The Impact of Contextual and Process Factors on the Evaluation of Activity Based Costing Systems 1999 Accounting Organizations and Society

The impact of contextual and process factors on theevaluation of activity-based costing systems$

Shannon W. Anderson a,*, S. Mark Young b

aAccounting Department, University of Michigan Business School, Ann Arbor, MI 48109, USAbLeventhal School of Accounting, University of Southern California, Los Angeles, CA 90089, USA

Abstract

This paper investigates associations between evaluations of activity based costing (ABC) systems, contextual factors,and factors related to the ABC implementation process using interview and survey data from 21 field research sites of

two firms. Structural equation modeling is used to investigate the fit of a model of organizational change with the data.The results support the proposed model; however, the significance of specific factors is sensitive to the evaluation cri-terion. The model is stable across firms and respondents, but is sensitive to the maturity of the ABC system. # 1999Elsevier Science Ltd. All rights reserved.

1. Introduction

Early proponents of ABC claimed superiorityover traditional costing methods that stemmedfrom employing causally related cost drivers toassign common costs to business activities, pro-ducts and services (Cooper, 1988; Cooper &Kaplan, 1988). Later studies argued that a judi-ciously designed ABC system provides eectivebehavioral control (Cooper & Kaplan, 1991;Cooper & Turney, 1990; Foster & Gupta, 1990.Evidence of ABC implementation failures1 hascaused researchers to suggest that achieving eitherobjective depends critically on organizational andtechnical factors (Anderson, 1995; Malmi, 1997)and recent empirical evidence supports this view

(Chenhall & Langfield-Smith, 1998; Foster &Swenson, 1997; Gosselin, 1997; Innes & Mitchell,1995; Krumwiede, 1998; McGowan & Klammer,1997; Shields, 1995). This paper combines theresults of previous studies with theory on organi-zational change to propose a structural model ofthe relation between evaluations of ABC systems,contextual factors and factors related to the ABCimplementation process.We evaluate the models descriptive validity

using survey data from managers and systemdevelopers associated with 21 implementationprojects in two automobile manufacturers. Struc-tural equation modeling (SEM) is used to investi-gate the influence of the contextual environmentand the implementation process on evaluations of

0361-3682/99/$ - see front matter # 1999 Elsevier Science Ltd. All rights reserved.PI I : S0361-3682(99 )00018-5

Accounting, Organizations and Society 24 (1999) 525559

www.elsevier.com/locate/aos

$ The authors are not permitted to redistribute the data of

this study without permission of the participating firms.

* Corresponding author. Tel.: +1-734-647-3308; fax: +1-

734-936-8716.

E-mail address: [email protected] (S.W. Anderson)

1 By some estimates only 10% of firms that adopt ABC

continue to use it (Ness & Cucuzza, 1995). In reviews of inter-

national studies of ABC adoption, Innes and Mitchell (1995);

and Chenhall and Langfield-Smith (1998) find adoption rates

generally less than 14%.

the ABC system and the influence of the con-textual environment on the ABC implementationprocess. The data are consistent with the proposedstructural model. After establishing a plausiblemodel structure, we investigate its applicability todierent evaluation criteria and its stability acrossdierent sub-groups in our sample. Thus, theresearch contributes a unified investigation ofthree aspects of ABC implementation: modelstructure; variable definition and measurement; and,model stability.We test a structural relation between contextual

variables, process variables and ABC system eva-luations that is hypothesized in process theoriesof ABC implementation (Anderson, 1995; Argyris& Kaplan, 1994; Kaplan, 1990; Shields & Young,1989). By separating the influence of the con-textual environment on the ABC implementationproject from its influence on the evaluation of theABC system, we extend previous studies thatdocument correlation between ABC project out-comes and contextual and process factors. In acase study of an ABC project that did not sur-vive, Malmi (1997) posits that implementationfailures are related more to exogenous contextualfactors than to the process of implementation that even good implementation processes fail onbarren ground. Our results support this observa-tion and point to specific exogenous factors thatmake ABC less suitable and that are unlikely tobe remedied by improving the implementationprocess.The study contributes to the area of variable

