Only one variable (size) has consistently been identified
as a significant variable. Product diversity was identified as a significant variable in two of the four studies
and cost structure was not a significant variable at the 5% level in the three studies that examined this variable. The interaction study by Cagwin and Bouwman (2002) reported a positive association between
the interactions of ABC with business complexity and the use of other initiatives employed concurrently
with ABC (e.g. JIT, TQM, BPR etc.) and improvements in return on investment.
The literature review identified only two studies that sought to classify product cost systems by characteristics
other than by the discrete alternatives of traditional and ABC systems. The first by Abernethy
et al. (2001) adopted an interactive approach to fit. Based on case study research they classified product
costing systems by their level of sophistication using data collected from five divisions within two firms in
Australia. Four divisions had a low level of sophistication but there was a reasonable level of satisfaction
with the information provided by the costing systems at three of the four divisions. The authors attributed
this to the ‘fit’ between the levels of sophistication of the costing system and the contextual factors of
cost structure and product diversity. All three divisions had low product diversity and low overhead costs.
In the fourth division overhead costs and product diversity were high. Management was dissatisfied with
the costing system and the authors attributed this to the lack of ‘fit’ between the contextual factors and
the existing costing system.
The fifth division operated a sophisticated traditional costing system. The users were very satisfied
with the costing system. Product diversity was high but this was facilitated by investment in advanced
manufacturing technology (AMT) resulting in overhead costs being mainly associated with investment
in AMT, which represented facility-sustaining costs. In these circumstances the authors argued that there
was little justification for sophisticated ABC systems because the batch-related and product sustaining
costs associated with product diversity were low thus reducing the need for incorporating a variety of
non-volume-based drivers.
The second study that adopted a broader perspective to classify costing systemswas a survey undertaken
by Drury and Tayles (2005). A measure of cost system complexity represented the dependent variable.
An 8-point scale was used to obtain information relating to the number of cost pools and different types
of cost drivers. The two scales were aggregated to subjectively determine a measure of cost system
complexity.6 The contextual variables, derived mostly from single questions, were incorporated into a
multiple regression model with the dependent variable being the measure of cost system complexity. Four
variables were statistically significant – product diversity, degree of customization, size and corporate
sector (the financial and service sectors had significantly higher levels of cost system complexity compared
with companies operating in the manufacturing sector).