Presenting the Optimal Model of Attracting Citizens' Participation in Urban Management, Case Study: Mashhad Metropolis

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Ghanavizchi Ali; Gorji Mohammad Bagher; Cheraghali Mahmoud Reza; Khayat Moghadam Saeed

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Journal Paper

Paper Information

Journal: JOURNAL OF DYNAMIC MANAGEMENT BUSINESS ANALYSIS Year:2024 | Volume:2 | Issue:4 Page(s): 112-127

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Title

Presenting the Optimal Model of Attracting Citizens' Participation in Urban Management, Case Study: Mashhad Metropolis

Author(s)

Ghanavizchi Ali | Gorji Mohammad Bagher | Cheraghali Mahmoud Reza | Khayat Moghadam Saeed | Issue Writer Certificate

Keywords

Optimal Model

citizen participation

Urban Management

Mashhad metropolis

Abstract

Participation is a voluntary and spontaneous process that causes the conflict of different citizen groups to solve issues and problems. The participation of citizens, while it can increase the probability of success of urban plans and projects, can be an effective factor in improving the quality of life in urban environments. This research seeks to provide an optimal model to attract citizens' participation for urban management activities. The present research is of applied type in terms of its purpose, which was carried out according to the quantitative-qualitative nature of the research using the descriptive-analytical method. In this research, firstly, using the exploratory approach and through the grounded theory method, the effective parameters on participation were identified, in the next step, using the fuzzy TOPSIS method, which is one of the methods of multi-criteria decision-making in conditions of uncertainty. The identified dimensions have been measured. The research results showed that in the open coding phase, 37 subcategories and 5 main categories (causal conditions, background conditions, strategies, intervening conditions, consequences) were identified from a total of 58 interviews. Also, based on the results of the research, the interactive and social spirit index of the component of the causal conditions with a score of 0.632 fuzzy weight ranks first among the research indicators.

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