unlocking the potential of time-driven activity-based costing for small logistics companies

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Unlocking the potential of time-drivenactivity-based costing for small logisticscompaniesSirirat Somapa a , Martine Cools b c & Wout Dullaert d ea Department of International Business , Logistics & Transport,Thammasat Business School, 2 Prachan Rd., Phra Nakhon,Bangkok , 10200 , Thailandb Department of Business Studies , Lessius – KULeuven, KorteNieuwstraat 33, Antwerp , 2000 , Belgiumc Rotterdam School of Management , University of Rotterdam ,Burgemeester Oudlaan 50, 3062 PA Rotterdam, The Netherlandsd Faculty of Economics and Business Administration , VU Universityof Amsterdam , De Boelelaan 1105, 1081 HV , Amsterdam , TheNetherlandse Institute of Transport and Maritime Management Antwerp,Antwerp University , Kipdorp 59, Antwerp , 2000 , BelgiumPublished online: 19 Nov 2012.

To cite this article: Sirirat Somapa , Martine Cools & Wout Dullaert (2012) Unlocking the potentialof time-driven activity-based costing for small logistics companies, International Journal of LogisticsResearch and Applications: A Leading Journal of Supply Chain Management, 15:5, 303-322, DOI:10.1080/13675567.2012.742043

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International Journal of Logistics: Research and ApplicationsVol. 15, No. 5, October 2012, 303–322

Unlocking the potential of time-driven activity-based costing forsmall logistics companies

Sirirat Somapaa, Martine Coolsb,c and Wout Dullaertd,e*

aDepartment of International Business, Logistics & Transport, Thammasat Business School, 2 PrachanRd., Phra Nakhon, Bangkok 10200, Thailand; bDepartment of Business Studies, Lessius – KULeuven,

Korte Nieuwstraat 33, Antwerp 2000, Belgium; cRotterdam School of Management, University ofRotterdam, Burgemeester Oudlaan 50, 3062 PA Rotterdam, The Netherlands; dFaculty of Economics and

Business Administration, VU University of Amsterdam, De Boelelaan 1105, 1081 HV Amsterdam,The Netherlands; eInstitute of Transport and Maritime Management Antwerp, Antwerp University,

Kipdorp 59, Antwerp 2000, Belgium

(Received 10 July 2011; final version received 17 October 2012)

This paper reports on the development of a time-driven activity-based costing (TDABC) model in a small-sized road transport and logistics company. Activity-based costing (ABC) leads to increased accuracybenefiting decision-making, but the costs of implementation can be high. TDABC tries to overcome someof the disadvantages of ABC and seems particularly useful for the road transport and logistics sector. Wefind that small firms can benefit from TDABC because of the use of simplified parameters. However, thelack of quantitative data on cost drivers remains a problem. To enhance the effectiveness and efficiency ofTDABC, a thorough redesign of the company’s recording system is recommended.

Keywords: time-driven activity-based costing; cost and performance benchmarking; transport andlogistics management

1. Introduction

The road transport sector, like many others, has found the recent economic recession and volatilefuel prices very challenging. Although the severity of recession varies from country to country, itis obvious that road transport and logistics firms are under pressure to review their cost structureand to find an effective cost management system that relates the company’s performance toits strategic goals. Among the recently popular cost management techniques is activity-basedcosting (ABC), which identifies the cost of products, customers or channels (the cost objects) byfirst allocating indirect costs to the activities that trigger them, before allocating them to the costobjects. By taking into account the number of resources consumed by the activities, the costs ofthese activities are then related to the cost objects driven by the degree to which they make use ofthe various activities. As compared to the traditional volume-based systems directly linking cost

*Corresponding author. Email: [email protected]

ISSN 1367-5567 print/ISSN 1469-848X online© 2012 Taylor & Francishttp://dx.doi.org/10.1080/13675567.2012.742043http://www.tandfonline.com

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304 S. Somapa et al.

pools to the cost objects, ABC increases the accuracy of the costing exercise (Cooper and Kaplan1988). This cost information can consequently be used to help the manager in strategic decision-making and can inform process improvements, cost reductions, innovative pricing, budgeting,outsourcing evaluations, etc. (Cardinaels et al. 2004, Stapleton et al. 2004, Kaplan and Anderson2007).

In spite of the interest amongst practitioners and academics, recent surveys document the slowdiffusion of ABC in practice. Gosselin (2007) finds that relatively few companies employ ABCand that a significant number of ABC adopters do not actually implement it. This could be dueto the fact that traditional ABC systems are expensive to build, complex to sustain and difficultto modify (Everaert and Bruggeman 2007, Kaplan and Anderson 2007). In response, Kaplanand Anderson (2004) started to promote time-driven activity-based costing (TDABC). TDABCprovides a simplified version of ABC, making it more capable of capturing the complexity ofreal-life settings while requiring less time and financial effort. Since TDABC reduces the burdenof updating cost models, it is enthusiastically implemented in a variety of industries, includingthe financial and medical sectors, educational services and wholesale companies (Kaplan andAnderson 2007, Pernot et al. 2007, Everaert et al. 2008a, 2008b, Demeere et al. 2009).

TDABC offers an interesting alternative costing system for road transport and logistics com-panies. Kaplan and Anderson (2004) provide examples of activities such as ‘shipping order tocustomer’. The complexity caused by the variation in resources required by different shippingarrangements can better be captured by TDABC than by traditional ABC models because TDABCtakes into account that the cost of an activity can differ in terms of the specific context in whichthis activity takes place. Similarly, Everaert and Bruggeman (2007) demonstrate the opportunitiesfor TDABC in environments with complex activities, often found in service sector companies andmore particularly in logistics and distribution companies. The aim of our paper is to investigatethe potential role of TDABC in cost management in a small transport and logistics firm. While thesuccess of ABC/TDABC approaches has been confirmed in various studies (Needy et al. 2003,Cardinaels and Ierland 2007), most studies on ABC/TDABC in the transport and logistics sectorinvestigate medium-sized to large companies. We therefore contribute to the literature by describ-ing and discussing how a TDABC model was developed in a particular case, more specificallyin a small road transport and logistics company in Thailand. Since Thailand is characterised by alarge number of small companies (Organization for Small and Medium Enterprises and RegionalInnovation JAPAN 2008), it provides an interesting setting to investigate the potential of TDABCfor small companies worldwide. In addition, it is a developing country in which most firms arenot equipped with advanced software packages; so it provides a basic setting in which the benefitsof TDABC can be investigated. After describing the transport services offered by the Thai firm,we discuss the problems encountered during the TDABC development process and the benefitsprovided for managerial decision-making.

