Directory UMM :Data Elmu:jurnal:A:Agricultural Systems:Vol67.Issue2.2001:
Agricultural Systems 67 (2001) 71±82
www.elsevier.com/locate/agsy
Application of simulation technique to
activity-based costing of agricultural systems:
a case study
Tzong-Ru Lee *, Jui-Sheng Kao
Department of Agricultural Marketing, National Chung-Hsing University, Taichung, Taiwan,
Republic of China
Received 15 December 1999; received in revised form 20 May 2000; accepted 25 August 2000
Abstract
The aim of this paper is to analyse the operational costs of the Pu-Shin wholesale ®sh
market in Taiwan, using both the activity-based costing (ABC) model and the simulation
technique. By using simulation results in the calculated model of ABC, allocated resource
costs are more accurate and arbitrary allocation is avoided. The objective of this study is to
compute the processing cost per kilogram of ®sh. We conclude by providing relevant and
accurate information about cost management of the Pu-Shin wholesale ®sh market, comparing ABC with traditional costing methods, and discussing key related issues which may provide opportunities for future research. We believe that the use of the ABC model in
conjunction with simulation techniques can also be applied to agricultural systems in other
countries. # 2001 Elsevier Science Ltd. All rights reserved.
Keywords: Activity-based costing; Simulation technique; Wholesale ®sh market; Cost management
1. Introduction
Activity-based costing (ABC; Hansen and Mowen, 2000) is a system that assigns
costs to cost objects by ®rst tracing costs to activities and then tracing costs to cost
objects. Cost object is a technical term in cost management and is any item such as
products, departments, projects, activities, and so on, for which costs are measured
* Corresponding author. Tel./fax: +886-4-2861437.
E-mail address: trlee@dragon.nchu.edu.tw (T-R. Lee).
0308-521X/01/$ - see front matter # 2001 Elsevier Science Ltd. All rights reserved.
PII: S0308-521X(00)00042-1
72
T-R. Lee, J.-S. Kao / Agricultural Systems 67 (2001) 71±82
and assigned. Cost objects are used to assign costs and ultimately the objective to
compute the total processing cost is achieved.
The use of ABC is still developing. In recent years, many organizations have
improved their cost management by utilizing the ABC system, a tool for providing
accurate and relevant cost information. To maintain a competitive advantage,
organizations must monitor and promptly remove wasted eorts or other nonproductive activities. ABC allows organizations to improve their productivity by
eliminating non-productive eorts, as well as managing the operational costs
through observation and analysis.
In Taiwan, the wholesale ®sh market plays a very important role in ®sh marketing. To strengthen the business of wholesale ®sh markets, it is necessary to continually modify and improve operational procedures as well as manage operational
costs. Hence, this paper discusses activity-based costing in the context of the PuShin wholesale ®sh market in Taiwan.
This paper consists of four sections. First, the general structure of the ABC model
is described. Second, the application of system simulation to the ABC system is
discussed. Third, a case study is administered. The resource costs are calculated by
simulation results. In this way, allocated resource costs are more accurate and arbitrary allocation is avoided. We conclude by discussing key related issues which may
provide opportunities for future research.
2. The general structure of the ABC model
Since the eorts of Robin Cooper in the late 1980s, many industries have successfully employed ABC to improve operational performance. ABC has continued
to provide relevant and accurate information about cost management. In addition,
because the ABC system focuses on activities rather than products, it helps prevent
distorted product cost information that can arise from the use of traditional costing
systems (Gunasekaran and Singh, 1999; Cooper and Kaplan, 1991). The basic
assignments of the ABC model are to identify the activities of an organization, calculate the cost of each activity, and then cost the product based on activity consumption (Gunasekaran and Singh, 1999). Moreover, the ABC approach can be
used to allocate various activities to related resources. Costs are appropriately allocated to selected cost objects by using the cost driver1 of each activity. Therefore,
accuracy of product cost is contingent upon both calculations of activity cost and
cost driver volume.
The structure of the ABC model is illustrated in Fig. 1. It contains information
relevant to organizational resources, activities, and cost objects. The implication is
that the cost object is the cause of activities and that resources exist solely to carry
out those activities. After the resource costs have been assigned to their respective
1
Cost drivers are the factors that drive the cost of operational activities. They include such factors as
number of parts, number of moves, number of products, number of customer orders, and number of
returned products.
T-R. Lee, J.-S. Kao / Agricultural Systems 67 (2001) 71±82
73
Fig. 1. The structure of an activity-based costing model.
activities, they are subsequently allocated to cost objects by means of activity
drivers2. By obtaining these measures, activity drivers become a way of assigning the
cost of activities to the actual cost object (Goebel et al., 1998). Hence, in the ABC
system, the total cost of a product also includes the cost of all activities required to
produce or handle it. In the ABC model, accuracy frequently depends upon the
details of the ABC model and the type of activity driver used. There are three types
of activity drivers (Cooper, 1990; Spedding and Sun, 1999): (1) Transaction drivers,
which count each time an activity takes place; (2) Duration drivers, which represent
the time taken for each activity and also takes into account variation; and (3)
Intensity drivers, which directly cost the resources used each time an activity takes
place. In this study, we employed all three types of activity drivers.
3. The application of simulation technique
The purpose of system simulation techniques is to design a model for a real system,
which provides users with the approximated behavior of that real system. Since the
simulation technique is capable of establishing dynamic relationships between variables in a dynamic system, it can also presume actual relationships between variables
based on the results, and the results can be used to solve complicated problems.