definition and measurement through field researchand the use of multiple data collection methods.Multiple modes of data collection (e.g. surveysand personal interviews) provide the opportunityto address the question: What is meant by suc-cess in ABC implementation? A danger of askingmanagers to rate ABC implementation successwithout specifying the definition of success is fail-ure to detect cases in which individuals hold dif-ferent views on the definition of success but shareviews on attainment of a particular dimension ofsuccess. In light of evidence that success in ABCimplementation is multi-dimensional (Cooper,Kaplan, Maisel, Morrissey & Oehm, 1992) witheach dimension having somewhat dierent corre-

lates (Foster & Swenson, 1997), it is appropriateto ask what criteria respondents use in evaluatingABC. Content analysis of interviews conductedwith survey respondents reveals two dominantviews of what defines an eective ABC system:whether ABC data are used in product costreduction or process improvement; and, whetherABC data are more accurate than data from thetraditional cost system. Further investigationindicates that the respondents job is a predictor ofwhich view is held. Previous studies explore deter-minants of dierent evaluation measures (Foster &Swenson, 1997) and document respondent-eectson evaluation levels (McGowan & Klammer, 1997).This study investigates whether dierent evaluationmeasures correspond to dierent views on appro-priate evaluation criteria. Then, using survey datawe estimate simultaneously the contextual andprocess determinants of respondents evaluationsof the ABC systems according to the operativecriteria. Simultaneous estimation methods allowus to consider whether the factors that influencedierent evaluation measures are common (suggesting that all criteria may be achieved) ormutually exclusive (suggesting that successalong one dimension is achieved at the expense ofanother).A final contribution of this research is investi-

gation of the stability of the relation between eva-luations of ABC implementation and factorsrelated to context and the implementation process.The research design and sampling plan permitinvestigation of three potential sources of modelinstability: company eects, respondent eectsand eects of ABC system maturity. Companyeects are examined in the spirit of sensitivityanalysis, to explore the degree to which the resultsgeneralize. We can not address the degree to whichresults generalize to dierent industry settings;however, we find few dierences between the firmsand reject the hypothesis that a firm-specific modelis warranted. The exploration of respondenteects, specifically of dierences between man-agers and ABC system developers, is a uniquecontribution of this study.2 Previous research reliesalmost exclusively on data taken from accountingprofessionals. These people may hold dierent viewson the ABC system as a result of proximity to or

526 S.W. Anderson, S.M. Young / Accounting, Organizations and Society 24 (1999) 525559

responsibility for ABC implementation, or as aresult of the degree to which ABC threatens or rein-forces their professional standing. The results indi-cate dierences in what determines evaluations ofthe ABC system betweenmanagers andABC systemdevelopers; however, statistical tests reject thehypothesis that a model that distinguishes betweenrespondent types improves model fit. Exploration ofeects of ABC system maturity on model stabilitycontinues the investigation of stages of ABCimplementation in Anderson (1995) and Krum-wiede (1998). The results indicate significant dier-ences in determinants of respondents evaluation ofABC as a function of ABC system maturity. Thus,the maturity-specific model fits the data better thana model that omits this factor.Section 2 reviews the literature and develops the

research questions. Section 3 describes theresearch sites and data collection methods.Variable measures and descriptive statistics arepresented in Section 4. Evidence on the relationbetween ABC system evaluations and contextualand process variables is presented in Section 5.The stability of the model between dierentcompanies, respondents and ABC systems ofdiering maturity is investigated in Section 6.Section 7 summarizes the contributions of theresearch and discusses avenues for future investi-gation.