The remainder of this paper is structured as follows. Section 2 contains a review of the literatureon ABC and TDABC. Section 3 introduces the case, while Section 4 provides the operationaldetails and develops the TDABC models. Section 5 discusses the implications of the introductionof TDABC in small firms in terms of cost allocation and managerial decision-making. Finally,our conclusions and directions for further research are formulated.

2. Theoretical background

In this section, we provide a literature review on the use of ABC and TDABC, and focus onthe potential usefulness of TDABC in small- and medium-sized firms. Because of the focusof this paper, we document the use of ABC-type approaches in the transport and logisticssector.

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International Journal of Logistics: Research and Applications 305

2.1. The traditional activity-based costing approach

ABC has been used predominantly because of its ability to manage overhead costs which haveincreased dramatically over the last few decades (Gosselin 2007). Implementing ABC involvestaking four steps: (1) developing the activity dictionary that lists and defines every major activityperformed in the production facility, (2) determining how much the organisation is spendingon each of its activities by using the resource cost drivers, (3) identifying the organisation’sproducts, services and customers and (4) selecting activity cost drivers that link activity coststo the organisation’s products, services and customers (Kaplan and Cooper 1998). Selection ofthe activity cost drivers (namely, transaction, duration and intensity drivers) reflects a subjectivetrade-off between accuracy and the cost of measurement. Transaction drivers are used to count thefrequencies of an activity (e.g. the number of orders). Duration drivers represent the amount oftime required to perform an activity (e.g. the time needed to load a truck). Intensity drivers referto directly charging for the resources used each time an activity is performed. Of the three types,transaction drivers are the least expensive and also the least accurate type due to the inherentassumption that activities are homogenous across the products. In other words, transaction costdrivers assume that for every similar event, the same number of resources is consumed. On theother hand, duration and intensity drivers are more expensive owing to the fact that more effort isneeded to estimate time used in the individual activity or to directly charge the resources to theactivity.

The use of ABC in the transportation and logistics sector has been documented for abouttwo decades now. Several studies investigate the airline industry. Banker and Johnston (1993)recommend the adoption of multiple operation-based cost drivers in addition to the normativevolume-based drivers generally used by airlines. Examples of operation-based drivers are aircrafttype and size or density of the network operated. These drivers impact the level of resource con-sumption and consequently affect the costs of individual services. Tsai and Kuo (2004) calculatethe ABC cost per unit (seat/kilometre and ton/kilometre) for an individual flight. The ensuingresults offer an improvement on other costing models as they reflect the different rates of resourceconsumption by different aircraft. Koch and Weber (2008) utilise ABC for revenue and cost con-trol and planning at Stuttgart Airport. First, a number of profit and cost centres are establishedbased on the airport’s services. These cost centres reflect the resource pools. Second, overheadcosts occurring within each centre are attributed to the processes performed by the centres. Costallocations vary due to several factors, such as the type of aircraft, the kind of flight (passengeror cargo) and aircraft standing location (passenger bridge or remote stand). Finally, cost informa-tion is exploited at the strategic level to analyse the revenues and costs occurring in alternativescenarios where changing traffic volumes are estimated.

An example of the implementation of ABC related to land transport can be found in Baykasogluand Kaplanoglu (2008) who study a Turkish land transport company. They provide a thoroughexplanation of the resource and activity cost drivers and make use of the Analytical HierarchyProcess to systematically structure overhead cost allocation. Costs are assigned to the serviceswhich are classified by characteristics such as destinations and whether traffic is domestic orinternational. The authors validate the cost allocation by comparing the disparity between theservice costs obtained from traditional cost accounting and those fromABC. Themido et al. (2000)present the management implications of ABC for a third-party logistics company in Portugal. AnABC profitability analysis for individual services reveals profit, loss and the associated root causes.The management team was hence able to renegotiate the services for loss-making customers andoffered alternative delivery patterns for varying prices. The new contracts satisfied both partiesas customers received a better service level and the company turned losses into profits. ABChas also been increasingly used by distributors, warehouse operators and wholesalers. Goldsbyand Closs (2000) document the use of ABC in the context of the reverse logistics of beverage

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products. Through estimating costs of return activities, they found that the costs were excessivelyhigh. Hence, they recommended the coordination of processes and outsourcing to an independentthird-party logistics provider. This cooperation resulted in a total saving of $11.4 million annually.

While these studies highlight the success stories ofABC, the inherently tedious and costly designand maintenance of the models plus the restricted capacity to expand to large-scale operationshave impeded the widespread adoption of ABC (Kaplan and Anderson 2004, 2007). Early surveyson ABC use reveal the following negative experiences and perceptions of ABC: unavailability ofdata, shortage of resources, managers’ resistance to change, lack of training, information tech-nology inadequacy, lack of senior management commitment, difficulties in linking cost drivers toindividual products and of collecting quantitative information on cost drivers (Cobb et al. 1992,Nicholls 1992, Armitage and Nicholson 1993, Pohlen and La Londe 1994). Goldsby and Closs(2000) add that ABC should be used with caution to avoid the cost distortions caused by the factthat similar cost centres undertake heterogeneous activities. Kaplan and Anderson (2004) relatethe problems with ABC to a large extent to the way in which people traditionally construct ABCmodels. First, a traditional ABC model requires that managers survey employees to estimate thepercentage of time they spend (or expect to spend) on various activities. The department’s resourceexpenses are assigned according to the average percentages resulting from the survey. While thisapproach works well in the limited setting of a single department, plant or location, it is difficult toapply on a larger scale for use on an ongoing basis. In addition, the interview and survey processitself causes serious problems. ‘When people estimate how much time they spend on a list ofactivities handed to them, they invariably report percentages that add up to 100. Few individualsreport that a significant percentage of their time is idle or unused’ (Kaplan and Anderson 2004,p. 2). It means that the cost driver rates are calculated based on the assumption that resourcesare working at full capacity, with the consequence that they are usually overstated. Further, onceput in place the ABC model is updated infrequently because of the costs of re-interviewing andresurveying. As a result, the estimates of process, product and customer costs rapidly becomeinaccurate. Kaplan and Anderson (2004) also indicate that as the activity dictionary expands toreflect more detail about activities or to roll out the model to the entire enterprise, the ABC systemstarts to exceed the capacity of generic spreadsheet tools such as Microsoft Excel or OpenOfficeCalc and many ABC software packages. Finally, we want to stress on the inadequacy of traditionalABC models in capturing the complexity of real-life logistics operations. Instead of assuming aconstant cost per order shipped, it makes sense for the shipper to recognise the cost differencesfor full- vs. half-loaded trucks, overnight express vs. commercial carrier, etc. In the traditionalABC approach, the differences in resources required by different shipping arrangements lead toa significant expansion of the model’s complexity (Kaplan and Anderson 2004).

