Lagging Effects of the Use of Activity-Based Costing on the Financial Performance of Small Firms

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Lagging Effects of the Use of Activity-Based Costing on the Financial Performance of

Small Firms* jsbm_364 498..523

by Sinikka Jänkälä and Hanna Silvola

This paper contributes to the earlier small business literature by investigating the lagging effects of the use of activity-based costing (ABC) on small firms’ performance.

Moreover, we examine if the small firms’ past financial performance drives the adoption of ABC and explore whether the extent of ABC use leads, in turn, toimprovements in firms’ financial performance in the immediate future. In sum, the

survey results indicate that small firms with adequate financial resources as well as firms experiencing declining growth tend to use ABC and such use facilitates their subsequent growth and profitability. Small firms seem to benefit from using ABC.

Introduction Activity-based costing (ABC) has often

been promoted as an advanced systemthat is able to identify relevant costs andrevenues for products and services moreaccurately than traditional cost account-ing systems, helps to achieve competitiveadvantage, and finally improves financial

performance of an organization (e.g.,Kaplan and Cooper 1998). However, theearlier literature has provided limitedempirical evidence on the effect of ABCusage on the firm’s financial perfor-mance, even though ABC has been oneof the most intensively explored topics inthe recent decades (Baird, Harrison, andReeve 2004; Banker, Bardhan, and Chen

*We are grateful for the constructive comments and suggestions of Alnoor Bhimani, RobertH. Chenhall, Erkki K. Laitinen, Hélène Löning, Sally Widener, and the anonymous reviewers. We also gratefully acknowledge the comments provided by the participants at the 6th Confer-ence on New Directions in Management Accounting 2008, Brussels, Belgium and the AnnualCongress of the European Accounting Association 2007, Lisbon, Portugal.

Sinikka Jänkälä is a principal lecturer of accounting at Kemi-Tornio University of AppliedSciences, Finland.

Hanna Silvola is an assistant professor at Aalto University School of Economics, Finland. Address correspondence to: S. Jänkälä, Department of Business Administration, Kemi-Tornio

University of Applied Sciences, Tietokatu 1, FI-94600 Kemi, Finland. Tel: +358 40 538 0760;Fax: +358 16 251 123. E-mail: [email protected].

Journal of Small Business Management 2012 50(3), pp. 498–523

JOURNAL OF SMALL BUSINESS MANAGEMENT498



2008; Cagwin and Bouwman 2002; alsoGosselin 2007, for a review). Particularly,the empirical research on the use of ABCand its influence in small firms seems tobe very limited so far (see Gosselin2007).

In this study, we aim to contribute to

the existing literature investigating theobvious gap on the lagging financial per-formance effects of the use of ABC in thesmall business context. More specifically,

we investigate, if the past financial per-formance of small sustaining andgrowing firms drives the extent to which

ABC is used and explore, whether theuse of ABC relates to a small firm’s sub-sequent financial performance. It has

been stated that ABC might be very useful for small firms, too, providingbenefits for their cost-efficiency,decision-making, and performance(Baxendale 2001; Gunasekaran, Marri,and Grieve 1999; Hicks 1999; Kaplan andCooper 1998; Roztocki et al. 2004).

The data of the study cover the survey responses of 154 small sustaining andgrowing Finnish firms and their statutory financial statements over a total of five

years: the financial performance mea-sures of growth (measured by the growthin net sales) and profitability (measuredby the return on investments [ROI]) arecalculated for the past two years beforethe survey, the year of the survey as wellas for the following two years after thesurvey. Such a statutory approach to

firms’ success in competitiveness in themarket and profitability in terms of finan-cial performance measurement has beenlimited in earlier studies, also in thelarger firm context (see, e.g., Cagwin andBouwman 2002). This is likely due to thefact that, although the financial perfor-mance measures of larger companies areusually publicly available, many studiesare, however, done at the subunit level

without access to statutory financial mea-sures of the subunit. Financial informa-tion on smaller firms is not often evenincluded in the databases publicly avail-

able. Thus, in this study, the use of archival financial data provides rather anexceptional approach to examine thelinkages between the use of ABC andfinancial performance in small firms.

We divide the remainder of this paperinto four sections. A literature review

with theoretical discussions of the pro-posed linkages, and the development of a path model including hypotheses arepresented in the next section. The thirdsection describes the research method of the study. The results of the study arepresented in the fourth section. Finally,the discussions of the findings, conclu-sions as well as limitations and sugges-tions for further research are provided.

Theoretical Development Use of ABC in small firms

ABC as a cost accounting practice isrelated to the strategic dimensions of company development and consideredas a part of so-called strategic cost man-agement (Shank and Govindarajan 1993,1995). The adoption of ABC is a strategicdecision, as it has been claimed torequire considerable resource commit-ment and has the potential to influencethe strategic direction and performanceof the organization (Kaplan 1994; Shankand Govindarajan 1995). In practice,

ABC is a technique that has been intro-duced as an advanced cost accountingsystem, helping firms to make more effi-cient use of their resources and produce

critical decision-making information,thereby assisting firms to achieve a bettercost-efficiency, competitiveness, andoverall performance in their businessactivities (Gosselin 2007; Kaplan andCooper 1998).

The previous literature has typically argued that small firms do not use stra-tegic and advanced managementaccounting systems because of their

simple organizational structure and lackof resources (Anthony and Govindarajan2001; Chenhall 2003; Laitinen 2001a;Mitchell and Reid 2000; Simons 2000;

JÄNKÄLÄ AND SILVOLA 499



also McMahon 2001). Furthermore, theempirical ABC research has focusedmainly on large companies showing thatfirm size drives the adoption of ABC(e.g., Al-Omiri and Drury 2007; Baird,Harrison, and Reeve 2004). It has beenreported that larger firm size means

more resources needed to experiment with innovations like ABC (e.g., Chenhall2003).

On the other hand, recent literaturealso shows that the use of ABC is relatedto the managerial needs of the organiza-tional life cycle stages rather than firmsize only (Kallunki and Silvola 2008).Even though all firms may not growlarger as they grow older, managerial

needs and organizational developmentmay still involve firms in more advancedmanagement control systems and tech-niques such as ABC. Thus, ABC may alsobe used by small firms, if their manage-rial and organizational needs so require.

The recent organizational life cycle litera-ture illustrates the importance of the roleof accounting practices in small-sizedgrowth firms showing that initialaccounting systems provide a base forfirms’ future development (Davila andFoster 2005; Davila, Foster, and Li 2009;Moores and Yuen 2001; Sandino 2007).Furthermore, in the literature discussingthe applicability of ABC to the smallbusiness context, it has been suggestedthat ABC system might also be very suit-able for small firms, providing benefits

for their cost-efficiency and decision-making in pursuing competitive advan-tages as well as improved performance(Baxendale 2001; Gunasekaran, Marri,and Grieve 1999; Hicks 1999; Kaplan andNorton 2001; Roztocki et al. 2004; seealso Sandino 2007).

