Utilization of Conjoint Analysis in Understanding Consumer Preferences for Footwear

Abstract

This study was carried out to analyze the importance of using consumer preferences while stocking footwear by the retailer. Consumer stated preference data was collected in five footwear retail stores. A saturated sampling method was followed. A total of 425 data was collected. The collected consumer preference data was analyzed using conjoint analysis. This resulted in the importance score and utility score for various features of footwear. These scores are useful in estimating the consumer preferences in footwear. The results are estimated using a maximum utility model. The footwear retailers can make use these results in forecasting and stocking decisions for footwear.