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... range of evaluation situations where various OPMs can be applied in light of their underlying assumptions. Moreover, they illustrate the feasibility of using a specific OPM, the Black-Scholes model, to analyze a real deferral option on the deployment of point-of-sale (POS) debit services by the Yankee 24 shared electr on banking network of New England. (Busby, 1997). Yet, to date there has not been a study that truly tests the claimed strengths of OPMs in the context of IT evaluation problems while balancing these strengths against the methodological difficulties that OPMs are believed to involve. The need for such a study is fueled by the expansion of work on real options along two fronts.
On one front, the business world started to seriously attempt to apply OPMs. For example, in a Harvard Business Review interview, the Chief Financial Officer of Merck & Co. , discusses ways her firm evaluates research and development projects intended to yield new drugs by applying OPMs to abandonment, growth, and investment staging options embedded in these projects (Nichols 1994). There are other examples of how these models are applied to real-world business investments, including natural resource mining projects involving deferral, abandonment, and expansion options. Along another front, recent empirical studies have begun providing evidence in favor of using OPMs. In a survey of how financial officers deal with flexibility in capital appraisal, Busby and Pitts (1997, p. 169) found that "very few decision makers seemed to be aware of real option research but, mostly, their intuitions agreed with the qualitative prescriptions of such work. " The study found that managers unaided by OPMs tended to overvalue real options, although their valuations did not differ significantly from those produced by these models. While this study suggests that managers can decide in a manner analogous to OPMs without having learned these models, it also shows that the least overvaluation tendency was among managers from the oil and pharmaceutical industries, two industries already using real option models in capital budgeting.
Overall, the study indicates that OP Ms are adequate for formalizing managers' intuition and that familiarity with these models can improve the valuation of investments involving options. (Chalasani, 1986). In this light, the present paper seeks to evaluate and operation alize relevant real options analysis concepts in the IS context. We present the case study details behind Yankee 24 's IT investment in POS debit services describe the structured interview used to obtain from Yankee 24 's senior management evidence that enabled us to analyze this investment from a real options perspective, and subsequently use the analysis results to offer case study insights specific to electronic banking service deployment decision making. We put to a real test the claimed strengths and weaknesses of the Black-Scholes model to show the pragmatic value of applying this model to realistic IT investment evaluation problems.
We specifically focus on two traits of the model. We examine methodological issues involved in using OPMs. We discuss factors that must be carefully analyzed before an IT investment decision like the one we study can be cast as a real options analysis problem. We also assess the claim that the estimation of certain option parameters (e. g. , variability of the option's underlying asset) involves major difficulties and thus present practical guidelines that can help to alleviate those claimed difficulties. (Brealey, 1988). Research on real options seeks to address criticism concerning the inadequacy of traditional capital budgeting methods for evaluating a project that offers management the flexibility to take actions which can change traits of the project over time.
The term flexibility is "nothing more (or less) than a description of the options made available to management as part of the project." This flexibility adds value to the passive NPV of a project, where one has assumed that no in-project actions are possible to affect its expected value outcomes. It changes the probability distribution of project payoffs asymmetrically by enhancing the upside potential or reducing the downside risk. This corresponds to the notion of an active NPV, whose expected value trajectory is controllable by management. Figure 1 illustrates these changes and provides examples of specific real options that cause them.
Real options offering in-project flexibility are termed operating options. They differ from so-called growth options, whose value stems from future investment opportunities that they open up. (Busby, 1997). Two approaches commonly used to evaluate investments are DCF (NPV) analysis and decision tree analysis (DTA). In addition to the theoretical reasons for these approaches being inadequate for investments involving options, a pragmatic question is: Why can't they be adapted to such investments? The key problem with adapting DCF analysis is that it can evaluate only the actual cash flows a project is expected to yield. DCF analysis does not explicitly recognize that managerial flexibility has a value equivalent to a "shadow, " non-actual cash flow.
