Customer based Discrepancy Theory

From IS Theory
Jump to: navigation, search

Customer based Discrepancy Theory

The basis of discrepancy theory–derived satisfaction is the cognitive comparison on the part of an individual. A comparison requires that each individual establish an anchor, have a context-dependent state of nature to compare to the anchor, realize individual expectations or perceptions of both the anchor and state of nature, and judge these with a (potentially) complex relationship that determines how satisfaction is derived from the two components (anchor and state of nature).[1]

Customer satisfaction with IS, this is a stream of research draws from both marketing and management disciplines.Satisfaction is considered by many researchers to be the effect of a judgment of the difference between what is expected or desired compared to what is actually experienced about a product or service . Discrepancy theory research, is the study of this difference between an a prior state and subsequent perception.[1]

The literature in consumer satisfaction provides a general framework for the examination of how perceptions of delivery and expectations can impact user satisfaction . Consumer satisfaction is commonly defined as a “post-choice evaluation which varies along a hedonic continuum from unfavorable to favorable, in terms of whether or not the experience of a specific purchase was at least as good as it was supposed to be”. [1]

User satisfaction has been measured in terms of attitude , perceived information value and quality, and perceived improvements in decision-making effectiveness.[1]


Main dependent constructs/factors

Customer satisfaction and User satisfaction.


Main independent construct(s)/factor(s)

Manipulated expectations, Manipulated performance, Perceived performance, Perceived Expectations, Dis-conformation (or) Confirmation of expectations.


Diagram/schematic of theory

Churchill Jr, G. A., & Surprenant, C. (1982). An investigation into the determinants of customer satisfaction. Journal of marketing research, 491-504. [2]

Originating author(s)

Locke,Michalos, Oliver and Rice


Seminal articles

Michalos, A. C. (1985). Multiple discrepancies theory (MDT). Social indicators research16(4), 347-413.[3]

Oliver, R. L. (1981). Measurement and evaluation of satisfaction processes in retail settings. Journal of retailing.[4]

Rice, R. W., McFarlin, D. B., & Bennett, D. E. (1989). Standards of comparison and job satisfaction. Journal of Applied Psychology74(4), 591.[5]

Locke, E. A. (1969). What is job satisfaction?. Organizational behavior and human performance4(4), 309-336.[6]

Szymanski, D. M., & Henard, D. H. (2001). Customer satisfaction: A meta-analysis of the empirical evidence. Journal of the academy of marketing science29(1), 16-35.[7]

Churchill Jr G, Surprenant C. An investigation into the determinants of customer satisfaction. Journal of Marketing Research. 1982;19(4):491–504[2]


Originating area

Management and Marketing


Links from this theory to other theory

Expectation conformation theory


Level of analysis

Individual customers


IS articles that use the theory

Ang J, Soh P. User information satisfaction, job satisfaction and computer background: An exploratory study. Information Management. 1997;32(5):255.[8]

Au N, Ngai E, Cheng T. Extending the understanding of end user information systems satisfaction formation: An equitable needs fulfillment model approach. MIS Quarterly. 2008;32(1):43–66.[9]

Baroudi J, Orlikowski W. A short-form measure of user information satisfaction: A psychometric evaluation and notes on use. Journal of Management Information Systems. 1988;4(4):44–59.[10]

Bergeron F, Berube C. The management of the end-user environment: An empirical investigation. Information Management. 1988;14(3):107–113.[11]

Bhattacherjee A. Understanding information systems continuance: An expectation-confirmation model. Management Information Systems Quarterly. 2001;25(3):351–370.[12]

Bhattacherjee A, Premkumar G. Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. Management Information Systems Quarterly. 2004;28(2):229–254.[13]

Chin WW, Lee MKO. A proposed model and measurement instrument for the formation of IS satisfaction: The case of end-user computing satisfaction. Proceedings of the 21st International Conference on Information Systems, Atlanta, GA; 2000. p. 553–563.[14]

Chiou WC, Lin CC, Perng C (2010). A strategic framework for website evaluation based on a review of the literature from 1995~2006. Information & Management. Accessed 4 June 2010.[15]

Davis F. Perceived usefulness, perceived ease of use, and user acceptance of information technology. Management Information Systems Quarterly. 1989;13(3):318–339.[16]

DeLone W, McLean E. Information systems success: The quest for the dependent variable. Information Systems Research. 1992;3(1):60–95.[17]

DeLone W, McLean E. The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems. 2003;19(4):9–30.[18]

Doll W, Torkzadeh G. The measurement of end-user computing satisfaction. Management Information Systems Quarterly. 1988;12(2):259–274.[19]

