-b

As

Auckla

c Abu Dhabi University, UAE

a r t i c l e i n f o

Article history:

Received 26 January 2009

Accepted 12 August 2009Available online 18 August 2009

Keywords:

Supply chain management

Organisational factors

Activity-based costing

are trying to make better use of SCM by implementing a

boute in008;hadi,

1998; Kee, 2008; Qian and Ben-Arieh, 2008; Singer and

a complex costing system that assists managers in making

Contents lists available at ScienceDirect

journal homepage: www.e

Int. J. Productio

Int. J. Production Economics 127 (2010) 2382480925-5273/$ - see front matter & 2009 Elsevier B.V. All rights reserved.

doi:10.1016/j.ijpe.2009.08.004important strategic business decisions. They emphasise thatevery aspect of decision making process in SCM requires costdata. This highlights the signicance of the relationshipbetween ABC and SCM. Given the current intense global

Corresponding author. Tel.: +64 99235785; fax: +64 93737406,+64 93737444, +64 93737019.

E-mail address: d.askarany@auckland.ac.nz (D. Askarany).variety of different techniques such as just-in-time (JIT),total quality management (TQM), lean production (LP),

Donoso, 2008; Tornberg et al., 2002; Tsai et al., 2008).Integrating ABC and SCM, Lin et al. (2001) describe ABC asa key component of competitive strategy to enhanceorganisational productivity, performance and protability(Gunasekaran et al., 2004). Given the above, according toGunasekaran et al. (2004), managers in many industries

ABC can be considered as one the most talked atechniques for improving SCM and performancorganisations (Baykasoglu and Kaplanoglu, 2Ben-Arieh and Qian, 2003; Gunasekaran and Sar1. Introduction

Supply chain management (SCM) can be considered as

computer generated enterprise resource planningschedule (ERP), Kaizen and activity-based costing (ABC).Among recently developed techniques (such as above),a b s t r a c t

In todays intense global competition, supply chain management (SCM) is as a vital tool

for helping managers to improve productivity, protability and the performance of their

organisations. In doing so, SCM requires more accurate cost data regarding all activities

and processes within the organisations. Given the above, activity-based costing (ABC)

can signicantly contribute to global supply chain management as it is suggested to

full the above requirements by providing more accurate, detailed and up-to-date

information on all activities and processes in organisations.

Contributing to the SCM and ABC literature, current study rst identies different

types of improvements which ABC can offer to SCM and the performance of the

organisations, then it examines the extent of association between business size as well

as business industry (as organisational factors) affecting the adoption of ABC in New

Zealand (NZ) through using a survey questionnaire and targeting NZ qualied CIMA

members. To improve SCM and organisations performance by increasing the adoption

of ABC in organisations, one of the main implications of the ndings is that the adoption

of ABC in smaller rms needs more attention compared with the larger rms regardless

of their industries (manufacturing versus non-manufacturing rms). However, when the

decision is made to implement ABC, non-manufacturing rms (rather than manufactur-

ing rms) need more attention to proceed with a higher level of adoption of ABC.

& 2009 Elsevier B.V. All rights reserved.Supply chain management, activityorganisational factors

Davood Askarany a,, Hassan Yazdifar b, Saeeda Business School, Department of Accounting and Finance, The University ofb Shefeld University, UKased costing and

kary c

nd, Private Bag: 92019, New Zealand

lsevier.com/locate/ijpe

n Economics

and SCM, an accumulated body of literature have specied

D. Askarany et al. / Int. J. Production Economics 127 (2010) 238248 239a variety of contributions which ABC is providing to SCMin organisations such as: cost reduction, cost estimation,performance measurement, etc. (Baykasoglu andKaplanoglu, 2008; Charles and Hansen, 2008a, b; Hom-burg, 2005; Qian and Ben-Arieh, 2008; Satoglu et al., 2006;Thyssen et al., 2006). However, despite the vital role of ABCin improving the organisations performance and theirSCM, the adoption of ABC is not highly prevalent afteralmost 25 years since its introduction (Al-Omiri and Drury,2007b; Askarany and Smith, 2008; Askarany and Yazdifar,2007). Adopting the diffusion of innovation theory, anumber of studies have investigated the relationshipsbetween the adoption of ABC and a variety of contextualfactors. However, very few studies examined the adoptionof ABC as a process (e.g. a set of different adoption levels)and paid adequate attention into the detailed adoptionsteps of ABC (Brierley et al., 2006). Indeed, the adoption ofABC include performing a number of different activities(such as activity analysis, allocation of costs to cost pools,and allocation of cost pools to products/services), whilemost of the literature on SCM and ABC have looked at theABC adoption as one stage process (e.g. adoption versusnot adoption) and made no distinction between differentadoption levels. So, it is not clear if any particular stage/level of adoption of ABC need more attention (in order tofacilitate its diffusion in organisations).

Furthermore, though very few studies have dealt withthe relationship between adoption stages/levels of ABCand organisational factors (such as size and organisationalindustry), their ndings have been mixed and inconsistent(Al-Omiri and Drury, 2007b; Baird, 2007; Brown et al.,2004; Cohen et al., 2005; Innes and Mitchell, 1995; Libbyand Waterhouse, 1996).

