A rationale for the payback criterion

Textbooks on financial management have emphasized the shortcomings of the payback criterion for decades. However, empirical evidence suggests that in actual capital budgeting procedures the payback method is used quite regularly. Mostly, it is implemented supplementary to net present value or internal rate of return, but small companies tend to rely on payback times as single criterion. A convincing theoretical foundation for the observed use of the payback criterion is lacking. Consequently, our goal is to provide such an explanation for the payback criterion’s popularity. We demonstrate from a decision theoretical perspective how relying on payback times simplifies investment decisions in modern organizations. Gathering information from different management levels and ensuring the utilization of individual skills requires a multi-stage capital budgeting process. Accordingly, we consider fundamental organizational features of this process with respect to their impact on the payback method’s use. For this purpose, we built upon almost stochastic dominance (ASD) as modeling device. Firstly, we show that applying his concept allows to include the risk preferences of all relevant decision makers into the analysis. Secondly, we illustrate that the criteria derived from this model help conveying these preferences to those who do the preparatory work preceding the final decision. To some extent, these new criteria are generalizations of payback times. This finding provides a potential explanation for the payback’s persisting prominence.

A rationale for the payback criterion : an application of almost stochastic dominance to capital budgeting

Textbooks on financial management have emphasized the shortcomings of the payback criterion for decades. However, empirical evidence suggests that in actual capital budgeting procedures the payback method is used quite regularly. Mostly, it is implemented supplementary to net present value or internal rate of return, but small companies tend to rely on payback times as single criterion. A convincing theoretical foundation for the observed use of the payback criterion is lacking. Consequently, our goal is to provide such an explanation for the payback criterion’s popularity. We demonstrate from a decision theoretical perspective how relying on payback times simplifies investment decisions in modern organizations. Gathering information from different management levels and ensuring the utilization of individual skills requires a multi-stage capital budgeting process. Accordingly, we consider fundamental organizational features of this process with respect to their impact on the payback method’s use. For this purpose, we built upon almost stochastic dominance (ASD) as modeling device. Firstly, we show that applying his concept allows to include the risk preferences of all relevant decision makers into the analysis. Secondly, we illustrate that the criteria derived from this model help conveying these preferences to those who do the preparatory work preceding the final decision. To some extent, these new criteria are generalizations of payback times. This finding provides a potential explanation for the payback’s persisting prominence

Capturing Risk in Capital Budgeting

NPS NRP Technical ReportThis proposed research has the goal of proposing novel, reusable, extensible, adaptable, and comprehensive advanced analytical process and Integrated Risk Management to help the (DOD) with risk-based capital budgeting, Monte Carlo risk-simulation, predictive analytics, and stochastic optimization of acquisitions and programs portfolios with multiple competing stakeholders while subject to budgetary, risk, schedule, and strategic constraints. The research covers topics of traditional capital budgeting methodologies used in industry, including the market, cost, and income approaches, and explains how some of these traditional methods can be applied in the DOD by using DOD-centric non-economic, logistic, readiness, capabilities, and requirements variables. Stochastic portfolio optimization with dynamic simulations and investment efficient frontiers will be run for the purposes of selecting the best combination of programs and capabilities is also addressed, as are other alternative methods such as average ranking, risk metrics, lexicographic methods, PROMETHEE, ELECTRE, and others. The results include actionable intelligence developed from an analytically robust case study that senior leadership at the DOD may utilize to make optimal decisions. The main deliverables will be a detailed written research report and presentation brief on the approach of capturing risk and uncertainty in capital budgeting analysis. The report will detail the proposed methodology and applications, as well as a summary case study and examples of how the methodology can be applied.N8 - Integration of Capabilities & ResourcesThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

The economics of converting a sheep farm into a springbuck (Antidorcas marsupialis) ranch in Graaff-Reinet: a simulation analysis

