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An Application of Expectancy Theory for Assessing User Motivation to Utilize an Expert System.

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Title: An Application of Expectancy Theory for Assessing User Motivation to Utilize an Expert System.
Authors: Burton, F. Greg1, Yi-Ning Chen1, Grover, Varun2, Stewart, Kathy A.1
Source: Journal of Management Information Systems. Winter92/93, Vol. 9 Issue 3, p183-198. 16p. 2 Charts.
Subjects: Expert systems, Business students, Attitudes toward technology, Expectancy theories, Innovation adoption, Act psychology, Psychology
Abstract: Evaluation of information system success has been the focus of much research. However, most variables such as user satisfaction and system usage can only be measured after system implementation. To predict system success before actual implementation, behavioral theories indicate that it is necessary to evaluate behavioral intention or users' motivation to use the system. Expectancy theory is considered one of the most promising models of individual motivation. This study examines the use of expectancy theory in explaining the motivation to use an expert system. Data gathered from 95 M.B.A. students in a judgmental modeling exercise suggest that the model is a significant predictor of motivation. It also provides insight into the development of such systems. The successful use of this model further suggests that it is appropriate for evaluating and understanding individual motivation to use a system and, subsequently, system success. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Management Information Systems is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Management+Information+Systems%22">Journal of Management Information Systems</searchLink>. Winter92/93, Vol. 9 Issue 3, p183-198. 16p. 2 Charts.
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  Data: <searchLink fieldCode="DE" term="%22Expert+systems%22">Expert systems</searchLink><br /><searchLink fieldCode="DE" term="%22Business+students%22">Business students</searchLink><br /><searchLink fieldCode="DE" term="%22Attitudes+toward+technology%22">Attitudes toward technology</searchLink><br /><searchLink fieldCode="DE" term="%22Expectancy+theories%22">Expectancy theories</searchLink><br /><searchLink fieldCode="DE" term="%22Innovation+adoption%22">Innovation adoption</searchLink><br /><searchLink fieldCode="DE" term="%22Act+psychology%22">Act psychology</searchLink><br /><searchLink fieldCode="DE" term="%22Psychology%22">Psychology</searchLink>
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  Data: Evaluation of information system success has been the focus of much research. However, most variables such as user satisfaction and system usage can only be measured after system implementation. To predict system success before actual implementation, behavioral theories indicate that it is necessary to evaluate behavioral intention or users' motivation to use the system. Expectancy theory is considered one of the most promising models of individual motivation. This study examines the use of expectancy theory in explaining the motivation to use an expert system. Data gathered from 95 M.B.A. students in a judgmental modeling exercise suggest that the model is a significant predictor of motivation. It also provides insight into the development of such systems. The successful use of this model further suggests that it is appropriate for evaluating and understanding individual motivation to use a system and, subsequently, system success. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Management Information Systems is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/07421222.1992.11517973
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        Text: English
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        PageCount: 16
        StartPage: 183
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      – SubjectFull: Expert systems
        Type: general
      – SubjectFull: Business students
        Type: general
      – SubjectFull: Attitudes toward technology
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      – SubjectFull: Expectancy theories
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      – SubjectFull: Innovation adoption
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      – SubjectFull: Act psychology
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              Text: Winter92/93
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              Y: 1992
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