The Research of Effectiveness of Using ABC in China’s Listed Companies

The Research of Effectiveness of Using ABC
in China’s Listed Companies
XU Yan1, CAO Deli2
1 College of Accounting, Central University of Finance and Economics, P. R. China, 100081
1 2 College of Management and Economics, North China University of Technology, P.R.China, 100144
[email protected]
Abstract: Since it was introduced to China in the early 1990s, the research and application of activity
based costing (ABC) have been improved in China. But compared to the developed western countries,
the research and application of ABC in China are still at developing stage. There is no empirical
research on the effectiveness of activity-based costing application in China. Based on the theory of the
activity-based costing, this paper summarizes the advantages of the activity-based costing and reviews
the literature about ABC. The paper demonstrates that the return on asset of listed companies in China is
positively relevant with ABC application, and analysis result verifies the effectiveness of application of
activity-based costing in the listed companies of China.
Keywords: Activity-based costing, Effectiveness, Return on assets
1. Introduction
Activity based costing (ABC) is a costing method. The basic principle of ABC is “products consume
activities and resources consume activities.” ABC has predominantly been used to support strategic
decisions such as pricing, outsourcing and identification and measurement of process improvement
initiatives. Managers focus on activities, allocate indirect cost by using different cost drivers and get
more accurate costs in business. Compared with traditional costing method, instead of on only one
distribution base, ABC allocates cost on several distribution bases. By using ABC method, managers can
find different cost drivers of different indirect costs; many indirect costs become controllable which are
uncontrollable when in traditional cost accounting. In this way an organization can establish the true
cost of its individual products and services. ABC also makes it very clear that integrated costs associated
with the services that the customer demands play a crucial role in determining each customer's
contribution to net profit.
ABC can provide more appropriate accounting information required by management than traditional
costing can. In providing the required information, management can give appropriate consideration to
the cost of obtaining and providing the information in relation to the benefits to be derived from the
information. ABC can help managers to control costs more effectively; to make decisions more properly
and to realize the optimization of resource distribution. So, we assume that ABC application helps to
improve performance.
The remainder of the paper is organized as follows The second section presents situation of the ABC
application in China. The third section reviews the literature and develops the hypothesis. The fourth
section presents data analysis and discuses the effectiveness of ABC application in China. The last
section concludes.
：
2. The situation of ABC application in China
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Since it was introduced to China in the early 1990s, practitioners and researchers have been exploring
the ABC application in China and have obtained some achievements. Because the history of using and
research of ABC in China is much shorter than those in western countries, the extent of using ABC is
not widespread in China. The companies using ABC mainly belong to the industries of manufactory,
finance and posts and telecommunications, such as XJ Electronics Co., DFAC and China Construction
Bank, etc. There is no related research about the effectiveness of ABC application in China. Therefore,
the prime purpose of this paper is to see whether the application of ABC can, on average, improve
business performance.
3. Literature reviews and the hypothesis developing
The popularity of activity-based costing (ABC) in the mid-1980s has enriched both the management
accounting literature and practice. Research has concentrated on the following fields: Foster and Gupta
(1990), Noreen (1991), Banker and Johnston (1993) and McGowan (1998) assess the integrity of the
ABC process; Cooper and Kaplan (1999), Nicholls (1992), Innes and Mitchell (1995, 1997) and Malmi
(1999) assess the degree of interest and adoption examine its application and implementation in a single
case study situation. Cooper and Kaplan (1992) assert that "the goal of ABC is to increase profits, not to
obtain more accurate costs". Affleck and Graves (2002) find that the choice of a management accounting
system, such as ABC, may have a significant impact on firm value. They suggest that ABC adds to firm
value through better cost controls and asset utilization, coupled with greater use of financial leverage.
Wenner and Le Ber (1989) find that ABC can provide information crucial to an understanding of how a
firms' competitive advantage is generated. By more accurately attributing cost to products, services, and
customers, ABC can play an important role in providing relevant information for management operating
decisions, which, in turn, should impact on profitability and, ultimately, shareholder value. Ward and
Patel (1990) suggest that ABC provides a sound foundation for future cash flow projections. They argue
that this leads to investment in value-added activities that support products, services, customers, and
market segments, thereby increasing shareholder value.
Because ABC method can help to get more accurate cost information, control cost more effectively, and
then affect future performance, we have the following hypothesis:
H: ABC application helps company to improve performance.
4. The consequences of ABC application in China
4.1 Data collection and model analysis
Many factors can affect company’s performance. Overseas researchers have chosen some factors in
studying the effectiveness of using ABC on performance, including firm size, production type, degree of
centralization, product diversity, and the ratio of indirect to total costs, etc. But in different countries,
periods and industries, there may be different factors that affect the performance of companies. In this
paper, we choose ROA (return on assets) as dependent variable, ABC (whether or not the company uses
ABC) as independent variable, SIZE (the firm size) and IROA (industry average return on assets) as
control variables. All the variables are described as table 1:
Table 1 Description of Variables
Items
Variables
Descriptions of Variables
ROA
Returns of total assets
ABC
Whether or not using ABC
SIZE
Firm size
Natural log of total assets
IROA
industry average ROA
industry average ROA
ROA=net income/total assets
Dummy variable, 1 for yes, 0 for no
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We collected respectively 23 listed companies that use ABC method and 23 listed companies that do not
use ABC method. In the 46 listed companies, of which 28 companies are from Shanghai Stock Market
and 18 companies from Shenzhen Stock Market. We use 2007 and 2008 annual data for our test. All the
data we used are from CSMAR, and the websites of www.cninfo.com.cn, www.sse.com.cn,
www.szse.cn and www.cei.gov.cn.
