فهرست مطالب omid solatinejad

Artificial intelligence enhances energy infrastructure efficiency, reduces waste in distributed energy systems, and ensures long-term durability. Additionally, green Internet of Things technology is positively linked to green innovation practices promoting sustainability. In this context, the primary objective of this study is to examine the impact of the Internet of Things and artificial intelligence on environmental sustainability performance, considering the mediating influence of green supply chain management within the hotel industry. This study is designed as applied research, and the data collection method is descriptive and correlational. The statistical population comprises hotel managers in Urmia City, with a sample size of 34 hotels determined using "Krejcie and Morgan" and "Cohen" tables. Sixty-four questionnaires were distributed among hotel managers in Urmia City. A standard questionnaire, validated by experts, was used to collect data. Its reliability was estimated using Cronbach's alpha coefficient. Structural equation modeling was used for data analysis, revealing that the Internet of Things and artificial intelligence positively impact green supply chain management. Furthermore, a positive relationship was observed between green supply chain management practices and environmental sustainability performance. This study suggests that adopting the Internet of Things and artificial intelligence technologies can enhance the efficiency of green supply chain management processes, emphasizing the importance for managers to grasp the impact of these two emerging technologies on overall supply chain performance.

The purpose of this study is to investigate the effect of COVID-19 on the robustness, resilience, and sustainability of the supply chain of e-commerce companies. The statistical population of this research is all e-commerce chain stores in Semnan. As the number of units located in this city is limited to several e-commerce chain stores; Therefore, due to the limited statistical population, the statistical sample size of 136 people is considered using the Morgan table. On the other hand, the sampling method used in the present study is convenience sampling. In addition, four standard questionnaires were used to assess research variables. Cronbach's alpha coefficient was also used to measure reliability. Data analysis in this study was performed using structural equation modeling with partial least squares approach using SPSS and SmartPLS software. Findings showed that Covid-19 has a negative and significant effect on supply chain resilience and robustness. Supply chain resilience and robustness have a positive and significant effect on supply chain sustainability and sustainable outcomes.