This paper aims to contribute with a literature review on the use of AI for cleaner production throughout industries in the consideration of AI’s advantage within the environment, economy, and society. The survey report based on the analysis of research papers from the recent literature from leading database sources such as Scopus, the Web of Science, IEEE Xplore, Science Direct, Springer Link, and Google Scholar identifies the strategic strengths of AI in optimizing the resources, minimizing the carbon footprint and eradicating wastage with the help of machined learning, neural networks and predictive analytics. AI integration presents vast aspects of environmental gains, including such enhancements as a marked reduction concerning the energy and materials consumed along with enhanced ways of handling the resulting waste. On the economic aspect, AI enhances the processes that lead to better efficiency and lower costs in the market on the other hand, on the social aspect, the application of any AI influences how people are utilized as workers/clients in the community. The following are some of the limitations towards AI adoption as proposed by the review of related literature; The best things that come with AI are yet accompanied by some disadvantages; there are implementation costs, data privacy, as well as system integration that may be a major disadvantage. The review envisages that with the continuation of the AI development in the following years, the optic is going to be the accentuation on the enhancement of the process of feeding the data in real-time mode, IoT connections, and the implementation of the proper ethical approaches toward the AI launching for all segments of the society. The conclusions provide precise suggestions to the people working in the industry to adopt the AI advancements appropriately and at the same time, encourage the lawmakers to create favorable legal environments to enable the ethical uses of AI. This review therefore calls for more targeted partnerships between the academia, industry, and government to harness the full potential of AI for sustainable industrial practices worldwide.

In this paper, we will provide an extensive analysis of how Generative Artificial Intelligence (GenAI) could be applied when handling Supply Chain Management (SCM). The paper focuses on how GenAI is more relevant in industries, and for instance, SCM where it is employed in tasks such as predicting when machines are due for a check-up, man-robot collaboration, and responsiveness. The study aims to answer two main questions: (1) What prospects can be identified when the tools of GenAI are applied in SCM? Secondly, it aims to examine the following question: (2) what difficulties may be encountered when implementing GenAI in SCM? This paper assesses studies published in academic databases and applies a structured analytical framework to explore GenAI technology in SCM. It looks at how GenAI is deployed within SCM and the challenges that have been encountered, in addition to the ethics. Moreover, this paper also discusses the problems that AI can pose once used in SCM, for instance, the quality of data used, and the ethical concerns that come with, the use of AI in SCM. A grasp of the specifics of how GenAI operates as well as how to implement it successfully in the supply chain is essential in assessing the performance of this relatively new technology as well as prognosticating the future of generation AI in supply chain planning.

This study, based on the Theory of Planned Behavior (TPB), aims to explore the entrepreneurial intentions of university students in Shandong Province, China, and analyze the major factors influencing these intentions. Structural Equation Modeling was applied to data collected from 680 students across five universities in Shandong Province. The findings reveal that attitudes, subjective norms, and perceived behavioral control significantly influence the students’ entrepreneurial intentions. Specifically, a positive attitude towards the outcomes of entrepreneurship emerged as the strongest factor influencing their intentions, indicating that positive perceptions and expectations of entrepreneurship significantly enhance students’ entrepreneurial inclinations. Perceived behavioral control also showed a strong influence, suggesting that enhancing students’ self-efficacy and awareness of accessible resources is crucial for fostering entrepreneurial intentions. However, the influence of subjective norms was weaker, which may relate to specific cultural and social environmental factors. This study not only provides an empirical basis for entrepreneurship education and policy-making in Shandong Province and beyond but also offers new insights into the application of TPB in the field of entrepreneurship research.

The rise of Internet technology has transformed consumer shopping behaviors, offering convenience and a wide range of options, making online shopping increasingly popular. In Saudi Arabia, this trend has grown significantly due to higher internet penetration, technological advancements, and shifting consumer preferences. However, building and maintaining consumer trust remains a crucial challenge. Despite the growing interest, there is limited research on the unique aspects of Saudi consumers’ online shopping behaviors. This study aims to address this gap by identifying key factors influencing these behaviors and examining their impact on purchase intentions, with a focus on the mediating role of consumer trust. This study explores factors influencing online shopping behavior and their impact on purchase intention, with a focus on consumer trust as a mediator. Using a survey of 573 respondents from Jeddah and Medina, Saudi Arabia, key factors identified through literature review include perceived usefulness, ease of use, risk perception, website quality, and social influence. The quantitative analysis revealed that customer service and return policies, information quality, perceived convenience, ease of use, usefulness, cost-saving, product variety, and social influence significantly affect consumer trust, which in turn enhances purchase intention. These findings provide valuable insights for businesses to optimize digital strategies, enhance consumer engagement, and foster long-term customer relationships, thereby boosting satisfaction and online business success.