Such flexibility is borne by the presence of embedded options and it allows management to adjust traits of the investment (timing, scope, scale, etc. ) to changing environmental conditions. Even if DCF analysis were to consider this shadow cash flow, or option value, risk-adjusted discounting remains a problem. Because the risk of an option is not the same as that of actual cash flows, and because this risk changes as a function of time and the uncertain size of actual cash flows, it is neither possible to predict the option risk nor find a risk-adjusted discount rate that applies to it. (Chalasani, 1986). DTA provides a significant conceptual improvement over the way DCF analysis handles options. A decision tree shows the expected project payoffs contingent on future in-project actions that management can take over time (e. g. , abandon an operational project at time t, if the salvage value of resources used exceeds the payoffs arriving after t).
As the tree represents each action as a decision node, corresponding to an option, evaluating the project requires working backward from the future to the present to calculate how much the presence of these actions adds to the project value. This approach yields useful results only after poor tree branches are pruned. Pruning means finding out how embedded options alter the range of expected payoffs and then adjusting the discount rate to recognize the change in risk (or variability of payoffs). Unfortunately, DTA provides no direct basis for discount rate adjustment. Only with a proper modification involving an estimation of the investor's (management) utility function can DTA be adequately applied to projects embedding options. Real options analysis strives to complement the other two approaches, in light of the difficulties involved in adapting these approaches to investments embedding options.
It looks at the active NPV of a project as the sum of the passive NPV and the value of embedded options. The intuition behind how it evaluates an embedded option resides in two factors. First, it models payoff contingencies using a probability distribution function (e. g. , log-normal, binomial), enabling it to translate the presence of an option into expectations of shifts in this distribution. Second, it replaces the actual probabilities of payoffs by risk-neutral (certainty-equivalent) probabilities, to facilitate discounting by the risk-free rate instead of a risk-adjusted rate.
This is equivalent to allowing an analyst to prune unattractive branches in a decision tree without having to worry about discount rate adjustment. (Brigham, 1998). However, these factors raise two issues. The first requires estimating the variability of uncertain payoffs and costs modeled using probability distributions. As to the other factor, the validity of discounting by the risk-free rate is questionable when options are not traded in a market.
We return to these issues later, to show that they do not limit the applicability of real options analysis to IT options. (Chalasani, 1986). In the rest of this section, we formalize real option pricing concepts based on prior work in finance. We focus in particular on deferral options because the case study we present in later sections involves a deferral option. The fundamental options are financial calls and puts.
A European call (put) on some underlying asset, whose current value is V, gives its holder the right to buy (sell) the asset for an agreed exercise price, X, at a fixed expiration date, T. For instance, a "June 99 call" on IBM stock with a $ 75 strike price allows its holder to buy IBM shares for $ 75 on June 15, 1999. This call is worth exercising only if the value of an IBM share on June 15 exceeds $ 75, in which case it is said to be in-the-money. (Roulac, 1993). Thus, the terminal value of a call, or its value on expiration, CT, is max (0, [V.
sub. T]-X), where [V. sub. T] is the terminal value of the underlying asset. An American option is like a European option, but it can be exercised at any time t, t [leq] T. We first focus on European calls because they are simpler to understand, and later return to discuss American options. (Brealey, 1988).
For a firm facing a project embedding the right to defer investment, the analogy with a financial call is direct. The firm can get the value of the operational project via immediate investment, V - X, or hold on to the investment opportunity. This is akin to a call option to convert the opportunity into an operational project. The option (opportunity) offers the flexibility to defer conversion until circumstances turn most favorable, or to back out if they are not satisfactory. Its value corresponds to the active NPV, equaling the passive NPV plus the value of the deferral flexibility. (Detemple, 1990). The option parameters are (1) the time to expiration, T, is the time that the opportunity can be deferred; (2) the underlying asset, V, is the present value of risky payoffs expected upon undertaking the investment; (3) the exercise price, X, is the irreversible cost of making the investment; and (4) the volatility, [sigma], is the standard deviation of risky payoffs from the investment.
When V can fluctuate, the unexercised op tion (opportunity) can be more valuable than immediate investment, max (V - X) [greater than] V - X. The value of the option depends on how much the decision maker expects to learn about the way the value of risky payoffs, V, will evolve due to changes that might occur within the firm or in its environment during deferral. The more uncertain is V, the more learning can take place during deferral, and the more valuable is the option. This is consistent with what finance theory postulates about the effect of [sigma], the variability of V, on the value of financial options. (Brealey, 1988). While reading the book on financial management, I indicated some points for discussion and expressing my opinion. If professionals, academicians, and students expect to readily and effortlessly understand and use much of the book, I suspect they will be disappointed.