System simulation is also able to locate system bottlenecks for future improvement
and create optimum conditions between system inputs and outputs (Lee and Kao,
2
Activity drivers measure the demands that cost objects place on activities.
74
T-R. Lee, J.-S. Kao / Agricultural Systems 67 (2001) 71±82
1999; Chiu, 1997; Chen et al., 1997). Hence, system simulation helps policy-makers
make decisions under various circumstances and keep a balance between costs and
bene®ts. In other words, simulation results can be used to evaluate the merits
and demerits of policies (Karim, 1998).
Through data collection and analysis, we can create an operational simulation
model. Continued adjustments are made within the simulation model until results resemble those of the ``real world''. Afterwards, data from the simulation results
(operational time and number of resources used) are applied within an ABC model.
The application of the simulation technique in ABC provides users with an
enhanced means of assessing the cost-bene®t factors of all activities. Furthermore,
by using simulation results in the calculated model of ABC, allocated resource costs
are more accurate and arbitrary allocation is avoided.
4. Case study
The Pu-Shin wholesale ®sh market, which has the highest automation level in
Taiwan, is the subject. Observations include the product ¯ow from unloading to the
completion of the auctioning process. The steps of applying the ABC model are as
follows.
4.1. Analysis of activities
There are ®ve sections in the auction area: cultured ®sh section A, cultured ®sh
section B, cold-storage polyester box section, cold-storage ®sh-basket section and
imported ®sh section. The major activities are: unloading, ordering, billing, grading
and weighing, numbering, auctioning (computer auctioning in the cultured ®sh section A, cultured ®sh section B, and cold-storage polyester box section; manual auctioning in storage ®sh-basket section and imported ®sh section), and administrative
operation.
4.2. Allocation of resource costs
After identifying the activities, resource costs are allocated to each respective
activity. Allocation can be classi®ed into three categories (Ostrenga, 1990): (1) direct
charging, which allocates resource costs directly into the activities; (2) estimation,
which allocates resource costs by using resource drivers3; and (3) arbitrary allocation, which arbitrarily allocates resources into the activities. This study utilizes both
direct charging and estimation to allocate the resource costs. The activities, resource
costs, and resource drivers are presented in Table 1.
3
Resource drivers are factors that measure the demands placed on resources by activities and are used
to assign the cost of resources to activities.
T-R. Lee, J.-S. Kao / Agricultural Systems 67 (2001) 71±82
75
Table 1
Activities, resource costs and resource drivers in the Pu-Shin wholesale ®sh market
Activity
Category of Resource Costs
Resource Drivers
Unloading
Sta wages, cost of electricity resources
Pallets
Sta wages, cost of electricity resources,
Automated guided vehicle (AGV), porter,
fork porter, cost of reconditioning
machines, cost of machinery fuel
Sta wages, cost of electricity resources
Sta wages, cost of electricity resources
Fish-baskets
Sta wages, cost of electricity resources
Numbering machine
Sta wages, cost of electricity resources,
cost of reconditioning machines, cost of
machinery fuel
Computer auction clock, computer
auction machine C, computer auction
machine D
Sta wages, cost of electricity resources
Administrative spending, meeting costs,
computers
Operation time
Volume of use
Operation time
Ordering
Billing
Grading and weighing
Numbering
Auctioning
Administrative operation
Operation time
Operation time
Volume of use
Operation time
Direct charging
Operation time
Direct charging
Operation time
Direct charging
4.3. Computed resource costs
To obtain more accurate allocated resource costs and to avoid arbitrary allocation, this study applies the simulation technique to ABC of the Pu-Shin wholesale
®sh market.
To record the time spent for each activity, a V8 camcorder was installed from
23:00 on 11 August to 06:00 on 12 August 1998. Time study skill was used to measure the duration of each operation. The Stat: Fit statistics software was employed.
Table 2 shows the probability distribution function (pdf) and parameters for each
operational event. The results of the chi-square/goodness-of-®t test show that all
pdf results for operational events are acceptable. Furthermore, the operational time
of the simulation model is 7.3 h, which does not dier much from the ``real time'' of
7.5 h. Therefore, the simulation results are compatible to those of the real system. In
other words, the simulation model is developed by observing and analysing the
actual processing time for the activities and then categorizing their statistical distributions. Random numbers from observed statistical distributions are generated to
represent the duration of the activities. The dynamic process of simulation is shown
in Fig. 2.
As described, this study also employs a system simulation to estimate the volume
of resource drivers. The simulation results are presented in the third column of
Table 3. Using these results with estimates of machinery depreciation, we can then
compute the resource costs for each activity.
76
Table 2
The optimal pdf and its parameter(s) for each operational event in the Pu-Shin wholesale ®sh market
Operational events
a
b
c
d
Probabilitya (%)
Mean
Variance
Parameters
a
b
w2 testb
Test result
Pearson 5
Weibull
Exponential
Exponential
Lognormal
Pearson 5
96
100
97
100
100
100
3.15
6.17
24.20
115.52
3.31
8.53
1.47
3.22
328.8
20.8
2.5
10.4
5.21
1.84
ÿc
ÿ
ÿ
2.97
9.05
3.56
16.20
8.17
ÿ
9.63
1.45
0.67
2.80
3.56
5.10
0.13
Accepted
Accepted
Accepted
Accepted
Accepted
Accepted
Exponential
100
11.83
25.9
ÿ
5.83
0.67
Accepted
Lognormal
100
3.19
0.9
ÿ
ÿ
21.6
Accepted
Exponential
Pearson 6
100
99
2.35
4.19
1.6
3.8
1.35
1.21
8.40
0.79
Accepted
Accepted
Pearson 6
100
8.32
27.0
105.6
100
Accepted
Weibull
97
4.26
0.7
ÿ
a1=4.89,
a2=3.69
a1=1.51,
a2=23.78
2.85
2.36
0.13
Accepted
Exponential
100
5.98
8.6
ÿ
2.98
0.13
Accepted
The probability represents the acceptable level of distribution.
