Mapping innovation: A strategic framework and entropy-based fuzzy c-means analysis for regional economic growth in Türkiye

Abstract

Innovation is crucial for national economies to drive growth and sustainability. Analyzing and interpreting a regional economy’s current state requires a systematic, data-driven strategy. This study presents a strategic framework to address these challenges, focusing on 81 provinces in Türkiye. The framework comprises three stages. In the first phase of the analysis, we evaluated the innovation indicators, which include intellectual property data. We also considered economic indicators, specifically gross domestic product, the number of workplaces, and the number of universities. The second phase of the framework involves applying the entropy weight method to determine the weights of each indicator. Ultimately, we calculate the innovation index using the derived weights and the dataset employed in the study. The fuzzy c-means approach groups provinces based on the representative innovation index. After reviewing the results, we found that Istanbul belongs to the first cluster. The second cluster includes Ankara, Bursa, and Izmir, whereas the third cluster comprises Kocaeli, Konya, Kayseri, Antalya, and Gaziantep. This study can provide useful insights for developing regional policies and strategies by identifying provinces with a strong innovation capacity and good economic performance.

Keywords

• Entropy weight method
• Fuzzy c-means
• Innovation index
• Regional economic growth

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