Online Price Search: Impact of Price Comparison Sites on Offline Price Evaluations |
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| Affiliation: | 1. Associate Professor, Concordia University, Marketing Department, 1455 De Maisonneuve Blvd. W., Montreal, QC H3G 1M8, Canada;2. Associate Professor Emeritus, Virginia Tech., Department of Marketing, 2016 Pamplin Hall, Blacksburg, VA 24061-0236, USA;3. John P. Morgridge Chair in Business Administration, Marketing Department, University of Wisconsin-Madison, 975 University Avenue, Madison, WI 53706, USA;1. Owen Graduate School of Management, Vanderbilt University, Nashville, TN 37203, United States;2. Jindal School of Management, The University of Texas at Dallas, Richardson, TX 75080, United States;3. School of Business, Renmin University of China, Beijing, China;1. Department of Marketing, University of Texas at San Antonio, 1 UTSA Circle, San Antonio, TX 78249, United States;2. Department of Marketing, London School of Economics and Political Science, Houghton Street, NAB 5.13, London WC2A 2AE, United Kingdom;3. Darla Moore School of Business, University of South Carolina, 1014 Greene Street, Columbia, SC 29208, United States;4. School of Business Administration, University of California, Riverside, CA, United states;1. Graduate School of Business, Fordham University, United States;2. Department of Marketing & Supply Chain Management, Fogelman College of Business and Economics, The University of Memphis, Memphis, TN 38152, United States;3. Industrial Marketing Unit, Department of Industrial Economics & Management, School of Industrial Engineering and Management, Royal Institute of Technology, Lindstedtsvägen, Stockholm, Sweden;1. Department of Business Administration, University Pablo de Olavide, Ctra. Utrera, Km. 1, 41013 Sevilla, Spain;2. Department of Marketing, Faculty of Economics and Business, University of Zaragoza, Gran Vía 2, 50005 Zaragoza, Spain;3. Department of Marketing, Faculty of Economics and Business, University of Zaragoza, C/ María de Luna, s/n, 50018 Zaragoza, Spain;1. Marketing Department, Marshall School of Business, University of Southern California, 3660 Trousdale Parkway, Room ACC 306E, Los Angeles, CA 90089-0443, United States;2. Marketing and Consumer Behaviour Group, Wageningen University, Postbus 8130, 6700 EW Wageningen, The Netherlands;3. Marketing Department, Katz Graduate School of Business, University of Pittsburgh, 364 Mervis Hall, Pittsburgh, PA 15260, United States;1. Computer Science Department, Bar-Ilan University, Ramat-Gan 52900, Israel;2. Department of Computer Science and Mathematics, Ariel University, Ariel 40700, Israel |
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| Abstract: | Consumers increasingly rely on Internet price comparison sites (PCS) to gain knowledge about the market. The prices generated by a PCS search can act as contextual reference prices and influence the attractiveness of prices encountered later as consumers shop offline at local stores. This paper demonstrates that both PCS retailer ratings and the shape of the PCS price distribution influence the impact of PCS search results on later price evaluations. A favorable PCS retailer rating increases the perceived validity of the price associated with that retailer, enhancing the impact of that PCS price on offline price evaluations (Study 1). The shape of the PCS price distribution can also influence later price evaluations, however this effect depends on the information provided by the PCS retailer ratings. When PCS retailer ratings are similar, implying similar validity for the associated prices, low PCS prices and those appearing more frequently in the PCS price distribution have more impact (Studies 2 and 3). When PCS retailer ratings are variable (some high and some low), the PCS price distribution effect occurs only when the PCS retailer ratings provide congruent information about price validity — that is, the most frequent price is offered by retailers with more favorable ratings. Study 3 shows that price validity inferences do mediate this result. Finally, we depart from the offline shopping context to show that when consumers choose a retailer directly from the PCS search results, the effect of PCS retailer ratings is stronger for high-priced retailers and for consumers who rely less on the retailer price as a heuristic to infer retailer service level. Based on our findings we offer insights for online and offline retailers when considering strategic responses, such as price matching guarantees. |
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| Keywords: | Online price search Multiple reference prices Price validity Retailer quality Price comparison site Online retailer choice |
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