2. Associations between context, process andevaluations of ABC systems

2.1. Summary of prior research

Practitioner accounts of ABC projects and casestudy research on determinants of project outcomeshave long associated technical and behavioral factorswith ABC implementation success (Beaujon &Singhal, 1990; Foster & Gupta, 1990; Cooper,

1990; Cooper et al., 1992; Drumheller, 1993; Eiler& Campi, 1990; Foster & Gupta, 1990; Haedicke& Feil, 1991; Jones, 1991; Kleinsorge & Tanner,1991; Richards, 1987; Shields & Young, 1989;Stokes & Lawrimore, 1989). Anderson (1995) sur-veys the literature on ABC and information tech-nology implementation and compiles fivecategories of 22 variables that are implicated inABC project outcomes. More recent empiricalstudies provide evidence on the correlationbetween these factors and ABC implementationeectiveness and introduce five new variables(Chenhall & Langfield-Smith, 1998; Foster &Swenson, 1997; Gosselin, 1997; Innes & Mitchell,1995; Krumwiede, 1998; Malmi, 1997; McGowan& Klammer, 1997; Shields, 1995). Table 1 updatesAndersons (1995) list of variables hypothesized toinfluence ABC system evaluations (column 1) andsummarizes the statistical relations documented inthese studies (column 3).A diculty in specifying the hypothesized eect

of each factor on evaluations of ABC systems isthat each study is dierent in ways that draw intoquestion comparability of results. For example,Anderson (1995), Gosselin (1997) and Krumwiede(1998) distinguish dierent stages of ABC imple-mentation and find evidence that dierent factorsinfluence success at each stage. Foster andSwenson (1997), McGowan and Klammer (1997)and Malmi (1997) study specific ABC imple-mentation projects, while other studies gather dataat the firm level. Moreover, Foster and Swensondocument somewhat dierent correlates for fourdierent measures of ABC implementation suc-cess. Finally, McGowan and Klammer collectdata from dierent informants at an ABC imple-mentation site and find evidence of a shift in themean level of evaluation that is associated withrespondents involvement with the ABC project.Other studies rely almost exclusively on informantsfrom accounting functions (of the firm or the ABCsite). In sum, comparing empirical studies of thedeterminants of ABC implementation eectivenessrequires strong assumptions about invariance ofthese relations across time, respondent groups,measures of eectiveness and units of analysis.In spite of caveats concerning comparability of

prior studies, the research findings are remarkably

2 McGowan and Klammer (1997) document a significant

dierence in the level of satisfaction with ABC between those

who developed the ABC data and those who use the data. They

assume a common (stable) model for both populations with

dierences reflected only in a shift in the mean level of satis-

faction.

S.W. Anderson, S.M. Young / Accounting, Organizations and Society 24 (1999) 525559 527

Table1

CandidatevariablesforanalysisofdeterminantsofevaluationsofABCimplementation:contextualfactorsandprocessfactorsidentified

