| Summary: | Today, there are more than 300 types of cars in Iran auto market, which has a significant growth in recent decade. High variety have challenges for decision makers in selecting cars. No mathematical model has been developed yet for segmenting and ranking Iran auto market, which carry out both defining automatic cluster numbers as well as automatic weighting criteria by the model.
This research develops a Hybrid DEMATEL-Two-Step Clustering-TOPSIS approach. The model first finds the beat appropriated criterion for segmentation. Then uses a two-step clustering approach for segmenting Iran auto market based on price criterion. Second, the criteria will be weighted automatically using Shannon entropy weighting method and then, TOPSIS method rank competitors in each defined price segment (lower 900 Million Rials). Also, the Spearman's rank correlation test is used to compare the model results with Iranian customer behavior (with selling volume). The price segmentation results reveal that the Iran auto market can be segmented in six different levels. Furthermore, the ranking results disclose that price is not the only effective factor in finding car utility for the buyer. A weighted combination of performance, features and price will determine optimized selection for buyers
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