Considering the contribution of ABC to SCM inorganisations, examining the extent of the relationshipbetween adoption stages/levels of ABC and organisationalfactors (such as organisational size organisational indus-try) could lead to the recognition of factors facilitating orhindering different adoption stages/levels of ABC andtherefore could result in improved organisational produc-tivity, performance and protability. In doing so, currentstudy examines the extent of the association betweenbusiness size as well as business industry and thediffusion of ABC (stages/levels) in New Zealand throughusing a survey questionnaire and targeting more orless similar respondents (qualied CIMA members).The remaining of this paper is organised as follows:Section 2 provides a background to the research questions.Section 3 discusses research method, Section 4 presentsour empirical results and Section 5 concludes the study.

2. Background

Contributing to the SCM and ABC literature, thissection rst highlights different types of improvementscompetition, they also believe that the extent of theimportance of cost data in SCMled as well as the integrationbetween ABC and SCM will increase in the near future.

Highlighting the extent of the integration between ABCwhich ABC can offer to SCM and the performance of theorganisations. Following the signicance of the integra-tions between SCM and ABC, the current section demon-strates the controversy on the extent of associationbetween business size as well as business industry (asorganisational factors) and the adoption of ABC. Given theabove, then it suggests relevant propositions which theirexaminations could lead to the recognition of factorsinuencing the adoption of ABC and therefore could resultin improved organisational productivity, performance andprotability by contributing to the higher levels of theadoption of ABC.

An accumulated body of the literature suggest that ABCcan contribute to SCM and organisational performancefrom many different perspectives (Baykasoglu andKaplanoglu, 2008; Charles and Hansen, 2008a, b;Homburg, 2005; Qian and Ben-Arieh, 2008; Satogluet al., 2006; Thyssen et al., 2006). For example, Baykasogluand Kaplanoglu (2008) suggest that ABC can improveorganisational performance as follows: helping organisa-tions to become more efcient and more effective;providing organisations with a clear picture of whereresources are being spent, customer value is being created,and money is being made or lost; offering organisations abetter alternative to volume-based product costing;identifying value-added activities and eliminating orreducing non-value added activities.

Supporting the above suggestions, Tsai et al. (2008)explain that ABC provides organisations with an under-standing of cause and effect relationship between costsand the demands for activities within a process leading tobetter organisational performance. They further empha-sise that traditional cost accounting can distort productcosts in advanced manufacturing environments especiallywhen overhead costs are a signicant portion of totalcosts of products or services. According to Tsai et al.(2008), ABC can improve the accuracy of processes andproducts cost data and obtain the highest long-termprot by exercising complete control over overheadresources in organisations.

Kee (2008) suggests ABC can be used as a tool fordecision making especially for product mix costing andpricing decisions. Further to the above advantages, Qianand Ben-Arieh (2008) consider ABC as a more accuratecost-estimation method. They argue that ABC can helpmanagers to become aware of original parameters thatcreate demands on indirect and support resources andtherefore can identify and remove non-value-addingactivities. According to Ben-Arieh and Qian (2003) andQian and Ben-Arieh (2008), the ABC approach hasdemonstrated to be more accurate than the traditionalcost estimation. Testing the validity of ABC cost estima-tion, Singer and Donoso (2008) examined the accuracy ofABC in terms of real indirect cost versus its forecast withABC and concluded that the accuracy of estimation ofcosts made by ABC was valid.

With regards to the current competitive environmentand product diversity, there should be no doubt thataccurate product-cost information is critical for decisionmakers in organisations. In line with the above argument,Charles and Hansen (2008b) recommend ABC as true

D. Askarany et al. / Int. J. Production Economics 127 (2010) 238248240product-cost assignments approach. Their ndings showthat ABC is a more accurate product-costing system thantraditional volume-based costing systems especially whenorganisations are facing higher product diversity. High-lighting the importance and the contribution of ABC tosupply chain management, Comelli et al. (2008) supportthe argument that ABC is the best costing modelespecially for diverse and complex manufacturing systemsbecause of its connections with supply chain manage-ment.

Supporting the above argument, the supply chainmanagement literature provides an accumulated body ofevidence regarding the integration between ABC and SCMand the types of contributions which ABC is able to offerto organisations performance, processes, productivity,protability, etc. According to the SCM literature, ABCcan improve organisational performance, productivity,and protability in organisations as follows: improvingorganisation process by providing decision support forconversion to the decentralised mini-storages (Satogluet al., 2006); costing services of the land transportationcompany (Baykasoglu and Kaplanoglu, 2008); facilitatingoptimal joint product mix decisions (Tsai et al., 2008);pricing, product mix, and capacity expansion decisions(Kee, 2008); offering cost-estimation model (Kingsmanand de Souza, 1997; Ozbayrak et al., 2004; Qian andBen-Arieh, 2008); providing more accurate product-costinformation and improving decision quality (Charles andHansen, 2008b); offering more accurate costing of holdinginventory (Berling, 2008); estimating cash ow created bysupply chain tactical production planning (Comelli et al.,2008); improving efciency by identifying and eliminat-ing areas of non-value added activity in supply chainprocesses (Whicker et al., 2006); offering supportingdecision-making concerning product modularity methodfor assessing the cost consequences of modularisation(Thyssen et al., 2006); designing and development ofactivities for production (Ben-Arieh and Qian, 2003;Tornberg et al., 2002); Protability modelling, enterprisemodelling and business process reengineering (Tatsiopoulosand Panayiotou, 2000); offering cost reduction(Andrade et al., 1999); improving simulation models(Spedding and Sun, 1999); identifying area of waste andnon-value- added activities, improving productivity,quality and effectiveness in manufacturing and perfor-mance measurement systems, improving competitiveposition of organisations, reducing costs and productiontime (Gunasekaran and Sarhadi, 1998); contributing to thedecision support for designers, production managers andmanufacturers (Senechal and Tahon, 1998); planning(Boons, 1998; Schneeweiss, 1998); improving performancemeasurement system (Kim et al., 1997); improvingthe quality of the products protability information(Pirttila and Sandstrom, 1996); and predicting the eco-nomic consequences of production and processes actions(Salafatinos, 1996).