The debate in the small business lit-erature (e.g., Penrose 1959; Storey 1994)is also in line with the possible adoption

and use of ABC in small firms in statingthat the smaller firm size and simplerorganizational structure make these firmsmore flexible than large organizations in

their ability to change and introduce newpractices, too. However, following the

ABC literature (e.g., Baird, Harrison, andReeve 2004; Gosselin 2007), one may assume that smaller firms, being lessbureaucratic, may adopt more of theearlier levels of ABC (like activity analy-

sis and activity cost analysis) than thefinal level of ABC.

Furthermore, small firms haverecently experienced the same generalenvironmental changes of vigorous glo-balization, intensifying competition, andtechnological developments as theirlarger counterparts. Thus, these changesin business environments have also very likely affected the operations and struc-

tures of smaller firms and probably alsoimpacted on the design and use of theirmanagement control systems in strivingfor better cost-efficiency and competi-tiveness (see discussions in Chenhall2003). For example, Gumbus and Lussier(2006) report in their case study thatsmall to medium-sized firms use and canalso benefit from a balanced scorecardapproach in their strategic management.Respectively, the recent global develop-ment may also have raised a need for astrategic cost management system suchas ABC in small firms operating in anunpredictable and unstable environment.In fact, the empirical findings of Laitinen(2001a) in the area of managementaccounting support the view providingsome evidence on how the hard pressure

of competition enhances the willingnessof small, high technology firms to changetheir management accounting systemsinto more advanced control systemsincluding cost accounting.

Besides these previous, recent devel-opments in information technology andits usage as well as the extensive infor-mation on ABC provided during the last20 years may have open new options

also for small firms to develop their man-agement accounting practices to adapt tochallenges and threats faced in businessenvironments (see, e.g., discussions by




Bhimani et al. 2007; Chenhall 2003).First, the overwhelming emergence of information technology, like the Internetas well as the e-business software andrelated application services provided andpromoted, have been opening up new

virtual management accounting options

for flexible small firms for a long time,too (see also Riemenschneider andMykytyn 2000; Shields 1997). Second,the marketing of new managementaccounting approaches as well as mana-gerial imitation may be remarkable moti-

vational factors in the adoption of newmanagerial practices such as ABC amongsmall firms. Third, a lot of information on

ABC is also easily accessible in numerous

sources that may have encouraged alsosmall firms to adopt the practice. Overall,the adoption rates of ABC seem to berelatively higher today than in the early 1990s.1 Taking into account all the view-points previously, it could be expectedthat also small firms may have adoptedand implemented ABC.

Influence of Past FinancialPerformance on the Extent of ABC Use

The core ABC literature suggests thatthe adoption of ABC assists firms in theirdecision-making to achieve better perfor-mance in the organization (Cooper 1988;Kaplan 1994; Kaplan and Cooper 1998).

The information elicited through ABC isstated to be especially beneficial to firms

facing diminishing financial perfor-mance. Practically, this may mean thatthe firms have lost their customers andmarket shares under the pressure of competition, for example, resulting fromoverpricing their products or services(Shank and Govindarajan 1993). A moreeffective allocation of resources, better

decision-making, for example, in “makeor buy” situations and greater competi-tive advantage are potential outcomes of increased use of ABC in firms (Kaplanand Cooper 1998). Respective argumentshave also been presented regarding theoutcomes of ABC use in small firms (Bax-

endale 2001; Gunasekaran, Marri, andGrieve 1999; Hicks 1999; Kaplan andNorton 2001; Roztocki et al. 2004). Thus,such potential benefits might motivatefirms, especially those suffering frompoor past performance in terms of growth and profitability, to adopt anduse ABC to improve their financialperformance.

In light of the foregoing ABC litera-

ture and the possible benefits from theuse of ABC presented in it, we hypoth-esize that small sustaining and growingfirms with poorer past financial perfor-mance in terms of growth and profitabi-lity will make more use of ABC:

H1a: There is a negative relationshipbetween past financial performance in terms of growth and the extent of

ABC use.

H1b: There is a negative relationshipbetween past financial performance in terms of profitability and the extent of ABC use.

Influence of the Extent of ABC Useon Financial Performance

Modified from Kaplan and Cooper(1998, pp. 1–6) improved performance of the firms may result from the fact that thefirms are “doing the things right” or“doing the right things.” Thus, the adop-tion and use of ABC could direct theattention of firms’ management to opera-tional improvements as well as to

1

The adoption rates of ABC have typically been varying from around 10 percent to around 60percent (see, e.g., Al-Omiri and Drury 2007; Baird, Harrison, and Reeve 2004; Bjornenak andMitchell 2002; Bhimani et al. 2007; Chenhall and Langfield-Smith 1998; Kallunki and Silvola2008; also Gosselin 2007).




redirected strategic decisions. The ben-efits might be attained, for example,through cost reductions, better resourceutilisation, and cost avoidance. Thus, theprofitability of firms should improve,because resources are used moreefficiently.

Taking a strategic approach, based onthe more accurate and relevant informa-tion obtained through ABC, for example,on products, customers, market seg-ments, and distribution channels, thefirms might be able to change their waysto operate. Then the emphasis is moreon the improvements in performanceresulting from the shifting of activities tomore profitable ones. Firms using ABC

might improve their operational and stra-tegic decision-making that would finally assist the firms to improve their financialperformance (see Baxendale 2001;Gunasekaran, Marri, and Grieve 1999;Hicks 1999; Kaplan and Cooper 1998;Kaplan and Norton 2001; Roztocki et al.2004; Sandino 2007). Thus, the financialperformance relating to operationalimprovements may be visible in the formof improved profitability of firms. Never-theless, the strategic redesigns may firstlead to improved competitiveness in themarket. That development, in turn,

would be visible in terms of salesincrease (Kaplan and Cooper 1998,p. 188). These improvements may, inturn, impact positively on the profitabil-ity of firms, for example, based on better

utilization of economies of scale whensmall firms are growing larger (Sandino2007; see also McMahon 2001).

However, the concept of performanceis acknowledged as complex and multi-dimensional (Otley 1999; also McMahon2001). For example, earlier ABC surveyshave often examined the performanceeffects asking whether the respondentsbelieved that the ABC had been “success-

ful,” “worth implementing,” or whetherthe respondents were “satisfied” withtheir ABC system (see Foster andSwenson 1997; McGowan and Klammer

1997). In addition, the earlier literatureprovides only limited and even equivocalempirical evidence on the influence of the use of ABC on the financial perfor-mance of the firm (Gosselin 2007). It isalso noteworthy that most of the earlierstudies investigate the effects of the use

of ABC on performance of large firms(e.g., Kennedy and Affleck-Graves 2001;Ittner, Lanen, and Larcker 2002; Maigaand Jacobs 2007, 2008; Cagwin andBouwman 2002). In the small firmcontext, only the field studies by Gunasekaran and Singh (1999) andLaScola Needy et al. (2003) demonstratepositive impacts of ABC on operationalcontrol and overall performance in small

manufacturing firms.One reason for the equivocal empiri-

cal results may be that the cross-sectional research settings are unable toreveal whether there are possiblelagging effects of ABC on the financialperformance of firms over time. Theeffects of management control systemsincluding ABC may not be visible in thefinancial performance of firms immedi-ately after adoption (Chenhall 2004;Kaplan and Cooper 1998; Luft andShields 2003). Earlier studies point outthat sophisticated management controlsystems, ERP systems for example, havea lag of two years on firm performance(see Nicolaou and Bhattacharya 2006).