intheresearchliterature

Candidatevariables

Literature

sources(s)a

Hypothesized

eecton

evaluationof

ABCb

Contextualfactors

Processfactors

Research

designor

variable

mappingd

Individual

factors

Organizational

factors

ABCproject

managem

ent

Team

processc

Individualcharacteristics

Disposedto

change

A,C,E,F

+,+

,+,+

X

X

CHANGE

Productionprocessknowledge

A+

X

X

interviews

Roleinvolvem

ent

A,E

+,+

,X

XCOMMIT,

VALUES,AND

Mvs

D

Individualreceived

ABCtraining

G0

X

Mvs

D

Organizationalfactors

Centralization

A,D

+,+

X

X

C1vs

C2

Functionalspecialization

A,B

,0

X

X

C1vs

C2

Form

alization/jobstandardization

D+

X

X

C1vs

C2

Verticaldierentiation

D+

X

C1vs

C2

Form

alsupportinaccountingfunction

B,C

0,+

XX

C1vs

C2

Support

A,B,C,E,F,G,H

+,+

,+,+

,+,0,+

XX

Topmanagem

entsupport

MSUPPORT,

Localmanagem

entsupport

MIN

VOLVE,

Localunionsupport

USUPPORT

Internalcommunications

A+

X

X

C1vs

C2

Extrinsicreward

system

sA,B,E,G

+,+

,+,+

XX

REWARD

ABCtraininginvestm

ents

A,B,E,G,H

+,+

,+,+

,+

X

XTeam

Technologicalfactors

Complexityforusers

A,C

,

X

Team

Compatibilitywithexistingsystem

sA,B,C,I

+,0,+

,+

X

XN/A

Relativeimprovem

entsoverexisting

system

(accuracy

andtimeliness)

A,C,H

+,+

,0

X

XIN

FOQUAL

Relevance

tomanagersdecisionsand

compatibilitywithfirm

strategy

A,B,C,E,H,I

+,+

,+,+

,+

X

XIM

PCOST

Task

characteristics

Uncertainity/lack

ofgoalclarity

A,B,E,H

,0,,0

X

Team

Variety

A+

XTeam

Workerautonomy

A+

X

Team

Workerresponsibility/personalrisk

A

X

Team

Resourceadequacy

B,C,E

+,+

,+

X

RESOURCES

AvailabilityofABCsoftware

B,C

0,+

X

N/A


Externalenvironment

Heterogeneityofdem

ands

A,C,D,H,I

+,+

,+,+

,0

X

TURB

Competition

A,C,H

+,+

,+

X

COMPETE

Environmentaluncertainity

A,C,D,F,I,

,,+

,+,+

X

Likelihoodoflayo

s

LAYOFF

Growth

opportunities

NOGROW

Laborrelations

LABOR

Importance

ofsiteto

company

IM

PPLT

Externalcommunications/external

experts

A,B,

+,0

X

X

C1vs

C2and

Team

aSourcelegend:A:Anderson(1995).Andersonconstructsalistoffactorspreviouslyimplicatedin

ABCimplementationoutcomes

from

theresearchliterature

and

from

practitioneraccountsofimplementationsandprovidesevidence

onhowthesefactorsinfluence

onefirm

sadoptionofABC.Recentem

piricalresearch:B:Shields

(1995);C:InnesandMitchell(1995);D:Gosselin(1997);E:FosterandSwenson(1997);F:Malmi(1997);G:McG

owanandKlammer(1997);H:Krumwiede(1998);I:

ChenhallandLangfield-Smith(1998)

bFoster

andSwenson(1997),McG

owanandKlammer

(1997)andMalmi(1997)studyspecificABCimplementationsitesrather

thanfirm

-levelimplementation.

Anderson(1995),Krumwiede(1998)andGosselin

(1997)distinguishcorrelatesofdierentstages

ofimplementation.Because

westudyplantsthatimplementedABC

aftertheform

alcorporateadoptionofABC,wefocusonfactorsthatstage-specificstudiesfindto

influence

theadoptionandadaptationstages.Forstudiesthatdo

notdistinguishstage-specificeectsorthatem

ploymultiplemeasuresofABCprojectoutcomes,wereportthesignofthecorrelationbetweenofthevariableandoverall

evaluationsoftheABCproject.

cVariablesassociatedwithintrateamprocessesoftheABCdesignteam(e.g.groupcohesion,teamleadership)arenotexamined

inthisstudy.

dVariabletreatm

entlegend:C1vsC2indicatesavariablethatdiersbetweenbutnotwithincompanies.M

vsDindicatesavariablethatdiersbetweenmanagersand

ABCdevelopersbutnotwithineach

group.ThedesignationN/A

indicatesthatthevariableisnotexamined

inthisstudybecausethereisneitherwithinfirm

norbetween

firm

variation(e.g.allsitesuseacommonsoftwarepackageandnositeintegratedABCwithotherinform

ationsystem

spriorto

theendofthestudy).Teamindicatesa

variablethatreflectsintrateamprocessesoftheABCdevelopmentteam.TheeectsofintrateamprocessesonABCsystem

evaluationsarenotconsidered

inthispaper

(seeAndersonetal.,1999).WordsinUPPERCASEarevariablenamesoffactorsthatareexamined

inthispaper.Interviewsdesignatesanassociationthatisexamined

inthispaperusinginterviewdatabutnotsurvey

data.


