The S curve: A dynamic view of in ERP evaluation

Wu, Liang-Hong; Rushikesh Ulhas, Khire; Tan, Kim Hua; Wu, Liangchuan

Abstract

Most the previous Enterprise resource planning (ERP) works that used real options to evaluate investments are based on the closed-formed basis. A closed formed problem, such as financial assets with predefined exercise price and typical underlying asset value, is designed to mainly solve financial asset problems. The concept to take unique characteristics of ERP, the life cycle shape into evaluation has been long overdue. We propose a lifecycle model based on simulation and stochastic process. In doing so, the features that ERP value can be captured and evaluated in the model. An extreme case is that the life cycle analysis will be equivalent to pure closed form real options results without life cycle formation, when reversion rate, drift rate and growth rate are ignored in our model. Another extreme case is that the real options analysis results will be equivalent to NPV analysis when volatility equals zero. This helps the manager to consider unique characteristics of ERP implementation with additional key factors. Our results show that accounting for the life cycle, ERP value differs that from traditional wisdoms and helps the manager to consider unique characteristics of ERP implementation with additional key factors and support decision making from various factors and scopes.

• Journal Article Type: Article
• Acceptance Date: Apr 26, 2023
• Online Publication Date: May 13, 2023
• Publication Date: May 13, 2023
• Deposit Date: Jun 19, 2023
• Publicly Available Date: May 14, 2024
• Journal: The Engineering Economist
• Print ISSN: 0013-791X
• Electronic ISSN: 1547-2701
• Publisher: Taylor and Francis
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1080/0013791X.2023.2209080
• Keywords: ERP evaluation, ERP life cycle, stochastic model, uncertainty
• Public URL: https://nottingham-repository.worktribe.com/output/22146922
• Publisher URL: https://www.tandfonline.com/doi/abs/10.1080/0013791X.2023.2209080?journalCode=utee20
• Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis in The Engineering Economist on 13/05/2023, available at: https://doi.org/10.1080/0013791X.2023.2209080