However, despite the critical role of ABC in terms ofimproving the organisations performance and their SCM,the adoption of ABC is still relatively low (Al-Omiri andDrury, 2007b; Askarany and Smith, 2008; Askarany andYazdifar, 2007). For example, survey evidence suggeststhat the adoption rate for ABC by UK organisations is stillfairly low, being approximately 15% (Al-Omiri and Drury,2007a). The adoption of ABC in New Zealand is not muchhigher than the UK and follows a similar pattern (Williamet al., 2003). Conducting a comparative analysis, Cottonet al. (William et al., 2003) report an average of 20.3%adoption rate for ABC users (both in manufacturing andnon-manufacturing sectors) in New Zealand comparedwith a 17.5% adoption rate for the UK companies.However, they suggest that further adoption of ABC inthe future would receive less consideration in NZ than inthe UK. Except a few (Baird et al., 2004; Chenhall andLangeld-Smith, 1998; Langeld-Smith, 1997), most stu-dies have reported relatively low adoption rates for ABC inAustralia such as 10% (Warwick and Reeve, 1997), 12%(Booth and Giacobbe, 1997) and 28% (Askarany et al.,2007a).

Given the above, any investigation into the impact ofsuggested inuencing factors in the literature (such asorganisational size and organisational industry) on theadoption of ABC, would contributes to SCM as well as tothe performance of the organisations. That is why manystudies have investigated the extent of the relationshipsbetween the adoption of ABC and a variety of contextualfactors. However, very few studies examined the adoptionof ABC as a continuing process (e.g. a set of differentstages) and paid adequate attention into the adoptionstages of ABC (Al-Omiri and Drury, 2007a; Askarany,2006; Askarany et al., 2007b; Brierley et al., 2006). Indeed,the adoption of ABC includes performing a number ofdifferent activities (such as activity analysis, allocation ofcosts to cost pools, and allocation of cost pools toproducts/services), while most of the literature on SCMand ABC have looked at the ABC adoption as one stageprocess (e.g. adopted versus not adopted). Furthermore,very few studies deal with the relationship betweenadoption stages of ABC and organisational size andorganisational industry. Moreover, the ndings of suchstudies have been inconsistent and mixed (Al-Omiri andDrury, 2007b; Baird, 2007; Brown et al., 2004; Cohenet al., 2005; Innes and Mitchell, 1995; Libby and Water-house, 1996).

For example, while some studies suggest the larger thesizes of the rms the higher is the level of adoption of ABC(Al-Omiri and Drury, 2007b; Bjornenak, 1997; Innes andMitchell, 1995; Krumwiede, 1998), other studies suggestno relationship between business size and the extent ofadoption of ABC (Cohen et al., 2005; Gosselin, 1997; Libbyand Waterhouse, 1996). As with the business size, theliterature also shows some controversy regarding therelationship between organisational industry (manufac-turing versus non-manufacturing) and the extent of theadoption of ABC (Innes et al., 2000; Pierce, 2004). Forexample, while some studies report a higher adoption ratefor ABC users in non-manufacturing than in manufactur-ing organisations (Innes et al., 2000), other studiessuggest the opposite (Pierce, 2004).

Among the majority of contextual factors addressed inthe diffusion literature, size is one of the most contro-versial inuencing factor with suggested inconsistentimpact. For example, some authors argue that larger rms

D. Askarany et al. / Int. J. Production Economics 127 (2010) 238248 241have higher advantages over smaller rms specially interms of the ability to afford more resources to facilitatethe adoption of a new technique (Baird, 2007; Bjornenak,1997; Brown et al., 2004; Innes and Mitchell, 1995), whileothers argue that the adoption of a new technique insmaller rms is quicker than in larger rms (Acs andAuderetsch, 1988; Julien, 1993; Lefebvre and Lefebvre,1993; Riding, 1993) and list a number of advantages forsmaller rms as follows: less bureaucracy, greater motiva-tion, better survey of the entirety of the project, andgreater proximity to the market (Nooteboom, 1994).Supporting this argument, Julien (1993) argues that thekey factor in the continued existence of small rms lies intheir behaviours as being entrepreneurs and innovativeand also in their desires to be the leading adopters of newtechniques in the market. Such behaviours would helpsmaller rms to compete with larger rms, otherwiselarger rms may capture the markets and this could be animportant threat to the survival of small rms. Supportingthe above view, Shields and Young (1994) state that smallrms are increasingly gaining competitive advantagethrough innovative activity such as being the leadingadopters of new techniques. As smaller rms are expectedto compete with larger rms in the market, they wouldprobably need to be more adoptive to new techniquesthan their larger rivals (in order to improve their productsand services) otherwise they could fail.