consistent. Although some studies fail to docu-ment a statistically significant eect (denoted 0),in only one case (environmental uncertainty) dostudies find significant but conflicting eects. Inthis case, Innes and Mitchell (1995) investigateuncertainty associated with the likelihood of ABCdata threatening respondents employment (e.g.cost reduction through layos), while other studiesfocus on the potential for ABC data mitigatinginformational uncertainties and promoting betterdecision-making. Thus, this is a case of dierentdefinitions of uncertainty rather than substantivedisagreement between the studies results. In sum-mary, there is widespread agreement in the aca-demic literature on broad correlates of ABCimplementation eectiveness. Sources of instabilityin the relation are less well understood. Theseobservations are the departure point for this study,which tests a structural framework among corre-lates of ABC system eectiveness and examines thestability of the structural model.

2.2. The proposed structural framework

Although the empirical literature has progressedfrom case studies and anecdotes to systematicevidence on correlates of ABC project outcomes,

there is little correspondence between empiricalstudies and studies that propose process theoriesof ABC implementation (Anderson, 1995; Argyris& Kaplan, 1994; Kaplan, 1990; Shields &Young,1989). Process theories hypothesize thatproject outcomes depend critically on the imple-mentation process and on contextual factors relatedto the external environment. Process theories ofABC implementation are similar to Rogers (1962,1983) model of organizational change and innova-tion. In Rogers model, managers consideration ofan innovation is motivated or constrained by cir-cumstances in the firms external and internal envir-onment and by characteristics of the individualevaluating the innovation what we refer to col-lectively as contextual factors. Subsequent evalua-tions of the innovation are influenced bycomparison between the innovation, the status quo,and alternative innovations, and by factors relatedto the innovation experience what we term pro-cess factors. Contextual factors influence the processof implementation and the evaluation of the result-ing ABC system. Process factors only influence eva-luations of the ABC system. This structure thatprocess theories hypothesize is depicted by arrowsthat connect the boxes in Fig. 1 (ignore for nowrelations among process factors).

Fig.1. Structural model of ABC implementation.


Process theories distinguish from the list of cor-relates in Table 1 those that relate to the context inwhich the evaluation of ABC is conducted including factors related to organizational contextand factors related to the individual asked to ren-der an evaluation and those that relate to theprocess of implementing ABC. This distinction isreflected in columns 47 of Table 1. The categoriesare not perfectly separablefor example, organi-zational norms with respect to functional speciali-zation may be mirrored in how the ABC project ismanaged (e.g. as an accounting project or as amulti-disciplinary project). Nonetheless, theseparation is reasonably straightforward. Con-textual factors include those related to the organi-zation (column 4) and those related to theindividual asked to evaluate the ABC system (col-umn 5). Implementation process factors are alsodivided into two types: those that reflect interac-tions between the ABC project team and theorganization (column 6), and those that reflect theinternal functioning of the ABC project team(column 7, e.g. communications and goal clarityamong team members). The organizational litera-ture discusses the relation between project outcomesand internal team processes (e.g. Bettenhausen,1991; Cohen, 1993; Cohen & Bailey, 1997). How-ever, because these research questions are not clo-sely related to the accounting literature that weextend, are motivated by dierent organizationaltheories and demand a dierent unit of analysis,we consider the variables in column 7 outside thescope of this paper.3 We focus instead on thestructure and stability of relationships between thevariables in columns 46 and evaluations of ABCsystems.