However, if they are willing to traverse through the "stretching of conventionality" and the expositional rough spots, I predict that they are likely to be rewarded and feel satisfied. The following eight-point discussion provides more specifics on this characterization. The concept of opportunity cost as the appropriate discount rate, in my view, pushes the envelope too far. More specifically, one must question the validity of their concept called "opportunity cost of debt funds. " I can't find this concept in any leading finance textbook, and if it is advanced and rationalized anywhere in the journal literature. Closely connected to their concept of "opportunity cost of debt funds, " the book contend, similar to some other production and management texts in agricultural economics, that a major reason why debt interest rates should increase as more funds of the firm are borrowed is due to internal credit constraints - a so-called "liquidity premium" which leads to higher debt interest costs "as the firm's credit reserve is reduced." (Brigham, 1998).
I find this concept unconventional at best. It's certainly not in tune with the literature in managerial finance. In the mainstream literature and leading finance texts, as the firm increases its debt, the increased incurred risk is the essence of financial risk and thus is reflected in risk taking by the entrepreneurs, i. e. , in an increasing cost of equity capital, not debt capital. The financial management book contend and demonstrate, unlike other texts on capital budgeting, when several independent projects are being simultaneously considered that the internal-rate-of-return (IRR) and net present value (NPV) criteria .".. will always provide consistent rankings unless the homogenous measures principle is violated." However, one must question if forging this IRR-NPV ranking equivalency merits the reader's study. " (Brigham, 1998)...
since the NPV gives the correct answer even without adjusting for size... the adjustment... really is not needed... " One must remember that the purpose of an IRR analysis is to estimate the IRR. All other variables in the equation have known or assumed numerical values, whereas in an NPV analysis the target rate of return (the cost of capital) is assumed to be known and the purpose is to find the numerical value of the NPV. Forging of a ranking equivalency for several projects of different sizes (of investment) can only be accomplished by artificially assuming the cost of capital in the IRR equation to be known before the equation is solved; but in reality, it isn't.
Thus, to forge equivalency between NPV and IRR rankings, they assume an answer before it can actually be known to the analyst - sort of like peeking at the answer in the back of the book before the problem is solved. But eventually, while writing this paper, I assumed all the concepts and principles mentioned above are known. Words: 4, 644. Bibliography: Kolb, R. W. , & Rodriguez, R. J. (1992).
Principles of Finance. Massachusetts: D. C. Heath and Company.
Roulac, Stephen E. (1993). The demise of the IRR? Real Estate Finance, 9, 11 - 18. Weston, J. F. , & Brigham, E. F. (1993).
Essentials of managerial finance. Fort Worth: The Dryden Press. Brealey, R. A. , and Myers, S. C. Principles of Corporate Finance, NY: McGraw-Hill, New York, 1988.
Busby, J. S. , and Pitts, C. G. C. "Real Options in Practice: An Exploratory Survey of How Finance Officers Deal with Flexibility in Capital Appraisal, " Management Accounting Research (8: 2), 1997, pp. 169 - 186. Chalasani, G. , 1986, "A Certainty-Equivalent Approach to Capital Budgeting" Financial Management (Winter), 23 - 32. Ross, S.
A. , 1989, "Institutional Markets, Financial Marketing, and Financial Innovation, " Journal of Finance (July), 541 - 556. Myers, S. C. and S.
M. Turnbull, 1977, "Capital Budgeting and the Capital Asset Pricing Model: Good News and Bad News, " Journal of Finance (May), 321 - 333. Jensen, M. C. , 1986, "Agency Costs of Free Cash Flow, Corporate Finance, and Takeovers, " American Economic Review (May), 323 - 329. Detemple, J. and P.
Join, 1990, "Option Listing and Stock Returns: An Empirical Analysis, " Journal of Banking and Finance (October), 781 - 801. Brigham, G. Financial Management. New York: Viking Press, 1998.
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