Fuzzy Analysis of Success Factors of Urban Management, Indicators of Future Cities

Subject Areas : Urban Management Studies

soleyman fayzi ¹ , afsaneh zamanimoghadam ^{2 *} , reza radfar ³ , seyed abdolah amin mosavi ⁴

1 - Student
2 - دانشیار، گروه مدیریت، واحدعلوم وتحقیقات، دانشگاه آزاداسلامی، تهران، ایران. [e-mail] (نویسنده مسئول)
3 - استاد، گروه مدیریت صنعتی، واحدعلوم وتحقیقات، دانشگاه آزاداسلامی، تهران، ایران. [e-mail]
4 - استاد، گروه مدیریت صنعتی، واحدعلوم وتحقیقات، دانشگاه آزاداسلامی، تهران، ایران. [e-mail]

Received: 2023-10-01 Accepted : 2023-10-31 Published : 2023-11-22

Keywords: Urban Management, indicators of future cities, Fuzzy Analysis,

Abstract :

The main goal of this research is the fuzzy analysis of urban management success factors of future city indicators. In terms of purpose, the present research is applied research and in terms of method, it is a descriptive-survey research method. Data collection tools included questionnaires and questionnaires. The statistical population of this research are experts in the field of urban management. Purposive sampling method was used to select sample people. Superdesign software was used for data analysis. In the first step, by reviewing the subject literature and research, a large number of indicators of the subject literature have been examined. Following the urban management model, the indicators of future cities were ranked using fuzzy network analysis. In the current research, the factors are placed in six levels. In such a way that laws and regulations were placed at the last level and tourism at the first level. In the continuation of the research, it is taken from the perspective of the future. Examining the results obtained from the above table, rights and laws and social learning and education were reported as the most influential factors with a score of 22. Also, tourism with a total of 17 factors was placed in the first priority of acceptability. The degree of usefulness of the matrix is 100%, which indicates the high validity of the questionnaire and its related answers. Special vector machine of the obtained software: the environment with a weight of 0.358 is the highest priority. The urban body with a normal weight of 0.267 is in the second priority. Transportation with a normal weight of 0.241 is in the third priority. Economy with a normal weight of 0.134 is one of the lowest priorities.    

References:

 

Evans, G., Foord, J., Gertler, M., Tesolin, L. & Weinstock, S. 2006. Strategies for creative spaces and cities: lessons learned, London & Toronto, Cities institute, London Metropolitan University & Munk centre for international studies, University of Toronto. pp:60-65

Lees, A. etal, Eds. The Urbanization and Economic Development in Germany 1815- 1914 , In : Town in Societies: Essays in economic history and historical society ( P. Abrams and E.A. Wrigley,Eds.) Cambridge Univ. press, 1976.

Lei, Y., Wang. J. a., Yue, Y., Zhou, H., & Yin, W. (2013).Rethinking the relationships of vulnerability.resilience, and adaptation from a disaster risk perspective. Natural Hazards, 70 (1), 609-627. doi: 10. 1007/ s12069- 013- 0831- 7.

Mc Gill, R. (1994). Integrated Urban planning and governance: Is there a Barcelona model. International Planning Studies, 11(1), 35-42.

Rotmans, J., & Van Asslt, M. (2000). Policies and innovations in developing countries. Westport: Greenwood Praeger Press

Stead, D. (2015): What does the quality of governance imply for urban prosperity?. Habitat International, 45,64-69.

Wong, C. (2015): A framework for ‘City Prosperity Index’: Linking indicators, analysis and policy. Habitat International, 45, 3-9.

Yigitcanlar, T., Dur, F., & Dizdaroglu, D. (2015): Towards prosperous sustainable cities: A multiscalar urban sustainability assessment approach. Habitat International, 45, 36-46.

Ying, Y ., Shou, Y., & Wu, X. (2005). Empirical Analysis of Urban Management and Public Services in Chinese Cities. International Conference on Services Systems and Services Management , China.