The adoption of ABC ought also to havelagged effects on firm performance,

because the new cost accounting infor-mation has to be produced before it canbe used in decision-making (Andersonand Young 1999; Cagwin and Bouwman2002; Chenhall 2004; Kaplan andCooper 1998). The consequences of decisions will then be realized in theform of financial performance in theimmediate future. Thus, in this study,

we advance from a purely contempora-

neous point of view to a more longitu-dinal assessment of possible laggingeffects of the use of ABC on subsequentfinancial performance of small firms




over a two-year period.2 Based on thearguments of the theoretical and empiri-cal literature discussed previously, westate the following hypotheses:

H2a: There is a positive direct relationship between the extent of ABC use

and subsequent performance in terms of growth over two immediate years.

H2b: There is a positive direct relationship between the extent of ABC use and subsequent performance in terms of profitability over two immediate

years.

H2c: There is a positive indirect relation-

ship between the extent of ABC use and subsequent performance in terms of profitability through growth over two immediate years.

Figure 1 illustrates the hypothesizedrelationships between small firm pastfinancial performance, the use of ABC,and the subsequent financial perfor-mance as a path model to be tested in thestudy.

Method Sample and Data

To assess the hypothesized relation-ships, the study is based on a combina-tion of a survey and archival data. Thedata gathered by a survey method (seeDillman 2000; Van der Stede, Young, and

Chen 2005) cover information on the useof ABC and organizational characteristicsof small firms (see Appendix). Archival

data consist of the financial statements of the sample firms, which were down-loaded from the commercial “Voitto+”database (Suomen Asiakastieto Oy) afterthe survey.3 Thus, no performance mea-sures were elicited from the respondentsof the survey. In total, archival data cover

the financial performance measures of firms over a total of five years: for thebaseline year of the survey, for the twopreceding years, and for the two follow-ing financial years after the survey.

The initial sample of small Finnishfirms was drawn from the database. Dueto a very limited research and knowl-edge on financial and managementaccounting techniques in small firms

(see, e.g., McMahon 2001; Mitchell andReid 2000), this study focuses on smallsustaining and growing firms. Thechoice results from the prior small busi-ness research stating that the use of more sophisticated planning andaccounting practices is more likely asso-ciated with the small firms that haveexperienced growth in net sales andemployed more than about 10 people(Davila 2005; Laitinen 2001a; Mitchelland Reid 2000; Orser, Hogarth-Scott, andRiding 2000; Perren, Berry, and Par-tridge 1998; Perry 2001). Thus, our sam-pling focuses on small sustaining andgrowing firms in which the technique of

ABC would more likely have beenadopted and be used than in withdraw-ing firms with diminishing sales.

In fact, a sample firm had to satisfy allthe following four ex ante criteria forinclusion in the sample selection: (1) to

2Our data consists of small firms for which company mergers and acquisitions are common. Therefore, the number of original small firms in our financial data decreases year by year. Asa result, too small sample size would not have allowed us to run statistical analyses over alonger time period than two subsequent years.3 According to the Finnish legislation, all limited companies have to deliver their statutory

financial statements to the National Board of Patents and Registration of Finland (PRH) withineight months after a financial year has ended. This information is publicly available. The“Voitto+” database bases its financial statement information on Finnish firms on the publicinformation of PRH and thus the information is regarded as extremely reliable.




employ from 10 to 49 persons,4 (2) to bean independent firm, (3) to have growthin net sales in the last financial year, and

(4) to offer its financial statements for thepast four years. On the other hand, thegrowth criteria of sales may also haveresulted into the rejection of potentialsample firms due to natural variations inannual sales typical for small firms(Delmar, Davidsson, and Gartner 2003).However, the procedure is not deemed

to lead to a severe bias in sample selec-tion. Furthermore, microfirms and very

young start-up firms were advisedly

excluded from the sample. Finally, astratified sampling of 1,000 small sustain-ing and growing firms was made.5 Theaim of stratification was to increase thelikelihood of the sample being represen-tative and containing different-sizedsmall firms for the empirical tests of thehypothesis (see Luft and Shields 2003).

4

The range of employees follows the definition of a small firm given by the EuropeanCommission (2003/361/EC).5On life cycle perspectives, the sample firms may well be in the growth or revival phase of theirorganizational life cycle (see, e.g., Moores and Yuen 2001).

Figure 1Hypothesized model

Subsequent financial

performance

Past financial

performance

Extent of

ABC use

H 1a − H 2a +

Past two-year period

before the survey

Baseline year of

the survey

Two-year period

after the survey

Past 3-year

growth

Past 3-year

profitability

H 2b +H 1b −

Change in

2-year growth

Change in2-year

profitability

H 2c +

ABC, activity-based costing.




A postal and pilot-tested question-naire was sent to the managing directorsof the firms operating in industries of

services, manufacturing, and trade. Table 1 presents the initial stratifiedsample of the study, the responses of managing directors, and the final usablesample of the study grouped accordingto the number of employees from 10 to19 and from 20 to 49. The majority (58.7percent) of the firms in the initial sample

were firms with 10–19 employees andthe minority (41.3 percent) were firms

with 20–49 employees (see Table 1). Allin all, 183 responses were received,giving a response rate of 18.3 percent. As

Table 1 shows, it seems that larger firmsemploying from 20 to 50 persons havebeen more willing to take part in thestudy than smaller ones from 10 to 19employees. This may implicate that

when the firm size increases, also theadministrative structure of the firmdevelops (Penrose 1959; Storey 1994).Perhaps managing directors of largersmall firms are also more accustomed to

respond to surveys as a part of their daily routines. The final sample used in theempirical analyses of this study contains

a total of 154 responses of private com-panies (response rate 15.4 percent),because 29 firms had to be excludedmainly due to missing financial data forthe subsequent two years after thesurvey.6

Table 2 reports the descriptive back-ground statistics for the firms in thesamples. The comparisons of the back-ground information of the final sample of

the 154 firms to the larger sample of 183small firms showed very similar profiles.7

Table 2 shows that typically the firms inthe final sample are about 16 years old,and the average size of firms is about 24employees with net sales of 3,500 thou-sand euro. The firms in the sample havealso been growing at the annual rate of about 10 percent, and ROI has beenabout 30 percent. Because the median

values of all the background variablesare slightly lower, the distributions of all

variables are a little bit skewed toward

6In total, for 28 firms, the database did not contain financial information on the second yearafter the survey. This kind of ex post information is required for the examination of possiblelagging effects of the use of ABC on subsequent financial performance of the firms. Thescreening of the data also revealed that one firm was a clear outlier having an extremely highpast three-year growth, and the case was finally excluded from the analyses to improve the

multivariate normality of the data set.7Even though the 154 small firms in the study seem to have slightly larger net sales and totalassets than the firms in the sample of 183 firms, the nonparametric tests confirm that the meansand frequencies do not differ significantly from those in the larger sample (see Table 2).

