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Article Excerpt
Management's ability to respond to changes in the marketplace or in the outlook for technology can enhance the value of an R&D project. However, many scholars have recognized that the traditional discounted cash flow (DCF) model fails to account for the value of such managerial flexibility. They emphasize that the real option method has the advantage of capturing the value of this flexibility (1-4). They also propose that the real option method is superior to the traditional DCF model, especially for highly unpredictable technological projects (5-7).
The application of real option pricing theory to the assessment of R&D projects is based mainly on the following arguments: The initial input for projects could be treated the same as purchasing a call option. After completing technological development, and depending on the market conditions at that time, a firm could determine whether or not to commercialize the new technology. The valuation framework for pricing such a real R&D option is analogous to a call option in financial markets. The input cost of commercialization could then be regarded as the exercised price of the call option.
From the viewpoint of options thinking, the more uncertain the future revenue streams associated with the R&D projects, the greater the value of managerial flexibility (8). Typically, there are five basic types of managerial flexibility to be identified: deferral option, abandonment option, expansion option, contraction option, and switching option (9).
The Black-Scholes (BS) and Cox-Ross-Rubinstein (CRR) option models are ordinarily utilized to evaluate R&D projects in the literature (1,2,10-13). However, these models make many assumptions that are often unsuitable for the valuation of technology projects. For example, the BS model assumes that the rate of return of the underlying asset follows a lognormal distribution, but this characteristic might not exist for many R&D projects. For this reason, an alternative assessment method has been proposed: relaxing the assumption of a lognormal distribution of the net cash flows associated with the R&D projects (14).
Another important assumption of both the BS and CRR models--the no-arbitrage condition--seems to be overlooked in the literature. We will attempt to take this into account here. Theoretically, the real option method is based on contingent claims analysis, developed for pricing options in financial markets. This approach assumes that a complete market of risky assets can be established and that a portfolio can be formed to replicate the new asset to be valued. The price of the asset must then equal the market value of this portfolio. Thus, the replication of the project's risk by the portfolio of some other traded assets should be required when applying this approach to the valuation of R&D projects (8). However, the risk of an R&D project is usually idiosyncratic, so, in this case, such a replication could not be close to being real. Therefore, many researchers typically assume that firms adopt a risk-neutral attitude toward R&D projects, with discounting at the risk-free rate (8,9,15-17).
Even though all the risks of R&D projects might not be duplicated completely with other assets, they cannot be eliminated completely through diversification. R&D firms still attempt to reduce the risks that stem from their general risk-aversion characteristics. Actually, manufacturers could reduce the unique risk of R&D projects by using investment diversification, such as investing in other similar projects or joining exploratory syndicates (1,18,19). In other words, firms could adopt hedging actions to reduce the risk faced while carrying out R&D projects. Thus, if the hedging behavior is considered, how will the real option value of R&D projects be properly evaluated? The purpose of this article is to apply contingent claims analysis, while incorporating the firm's hedging behavior, to fairly evaluate R&D projects. We also use a numerical example to compare the assessment results obtained by the proposed method with the conventional NPV rule and real option methods.
Hedging Behavior of R&D Firms
Basically, the various uncertainties in an R&D investment can be synthesized into two kinds: technological and market uncertainties (19). Technological uncertainty usually occurs when firms do not know whether the new technology will work, whether the complementary technology will be ready in time, and what technological standards will be formulated. Market uncertainty involves determining whether there will be enough potential buyers, or whether the market demand is likely to change in the future. These uncertainty factors would...
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