Chen et al. is that providing training in AI can improve adoption intentions while lowering complexity through the awareness of AI.

The purpose of this study is to investigate the relationship between the use of business intelligence applications in accounting, particularly in invoice handling, and the resultant disruption and technical challenges. Traditionally a manual process, accounting has fundamentally changed with the incorporation of BI technology that automates processes and allows for sophisticated data analysis. This study addresses the lack of understanding about the strategic implications and nuances of implementation. Data was collected from 467 accounting stakeholder surveys and analyzed quantitatively using correlational analysis. Multiple regression was utilized to investigate the effect of BI adoption, technical sophistication on operational and organizational performance enhancements. The results show a weak association between the use of BI tools and operational enhancements, indicating that the time for processing invoices has decreased. Challenges due to information privacy and bias were significant and negative on both operational and organizational performance. This study suggests that a successful implementation of a BI technology requires an integrated plan that focuses on strategic management, organizational learning, and sound policies This paper informs practitioners of how accounting is being transformed in the digital age, motivating accountants and policy makers to better understand accounting as it evolves with technology and for businesses to invest in concomitant advances.

Communication is considered to be significant to universities: provide students updated information to make appropriate choices and decisions during their learning process; and promptly feedback to contribute to building a better educational and training environment; improve institutional governance efficiency. Communication tools used in universities are diverse in forms and contents. This study focuses on two popular forms, which are policy communication (communication of policies and laws on higher education) and internal communication (communication about professional activities and community activities of the university). The theoretical framework has been developed and a survey was conducted to collect opinions of 450 students from many universities representing 3 regions of Vietnam, including: Vietnam National University, Hanoi (VNU) (Northern region); The University of Danang (UD) (Central region); Vietnam National University, Ho Chi Minh City (VNU-HCM) (Southern region). The results show that the policy communications of these universities are not effectively implemented. The findings suggest innovations for managers to improve communication effectiveness and governance efficiency in these higher education institutions.

Recent times have seen significant advancements in AI and NLP technologies, poised to revolutionize logistical decision-making across industries. This study investigates integrating ChatGPT, an advanced AI language model, into strategic, tactical, and operational logistics. Examining its applicability, benefits, and limitations, the study delves into ChatGPT's capacity for strategic logistics planning, facilitating nuanced decision-making through natural language interactions. At the tactical level, it explores ChatGPT's role in optimizing route planning and enhancing real-time decision support. The operational aspect scrutinizes ChatGPT's capabilities in micro-level logistics and emergency response. Ethical implications, encompassing data security and human-AI trust dynamics, are also analyzed. This report furnishes valuable insights for the logistics sector, emphasizing AI's potential in reshaping decision-making while underscoring the necessity for foresight, evaluation, and ethical considerations in AI integration. In this publication, it is assumed that ChatGPT is not entirely reliable for decision-making in the logistics field: at the strategic level, it can be effectively used for "brainstormin" in preparing decisions, but at the tactical and operational level, the depth of the knowledge is not sufficient to make appropriate decisions. Therefore, the answers provided by ChatGPT to the defined logistic tasks are compared with real logistic solutions. The article highlights ChatGPT's effectiveness at different levels of logistics and clarifies its potential and limitations in the logistics field.