Table 1Sample and Response Rates

Small Firms Total Sample Responses Usable Responses

Number

Number Response

Rate

Number Response

Rate

10–19 employees 587 88 15.0 70 11.920–49 employees 413 95 23.0 84 20.3

Total 1,000 183 18.3 154 15.4




Table 2Descriptive Statistics on Final Sample and Responded

Firms in Baseline Year

Panel A. Descriptive Statisticsa

Final Sample(n = 154)

Responded Firms(n = 183)

Mean S.D. b Median Mean S.D. b Median

Net sales (1000 EUR) 3533.4 3948.5 2193.1 3325.6 3712.8 2110.8 Total assets (1000 EUR) 1756.1 2091.3 976.8 1702.4 1987.9 972.8Growth rate in net sales

(percent)10.4 27.3 8.1 9.6 27.8 7.6

ROI (percent) 30.2 29.0 27.8 27.6 30.3 26.5Number of employees 23.8 11.8 22 23.4 11.7 21Firm age in years 16.4 10.8 14.0 16.5 10.9 13.0

Panel B. Organizational Background Information

Final Sample(n = 154)

Responded Firms(n = 183)

Number of Firms

Percentage Number of Firms

Percentage

Industry Service 69 44.8 81 44.3Manufacturing 63 40.9 79 43.2

Trade 22 14.3 23 12.6Growth Orientation

Planned high growth 41 26.6 45 24.6Growth when opportunities

appear

98 63.6 120 65.6

No growth 15 9.7 18 9.8Level of Competition

Low 4 2.6 5 2.7Moderate 63 40.9 74 40.4High 87 56.5 104 56.8




greater values of background informa-tion. In addition, about 45 percent of thefirms in the final sample are service com-panies, whereas manufacturing firmsrepresent about 41 percent and tradefirms represent only about 14 percent.

A general tendency of diminishingresponse rates of mail surveys could berecognized in this study, too (see, e.g.,Laitinen 2001a; Moores and Yuen 2001;

Van der Stede, Young, and Chen 2005).Even though the nonrespondents’ realreasons for their refusal to participate inthe survey remained widely unknown, intotal, 14 firms announced that mainreasons for their nonresponse were thelack of time and/or that they havereached their saturation point due tohuge overload of various surveysaddressed to small firms nowadays.

Thus, the causes of nonresponses seemnot to originate in the subject matter of the study, but more likely they wererelated to factors in small firms.

Nonresponse bias tests were also con-ducted to ensure the representativenessof the small firms responded (Van derStede, Young, and Chen 2005). Theresults of one sample chi-square testsindicated that there were no significantdifferences between the final sample of the study and the total sample, forexample, between the geographical loca-tions of firms across Finnish provinces

( p =

.390) and financial categories of firmsranked by the database ( p = .443). Fur-thermore, the comparisons of distribu-tions of the study variables between theearliest and latest 20 percent of respon-dents provided some evidence for theabsence of a response bias, because theresults of Mann–Whitney U-tests and one-sample chi-square tests were insignifi-cant. Only a weak tendency toward lower

past three-year growth rate in net sales( p = .088) and growth rate in net sales inthe year of the survey ( p = .077) wasdetected. Based on all these aspects

Table 2Continued

Panel C. Characteristics of Management Team

Characteristics Final Sample

(n = 154)

Responded Firms

(n = 183)

Mean S.D. b Mean S.D. b

Number of managers and heads 4.83 3.05 4.84 3.20Number of experts in business managementc 2.04 1.49 2.04 1.51Diversification of the functional skillsd 2.42 0.82 2.44 0.81

a The information is updated based on the annual reports of the financial year that has

afterward been collected from the “Voitto+” database. Therefore, the figures differslightly from the respective information on the previous financial year that wasmainly used for the sample selection.bS.D., standard deviation.cBusiness management is defined as a number of experts in accounting, marketing,and general management.dFunctional skills cover technical, accounting, marketing, and all the other expertise.ROI, return on investment.




pointed out previously, a possible nonre-sponse bias is not considered to be sub-stantial for this study. However, the lowresponse rate is still a limitation of thestudy despite a considerable absolutenumber of usable responses. Thus, any generalizations of the results to the whole

population of small firms must be done with caution.

Measurement of VariablesThe Extent of ABC Use. The question-naire was designed to empirically iden-tify first, whether the more advancedtechnique of management accountingsuch as ABC has been adopted by smallfirms and second, how intensively ABC is

used by the firms in practice, if adopted. To avoid too complicated and academic wording in surveys addressed to smallfirms’ managers, the survey item askedmanaging directors to indicate the extentof their firms’ use of calculations of costsbased on ABC (see Perren and Grant2000). In practice, ABC may take variousforms depending on the contextualfactors (Baird, Harrison, and Reeve 2004;Cooper 1988; Gosselin 2007; Laitinen2001a). However, in this small firmstudy, the survey item did not make, forexample, a distinction whether the cal-culations were made at the level of costsof activities or costs of products orservices.

A five-point Likert-type scale wasapplied ranging from “not used at all”

(scored 0) up to “used systematically as apart of normal routines” (scored 4). Theother scores between these two mea-sured occasional use from “very seldom”(scored 1), “at times” (scored 2) to “quiteoften” (scored 3). If a firm reported notusing ABC at all, it was interpreted thatthe firm had not adopted the practice

(see Baird, Harrison, and Reeve 2004).Overall, the scale was created to reflectthe spread of the use of ABC as well assmall firms’ commitment to the use of the

ABC practice (see Appendix).

Measures of Financial Performance.

Despite the limited amount of manage-ment accounting research in the smallbusiness context, it is noteworthy thatthe most common financial performance measures in small business studies aregrowth in net sales and/or ROI (seeLaitinen 2001a; Orser, Hogarth-Scott, andRiding 2000; Peel and Bridge 1998; Rueand Ibrahim 1998). However, the collec-tion of statutory financial information

from a database as executed after thesurvey in this study seems to be rare.

This obviously results from the fact thatthe information of small firms is notextensively published in the public data-bases available to researchers.

