In the era of artificial intelligence, smart clothing, as a product of the interaction between fashion clothing and intelligent technology, has increasingly attracted the attention and affection of enterprises and consumers. However, to date, there is a lack of focus on the demand of silver-haired population’s consumers for smart clothing. To adapt to the rapidly aging modern society, this paper explores the influencing factors of silver-haired population’s demand for smart clothing and proposes a corresponding consumer-consumption-need theoretical model (CCNTM) to further promote the development of the smart clothing industry. Based on literature and theoretical research, using the technology acceptance model (TAM) and functional-expressive-aesthetic consumer needs model (FEAM) as the foundation, and introducing interactivity and risk perception as new external variables, a consumer-consumption-need theoretical model containing nine variables including perceived usefulness, perceived ease of use, functionality, expressiveness, aesthetics, interactivity, risk perception, purchase attitude, and purchase intention was constructed. A questionnaire survey was conducted among the Chinese silver-haired population aged 55–65 using the Questionnaire Star platform, with a total of 560 questionnaires issued. The results show that the functionality, expressiveness, interactivity, and perceived ease of use of smart clothing significantly positively affect perceived usefulness (P < 0.01); perceived usefulness, perceived ease of use, aesthetics, and interactivity significantly positively affect the purchase attitude of the silver-haired population (P < 0.01); perceived usefulness, aesthetics, interactivity, and purchase attitude significantly positively affect the purchase intention of the silver-haired population (P < 0.01); functionality and expressiveness significantly positively affect perceived ease of use (P < 0.01); risk perception significantly negatively affects purchase attitude (P < 0.01). Through the construction and empirical study of the smart clothing consumer-consumption-need theoretical model, this paper hopes to stimulate the purchasing behavior of silver-haired population’s consumers towards smart clothing and enable them to enjoy the benefits brought by scientific and technological advancements, which to live out their golden years in comfort, also, promote the rapid development of the smart clothing industry.

This study investigates the impact of Corporate Social Responsibility (CSR) on employee job satisfaction within Pakistan's construction industry, with a focus on the mediating role of organizational commitment and the moderating role of perceived organizational support (POS). Employing survey data collected from a diverse range of construction firms across Pakistan, the quantitative analysis reveals that CSR initiatives significantly enhance employee job satisfaction, primarily through the mediating influence of organizational commitment. The findings suggest that when employees perceive their organization as socially responsible and engaged in community betterment, they exhibit greater commitment to the organization, which in turn fosters higher levels of job satisfaction. Although POS does not significantly moderate the CSR—job satisfaction relationship, it remains a critical factor in cultivating a supportive and positive work environment. This study contributes to the growing literature on CSR and employee outcomes by offering empirical evidence from a developing economy context. The results have practical implications for construction firms aiming to enhance employee morale and reduce turnover by leveraging CSR as a strategic tool to improve organizational commitment and overall job satisfaction.

Dredging and reclamation operations are pivotal aspects of coastal engineering and land development. Within these tasks lie potential hazards for personnel operating dredging machinery and working within reclamation zones. Due to the specialized nature of the work environment, which deviates from conventional workplace settings, the risk of workplace accidents is significantly heightened. The aim of this study is to conduct a comprehensive risk analysis of the safety aspects related to dredging and reclamation activities, with the goal of enhancing safety and minimizing the frequency and severity of potential dangers. This research comprises a thorough risk analysis, integrating meticulous hazard identification from sample projects and literature reviews. It involves risk assessment by gathering insights from experts with direct working experience and aims to assess potential risks. The study focuses on defining effective risk management strategies, exemplified through a case study of a nearshore construction project in Thailand. The study identified numerous high and very high-risk factors in the assessment and analysis of occupational safety in dredging and reclamation work. Consequently, a targeted response was implemented to control and mitigate these risks to an acceptable level. The outcome of this study will provide a significant contribution to the advancement of guidelines and best practices for improving the safety of dredging and reclamation operations.

It is important for society to know the actions implemented by companies in the construction sector to reduce the environmental pollution generated by this industry and to contribute to the solution of economic and social problems in their environment; however, the variables that allow identifying their contributions and impacts are not known. Based on this problem, the study focuses on identifying the factors that influence sustainability management within the construction sector in Colombia. The research presents a predictive approach and uses a quantitative methodology, applying statistical modeling techniques. The sample corresponds to 84 Colombian companies. As a result, a system of equations of the form y=mx+b is presented to describe the deviation of the environmental, economic, social, compensation measures, management, indicators and sustainability reports. The analysis of the intersections constitutes a projective tool to evaluate the relationships and balance points between the dimensions analyzed, helping to identify strengths and opportunities for improvement.

Climate change plays a vital role in shaping the knowledge construction of farmers for managing their agricultural land. Therefore, this study aims to analyze the coffee farmers’ knowledge construction process regarding climate change. This research utilizes qualitative methods. This research approach uses the grounded theory, which can help researchers uncover the relationship between the coffee farmers’ knowledge construction and climate change. The data were collected through semi-structured interviews and analyzed using constant comparative methods. The transcription of the field notes was analyzed using NVivo version 12, a program for analyzing qualitative data. There were 33 informants in the study. This study found that the conditions and situations of wind speed and uncertain whether strongly influence the farmers’ construction of climate knowledge. Coffee farmers are looking for new ways to respond to climate change, such as increasing the intensity of the care they give to their coffee plants, gradually harvesting according to the ripeness of the coffee fruits, finding alternative ways to dry the coffee beans, and reducing the use of fertilizer. However, coffee farmers are also starting to adapt old knowledge from their parents to the latest perceived climate phenomena, so that they can look for alternative sources of livelihood outside their farms. This knowledge construction process serves as a form of adaptation by the coffee farmers to climate change, and reflects the dynamic between traditional knowledge and current experience. Understanding this knowledge construction helps coffee farmers to cope with climate change and to design appropriate policy strategies to support the sustainability of coffee farming in an era of climate change. Further research is needed at the regional level.