Investigating the Drivers of Knowledge-Based Growth Management Using Fuzzy MICMAC: A Case Study in Iran

Abstract

Attention to a city’s physical development is necessary for urban development plans. In Iran, the rapid physical expansion of cities in the form of unplanned and unbalanced growth due to various reasons, including indiscriminate migration, is considered a fundamental problem. This phenomenon is known as urban sprawl, which is one of the results of this type of growth. The research aims to identify and prioritize the indicators of the realization of knowledge-based growth management (KBGM) in the city of Tabriz, using foresight methods to analyze the effective drivers. The fuzzy linguistic MICMAC method was used to analyze mutual effects by converting linguistic variables into fuzzy numbers. In addition, using the theory of fuzzy sets for experts participating in research, the relationships between the 32 research variables were investigated. This research showed that the city of Tabriz had a scattered, isolated, fast, and unplanned growth, and it has relative compatibility. Despite the possibility of development within the limits of urban growth, most of the construction activities were outside the boundaries of urban growth. Key factors affecting the management of knowledge-based growth in Tabriz city were identified. Based on our findings, the university’s reputation, government effectiveness, urban competitiveness, city branding, quality of life, and strategic planning will impact the knowledge-based development process in Tabriz.