Privacy calculus and its utility for personalization services in e-commerce

An analysis of consumer decision-making

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Modern consumers increasingly embrace the personalization of services. Whether to disclose private information to companies for the sake of receiving personalized service is largely contingent to relative valuations and the utility of private information. Unfortunately, there is a lack of balanced research that analyzes and reconciles the contradiction between privacy and personalization service. In this study, based on the multi-attribute utility theory (MAUT), we introduce a utility model of privacy in personalization. Our simulation results validate our white-box utility model by demonstrating significant distinctions of calculating benefits and costs among three groups of consumers.
Original languageEnglish
Pages (from-to)427-437
JournalInformation & Management
Volume54
Issue number4
DOIs
Publication statusPublished - Jun 2017

Fingerprint

Decision making
Costs
Industry
Electronic commerce
Personalization
Consumer decision making
Privacy
Private information
Costs and benefits
Multi-attribute utility theory
Simulation
Relative valuation

Keywords

  • privacy calculus
  • personalization service
  • multi-attribute utility theory (MAUT)
  • trade-off
  • consumer preferences
  • fuzzy logic

Cite this

@article{d310339054ea4858bd54d2bd97276414,
title = "Privacy calculus and its utility for personalization services in e-commerce: An analysis of consumer decision-making",
abstract = "Modern consumers increasingly embrace the personalization of services. Whether to disclose private information to companies for the sake of receiving personalized service is largely contingent to relative valuations and the utility of private information. Unfortunately, there is a lack of balanced research that analyzes and reconciles the contradiction between privacy and personalization service. In this study, based on the multi-attribute utility theory (MAUT), we introduce a utility model of privacy in personalization. Our simulation results validate our white-box utility model by demonstrating significant distinctions of calculating benefits and costs among three groups of consumers.",
keywords = "privacy calculus, personalization service, multi-attribute utility theory (MAUT), trade-off, consumer preferences, fuzzy logic",
author = "H. Zhu and Carol Ou and {van den Heuvel}, Willem-Jan and H.W. Liu",
year = "2017",
month = "6",
doi = "10.1016/j.im.2016.10.001",
language = "English",
volume = "54",
pages = "427--437",
journal = "Information & Management",
issn = "0378-7206",
publisher = "Elsevier",
number = "4",

}

Privacy calculus and its utility for personalization services in e-commerce : An analysis of consumer decision-making. / Zhu, H.; Ou, Carol; van den Heuvel, Willem-Jan; Liu, H.W.

In: Information & Management, Vol. 54, No. 4, 06.2017, p. 427-437.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Privacy calculus and its utility for personalization services in e-commerce

T2 - An analysis of consumer decision-making

AU - Zhu, H.

AU - Ou, Carol

AU - van den Heuvel, Willem-Jan

AU - Liu, H.W.

PY - 2017/6

Y1 - 2017/6

N2 - Modern consumers increasingly embrace the personalization of services. Whether to disclose private information to companies for the sake of receiving personalized service is largely contingent to relative valuations and the utility of private information. Unfortunately, there is a lack of balanced research that analyzes and reconciles the contradiction between privacy and personalization service. In this study, based on the multi-attribute utility theory (MAUT), we introduce a utility model of privacy in personalization. Our simulation results validate our white-box utility model by demonstrating significant distinctions of calculating benefits and costs among three groups of consumers.

AB - Modern consumers increasingly embrace the personalization of services. Whether to disclose private information to companies for the sake of receiving personalized service is largely contingent to relative valuations and the utility of private information. Unfortunately, there is a lack of balanced research that analyzes and reconciles the contradiction between privacy and personalization service. In this study, based on the multi-attribute utility theory (MAUT), we introduce a utility model of privacy in personalization. Our simulation results validate our white-box utility model by demonstrating significant distinctions of calculating benefits and costs among three groups of consumers.

KW - privacy calculus

KW - personalization service

KW - multi-attribute utility theory (MAUT)

KW - trade-off

KW - consumer preferences

KW - fuzzy logic

U2 - 10.1016/j.im.2016.10.001

DO - 10.1016/j.im.2016.10.001

M3 - Article

VL - 54

SP - 427

EP - 437

JO - Information & Management

JF - Information & Management

SN - 0378-7206

IS - 4

ER -