First, we made the partial correlation analysis of the four variables and got the result as in table 2:
Table 2 Partial Correlation Analysis
Variables
ROA
ABC
1.000
.449
significant level two-tail
.
.002
df
0
42
correlations
.449
1.000
significant level two-tail
.002
.
df
42
0
Correlations
（
ROA
ABC
）
（
）
By reading table 2, we find that the partial correlation coefficient of ROA and ABC is 0.449, and the
significant level (Sig. two-tail) is 0.002 that is less than 0.01. That means the correlation of ROA and
ABC are positive significant. We then have the conclusion: after controlling firm size and industry
average ROA, the ABC application is significantly positive associated with the ROA; business that uses
ABC method can improve its performance.
Second, we run the following regression:
ROA = β 0 + β1 ABC + β 2 SIZE + β 3 IROA + ε
Table 3 reports the regression results:
Table3 Correlation
ROA
ABC
SIZE
IROA
ROA
1.000
.454
.198
.353
ABC
.454
1.000
.170
.085
Size
.198
.170
1.000
.362
IROA
.353
.085
.362
1.000
ROA
.
.001
.093
.008
Pearson correlation
Sig.
（one-tail）
607
ABC
.001
.
.130
.288
Size
.093
.130
.
.007
IROA
.008
.288
.007
.
Table 3 shows the correlations of the four variables. The correlation of ROA and ABC is the most
significant of all. ROA is also significantly relevant with IROA, because any company must be affected
by both industry characteristics and developing situation it belongs to. In addition, the significant level
of ABC is 0.001. The result indicates that using ABC method plays an active role in improving
company’s performance.
Table 4 Goodness-of-Fit Testb
Model R
1
.553a
R square Adjusted R square
Standard error estimate
Durbin-Watson
.306
4.39122
2.052
.256
a. Predictive variables: (constant), IROA, ABC, SIZE
b. Dependent variable: ROA
。
Table 4 shows the test result of goodness-of-fit. In general, we use adjusted R square to determine the
goodness-of-fit of a multivariable linear regression model. In this case, the adjusted R square of 0.256
indicates that to some extent the predictive variables can explain the ROA.
Table 5 Anovab
Model
1
Sum Of Squares df
Mean square
F
Sig.
Regression
356.595
3
118.865
6.164
.001a
Residual
809.880
42
19.283
Total
1166.475
45
a. Predictive variables: (constant), IROA, ABC, SIZE
b. Dependent variable: ROA
。
Table 5 shows that the significant level of the regression model is 0.001, in other words, at the
significant level of 1%, test value of F is 6.164. So we can conclude that the linear correlations of the
regression model are significant. That means the correlation of application of ABC, firm size and
industry average ROA are all statistically significant with ROA.
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Table 6 Regression analysisa
Unstandard coefficients
Model
1
Regression
coefficients
Standard error
(constant)
-.515
6.545
ABC
4.280
1.314
SIZE
.028
IROA
.197
Standard
coefficients
Beta
T test
Sig.
-.079
.938
.425
3.256
.002
.300
.013
.094
.925
.087
.312
2.264
.029
a. Dependent variable: ROA
Table 6 is the result of regression analysis. The result indicates that the effect of application of ABC,
firm size and IROA on ROA can be described as follows:
ROA = −0.515 + 4.28ABC + 0.028SIZE + 0.197IROA + ε
Table 6 shows that the sig. of ABC is 0.002 at 1% significant level and that of IROA is 0.029 at 5%
significant level. The result of regression indicates that the ABC application is statistically positive
significant with ROA. It further indicates that the application of ABC can improve business’
performance.
Table 7 shows the result of collinearity diagnostics.
Table 7 Collinearity Diagnostics a
Variance ratio
Model
1
Degree
Characteristic
root
Conditions Index
(constant)
ABC
SIZE
IROA
1
3.178
1.000
.00
.03
.00
.03
2
.479
2.575
.00
.42
.00
.57
3
.338
3.067
.01
.54
.00
.29
4
.005
25.954
.99
.01
.99
.10
a. Dependent variable: ROA
Table 7 indicates that the tolerances of the three independent variables are all less than 1, and the VIF of
the three variables are also accepted.
5. Conclusion
This paper analyzes the effect of ABC application on ROA. The analysis data in this paper approve that
ABC application, firm size and IROA are all significant with ROA, and the correlation of ABC is most
significant of all; to some extent, the explanatory variables can explain the ROA, but the ROA can’t be
accounted for completely. The result means using ABC in company can improve its operation level and
performance. It supports our hypothesis. But, we should also pay attention that ABC may not be suitable
for every firm. Recent research shows that successful implementation depends on many aspects. For
example, Anderson (1995) and Malmi (1997) argue that successful implementation depends on
organizational and technical factors, adoption depends on several factors including firm size, production
type, degree of centralization, product diversity, and the ratio of indirect to total costs. Gosselin (1997)
609
suggests that specific characteristics in their business strategy and organizational structure lead certain
firms to adopt and implement ABC and, by implication, other firms not to implement ABC.
Acknowledgements:
1. Beijing municipal excellent teaching team (accounting series courses teaching team) program.
NO. PHR200907203
2. Beijing municipal discipline and graduate student education of business administration program.
NO.PXM 2009-014212-78362
Author in brief:
XU Yan, associate professor, mainly engaged in cost management and performance evaluation.
Email: [email protected].
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