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Widely used DCF (Discounted Cash Flow) method for the appraisal of IT and e- business investment valuation forecasts future cash flow and discount them at risk adjusted rate, the opportunity cost of capital. This method assumes low market uncertainty. All opportunities are calculated based on current information and there is no possibility to make decision in future. The method does not capture flexibility as the investment decisions are fixed at the beginning. Investment appraisal technique such as Net Present Value (NPV) have been widely criticized because of their inability to model uncertainty, a factor that is particularly relevant in the context of e-business investment decisions. Even when such investment appraisal yields a negative NPV (usually taken as a signal that the investment should not take place), an investment could still generate potentially valuable Options which is favourable. Circumstances could make the initial investment worthwhile e.g., infrastructure investments are often made without any immediate expectation of payback. They can act as a basis for follow-on investments like wireless technical infrastructure, investments in data warehouse etc. Their investment appraisal may yield a negative NPV, but they create value over time. Such investments create valuable follow-on contingent investment opportunities.
Real Option analysis has been an alternative approach that incorporates impact of flexibility while evaluating IT and e-business projects. The basic idea of the Real Options approach is to transfer the sophisticated Option pricing model used in the capital market theory to the valuation of risky projects. Real Option theory views investment activities as discretionary decisions in uncertain environment and thus is able to capture the value of decision flexibility ignored by existing net cash flow method. The initial investment of these projects is similar to purchase of an Option on a further dependent projects’ investment. The value of the project investment is not primarily determined by the initial investment but by the future investment opportunities provided by the initial investment. The NPV and the DCF based analysis are not suited well for risky IT and e-business projects as they are not able to estimate the managerial flexibility underlying such investments. Therefore, the value of the successful project is usually underestimated while the value of the failure is overestimated. In Real Option valuation approach, the initial investment of such project is similar to the purchase of an Option on the further dependent e-business project’s investment. Therefore, the basic idea is to add the call Option value of the dependent project to the initial project value. So, the total value of each project will be the addition of its own DCF value and the call Option value of the dependent projects to be implemented in the subsequent time period.
E-entrepreneurs and the companies that select IT projects to provide services for e-business purpose face an important problem of selecting a project portfolio for funding. The purpose of project portfolio decision is to allocate a limited set of resources to projects in a way that balances risk and reward. Since these project portfolio decision deals with future events and opportunities, much of the information required to make portfolio decisions is at best uncertain and at worst very unreliable. However, even with this doubtful information, the project portfolio decision still must be made. Moreover, resource or budget availability may be 〉exible because additional budget may be re-allocated from other budget categories.
Fuzzy set theory has been used to model imprecise and preference information in many applications. It can also be used to represent uncertain project information. Pereira and Junior (1988) formulated a simple fuzzy multi-criteria R&D portfolio selection problem that represented project appraisals for each criterion as fuzzy set and developed an algorithm to get non-dominated solutions. Machacha and Bhattacharya (2000) modelled uncertain critical factors involved in the information system project selection by fuzzy sets and developed a fuzzy logic approach to emulate the human reasoning process and make decisions based on vague or imprecise data. Mohamed and McCowan (2001) applied fuzzy set theory to handle the inherent uncertainty of both momentary and non-momentary aspects in construction projects and used a fuzzy ranking index to rank and select construction projects. Hsu et al. (2003) applied the fuzzy AHP approach to select government-sponsored frontier technology R&D projects and indicated the adequacy of fuzzy approach in selecting R&D projects. Fuzzy set theory is also applied to model uncertain and flapible project information. Wang (2004) has used fuzzy set theory to describe uncertain and flexible project information.