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When and how consumers are willing to exchange data with retailers: An exploratory segmentation
Affiliation:1. Sauder School of Business, University of British Columbia (UBC), Vancouver, British Columbia, V6T 1Z2, Canada;2. Rowe School of Business, Dalhousie University, Halifax, NS, B3H 4R2, Canada;1. Ehrenberg-Bass Institute, UniSA Business, University of South Australia, City West Campus Level 4, Yungondi Building, North Terrace Adelaide, SA 5000, Australia;2. Massey University, Auckland, New Zealand;1. Faculty of Economics and Business Administration, Ruppin Academic Center, Emek Hefer, 4025000, Israel;2. Paris School of Business, France;1. Operation Management Group, Indian Institute of Management Ranchi, Ranchi, Jharkhand, India;2. Operation Management Group, Indian Institute of Management Calcutta, Kolkata, West Bengal, India;3. Trinity Business School, Trinity College Dublin, Ireland
Abstract:Consumer data is a crucial resource for retailers. Yet accessing this data increasingly requires consumers to willingly participate in data exchange. This paper draws on social exchange theory and privacy calculus to investigate differences in consumer willingness to exchange data with retailers. Consumers are also profiled on their perceptions of retailer's use and abuse of data, along with the antecedents and outcomes of these perceptions. We employ a cross-sectional quantitative survey and collect data from a sample of 463 US consumers. For statistical analysis, we employ a latent class segmentation and identify six consumer segments which differ in their perceptions of the consumer-retailer data exchange. The key drivers of these segment differences include privacy concerns, technology readiness, and general trust of, and engagement with, retail brands. The segments also differ in their subsequent views towards the use and abuse of their data by retailers, including willingness to exchange data. Hence, when accessing and utilizing consumer data, it is important that brands identify different segments, and adapt their approach accordingly.
Keywords:Consumer data  Data exchange  Data privacy  Privacy calculus  Personalization
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