A Model of Portal Competition in the Presence of Privacy Concerns: Strategic and Welfare Implications
نویسندگان
چکیده
The revenue model of online portals is based on access to consumers and their preference information through offerings of “free” personalized services. Extant research has characterized consumer behavior in this context by a personalization for privacy (p4p) ratio, which represents consumer’s tradeoff between value for personalized services and nonmonetary privacy costs incurred in sharing their preference information. In determining the optimal level of services, two factors affect a portal’s personalization strategy: its marginal value for preference information (MVI) and its ability to enforce consumers’ usage of services. Counter to intuition, our results show that a monopolist is indifferent to enforcement abilities, even if social welfare is strictly higher in the absence of enforcement. Our duopoly model reveals that when portals do not enforce services usage, a symmetric equilibrium exists if and only if the MVI of both portals is high and no equilibrium is found otherwise. On the other hand, when portals enforce services usage there are two possible outcomes: (1) an asymmetric equilibrium exists if one portal has high marginal value for information and the other has sufficiently lesser MVI, and (2) a symmetric equilibrium exists if and only if both portals have high MVI. We discuss our results in light of portals’ usage enforcement and from the perspective of a regulator who is interested in social welfare in the presence of privacy concerns.
منابع مشابه
A model of advertiser - portal contracts: Personalization strategies under privacy concerns
Online portals provide personalization for “free” since the information acquired from consumers’ usage of these services is valuable for advertising and targeted marketing purposes. Consumers’ usage of services is determined by the tradeoff between their marginal value for personalized services and the resulting information privacy concerns and is captured by their personalization for privacy (...
متن کاملAnalyzing Tools and Algorithms for Privacy Protection and Data Security in Social Networks
The purpose of this research, is to study factors influencing privacy concerns about data security and protection on social network sites and its’ influence on self-disclosure. 100 articles about privacy protection, data security, information disclosure and Information leakage on social networks were studied. Models and algorithms types and their repetition in articles have been distinguished a...
متن کاملDifferentially Private Local Electricity Markets
Privacy-preserving electricity markets have a key role in steering customers towards participation in local electricity markets by guarantying to protect their sensitive information. Moreover, these markets make it possible to statically release and share the market outputs for social good. This paper aims to design a market for local energy communities by implementing Differential Privacy (DP)...
متن کاملAn Architecture for Security and Protection of Big Data
The issue of online privacy and security is a challenging subject, as it concerns the privacy of data that are increasingly more accessible via the internet. In other words, people who intend to access the private information of other users can do so more efficiently over the internet. This study is an attempt to address the privacy issue of distributed big data in the context of cloud computin...
متن کاملAnalysis and Evaluation of Privacy Protection Behavior and Information Disclosure Concerns in Online Social Networks
Online Social Networks (OSN) becomes the largest infrastructure for social interactions like: making relationship, sharing personal experiences and service delivery. Nowadays social networks have been widely welcomed by people. Most of the researches about managing privacy protection within social networks sites (SNS), observes users as owner of their information. However, individuals cannot co...
متن کامل