When the con®dence interval=95%, all operational events pass the chi-square/goodness-of-®t test.
``ÿ'' means that there is no such parameter in that distribution.
Delay time would appear in each computer auctioning of the Pu-Shin wholesale ®sh market (listed as the computer-auction-delay-time [CADT]).
T-R. Lee, J.-S. Kao / Agricultural Systems 67 (2001) 71±82
Unloading time per box
Unloading time per basket
Ordering time per pallet
Grading/weighing time per basket
Numbering time per basket
Manual auction time per basket in cold-storage
®sh-basket section
Manual auction time per box in imported ®sh
section
Computer auction time per auction in cultured
®sh section A
CADT per auction in cultured ®sh section Ad
Computer auction time per auction in cold-storage
polyester box section
CADT per auction in cold-storage polyester
box sectiond
Computer auction time per auction in cultured ®sh
section B
CADT per auction in culture ®sh section Bd
Distribution
T-R. Lee, J.-S. Kao / Agricultural Systems 67 (2001) 71±82
77
Fig. 2. The operational cost analysis in a simulation model for the Pu-Shin wholesale ®sh market.
4.4. Activity cost and cost objective
Activity cost is a measure of the frequency and the intensity of demand placed on
each activity by cost objects (Gunasekaran and Singh, 1999). Cost objects are used
to obtain accurate product information. The objective in this study is to compute the
processing cost per kilogram of ®sh. However, before we calculate the unit cost
for each activity, we need: (1) to calculate the volume of ®sh and the units handled in
each section (Table 4); and (2) to locate the allocation paths or the links between the
activities and the auction area (Fig. 3).
Table 5 shows the activity driver for each activity and the calculated results of the
cost objects. The results show that the total processing cost per kilogram of ®sh is
NT$2.36 (US$1=NT$31).
As shown in Table 6, the wages of auctioning sta are NT$890.48 per day, which
are relatively higher than those of other sta. It implies that the auctioning sta are
a key resource. Therefore, the manager in the Pu-Shin wholesale ®sh market must
focus on the eciency and eectiveness of the auctioning sta.
Because it would take a long time to improve grading and weighing activities and
it is not easy to reduce the cost of administrative operation in a short time, we analyze the cost impact of computer auctioning without manual auctioning. Furthermore, the scenario of implementing computer auctioning in all sections is simulated.
Fig. 4 shows that manual auctioning is not used when computer auctioning is
implemented. Numbering and computer auctioning operations are included in both
the cold-storage ®sh-basket section and the imported ®sh section.
Simulation results show that the auctioning operational time (60 min) does not
change, but the numbering operational time is 87 min (an increase of 27 min from 60
min). The processing cost for numbering (from $0.09 to $0.07 per kg of ®sh), the
processing cost for auctioning (from $0.44 to $0.23 per kg of ®sh) and the total
processing cost (from NT$2.36 to NT$2.12 per kg of ®sh) are all reduced/decreased
(see Table 7). Even though the cost of manual auctioning is cheaper than that of
computer auctioning, however, the total processing cost per kg of ®sh actually goes
down from NT$2.36 to NT$2.12 when computer auctioning is implemented in all
78
Table 3
The resource costs per activity in the Pu-Shin wholesale ®sh market
Category of resource costs (m)a
Simulation results
Estimation of
machinery
depreciation (n)
Resource costs
for each activityb
(NT$/day)c
Unloading
Sta(4), cost of electricity resources
Pallets
Sta(4), cost of electricity resources, cost of
reconditioning machines, cost of machinery fuel
AGV(1), fork porter(3)
Sta(1), cost of electricity resources
Sta(5), cost of electricity resources
Weighing machines
Fish-baskets
Sta(5), cost of electricity resources
Numbering machine(1)
Sta wages(5), cost of electricity resources,
cost of reconditioning machine, cost of
machinery fuel
Computer auction clock(1), computer auction
machine A(2), computer auction machine B(2)
Sta wages(15), cost of electricity resources
Administrative spending, meeting costs
Computers
105 min
Number used=82
180 min
±d
6
±
1898.25
±
66 min
145 min
±
Number used=290
60 min
±
102 mine
10
±
±
10
6
±
10
±
Manual auctioning=1657.69
±
10
Computer auctioning=4826.21
150 min
±
±
±
±
10
15191.37
Ordering
Billing
Grading and weighing
Numbering
Auctioning
Administrative operations
a
b
c
d
e
5254.88
850.59
4372.01
1877.73
(m):m is the number of sta or machines utilized.
The resource costs for each activity equal ``the resource costs per day in that activity'' times ``the percentage of resource allocation''.
US$1=NT$31.
``±'' means that there is no such data.
The manual auction time is 42 min, and the computer auction time is 60 min.