However, the controversy regarding the impact ofbusiness size on the adoption of new techniques such asABC has been further complicated by the mixed results ofthe studies investigating the association between size andthe adoption of ABC in organisations (Al-Omiri and Drury,2007b; Baird, 2007; Baird et al., 2004; Booth andGiacobbe, 1998; Brown et al., 2004; Damanpour, 1992;Gosselin, 1997; Krumwiede, 1998; Libby and Waterhouse,1996; Pierce, 2004). For instance, Libby and Waterhouse(1996) nd no statistically signicant association betweensize and the adoption of ABC. Similarly, Gosselins (1997)and Cohen et al.s (2005) ndings suggest no statisticallysignicant association between size and the adoption ofABC. As with the above ndings, Baird (2007) also nds noassociation between business size and the adoption ofABC.

Despite the above, other studies suggest that lagerrms are more likely to adopt ABC than smaller rms(Al-Omiri and Drury, 2007b; Bjornenak, 1997; Innes andMitchell, 1995; Krumwiede, 1998; Malmi, 1999; Pierce,2004). For example, Al-Omiri and Drury (2007b) nd asignicant association between business size and theadoption of ABC in UK organisations. Innes et al. (2000)nd that the adoption of ABC is signicantly higher(26.3%) in larger organisations than in smaller organisa-tions (15.8%). Pierces (2004) ndings also conrm thatthe adoption of ABC is signicantly higher among largerorganisations than smaller rms. Similarly, Brown et al.(2004) nd a signicant positive association (po0.05level) between organisational size and the adoption ofABC.

Addressing the above controversy, Baird et al. (2004)nd that organisational size is associated with the rstand the second levels (activity analysisAA and activitycost analysisACA) of ABC adoption but not with thethird level (cost allocation) of ABC. The ndings of Bairdet al. (2004) may suggest that some of the reportedvariations (mixed results regarding the degree of associa-tion between business size and the adoption of ABC) inthe literature could be related to the application ofdifferent adoption processes (e.g. the levels of adoptionin some studies and the stages of adoption in otherstudies). To further clarify the distinction between thestages and the levels of adoption of ABC, it is importantto note that some studies refer to ABC as one wholeprocess (Al-Omiri and Drury, 2007a; Anderson, 1995;Pierce, 2004), while others (Baird et al., 2004; David et al.,2004; Gosselin, 1997; Krumwiede, 1998) have used it torefer to different levels of ABC adoption.

However, much of the studies which have looked atABC as one whole process made some distinction betweendifferent steps/levels of adoption process of ABC. Whenlooking at ABC as one whole process, the most commonstages used to examine the adoption of ABC are as follows:no consideration/decision is given to the introduction,decided not to adopt or decided to reject, someconsideration is given to the introduction of ABC in thefuture, implemented on a trial basis and nally,implemented and accepted (Al-Omiri and Drury, 2007a;Askarany et al., 2007a; Pierce, 2004). Some other studieshave extended these stages up to 10 stages (Brown et al.,2004; Krumwiede, 1998).

Looking at ABC as a set of different processes, otherstudies have categorised the adoption of ABC intodifferent levels as follows: activity analysis (AA) whichis the rst stage for identifying the activities andprocedures performed to make the nal products/services; activity cost Analysis (ACA) which is the secondstage for identifying the costs of each activity and costdrivers and nally, activity-based costing (ABC) which isthe third stage for tracing costs of activities to products/services (Baird, 2007; Baird et al., 2004; Gosselin, 1997).Studies which have investigated the association betweenorganisational size and the adoption of ABC either usedthe stages of adoption process or the levels of adoptionprocess. However, no study has been reported to considerboth the steps/stages and the levels of adoption of ABCat the same time. This study is trying to overcome theabove issue by using both the stages and the levels ofadoption of ABC at the same time. Comparing theadoption of ABC in New Zealand and the UK, Cottonet al. (2003a) nd that the adoption of ABC received lessconsideration in NZ than in the UK and at the same timethey nd that NZ rms tend to be signicantly smallerthan UK rms. Given the above, they suggest that aninvestigation into the association between size and theadoption of ABC is likely to be fruitful area for futureresearch. This suggestion further motivates the conduct ofthe current study.

Addressing the above controversy (in terms of positive,negative and neutral relationship between organisationalsize and the adoption of ABC), it could provide us withsome clues to make a better proposition if we take intoconsideration the factors addressed by the diffusion ofinnovation theory (Rogers, 1995). The ABC literature

online version of the questionnaire.

D. Askarany et al. / Int. J. Production Economics 127 (2010) 238248242suggests that the major factors hindering or constrainingthe diffusion of ABC in organisations are related to the lackof resources (Clarke et al., 1999; Gunasekaran et al., 1999),high costs, technical and complexity of ABC (Al-Omiri andDrury, 2007a; Cohen et al., 2005) which larger rms aremore capable in overcoming such barriers. So, given theabove we may suggest the following proposition: Largerrms are more likely to adopt ABC than smaller rms.

