Integrating cluster analysis with MCDM methods for the evaluation of local agricultural production

This study aims to cluster Turkish cities based on their local agricultural production and rank them in terms of performance by combining cluster analysis and multi-criteria decision-making (MCDM) methods. In this context, a three-phase methodology is developed. In the first phase, Ward's method is utilized to cluster cities according to agricultural production characteristics. In the second phase, the objective criteria weights are determined using the Criteria Importance Through Intercriteria Correlation technique (CRITIC). In the third phase, to rank the clusters in terms of performance, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is applied. Due to the results, the 81 cities are divided into six clusters in terms of agricultural production features. The cluster with the highest performance is Cluster 6, in which Konya is alone. Cluster 4, which includes Antalya and Mersin, follows this cluster. Cluster 1 with 25 cities and Cluster 2 with 19 cities are the clusters with the lowest results. The results show that only a few cities such as Konya, Antalya, and Mersin are generating more than tens of them in combination. These findings reveal that local governments should reconsider their agricultural programs and develop new strategies under the direction of the central government.

Automated summary

This study aims to cluster Turkish cities based on their local agricultural production and rank them in terms of performance using cluster analysis and MCDM methods. The results show that only a few cities such as Konya, Antalya, and Mersin are generating significant agricultural outputs, suggesting that local governments should reconsider their agricultural policies.