A quantitative model for ERP investment decision: considering revenue and costs under uncertainty

摘要

This paper evaluates ERP investment under uncertainty using a model based on the Real Options theory. We expand the Dixit and Pindyck (Dixit, A.K. and Pindyck, R.S., 1994. Investment under uncertainty. Princeton: Princeton University Press) model, which considers a single source of uncertainty, and apply it to the problem of ERP investment decision. Revenue and costs are well documented in the literature as uncertain and critical factors. We developed a quantitative model using the concept of dynamic programming, which takes into account multiple uncertain factors, to determine the optimal threshold ratio of revenue to cost, as a means to evaluate investment in ERP. In addition, we performed sensitivity analysis on the effects various parameters have on the value of ERP projects. In contrast to conventional wisdom, we showed that the evaluation of ERP based on Real Options theory differs from that of NPV and captures a more realistic valuation of investment in ERP. This paper contributes to the literature by taking both uncertain revenue and costs into account, and makes up for the lack of tools required to quantify investments in ERP under uncertainty.