Empirical validity of the claim that overhead costs are driven not by production volume but by transactions resulting from production complexity is examined using data from 32 manufacturing plants from the electronics, machinery, and automobile components industries. Transactions are measured using number of engineering change orders, number of purchasing and production planning personnel, shop-floor area per part, and number of quality control and improvement personnel. Results indicate a strong positive relation between manufacturing overhead costs and both manufacturing transactions and production volume. Most of the variation in overhead costs, however, is explained by measures of manufacturing transactions, not volume.

Conventional management accounting principles used to evaluate relevant costs have been developed under the assumption of deterministic manufacturing settings. Manufacturing operations, however, are complex and stochastic. In this paper we examine the impact of stochasticity in the production process on relevant costs based on a dynamic assessment of capacity constraints. We develop a model to analyze the behavior of relevant costs with respect to changes in the expected duration and variability in set-ups and processing. An implication of this analysis is that for profit maximization capacity will exceed expected demand if production rates or demand are stochastic.

This paper employs a generalized principal‐agent model to analyze accounting situations in which the outcome is not jointly observable and the principal's and agent's preferences are multiattribute in nature. This requires the consideration of accounting signals for risk‐sharing (or insurance) information in addition to performance evaluation (or incentive) information. It is shown that precisely two factors determine whether a signal will be valuable in the agency relationship: Observability of the agent's effort and the principal's multivariate risk neutrality. Sufficient conditions for various accounting signals to have value are also developed. Furthermore, when multiple accounting signals are available, it is shown that under certain conditions, the insurance components of the multiple signals can be aggregated into a single aggregate insurance measure and the incentive components of the signals can be aggregated (via a different aggregation procedure) into another aggregate incentive measure. Résumé. Les auteurs utilisent un modèle généralisé mandant‐mandataire pour analyser les situations comptables dans lesquelles le résultat n'est pas observable conjointement et les préférences du mandant et du mandataire comportent, par nature, de multiples attributs. Cela exige la prise en considération d'indicateurs comptables relatifs à l'information sur le partage des risques (ou de l'assurance) en plus de l'information relative à l'évaluation du rendement (ou aux stimulants). Les auteurs démontrent que deux facteurs permettent de déterminer avec précision si un indicateur sera valable dans la relation de mandataire: le caractère observable de l'effort du mandataire et la neutralité multivariée du mandant à l'égard du risque. Des conditions suffisantes pour que les divers indicateurs comptables soient valables sont également établies. En outre, lorsque des indicateurs comptables multiples sont disponibles, les auteurs démontrent que dans certaines conditions, les éléments des indicateurs multiples liés à l'assurance peuvent faire l'objet d'une regroupement en une seule mesure globale d'assurance, et que les éléments des indicateurs liés aux stimulants peuvent faire l'objet d'une regroupement (au moyen d'une méthode différente) en une autre mesure globale des stimulants.

Examines relationships between support activity costs and prices. Assumptions and definitions for various components of the cost and demand functions; Optimal pricing and capacity decisions of a centralized monopolist firm; Activity-based unit costs.

Recent research on cost driver analysis by Miller and Vollman (1985) and Cooper and Kaplan (1987) suggests that transactions deriving from the diversity of a firm's product line and the complexity of its production process, in addition to output volume, drive overhead costs. As a consequence, it is argued, conventional cost accounting systems based only on volume-related measures, such as units of output, direct labor hours, or machine hours, produce biased and materially misleading cost estimates for managerial decisions on price and product line (whether to continue or discontinue products, or to offer additional products). Systematic biases in cost estimates may also lead to distortions in flexible budgeting systems, variance analyses, and responsibility-accounting systems. Perhaps more important in the long run, omission of operations-based cost drivers may distort the investigation of the likely effects on costs of changes in operating strategies. Many firms have moved ahead on the basis of this perceived need for more accurate cost estimates and have designed and implemented activity-based costing systems (Schiff 1991). From an academic perspective, however, there is a need for further formal empirical research in this field. Cooper and Kaplan's (1987) evidence is based on field-study discussions with managers in a variety of manufacturing settings and experimentation with cost allocation and product-costing systems based on transactions. Foster and Gupta (1990) provide some of the first empirical evidence on the correlation of manufacturing overhead with output volume and operations- based measures that reflect characteristics of the manufacturing process. Using data obtained from 37 plants of a single manufacturing firm, Foster and Gupta found that most of the volume-related measures of output were highly correlated with manufacturing overhead (MOH), but because only a few measures of manufacturing complexity and efficiency were highly correlated with MOH, their findings leave the impression that systems based on just volume may not significantly distort information generated for managerial decision making. In contrast, we find empirical evidence in favor of incorporating operations-based cost drivers along with measures of volume in cost driver models. We draw upon previous work in cost accounting and economics to develop analogs in the airline industry for product diversity, production run volumes, and process complexity, and propose a framework for cost driver analysis in the U.S. airline industry. Using a panel of quarterly data for 1981-1985 compiled primarily from traffic and financial statistics submitted by carriers to the Civil Aeronautics Board (CAB) and Department of Transportation (DOT), we specify and estimate a multivariate system of cost functions with multiple cost drivers for the industry during the transition following deregulation. We find both volume- and operations-based cost drivers to be statistically significant. We also demonstrate the potential managerial importance of the operations-based drivers by explaining variations in marginal costs across airlines in terms of operating strategies reflected in the cost driver values. Empirical cost driver analysis is managerially significant for the industry and period that we examine. The proportion of indirect costs is large, and identification of input consumption for specific services is difficult. During the transition following deregulation, carriers adopted a rich variety of strategies to improve productivity, reduce costs, and increase market share. These strategies directly involved both volume- and operations-based cost drivers. The analytical framework and model that we have developed on the basis of prior literature concerned with the airline industry enable us to examine the differential cost effects of some of the most important strategies adopted.