2.2. Time-driven activity-based costing

In response to the disadvantages of the traditional ABC approach, TDABC has recently beenpromoted (Kaplan and Anderson 2004, 2007). ‘The solution to the problems with ABC is not toabandon the concept.ABC after all has helped many companies identify important cost- and profit-enhancing opportunities . . . fortunately, simplification is now possible’ (Kaplan and Anderson2004, p. 2). TDABC is a refined model that is better capable of incorporating the heterogeneityin the processes and of allocating more precise resource consumption rates to the cost objects.Under TDABC, the efforts of regularly interviewing employees and the ambiguous estimation ofthe percentage of time dedicated to an individual activity in ABC are replaced by estimating twoparameters: (1) the estimate of the time required to perform each activity and (2) the estimateof costs and capacities employed in each department. Time estimation is expressed in a timeequation, taking into account the different consumption rates for the same activity in a differentcontext. Employees are not surveyed on how they spend their time. Instead, managers first directly

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estimate the practical capacity of the resources supplied as a percentage of the theoretical capacity(Kaplan and Anderson 2004). For the road transport company ‘time spent on loading the trucks’,a basic activity for all service routes, varies significantly with the arrival time of trucks and thelocation of the warehouses at which cargos are loaded. Instead of creating multiple activitiesto accommodate the variations in time consumption, the time equation introduces ‘interactive’variables for the arrival time and the warehouse location. Accordingly, the time equation enablesmanagers to capture the different amounts of time consumed by trucks for different individualtrips. This ‘bottom-up’characteristic of TDABC contributes to an accurate allocation of time (andhence costs) of the services of a company. As a consequence, TDABC also allows easy updatingof the cost system when products or service offerings change, or when production and serviceprocesses are redesigned. By no longer using the transaction driver (e.g. the number of orders),but instead considering the time required to perform a certain activity (e.g. order-processing), thecost per unit (order) can be made fully situation dependent without rebuilding the whole model(Everaert and Bruggeman 2007).

In the context of transport and logistics, Varila et al. (2007) explore a more precise imple-mentation of ABC in a warehouse. They state that a single transaction driver is not sufficient forcost allocation. They therefore suggest the use of interactive variables for cases in which onevariable has an effect on another. To validate this assumption, the authors compare the accuracyin the time estimate models of the picking activity when using a single transaction variable vs.the use of multiple interactive variables. Their findings demonstrate that the latter provides moreaccurate time estimates, which confirms the usefulness of the interactive variable structured inTDABC models. To investigate further the practicality of TDABC in transport and logistics firms,Everaert and Bruggeman (2007) and Everaert et al. (2008b) corroborate the merit of TDABC forobtaining more accurate cost estimates for a wholesaler in Belgium. The case illustrates the abilityof TDABC in capturing heterogeneous processes by incorporating a number of subtasks in thetime equations. The authors provide empirical evidence on the determination of time drivers andthe interaction effect between the drivers. The illustrated time equations contain three types ofvariables: continuous, discrete and indicator variables. Continuous variable are real values suchas the weights of pallets. Discrete variables are the integer values such as the number of orders.Finally, indicator or dummy variables can only take the value of 0 or 1 to indicate, e.g. whether acustomer is an existing or a new customer. Incorporating these variables in the models simplifiesthe formulation of the equations.

Nevertheless, TDABC practitioners must be aware of potential errors which may occur dur-ing the estimation process in an ABC-type costing system. Generally, three types of error havebeen identified: specification error, aggregation error and measurement error (Datar and Gupta1994). Specification error is the selection of irrelevant cost drivers, aggregation error is the failureto address the heterogeneous resource consumption and measurement error refers to the wrongmeasurement of the time unit or resource cost. Cardinaels and Labro (2008) stated that measure-ment error tends to increase when the activities are less aggregated, due to the limited memoryspan of the estimators. In addition, minute-based time estimates are associated with overestima-tion bias since the estimation might include idle time. These biases might jeopardise the accuracyof the models. TDABC users might make the wrong decisions in the short term, because TDABCincorporates the fixed costs into the product costs, and therefore provides the full absorptioncost of the cost object (Lowder 2006). In contrast, for short-term decision-making, marginal costpricing is a preferable choice.

2.3. ABC and TDABC in small- and medium-sized enterprises

Implementation of ABC is more frequently found in large organisations than in small- andmedium-sized enterprises (SMEs) (Armitage and Nicholson 1993, Bjornenak 1997, Krumwiede

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1998, Innes et al. 2000, Pierce and Brown 2004, Gosselin 2007). ABC is often perceived asan inappropriate tool for SMEs. This perception stems from the harsh experiences of managerswho have tried to implement the system in large companies and had to invest a massive effortduring the implementation process (Hicks 1999). In fact, there are several restrictions for SMEs.First, they basically employ financial accounting as specified by the regulatory FinancialAccount-ing Standards Board of their countries to provide information for lenders and for tax purposes.Intended to limit the administrative burden for small-sized businesses, these accounting sys-tems fail to provide the necessary information needed for strategic planning and decision-making(Baxendale 2001). In other words, necessary information needed to support the modelling ofthe time equations, such as quantitative information on the cost drivers, is lacking. Similarly,Januszewski (2007) documented that the high time consumption in data preparation resultedfrom purely manual verification since those data were not recorded in the current accountingsystem. The second restriction is related to company resources. Since small businesses often faceresource poverty – limited technical, financial and human resources and inadequate computeri-sation – this might prevent the company from implementing the system (Roztocki et al. 2004).This scarcity of resources raises concerns for SMEs that the benefit of improved cost informationdoes not justify the required effort. Inhibiting factors include the costs of consulting support,possible productivity decrease during the implementation process and the maintenance of addi-tional data (Needy et al. 2003). Bharara and Lee (1996) also mention the resistance to changein their study of ABC implementation in a small business. Participants were reluctant to fill inthe time sheets and had difficulty in maintaining the databases with the number of activities anddrivers.

Despite these inconveniences, ABC-type approaches can have a merit in small businessesand have therefore been introduced in various small firms (Bharara and Lee 1996, Hicks 1999,Gunasekaran et al. 2000, Needy et al. 2003, Roztocki et al. 2004, Cardinaels and Ierland 2007,Januszewski 2007). ABC not only provides accurate cost information: the benefits are expandedto the elimination of non-value-added activities (Gunasekaran et al. 2000), the revelation ofconstraint resources and possible areas for process improvement (Baxendale 2001) and customerprofit analysis (Cardinaels and Ierland 2007). Some authors include suggestions for a smoothand simplified implementation process. Bharara and Lee (1996) suggest that small firms usepersonalised time sheets to keep information on differences in activity details and to be able to traceindirect labour costs to activities. Roztocki et al. (2004) introduce the expense-activity-dependencematrix to match activities to the expense categories, and the activity-product-dependence matrixto match activity expenses to products. Calculations are undertaken in routine spreadsheets andthe implementation process does not require sophisticated data collection systems.