The construction industry is a significant contributor towards global environmental degradation and resource depletion, with developing economies facing unique challenges in adopting sustainable construction practices. This systematic review aims to investigate the gap in sustainable construction implementation among global counterparts. The study utilizes the P5 (People, Planet, Prosperity, Process, Products) Standard as a framework for evaluating sustainable construction project management based on environmental, social, and economic targets. A Systematic Literature Review from a pool of 994 Sustainable Construction Project Management (SCPM) papers is conducted utilizing the PRISMA methodology. Through rigorous Identification, Screening, and Eligibility Verification, an analysis is synthesized from 44 relevant literature discussing SCPM Implementations worldwide. The results highlight significant challenges in three main categories: environmental, social, and economic impacts. Social impacts are found as the most extensively researched, while environmental and economic impacts are less studied. Further analysis reveals that social impacts are a major concern in sustainable construction, with numerous studies addressing labor practices and societal well-being. However, there is a notable gap in research on human rights within the construction industry. Environmental impacts, such as resource utilization, energy consumption, and pollution, are less frequently addressed, indicating a need for more focused studies in these areas. Economic impacts, including local economic impact and business agility, are further substantially underrepresented in the literature, suggesting that economic viability is a critical yet underexplored aspect of sustainable construction. The findings underscore the need for further research in these areas to address the implementation challenges of sustainable project management effectively. This research contributes towards the overall research of global sustainable construction through the utilization of the P5 Standards as a new lens of determining sustainability performance for construction projects worldwide.

This paper examines the transformative potential of e-government in public administration, focusing on its capacity to enhance service delivery, transparency, accessibility, cost efficiency, and civic engagement. The study identifies key challenges, including inadequate technological infrastructure, cybersecurity vulnerabilities, resistance to change within public institutions, and a lack of public awareness about e-government services. These barriers hinder the seamless operation and adoption of digital government initiatives. Conversely, the study highlights significant opportunities such as streamlined service delivery, enhanced transparency through real-time access to government data, increased accessibility for marginalized and remote communities, substantial cost savings, and greater civic engagement via digital platforms. Addressing these challenges through targeted strategies—enhancing technological infrastructure, bolstering cybersecurity, managing organizational change, and raising public awareness—can help policymakers and public administrators implement more effective and inclusive e-government initiatives. Additionally, the integration of these digital solutions can drive sustainable development and digital inclusion, fostering social equity and economic growth. By leveraging these opportunities, governments can achieve more efficient, transparent, and accountable governance. Ultimately, the successful implementation of e-government can transform the relationship between citizens and the state, building trust and fostering a more participatory democratic process.

 In the face of growing disruptions within the unconventional business environment, this study focuses on enhancing supply chain resilience through strategically reforming resources. It highlights the importance of understanding the dynamics and interactions of resources to tackle supply chain vulnerability (SCV) in the manufacturing sector. Employing the Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology alongside an adapted Analytic Network Process (ANP), the research investigates supply chain vulnerabilities in Pakistan’s large-scale manufacturing (LSM) public sector firms. The DANP method, through expert questionnaires, helps validate a theoretical framework by assessing the interconnectedness of supply chain readiness dimensions and criteria. Findings underscore Resource Reformation (RR) as a critical dimension, with the positive restructuring of resources identified as pivotal for public sector firms to align their operations with disruption magnitudes, advocating for a detailed analysis of resource utilization.

This research explores the advancement of Artificial Intelligence (AI) in Occupational Health and Safety (OHS) across high-risk industries, highlighting its pivotal role in mitigating the global incidence of occupational incidents and diseases, which result in approximately 2.3 million fatalities annually. Traditional OHS practices often fall short in completely preventing workplace incidents, primarily due to limitations in human-operated risk assessments and management. The integration of AI technologies has been instrumental in automating hazardous tasks, enhancing real-time monitoring, and improving decision-making through comprehensive data analysis. Specific AI applications discussed include drones and robots for risky operations, computer vision for environmental monitoring, and predictive analytics to pre-empt potential hazards. Additionally, AI-driven simulations are enhancing training protocols, significantly improving both the safety and efficiency of workers. Various studies supporting the effectiveness of these AI applications indicate marked improvements in risk management and incident prevention. By transitioning from reactive to proactive safety measures, the implementation of AI in OHS represents a transformative approach, aiming to substantially reduce the global burden of occupational injuries and fatalities in high-risk sectors.