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Relationship of Skill Expectation Gap Between IS Employees and Their Managers with User Satisfaction

Relationship of Skill Expectation Gap Between IS Employees and Their Managers with User Satisfaction

James Jiang, Gary Klein, Eric T.G. Wang
Copyright: © 2007 |Volume: 20 |Issue: 3 |Pages: 13
ISSN: 1040-1628|EISSN: 1533-7979|ISSN: 1040-1628|EISBN13: 9781615200078|EISSN: 1533-7979|DOI: 10.4018/irmj.2007070105
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MLA

Jiang, James, et al. "Relationship of Skill Expectation Gap Between IS Employees and Their Managers with User Satisfaction." IRMJ vol.20, no.3 2007: pp.63-75. http://doi.org/10.4018/irmj.2007070105

APA

Jiang, J., Klein, G., & Wang, E. T. (2007). Relationship of Skill Expectation Gap Between IS Employees and Their Managers with User Satisfaction. Information Resources Management Journal (IRMJ), 20(3), 63-75. http://doi.org/10.4018/irmj.2007070105

Chicago

Jiang, James, Gary Klein, and Eric T.G. Wang. "Relationship of Skill Expectation Gap Between IS Employees and Their Managers with User Satisfaction," Information Resources Management Journal (IRMJ) 20, no.3: 63-75. http://doi.org/10.4018/irmj.2007070105

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Abstract

The skills held by information system professionals clearly impact the outcome of a project. However, the perceptions of just what skills are expected of information systems (IS) employees have not been found to be a reliable predictor of eventual success in the literature. Though relationships to success have been identified, the results broadly reported in the literature are often ambiguous or conflicting, presenting difficulties in developing predictive models of success. We examine the perceptions of IS managers and IS employees for technology management, interpersonal, and business skills to determine if their perceptions can serve to predict user satisfaction. Simple gap measures are dismissed as inadequate because weights on the individual expectations are not equal. Exploratory results from polynomial regression models indicate that the problems in defining a predictive model extend beyond the weighting difficulties, as results differ by each skill type. Compound this with inherent problems in the selection of a success measure, and we only begin to understand the complexities in the relationships that may be required in an adequate predictive model relating skills to success.

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