In Graaff-Reinet, domestic livestock farming and springbuck ranching are similar in that they both rely on the rangeland for their sustainability. However, as a consequence of repeated monotonous domestic livestock farming, resulting in compromised biological productivity and diversity, the rangelands have disintegrated. This, unfortunately, has placed the future sustainability of these rangelands and the livelihoods of the local people in an indeterminate state. In recent years, there has been an increasing interest in springbuck ranching for meat production as an alternative to domestic livestock farming in the area following (a) fears of worsening environmental challenges; (b) declining profitability in commercial domestic livestock farming and; (c) growing calls for the sustainable use of these rangelands for the benefit of future generations. The springbuck has emerged as a credible alternative to utilising the rangelands - as opposed to sheep - because of its promise to addressing the above challenges. This is in an attempt to tap into the multitude of benefits that the springbuck possesses (by virtue of being part of the natural capital of the area) that have a potential towards restoring ecological integrity by extenuating some of the detrimental effects of sheep farming on the rangelands and presenting opportunities for diversifying incomes. Yet, despite the general increase in interest, a resistance towards the uptake of springbuck ranching for meat production exists. The main contention is that springbuck meat production cannot out-perform the economic returns of wool sheep farming. This study attempts to address these concerns by investigating the profitability and economic sustainability of converting a sheep farm into a springbuck ranch in Graaff-Reinet. The study uses stochastic simulation to estimate the probability distribution of some key output variables, namely: net cash income, ending cash balance, real net worth and the net present value (NPV) in evaluating the profitability of converting a 5 000ha sheep-dominated farm into a springbuck-dominated ranch under three alternative scenarios. The use of stochastic simulation allows for the incorporation of downside risk associated with the production and marketing of wool, mutton and springbuck meat. The study uses stochastic prices and yields to calculate net returns variability. Incorporating scenario analysis helped to evaluate how alternative wool sheep-dominated and springbuck-dominated combinations would perform based on the probable outcomes of different assumptions in the various scenarios. By applying stochastic efficiency with respect to a function (SERF) criterion to the simulated NPVs, this study compares the profitability of alternative scenarios based on various risk aversion coefficients. The study finds that converting a 5 000ha wool sheep dominated farm into a springbuck dominated ranch could potentially be a more profitable investment than wool sheep farming over a 15 year planning horizon, in Graaff-Reinet. The SERF results indicate that for all scenarios tested, the best strategy of converting a wool sheep dominated farm into a springbuck ranch would be one which comprise a combination of 70% springbuck, 20% mutton and 10% wool production as the likely profitable enterprise mix. Using economic sustainability analysis, the study reveals that because of low costs in springbuck ranching, springbuck meat production enterprises are most likely to be more financially sustainable than wool sheep-dominated enterprises. This suggests that rangeland owners may be better off converting their wool sheep-dominated farms into springbuck-dominated ranches. Thus, as the call for more environmentally benign rangeland utilising economic-ecological systems intensifies, rangeland owners in the Eastern Cape Karoo have a practicable option. At the very least, there exists an option to broaden their incomes whilst promoting ecological restoration with springbuck meat production

Simplified models for multi-criteria decision analysis under uncertainty

Includes abstract.Includes bibliographical references.When facilitating decisions in which some performance evaluations are uncertain, a decision must be taken about how this uncertainty is to be modelled. This involves, in part, choosing an uncertainty format {a way of representing the possible outcomes that may occur. It seems reasonable to suggest {and is an aim of the thesis to show {that the choice of how uncertain quantities are represented will exert some influence over the decision-making process and the final decision taken. Many models exist for multi-criteria decision analysis (MCDA) under conditions of uncertainty; perhaps the most well-known are those based on multi-attribute utility theory [MAUT, e.g. 147], which uses probability distributions to represent uncertainty. The great strength of MAUT is its axiomatic foundation, but even in its simplest form its practical implementation is formidable, and although there are several practical applications of MAUT reported in the literature [e.g. 39, 270] the number is small relative to its theoretical standing. Practical applications often use simpler decision models to aid decision making under uncertainty, based on uncertainty formats that `simplify' the full probability distributions (e.g. using expected values, variances, quantiles, etc). The aim of this thesis is to identify decision models associated with these `simplified' uncertainty formats and to evaluate the potential usefulness of these models as decision aids for problems involving uncertainty. It is hoped that doing so provides some guidance to practitioners about the types of models that may be used for uncertain decision making. The performance of simplified models is evaluated using three distinct methodological approaches {computer simulation, `laboratory' choice experiments, and real-world applications of decision analysis {in the hope of providing an integrated assessment. Chapter 3 generates a number of hypothetical decision problems by simulation, and within each problem simulates the hypothetical application of MAUT and various simplified decision models. The findings allow one to assess how the simplification of MAUT models might impact results, but do not provide any general conclusions because they are based on hypothetical decision problems and cannot evaluate practical issues like ease-of-use or the ability to generate insight that are critical to good decision aid. Chapter 4 addresses some of these limitations by reporting an experimental study consisting of choice tasks presented to numerate but unfacilitated participants. Tasks involved subjects selecting one from a set of five alternatives with uncertain attribute evaluations, with the format used to represent uncertainty and the number of objectives for the choice varied as part of the experimental design. The study is limited by the focus on descriptive rather than real prescriptive decision making, but has implications for prescriptive decision making practice in that natural tendencies are identified which may need to be overcome in the course of a prescriptive analysis