Disconfirming user expectations of the online service experience: inferred versus direct disconfirmation modeling

Abstract

Heightened competition in the e‐commerce domain continues to force the need for a reliable and user‐friendly service quality measurement methodology. The challenge facing practitioners, however, is to identify and implement the most appropriate measurement tools for their operation. Disconfirmation measures have come to dominate the debate concerning this very issue, with both direct and inferred techniques presenting themselves as reliable and valid measures of online quality. This paper addresses this very debate in the context of an online library service setting. It presents findings that attest to the psychometric and diagnostic performance of both techniques and suggests that while much time is taken up discussing the former, the real power of such techniques for online operators rests with the latter, i.e. their ability to pinpoint service failures and direct continuous quality improvement efforts.

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