A Review of: BUSINESS COST-BENEFIT ANALYSIS

This paper reports the findings of a survey of 427 large hospitals nationwide. The survey provided information regarding the techniques employed as primary and secondary tools of capital budgeting, the percentage of capital projects formally evaluated, the methods used in capital budgeting, the qualitative factors which influence the capital budgeting decisions and the extent of their impact in determining the acceptance decision, and the nature and frequency of involvement of the medical staff in major capital investment decisions.     

THE MAPI URGENCY RATING

There is substantial agreement in the capital budgeting literature that the presence of project interactions has to be recognized in evaluating capital projects. Most existing approaches require the explicit assessment of such interactions, which is an extremely difficult task. This paper proposes an alternative framework to overcome this difficulty. The suggested framework utilizes the accounting relationships inherent in the Impact of the projects to evaluate complex interactions. The framework is first presented in terms of a heuristic selection rule and subsequently formulated as a non-linear zero-one programming problem.     

Duality Results for Discrete Capital Budgeting Models

The application of linear and non-linear programming duality theory to capital budgeting models had resulted in the identification of various properties of optimal solutions and has provided economic interpretations of the models. This paper illustrates that similar results may be obtained for discrete capital budgeting models by applying recent advances in duality theory for integer programming problems (1), (2), and (3).In addition, a dual solution method is developed that permits a degree of decentralization of a firm's capital budgeting decision.     

Analysis of Investment Returns by Computer

This paper concerns itself with providing the means by which a decision-maker may choose among competing projects and arrive at the optimal allocation of the firm's scarce dollar resources. The problem is handled in the mathematical programming framework. The model holds with or without the assumption of capital rationing and permits the incorporation of the effects of growth and of alternative financial mixes on the cost of capital for the firm. When iterated, the model equates marginal revenue to marginal cost, thus yielding the optimal investment level for the firm. Several investment alternatives not considered in the existing literature on the subject are examined, and some novel interpretations of the constraints and results are offered.     

Project Valuation With Time-Varying Cash Flows: A Bayesian Approach

This article investigates the valuation of a project when the distributions of cash flows vary over time. The decision maker is assumed to be a Bayesian decision maker under uncertainty. Using the dynamic programming principle of backward induction and assuming that the capital asset pricing model is valid in each time period, we derive the project's valuation formulas and systematic risks, and investigate their characteristics. Our valuation formulas embed a Bayesian learning effect and differ from the traditional textbook capital budgeting formulas.     

Financing Cost of Construction Projects

A recent contribution In the finance literature presents a goal programming solution to the problem of estimating the systematic risk (beta) of an operating division. The estimation problem is difficult, but the necessity of a reliable risk estimate is undeniable for sound capital budgeting decisions. This paper describes a method Introduced recently In the statistics literature for assessing the precision of the estimator.     

INTEGRATING TRADITIONAL CAPITAL BUDGETING CONCEPTS INTO AN INTERNATIONAL DECISION-MAKING ENVIRONMENT

The capital budgeting policies of 146 multinational companies are analyzed in light of current financial theory. Extensions of domestic practices into the international area are examined. There are a number of misapplications such as applying corporatewide weighted average cost of capital to foreign affiliate cash flows rather than to cash flows actually remitted to the corporation. Also, risk is frequently measured on a local project basis (in a foreign country) rather than considering the portfolio effect on the total corporation. Ultimately, it is shown that the survey respondents hedge against the uncertainty of the procedures by adding a premium to the weighted average cost of capital as computed by financial analysts.     

实物期权定量分析方法在风险投资决策中的应用

在风险投资项目中，不确定性对风险项目投资评价、决策起到了决定性的作用。运用实物期权原理分析了不确定性对风险投资项目评价和决策的影响，通过风险中性概率方法将这些影响予以定量化，并进一步对实际投资行为作出解释。     

Capital Budgeting Practices for R&D: A Survey and Analysis of Business Week's R&D Scoreboard

This paper discusses results of a survey of U.S. Corporations regarding the extent of the utilization of standard capital budgeting measures of investment worth to evaluate R&D projects. This study analyzes responses by three types of R&D activity: Basic, Applied and Development research. The results indicate that discounted cash flow methods are widely utilized in the evaluation of Development projects, and the analysis of Development projects is as sophisticated as the evaluation of non-R&D projects. The use of discounted cash flow analysis techniques for Applied projects is considerably less widespread than for Development projects. However, the utilization of Net Present Value and Internal Rate of Return increases with firm size. Basic research projects are much less likely to be subjected to a formal economic analysis and are generally thought of as being “strategic” investments. This research also indicates that post-audits of Applied and Development projects are based on economic measures, whereas Basic research projects focus on physical or operational goals. Lastly, this research indicates that most R&D projects are terminated because R&D priorities have changed rather than because they are not technically feasible.     