TDABC seems more useful for small transport and logistics firms than the traditional ABCapproach. First, the inherent complexity of logistics activities with different operational charac-teristics can be captured and, second, TDABC allows flexible and regular updating of the costingsystem (Everaert and Bruggeman 2007). Third, in contrast to traditional ABC models, only themanagers (rather than all employees) are heavily involved in providing detailed cost information.In this way, the reported employee irritation in large ABC exercises (Kaplan and Anderson 2004)can be avoided. Fourth, these managers directly estimate the resource demands imposed by eachtransaction, product and/or customer, thus avoiding a complicating step to assign costs first toactivities as in the traditional ABC model (Kaplan and Anderson 2004, Everaert and Bruggeman2007). Fifth, since all measures are expressed in time units, the calculations and understandingare quite easy. Last, since the scale of the firms is limited, we expect that generic spreadsheettools will be sufficient to support the cost calculations. Despite these advantages we are awareof the fact that, similar to other costing approaches, a number of problems will remain. There istherefore value in probing the practicality of TDABC in the context of one small-scale operatorand investigating the problems during the design and implementation process.

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3. The case study context

An in-depth case study provides us with the opportunity to identify key problems associated withTDABC implementation in a small firm. We first explain the set-up of our case study, and thenpresent the case company, RC Transport.

3.1. Set-up of the case study

This case focuses on the transport and logistics industry, one of the industries most influencedby the economic crisis. We targeted a small-sized transportation company, since small firms aremore vulnerable to insolvency due to their limited capital support (Bradley and Cowdery 2004).The company was selected based on its size and product diversity. The research team contacted themanagement of the company and requested if they could examine the company’s cost structure.The owner/manager agreed to provide the required information because he anticipated that thestudy would potentially bring about cost reductions and process improvement. The name of thecompany is disguised in this paper for reasons of confidentiality. We will refer to the firm as ‘RCTransport’. At the start of our study, the firm used a traditional cost accounting model and did nothave any experience with ABC. The owner’s perception towards ABC was neutral, which wasan advantage to the study as it reduced possible resistance to the research findings. Similar toother small-scale operators, the company relied on a few customers. This limited the role of thecompany to being a price-taker on the market. Accordingly, profitability depended largely on thecost level. The application of TDABC was expected to provide beneficial cost information andsuggest tentative strategic actions to the management team.

To be able to build the TDABC model, we required data to estimate the two parameters: the costper unit for the consumption of resources in the resource pools and the time consumed by theactivities in the processes. Data were collected by different means to obtain sufficient detail for themodels. These included the gathering of relevant documents (financial statements, bill of orders,etc.), interviews with the management team and personnel, and the observation of the operationsat the company premises. Time estimates were obtained by reconciling the information providedby the managers and the frontline operators in an effort to reduce measurement error. The datagathering process was highly time-consuming and required repetitive visits to the site. When nocompany data were available (e.g. on some cost drivers), estimates provided by the owner wereused. The second part of the study consisted of examining the cost information for potential areasof improvement.

3.2. Company background

RC Transport is a small-sized road transport company. The firm has 13 permanent staff membersincluding the owner/manager, and 25 contract staff who are primarily the drivers and workers forloading and unloading the trucks. The total asset value is approximately 25 million Baht (±625,000Euro), and the business turnover is 37 million Baht (±925,000 Euro). It provides transport anddistribution services to several domestic destinations in the central and north regions in Thailand.Product diversity results from servicing several types of stores, handling various cargos and usinga variety of delivery patterns. Currently, there are five routes that are classified as the forward andbackward hauls. The forward hauls comprise three routes: Sri Racha–Lampoon, Sri Racha–ChiangMai and Sri Racha–Mae Hongson. The backward hauls are Lampoon–Bangkok and Lampoon–Sri Racha (see Figure 1). These routes are concentrated in the same regions to reduce emptymileage between the routes. Cargoes are dispatched to the destinations which are segmentedinto super stores, wholesale stores and retail stores. Super stores and wholesale stores tend toorder full truckloads while the retail stores’ orders are fragmented and require less than truckload

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Figure 1. Geographical coverage of transport services.

(LTL) shipments which necessitate cross-docking at the company’s warehouse in Chiang Mai.The company currently outsources the distribution to Mae Hongson and Chiang Mai retail storesto local truck companies in order to minimise the capital sunk costs. The company owns a numberof trucks. The fleet consists of eight trucks and two semi-trailer trucks. To cope with the uncertaindemand, the company has decided to ally with two other companies to form a truck pool. In thispaper the vehicles concerned are referred to as the ‘joint trucks’. The ‘own’ and ‘joint’ trucks areelements of the variation incorporated in the time equations since they consume different timeand cost effort.

4. Development of the TDABC model

In this section, we develop the TDABC model by first identifying the resources and practicalcapacity. Next, we estimate the time needed for the activities and the time drivers, and finally weidentify the time equations. The TDABC procedure is presented in Figure 2.

4.1. Resources and practical capacity

Since RC Transport does not separate its organisation into divisions and departments, the resourcepools are established unofficially based on actual functions performed. The four resource pools –planning, accounting, transportation and warehousing units – are depicted in Figure 2. These unitsconsume resources and generate expenses for every transaction. In general, there are five mainresource types: personnel, building and facilities, vehicles, warehouses and expenses not related to

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Figure 2. TDABC procedure.

any of the previously mentioned resources, which can therefore not be attributed to any particularfunction. These expenses are named ‘corporate-sustaining expenses’ as recommended by Kaplanand Anderson (2007). Resource capacities are expressed in terms of the number of working hours.We assume that employees work up to 80% of their available time. This rule equally applies to thevehicles, since verification with the management team revealed that off-work hours (maintenanceand repair) of the vehicle take up approximately between 10 and 20% of the total operating hours,dependent on the age and condition of the vehicles. For the transportation unit, resources areseparated into vehicles and labour due to the different actual working hours and the different

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Table 1. Capacity cost rates (in Baht, 1 Baht equals 0.03 USD approximately).

