A Note on Nucleolus/MTPD Accounting Allocations

The nucleolus linear programming (LP) method for allocating joint costs associated with a shared resource often stops short of uniquely specifying all savings allocations. Barton [1] recently presented the minimum total propensity to disrupt (MTPD) as a secondary criterion for uniquely determining those allocations not provided by the initial LP solution. Barton demonstrated the uniqueness of his solution on a specific example with a four-entity grand coalition. We show a practical approach for implementing Barton's two-step procedure. Our purpose is to make the nucleolus/MTPD model readily accessible to a wide range of practitioners using commonly available spreadsheet tools. We also demonstrate the global optimality of the allocations that the model provides.     

JOINT PRODUCT COST ALLOCATION IN THE CONTEXT OF COST-PLUS PRICING DETERMINATIONS WITH NON-UNIFORM MARKUPS

Companies that use cost-based pricing sometimes manufacture products that involve joint cost allocation. A problem with this is that, while product prices are a function of the full cost, joint cost allocation methods using net realizable values depend on the product prices. This paper demonstrates that when all costs and production quantities are known or can be budgeted, it is possible to simultaneously determine unique product prices (having non-uniform markup rates) and cost allocations using the net realizable value method.     

Simultaneous Determination of Joint Product Cost Allocations and Cost-Plus Prices*

Use of the net realizable value approach for joint manufacturing cost allocations requires knowledge of selling prices of joint products. However, joint product selling prices themselves are functions of the allocated costs under a cost-plus pricing policy. In this case, it is necessary to determine joint cost allocations and joint product prices simultaneously. This paper applies a nonlinear programming (NLP) approach to simultaneously determine the optimal joint production decision, joint product cost-plus prices, and joint cost allocations using the net realizable value method. The NLP solution provides not only the optimal joint production and pricing decisions, but also the necessary conditions for such optimal decisions.     

A Unique Solution for the Nucleolus in Accounting Allocations*

The nucleolus method has been suggested in the literature as a means for accounting decision makers to allocate joint costs in situations where entities share a common resource. The nucleolus has the advantage, vis-à-vis other methods, of maximizing the benefit to the least-well-off entity or groups of entities, and therefore reducing the possibility that one or more entities may desire to withdraw from the sharing arrangement. The nucleolus is basically a linear programming model. Because of its formulation, the nucleolus may yield multiple optimal solutions. No reformulation of the nucleolus seems to exist to overcome this problem The minimum total propensity to disrupt (MTPD) is suggested as an extension of the nucleolus to identify unique values for allocations with multiple solutions. The MTPD, while exhibiting deficiencies as a stand-alone method, is similar in overall objective to the nucleolus and its mathematical function possesses a unique minimum. It is therefore the logical method for identifying a unique nucleolus solution. The use of the MTPD extension is critically examined through a representative application.     

Neural Networks: A New Tool for Predicting Thrift Failures*

A neural network model that processes input data consisting of financial ratios is developed to predict the financial health of thrift institutions. The network's ability to discriminate between healthy and failed institutions is compared to a traditional statistical model. The differences and similarities in the two modelling approaches are discussed. The neural network, which uses the same financial data, requires fewer assumptions, achieves a higher degree of prediction accuracy, and is more robust.     

The Representation and Impact of Information System Reliability on Cost Variance Decisions*

Management does not directly observe cost variance processes from the production system; instead, management depends on a report from the cost variance information system as to whether a process is in control or out of control. Unfortunately, cost variance information systems are not always perfectly reliable. Accordingly, this paper extends the cost variance analysis model to include reliability of the cost variance information system. Reliability is introduced by distinguishing between the report from the information system and the actual cost variance. Although previous cost variance models do not include reliability, management is still likely to be aware of the lack of reliability in cost variance systems. To account for this lack of reliability, management is likely to use any of a number of heuristics. This paper demonstrates that ad hoc heuristics are unlikely to result in the same solutions suggested by the analytic model. In addition, it is shown analytically that not including reliability in cost variance models can lead to examining variances that do not require investigation and not examining variances that do require investigation.     