APPLICATION OF CHANCE-CONSTRAINED PROGRAMMING TO CAPITAL RATIONING PROBLEMS WITH ASYMMETRICALLY DISTRIBUTED CASH FLOWS AND AVAILABLE BUDGET

Most applications of chance-constrained programming are based on either normally distributed random variables or random variables with symmetric distributions such as uniform, which can be approximated rather accurately by the normal distribution. In this paper we study pure capital rationing with selection of the best project mix when cash flows and available budget are random variables with asymmetric distributions. We show that solutions obtained by chance-constrained programming using normality approximation for asymmetrically distributed random variables fail to satisfy budget constraints when cash outflows are skewed to the left, indicating that realized cash outflows are more likely to be higher than expected.     

Borrowing Interest Rate as a Function of the Debt-Equity Ratio in Capital Budgeting Models

This research extends Weingartner's basic horizon model by letting the borrowing terest rate vary from period to period as a function of the debt-equity ratio. blicly available data for two industries are used to obtain the function. Two models 2 developed: a non-convex nonlinear programming problem, which is solved by the oke and Jeeves algorithm; and an iterative linear model. It is concluded that either del can be used to represent the relationship between borrowing interest rate and Dt-equity ratio in the context of the capital budgeting problem.     

Measuring and Utilizing Corporate Risk Tolerance to Improve Investment Decision Making

Strategic investment decisions are generally characterized by financial risk as well as an irrevocable commitment of significant amounts of capital. The firm's willingness to undertake financial risks plays an important role in the investment decision making process. A comprehensive economic decision analysis to evaluate strategic investment decisions requires a measure of the firm's tolerance for financial risk. This article describes a decision analysis–based technique for assessing managerial risk tolerance as well as managers' ability to be consistent in terms of their financial risk taking. These assessments are then utilized to assist the firm in establishing a corporate risk policy that can guide strategic decisions under uncertainty. The study firm is a business unit within a U.S.-based major oil company with an annual capital budget of approximately $400 million. Our findings suggest that managers are generally risk averse but struggle in terms of being consistent in their financial risk-taking decisions. This work enabled the firm to implement a financial risk tolerance that could be utilized in the economic decision analysis of investment decisions.     

Incorporating uncertainty into a supplier selection problem

Supplier selection is an important strategic supply chain design decision. Incorporating uncertainty of demand and supplier capacity into the optimization model results in a robust selection of suppliers. A two-stage stochastic programming (SP) model and a chance-constrained programming (CCP) model are developed to determine a minimal set of suppliers and optimal order quantities with consideration of business volume discounts. Both models include several objectives and strive to balance a small number of suppliers with the risk of not being able to meet demand. The SP model is scenario-based and uses penalty coefficients whereas the CCP model assumes a probability distribution and constrains the probability of not meeting demand. Both formulations improve on a deterministic mixed integer linear program and give the decision maker a more complete picture of tradeoffs between cost, system reliability and other factors. We present Pareto-optimal solutions for a sample problem to demonstrate the benefits of the SP and CCP models. In order to describe the tradeoffs between costs and risks in an analytical form, we use multi-parametric programming techniques to more completely analyze the alternative Pareto-optimal supplier selection solutions in the CCP model. This analysis gives insights into the robustness of the solutions with respect to number of suppliers, costs and probability of not meeting demand.     

COST EFFECTIVENESS— The Economic Evaluation of Engineered Systems Edited by J. Morley English John Wiley and Sons,Inc.