Practical capacity

Normal Working Capacity 80% Capacity CapacityNo. of working hour days per Capacity Aggregated cost rate rate cost

employees per day per year year (h) per year (h) costs (Baht) (Baht/h) (USD/h)

Planning and controlunit

5 8 313 12,520 10,016 2,099,701 209.63 6.29

Accounting andfinance unit

3 8 313 7512 6009.6 1,575,182 262.11 7.86

Transportation unit(vehicles)

10 24 345 82,800 66,240 24,645,188 372.06 11.16

Transportation unit(labour)

15 10 338 50,700 40,560 2,911,158 71.77 2.15

Warehousing unit 5 8 313 12,520 10,016 2,112,169 210.88 6.33

utilisation rates. Practical capacity is assessed by multiplying the normal working hours of theemployee with the number of employees in the functional units and the number of working daysper year. The result indicates the practical working hours in a year. Capacity cost rates are finallyderived by dividing the total costs in the functional units by these practical working hours.

A difficulty in the practical capacity assessment is caused by the irregular working hours of theemployees and workers. This is a typical situation for small-sized enterprises in developing coun-tries, since the relationship between the entrepreneur and his employees is often quite personal.As a consequence, there are no formal working hours. Some employees have a night shift or workduring the weekend without additional payment, while other employees are allowed to take leavefor personal reasons during the working hours. Therefore, we estimate practical capacity basedon general practice as shown in Table 1.

4.2. Time estimates for the activities and time drivers

As illustrated in Figure 2, there are six operational processes in total: shipment preparation,loading, transportation, unloading, warehouse operations and invoicing/auditing. Being a smallcompany, RC Transport has not invested in automation technology such as bar codes, RFID andGPS, and is therefore incapable of obtaining real-time data. Time estimates for activities related tothese processes are based primarily on interviews with the management team and staff. The figuresare assessed first hand by the supervisor and manager, and if they are uncertain they consult withthe operators to obtain the time in practice. This ‘top down’ approach provides quick access to thedata and reduces the frustration felt by employees when asked to provide the main assessment ofthe exact operational time.

Time drivers are attained by interviewing supervisors and managers on activities and their timeconsumption. They comprise a small set of critical drivers that can be obtained with moderateeffort. As reported by Cardinaels and Ierland (2007), such reduced models (with few drivers)do not sacrifice accuracy if they are able to explain the majority of the process variation. Theinitial stage is to map the detailed activities within the processes, along with the estimated timefor those activities. We re-examined the time appraisals – by asking ‘why’ – in an attempt toidentify the drivers influencing the duration of the activities. The information received confirmsthe time variation in the processes related to the service routes and the requirement for each trip.For example, shipment preparation time for the route to Chiang Mai may be longer than theroute to Lampoon since employees spend more time contacting the local truck companies whoactually distribute the cargo. But, this does not necessarily mean that the Chiang Mai trips alwaysconsume more preparation time than the Lampoon trips. Another determining factor is whether

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Table 2. Factors for time variation in the processes.

Processes Variation within the processes (drivers)

Shipment preparation Number of ordersAdditional contact with the local truck companies (for distribution purpose)Additional contact with the allied companies to call for the joint trucks (when own trucks are

not available or are not sufficient)Loading operation Location of the loading points

Waiting time before loadingAdditional time to amend the document if there is discrepancy

Transportation Distance between truck yard and loading points (empty hauls)Distance between loading and unloading points (laden hauls)Distance between each unloading point (laden hauls)Distance between unloading points and truck yard (empty hauls)Number of dropsAdditional time if there are unforeseen incidents

Unloading operation Location of the unloading pointsTypes of destination (super stores, wholesale stores and retail stores)Waiting time before unloadingNumber of dropsAdditional time to record the document (in case of damage)

Warehouse operation Cargo consolidation (in case of LTL shipment)Store readiness (postponed delivery)Number of days (storage)

Invoicing and auditing Number of ordersNumber of transactions (e.g. receipts)

the trip requires a joint truck or an own truck. Since joint trucks involve additional time usedto contact allied companies, a trip which necessitates a joint truck would end up with a longershipment preparation. TDABC is found to be highly capable of addressing the variation in theprocesses. Table 2 provides a summary of the process variation. Note that complex operationsoccur in small companies, just as they do in large ones.

4.3. Modelling the time equations

During the time appraisals, a number of difficulties were encountered. First, it was difficult forthe management team to reach a consensus on the duration of the activities, more specifically onthe exact start and finish times. The definition of an activity inevitably affects its duration and thefunctional units that are the owners of the processes. One example from the invoicing process isthe gathering of the order bills to produce invoices. This activity is not continuous and there are noobvious start and end times, making staff reluctant to quantify activity duration. This drawbackmay induce a measurement error in the time equation models. Second, there was a discussion onwhether to take into account waste activities such as waiting time in the duration of the processes,since resources are not economically utilised during these moments. Embracing these time periodsin the process duration would probably overestimate the utilisation rates. One example relates totruck operating time. After completing its journey, a truck then has to park in the truck yard whilewaiting for the next cargo. This activity is not part of any operational process. Ignoring it wouldmake the time model incomplete but including it in the duration of the process would result inan artificially high capacity utilisation of the trucks. The management team concluded that thetime should be incorporated in the models to provide insight into the scale of waste activities. Atthe same time, waste was deliberately removed from the activity durations for assessing capacityutilisation. Hence, the time equation for the loading operation includes the waiting time of thetrucks to reflect the total time allocated to these activities, but these times are not counted in theresource utilisation assessment, by excluding the activity from the relevant calculation sheet.

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Table 3. Time equations and variables.

Processes and activities Time equations and variables

Shipment preparation Tj1 = 0.17X1 + 0.5X1 + 1 + 0.5 + 0.17X1 + 0.17X3

+0.5X3 + 2X4 + 0.5X5

receive the order + pick the order + planning + wagepayment + notify receivers + contact drivers (if usingcompany truck) + pre-trip inspection (if using companytruck) + contact truck company (if using joint trucks) + contactdistributors (if cargo needs distribution)

X1 = number of orders per tripX3 = 1 (if using company truck) 0 (if not)X4 = 1 (if using joint truck) 0 (if not)X5 = 1 (if contact distributor) 0 (if not)

Loading operation Tj2 = 1 + X8X10X18 + X8X11X18 + 0.17 + 0.17X19

loading + waiting time(if Sri Racha) + waiting time(ifLampoon) + tally/inspection + correction (if discrepancy)

X8 = waiting time before loadingX10 = 1 (if loading cargo at Sri Racha) 0 (if not)X11 = 1 (if loading cargo at Lampoon) 0 (if not)X18 = 1 (if truck arrives earlier than schedule) 0 (if truck arrives

on time)X19 = 1 (if there is discrepancy between actual load and document)

0 (if not)

Transportationa Tj3 = 0.5X10 + 2X11 + 12X12 + 14X13 + 14X14 + 14X15

+12X16 + 0.17X21 + 0.34X22 + 0.5X24

+12X12X25 + 14X13X25 + 14X25 + 0.5X15 + 2X16

journey time between truck yard and loading point + journey timebetween loading point and first drop + journey time during thenumber of drops + journey time between last drop and truckyard (if no backhaul cargo)

