A real option theoretic fuzzy evaluation model for enterprise resource planning investment
The high failure rate of ERP implementation is due to a common pitfall that ERP projects are often enacted as merely investment into installation of IT infrastructure, rather than systematic planning of operation changes, business process re-engineering and a paradigm shift for the operation and man...
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sg-ntu-dr.10356-967142020-03-07T13:19:20Z A real option theoretic fuzzy evaluation model for enterprise resource planning investment You, Chew Jian Chen, S. L. Jiao, Roger J. Lee, C. K. M. School of Mechanical and Aerospace Engineering DRNTU::Engineering::Mechanical engineering The high failure rate of ERP implementation is due to a common pitfall that ERP projects are often enacted as merely investment into installation of IT infrastructure, rather than systematic planning of operation changes, business process re-engineering and a paradigm shift for the operation and management. To manage ERP investment in a changing environment for high payoff, this paper adopts a real option theoretic method. Fuzzy payoff valuation is introduced to deal with uncertainties in order to minimize the risk of failure. The proposed ERP evaluation model is geared towards small and medium enterprises. A case study is presented to validate the proposed fuzzy real options. The results indicate the potential of modeling ERP investment as “Expand”, “Contain” and “Abandon” options in different scenarios. The fuzzy real option model bestows a novel ex-ante cost analysis for justifying ERP investment in the implementation cycle. 2013-12-05T02:43:53Z 2019-12-06T19:34:11Z 2013-12-05T02:43:53Z 2019-12-06T19:34:11Z 2012 2012 Journal Article You, C. J., Lee, C.K.M., Chen, S.L., & Jiao, R. J. (2012). A real option theoretic fuzzy evaluation model for enterprise resource planning investment. Journal of engineering and technology management, 29(1), 47-61. 0923-4748 https://hdl.handle.net/10356/96714 http://hdl.handle.net/10220/18066 10.1016/j.jengtecman.2011.09.005 en Journal of engineering and technology management |
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DRNTU::Engineering::Mechanical engineering You, Chew Jian Chen, S. L. Jiao, Roger J. Lee, C. K. M. A real option theoretic fuzzy evaluation model for enterprise resource planning investment |
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The high failure rate of ERP implementation is due to a common pitfall that ERP projects are often enacted as merely investment into installation of IT infrastructure, rather than systematic planning of operation changes, business process re-engineering and a paradigm shift for the operation and management. To manage ERP investment in a changing environment for high payoff, this paper adopts a real option theoretic method. Fuzzy payoff valuation is introduced to deal with uncertainties in order to minimize the risk of failure. The proposed ERP evaluation model is geared towards small and medium enterprises. A case study is presented to validate the proposed fuzzy real options. The results indicate the potential of modeling ERP investment as “Expand”, “Contain” and “Abandon” options in different scenarios. The fuzzy real option model bestows a novel ex-ante cost analysis for justifying ERP investment in the implementation cycle. |
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School of Mechanical and Aerospace Engineering |
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School of Mechanical and Aerospace Engineering You, Chew Jian Chen, S. L. Jiao, Roger J. Lee, C. K. M. |
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Article |
author |
You, Chew Jian Chen, S. L. Jiao, Roger J. Lee, C. K. M. |
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You, Chew Jian |
title |
A real option theoretic fuzzy evaluation model for enterprise resource planning investment |
title_short |
A real option theoretic fuzzy evaluation model for enterprise resource planning investment |
title_full |
A real option theoretic fuzzy evaluation model for enterprise resource planning investment |
title_fullStr |
A real option theoretic fuzzy evaluation model for enterprise resource planning investment |
title_full_unstemmed |
A real option theoretic fuzzy evaluation model for enterprise resource planning investment |
title_sort |
real option theoretic fuzzy evaluation model for enterprise resource planning investment |
publishDate |
2013 |
url |
https://hdl.handle.net/10356/96714 http://hdl.handle.net/10220/18066 |
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1681048183627579392 |