Quality-adjusted consumer surplus for online labor markets with asymmetric information

Yili Hong, Paul A. Pavlou, Pei-yu Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Traditional measures of consumer surplus (CS) have implicitly assumed that the quality expected is the same as the quality that is paid for ex ante. However, when product or service quality cannot be perfectly verified ex ante by consumers in markets with asymmetric information, and actual quality received may not necessarily equal quality expected, CS would not be precisely measured. In this paper, we propose a quality-adjusted measure of CS for IT outsourcing e-markets with asymmetric information. We first relax the assumption that consumers always receive the quality they expect ex ante. Second, we leverage expectationconfirmation theory to construct the utility function to derive the proposed quality-adjusted measure of CS. Measurement development is followed by an empirical study of the effects of different measures of CS. We found the quality-adjusted measure better predicts market outcomes, i.e., continuation, subsequent projects and payments.

Original languageEnglish (US)
Title of host publicationInternational Conference on Information Systems (ICIS 2013)
Subtitle of host publicationReshaping Society Through Information Systems Design
Pages3240-3258
Number of pages19
StatePublished - 2013
EventInternational Conference on Information Systems, ICIS 2013 - Milan, Italy
Duration: Dec 15 2013Dec 18 2013

Publication series

NameInternational Conference on Information Systems (ICIS 2013): Reshaping Society Through Information Systems Design
Volume4

Other

OtherInternational Conference on Information Systems, ICIS 2013
Country/TerritoryItaly
CityMilan
Period12/15/1312/18/13

Keywords

  • Asymmetric information
  • Consumer surplus
  • Market performance
  • Online labor markets

ASJC Scopus subject areas

  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Applied Mathematics
  • Library and Information Sciences

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