Masuyama, Ryo (2023): Endogenous privacy and heterogeneous price sensitivity.
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Abstract
This study analyzes a model in which two firms, one with profiling technology and one without, compete for old and new markets. In the old market, consumers leave their personal information online, whereas, in the new market, consumers do not. When a firm with profiling technology observes consumers' personal information, it sets personalized prices for them. Additionally, consumers can conceal their personal information by paying privacy costs. We introduce heterogeneity in price sensitivities among consumers into our model. We obtain the following result. For greater heterogeneity in price sensitivities, consumer and total surpluses are maximized with no privacy cost; for lower heterogeneity, a sufficiently high privacy cost is desirable for consumers and society; for intermediate heterogeneity, while consumers prefer no privacy cost, total surplus is maximized at a sufficiently high privacy cost. Therefore, when deciding on privacy policy, authorities should consider the heterogeneity in price sensitivities.
Item Type: | MPRA Paper |
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Original Title: | Endogenous privacy and heterogeneous price sensitivity |
Language: | English |
Keywords: | personalized pricing; privacy; personal information; heterogeneous consumers; Hotelling model |
Subjects: | D - Microeconomics > D4 - Market Structure, Pricing, and Design > D43 - Oligopoly and Other Forms of Market Imperfection L - Industrial Organization > L1 - Market Structure, Firm Strategy, and Market Performance > L10 - General L - Industrial Organization > L1 - Market Structure, Firm Strategy, and Market Performance > L13 - Oligopoly and Other Imperfect Markets |
Item ID: | 117316 |
Depositing User: | Ryo Masuyama |
Date Deposited: | 15 May 2023 14:34 |
Last Modified: | 15 May 2023 14:34 |
References: | Acquisti, A. & Varian, H. R. (2005) Conditioning prices on purchase history. Marketing Science, 24(3), 367–381. Acquisti, A., Taylor, C., & Wagman, L. (2016) The economics of privacy. Journal of Economic Literature, 54(2), 442–492. Casadesus-Masanell, R. & Hervas-Drane, A. (2015) Competing with privacy. Management Science, 61(1), 229–246. Choe, C., King, S., & Matsushima, N. (2018) Pricing with cookies: Behavior-based price discrimination and spatial competition. Management Science, 64(12), 5669–5687. Choe, C., Matsushima, N., & Tremblay, M. J. (2022) Behavior-based personalized pricing: When firms can share customer information. International Journal of Industrial Organization, 82, 102846. Conitzer, V., Taylor, C., & Wagman, L. (2012) Hide and seek: Costly consumer privacy in a market with repeat purchases. Marketing Science, 31(2), 277–292. Coughlan, A. T. & Soberman, D. A. (2005) Strategic segmentation using outlet malls. International Journal of Research in Marketing, 22(1), 61–86. Dedehayir, O., Ortt, R. J., Riverola, C., & Miralles, F. (2017) Innovators and early adopters in the diffusion of innovations: A literature review. International Journal of Innovation Management, 21(8), 1740010. Douglas, E. M. (2021) The new antitrust/data privacy law interface. Yale Law Journal Forum, 130, 647–684. Esteves, R. B. (2009) A survey on the economics of behaviour-based price discrimination. NIPE Working paper. Esteves, R. B. (2010) Pricing with customer recognition. International Journal of Industrial Organization, 28(6), 669–681. Esteves, R. B. (2022) Can personalized pricing be a winning strategy in oligopolistic markets with heterogeneous demand customers? Yes, it can. International Journal of Industrial Organization, 85, 102874. Fudenberg, D. & Tirole, J. (2000) Customer poaching and brand switching. RAND Journal of Economics, 31(4), 634–657. Fudenberg, D. & Villas-Boas, J. (2006) Behavior-based price discrimination and customer recognition. Handbook on Economics and Information Systems, 1, 377–436. Fudenberg, D. & Villas-Boas, J. (2012) Price discrimination in the digital economy. Oxford Handbook of the Digital Economy, 254–272. Goldsmith, R. E. & Newell, S. J. (1997) Innovativeness and price sensitivity: Managerial, theoretical and methodological issues. Journal of Product & Brand Management, 6(3), 163–174. Ishibashi, I. & Matsushima, N. (2009) The existence of low-end firms may help high-end firms. Marketing Science, 28(1), 136–147. Jin, G. Z. & Wagman, L. (2021) Big data at the crossroads of antitrust and consumer protection. Information Economics and Policy, 54, 100865. Koh, B., Raghunathan, S., & Nault, B. R. (2017) Is voluntary profiling welfare enhancing? Management Information Systems Quarterly, 41(1), 23–42. Mattioli, D. (2012) On Orbitz, Mac users steered to pricier hotels. Wall Street Journal, (August 23), http://online.wsj.com/article/SB10001424052702304458604577488822667325882.html Mehra, A., Sajeesh, S., & Voleti, S. (2020) Impact of reference prices on product positioning and profits. Production and Operations Management, 29(4), 882-892. Montes, R., Sand-Zantman, W., & Valletti, T. (2019) The value of personal information in online markets with endogenous privacy. Management Science, 65(3), 1342–1362. Rogers, E.M. (1983) Diffusion of Innovations, 3rd ed., The Free Press, New York, NY. Shaffer, G. & Zettelmeyer, F. (2004) Advertising in a distribution channel. Marketing Science, 23(4), 619–628. Shaffer, G. & Zhang, Z. J. (2002) Competitive one-to-one promotions. Management Science, 48(9), 1143–1160. Shy, O. & Stenbacka, R. (2016) Customer privacy and competition. Journal of Economics & Management Strategy, 25(3), 539–562. Taylor, C. (2004) Consumer privacy and the market for customer information. RAND Journal of Economics, 35(4), 631–650. Taylor, C. & Wagman, L. (2014) Consumer privacy in oligopolistic markets: Winners, losers, and welfare. International Journal of Industrial Organization, 34, 80–84. Thisse, J. F. & Vives, X. (1988) On the strategic choice of spatial price policy. American Economic Review, 78(1), 122–137. Valletti, T. & Wu, J. (2020) Consumer profiling with data requirements: Structure and policy implications. Production and Operations Management, 29(2), 309–329. Vestager, M. (2019) Defending competition in a digitised world, European Consumer and Competition Day, Bucharest, 4 April, https://wayback.archive-it.org/12090/20191129202059/https://ec.europa.eu/commission/commissioners/2014-2019/vestager/announcements/defending-competition-digitised-world_en Villas-Boas, J. (1999) Dynamic competition with customer recognition. RAND Journal of Economics, 30(4), 604–631. Villas-Boas, J. (2004) Price cycles in markets with customer recognition. RAND Journal of Economics, 35(3), 486–501. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/117316 |
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