T-R. Lee, J.-S. Kao / Agricultural Systems 67 (2001) 71±82
Activity
79
T-R. Lee, J.-S. Kao / Agricultural Systems 67 (2001) 71±82
Table 4
The volume of ®sh and the units handled in the Pu-Shin wholesale ®sh marketa
Auction area
Volume of ®sh (kg)
Units handledb
Cultured ®sh section A
Cultured ®sh section B
Cold-storage polyester box section
Imported ®sh section
Cold-storage ®sh-basket section
8105
3571
7610
4107
4618
675
298
634
342
290
a
Source: actual auction data on 11 August 1998.
The unit handled in the cold-storage ®sh-basket section is the basket (capacity=15 kg), and the unit
handled in all other sections is the box (capacity=12 kg).
b
Fig. 3. The allocation paths in the Pu-Shin wholesale ®sh market.
sections. Furthermore, one disadvantage of manual auctioning is that the process
may not be fair. By implementing computer auctioning in all sections, these are
impartial, public, and equitable contributions in the auctioning process, and the
total processing cost per kg of ®sh is reduced.
5. Comparing ABC with traditional costing methods
According to the results of the ABC model, the total processing cost is NT$2.36
per kilogram of ®sh. It is higher compared to NT$2.19, the processing cost calculated by using traditional accounting methods (data supplied by the Pu-Shin
wholesale ®sh market). One reason is that Pu-Shin wholesale ®sh market does not
calculate machinery depreciation during cost calculation. If we do not add machinery depreciation into the ABC model, the total processing cost would be NT$2.28
per kilogram of ®sh, which is more compatible to the calculated results of the traditional accounting methods. However, the ABC model still provides decision
makers with relevant information about cost management that the traditional
methods does not.
80
T-R. Lee, J.-S. Kao / Agricultural Systems 67 (2001) 71±82
Table 5
The activity drivers and the calculated results of cost objects in the Pu-Shin wholesale ®sh market
Activity
Resource costs
for each activitya
($ NT/day)
Activity driver
(X)
Unloading
Ordering
Billing
Grading and
weighing
Numbering
Manual auctioning
Computer auctioning
Administrative
operation
Activity
driver
volumeb
Unit cost
for each
activity
(Y)
(Z=X/Y)
Processing
cost per kg
of ®sh
%
$1898.25
$5254.88
$850.59
$4372.01
Number of boxes
Number of boxes
Billing time
Number of boxes
1949
1949
1949
290
$0.97
$2.69
$0.44
$15.07
$0.08
$0.23
$0.04
$0.94
3.4
9.7
1.7
39.8
$1877.73
$1657.69
Number of boxes
Number of boxes
or baskets
Number of boxes
Minutes
1607
650
$1.17
$2.55
$0.09
$0.19
3.8
8.1
1607
150
$3.00
$101.27
$0.25
$0.54
10.6
22.9
$4826.21
$15191.37
Total
$2.36
100
a
The resource costs for each activity is calculated from Table 3.
The activity driver volume is calculated by referring to the units handled in Table 4 and the allocation
paths in Fig. 3. For example, the activity driver volume of unloading is calculated as follows: 1949=
675+298+634+342.
b
Table 6
The wages of sta in each activity of the Pu-Shin wholesale ®sh market per day
Activity
Unloading Ordering Billing Grading and Numbering Auctioning Administrative
weighing
operation
Wages of
$345.89
sta per day
(NT$)
$592.97
$550
$735.21
$304.23
$890.48
$820.40
6. Conclusions
To improve the functions of the wholesale ®sh market and encourage the trends of
economic liberalization and internationalization, it is necessary to pay close attention to cost management. For this purpose, this study has applied ABC and simulation techniques to analyse the operational costs of the Pu-Shin wholesale ®sh
market. The results show that the wages of the auctioning sta are the highest of all
activities, an implication that the auctioning sta plays a vital role. Furthermore, the
total processing cost per kg of ®sh is reduced by implementing computer auctioning
in the auction area. However, the ®ndings are based on a one-day simulation only.
For possible future research, we suggest a day-by-day data simulation to obtain
81
T-R. Lee, J.-S. Kao / Agricultural Systems 67 (2001) 71±82
Fig. 4. The allocation paths in the Pu-Shin wholesale ®sh market after computer auctioning is
implemented. Note: The bold lines represent the additive allocation paths after computer auctioning
is implemented.
Table 7
The activity drivers and the calculated results of cost items when computer auctioning is implemented in
the Pu-Shin wholesale ®sh market
Activity
Resource costs
for each
activity
($ NT/each day)
Activity driver
Unit cost
for each
activity
Processing
cost per kg
of ®sh
(Y)
(Z=X/Y)
1949
1949
1949
290
2239
2239
$0.96
$2.65
$0.43
$15.00
$0.84
$2.88
$0.08
$0.22
$0.04
$0.94
$0.07
$0.23
3.7
10.8
1.9
44.1
3.3
10.8
150
$100.85
$0.54
25.4
$2.12
100
Activity
driver
volume
(X)
Unloading
Ordering
Billing
Grading and weighing
Numbering
Computer auctioning
$1882.79
$5228.37
$840.87
$4350.66
$1887.89
$6468.89
Administrative
operation
$15128.54
Total
Number of boxes
Number of boxes
Billing times
Number of baskets
Numbering times
Number of boxes
or baskets
Minutes
%
accurate information about cost management. We believe that the ABC model used
with system simulation can certainly be applied to agricultural systems in other
countries.