Referring to size as a variable in this study, we shouldnote that different proxies such as total sales, annualturnover, and number of employees could be used tomeasure organisational size. For example, Krumwiede(1998) and Al-Omiri and Drury (2007b) use the level ofsales revenue to measure the size of organisations, whileother studies use the number of employees for suchpurpose (Baird, 2007; Baird et al., 2004; Gosselin, 1997).However, using the number of employees as a proxy fororganisational size is the most popular method used inthe literature (Gosselin, 1997). Given the above, we use thenumber of employees as a proxy for organisational size inthis study.

As with organisational size, the ABC literature alsoshows some controversy on the level of associationbetween organisational industry and the adoption ofABC. For example, investigating the adoption of ABC,Innes et al. (Innes and Mitchell, 1995) nd a higher (22%)adoption rate for non-manufacturing and a lower (15.5%)adoption rate for manufacturing organisations in the UK.In another study (ve years later) Innes et al. (2000)similarly nd a higher adoption rate for ABC users in non-manufacturing than in manufacturing organisations in theUK. As with the above Al-Omiri and Drury (2007b) nd asignicant association (po0.05) between non-manufac-turing rms (e.g. nancial sectors and service sectors) andthe adoption of ABC in the UK. These ndings supportKaplan and Coopers (1998) suggestion that service rmsare more suitable than manufacturing rms for theadoption of ABC as most of their costs are xed. However,despite the above ndings, there is some evidence whichsuggests that the adoption of ABC is higher in manufac-turing organisations than in non-manufacturing organisa-tions (Pierce, 2004). As with the above controversy,the ABC literature also support further studies into therelationship between organisational industry and theadoption of ABC (Cotton et al., 2003b).

Looking at the main benets/advantages of ABCaddressed in the literature could provide us with someclues to make a better proposition in terms of theexpected relationship between the adoption of ABC andorganisational industry. According to the ABC literature,the main benet/advantage of ABC over traditional costaccounting techniques is related to its ability in providingmore accurate cost information especially in terms of costallocation for products which consume different amountof overhead costs at different levels of cost hierarchiessuch as unit level, batch level, product level and facilitylevel (Drury, 2004; Kaplan and Anderson, 2007; Kaplan,1986). The implementation of these cost hierarchies aremore in line with complex manufacturing products ratherthan service industry. So, given the above we may suggestthe following proposition: Manufacturing organisationsExamining the stages (adoption versus non-adoption)of adoption of ABC as one whole process (Al-Omiri andDrury, 2007a; Anderson, 1995; Pierce, 2004), respondentswere asked to indicate their organisations attitudestowards ABC adoption by using a 5-point Likert-typescale (Abdel-Kader and Luther, 2006; Innes et al., 2000) asfollows: with anchors of (1) discussions have not takenplace regarding the introduction of ABC; (2) a decision hasbeen taken not to introduce ABC; (3) some considerationis being given to the introduction of ABC in the future; (4)ABC has been introduced on a trial basis; and (5) ABC hasbeen implemented and accepted.

In order to measure the levels of adoption of ABC(after ABC is implemented), Gosselins levels of ABCadoption (1997) which was also implemented by Baird etal. (2004) and Baird (2007) was used and the adopters ofABC were asked to identify the level of adoption of ABC intheir organisations as follows: activity analysisAA(identication of activities and procedures performed intheir organisations to make the nal products/services);are more likely to adopt ABC than non-manufacturingorganisations.

So, given the above and adopting the diffusion ofinnovation theory, this study is aiming to examine thelevels of associations between organisational size as wellas organisational industry and the adoption of ABC (bothin terms of the stages and the levels of adoption) in NewZealand by using a consistent proxy (number of employ-ees) and targeting similar respondents (qualied CIMAmembers who are working in a managerial accountingposition in organisations) in the same period (2007).Considering the scope of the integration between ABC andSCM (demonstrated earlier in this section), examining theextent of the relationship between the adoption of ABCand organisational factors (both the organisational sizeand the organisational industry) could lead to a higherlevel of adoption of ABC and therefore may result inimproved organisational productivity, performance andprotability.

3. Method

A survey questionnaire was mailed to almost all (366)members of Chartered Institute of Management accoun-tants (CIMA) in New Zealand. CIMA is a professionalmanagement accounting body with over 155,000 mem-bers and students in 158 countries. Given the levels ofrequirements for becoming a CIMA qualied, it can beargued that CIMA professionals are equipped withnecessary skills and knowledge to make better strategicdecisions for organisations. This makes each CIMAmember a suitable candidate for current study whichfocuses on the adoption of management accountingtechniques in organisations.

Hard copies of the questionnaires were sent to alltargeted populations followed by a general announcementon CIMA website (in three weeks time) encouraging thoseCIMA members who had received the hard copies of thequestionnaires but did not complete them to ll up an

Activity Cost Analysis-ACA (identication of cost driversand allocation of costs to cost pools; and Activity-BasedCostingABC (allocation of costs of activities to products/services).

In order to measure the sizes of organisations,respondents were asked to record the number of employ-ees in their organisations. Although there are a variety offactors such as annual sales, total assets, total revenue, networth of rms and number of employees which could beused to dene rm size, the number of employees isconsidered to be the most frequently used proxy formeasuring the size of organisations (Gosselin, 1997). Aschanges in factors such as annual sales, total revenue, totalassets, and net worth of rms occur more frequently thanchanges in the number of employees each year, measuringrms sizes based on such volatile factors may result inchanging the classication of rms sizes every year.

similar information gathered by the surveys, and througha comparison between early and late responses. The

these responses, suggesting that non-response bias wouldnot inuence the outcomes.

