Donald W. Gribbin

Cost Efficiency Benchmarking for Operational Units with Multiple Cost Drivers

We consider the activity-based costing situation, in which for each of several comparable operational units, multiple cost drivers generate a single cost pool. Our study focuses on published data from a set of property tax collection offices, called rates departments, for the London metropolitan area. We define what may be called benchmark or most efficient costs per unit of driver. A principle of maximum performance efficiency is proposed, and an approach to estimating the benchmark unit costs is derived from this principle. A validation approach for this estimation method is developed in terms of what we call normal-like-or-better performance effectiveness. Application to longitudinal data on a single unit is briefly discussed. We also consider some implications for the more routine case when costs are disaggregated to subpools associated with individual cost drivers.

Accounting Practitioners' Views of the Relative Importance of Teaching and Research in Accounting Education

Abstract Within the accounting profession and academia there is a continuing debate over the relative importance of research and teaching. National leaders of the accounting profession have made their “pro-teaching” views known. To determine how generally accepted these views are, we conducted a survey of practicing accountants. In general, the results indicate that accounting practitioners hold opinions consistent with those of the national leadership, that is, the respondents valued quality teaching over quality research. These results may be of interest as accounting academicians debate the direction of future accounting programs within the universities.

A Cost Allocation Model for Random-Variable Cost Functions

Abstract Traditional cost allocation procedures do not explicitly consider the stochastic nature of costs. This paper presents a methodology that can be used to incorporate the probabilistic aspect of cost estimates. Such probabilistic information has the potential to be much more informative for decision-making purposes. The specific objectives of this paper are to: (1) illustrate the simplicity with which stochastic cost estimation procedures can be implemented; (2) demonstrate how computer software packages can be utilized to estimate the underlying parameters even when the data is non-normally distributed; and (3) illustrate how a predetermined measure of “conservatism” can be incorporated into internal decision making. The study includes an illustration which demonstrates how the discussed procedures can easily be implemented by users with only minimal statistical expertise.