The model of sustainability indicators in eco-cities with the approach of GPT chat engine

Document Type : Science - Research

Authors

1 Ph.D. in Business Administration, University of Tehran, Tehran, Iran

2 Associate Professor Department of Human Resource Management, Faculty of Organizational Resources, Amin Police University, Tehran, Iran

Abstract

With the increase in urban population and environmental pressures, the evaluation and optimal management of resources and factors influencing urban sustainability have gained significant importance. Advanced intelligent technologies can play a crucial role in designing sustainability index models. This paper examines the sustainability index model in eco-cities using the GPT chat engine. This engine, based on artificial intelligence and deep learning, has the capability to automatically analyze data and extract urban behavioral patterns. The research method in this study, aimed at practical application and exploratory nature, was conducted in two phases. In the first phase, the GPT AI engine was used to collect data. Questions related to urban sustainability indices were continuously asked of the system until the responses reached saturation. In the second phase, the data were coded and analyzed. The codes were then categorized into larger groups and related themes. The validity and reliability of the data were confirmed through content validity and Kappa reliability with over 70% agreement among experts. The findings indicate ten themes, including environmental sustainability, improvement of infrastructure and smart technologies, social development and education, public health and quality of life, water resource management and environmental protection, sustainable economy and innovative businesses, urban security and crisis response, sustainable architecture and design, urban agriculture and food security, and urban culture and identity. These findings demonstrate the extensive application of intelligent technologies in improving sustainability indices in eco-cities.

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Articles in Press, Accepted Manuscript
Available Online from 27 July 2024
  • Receive Date: 10 March 2024
  • Revise Date: 30 June 2024
  • Accept Date: 01 July 2024