Edwards J. The study of congruence in organizational behavior research: Critique and a proposed alternative. Organizational Behavior and Human Decision Processes. 1994;58(1):51–100.[20]

Emmons RA, Diener E. Factors predicting satisfaction judgements: A comparative examination. Social Indicators Research. 1985;16:157–167.[21]

Erevelles S, Srinivasan S, Rangel S. Consumer satisfaction for internet service providers: An analysis of underlying processes. Information Technology and Management. 2003;4(1):69–89.[22]

Gallagher C. Perceptions of the value of a management information system. Academy of Management Journal. 1974;17(1):46–55.[23]

Griffith T, Northcraft G. Cognitive elements in the implementation of new technology: Can less information provide more benefits? Management Information Systems Quarterly. 1996;20(1): 99–110.[24]


External links


Original Contributor(s)


  1. 1.0 1.1 1.2 1.3 Dwivedi, Y. K., Wade, M. R., & Schneberger, S. L. (Eds.). (2011). Information Systems Theory: Explaining and Predicting Our Digital Society (Vol. 1). Springer Science & Business Media.)
  2. 2.0 2.1 Churchill Jr, G. A., & Surprenant, C. (1982). An investigation into the determinants of customer satisfaction. Journal of marketing research, 491-504.
  3. Michalos, A. C. (1985). Multiple discrepancies theory (MDT). Social indicators research16(4), 347-413.
  4. Oliver, R. L. (1981). Measurement and evaluation of satisfaction processes in retail settings. Journal of retailing.
  5. Rice, R. W., McFarlin, D. B., & Bennett, D. E. (1989). Standards of comparison and job satisfaction. Journal of Applied Psychology74(4), 591.
  6. Locke, E. A. (1969). What is job satisfaction?. Organizational behavior and human performance4(4), 309-336.
  7. Szymanski, D. M., & Henard, D. H. (2001). Customer satisfaction: A meta-analysis of the empirical evidence. Journal of the academy of marketing science29(1), 16-35.
  8. Ang J, Soh P. User information satisfaction, job satisfaction and computer background: An exploratory study. Information Management. 1997;32(5):255.
  9. Au N, Ngai E, Cheng T. Extending the understanding of end user information systems satisfaction formation: An equitable needs fulfillment model approach. MIS Quarterly. 2008;32(1):43–66.
  10. Baroudi J, Orlikowski W. A short-form measure of user information satisfaction: A psychometric evaluation and notes on use. Journal of Management Information Systems. 1988;4(4):44–59.
  11. Bergeron F, Berube C. The management of the end-user environment: An empirical investigation. Information Management. 1988;14(3):107–113
  12. Bhattacherjee A. Understanding information systems continuance: An expectation-confirmation model. Management Information Systems Quarterly. 2001;25(3):351–370.
  13. Bhattacherjee A, Premkumar G. Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. Management Information Systems Quarterly. 2004;28(2):229–254.
  14. Chin WW, Lee MKO. A proposed model and measurement instrument for the formation of IS satisfaction: The case of end-user computing satisfaction. Proceedings of the 21st International Conference on Information Systems, Atlanta, GA; 2000. p. 553–563.
  15. Chiou WC, Lin CC, Perng C (2010). A strategic framework for website evaluation based on a review of the literature from 1995~2006. Information & Management. Accessed 4 June 2010.
  16. Davis F. Perceived usefulness, perceived ease of use, and user acceptance of information technology. Management Information Systems Quarterly. 1989;13(3):318–339.
  17. DeLone W, McLean E. Information systems success: The quest for the dependent variable. Information Systems Research. 1992;3(1):60–95.
  18. DeLone W, McLean E. The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems. 2003;19(4):9–30.
  19. Doll W, Torkzadeh G. The measurement of end-user computing satisfaction. Management Information Systems Quarterly. 1988;12(2):259–274.
  20. Edwards J. The study of congruence in organizational behavior research: Critique and a proposed alternative. Organizational Behavior and Human Decision Processes. 1994;58(1):51–100.
  21. Emmons RA, Diener E. Factors predicting satisfaction judgements: A comparative examination. Social Indicators Research. 1985;16:157–167.
  22. Erevelles S, Srinivasan S, Rangel S. Consumer satisfaction for internet service providers: An analysis of underlying processes. Information Technology and Management. 2003;4(1):69–89.
  23. Gallagher C. Perceptions of the value of a management information system. Academy of Management Journal. 1974;17(1):46–55.
  24. Griffith T, Northcraft G. Cognitive elements in the implementation of new technology: Can less information provide more benefits? Management Information Systems Quarterly. 1996;20(1): 99–110.