PurposeThe purpose of this paper is to explore the impact of retailer personality on consumer‐based retailer equity.Design/methodology/approachThe authors developed a retailer personality scale and find its impact on consumer‐based retailer equity by adopting the scale developed by Pappu and Quester. A mall‐intercept survey was undertaken using a systematic sampling of department store shoppers of age 18 years and above in a metropolitan city, Kolkata, India. The questionnaire was used to collect data from seven department retail brands. The impact of each retailer personality dimension on each consumer‐based retailer equity dimension was explored, using structural equation modeling.FindingsThe study proposed a five‐dimensional scale to measure department store personality. Results indicated that the three dimensions of store personality, namely sophistication, dependability and empathy, have significant positive impact on each consumer‐based retailer equity dimension except one (empathy→retailer loyalty). The remaining two dimensions of retailer personality, namely authenticity and vibrancy, have no impact on each consumer‐based retailer dimension.Originality/valueThe paper is the first to propose a scale for measuring department store personality and to explore the link between retailer personality and consumer‐based retailer equity.

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The objective of this study was to explore the impact of store personality antecedents on store personality dimensions. A mall-intercept survey was undertaken using a systematic sampling of department store shoppers of age 18 years and above in Kolkata, a metropolitan city of India. Questionnaire was used to collect data from busy shopping malls or centres located in different places of Kolkata with systematic sampling. The impact of store personality antecedents on store personality dimensions was explored using stepwise regression analysis.Results revealed that different sets of store personality antecedent affect various department store personality dimensions differently. The impacts of all sets are positive and significant. Arguably, this article was the first to explore the link between store personality antecedents and store personality dimensions in Indian and department store personality contexts.

He has many publications in reputed international journals and has written books on Image processing and Machine leaning. His areas of expertise include data mining, machine learning, image processing, and business consultation.

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The importance of data mining techniques for market segmentation is becoming indispensable in the field of marketing research. This is the first identified academic literature review of the available data mining techniques related to market segmentation. This research paper provides surveys of the available literature on data mining techniques in market segmentation. A categorization has been provided based on the available data mining techniques used in market segmentation. Eight online journal databases were used for searching, and finally, 103 articles were selected and categorized into 13 groups based on data mining techniques. The utility of data mining techniques and suggestions are also discussed. The findings of this study show that neural networks is the most used method, and kernel-based method is the most promising data mining techniques. Our research work provides a comprehensive understanding of past, present as well as future research trend on data mining techniques in market segmentation. We hope this paper provides reasonable insight and clear understating to both industry as well as academic researchers.

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