References
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Chen, L.-H., Shaw, J.-T., Chan, T.-H., 1997. Simulation of rice and handling system. Journal of Agriculture Machinery 6, 85±96.
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Computers & Industrial Engineering 37, 413±416.
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orientation. Industrial Marketing Management 27, 497±510.
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www.elsevier.com/locate/agsy
Application of simulation technique to
activity-based costing of agricultural systems:
a case study
Tzong-Ru Lee *, Jui-Sheng Kao
Department of Agricultural Marketing, National Chung-Hsing University, Taichung, Taiwan,
Republic of China
Received 15 December 1999; received in revised form 20 May 2000; accepted 25 August 2000
Abstract
The aim of this paper is to analyse the operational costs of the Pu-Shin wholesale ®sh
market in Taiwan, using both the activity-based costing (ABC) model and the simulation
technique. By using simulation results in the calculated model of ABC, allocated resource
costs are more accurate and arbitrary allocation is avoided. The objective of this study is to
compute the processing cost per kilogram of ®sh. We conclude by providing relevant and
accurate information about cost management of the Pu-Shin wholesale ®sh market, comparing ABC with traditional costing methods, and discussing key related issues which may provide opportunities for future research. We believe that the use of the ABC model in
conjunction with simulation techniques can also be applied to agricultural systems in other
countries. # 2001 Elsevier Science Ltd. All rights reserved.
Keywords: Activity-based costing; Simulation technique; Wholesale ®sh market; Cost management
1. Introduction
Activity-based costing (ABC; Hansen and Mowen, 2000) is a system that assigns
costs to cost objects by ®rst tracing costs to activities and then tracing costs to cost
objects. Cost object is a technical term in cost management and is any item such as
products, departments, projects, activities, and so on, for which costs are measured
* Corresponding author. Tel./fax: +886-4-2861437.
E-mail address: trlee@dragon.nchu.edu.tw (T-R. Lee).
0308-521X/01/$ - see front matter # 2001 Elsevier Science Ltd. All rights reserved.
PII: S0308-521X(00)00042-1
72
T-R. Lee, J.-S. Kao / Agricultural Systems 67 (2001) 71±82
and assigned. Cost objects are used to assign costs and ultimately the objective to
compute the total processing cost is achieved.
The use of ABC is still developing. In recent years, many organizations have
improved their cost management by utilizing the ABC system, a tool for providing
accurate and relevant cost information. To maintain a competitive advantage,
organizations must monitor and promptly remove wasted eorts or other nonproductive activities. ABC allows organizations to improve their productivity by
eliminating non-productive eorts, as well as managing the operational costs
through observation and analysis.
In Taiwan, the wholesale ®sh market plays a very important role in ®sh marketing. To strengthen the business of wholesale ®sh markets, it is necessary to continually modify and improve operational procedures as well as manage operational
costs. Hence, this paper discusses activity-based costing in the context of the PuShin wholesale ®sh market in Taiwan.
This paper consists of four sections. First, the general structure of the ABC model
is described. Second, the application of system simulation to the ABC system is
discussed. Third, a case study is administered. The resource costs are calculated by
simulation results. In this way, allocated resource costs are more accurate and arbitrary allocation is avoided. We conclude by discussing key related issues which may
provide opportunities for future research.
2. The general structure of the ABC model
Since the eorts of Robin Cooper in the late 1980s, many industries have successfully employed ABC to improve operational performance. ABC has continued
to provide relevant and accurate information about cost management. In addition,
because the ABC system focuses on activities rather than products, it helps prevent
distorted product cost information that can arise from the use of traditional costing
systems (Gunasekaran and Singh, 1999; Cooper and Kaplan, 1991). The basic
assignments of the ABC model are to identify the activities of an organization, calculate the cost of each activity, and then cost the product based on activity consumption (Gunasekaran and Singh, 1999). Moreover, the ABC approach can be
used to allocate various activities to related resources. Costs are appropriately allocated to selected cost objects by using the cost driver1 of each activity. Therefore,
accuracy of product cost is contingent upon both calculations of activity cost and
cost driver volume.
The structure of the ABC model is illustrated in Fig. 1. It contains information
relevant to organizational resources, activities, and cost objects. The implication is
that the cost object is the cause of activities and that resources exist solely to carry
out those activities. After the resource costs have been assigned to their respective
1
Cost drivers are the factors that drive the cost of operational activities. They include such factors as
number of parts, number of moves, number of products, number of customer orders, and number of
returned products.
T-R. Lee, J.-S. Kao / Agricultural Systems 67 (2001) 71±82
73
Fig. 1. The structure of an activity-based costing model.
activities, they are subsequently allocated to cost objects by means of activity
drivers2. By obtaining these measures, activity drivers become a way of assigning the
cost of activities to the actual cost object (Goebel et al., 1998). Hence, in the ABC
system, the total cost of a product also includes the cost of all activities required to
produce or handle it. In the ABC model, accuracy frequently depends upon the
details of the ABC model and the type of activity driver used. There are three types
of activity drivers (Cooper, 1990; Spedding and Sun, 1999): (1) Transaction drivers,
which count each time an activity takes place; (2) Duration drivers, which represent
the time taken for each activity and also takes into account variation; and (3)
Intensity drivers, which directly cost the resources used each time an activity takes
place. In this study, we employed all three types of activity drivers.
3. The application of simulation technique
The purpose of system simulation techniques is to design a model for a real system,
which provides users with the approximated behavior of that real system. Since the
simulation technique is capable of establishing dynamic relationships between variables in a dynamic system, it can also presume actual relationships between variables
based on the results, and the results can be used to solve complicated problems.