X10 = 1 (if loading cargo at Sri Racha) 0 (if not)X11 = 1 (if loading cargo at Lampoon) 0 (if not)X12 = 1 (if unloading cargo at Lampoon) 0 (if not)X13 = 1 (if unloading cargo at Chiang Mai) 0 (if not)X14 = 1 (if unloading cargo at Mae Hongson) 0 (if not)X15 = 1 (if unloading cargo at Sri Racha) 0 (if not)X16 = 1 (if unloading cargo at Bangkok) 0 (if not)X21 = number of drops in LampoonX22 = number of drops in Chiang MaiX24 = number of drops in BangkokX25 = 1 (if no backhaul cargo) 0 (if there is backhaul cargo)

Unloading operation Tj4 = 1X17X12X21 + 1X17X13X22 + 1X17X15X23 + 1X17

X16X24 + X9X18X12 + X9X18X13 + X9X18X15

+X9X18X16 + 0.17 + 0.17X20

unloading + waiting time + tally/inspection + amend the document(if damage occurs)

X9 = waiting time before unloadingX12 = 1 (if unloading cargo at Lampoon) 0 (if not)X13 = 1 (if unloading cargo at Chiang Mai) 0 (if not)X15 = 1 (if unloading cargo at Sri Racha) 0 (if not)X16 = 1 (if unloading cargo at Bangkok) 0 (if not)X17 = 0 (if unloading cargo at retail store) 1 (if unloading cargo at

super stores) 2 (if unloading cargo at wholesale stores)X18 = 1 (if truck arrives earlier than schedule) 0 (if truck arrives

on time)X20 = 1 (if there is discrepancy between actual unload and

document) 0 (if not)X21 = number of drops in LampoonX22 = number of drops in Chiang MaiX23 = number of drops in Sri RachaX24 = number of drops in Bangkok

Warehouse operation Tj5 = 2X27 + 2X6 + 1X6 + 1X6 + X26X6 + 1X6

+0.17X6 + 0.17X27 + 1X6 + 1X27

unloading + space planning (if cargo requires stor-age) + moving (if cargo requires storage) + storage (ifcargo requires storage) + order picking (if cargo requiresstorage) + sorting + loading

X6 = 1 (if cargo requires storage) 0 (if not)X26 = number of days of storageX27 = 1 (if cargo is distributed to Chiang Mai retailers)

0 (if not)

Invoicing and auditingb Tj6 = 0.5X1+ 1X1+ 0.25X2+ 0.2X2

notify customer + prepare invoice + verify transaction + preparefinancial report

X1 = number of orders per tripX2 = number of transactions per trip

aThere is only one drop in Sri Racha so it does not require a distinct variable.bTransactions refer to all expenses and bills associated with the trip.

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The next step is to construct the time equations. We make use of the linear models introducedby Everaert and Bruggeman (2007). The models comprise three parameters: activities j, processesk and functional unit i. Costs per trip for individual routes (TCr) are derived from the total timeconsumed by all activities in the processes multiplied by the cost per unit of the relevant functionalunits.

TCr =N∑

i=1

M∑

j=1

L∑

k=1

TjkCi

where Tjk is the total time (hours) consumed by activity j in process k; Ci the cost per hour ofthe functional unit i; L the number of processes; M the number of activities; N the number offunctional units and r the individual service route.

Each time equation (Tjk) represents the total time for a process. Time drivers are expressed bythe variable X. The variables consist of a mix of continuous, discrete and indicator types. Theyrefer to the variation in the processes. The generic form of the equation is shown below.

Total time in the process (Tjk) =∑

(βp · Xp); p ∈ j, k, r

or = β0 + β1X1 + β2X2 + β3X3 + · · · + βpXp

where βp is the time estimated for activity j in process k for route r and Xp is the time drivers foractivity j in process k for route r.

A summary of all time equations is exhibited in Table 3. These time consumptions reflect theallocation of the indirect costs. Note that they do not take into account the time for distribution ofcargo to Mae Hongson, as those activities are outsourced to local trucks and accordingly becomethe direct costs of the route.

5. Implications of the introduction of the TDABC model

Based on the TDABC information, RC Transport’s management team was able to draw a numberof conclusions.

5.1. Insights from the identification of costs and profits

Cost calculations for the services are conducted in three steps. The first step is to identify the costsof an individual activity in the processes by applying the activity times to the relevant resourcecosts (capacity cost rates). Some activities, such as loading and unloading operations, consumemultiple resources (trucks and labour) simultaneously. The second step is therefore to calculatethe process costs, by summing the activity costs in the process. The last step is to calculate theprocess cost per unit for each service route and destination. These unit costs, as shown in Table 4,are subsequently analysed to understand the profitability and the potential opportunity for costreduction of each route.

As shown in Table 4, the Mae Hongson route is the most expensive route due to its high storagecost. Since the order size is small, the company consolidates the orders on this route until a fulltruckload shipment size is reached. This typically requires an average of five days of storage.Storage costs also account for the high cost of the Chiang Mai retailer and wholesaler routes, asthey rank second and third on the list. Next is the Bangkok route which displays proportionallyhigh costs related to the waiting time before unloading. Trucks arriving in Bangkok at the truck-ban period are detained for 4 h on average. This is an unavoidable cost for the route. In contrast, thecomparatively lower costs of the Lampoon and Sri Racha services result from the short distanceand the few drops along the routes.

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Table 4. Time and cost per unit of service routes (in minutes and Baht).

Shipment Invoicing andpreparation Loading Unloading Transport Warehousing accounting Total

Routes/processes Time Cost Time Cost Time Cost Time Cost Time Cost Time Cost Time Cost

Lampoon• Super stores 0.25 1.02 0.36 2.59 0.10 0.74 1.29 7.95 0.00 0.00 0.59 2.80 2.59 15.10• Wholesale stores 0.31 1.44 0.35 2.54 0.35 2.54 1.28 7.89 0.00 0.00 0.71 3.31 3.00 17.73

Chiang Mai• Super stores 0.25 1.02 0.36 2.60 0.10 0.74 1.51 9.33 0.00 0.00 0.59 2.80 2.82 16.48• Wholesale stores 0.25 1.02 0.36 2.60 0.19 1.36 1.51 9.33 1.14 4.24 0.59 2.80 4.04 21.34• Retail stores 0.44 2.09 0.36 2.60 0.02 0.12 1.54 9.54 2.97 11.69 0.85 3.96 6.18 30.00

Mae Hongson 0.43 2.08 0.36 2.58 0.02 0.12 1.47 9.05 10.75 39.01 0.84 3.94 13.87 56.77Sri Racha 0.22 0.88 0.14 1.01 0.10 0.74 1.42 8.70 0.00 0.00 0.59 2.80 2.47 14.13Bangkok 0.36 1.79 0.14 1.01 0.70 5.07 1.50 9.35 0.00 0.00 0.85 3.96 3.55 21.17

Figure 3. Profit and loss for service routes and destinations.

