Paradox of choice and sharing personal information

The purpose of this study is to investigate the relationship between a firm’s strategy and consumers’ decisions in the presence of the paradox of choice and sharing personal information. The paradox of choice implies that having too many choices does not necessarily ensure happiness and sometimes having less is more. A new model is constructed introducing a factor of information sharing into the model of a previous study that embedded the paradox of choice only (Kinjo and Ebina in AI Soc 30(2):291–297, 2015). A key feature of the model is its disutility function. It is demonstrated that if the sign of the cross derivative of the function is positive (negative) at the optimum, there is a positive (negative) correlation between the degree of sharing personal information chosen by the consumers and the number of products offered by the firm in its recommendation systems. It is also numerically indicated that the profit function of the firm becomes convex or concave depending on the shape of the disutility function. These results suggest that firms should carefully investigate the shape of the disutility function, under the paradox of choice and sharing personal information.

[1]  Timothy Van Zandt,et al.  Information Overload in a Network of Targeted Communication , 2001 .

[2]  P. Todd,et al.  Can There Ever Be Too Many Options? A Meta-Analytic Review of Choice Overload , 2010 .

[3]  Bradley J. Alge,et al.  Information privacy in organizations: empowering creative and extrarole performance. , 2006, The Journal of applied psychology.

[4]  Edith G. Smit,et al.  The privacy trade-off for mobile app downloads: The roles of app value, intrusiveness, and privacy concerns , 2018, Decis. Support Syst..

[5]  Vincent Koenig,et al.  How Acceptable Is This? How User Experience Factors Can Broaden our Understanding of The Acceptance of Privacy Trade-offs , 2020, Comput. Hum. Behav..

[6]  André Calero Valdez,et al.  The Users' Perspective on the Privacy-Utility Trade-offs in Health Recommender Systems , 2018, Int. J. Hum. Comput. Stud..

[7]  Kai Lung Hui,et al.  Consumer Privacy and Marketing Avoidance: A Static Model , 2008, Manag. Sci..

[8]  J. Borges,et al.  A TAXONOMY OF PRIVACY , 2006 .

[9]  Pietro Ortoleva,et al.  The price of flexibility: Towards a theory of Thinking Aversion , 2013, J. Econ. Theory.

[10]  Latanya Sweeney,et al.  k-Anonymity: A Model for Protecting Privacy , 2002, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[11]  Peter E. Rossi,et al.  Hierarchical Bayes Models , 2006 .

[12]  Antti Oulasvirta,et al.  When more is less: the paradox of choice in search engine use , 2009, SIGIR.

[13]  Yi-Cheng Ku,et al.  Personalized Content Recommendation and User Satisfaction: Theoretical Synthesis and Empirical Findings , 2006, J. Manag. Inf. Syst..

[14]  Robert E. Crossler,et al.  Privacy in the Digital Age: A Review of Information Privacy Research in Information Systems , 2011, MIS Q..

[15]  Mark de Reuver,et al.  A Consumer Perspective on Mobile Service Platforms: A Conjoint Analysis Approach , 2014, CAIS.

[16]  Cynthia Dwork,et al.  Differential Privacy , 2006, ICALP.

[17]  Jin Wang,et al.  Improved Collaborative Filtering Recommendation Algorithm Based on Differential Privacy Protection , 2018, MUE/FutureTech.

[18]  Curtis R. Taylor,et al.  The Economics of Privacy , 2016 .

[19]  M. Lepper,et al.  The Construction of Preference: When Choice Is Demotivating: Can One Desire Too Much of a Good Thing? , 2006 .

[20]  Mark S. Ackerman,et al.  Privacy in e-commerce: examining user scenarios and privacy preferences , 1999, EC '99.

[21]  Francisco J. Martínez-López,et al.  Psychological elements explaining the consumer's adoption and use of a website recommendation system: A theoretical framework proposal , 2010, Internet Res..

