skip to main content
10.1145/2378104.2378113acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicecConference Proceedingsconference-collections
research-article

Demographic factors in assessing perceived risk in online shopping

Published: 03 August 2011 Publication History

Abstract

Research in online shopping was the focus of many studies as the age of electronic commerce began in the late 1990's. More recently, research in this area has declined, even as shopping on the Internet continues to increase and now dominates some product categories. This research offers a timely update on this literature by investigating online shopping from a perceived risk perspective. The results find that overall perceived risk is low with only some consumer concerns in psychological, time and performance risk. Analysis of perceived risk across six product categories and four demographic factors finds a significant level of perceived risk for lower income individuals when purchasing consumer electronics, but not in any other construct examined in this research. Overall, this study provides empirical evidence to substantiate the common perception that perceived risk in online shopping is declining and does not differ greatly across product category or demographic factor.

References

[1]
Bellman, S., Lahse, G. L., and Johnson, E. J. 1999. Predictors of online buying behavior, Communications of the ACM. 42, 12, 32--38.
[2]
Bhatnagar, A., Misra, S., and Rao, H. R. 2000. On risk, convenience, and internet shopping behavior. Communications of the ACM, 43, 11, 98--105.
[3]
Donthu, N. and Garcia, A. 1999. The internet shopper. Journal of Advertising Research. 39, 3, 52--58.
[4]
Doolin, B., Dillon, S., Thompson, F., and Corner, L. 2005. Perceived risk, the Internet shopping experience and online purchasing behavior: A New Zealand perspective, Journal of Global Information Management. 13, 2, 66--88.
[5]
Hyokjin, K., Fox, R. J., and Zinkhan, G. M. 2002. What products can be successfully promoted and sold via the Internet? Journal of Advertising Research. 42, 1, 23--38.
[6]
Introna, L. D. and Pouloudi, A. 1999. Privacy in the Information Age: Stakeholders, interests and values. Journal of Business Ethics. 22, 1, 27--38.
[7]
Jacoby, J. and Kaplan, L. B. 1972. The components of perceived risk, Proceedings of the Third Annual Conference of the Association for Consumer Research. Chicago, IL, 382--393.
[8]
Kaplan, L. B., Szybillo, G. J., and Jacoby, J. 1974. Components of perceived risk in product purchase: A cross-validation. Journal of Applied Psychology. 59, 3, 287--291.
[9]
Katz, J. and Aspden, P. 1997. Motivations for and barriers to Internet usage: Results of a national public opinion survey, Internet Research. 7, 3, 170--188.
[10]
Kim, D. J., Cho, B., and Rao, H. R. 2000. Effects of consumer lifestyles on purchasing behavior on the Internet: A conceptual framework and empirical validation, Proceedings of the 21st International Conference on Information Systems. December 10--13, Brisbane, Australia, 688--695.
[11]
Kim, D. J., Ferrin, D. L., and Rao, H. R. 2008. A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems. 44, 2, 544--564.
[12]
Li, H., Kuo, C., and Russell, M. G. 1999. The impact of perceived channel utilities, shopping orientations, and demographics on the consumer's online buying behavior, Journal of Computer-Mediated Communication. 5, 2, 1--20.
[13]
Liebermann, Y. and Stashevsky, S. 2002. Perceived risks as barriers to Internet and e-commerce usage, Qualitative Market Research: An International Journal. 5, 4, 291--300.
[14]
Miyazaki, A. D. and Fernandez, A. 2001. Consumer perceptions of privacy and security risks for online shopping, Journal of Consumer Affairs. 35, 1, 27--44.
[15]
Murray, K. B. and Schlacter, J. L. 1990. The impact of services versus goods on consumers' assessment of perceived risk and variability, Journal of the Academy of Marketing Science. 18, 1, 51--65.
[16]
Nielsen. 2008. Nielsen Online Retail Monitor - Quarter 1, 2008. http://nz.nielsen.com/news/documents/OnlineRetailMonitorQ4March09Final.pdf
[17]
Roselius, T. 1971. Consumer rankings of risk reduction methods, Journal of Marketing. 35, 1, 56--61.
[18]
Statistics New Zealand. not dated. Quickstats About Incomes. Retrieved 24 June, 2010, from http://www.statistics.govt.nz/Census/2006CensusHomePage/QuickStats/quickstats-about-a-subject/incomes/family-income.aspx.
[19]
Teo, S. H. T. 2001. Demographic and motivation variables associated with Internet usage activities, Internet Research. 11, 2, 125--137.
[20]
Ueltschy, L. C., Krampf, R. F., and Yannopoulos, P. 2004. A cross-national study of perceived consumer risk towards online (Internet) purchasing. Multinational Business Review. 12, 2, 59--82.

Cited By

View all
  • (2024)Demographic analysis of online grocery shopping during the COVID-19 pandemic: a theoretical perspective with an expanded technology acceptance modelCogent Business & Management10.1080/23311975.2024.233671211:1Online publication date: 23-Apr-2024
  • (2023)Analysis of the Consumer Perceptions of Online Shopping: Case of BangladeshAsian Business Review10.18034/abr.v13i1.65413:1(7-12)Online publication date: 30-Apr-2023
  • (2019)Consumer Purchase Intention toward Crowdfunding Products/Services: A Cost–Benefit PerspectiveSustainability10.3390/su1113357911:13(3579)Online publication date: 28-Jun-2019
  • Show More Cited By

Index Terms

  1. Demographic factors in assessing perceived risk in online shopping

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    ICEC '11: Proceedings of the 13th International Conference on Electronic Commerce
    August 2011
    261 pages
    ISBN:9781450314282
    DOI:10.1145/2378104
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 03 August 2011

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. demographics
    2. e-business
    3. e-commerce
    4. online shopping
    5. risk

    Qualifiers

    • Research-article

    Conference

    ICEC '11
    ICEC '11: 13th International Conference on Electronic Commerce
    August 3 - 5, 2011
    Liverpool, United Kingdom

    Acceptance Rates

    Overall Acceptance Rate 150 of 244 submissions, 61%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)11
    • Downloads (Last 6 weeks)2
    Reflects downloads up to 16 Feb 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2024)Demographic analysis of online grocery shopping during the COVID-19 pandemic: a theoretical perspective with an expanded technology acceptance modelCogent Business & Management10.1080/23311975.2024.233671211:1Online publication date: 23-Apr-2024
    • (2023)Analysis of the Consumer Perceptions of Online Shopping: Case of BangladeshAsian Business Review10.18034/abr.v13i1.65413:1(7-12)Online publication date: 30-Apr-2023
    • (2019)Consumer Purchase Intention toward Crowdfunding Products/Services: A Cost–Benefit PerspectiveSustainability10.3390/su1113357911:13(3579)Online publication date: 28-Jun-2019
    • (2017)No Such Thing as Too Much ChocolateProceedings of the 2017 CHI Conference on Human Factors in Computing Systems10.1145/3025453.3025778(4358-4369)Online publication date: 2-May-2017
    • (2017)Community CommerceProceedings of the 2017 CHI Conference on Human Factors in Computing Systems10.1145/3025453.3025550(4344-4357)Online publication date: 2-May-2017

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media