In this study, financial performance isunderstood to comprise two dimensionsincluding small firm’s growth and profit-ability (see Wolff and Pett 2006). Growthis operationalized by a measure of growth rate in net sales that describes asmall firm’s achieved success in themarket. Profitability is measured by theROI. Even though ROI may be affectedby industry sensitive factors, on the otherhand, it reduces the effects of firm size as

well as of possible smoothing of earningsin small firms. Furthermore, nowadays,

the growth in net sales and profitability of many small firms may be related moreto firm-specific features, for example,

various clusters of firms they interact with than to small firm’s own industry assuch. In addition, the focus in this study is on how the performance of a firm hasdeveloped during the years studied.8

8

Correlation analyses revealed no significant relationships between industry (measured by twodummies) and the measures of change in subsequent performance over two immediate yearsin terms of growth in net sales and ROI. Results support the view that industry-specific featuresare not crucial to the findings.




Past financial performance of firms was measured by average past three-yeargrowth rate in net sales and average pastthree-year ROI including the year of thesurvey. For small firms especially, it is

justified to calculate the longer termfinancial ratios because the annual sales

of firms may fluctuate quite a lot from year to year (Delmar, Davidsson, andGartner 2003). Thus, past long-term per-formance of three years was consideredto be a more reliable and valid indicatorthan past short-term performance of afiscal year. Regarding subsequent finan-cial performance in the immediatefuture, first, the changes in a firm’sgrowth in net sales and ROI covering the

baseline year of the survey were calcu-lated. Second, the changes in ratiosduring the next year, and third, over thetwo years after the survey were calcu-lated to gain a longer term understand-ing of the dynamism between the extentof ABC use and financial performance of firms over the subsequent years. Thisprocedure enabled us to examine

whether the possible performance effects would be visible after a longer timeperiod in order to detect the possiblelagging effects of the use of ABC onfinancial performance of firms.

Statistical Methods The main statistical method of the

study is structural equation modeling(SEM) due to its advantage over other

typical multivariate techniques; it cantake all the interrelated dependence rela-tionships and measurement error intoaccount simultaneously in the estimationprocedure of a single model (Hair et al.1998; Ullman 2001). Such a comprehen-sive approach is preferred because of thetentative nature of the study to examine

how well the hypothesized model fits theempirical data of the small businesses(Hair et al. 1998). Furthermore, themethod of maximum likelihood is usedin the modeling.9 However, because theunivariate and multivariate normality arenot complete among the study variables,

a bootstrap procedure is used as an aidto validate the results of the path-analytical models (Hair et al. 1998).10

ResultsDescriptive Statistics

Table 3 provides descriptive informa-tion for the variables used in the pathmodels of the study.

As panel A in Table 3 shows about 30percent of sample firms that do not use

ABC at all, that is, have not adopted it.Furthermore, in total, 70 percent of thefirms report using ABC at least to someextent (scores 1–4). On the other hand,only 12 percent of the firms report using

ABC systematically as a part of theirnormal routines, whereas 19 percentreport using ABC quite often. Compari-sons of the figures with the adoptionrates recently found in larger companiesare problematic due to different instru-ments and samples used in the studies.Nevertheless, Baird, Harrison, and Reeve(2004) have applied quite a similarapproach to the measurement of theextent of adoption of activity manage-ment (AM) among larger companies in

Australia. However, Baird, Harrison, andReeve (2004) distinguish the variouslevels of AM, that is, activity analysis,activity cost analysis, and ABC, and askthe extent of adoption of each level intheir survey. The aggregate adoption rateof the levels of AM is about 95 percentand about 42 percent of the companies

9

The statistical packages SPSS 15.0 and AMOS 8 (Graphics) are utilized for all the statisticalprocedures.10 The number of subsamples requested is 500, and the bias-corrected confidence intervals forevaluation of parameter estimates are set at 90 percent.




Table 3Descriptive Statistics on the Model Variables (n = 154)

Panel A. Extent of ABC Use

Survey Item

Scale

0 1 2 3 4

Not Used Very Seldom

At Time QuiteOften

Systematically

Extent of ABC use

46(30 percent)

31(20 percent)

30(19 percent)

29(19 percent)

18(12 percent)

Panel B. Descriptive Statistics

Variable Mean S.D. Skewness Kurtosis

Extent of ABC use 1.62 1.39 0.29 -1.22Past three-year financial performance

Past three-year growth rate in net sales 15.45 16.94 1.77 5.17Past three-year growth rate in net sales(Sqrt)

6.71 1.16 0.96 2.33

Past average three-year ROI 30.53 23.79 0.35 1.40Baseline model, changes in financialperformanceD Growth rate in net sales -25.00 61.29 -3.02 16.29D ROI -4.44 30.87 -0.27 5.46

Future 1-year model, changes in financialperformanceD Growth rate in net sales after a year -3.30 44.44 1.32 9.98D ROI after a year -3.77 33.36 0.51 13.48

Future 2-year model, changes in financial

performanceD two-year growth rate in net sales -7.83 34.73 -0.79 6.77D Average two-year ROI -6.45 31.25 1.76 10.07

D denotes the change in the variable.Baseline model consists of the proposed links of independent variables and ABC andthe association between ABC and changes in financial performance in the baseline

year of the survey.Future 1-year model focuses on the changes one year after the survey and Future

2-year model focuses on the changes over a two-year period after the survey. ABC, Activity-based costing; ROI, return on investment; S.D., standard deviation.




have adopted the ABC of AM to a greatextent. Chenhall and Langfield-Smith(1998) have likewise reported high adop-tion rates from Australia: 68 percent foractivity-based management, 78 percentfor activity-based budgeting, and 56percent for ABC.

Taking into account the traditionalclaims that small firms do not utilizeadvanced or even formal managementaccounting, the adoption rate of 70percent identified in this study is surpris-ingly high. However, it is noteworthy that the percentage regarding the firmssystematically using calculations of costsbased on ABC is only 12 percent. When

we combine the percentage with the

small firms reporting to use the practicequite often, the adoption rate rises up to31 percent. Laitinen (2001b) has alsoreported that about 40 percent of Finnishtechnology companies use ABC.However, that sample included bothsmall and larger firms, and the survey instrument was different from the instru-ment used in this study. Al-Omiri andDrury (2007) also report that 12 percentof the smallest companies in their samplehad adopted ABC systems in the UnitedKingdom.

It seems obvious that the versatility of survey instruments used in ABC studiesexplains quite well the variation of adop-tion rates between studies. This study approaches the adoption and the extentof ABC use in small firms from a general

and aggregate view. Thus, the use of ABC in this study may range from ad hoccalculations of activity costs to even theroutine use of a sophisticated ABCsystem. Nevertheless, the results of thisstudy show that small sustaining andgrowing firms have adopted variouslevels of ABC and are also using thetechnique in practice.

Next, to elicit more information on

the possible organizational factors of small firms driving their use of ABC,correlation analyses between ABC andthe characteristics of small firms are

processed. Table 4 provides the coeffi-cients of Pearson correlation for therelationships and the respective signifi-cance levels.

As Table 4 shows, the use of ABC insmall firms seems to correlate signifi-cantly with three organizational factors.