System simulation is also able to locate system bottlenecks for future improvement
and create optimum conditions between system inputs and outputs (Lee and Kao,
2
Activity drivers measure the demands that cost objects place on activities.
74
T-R. Lee, J.-S. Kao / Agricultural Systems 67 (2001) 71±82
1999; Chiu, 1997; Chen et al., 1997). Hence, system simulation helps policy-makers
make decisions under various circumstances and keep a balance between costs and
bene®ts. In other words, simulation results can be used to evaluate the merits
and demerits of policies (Karim, 1998).
Through data collection and analysis, we can create an operational simulation
model. Continued adjustments are made within the simulation model until results resemble those of the ``real world''. Afterwards, data from the simulation results
(operational time and number of resources used) are applied within an ABC model.
The application of the simulation technique in ABC provides users with an
enhanced means of assessing the cost-bene®t factors of all activities. Furthermore,
by using simulation results in the calculated model of ABC, allocated resource costs
are more accurate and arbitrary allocation is avoided.
4. Case study
The Pu-Shin wholesale ®sh market, which has the highest automation level in
Taiwan, is the subject. Observations include the product ¯ow from unloading to the
completion of the auctioning process. The steps of applying the ABC model are as
follows.
4.1. Analysis of activities
There are ®ve sections in the auction area: cultured ®sh section A, cultured ®sh
section B, cold-storage polyester box section, cold-storage ®sh-basket section and
imported ®sh section. The major activities are: unloading, ordering, billing, grading
and weighing, numbering, auctioning (computer auctioning in the cultured ®sh section A, cultured ®sh section B, and cold-storage polyester box section; manual auctioning in storage ®sh-basket section and imported ®sh section), and administrative
operation.
4.2. Allocation of resource costs
After identifying the activities, resource costs are allocated to each respective
activity. Allocation can be classi®ed into three categories (Ostrenga, 1990): (1) direct
charging, which allocates resource costs directly into the activities; (2) estimation,
which allocates resource costs by using resource drivers3; and (3) arbitrary allocation, which arbitrarily allocates resources into the activities. This study utilizes both
direct charging and estimation to allocate the resource costs. The activities, resource
costs, and resource drivers are presented in Table 1.
3
Resource drivers are factors that measure the demands placed on resources by activities and are used
to assign the cost of resources to activities.
T-R. Lee, J.-S. Kao / Agricultural Systems 67 (2001) 71±82
75
Table 1
Activities, resource costs and resource drivers in the Pu-Shin wholesale ®sh market
Activity
Category of Resource Costs
Resource Drivers
Unloading
Sta wages, cost of electricity resources
Pallets
Sta wages, cost of electricity resources,
Automated guided vehicle (AGV), porter,
fork porter, cost of reconditioning
machines, cost of machinery fuel
Sta wages, cost of electricity resources
Sta wages, cost of electricity resources
Fish-baskets
Sta wages, cost of electricity resources
Numbering machine
Sta wages, cost of electricity resources,
cost of reconditioning machines, cost of
machinery fuel
Computer auction clock, computer
auction machine C, computer auction
machine D
Sta wages, cost of electricity resources
Administrative spending, meeting costs,
computers
Operation time
Volume of use
Operation time
Ordering
Billing
Grading and weighing
Numbering
Auctioning
Administrative operation
Operation time
Operation time
Volume of use
Operation time
Direct charging
Operation time
Direct charging
Operation time
Direct charging
4.3. Computed resource costs
To obtain more accurate allocated resource costs and to avoid arbitrary allocation, this study applies the simulation technique to ABC of the Pu-Shin wholesale
®sh market.
To record the time spent for each activity, a V8 camcorder was installed from
23:00 on 11 August to 06:00 on 12 August 1998. Time study skill was used to measure the duration of each operation. The Stat: Fit statistics software was employed.
Table 2 shows the probability distribution function (pdf) and parameters for each
operational event. The results of the chi-square/goodness-of-®t test show that all
pdf results for operational events are acceptable. Furthermore, the operational time
of the simulation model is 7.3 h, which does not dier much from the ``real time'' of
7.5 h. Therefore, the simulation results are compatible to those of the real system. In
other words, the simulation model is developed by observing and analysing the
actual processing time for the activities and then categorizing their statistical distributions. Random numbers from observed statistical distributions are generated to
represent the duration of the activities. The dynamic process of simulation is shown
in Fig. 2.
As described, this study also employs a system simulation to estimate the volume
of resource drivers. The simulation results are presented in the third column of
Table 3. Using these results with estimates of machinery depreciation, we can then
compute the resource costs for each activity.
76
Table 2
The optimal pdf and its parameter(s) for each operational event in the Pu-Shin wholesale ®sh market
Operational events
a
b
c
d
Probabilitya (%)
Mean
Variance
Parameters
a
b
w2 testb
Test result
Pearson 5
Weibull
Exponential
Exponential
Lognormal
Pearson 5
96
100
97
100
100
100
3.15
6.17
24.20
115.52
3.31
8.53
1.47
3.22
328.8
20.8
2.5
10.4
5.21
1.84
ÿc
ÿ
ÿ
2.97
9.05
3.56
16.20
8.17
ÿ
9.63
1.45
0.67
2.80
3.56
5.10
0.13
Accepted
Accepted
Accepted
Accepted
Accepted
Accepted
Exponential
100
11.83
25.9
ÿ
5.83
0.67
Accepted
Lognormal
100
3.19
0.9
ÿ
ÿ
21.6
Accepted
Exponential
Pearson 6
100
99
2.35
4.19
1.6
3.8
1.35
1.21
8.40
0.79
Accepted
Accepted
Pearson 6
100
8.32
27.0
105.6
100
Accepted
Weibull
97
4.26
0.7
ÿ
a1=4.89,
a2=3.69
a1=1.51,
a2=23.78
2.85
2.36
0.13
Accepted
Exponential
100
5.98
8.6
ÿ
2.98
0.13
Accepted
The probability represents the acceptable level of distribution.