In this case study four actual energy efficiency projects are analyzed with two traditional engineering economy capital budgeting methods - internal rate of return and payback period - and the results compared with those obtained using the capital asset pricing model (CAPM). The alternative scenarios of the future states-of-the-world necessary for the latter are based on information available in Department of Energy reports. The traditional and CAPM approaches result in different economic conclusions for some of the projects. These differences are analyzed and the implications for certain types of improvement projects and equipment replacement problems as well as financial decision-making in general are discussed.     

THE ASSOCIATION BETWEEN THE USE OF SOPHISTICATED CAPITAL BUDGETING PRACTICES AND CORPORATE PERFORMANCE

Since the early 1950s, the academic community has tried lo convince corporate managers that there are sophisticated techniques that can improve the capital budgeting decision-making process. Over the years, many studies have documented a trend toward increasing business use of such sophisticated capital budgeting techniques. However, there is no clear evidence whether better performing companies are more likely to employ sophisticated capital budgeting processes than are lower performing companies. This study is an attempt to measure the relationship between capital budgeting sophistication and business performance. It advances upon earlier studies by utilizing a more comprehensive capital budgeting sophistication metric, incorporating industry-adjusted independent variables (firm size, risk, capital intensity, and degree of focus), and by focusing on United States corporations. The results are similar with those of earlier studies; there is no discernible relationship between capital budgeting sophistication and corporate performance.     

RECONSIDERING THE SUNK-COST CONCEPT

This paper presents a decision procedure to aid in making capital rationing investment and borrowing decisions. Weingartner's Basic Horizon Model and Oakford and huesen's Maximum Prospective Value criterion are both extended to explicitly include long-term borrowing decisions. Information derived from interviews with financial executives on the subject of business attitudes toward borrowing is used to develop the conceptual logic of the decision procedure, which is presented in terms of a mathematical programming formulation.     

A BETTER UNDERSTANDING OF WHY NPV UNDERVALUES MANAGERIAL FLEXIBILITY

The Real Options paradigm addresses the valuation of managerial flexibility in capital budgeting. Despite the great strides achieved by researchers in this field, many financial analysts have chosen not to adopt this new paradigm due to a lack of comfort with the approach and the mathematical complexity of the valuation models. This article shows how some projects with real options can be valued using simple and familiar tools-discounting expected cash flows after adjusting the discount rate. Unless the discount rate is adjusted to account for the impact of real options on risk, a traditional net present value (NPV) analysis misses the value of flexibility. By narrowing the gulf between Real Options analysis and more familiar tools, the weighted average discount rate (WADR) approach introduced in this paper may help novices better understand die Real Options paradigm, which subsequently may gain the wider acceptance it deserves. Though the WADR approach is practical only for simple real options, comfort with the approach may encourage analysts to pursue more advanced and robust real option valuation techniques for more complex applications.     

A Robust Optimization Approach to Capital Rationing and Capital Budgeting

We study the pure capital rationing and the horizon capital budgeting problems using a robust optimization framework. The models and the methodology we propose take into account the uncertainty of the input data. The uncertainty of the cash flows is modeled as a range of values that is allowed for each uncertain data. Unlike stochastic models, this approach does not make assumptions on the probability distribution of uncertain data. Moreover, this approach is highly tractable, easy to implement, and provides insights into portfolio selection problems. An attractive point of the model is that the decision maker can set the value of the parameters that control the robustness of the optimal solution, in order to balance the trade-off between protection level and performance. We illustrate our models with examples that show promising results. We also provide new duality and KKT optimality conditions.     

Using Copula Functions in Bayesian Analysis: A Comparison of the Lognormal Conjugate

Bayesian techniques have been applied to analyze sequential investment decisions in the capital budgeting literature. This article introduces copula-based Bayesian analysis as an alternative to the traditional approach where conjugate relationships do not exist. Using a numerical example, we illustrate the steps involved in the copula-based Bayesian approach. Graphical techniques for selecting an appropriate copula are also discussed. The unique ability of copulas to model nonlinear dependence rationalizes the use of copula functions as an alternative technique.     

一个投资方案的优化实例

根据某大型联合企业的现状和生产发展规划项目表，探讨如何使有限的自有资金发挥尽可能大的经济效益。根据规划模型的解，得出了企业在有限的资金条件下，应考虑新上哪 些技术和基本建设项目。