PreprintCited by 55Privacy, Security, and Data ProtectionInformation and Cyber SecurityInformation Technology Governance and Strategy

Control and Assurance in E-Commerce: Privacy, Integrity, and Security at Ebay

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Duh, Rong-Ruey, Sunder, Shyam, Jamal, Karim·2002·SSRN Electronic Journal

Abstract

Concern about privacy, integrity, and security of online transactions hampers absorption of e-commerce technologies as a normal way of doing business. To gain acceptance and trust of their participants, all organizations much achieve control or expectations equilibrium - a state where participants choose to do what others expect of them. Establishing control in e-commerce requires us to expand the traditional view of internal control to encompass the activities of customers, suppliers, and other "outside" users of their electronic platforms. We present a framework for analyzing control in online auctions. Privacy, authentication, and denial-of-service attacks are three classes of risk especially prevalent in e-commerce. Using the control practices of eBay as an illustrative example, we suggest possible ways of controlling these risks. Privacy, integrity, and security of online transactions demand new types of assurance services in e-commerce. We analyze assurance services available in 2002 and discuss challenges and opportunities facing existing services such as WebTrust. The merits of developing proprietary versus industry standards, and simple operational vertification of client-specific policies for e-commerce assurance services are also discussed.

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Research works printed but not linked: 14

  1. Black, H.C. 1976. Black's Law Dictionary. Revised Fourth Edition. West Publishing: St Paul, Minnesota.
  2. Carlton, J., and P.W. Tam. 2000. Online auctioneers face growing fraud problem. Wall Street Journal (Eastern Edition). May 12. p.B6.
  3. Cassady, R. 1967. Auctions and Auctioneering . University of California Press, Berkeley, CA.
  4. Dobrzynski, J.H. 2000. In online auction world, hoaxes aren't easy to see. (Late New York Edition). June 2. p.A1+. New York Times
  5. Elliot, R.K. 1998. Assurance services and the auditing heritage. Auditing: A Journal of Practice and Theory (supplement) . pp.1-7.
  6. Gode, D.K., and S. Sunder. 1997. What makes markets allocationally efficient? Quarterly Journal of Economics , Vol. CXII No. 2 (May 1997), pp. 603-630.
  7. Guidera, J. 2000. FTC, states target online-auction fraud. Wall Street Journal (Eastern Edition). February 15. p.B8.
  8. Jamal, K., M. Maier, and S. Sunder. 2002. Privacy in e-commerce: Reporting standards, disclosure practices and demand for audit sans government regulation. Presented at the Journal of Accounting Research Conference, University of Chicago.
  9. Lucking-Reiley, D. 1999b.Using field experiments to test equivalence between auction formats: Magic on the Internet. American Economic Review. December. pp.10631080.
  10. Porter, M.E. 2001. Strategy and the Internet. Harvard Business Review . March: 63 - 78. Ray, T. 2000. Trust in big business. Smartmoney.com . June 27. www.smartmoney.com/smt/columns/tech/index.cfm?story=200006271. http://www.smartmoney.com/smt/columns/tech/index.cfm?story=200006271
  11. Resnick, P., and R. Zeckhauser. 2001. Trust among strangers in Internart transactions: Empirical analysis of eBay's reputation system.Working Paper for NBER Workshop on Empirical Studies of Electronic Commerce. http://www.si.umich.edu/~presnick/papers/ebayNBER/index.html.
  12. Shapiro, C., and Hal R. Varian. 1999. Information Rules . Boston, MA: Harvard Business School Press.
  13. Simpson, G.R. 2000a. EBay site was raided by rival, FTC says. Wall Street Journal (Eastern Edition). January 7. p. B6.
  14. Standifird, S.S. 2001. Reputation and e-commerce: eBay auctions and the asymmetrical impact of positive and negative ratings. Journal of Management 27: 279-295.

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Authors
Duh, R.-R., Sunder, S., & Jamal, K.
Affiliations
  • National Taiwan University (TW)
  • Yale University (US)
  • University of Alberta (CA)
Corresponding author
Sunder, Shyam
Venue
SSRN Electronic Journal
Publisher
Elsevier BV
Published
2002
ISSN
1556-5068 (ISSN-L)
OpenAlex
W1894147963
Cited by
55
References
0
Citations by year
2025: 1 · 2023: 1 · 2021: 2 · 2020: 4 · 2019: 2 · 2018: 4 · 2017: 3 · 2016: 1 · 2015: 2 · 2014: 3 · 2013: 3 · 2012: 2
Type
posted content
Language
en
Open access
Locations
  • SSRN Electronic Journal (acceptedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
  • Physical Sciences › Computer Science › Information Systems › Information and Cyber Security
  • Social Sciences › Business, Management and Accounting › Management Information Systems › Information Technology Governance and Strategy
Keywords
e-commerce, internal control, assurance services, online auctions, eBay, privacy, data integrity, internet security, authentication, denial-of-service attacks, risk management, operational verification, trust in online transactions

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