When the con®dence interval=95%, all operational events pass the chi-square/goodness-of-®t test.
``ÿ'' means that there is no such parameter in that distribution.
Delay time would appear in each computer auctioning of the Pu-Shin wholesale ®sh market (listed as the computer-auction-delay-time [CADT]).
T-R. Lee, J.-S. Kao / Agricultural Systems 67 (2001) 71±82
Unloading time per box
Unloading time per basket
Ordering time per pallet
Grading/weighing time per basket
Numbering time per basket
Manual auction time per basket in cold-storage
®sh-basket section
Manual auction time per box in imported ®sh
section
Computer auction time per auction in cultured
®sh section A
CADT per auction in cultured ®sh section Ad
Computer auction time per auction in cold-storage
polyester box section
CADT per auction in cold-storage polyester
box sectiond
Computer auction time per auction in cultured ®sh
section B
CADT per auction in culture ®sh section Bd
Distribution
T-R. Lee, J.-S. Kao / Agricultural Systems 67 (2001) 71±82
77
Fig. 2. The operational cost analysis in a simulation model for the Pu-Shin wholesale ®sh market.
4.4. Activity cost and cost objective
Activity cost is a measure of the frequency and the intensity of demand placed on
each activity by cost objects (Gunasekaran and Singh, 1999). Cost objects are used
to obtain accurate product information. The objective in this study is to compute the
processing cost per kilogram of ®sh. However, before we calculate the unit cost
for each activity, we need: (1) to calculate the volume of ®sh and the units handled in
each section (Table 4); and (2) to locate the allocation paths or the links between the
activities and the auction area (Fig. 3).
Table 5 shows the activity driver for each activity and the calculated results of the
cost objects. The results show that the total processing cost per kilogram of ®sh is
NT$2.36 (US$1=NT$31).
As shown in Table 6, the wages of auctioning sta are NT$890.48 per day, which
are relatively higher than those of other sta. It implies that the auctioning sta are
a key resource. Therefore, the manager in the Pu-Shin wholesale ®sh market must
focus on the eciency and eectiveness of the auctioning sta.
Because it would take a long time to improve grading and weighing activities and
it is not easy to reduce the cost of administrative operation in a short time, we analyze the cost impact of computer auctioning without manual auctioning. Furthermore, the scenario of implementing computer auctioning in all sections is simulated.
Fig. 4 shows that manual auctioning is not used when computer auctioning is
implemented. Numbering and computer auctioning operations are included in both
the cold-storage ®sh-basket section and the imported ®sh section.
Simulation results show that the auctioning operational time (60 min) does not
change, but the numbering operational time is 87 min (an increase of 27 min from 60
min). The processing cost for numbering (from $0.09 to $0.07 per kg of ®sh), the
processing cost for auctioning (from $0.44 to $0.23 per kg of ®sh) and the total
processing cost (from NT$2.36 to NT$2.12 per kg of ®sh) are all reduced/decreased
(see Table 7). Even though the cost of manual auctioning is cheaper than that of
computer auctioning, however, the total processing cost per kg of ®sh actually goes
down from NT$2.36 to NT$2.12 when computer auctioning is implemented in all
78
Table 3
The resource costs per activity in the Pu-Shin wholesale ®sh market
Category of resource costs (m)a
Simulation results
Estimation of
machinery
depreciation (n)
Resource costs
for each activityb
(NT$/day)c
Unloading
Sta(4), cost of electricity resources
Pallets
Sta(4), cost of electricity resources, cost of
reconditioning machines, cost of machinery fuel
AGV(1), fork porter(3)
Sta(1), cost of electricity resources
Sta(5), cost of electricity resources
Weighing machines
Fish-baskets
Sta(5), cost of electricity resources
Numbering machine(1)
Sta wages(5), cost of electricity resources,
cost of reconditioning machine, cost of
machinery fuel
Computer auction clock(1), computer auction
machine A(2), computer auction machine B(2)
Sta wages(15), cost of electricity resources
Administrative spending, meeting costs
Computers
105 min
Number used=82
180 min
±d
6
±
1898.25
±
66 min
145 min
±
Number used=290
60 min
±
102 mine
10
±
±
10
6
±
10
±
Manual auctioning=1657.69
±
10
Computer auctioning=4826.21
150 min
±
±
±
±
10
15191.37
Ordering
Billing
Grading and weighing
Numbering
Auctioning
Administrative operations
a
b
c
d
e
5254.88
850.59
4372.01
1877.73
(m):m is the number of sta or machines utilized.
The resource costs for each activity equal ``the resource costs per day in that activity'' times ``the percentage of resource allocation''.
US$1=NT$31.
``±'' means that there is no such data.
The manual auction time is 42 min, and the computer auction time is 60 min.