Most service routes and destinations are profitable except for the Chiang Mai retail, MaeHongson and Bangkok routes (see Figure 3). The Lampoon route yields the highest profit.However, its contribution to the overall profit is limited due to its small volume (the annualvolume accounts for only 3% of the total cargo volume). Alternatively, the Chiang Mai routes,despite the lower yield, are the main source of revenue for the company as they include 43% ofthe overall cargo carried in a year. Losses incurred in the unprofitable routes are thus subsidisedby profits earned from the profitable ones. The breakdown of revenue and cost details by serviceroutes enables the manager to concentrate his efforts on the areas most in need of attention.

5.2. Cost improvement and resource utilisation suggestions

Acknowledging the cost and profit insights from the TDABC analysis, the management teamsees two options: cost reduction and resource utilisation improvement. To identify opportunitiesfor cost reduction, the team can start from the time and cost comparison of the activities. Thecomparison, as shown in Figure 4, reveals the distinct areas where the accumulated time andcosts increase considerably when the activities are performed. These are transport, warehouseand invoice and accounting activities. Since the cost level depends on two parameters – time

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Figure 4. Accumulated time and costs for the activities (in hours and 1000 Baht).

consumption and capacity cost rates – cost improvements are related to either or both of thesefactors. Regarding transportation, the management team may choose to renegotiate the freightrate for the contracted truck drivers in order to reduce the capacity cost rate of the trucks. Equallyimportant is improving the effectiveness of truck hours by eliminating the waiting time beforeloading and discharging. For example, the trucks heading towards Bangkok are regularly affectedby the truck-ban period and have to wait 4 h on average. The company may wish to renegotiatethe loading time at the client’s warehouse in Lampoon to avoid this problem.

For warehouse operations, storage time constitutes the lion’s share of warehouse activity. Reduc-ing the storage time accordingly would result in an improvement of the overall time consumption.As illustrated in Table 4, warehousing cost per unit for the Mae Hongson route accounts for 69%of the total costs. This is due to the fact that the cargoes rest in the warehouse for approximately5 days before shipment. The delay in shipment is caused by the need to wait until small ordersizes can be consolidated to provide a complete truck load. One option for the manager wouldbe to seek additional cargo to Mae Hongson in order to reduce storage times before despatch. Ifthe storage time could be reduced to 2.5 days, for example, warehousing cost per unit would bereduced from 39 Baht to 21 Baht (or a 46% reduction), which would virtually turn a loss-makingservice into a profitable one. Since warehousing costs account for approximately one-fifth of theoverall costs, warehousing cost savings have the potential to make a major contribution towardsthe profit of this route. A warehouse is a resource that has an opportunity cost, and even thoughmore efficient use of the warehouse would not necessarily lead to immediate cost savings, suchsolutions offer potential for lower costs in the future.

Another area for improvement is the time consumption of the accounting activities. Sincethe hourly cost of the accounting staff is relatively high, efficiency needs to be increased byaccelerating this process. Amongst a range of accounting-related activities, the verification oftransaction activity consumes the largest amount of time; so there is a clear need for managers toidentify the bottlenecks and their causes and seek appropriate solutions.

Analysis of the resource utilisation of each functional unit is shown in Figure 5. Resourceutilisation refers to the operating time compared to the practical capacity of the resources. The

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Figure 5. Resource utilisation for the functional units.

analysis reveals a relatively low utilisation rate per transportation unit (24% for labour and 65% fortrucks) whereas the planning unit is almost fully utilised (86%) and the warehouse and accountingcapacities are overly exploited. The low utilisation rates for labour and trucks partly result fromthe time waiting for the next journey. On average, a truck waits 6 h at the truck yard before loadingcommences. Seeking additional cargo or additional drop points would be a rational strategy, togenerate more truck activity and minimise idle time. For labour, seeking additional cargo mightnot be the only solution, because the low utilisation rate also indicates that there is excessivelabour. The manager may need to review the contracts and re-assess the appropriate workinghours to suit the actual operations. At the time of our study, the manager was indeed in the processof renegotiating contract payments. A change was made whereby, remuneration was paid as afixed amount per loading per truck, irrespective of the number of workers involved. Previously,the wages were based on a fixed amount per head per day and, as a result, the firm was confrontedwith a situation of unused capacity. The new method is expected to remove this problem.

The high utilisation rate for warehouse resources is due to limited human resources and limitedstorage space during peak periods, the latter being caused by the free storage allowance given tosome wholesalers and retailers.

The high utilisation rate for accounting resources is related to the time estimates for jointactivities and concurrent activities, which tend to be larger than the actual times. Estimated timesfor the joint activities such as the preparation of invoices for consolidated cargoes are countedfor each of the consolidated cargoes in a trip, because they represent different destinations, butare actually only incurred once. The time estimates for concurrent activities such as transactionverification are taken into account sequentially whereas they can be performed concurrently withthe other subtasks.

5.3. Difficulties with TDABC in small enterprises

Though a small road transport and logistics firm can benefit from TDABC because of the moresimplified development process compared to traditional ABC, TDABC developers may encountera number of problems that cannot be easily overcome. The first problem is the lack of essentialquantitative data to support the building of time equations and the calculation of capacity costs.

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The second problem is the difficulty in estimating the time for certain activities especially forthose that do not run continuously. The final problem is the judgment of time allocation for theconsolidated services.

5.3.1. Lack of quantitative data to support the development of time equations and capacitycosts

The lack of quantitative data on cost drivers is the main obstacle when developing TDABC in asmall firm. Principally, this problem originates from the lack of records on the daily transactions. Ina large company, these transaction records can be retrieved from the corporate ERP database, but insmall firms acquiring this kind of data must be done manually. As stated by Kaplan and Anderson(2007), building up a time-driven model may be difficult if it is to be applied in a company whichdoes not have a convenient source for transaction data.At RC Transport, managers were previouslyunaware of the importance of the critical data, e.g. the number of drops for each individual tripwhich is an important cost driver of the transportation and unloading duration. Since each triphas different drop points, it is not easy to estimate the average number of drops. A rough estimatewas made by dividing the annual number of order bills, which represent the drop points, by thenumber of trips over the entire year. However, this average number may not be very accurate.Care and attention to the transaction data is clearly essential if companies wish to develop andmaintain reliable cost models.