2.3. Research questions

Two sets of related research questions are con-sidered. The first research questions are related to theobjective of testing the descriptive validity of processtheories of ABC implementation. Specifically, weinvestigate whether there are associations between:

1.1 evaluations of ABC systems and contextualvariables that represent individual andorganizational circumstances;

1.2 evaluations of ABC systems and the imple-mentation process; and,

1.3 the ABC implementation process and con-textual variables that represent individualand organizational circumstances.

These research questions are depicted in Fig. 1as arrows between three groups of variables: con-textual and process factors and implementationoutcomes. Questions 1.1 and 1.2 have been con-sidered in previous empirical research on corre-lates of ABC implementation eectiveness.Question 1.3, which links process theories of ABCimplementation and theories of organizationchange to the existing empirical literature, is aunique contribution of this study.A second set of research questions is motivated

by the earlier observation that the third column ofTable 1 can not be constructed without assumingvery strong forms of model stability. We explorethe validity of these assumptions in two ways.First, we use field research to explore criteria thatour respondents employ in evaluating ABC sys-tems. We then investigate how the model of ABCevaluation is aected by the evaluation criterion.Second, our research design and sample selectionpermits us to test for forms of model stabilitysuggested by previous studies. Thus, we explore:

2.1 what criteria are used by managers andABC system developers to evaluate ABCimplementation eectiveness;

2.2 do the associations examined in researchquestions 1.11.3 dier for dierent evalua-tion criteria; and,

2.3 are the associations examined in researchquestions 1.11.3 stable across firms, acrossrespondents with diering involvement inthe ABC project, and across sites with ABCsystems that are of dierent maturity?

In summary, this paper attempts to link empiricalstudies of correlates of ABC implementation withprocess theories of ABC implementation (questions1.11.3) and provides evidence on model stabilityacross a number of dimensions (questions 2.12.3).

3 We investigate questions related to intrateam processes of

designing and maintaining ABC systems in a second paper

from this study (Anderson, Hesford & Young, 1999).


3. Research design

The research design is defined by three choices:selection of firms and specific ABC implementationprojects for study and selection of qualified respon-dents for each project. Evaluating process models ofABC implementation necessitates an understandingof the firms approach to implementing ABC andaccess to several ABC implementation projects ateach firm. A research design that employs field-based research oers this level of understanding andaccess; however, costs of field research and the timeto develop relationships with corporate partnerslimit the sample size. We study two automobilemanufacturing firms, both with mature corporateABC programs and many ABC implementationsites. In the sections that follow, we discuss thefirms programs for implementing ABC and ourapproach for selecting sites for study.

3.1. ABC implementation in two automobilemanufacturers

The US auto industry is an appropriate settingfor studying the applicability of models of organi-zational change to ABC implementation becausefirm-wide implementation demands developingABC models for many of remote locations andbecause in 1995 ABC was a mature technology fortwo of the firms. Previous research that examinesABC adoption by the firm finds that large organi-zations with hierarchical structures, centralizeddecision-making and significant job standardiza-tion are more likely to adopt ABC (Gosselin,1997). Moreover, ABC is attractive to firms incompetitive environments that demand con-tinuous cost reduction (Chenhall & Langfield-Smith, 1998), particularly when existing cost sys-tems fail to support decisions related to costreduction. In the early 1980s, the then Big 3 USauto manufacturers fit this characterization. Con-sequently, it is not surprising that when ABCbecame visible in the practitioner literature (e.g.Cooper, 1988), at least two firms began experi-menting with it and adopted it by 1991. Anderson(1995) investigates the correspondence of a modelof innovation with one companys eight yearexperience of moving from problem awareness, to

experimentation and evaluation of alternative costsystems, and finally, to adoption of ABC.4 Thispaper continues the exploration, adding a secondfirm that adopted ABC shortly after the first firm,and shifting the unit of analysis to individualsinvolved in 21 ABC implementation projects.After the firms adopted ABC as a corporate

