The purpose of this paper is to identify men’s clothing market segments based on store types and generational cohorts and the retail attributes.
A total of 2,808 US male consumer data from Predictive Analytics survey were analyzed with correspondence analysis (CA) (to identify segments based on store types and generations), general linear model (GLM) (to determine what retail attributes were important to target each segment) and a Rasch tree model (to test items of each factor in their relative importance).
The CA produced three segments: Segment 1 (Gen Y male consumers who frequently shop at specialty stores), Segment 2 (Gen X males who frequently shop at discount stores and online stores) and Segment 3 (Baby Boomers and Seniors who frequently shop at department stores). GLM shows that fundamentals were important to all segments; experiential was most important to Segment 1, while promotion was most important to Segment 3. Rasch tree analysis provided specific information on retail attributes for each store type and each generation.
Future research could employ both the importance and performance of retail attributes that are measured on a rating scale to understand consumers’ attitudes toward each retail format.
This study provided men’s clothing retailers with current insights into the male consumer segments based upon generational cohorts and store types from which they can better develop appropriate positioning strategies to satisfy the needs of each segment.
This study addressed the men’s clothing market, a growing but largely ignored market in the clothing industry and the retail literature.
Kim, Y.-K., Ha, S. and Park, S.-H. (2019), "Competitive analyses for men’s clothing retailers: segmentation and positioning", International Journal of Retail & Distribution Management, Vol. 47 No. 12, pp. 1266-1282. https://doi.org/10.1108/IJRDM-08-2018-0172
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