In addition to the cost drivers, the ability to track the sources of corporate expenditure isequally significant. The general ledgers currently used in small businesses do not provide sufficientdetail as to which department has created these expenses. When inaccurately allocated costsare pooled into the departments, the resource cost pools may be over- or undercharged andthus contain measurement error (Labro and Vanhoucke 2007). This error is then carried forwardinto the misjudged capacity cost rates and eventually results in distorted service costs for thecompany. Small firms therefore need to give thorough attention to establishing links betweenexpenses and the departments responsible. The incremental tasks relating the cost drivers anddepartmental expenditure may lead to additional work, but this is usually compensated by theincreasing accuracy in the cost models.

5.3.2. Difficulty in estimating time for certain activities

Though small businesses benefit from the simplified time estimates provided by TDABC, thetool is not necessarily appropriate in every situation. Where the amount of time cannot be effec-tively predicted, such as in advisory work or consulting, a more formal time-tracking system inaddition to the interview may be required (Max 2007). As suggested by Kaplan and Anderson(2007), the time estimates for TDABC system require a measurement capability. In fact, thiscapability already exists in many organisations which establish standard procedures to measurethe time occurred in the processes, but this capability may not be in existence in small busi-nesses. It is difficult to estimate time for activities that are non-standardised. In the case of RCTransport, non-standardised and non-continuous activities occur in the invoice preparation andtransaction verification processes. Essentially, order bills signed by the consignees are returnedto the accounting units by truck drivers upon completion of their journeys. However, exceptionsarise in many instances, such as when cargoes cannot be delivered immediately and have to bekept in the warehouse for a certain period. Delays in the order bill collection process unavoidablyimpact the invoice preparation. Delay may last for a day or a week, dependent on the ability todeliver the cargo. This uncertainty is partly caused by external factors such as the lack of spacein the wholesalers’ warehouses. Consequently, time estimates for invoice preparation are, to acertain extent, unpredictable. The problem is resolved by assuming that processes are undertaken

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continuously with minimal variation. This assumption corresponds to the so-called ‘light mea-surements’ proposed by Kaplan and Anderson (2007) who state that the purpose of the TDABCmodel is to achieve accuracy rather than precision. A project leader should estimate the approx-imate time for the task rather than taking a costly measurement to calculate the exact standardtimes per transaction. As a result, the time estimate for invoice preparation is not the precise timebut the estimate of the average waiting time for the returned order bills and the average preparationtime for the invoice.

5.3.3. Allocation of resources to the consolidated services

Consolidated services typify the operations of many third-party logistics providers (3PL), sinceeach consignor delivers its product to several consignees and, similarly, different consignors shareseveral consignees, which accordingly means that the fleet is used to deliver products of differentconsignors in the same journey or vice versa (Griful-Miquela 2001). Selecting the cost objects fora 3PL (or a road transport company) is determined according to either consignor-oriented (Griful-Miquela 2001) or consignee-oriented (Themido et al. 2000, Baykasoglu and Kaplanoglu 2008)approaches. A consignor-oriented approach means costs are allocated to the individual consignorwhile the consignee-oriented approach refers to the allocation of costs to different destinations ordistribution channels. In either case, there is an opportunity for consolidated services to impacton the cost allocation for various cost objects sharing the same resources in a journey. However,this topic is seldom examined in the extant ABC and TDABC literature. In TDABC models, thetime equation for transportation activity contains duration of journey time for a single destinationwhile in practice a journey regularly combines several destinations to utilise the full space inthe truck. Simply allocating the journey time to the individual destination may lead to the over-consumption of resources when summing transportation time for all destinations. Furthermore,this time allocation problem also exists for the empty backhauls. In principle, the time consumedin backhauls should be shared between the cost objects (destinations or distribution channels)involved in the same journey. These backhaul costs represent the joint costs inherent in thetransportation service. In practice, it is difficult to collect data on which destinations are supposedto bear the backhaul costs for individual trips since the data might not exist in the transactionrecords. Hence, common costs and joint costs for transportation activities remain a significantchallenge for TDABC model building in small road transport and logistics firms.

6. Conclusions

This paper reviews the implementation ofABC and TDABC in the transport and logistics activitiesand describes the development of TDABC in a small-sized road transport company in Thailand.It aims to manage the complex cost calculations inherent in transportation and logistics servicesas the result of the diversity of services offered. It supports the previous assertion that transportand logistics is a typical sector that can benefit from TDABC (Kaplan and Anderson 2004).The system is able to provide the cost details which are applicable to the service routes and todifferent destination types such as wholesalers, retailers and super stores. The TDABC modelreveals the loss-generating routes and identifies the cause of loss, and accordingly introduces theroad map for potential cost reduction. In addition, the system illustrates the utilisation of companyresources, and simultaneously provides the level of opportunity cost occurring when resourcesare underutilised. This benefit is made possible due to the available capacity cost rates and theunderutilised hours derived from the time models. The paper also provides evidence on howTDABC models can be built and maintained with normal spreadsheet programmes. This is dueto the fact that data requirements are less extensive for small-scale firms. TDABC has advantages

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over traditional ABC which works well in the limited setting in which it was initially applied,typically a single department, plant or location, but becomes difficult when rolling out on a largescale on an ongoing basis.

Despite the benefits, a number of difficulties are found during the development process. Asa small-scale operator, the information supplied for the model development is far from perfectand relies to a great extent on average numbers, as frequently found in the time estimation andtransaction drivers. To enhance the accuracy of the model, the developer should make clearfrom the start what kind of data need to be collected. In addition, improved data recording ofcurrent practices should be undertaken. It is not necessary to invest in state-of-the-art technology.Sometimes, manual records, such as a log book and time stamping machines, are good enough.This paper complements the previous literature by showing that TDABC is applicable in smalland medium businesses as well as in larger ones despite the difficulties.

Since this study represents only one case of a small road transport and logistics firm, itsconclusions cannot be generalised: the difficulties encountered when implementing the TDABCmodel might be experienced differently in firms operating in a different environment. For instance,the narrow scale of operations (represented by a few known regular routes) in the case companyreflects the strategic choice of the owner, who prefers to concentrate on particular customers.These well-defined markets reduce the complexity of the models and limit otherwise hard-to-solveproblems, such as the sharing of joint and common costs or the fact that routes may constantly bein need of rescheduling and optimisation as business needs rapidly change. Such limitations canbe considered as a challenge for future research in the field. Future research may also take intoconsideration the potential for using real-time data offered by GPS and RFID technology and itsimpact on enhancing the accuracy of time estimates.

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unlocking the potential of time-driven activity-based costing for small logistics companies

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