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Dissertation/Thesis Abstract

Determining Relationships Between Technology Acceptance and Employee Attitudes Toward Automated Workflows in the Oil Industry
by Waldner, Bruce W., Ph.D., Northcentral University, 2013, 157; 3577845
Abstract (Summary)

Automated workflows are used to assist petroleum engineers in maximizing the productivity of oil reservoirs. However, for a workflow to be successful, end users must adopt the workflow. The purpose of this quantitative, ex post facto, correlational study was to determine the relationship between acceptance of automated workflow technology and attitudes toward automated workflow adoption. Participants included a cluster sample of 100 randomly selected petroleum engineers from five randomly chosen companies in the oil industry in the Middle East. Predictor variables were measured with a version of the Technology Acceptance Model (TAM) modified to address the issue of workflow adoption. The outcome variable was user attitude to automated workflow adoption, as measured with the Attitude subscale of the Theory of Reasoned Action (TRA) scale. A single multiple linear regression model was computed to answer all research questions. The results for the overall model were significant, adjusted R 2 = .43, F(6, 93) = 13.28, p < .001. After correcting for the number of years of engineering experience of the participants, attitudes toward using automated workflows were predicted by perceived ease of use, β = 0.30, p = .01; perceived usefulness, β = 0.24, p = .03; and computer self-efficacy, β = 0.20,p = .02. The level of automation, β = 0.12, p = .17, and perceived level of support, β = 0.08, p = .32, did not predict attitudes. The number of years of engineering experience was unrelated to attitudes to automated workflow adoption. These findings indicated three factors that have an effect on adoption of automated workflows: perceived ease of use, perceived usefulness, and the level of computer self-efficacy of the end-user. Areas for future research included confirmation of the reliability of the Level of Automation and the Perceived Level of Support subscales designed for this study. There is also a need for future research regarding how the level of automation and level of support affect the adoption of other technologies.

Indexing (document details)
Advisor: Shelton, Gary
School: Northcentral University
School Location: United States -- Arizona
Source: DAI-A 75/03(E), Dissertation Abstracts International
Subjects: Management, Information science
Publication Number: 3577845
ISBN: 978-1-303-64712-3
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