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Designing a satisfaction-oriented option analysis framework to support organization decisions on online training project

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1 Author(s)
Hsiao-Ya Chiu ; Dept. of Manage. Inf., Yu Da Coll. of Bus., Tainan

Online training or web-based training has been widely adopted by organizations. Due to the high cost of time, money and human resources, it is important for decision makers to superintend those projectspsila performance. However, existing frameworks for evaluating such projectpsilas performance are rare. In an attempt to help decision makers monitor their online training projects, this study proposes a satisfaction-oriented framework to evaluate nonprofit-oriented projectspsila performance using an option pricing approach. This framework can be also seamlessly applied to any IT project that has both quantitative and qualitative factors which require evaluation under uncertainties. In order to construct an ideal evaluation framework, this study proposes a satisfaction-oriented option analysis framework that can be applied to evaluate both quantitative and qualitative measurements on the same scale. Meanwhile, this study constructs a measurement framework that integrates Kirkpatrickpsilas and Black Scholes models with theoretical groundings to support performance evaluation. At the end of this paper provides an empirical study that demonstrates the analytical procedures to apply the proposed framework to real world applications.

Published in:

Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on

Date of Conference:

1-6 June 2008

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