Knowledge that Transforms

[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 stimates 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.]

[Audit planning is a crucial task in the audit process. While making planning decisions, auditors have a large amount of information available to them and their existing knowledge structures influence how this information is used to form a problem representation. This problem representation has a significant effect on all subsequent decision making. The purpose of this study is to investigate the nature and evolution of auditors' planning problem representations by an examination of free recalls. In the cognitive psychology literature, it has been reported that, as decision makers accumulate more experience, their knowledge structures change to embody more total knowledge, more knowledge of relationships, and more abstract knowledge. In the context of an audit planning task, I predicted that problem representations formed by more experienced auditors would reflect these characteristics. To test the hypotheses, an experimental study was conducted with 211 practicing auditors. Subjects were from 16 offices of the then Big Eight public accounting firms, with experience levels ranging from one month to 30 years. Using experimental materials that consisted of approximately 20 pages of background information on a hypothetical audit client, subjects completed a planning task, followed by a background questionnaire, and a surprise recall task. The free recalls provide indirect evidence on the nature of the problem representations formed during the planning task. The results suggest that the problem representations of managers and partners may be different from those of seniors or juniors. The manager/partner recalls included a smaller percentage of simple case facts and a higher number and percentage of abstractions from the basic facts. These results have potential implications for audit practice. To the extent that the managers and partners form "better" problem representations and are actively involved in the process, more effective and efficient audit planning might be possible. However, more research needs to be conducted to determine the specific effect of the exhibited differences on planning decisions.]