First, the aging of the firm seems torelate to more extensive use of ABC. Thisassociation concurs with the findings of Davila (2005) that the use of formal man-agement control systems increases as thefirm grows older. Second, the stiffer com-petition small firms face, the more exten-sively they use ABC also. Such arelationship is also supported by earliermanagement accounting studies (e.g.,

Al-Omiri and Drury 2007) and alsoregarding small change-oriented or dis-content resourceless technology firms(Laitinen 2001a).

Third, the wider range of businessexpertise among the managers andheads, the more the firm seems to use

ABC. This is consistent with the findingsregarding the influence of top manage-ment’s support on the perceived level of

ABC implementation success (Andersonand Young 1999; Baird, Harrison, andReeve 2004; Shields 1995). It is notewor-thy that especially in small firms withindividualized decision-making andsimpler organizational structures thiskind of involvement of the managingdirector as well as the whole of top man-agement can be seen as crucial for the

adoption and successful implementationof ABC. In addition, Berry (1998) hasfound that besides the experienced smallbusiness founder with technical skills,diversity in management teams is alsorelated to more formal strategic planningand control in successful high technol-ogy firms. Shields (1995) also reportsthat nonaccounting ownership is signifi-cantly associated with ABC success.

However, the range of the functionaldiversity of top management as such isnot associated with the extent of ABCuse in this study (Table 4).




Furthermore, the industry of manufac-turing, service, or trade seems not torelate to the use of ABC. This findinglikewise concurs with the ABC literaturestating that ABC suits all kinds of com-panies and organizations (Kaplan andCooper 1998). Interestingly, the strength

of growth orientation of small firms isnot associated with the use of ABC. Fur-thermore, the effects of these contextualfactors are also tested in additional analy-ses included in the path models, and theresults are provided at the end of thenext section.

Results for Path ModelsNext, three path models with identical

structures, but for different time periods,are constructed to test the hypothesispresented earlier in Figure 1. The firstmodel, called the Baseline model , con-

sists of the proposed links of indepen-dent variables and ABC and theassociation between ABC and changes infinancial performance in the baseline

year of the survey. The second model,called the Future 1-year model , focuseson the changes one year after the survey,

and the third model, called the Future

2-year model , focuses on the changesover a two-year period after the survey.

The purpose of these two latter models isto assess whether the extent of ABC usehas visible lagging effects on the subse-quent financial performance of the smallfirms.

The correlation matrix for the vari-ables used in the empirical analyses is

shown in Table 5. Next, Figure 2 illus-trates the results of Future 2-year modelas an example of the models examined inSEM. Table 6 depicts the selected fit

Table 4Pearson Correlations for Characteristics of Firms and ABC

(n = 154)

Variable Pearson Correlation

Extent of ABC Use

p

Firm size (Number of employees, Lg10) 0.034 0.678Firm age in years (Lg10) 0.157 0.052Industry, dummy 1a

-0.069 0.392Industry, dummy 2b 0.066 0.416Growth orientationc

-0.075 0.357Level of competitionc 0.208 0.010Number of managers and heads (Lg10) 0.100 0.216Number of experts in business management (Lg10)d 0.198 0.014Diversification of functional skillse 0.130 0.108

aIndustry, dummy 1: 0 = service and trade, 1 = manufacturing.bIndustry, dummy 2: 0 = trade and manufacturing, 1 = service.cScale: 1 = low, 2 = moderate, 3 = high.dBusiness management is defined as a number of experts in accounting, marketing,and general management.eFunctional skills cover technical, accounting, marketing, and all the other expertises.




indices of all the three models showingan acceptable fit within the data (seeHair et al. 1998). All the other fit indicesprovided by Amos, but not included inthe table, are also at acceptable levels.

Results of the Future 2-year model inFigure 2 indicate that the past growthrate in net sales is significantly related

to the extent of ABC use, and the sign of the direction is negative as expected. Onthe other hand, past ROI is positively associated with the extent of ABC use.

However, the sign of this relationship iscontrary to our expectations. Thus, only H1a is supported.

Consistent with the expectation, thefinding of the Future 2-year model indi-cates that the path between the extent of

ABC use and the change in growth ratein net sales is significant and positive,

albeit the significance of the associationis rather weak. In addition, the path fromthe growth to ROI is significant and posi-tive as proposed. However, the path

Table 5Pearson Correlation Matrix for the Variables in the Path

Models (n = 154)

Variable 1. 2. 3. 4. 5.

Panel A: Baseline Model1. Extent of ABC use 1.0002. Past three-year growth rate

in net sales (Sqrt)-0.168** 1.000

3. Past three-year ROI 0.153* 0.348*** 1.0004. D Growth rate in net sales -0.151* 0.076 -0.091 1.0005. D ROI -0.068 -0.031 -0.181** 0.370*** 1.000

Panel B. Future 1-year Model1. Extent of ABC use 1.0002. Past three-year growth rate


3. Past three-year ROI 0.153* 0.348*** 1.0004. D Growth rate in net sales

after a year0.145* -0.324*** -0.018 1.000

5. D ROI after a year 0.002 -0.207** -0.263*** 0.382*** 1.000Panel C. Future 2-year Model

1. Extent of ABC use 1.0002. Past three-year growth rate


3. Past three-year ROI 0.153* 0.348*** 1.0004. D two-year growth rate in

net sales0.195** -0.370*** -0.019 1.000

5. D Average two-year ROI -0.010 -0.215*** -0.301*** 0.396*** 1.000

D denotes the change in the variable.Descriptive statistics for all models have been provided in Table 3.Significance levels are the following: *** p < .01, ** p < .05, * p < .10 (two-tailed).

ABC, Activity-based costing; ROI, return on investment.




between the extent of ABC use and ROIis not significant. To summarize, thesefindings on the lagging effects of ABCuse on subsequent financial performancesupport H2a and H2c, but not H2b. Thus,the finding shows an indirect positive

association between the extent of ABCuse through the intervening variable of change in subsequent two-year growthrate and change in average ROI of the

small firms. Therefore, change in subse-quent growth rate provides a full medi-ating effect for the association betweenthe extent of ABC use and change in ROI(Baron and Kenny 1986).

The extent of ABC use has no clear

intervening role between the variables of past performance and subsequent perfor-mance of small firms. Nevertheless, theextent of ABC use has a significant, albeit

Figure 2Results of the Future 2-year Model

0.395***

Subsequent financial

performancePast financial

performance

Extent of ABC

use

− 0.251*** 0.137*

Past two-year period

before the survey year

Baseline year of

the survey

Two-year period

after the survey

Past 3-yeargrowth in net

sales

Past 3-year ROI

− 0.0440.241***

Change in2-year growthin net sales

Change in2-year ROI

− 0.347***

− 0.284***

Notes: RMSEA, root mean square error of approximation; ABC, activity-based

costing; ROI, return on investment; CMIN/DF, minimum discrepancy divided by

its degrees of freedom; GFI, goodness-of-fit index; CFI, comparative fit index;

AIC, Akaike Information Criterion. Future 2-year model depicts the results of

hypothesized model over two immediate years.

