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Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

System Quality and Information Quality: Do They Really Reflect Information System Success?

System Quality and Information Quality: Do They Really Reflect Information System Success?
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Author(s): Edward J. Garrity (Canisius College, USA) and G. Lawrence Sanders (State University of New York at Buffalo, USA)
Copyright: 2003
Pages: 4
Source title: Information Technology & Organizations: Trends, Issues, Challenges & Solutions
Source Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-59140-066-0.ch042
ISBN13: 9781616921248
EISBN13: 9781466665330

Abstract

Currently, there are a large number of IS success measures from which to choose. However, little research has been devoted to IS success dependent variable comparisons or to a better understanding of the IS success construct. Indeed, most of the existing instruments were developed through interviews and questionnaires and from scales derived from other scales (Shirani, Aiken, and Reithel, 1994). While this approach has an intuitive appeal, a sound theoretical basis for including questionnaire items is often lacking. The result of this is that many dependent variables continue to overlap in conceptual space leading to misinterpretation and confusion. In order to address these concerns with construct validity, we first develop a theoretical rationale to more precisely specify the IS success construct. In this way, we address issues of construct validity through an examination of face validity and content validity. This approach is definitional in nature – it assumes you have a good detailed definition of the construct and that you can check the operationalization against it (Trochim, 1999). Issues of content validity have plagued many existing dependent measures because of a lack of precise definitions for IS success. After detailing our conceptual understanding of the IS success construct, we compare and contrast two pervasive IS success measures: Perceived Usefulness and Information Quality. Next, we critique the dimensions of the DeLone and McLean model using this basic definitional framework.

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