4.1. Business size and the stage of adoption of ABC

With regards to the suggested classications (in termsof number of employees) for measuring business size inthe literature (Berryman, 1993; McMahon et al., 1993;Nooteboom, 1994; Watson and Everett, 1993), this studycategorises organisations into following six groups asfollows: (1) up to 25 employees; (2) from 26 up to 50employees; (3) from 51 up to 100; (4) from 101 up to 200employees; (5) from 201 up to 500 employees; and (6)more than 500 employees.

According to Vincent (2005), chi-square is one the beststatistics for the analysis of categorical (ordinal) and

Zea

Some

consi

being

the in

of th

0

0

0

0

6

10

16

Sig. (

0.000

D. Askarany et al. / Int. J. Production Economics 127 (2010) 238248 243former showed responses to be representative, the lattershowed that there was no perceived difference between

Table 1Relationship between business size the stages of adoption of ABC in New

Number of employees Discussions

have not taken

place regarding

the introduction

of ABC

A decision has

been taken not

to introduce

this practice

r25 Employees 24 826 Up to 50 employees 6 0

51 Up to 100 employees 6 4

101 Up to 200 employees 8 2

201 Up to 500 employees 6 0

More than 500 employees 8 6

Total 58 20

Value df

Pearson chi-square 55.134 20Therefore, this paper uses the number of employees tomeasure the sizes of organisations.

4. Results and discussion

The nal number of useable responses (both hardcopies and online replies) was 142 completed question-naires plus 10 not-completed or not delivered. The nalcompleted questionnaires have provided the authors witha satisfactory response rate of 39.5%. According toKrumwiede (1998), the normal response rates for thesekind of surveys is approximately 20% though there aremany published surveys with lower response rates such as12.5% (Brown et al., 2004) or 19.6% (Al-Omiri and Drury,2007a).

Non-response bias was examined both by using theaggregated data provided by CIMA (such as total numberof CIMA members working in manufacturing and non-manufacturing organisations, the average length of ex-periences of CIMA members and their average ages asqualied CIMA members) and comparing them withnominal data. Given the nature of data in this study(categorised in terms of the levels and the stages ofadoption, we would consider our data as categoricalrather than interval and ratio data.

Table 1 presents the detailed relationship betweenbusiness size and the stages of adoption of ABC in NewZealand. According to the performed statistical tests, thereis a signicant association between business size and thestages (adoption versus non-adoption) of adoption ofABC in New Zealand (signicant at 0.000 level based onPearson chi-square). The ndings suggest that the adop-tion of ABC in larger rms is higher than smaller rms inNew Zealand. So, we may argue that the ndings aresupporting the discussion that the larger the size of therms the higher is the level of adoption of ABC (Al-Omiriand Drury, 2007b; Bjornenak, 1997; Innes and Mitchell,1995; Krumwiede, 1998). The ndings are in line with thestated proposition in this paper and imply that theadoption of ABC in smaller rms need more attention ifwe want to improve the SCM and the performance of theorganisations through higher levels of adoption of ABC.

4.2. Business size and the levels of adoption of ABC

As with the stages of adoption (looking at ABC as onewhole process), this study examines the relationship

land.

deration is

given to

troduction

is practice

This practice

has been

introduced on a

trial basis

This practice

has been

implemented

and accepted

Total

0 6 38

0 4 10

0 0 10

2 4 16

0 2 14

4 10 38

6 26 126

2-sided)

between business size and the levels of adoption of ABC.The main purpose of this section is to investigate theimpact of business size on the levels of adoption of ABCafter ABC is implemented.

Despite the stages of adoption, Table 2 presents nosignicant association between business size and thelevels of adoptions of ABC in New Zealand. Given thatthe levels of adopting only applies to ABC adopters, thending suggest that there is no signicant differencebetween small and large rms in terms of the levels ofadoption of ABC in New Zealand after ABC is implemen-ted. In other words, the decision to proceed from one levelof adoption (e.g. AA or ACA) to a higher level (e.g. ABC) inNew Zealand is not signicantly associated with businesssize.

To summarise the above statistical tests, the ndings ofcurrent study support our stated proposition that largerrms are more likely to adopt ABC than smaller rms.However, when the adoption decision was made, there isno signicant difference between larger rms and smallerrms in terms of proceeding towards a higher level ofadoption of ABC (e.g. from activity analysis level toallocation of costs to products level).

4.3. Organisational industry and the stage of adoption of

ABC

As with organisational size, this paper also examinesthe level of the association between organisational

industry and the stages as well as the levels of adoptionof ABC. Contributing to the literature, the ndings areexpected to clarify whether the extent of adoption of ABCis higher among manufacturing rms (Pierce, 2004) oramong non-manufacturing rms (Al-Omiri and Drury,2007b; Innes et al., 2000).