Reviews the book "Improving Company Productivity: Handbook With Case Studies," by John W. Kendrick.

Recent attention on labor productivity has resulted in many manufacturing concerns negotiating incentive contracts with the labor force. Such incentive contracts provide for management and the work force to share monetary benefits generated by productivity gains. These gain‐sharing contracts require a benchmark level of labor productivity from which to assess productivity gains. This paper examines gain‐sharing contracts in an agency setting, deriving conditions under which contracts using a performance evaluation measure of a ratio of total labor hours to standard direct labor hours might be optimal. These optimality conditions are characterized in terms of the fixed and variable cost components of the total labor requirement and the standard direct labor requirements. An observed gain‐sharing contract based on such a measure is then evaluated using actual production data. The generalized method of moments is employed to estimate the key production parameters, indicating that the optimality conditions are violated. The characterization of optimal gain‐sharing contracts thus clarifies the manner in which productivity must be measured if these programs are to provide the proper incentives to the work force. Résumé. L'attention récemment accordée à la productivité de la main‐d'oeuvre a donné lieu à la négociation de contrats de rémunération au rendement dans de nombreuses entreprises de fabrication. Ces contrats de rémunération au rendement prévoient un partage des bénéfices monétaires résultant des gains de productivité, entre la direction et la main‐d'oeuvre. Les contrats de participation aux bénéfices nécessitent la détermination d'un point de repère en ce qui a trait à la productivité de la main‐d'oeuvre à partir duquel on puisse évaluer les gains de productivité. Les auteurs analysent les contrats de participation aux bénéfices dans le contexte d'une relation de mandataire, en dérivant les conditions dans lesquelles le contrat prévoyant une mesure du rendement fondée sur le rapport des heures de main‐d'oeuvre totales aux heures de main‐d'oeuvre directe standard peut être optimal. Ces conditions d'optimalité sont définies sous forme d'éléments de coûts fixes et de coûts variables des besoins en heures de main‐d'oeuvre totales et en heures de main‐d'oeuvre directe standard. Les auteurs analysent un contrat de participation aux bénéfices basé sur ce genre de mesure et l'évaluent ensuite à partir des données réelles de production. Ils recourent à la méthode généralisée des moments pour estimer les principaux paramètres de production indiquant que les conditions d'optimalité sont transgressées. La définition du contrat optimal de participation aux bénéfices éclaire ainsi la manière dont la productivité doit être mesurée pour que de tels contrats offrent à la main‐d'oeuvre les stimulants appropriés.

Recent studies report an increasing use of nonfinancial measures such as product quality, customer satisfaction, and market share in performance measurement and compensation systems. A growing literature suggests that because current nonfinancial measures are better predictors of long-term financial performance than current financial measures, they help refocus managers on the long-term aspects of their actions. However, little empirical evidence is available on the relation between nonfinancial measures and financial performance, and even less is known about performance impacts of incorporating nonfinancial measures in incentive contracts. Using time-series data for 72 months from 18 hotels managed by a hospitality firm, this study provides empirical evidence on the behavior of nonfinancial measures and their impact on firm performance. The results indicate that nonfinancial measures of customer satisfaction are significantly associated with future financial performance and contain additional information not reflected in the past financial measures. Furthermore, both nonfinancial and financial performance improve following the implementation of an incentive plan that includes nonfinancial performance measures.