MODELING MANAGERS' EFFORT-LEVEL DECISIONS FOR A WITHIN-PERSONS EXAMINATION OF EXPECTANCY THEORY IN A BUDGET SETTING

Ronen and Livingstone [42] have proposed that expectancy theory can provide a unifying framework for accounting research aimed at the motivational impact of budgets on managers. Unfortunately, researchers attempting to use this approach have employed an inappropriate across-persons methodology. This paper uses the decision modeling approach we recently developed [48] to provide a within-persons examination of Vroom's force model in a budget setting. An examination of two hypotheses questions the belief expressed in the budget literature to the effect that the use of currently attainable cost standards results in a cost budget with unique motivating characteristics. Strengths of this research are the use of the within-persons approach and the use of an innovative measure of motivational force.     

The Choice of Depreciation Method Under Uncertainty*

This study presents a framework for choosing between depreciation methods when future cash flows from operations are not assumed known with certainty but only in probabilistic terms. Specifically, the accelerated depreciation method and the straight-line depreciation method are compared and mathematical conditions are derived for the depreciation method that should be adopted in different circumstances and under different tax systems. It is shown that, contrary to conventional wisdom, the straight-line depreciation method is the preferred method for lowering the company's present value of tax liability in various realistic situations.     

Concepts,Theory, and Techniques INFLATION,MAINTENANCE OF CAPITAL,AND THE IRR MODEL OF CAPITAL BUDGETING*

Businesses operating under inflationary conditions need capital-budgeting models that help them judge the adequacy of returns on their investments and also allow them to keep capital intact by considering the erosive effects of inflation. The model proposed in this paper computes a modified internal rate of return (IRR); if cash inflows from a project are divided between earnings and recovery of capital, total recovery equals that amount which the capital-budgeting concept adopted by the business specifies (such as the original investment in constant dollars or its replacement cost). Under this model, a project should be accepted only if this computed rate equals or exceeds a hurdle rate that consists of the inflation-free rate of return plus the effect of inflation on such a return. Other modifications to the IRR model suggested in the literature do not completely satisfy the objective of capital budgeting under inflationary conditions.     

THE INVESTIGATION OF COST VARIANCES: A FUZZY SET THEORY APPROACH*

In a standard costing system, deviations (variances) of actual cost from standard cost should be investigated in order to help management identify the causes of the variances and who is responsible for them before corrective actions are taken. In reality, however, actual cost rarely equals standard cost and so many variances occur that it is impractical and uneconomical to investigate all of them. These two conflicting factors—the necessity of investigating cost variances and the impracticality of investigating all the variances—present management with the problem of deciding which variances to investigate. In this paper a model, based on fuzzy set theory, for the cost-variance investigation is proposed and applied to an actual investigation problem faced by a manufacturing company.     

Single and Multiple Period Decision Models for Analysis of Quality and Quantity of Validation*

This paper investigates a single period model for the analysis of the impact of the quality of the validation effort. The single period model uses a Bayesian approach to find that validation is a critical point process. That model is then extended to allow for the uncertainty of the validation process to determine the quality of the underlying model. Some monotonicity results are developed for the model and investigated in light of the process being a critical point process. The model indicates that, consistent with comments from real world settings, the impact of the quality of the validation effort can be substantial. The paper also presents two multiperiod models of the impact of the quantity of the validation effort. In practice, the development of an expert system may follow a recurring multiperiod life cycle, where a prototype is built, the system is validated to determine how well it performs, and based on that performance, is either funded or not funded. The first multiple period model assumes that validation and funding occurs at each point in the PVF budget cycle. The model employs Bayesian revision of probabilities to update the prior probability of obtaining a model with an appropriate level of success. It is found that the critical point for multiperiod problems is different than that for single period problems. This model forms the basis of the second model. The second multiple period model extends the first by assuming that the quantity of validation can be varied. The more validation, the more likely that flaws in the model will be found. Thus, the more validation, the better the understanding of the level of performance of the model.     

IMPACT OF PARTICIPATION IN THE BUDGETARY PROCESS ON MANAGERIAL ATTITUDES AND PERFORMANCE: UNIVERSALISTIC AND CONTINGENCY PERSPECTIVES*

Data from responsibility-center managers reveal that greater budgetary participation contributes to managerial performance and attitudes in high-environmental-uncertainty situations but hampers performance and attitudes in low-uncertainty situations. Higher budgetary participation reduces managers' propensity to create slack in high- (but not in low-) uncertainty conditions.     