According to Table 3, out of 142 useable responses(responses to organisational industry and adoption of ABCquestions) there are 22 manufacturing and 120 non-manufacturing rms in New Zealand. However, thendings show that the level of association betweenorganisational industry and the stages of adoptions ofABC in New Zealand is not statistically signicant. Despitethe signicant inuence of business size on the adoptionof ABC in New Zealand, the ndings suggest thatthere is no signicant difference between manufacturingand non-manufacturing organisations in New Zealand interms of the adoption of ABC (adoption versus non-adoption), suggesting that organisational industry is not adetermining factor for the adoption of ABC in NewZealand.

4.4. Organisational industry and the levels of adoption of

ABC

As with the stages of adoption, this paper examinesthe relationship between organisational industry andthe levels of adoption of ABC. The main purpose ofthis section is to investigate how manufacturing and

Zeal

catio

ls (AC

of A

Some

consi

being

the in

of th

2

16

18

Sig. (

0.695

D. Askarany et al. / Int. J. Production Economics 127 (2010) 238248244Table 2Relationship between business size the levels of adoption of ABC in New

Number of employees Activity analysis

(AA)

Allo

poo

r25 Employees 2 026 Up to 50 employees 0 2

101 Up to 200 employees 0 2

201 Up to 500 employees 0 4

More than 500 employees 4 8

Total 6 16

Value df

Pearson chi-square 8.277 8

Table 3Relationship between organisational industry and the stages of adoption

Number of employees Discussions

have not taken

place regarding

the introduction

of ABC

A decision has

been taken not

to introduce

this practice

Manufacturing organisations 12 4

Service organisations 52 18

Total 64 22

Value df

Pearson chi-square 2.223 4and.

n of costs to cost

A)

Allocation of cost

pools to products/

services (ABC)

Total

4 6

2 4

4 6

4 8

10 22

24 46

Sig. (2-sided)

0.407

BC in New Zealand.

deration is

given to

troduction

is practice

This practice

has been

introduced on a

trial basis

This practice

has been

implemented

and accepted

Total

0 4 22

6 28 120

6 32 142

2-sided)

of AB

catio

ls (AC

D. Askarany et al. / Int. J. Production Economics 127 (2010) 238248 245non-manufacturing organisations proceed with the higherlevels of adoption of ABC after they decide to implementthe technique. In other words, this section aims toexamine whether there is (or not) any signicantdifferences in terms of the levels of adoption of ABCbetween manufacturing or non-manufacturing organisa-tions after they decided to adopt the technique.

According to Table 4, the ndings indicate that theextent of association between organisational industry andthe levels of adoption of ABC in New Zealand isstatistically signicant (signicant at 0.015 based onPearson chi-square). Manufacturing rms are more likelyto proceed with a higher level of adoption of ABC thannon-manufacturing rms. So, we may suggest that being amanufacturing or non-manufacturing organisation in NewZealand is an important factor which could inuence thelevels of adoption of ABC in organisations after ABC isimplemented. This also implies that non-manufacturing(compared with manufacturing) organisations are morelikely to use ABC for managing their activities rather thanfor costing purposes.

As with the relationship between business size and theadoption of ABC, we need to take into consideration thatthe ndings are referring to the extent of the relationshipbetween business industry and two different factors: (a)the decision to adopt ABC (adoption versus not adoption)which are referred to as the stages of adoption of ABC inthis study and (b) the levels of adoption of ABC (after ABCis implemented) which are referred to as the levels ofadoption of ABC in this study. In terms of the rst factor(adoption versus non-adoption), the ndings of currentstudy support neither the suggestions of advocatorsof a higher adoption rate of ABC for non-manufacturing(e.g. Al-Omiri and Drury, 2007b; Innes and Mitchell, 1995;Kaplan and Cooper, 1998) nor the suggestions of advoca-

Table 4Relationship between organisational industry and the levels of adoption

Number of employees Activity analysis

(AA)

Allo

poo

Manufacturing organisations 0 0

Service organisations 6 24

Total 6 24

Value df

Pearson chi-square 8.438 2tors of a higher adoption rate of ABC for manufacturingorganisations (Pierce, 2004). Rejecting our secondstated proposition, the ndings of current study suggeststhat the decision to adopt (or not adopt) ABC isequally important for both manufacturing and non-manufacturing organisations. However, in terms ofthe second factor (the levels of adoption of ABC), thendings of current study suggest that after the ABC isimplemented, manufacturing (compared with non-man-ufacturing) organisations are more likely to proceed witha higher level of adoption of ABC (e.g. from activityanalysis level to allocation of costs to products level)(Table 4).5. Conclusions

Contributing to the SCM and ABC literature, the currentstudy highlights the integration between SCM and ABC interms of addressing a variety of different improvementswhich the adoption of ABC can offer to SCM andorganisational performance, processes, productivity, andprotability as follows: helping organisations to becomemore efcient and more effective; providing organisationswith a clear picture of where resources are being spent,customer value is being created, and money is being madeor lost; offering organisations a better alternative tovolume-based product costing; identifying value-addedactivities and eliminating or reducing non-value addedactivities; providing organisations with an understandingof cause and effect relationship between costs and thedemands for activities within a process leading to betterorganisational performance; improving the accuracy ofprocesses and products cost data and obtaining thehighest long-term prot by exercising complete controlover overhead resources in organisations; improvingorganisation process by providing decision support forconversion to the decentralised mini-storages; costingservices of the land transportation company; facilitatingoptimal joint product mix decisions; pricing product mixand capacity expansion decisions; offering cost-estima-tion model; providing more accurate product-cost in-formation and improving decision quality; offering moreaccurate costing of holding inventory; estimating cashow created by supply chain tactical production planning;improving efciency by identifying and eliminating areasof non-value added activity in supply chain processes;offering supporting decision-making concerning productmodularity method for assessing the cost consequences ofmodularisation; designing and development of activities