[22]  M. Lepper,et al.  When choice is demotivating: Can one desire too much of a good thing? , 2000 .

[23]  Paul A. Pavlou,et al.  State of the information privacy literature: where are we now and where should we go? , 2011 .

[24]  P. K. Kannan,et al.  The customer economics of internet privacy , 2002 .

[25]  Knut Liestøl,et al.  Generalized projection pursuit regression , 1998, SIAM J. Sci. Comput..

[26]  Yusufcan Masatlioglu,et al.  When more is less: Limited consideration , 2017, J. Econ. Theory.

[27]  Dietmar Jannach,et al.  Measuring the Business Value of Recommender Systems , 2019, ACM Trans. Manag. Inf. Syst..

[28]  Heng Xu,et al.  Information Privacy Research: An Interdisciplinary Review , 2011, MIS Q..

[29]  Mark P. Graus,et al.  Understanding the role of latent feature diversification on choice difficulty and satisfaction , 2016, User Modeling and User-Adapted Interaction.

[30]  Takeshi Ebina,et al.  Approaching the social dilemma of autonomous vehicles with a general social welfare function , 2021, Eng. Appl. Artif. Intell..

[31]  O. Günther,et al.  Privacy concerns and identity in online social networks , 2009 .

[32]  Mark P. Graus,et al.  Understanding choice overload in recommender systems , 2010, RecSys '10.

[33]  Kyohei Okumura,et al.  A Simple, Fast, and Safe Mediator for Congestion Management , 2020, AAAI.

[34]  G. Wolford,et al.  Buying Behavior as a Function of Parametric Variation of Number of Choices , 2007, Psychological science.

[35]  Hao Tang,et al.  Privacy Protection for Recommendation System: A Survey , 2019, Journal of Physics: Conference Series.

[36]  Komal Nagar,et al.  Exploring Choice Overload, Internet Shopping Anxiety, Variety Seeking and Online Shopping Adoption Relationship: Evidence from Online Fashion Stores , 2016 .

[37]  Yi-Cheng Ku,et al.  Consumer Preferences for the Interface of E-Commerce Product Recommendation System , 2014, HCI.

[38]  Takeshi Ebina,et al.  Consumer confusion from price competition and excessive product attributes under the curse of dimensionality , 2017, AI & SOCIETY.

[39]  Christine Legner,et al.  Understanding Users' Preferences for Privacy and Security Features - A Conjoint Analysis of Cloud Storage Services , 2019, BIS.

[40]  Spyros Kokolakis,et al.  Privacy attitudes and privacy behaviour: A review of current research on the privacy paradox phenomenon , 2017, Comput. Secur..

[41]  B. Schwartz The Paradox of Choice: Why More Is Less , 2004 .

[42]  Daniel J. Solove A Taxonomy of Privacy , 2006 .

[43]  Daniel R. Horne,et al.  Privacy attitudes and privacy-related behavior. , 2007 .

[44]  Yuan Li,et al.  Theories in online information privacy research: A critical review and an integrated framework , 2012, Decis. Support Syst..

[45]  Takeshi Ebina,et al.  Applying the peak‐end rule to decision‐making regarding similar products: A case‐based decision approach , 2021, Expert Syst. J. Knowl. Eng..

[46]  A. Chernev When More Is Less and Less Is More: the Role of Ideal Point Availability and Assortment in Consumer Choice This Research Argues That Choices from Different Size Assort- Ments Are a Function of the Degree to Which Consumers Have , 2022 .

[47]  Takeshi Ebina,et al.  Paradox of choice and consumer nonpurchase behavior , 2014, AI & SOCIETY.

[48]  Jari Vesanen What is personalization? A conceptual framework , 2007 .

[49]  Nicola Dimitri,et al.  The race for an artificial general intelligence: implications for public policy , 2018, AI & SOCIETY.

[50]  Jin Wang,et al.  Improved collaborative filtering recommendation algorithm based on differential privacy protection , 2018, The Journal of Supercomputing.