The Figure 2 shows the standardized estimates as follows:

*** p < 0.01, ** p < 0.05, * p < 0.10

c 2

= 1.575, df = 2, p = 0.455, CMIN/DF = 0.788, GFI = 0.996, CFI = 1.000,RMSEA = 0.000, AIC = 27.575 (saturated model 30.000).




weak, lagging positive effect on the per-formance regarding the change ingrowth rate in net sales and furtherthrough this variable finally on the posi-tive change in average ROI.

Table 7 shows the standardizedregression estimates and significance of

the paths between ABC and subsequentperformance of firms regarding all thethree path models examined. As Table 7indicates, the path between ABC andchange in growth rate in net sales in theBaseline model is significant, albeit nega-tive. Next, the Future 1-year modelshows a positive but not a significantresult for the measurement of the respec-tive path. Finally, the Future 2-year

model shows a positive and significanteffect. Furthermore, the paths between

ABC and changes in ROI are insignificantin all the three models. In addition, theassociations between changes in growthrates and changes in ROI are positiveand significant in all models. Thus, H2cis supported by the finding of the Future2-year model of two years lagged effects.

This finding indicates that more exten-sive ABC use has a positive lag in salesgrowth that also impacts positively onROI. In addition, the emerging trendfrom a significant negative path between

ABC use and growth in net sales in theBaseline model to the significant positiverespective path in the Future 2-yearmodel also demonstrates the evolvementof the lagging effect (see Table 7).

Though not hypothesized, the directeffects of past performance on subse-quent performance are also included inthe three models to check their impacton the final results (see Donaldson 2001;Hair et al. 1998). The paths between pastthree-year ROI and changes in subse-quent ROI in the Future 1-year modeland the Future 2-year model were nega-tive and significant but insignificant in

the Baseline model. A correspondingnegative association was also foundbetween past three-year growth in netsales and change in growth in net sales

T a b l e 6

F i t I n d i c e s f o r t h e M o d e l s

M o d e l

c 2

d f

p

C M I N / D F

R M S E A

G F I

C F I

A I C ( s a t u r a t e d

m o d e l )

B a s e l i n e

m o d e l

1 . 4 3 5

2

0 . 4 8 8

0 . 7 1 7

0 . 0 0 0

0 . 9 9 6

1 . 0 0 0

2 7 . 4 3 5 ( 3 0 . 0 0 0 )

F u t u r e 1 - y e a r m o d e l

1 . 1 8 1

2

0 . 5 5 4

0 . 5 9 1

0 . 0 0 0

0 . 9 9 7

1 . 0 0 0

2 7 . 1 8 1 ( 3 0 . 0 0 0 )

F u t u r e 2 - y e a r m o d e l

1 . 5 7 5

2

0 . 4 5 5

0 . 7 8 8

0 . 0 0 0

0 . 9 9 6

1 . 0 0 0

2 7 . 5 7 5 ( 3 0 . 0 0 0 )

T h e r u l e s o f t h u m b f o r a c c e p t a b l e fi t i n d i c e s a r e a s f o l l o w s ( e

. g . , H a i r e t a l . 1 9 9 8 ) : C M I N

/ D F s h o u l d b e n e a r 1 o r a t l e a s t l e s s t h a n 5 ;

t h e R o o t

M e a n S q u a r e E r r o r o f A p p r o x i m a t i o n ( R M S E A ) i n d i c a

t i n g a n e r r o r i n a p p r o x i m a

t i o n s h o u l d b e l e s s t h a n 0 . 0 5 ; G o o d n e s s - o f - F i t

I n d e x ( G

F I ) i n d i c a t i n g t h e o v e r a l l fi

t s h o u l d b e c l o s e t o 1 ; C o

m p a r a t i v e F i t I n d e x ( C F I ) s h o u l d b e g r e a t e r t h a n 0 . 9 ; a p e r f e c t fi t v a l u e

i s 1 . V a l u

e s o f A k a i k e I n f o r m a t i o n C

r i t e r i o n ( A I C ) r e l a t i n g t o b

a d n e s s o f fi t a n d c o m p l e x i t y s h o u l d b e l e s s t h a n t h e v a l u e o f a s a t u r a t e d

m o d e l .




in the Future 1-year model and theFuture 2-year model. These morecommon trends between past perfor-mance and its changes over the two fol-lowing years show that the firmsstruggling with their past growth havealso been able to increase their subse-quent growth rates more than the smallfirms with higher past growth even

without the use of ABC. Thus, moreextensive ABC use seems rather tosupport the subsequent growth of the

firms and the further improvements insubsequent profitability based on thepartial mediation found. Small firms withbetter past profitability seem not to havebeen able to improve their subsequentprofitability so much as the firms withpoorer past profitability. However, theuse of ABC seems to support theseearlier better performing firms also toattain greater improvements in their sub-

sequent profitability through fastergrowth in the market.Finally, the robustness of the results is

investigated by checking the influence of

characteristics of firms as control vari-ables (presented in Table 2). The level of competition and the number of expertsin business management have positiveand significant associations with theextent of ABC use as could be expectedbased on the significant correlationsreported in Table 4. However, the firmsize and age do not have a significantrelationship with ABC. Growth orienta-tion, main industry, and features otherthan the number of business experts in a

management team also have insignificantassociations with the use of ABC. Thus,our results on the hypothesized associa-tions in the initial path models remainthe same after checking for the effects of organizational characteristics.

Discussion and Concluding Remarks

ABC has been one of the most inten-

sively explored topics in managementaccounting research in the recentdecades, but only few earlier studies haveprovided empirical evidence of the use of

Table 7Regression Coefficients of the Paths between ABC and

Financial Performance in the Path Models (n = 154)

Model

Paths

ABC - > D ROI ABC - > D Growthin Net Sales

D Growth in NetSales - > D ROI

Standardized Estimate

p Standardized Estimate

p Standardized Estimate

p

Baseline model 0.009 0.91 -0.142 0.08 0.360 0.00Future 1-year

model-0.014 0.85 0.093 0.23 0.377 0.00

Future 2-yearmodel-

0.044 0.55 0.137 0.07 0.395 0.00

D denotes the change in the variable.Correlation matrix for the variables in all models has been provided in Table 5.

ABC, Activity-based costing; ROI, return on investment.




ABC on financial performance. Looking atthe sample of small firms in this study, thefindings indicate that the small firm’s pastfinancial performance is associated withthe extent of ABC use; the past growthnegatively and the past profitability posi-tively. In other words, relatively profit-

able small firms as well as firms struggling with their sales use ABC presumably inorder to achieve improved performance.

The findings may suggest that firms thathave faced pressures of increased compe-tition, decreasing market shares or salesprices have tried to be more cost-effectiveand have also tried to search for morecompetitive advantages to support andrefresh their sales growth in the market.