C in New Zealand.

n of costs to cost

A)

Allocation of cost

pools to products/

services (ABC)

Total

6 6

18 48

24 54

Sig. (2-sided)

0.015for production; Protability modelling, Enterprise model-ling and Business Process Reengineering; offering costreduction; improving simulation models; identifying areaof waste and non-value- added activities, improvingproductivity, quality and effectiveness in manufacturingand performance measurement systems, improving com-petitive position of organisations, reducing costs andproduction time; contributing to the decision supportfor designers, production managers and manufacturers;planning; improving performance measurement system;improving the quality of the products protabilityinformation; predicting the economic consequences ofproduction and processes actions.

Journal of Production Economics 116, 308324.Ben-Arieh, D., Qian, L., 2003. Activity-based cost management for design

and development stage. International Journal of Production Econom-ics 83, 169183.

D. Askarany et al. / Int. J. Production Economics 127 (2010) 238248246Given the above (demonstrating the vital role of ABC inimproving the organisations performance and their SCM),examining the relationship between the adoption of ABCand organisational factors (both the organisational sizeand the organisational industry) can be considered asanother contribution of the current study. Because such anexamination could improve the adoption of ABC byshedding some light on the impact of organisational sizeand the organisational industry on the adoption of ABCand therefore may result in improved organisationalproductivity, performance and protability.

In line with the above consideration, the ndings ofcurrent study support our rst stated proposition thatlarger rms are more likely to adopt ABC than smallerrms. However, when the adoption decision was made,there is no signicant difference between larger rms andsmaller rms in terms of proceeding towards a higherlevel of adoption of ABC (e.g. from activity analysis level toallocation of costs to products level). To improve SCM andorganisations performance through the higher levels ofadoption of ABC in organisations, one of the mainimplications of the ndings is that the adoption of ABCin smaller rms needs more attention than larger rmsregardless of their industries (manufacturing versus non-manufacturing rms). However, when the decision ismade to implement ABC, non-manufacturing rms (ratherthan manufacturing rms) need more attention toproceed with a higher level of adoption of ABC.

In line with the contribution towards the examining ofthe extent of the relationship between the adoption ofABC and organisational industry, the ndings of currentstudy reject our second stated proposition and suggestthat the decision to adopt (or not adopt) ABC is equallyimportant for both manufacturing and non-manufactur-ing organisations. However, in terms of the the levels ofthe adoption of ABC, the ndings of current study suggestthat after the ABC is implemented, manufacturing (com-pared with non-manufacturing) organisations are morelikely to proceed with a higher level of adoption of ABC(e.g. from activity analysis level to allocation of costs toproducts level). This also implies that non-manufacturing(compared with manufacturing) organisations are morelikely to use ABC for managing their activities rather thanfor costing purposes. Further research is recommended toinvestigate the extent of relationship between the adop-tion stages and levels of ABC and other contextual factorssuch as complexity of the system, relative advantage ofthe technique, organisational culture, organisationalstructure, etc.

Given the selected approach in the current study(targeting similar respondents and examining the extentof adoption of ABC both in terms of the stages ofadoption and the levels of adoption), it could be claimedthat the ndings of current study benets from havingless limitations compared with previous studies. However,normal limitations surrounding survey studies couldapply to the ndings of this study though the authorshave had the opportunity to further clarify any ambiguityon provided information through follow-up interviewsand have practiced this option when deemed necessary.Furthermore, although statistical tests were performed toBerling, P., 2008. Holding cost determination: an activity-based costapproach. International Journal of Production Economics 112,829840.

Berryman, B.J.E., 1993. Small business failure and bankruptcy: whatprogress has been made in the decade? Small Enterprise ResearchThe Journal of SEAANZ 2, 527.

Bjornenak, T., 1997. Diffusion and accounting: the case of ABC in Norway.Management Accounting Research 8, 317.

Boons, A.N.A.M., 1998. Product costing for complex manufacturingsystems. International Journal of Production Economics 55, 241255.look for evidence of non-response bias, there is no way todirectly test whether the non-respondents are system-atically different than the respondents. It should also benoted that as all respondents are members of the CIMA,they may have a bias toward reporting ABC adoption orimplementation. Thus, generalising the results of thisstudy should be done with caution.

Acknowledgements

The authors are grateful to the University of Auckland,Research Foundation of the Chartered Institute of Manage-ment Accountants (CIMA) of the UK and the University ofShefeld for funding and facilitating the research onwhich this paper is based.

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D. Askarany et al. / Int. J. Production Economics 127 (2010) 238248248

Supply chain management, activity-based costing and organisational factorsIntroductionBackgroundMethodResults and discussionBusiness size and the stage of adoption of ABCBusiness size and the levels of adoption of ABCOrganisational industry and the stage of adoption of ABCOrganisational industry and the levels of adoption of ABC

ConclusionsAcknowledgementsReferences