Analysis of variables affecting the development of the new city of Alishahr based on interpretive structural modeling

Document Type : Research Paper

Authors

1 Visiting Professor, Department of Urban Planning, Faculty of Art and Architecture, Persian Gulf University, Bushehr

2 Assistant Professor of Urban Planning, Department of Urban Planning, Faculty of Art and Architecture, Persian Gulf University, Bushehr, Iran

Abstract

Developing new cities entails expanding and advancing cities in various economic, social, cultural, physical, and infrastructural realms. These cities are usually established to attract an overflow population and alleviate the pressure on the mother cities of the region, create new employment opportunities, develop infrastructure, improve the quality of life, and attract investment for construction and development. The present research aims to analyze the factors influencing the growth of the new city of Aalishahr. The study is descriptive-analytical in terms of objective and method. It utilizes survey-based data collection tools, such as a questionnaire. The desired variables were collected through the purposeful sampling of experts in urban engineering, urban planning, and regional planning and then examined using a structural interpretive model to analyze the complex relationships between the variables affecting the development of the new city of Aalishahr. Ultimately, using the MICMAC technique, the types of variables were identified based on their influence and susceptibility to other variables. The results indicate that the influential variables "local government policies" and "rural population migration" rank with a penetration power of 23 at the lowest level, namely the fifth level. It is evident that governments today, more than private enterprises, determine and implement their various policies and programs to develop new cities. However, these programs must be aligned with priorities, objectives, and standards to attract new populations. Additionally, "urban population growth" and "population density" are susceptible variables at the highest level, namely the first level, with a penetration power of 2 and 4, respectively.

Keywords

Main Subjects

References

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Geography and Development
Volume 22, Issue 77 - Serial Number 77
December 2024
Pages 107-134

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History

  • Receive Date: 14 March 2024
  • Revise Date: 25 May 2024
  • Accept Date: 08 June 2024

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