Japan’s investment in the domestic construction industry has fallen to less than half its peak in 1992. Given the country’s declining population, Japanese construction companies must go global to remain profitable. To what extent the Japanese government and Japanese companies can contribute to meeting the growing infrastructure needs in the region is unclear as Japanese companies have long been operating primarily in Japan. The Japanese government has in recent years passed a series of new laws that encourage private sector participation in financing, building and operating public infrastructure. Through involvement in such public projects, Japanese companies have developed the skills and technologies to build a variety of infrastructures that are resilient to natural disasters and adaptable to various geographical conditions and social and economic development. But the major challenge for Japanese companies is to transform their business model drastically from one that relies on the domestic market to one that contributes to the social and economic development of third countries.

Every sector must possess the ability to identify potential dangers, assess associated risks, and mitigate them to a controllable extent. The mining industry inherently faces significant hazards due to the intricate nature of its systems, processes, and procedures. Effective risk control management and hazard assessment are essential to identify potential adverse events that might lead to hazards, analyze the processes by which these occurrences may transpire, and estimate the extent, importance, and likelihood of negative consequences. (1) The stage of industrial hazard analysis assesses the capability of a risk assessment process by acknowledging that hidden hazards have the potential to generate dangers that are both unknown and beyond control. (2) To mitigate hazards in mines, it is imperative to identify and assess all potentially dangerous circumstances. (3) Upon conducting an analysis and evaluation of the safety risks associated with identified hazards, the acquired knowledge has the potential to assist mine management in making more informed and effective decisions. (4) Frequently employed methods of data collection include interrogation of victims/witnesses and collection of information directly from the accident site. (5) After conducting a thorough analysis and evaluation of the safety hazards associated with hazard identification, the dataset has the potential to assist mine management in making more informed decisions. The study highlights the critical role of management in promoting a strong safety culture and the need for active participation in health and safety systems. By addressing both feared and unknown risks, educating workers, and utilizing safety-related data more effectively, mining companies can significantly improve their risk management strategies and ensure a safer working environment.

Smallholder paprika farmers in Zimbabwe contribute to local economies and food security but face supply chain challenges like limited market access and poor infrastructure which lead to post harvest losses and unpredictable prices. To survive, these farmers must adopt sustainable value networks to reduce operational costs and improve performance. This study sought to establish the effect of sustainable value networks on the operational performance of smallholder paprika farming in Zimbabwe. This study, using a positivist research philosophy and a quantitative approach, surveyed 288 smallholder paprika farmers in Zimbabwe. Exploratory factor analysis and partial least squares structural equation modelling were used to validate the constructs and test the hypothesised relationships. Results demonstrate a moderate level of implementation of value networks in smallholder paprika farming characterised by successes and challenges. The findings illustrated resource sharing among smallholder farmers, facilitated by initiatives, such as recycled seed exchanges and financial support through village savings and loan associations. However, results show that challenges persist, particularly with market access and financial support. Results indicate that there is a significant awareness and implementation of green supply chain management practices among smallholder paprika farmers even though they do not have access to resources and live in rural areas. The findings demonstrate that value networks significantly influence the adoption of green supply chain management practices, which in turn positively impact operational performance, environmental performance, and social performance. Green supply chain management practices were found to mediate the relationship between value networks and environmental performance, social performance, and operational performance, underlining the critical role of sustainable practices in enhancing performance outcomes. While environmental performance showed a positive effect on operational performance, the direct influence of social performance on operational performance was found to be statistically insignificant, suggesting the need for further exploration of the factors linking social benefits to operational efficiency. The research contributes to both theory and practice by presenting a sustainable value network model for smallholder paprika farmers, integrating value network, green supply chain management practices and environmental performance to enhance operational performance. Practical implications include policy recommendations to strengthen collaboration between smallholder farmers and other stakeholdersand address power imbalances with intermediaries. Future research should extend the study to other agricultural sectors and incorporate more diverse stakeholder perspectives to validate and generalise the proposed sustainable value network model.

Introduction: Many detrimental effects on employees’ health and wellbeing might result from inadequate illumination in the workplace. Headaches and trouble focusing can result from eye strain brought on by inadequate illumination. The purpose of this study was to simulate and optimize workplace illumination in the ceramic industry. Materials and methods: A common Luxmeter ST-1300 was used to measure the illumination in seven workplaces at a height of 100 cm above the floor. DIALux evo version 7.1 software was used to simulate the illumination of workplaces. To optimize the illumination conditions, a numerical experiment design consisting of 16 scenarios was used for each of the workplaces. Four factors were considered for each scenario: luminaire height, number of luminaires, luminous flux, and light loss factor. The Design-Expert program version 13.0.5.0 was applied for developing the scenarios. Finally, by developing quadratic models for each workplace, the optimization process was implemented. Results: Every workplace had illumination levels that were measured to be between 250 and 300 lux. Instead of using compact fluorescent luminaires, LED technology was recommended to maximize the illumination conditions for the workers. Following optimization, 376 lux of illumination were visible at each workstation in every workspace. For the majority of the workspaces, the simulated illumination was expected to have a desirability degree greater than 0.9. The uniformity and illumination of the workplace were significantly impacted by the two factors of luminaire height and luminaire count. Conclusion: The primary outcomes of this optimization were the environmental, political, and socioeconomic ones, including reduced consumption power, high light flux, and environmental compatibility. Nonetheless, the optimization technique applied in this work can be applied to the design of similar situations, such as residential infrastructure.

Artificial intelligence chatbots can be used to conduct research effectively and efficiently in the fifth industrial revolution. Artificial intelligence chatbots are software applications that utilize artificial intelligence technologies to assist researchers in various aspects of the research process. These chatbots are specifically designed to understand researchers’ inquiries, provide relevant information, and perform tasks related to data collection, analysis, literature review, collaboration, and more. The purpose of this study is to investigate the use of artificial intelligence chatbots for conducting research in the fifth industrial revolution. This qualitative study adopts content analysis as its research methodology, which is grounded in literature review incorporating insights from the researchers’ experiences with utilizing artificial intelligence. The findings reveal that researchers can use artificial intelligence chatbots to produce quality research. Researchers are exposed to various types of artificial intelligence chatbots that can be used to conduct research. Examples are information chatbots, question and answer chatbots, survey chatbots, conversational agents, peer review chatbots, personalised learning chatbots and language translation chatbots. Artificial intelligence chatbots can be used to perform functions such as literature review, data collection, writing assistance and peer review assistance. However, artificial intelligence chatbots can be biased, lack data privacy and security, limited in creativity and critical thinking. Researchers must be transparent and take in consideration issues of informed content and data privacy and security when using artificial intelligence chatbots. The study recommends a framework on artificial intelligence chatbots researchers can use to conduct research in the fifth industrial revolution.