The role of artificial intelligence in improving the environmental performance of the municipality with the mediating role of management support in the city of Natanz

Objective: The aim of the present study is to investigate the role of artificial intelligence in improving the environmental performance of the municipality with the mediating role of management support in the city of Natanz.

Methods: The present study was conducted in terms of applied purpose and descriptive-survey method. The statistical population of the present study included all employees of the Natanz municipality, 250 people, and the sample size was selected based on Cronbach's alpha as 152 people. The research tool included three standard questionnaires: artificial intelligence from Makilaw (2021) with 16 items, environmental performance from Maltik (2015) with 5 items, and management support from Sachs and Thorpe (2015) with 9 items. The validity of the tool in formal, content, and construct methods and its reliability based on Cronbach's alpha for the entire questionnaire was confirmed at 0.857. The collected data were analyzed based on structural equation path analysis in PLS software.

Results: The results indicated that artificial intelligence has an impact on environmental performance with an impact coefficient of 0.749 and a t value of 438.15, artificial intelligence has an impact on management support with an impact coefficient of 0.765 and a t value of 122.12, and management support has an impact on environmental performance with an impact coefficient of 0.563 and a t value of 252.6. Also, the results of the Sobel test showed that artificial intelligence has an impact on improving the environmental performance of the municipality with the mediating role of management support with a T value of 397.15.

Conclusions: The role of AI in improving the environmental performance of municipalities, especially in cities like Natanz, is very important. This can include the use of AI in areas such as air pollution monitoring, water resource management, waste management, energy consumption optimization, and environmental change prediction.