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While management-accounting research continues to focus on cost drivers, research has recently begun to examine revenue drivers. We review the research on revenue drivers with reference to five revenue-driver models in the accounting literature. The revenue drivers identified by quantitative empirical research are located in a revenue-driver model based on their levels of analysis (customer, product, organization, industry) and other characteristics of a revenue driver–revenue relation. Implications of this model for research are discussed.

The purpose of this paper is to highlight the particularities of the time consumption of transactions performed in an insurance firm and the prospective impact on costing.

This paper uses the results of an archival study conducted on data collected in an insurance firm.

The results suggest that the reasons underlying the heterogeneity of transactions’ time consumption are multiple and rule out a systematic and unique explanation. They lend support to the importance of the “human effect” in explaining the time consumption of service transactions and support the need for more research into the evolution of marketing thought that subordinates the concept of transaction to the concept of relationship. In addition, our results not only suggest that the drivers of time consumption and their importance are contingent on the type of service activity performed within the same firm, but also that inside a generic service activity, deviations in time consumption remain due to the provision of specific services.

Services have their own characteristics which make it difficult to trace their resource consumption. Yet limited research has focused on examining the impact of services’ characteristics on predicting costs. Our findings contribute to our understanding of such impact and cast doubt on the possibility of obtaining accurate costs for very detailed transactions for an acceptable cost-benefit trade-off.

This chapter applies the Consortium for Advanced Management, International (CAM-I) Activity-Based Cost Management (ABC/M) tool to paratransit. The intent is to enable agencies sponsoring rides to save money through sharing rides and vehicle-time.

Several paratransit cost-allocation models from Transit Cooperative Research Program (TCRP) and other sources are reviewed and one is adapted to the ABC/M methodology, based upon the author’s previous work proportionately allocating ride time among sponsoring agencies at a consolidated human service transportation agency and the price sheets used in contracted operations to minimize financial risk.

Through application of the principles of ABC/M, paratransit providers can properly allocate costs, determine the costs of providing proposed new services, plan for future vehicle acquisitions, and motivate their customers to tailor their transportation needs in a manner that will save them money and boost efficiency.

University-based transportation studies programs may be motivated to apply these strategies to urban and rural paratransit providers that serve several customer agencies.

If agencies sponsoring paratransit rides understand that funds can purchase more rides during off-peak hours or if rides are shared with clients of other agencies, then paratransit resources can be used more efficiently and to the benefit of more individuals.

By enabling the provision of more rides, a greater number of riders will be enabled to reach necessary services and participate in community life.

This is the first application of the ABC/M methodology to paratransit (and transit) and possibly to social services.

As manufacturers continue to increase their level of automation, the issue of how to allocate machinery costs to products becomes increasingly important to product profitability. If machine costs are allocated to products on a basis that is incongruent with the realities of machine use, then income and product profitability will be distorted. Adding complexity to the dilemma of identifying an appropriate method of allocating machine costs to products is the changing nature of machinery itself. Depreciation concepts were formulated in days when a machine typically automated a single operation on a product. Today’s collections of computer numerically controlled machines can perform a wide variety of operations on products. Different products utilize different machine capabilities which, depending on the function used, put greater or less wear and tear on the equipment. This paper presents a mini-case that requires management accountants to consider alternative machine cost allocation methods. The implementation of an activity-based method allows managers to better match machine cost consumption to products. Better matching of machine costs to products enables better strategic decisions about pricing, mix, customer retention, capacity utilization, and equipment acquisition.

This chapter demonstrates how the ‘golden rule’ can be applied by operators of flexible transport services to improve investment and pricing decisions.

The chapter explains why an appropriate decision making framework is particularly important for operators of flexible transport services and compares the traditional economic framework of fixed versus variable costs to the decision-oriented approach that analyses the activities of a firm in terms of costs that are avoidable (i.e. specific to a particular activity) and costs that are shared amongst a number of activities. The chapter introduces the ‘golden rule’ of decision making and discusses issues in implementing the rule.

An economic framework for decision making is particularly important for smaller scale transport operations (such as flexible transport services) because ‘lumpy’ investment costs are more significant than for larger operators. The traditional economic approach divides costs into fixed costs and those which vary by patronage. A better framework for decision making divides costs into those which are specific to a particular activity and, therefore, avoidable if that activity ceases, and those costs which are common to more than one activity.

Using this framework allows operators to apply the ‘golden rule’ in pricing their services so that the avoidable costs of each activity are recovered and the enterprise covers its shared costs overall.

This chapter will be useful to operators of flexible transport services who are new to the industry or are reacting to changes in the funding environment.