In so doing, they may rely on the assis-tance of ABC as an efficient, operational,and strategic management accountingtool. Our results show that better pastprofitability and thereby improved finan-cial resources of small firms seem to acti-

vate the use of ABC, even though the ABCliterature usually states the opposite (seeKaplan and Cooper 1998). However, ourfindings are in line with Laitinen (2001a),

who have found that small firms sufferingfrom a lack of financial resources tend notto be so willing to develop their manage-ment accounting systems toward exten-sive use of techniques like ABC.Furthermore, our findings regarding firms

with good past profitability and use of ABC may also reflect the invisible conse-quences of investing the earned profits in

further organizational development andgrowth by adopting and using moresophisticated management accountingtechniques to support these kinds of objectives.

The last set of the findings turns theattention toward the possible perfor-mance effects of the use of ABC. First, wefound that the more extensive use of

ABC has a positive lagging effect on the

development of sales in small firms overthe next two years. In fact, our resultsshow that more active users of ABC havefirst experienced a decrease in growth

during the year of the survey. However,the trend has finally turned to a moresignificant increase in growth after two

years compared with the more passiveusers of ABC. Perhaps the trend is aconsequence of improved cost-efficiency and improved competitiveness achieved

in the market of small firms using ABCmore extensively. Second, the pathmodel shows that the extent of ABC usehas a weak lagging effect on profitability through growth over the period of two

years studied. The result is also consis-tent with the findings of Cagwin andBouwman (2002) and Ittner, Lanen, andLarcker (2002) on larger companies. Asthe earlier literature reports, the effects

of ABC may not be visible in financialperformance immediately after adoption,and it may take even several years beforeany improvements in financial perfor-mance are achieved (Anderson and

Young 1999; Chenhall 2004; Kaplan andCooper 1998; Luft and Shields 2003). Thefindings of this study suggest that theimprovements in growth become visiblein small firms using ABC more exten-sively in two years.

From a practical point of view, theresults of this study indicate that an ABCadoption is a long-term investment thatstarts to generate financial benefits overtime. In this study the positive develop-ment became visible in a two-yearperiod. However, besides the financialbenefits, it could be argued that ABC

may be a helpful tool for managers intheir operative decision-making andmanagement, too. When creating adesign for an ABC system, managersneed to think about their business pro-cesses carefully and identify all the activi-ties as well. Since managers more deeply understand both the organizational andcost structure on activity level in thefirms, they are likely more capable to

apply activity-based management, too.Furthermore, by using accurate and rel-evant cost information in decision-making, managers are able to make more




profitable product mix decisions and, forexample, compare cost effects betweenoutsourcing and in-house production.

Though our findings show that ABChelps especially firms suffering frompoor development of sales, ABC may also assist managers to focus marketing

on the most profitable products and cus-tomers in generating growth. Finally,financial benefits may be seen to emergeas increasing growth but also as improv-ing profitability.

Several limitations have to be consid-ered, however, when drawing conclu-sions from the findings of this study.First, we acknowledge that performanceis a complex and multidimensional con-

struct that can be reflected by many various indicators. Second, the sampleconsists only of small sustaining andgrowing firms excluding small withdraw-ing firms with diminishing sales at thetime of sample selection. Thus, no gen-eralization of the results to the wholesmall firm sector can be made withoutconsiderable caution. Even though ABChas been widely known among practitio-ners for almost two decades, it is pos-sible that views of the concept of ABCdiffer among respondents. Our study isbased on a broad concept of ABC, andthus the survey item does not explainclearly whether the use of ABC meansthe use of activity cost analysis or ABC(see Baird, Harrison, and Reeve 2004;Gosselin 2007). Access to the exact time

of ABC adoption and yearly usage ratesof ABC for subsequent years would alsohave been useful. Finally, the use of asurvey method also causes limitations tothe study. For example, it is not possibleto check the real understanding of theuse of ABC requested by the question-naire with the respondents. Anotherdoubtful aspect is the content and quality of the ABC information used in small

firms. Additionally, the possible effectsof contextual variables beyond the scopeof the study, but perhaps still influencingthe model, remain unknown.

Notwithstanding these limitations, ourfindings suggest that small firms, espe-cially if they suffer from a falling trend innet sales or have adequate financialresources, do also use advanced costaccounting techniques such as ABC fairly

widely and benefit from the use of ABC

by achieving faster increase in growth interms of net sales and finally improvedprofitability as a consequence of thisgrowth. Nevertheless, it is very likely thatmuch of the increase in sales of the firmshas resulted from the interplay of variouscontextual factors and ABC has had only a supportive role (see also McMahon2001).

In light of the findings of this study,

there seems to be a need for furtherexaminations of ABC in the small busi-ness context. First, because our study does not reveal whether the more use of

ABC is linked with the use of some othermanagement practices (such as BalancedScorecard, Just In Time production,Enterprise Resource Planning Systems,for example), further studies couldenhance our approach toward this kindof “package” aspect and their jointeffects on financial performance (seealso Kennedy and Affleck-Graves 2001).Second, future studies could also lead torefining of the measure of ABC used inthe study to include more specific opera-tionalization of the ABC use, because ourresearch design did not permit us to dis-tinguish the possible levels as well as

types of analyses included in ABC of small firms, for example. Third, thefurther examinations could investigatehow organizational variables, forexample, such as management team andcompetition as well as various organiza-tional development processes, affect theadoption and use of ABC and the subse-quent emergence of performance insmall firms. Fourth, investigating the per-

formance implications using a broaderset of performance measures coveringboth perceived and actual financial infor-mation as well as nonfinancial variables




could also be useful in understanding theoutcomes of ABC. Finally, a case-study method might provide deeper under-standing of the many questions on thenature and other benefits of ABC use insmall firms that remained unexplored inthis study.

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Appendix: Survey ItemsCharacteristics of Small Firms

1 The main industry of your firm:1 Trade2 Manufacturing3 Service

2 How do you describe your current competition? (Please tick one.)1 Competition is low2 Competition is moderate3 Competition is high

2 The past three years’ development of your firm has, in the main, been: (Please tickonly one.)1 Planned high growth2 Growth when opportunities appear3 No growth

3 The core competence of managers and heads can be divided into number of persons as follows (also including you):

Technical expertise______personsMarketing expertise______persons Accounting expertise______persons What else?______persons




Extent of ABC UseNext, there are listed reports of various MCS practices and techniques that can be

used to support business management in several industries. Do you use theseanalyses or reports in your firm? If you do, how occasional (very seldom—quiteoften) is the use or is it systematic as a part of your normal routines? (Please circlethe most appropriate alternative for each row.)

Cost accounting and pricing:

notused

. . . occasionally . . . systematically

very seldom

attimes

quiteoften

Calculations of costs based onactivity-based costing (for

example, selling, purchasing,delivering etc.)

0 1 2 3 4

Documents

Lagging Effects of the Use of Activity-Based Costing on the Financial Performance of Small Firms