T-R. Lee, J.-S. Kao / Agricultural Systems 67 (2001) 71±82
Activity
79
T-R. Lee, J.-S. Kao / Agricultural Systems 67 (2001) 71±82
Table 4
The volume of ®sh and the units handled in the Pu-Shin wholesale ®sh marketa
Auction area
Volume of ®sh (kg)
Units handledb
Cultured ®sh section A
Cultured ®sh section B
Cold-storage polyester box section
Imported ®sh section
Cold-storage ®sh-basket section
8105
3571
7610
4107
4618
675
298
634
342
290
a
Source: actual auction data on 11 August 1998.
The unit handled in the cold-storage ®sh-basket section is the basket (capacity=15 kg), and the unit
handled in all other sections is the box (capacity=12 kg).
b
Fig. 3. The allocation paths in the Pu-Shin wholesale ®sh market.
sections. Furthermore, one disadvantage of manual auctioning is that the process
may not be fair. By implementing computer auctioning in all sections, these are
impartial, public, and equitable contributions in the auctioning process, and the
total processing cost per kg of ®sh is reduced.
5. Comparing ABC with traditional costing methods
According to the results of the ABC model, the total processing cost is NT$2.36
per kilogram of ®sh. It is higher compared to NT$2.19, the processing cost calculated by using traditional accounting methods (data supplied by the Pu-Shin
wholesale ®sh market). One reason is that Pu-Shin wholesale ®sh market does not
calculate machinery depreciation during cost calculation. If we do not add machinery depreciation into the ABC model, the total processing cost would be NT$2.28
per kilogram of ®sh, which is more compatible to the calculated results of the traditional accounting methods. However, the ABC model still provides decision
makers with relevant information about cost management that the traditional
methods does not.
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T-R. Lee, J.-S. Kao / Agricultural Systems 67 (2001) 71±82
Table 5
The activity drivers and the calculated results of cost objects in the Pu-Shin wholesale ®sh market
Activity
Resource costs
for each activitya
($ NT/day)
Activity driver
(X)
Unloading
Ordering
Billing
Grading and
weighing
Numbering
Manual auctioning
Computer auctioning
Administrative
operation
Activity
driver
volumeb
Unit cost
for each
activity
(Y)
(Z=X/Y)
Processing
cost per kg
of ®sh
%
$1898.25
$5254.88
$850.59
$4372.01
Number of boxes
Number of boxes
Billing time
Number of boxes
1949
1949
1949
290
$0.97
$2.69
$0.44
$15.07
$0.08
$0.23
$0.04
$0.94
3.4
9.7
1.7
39.8
$1877.73
$1657.69
Number of boxes
Number of boxes
or baskets
Number of boxes
Minutes
1607
650
$1.17
$2.55
$0.09
$0.19
3.8
8.1
1607
150
$3.00
$101.27
$0.25
$0.54
10.6
22.9
$4826.21
$15191.37
Total
$2.36
100
a
The resource costs for each activity is calculated from Table 3.
The activity driver volume is calculated by referring to the units handled in Table 4 and the allocation
paths in Fig. 3. For example, the activity driver volume of unloading is calculated as follows: 1949=
675+298+634+342.
b
Table 6
The wages of sta in each activity of the Pu-Shin wholesale ®sh market per day
Activity
Unloading Ordering Billing Grading and Numbering Auctioning Administrative
weighing
operation
Wages of
$345.89
sta per day
(NT$)
$592.97
$550
$735.21
$304.23
$890.48
$820.40
6. Conclusions
To improve the functions of the wholesale ®sh market and encourage the trends of
economic liberalization and internationalization, it is necessary to pay close attention to cost management. For this purpose, this study has applied ABC and simulation techniques to analyse the operational costs of the Pu-Shin wholesale ®sh
market. The results show that the wages of the auctioning sta are the highest of all
activities, an implication that the auctioning sta plays a vital role. Furthermore, the
total processing cost per kg of ®sh is reduced by implementing computer auctioning
in the auction area. However, the ®ndings are based on a one-day simulation only.
For possible future research, we suggest a day-by-day data simulation to obtain
81
T-R. Lee, J.-S. Kao / Agricultural Systems 67 (2001) 71±82
Fig. 4. The allocation paths in the Pu-Shin wholesale ®sh market after computer auctioning is
implemented. Note: The bold lines represent the additive allocation paths after computer auctioning
is implemented.
Table 7
The activity drivers and the calculated results of cost items when computer auctioning is implemented in
the Pu-Shin wholesale ®sh market
Activity
Resource costs
for each
activity
($ NT/each day)
Activity driver
Unit cost
for each
activity
Processing
cost per kg
of ®sh
(Y)
(Z=X/Y)
1949
1949
1949
290
2239
2239
$0.96
$2.65
$0.43
$15.00
$0.84
$2.88
$0.08
$0.22
$0.04
$0.94
$0.07
$0.23
3.7
10.8
1.9
44.1
3.3
10.8
150
$100.85
$0.54
25.4
$2.12
100
Activity
driver
volume
(X)
Unloading
Ordering
Billing
Grading and weighing
Numbering
Computer auctioning
$1882.79
$5228.37
$840.87
$4350.66
$1887.89
$6468.89
Administrative
operation
$15128.54
Total
Number of boxes
Number of boxes
Billing times
Number of baskets
Numbering times
Number of boxes
or baskets
Minutes
%
accurate information about cost management. We believe that the ABC model used
with system simulation can certainly be applied to agricultural systems in other
countries.
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