Consumers’ privacy calculus: The PRICAL index development and validation |
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| Institution: | 1. Department of Marketing, Faculty Economics and Business, University of Groningen, Nettelbosje 2, 9747 AE Groningen, Netherlands;2. De Nieuwe Zaak, Hanzeallee 28, 8017 KZ Zwolle, Netherlands;3. Copenhagen Business School, Department of Marketing, Solbjerg Plads 3, Copenhagen 2000 Denmark;1. Rennes School of Business, 2 Rue Robert D''Arbrissel – CS 76522, 35065 Rennes, France;2. Grenoble Ecole de Management, 12 Rue Pierre Semard, 38000 Grenoble, France;1. University of Amsterdam Business School, Plantage Muidergracht 12, 1018 TV Amsterdam, the Netherlands;2. Tilburg University, Warandelaan 2, 5037 AB Tilburg, the Netherlands;3. UNC-Chapel Hill, Chapel Hill, NC, USA;1. Rotman School of Management at the University of Toronto, 105 St. George Street, Toronto, Ontario, Canada;2. China Europe International Business School, 699 Hongfeng Road, Pudong, Shanghai 201206, China;1. Old Dominion University, Strome College of Business, Department of Marketing, 2055 Constant Hall, Norfolk, VA 23529, United States;2. Old Dominion University, Strome College of Business, Department of Marketing, 2117 Constant Hall, Norfolk, VA 23529, United States;3. University of Mississippi, Ole Miss Business School, Department of Marketing, 235 Holman Hall University, MS 38677, United States;4. Old Dominion University, Strome College of Business, Department of Marketing, Constant Hall, Norfolk, VA 23529, United States;1. University of Southern, Denmark;2. Brunel Business School, United Kingdom |
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| Abstract: | Although collecting personal information about consumers is crucial for firms and marketers, understanding of when and why consumers accept or reject information collection remains limited. The authors conceptualize a privacy calculus that represents a consumer’s trade–off of the valence and uncertainty of the consequences of the collection, storage, and use of personal information. For example, usage-based car insurance requires drivers to share data on their driving behavior in exchange for a discount (certain benefit) but at the risk of third parties intercepting location data for malicious use (uncertain disadvantage). Building on this conceptualization, the authors develop the privacy calculus (PRICAL) index. They empirically confirm the validity of the items (Study 1) and the index as a whole (Study 2). The PRICAL index is generally applicable and improves the explanation of behavioral intentions (Study 2) and actual behavior (Study 3), compared with currently used constructs (e.g., privacy concern, trust). Overall, the PRICAL index allows managers to understand consumers’ acceptance of information collection regarding financial, performance, psychological, security, social, and time-related consequences, which the authors demonstrate using the top five most valuable digital brands (Study 4). |
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| Keywords: | Privacy Privacy calculus Information collection Index development |
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