Author List: Venkatesh, Viswanath; Goyal, Sandeep;
MIS Quarterly, 2010, Volume 34, Issue 2, Page 281-303.
Individual-level information systems adoption research has recently seen the introduction of expectation-disconfirmation theory (EDT) to explain how and why user reactions change over time. This prior research has produced valuable insights into the phenomenon of technology adoption beyond traditional models, such as the technology acceptance model. First, we identify gaps in EDT research that present potential opportunities for advances--specifically, we discuss methodological and analytical limitations in EDT research in information systems and present polynomial modeling and response surface methodology as solutions. Second, we draw from research on cognitive dissonance, realistic job preview, and prospect theory to present a polynomial model of expectation-disconfirmation in information systems. Finally, we test our model using data gathered over a period of 6 months among 1,143 employees being introduced to a new technology. The results confirmed our hypotheses that disconfirmation in general was bad, as evidenced by low behavioral intention to continue using a system for both positive and negative disconfirmation, thus supporting the need for a polynomial model to understand expectation disconfirmation in information systems.
Keywords: difference scores; direct measures; expectation disconfirmation theory; IS continuance; nonlinear modeling; response surface methodology; technology acceptance model
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#136 0.326 expectations expectation music disconfirmation sales analysis vector experiences modeling response polynomial surface discuss panel new nonlinear period understand paper dissonance
#140 0.303 model use theory technology intention information attitude acceptance behavioral behavior intentions research understanding systems continuance models planned percent attitudes predict
#222 0.146 research researchers framework future information systems important present agenda identify areas provide understanding contributions using literature studies paper potential review
#276 0.079 satisfaction information systems study characteristics data results using user related field survey empirical quality hypotheses important success various indicate tested