A SIMULATION OF THE EFFECTS OF ALTERNATIVE RULE SYSTEMS FOR JAI ALAI*

The inequities of the present system of rules in jai alai are documented on the basis of empirical information and theoretical results from a Monte Carlo simulation model. Some suggestions are made for changing the rules in order to make the game more equitable for both players and bettors. The simulation model is used to compare the effectiveness of the suggested rules with that of the present rules.     

REFINEMENTS IN THE ISMAIL-LOUDERBACK STOCHASTIC CVP MODEL*

This paper presents results concerning the Ismail-Louderback stochastic cost-volume-profit model. For the case where demand is normally distributed, an analytic expression for the output that maximizes the probability of achieving specified profits is obtained and a new procedure for determining the output that maximizes the profits, given a target level of probability of their being achieved, is developed. If opportunity costs of lost sales are zero, then analytic expressions for both the above outputs are obtained for any demand distribution.     

VALIDATION OF EXPERT SYSTEMS- WITH APPLICATIONS TO AUDITING AND ACCOUNTING EXPERT SYSTEMS*

This paper proposes a set of definitions for the concepts “validation” and “assessment” applied to expert systems (ESs). It develops a framework for this validation and demonstrates the framework on existing accounting and auditing ESs to elicit some of the research issues involved in ES validation. Validation is critical to the design and implementation of decision-making ESs. In a setting where objectivity is sought and variance is avoided, validation ascertains what a system knows, knows incorrectly, or does not know. Validation ascertains the system's level of expertise and investigates the theoretical basis on which the system is based. It evaluates the reliability of decisions made by the system. The validation framework developed in this paper is research methods. It is designed to reflect the unique aspects of ESs (in contrast to other types of computer programs) and can be used by ES developers as a basis from which to perform validation and by researchers as a framework to elicit research issues in validation.     

TOTAL SETUP LOT SIZING WITH QUANTITY DISCOUNTS*

Often, order quantity decisions are made by purchasers facing a price schedule of quantity discounts. Traditional solution procedures have consisted of the evaluation of total cost at numerous price-break points in search of the lowest total cost. This approach is tedious and not particularly informative, especially when one is faced with lengthy schedules. This paper presents a total setup lot-sizing model that reduces the computations required to find the least-total-cost quantity, given parameters from a supplier's price schedule. The parameters are first obtained by simple regression (graphical or computer) and in themselves can provide valuable insight for the purchaser's decision making. A total setup lot-sizing model is next developed to define a “critical interval” that contains the solution. The model and algorithm are tested under a variety of conditions. Their application offers the decision maker a convenient alternative to determine the best quantity to order from a tendered price schedule.     

Compensation Schemes,Skill Level,and Task Performance: An Experimental Examination*

The effect of budget-based incentive compensation schemes is a fundamental issue in developing and implementing organizational control systems. This study investigates the effect of alternative compensation schemes on performance and satisfaction. A theoretical model outlining the primary relationships is formulated and related hypotheses specified. The hypotheses reflect an integration of agency theory and organization behavior research. Across-group and within-group effects are investigated using both single-period and multiperiod analyses. A laboratory study involving 40 subjects is undertaken and the findings provide insights into the individual and group effects of alternative compensation schemes and the dynamics of changing Compensation schemes on productivity and satisfaction. Specifically, a relationship is found between compensation schemes and performance. The effect on performance is independent of the compensation scheme's perceived fairness. Satisfaction is a function of the congruence between the preferred scheme and the implemented scheme.     

An Application of Markov Chain Analysis to the Game of Squash*

If the score in a squash game is tied late in the game, one player has a choice of how many additional points (from a prespecified set of possibilities) are to be played to determine the winner. This paper constructs a Markov chain model of the situation and solves for the optimal strategy. Expressions for the optimal strategy are obtained with a symbolic algebra computer package. Results are given for both international and American scoring systems. The model and analysis are very suitable for educational purposes. The resulting Markov chain is small enough that it can be easily presented in a classroom setting, yet the model is sufficiently complex that algebraic manipulation is nearly hopeless. The final results illustrate the power of the combination of mathematical and computer modeling applied to a problem of practical interest.