Abstract
Research Question: Under which conditions is the adoption of activity-based costing (ABC) beneficial to the business-unit and, hence, represents the optimal costing system design (CSD)? Motivation: Identifying the situations under which ABC is beneficial with regard to the performance of the business-unit and, thus, represents the optimal CSD is important in order to make a correct decision to invest in ABC. This necessitates the adoption of the matching form of fit when examining the relationship between the influential factors and ABC adoption as an optimal CSD due to its ability to reflect when ABC is beneficial and, therefore, indicate the optimal CSD. This study builds on Ittner et al. (2002) to examine this relationship from the standpoint of the matching form of fit, and also extends this line of research by examining the effect of the most key influential factors, using a sufficiently comprehensive multi-dimensional production complexity (PC) measure. Idea: This paper examines the role of the key influential factors on ABC adoption as an optimal CSD from the standpoint of the matching form of fit, using a sufficiently comprehensive multi-dimensional PC measure. Data: The data were collected from 200 Saudi manufacturing business-units. Tools: The questionnaire survey strategy was used to collect the data, which were then analysed using the residual analysis (RA) technique. Findings: Unexpectedly, the results of the RA showed that none of the examined key factors of competition, indirect costs, PC and information technology quality (IT quality) affects ABC adoption as an optimal CSD from the viewpoint of the matching form of fit. Contribution: This research contributes to the ABC adoption research by examining the situations under which ABC is beneficial and, hence, represents the optimal CSD through examining the impact of the key influential factors on ABC adoption as an optimal CSD from the standpoint of the matching form of fit.
Highlights
Activity-based costing (ABC) proponents have emphasised that, to obtain the benefits of activity-based costing (ABC), ABC should be the optimal costing system design (CSD) with respect to the assignment of indirect costs to products (Cooper, 1988b; Cooper, 1989b; Kaplan & Cooper, 1998)
Given: (1) the importance of identifying the situations under which ABC is beneficial and, represents the optimal CSD to make a correct decision regarding investing in ABC; and (2) the limitations of Ittner et al (2002) regarding the number of examined contingency factors and measurement of production complexity (PC), the aim of this paper is to examine the influence of the key contingency factors, namely the level of competition, the level of indirect costs, PC and IT quality, on ABC adoption as an optimal CSD from the standpoint of the matching form of fit, using a sufficiently comprehensive multi-dimensional PC measure
Due to: (1) the importance of identifying the situations under which ABC is beneficial and, represents the optimal CSD to make a correct decision about investing in ABC; and (2) the limitations of Ittner et al (2002) regarding the number of the examined contingency factors and measurement of PC, this paper aimed to examine the key impacts on ABC adoption as an optimal CSD from the viewpoint of the matching form of fit, utilising a sufficiently comprehensive multidimensional PC measure
Summary
Activity-based costing (ABC) proponents have emphasised that, to obtain the benefits of ABC, ABC should be the optimal costing system design (CSD) with respect to the assignment of indirect costs to products (Cooper, 1988b; Cooper, 1989b; Kaplan & Cooper, 1998). The optimal CSD is one that balances the cost of measurement required by the CSD and the cost of error resulting from poor decision-making based on distorted product costs (Cooper, 1988b; Kaplan & Cooper, 1998; Stuart, 2013; Drury, 2018) It represents a point where the marginal costs and benefits of improving the CSD by increasing its complexity, in relation to the assignment of indirect costs to products, are equal, and where any excess or shortages related to improving the CSD would lower its optimisation (Cooper, 1988b). Having a more complex than required costing system, where the cost of measurement exceeds the cost of error, or a less complex than required costing system, where the cost of error exceeds the cost of measurement, is harmful to the performance of the business-unit (Cooper & Kaplan, 1991; Cooper, 1989b; Stuart, 2013; Ittner et al, 2002; Pizzini, 2006) This indicates that the relationship between CSD and the outcome representing CSD optimality, e.g., financial performance, is curvilinear. The matching form of fit assumes that the relationship between CSD and the outcome representing its optimality is curvilinear and impacted by the contingency factors (Burkert et al, 2014).
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