initiative, corporate ABC groups were charged withsupporting implementation at all manufacturingsites. Nonmanufacturing sites were to follow, as thecorporate group gained implementation expertise.The process of implementing ABC at a site dierssomewhat between the two companies. Althoughboth companies espouse a theory of activity basedmanagement in which process or activity costsare as important as product costs Company 2 hasmade this more central to the objective of ABCimplementation than has Company 1. Neither com-pany used ABC in budgeting or performance eva-luation at the time of our study, although both wereexperimenting with these possibilities. Company 2used an outside consulting firm to oversee site-levelABC implementation projects and augmented siteteams with corporate ABC group members. Com-pany 1 relied solely on employees at the site,although divisional liaisons were available to assistthe team. Assistance most often took the form ofcomputer software technical support.In spite of these dierences, there are striking

similarities in the firms approach to ABC imple-mentation. Both firms had a corporate mandate toimplement ABC that allowed plants to implementABC within a three to five year window of localmanagements choosing. Both firms used whatLindquist and Mauriel (1989) term a depthstrategy of implementing ABC fully in a few sitesand adding sites over time, rather than a breadthstrategy of simultaneously implementing a morelimited version of ABC across all sites. Neitherfirm used ABC data for inventory valuation or inperformance evaluations of managers (e.g. calcu-lating ABC-based cost variances) at the close ofour study. Indeed both firms were advised by their(dierent) external auditors to delay using ABC

4 Anderson (1995) uses the firm as the unit of observation

and limits consideration of specific ABC projects to prototype

projects that were critical to the firm-level adoption decision.


for inventory valuation until all sites installed ABCsystems. Both firms standardized development andmaintenance of ABC models over time and used thesame PC-based software. Both firms managed ABCimplementation from a corporate group that reportsthrough the finance function, but attempted to gainsupport from the operations function. Both firmsasked that the local ABC team be multi-dis-ciplinary; however, most teams included at leastone accountant or budget analyst and the teamalways reported to the plant controller. Finally,both firms introduce the ABC project with anexecutive awareness session for functional managersat the site, training for ABC developers, and sub-sequent management reviews of project milestones.

3.2. Selection of ABC implementation sites andcritical informants

Anderson (1995) observed that, after the firmsdecision to adopt ABC, continued corporate sup-port of the ABC initiative did not depend uponsuccess of specific ABC projects. Rather, followinga period of controlled experimentation when pro-ject success was critical, the corporate initiativeacquired a life of its own. This pattern is con-sistent with research on innovation adoption andillustrates a critical distinction between individualand organizational adoption of innovations:

Because organizations are complex hierarchicalsystems, contradictory part-whole relations areoften produced when system-wide innovationsare introduced. An organization-wide innova-tion of change developed by one organizationalunit often represents an externally imposedmandate to adopt the innovation to other,often lower-level, organizational units. Thus . . .top management . . . may express euphoriaabout the innovation it developed for the entireorganization, while frustrations and opposi-tions to that same innovation are expressed bythe aected organizational units (Van de Ven,1993, p. 285).

Studies of ABC implementation that rely on asingle senior managers evaluation of a firms ABCsystem may reflect an average assessment of

widely diering project outcomes or biases of topmanagement. To address these concerns, wegather data from several ABC projects within eachfirm and use local informants for each project.ABC sites are selected using three criteria. First,

we select sites that initiated ABC development afterthe corporate decision to implement ABC but dur-ing dierent periods of the firms ABC implementa-tion history. We exclude experimental or prototypeprojects to avoid confounding routine implementa-tions with those that were linked to the organiza-tional decision to adopt ABC.5 Inclusion of projectsfrom dierent periods permits investigation of tem-poral influences on ABC system evaluations.A second factor in site selection is an attempt to

include all auto manufacturing production pro-cesses. Approximately half of the sites from eachfirm produce components that are unlikely to beoutsourced (termed core components), including:major metal stampings, foundry castings, engines,and transmissions. The remaining sites produceperipheral components and face external competi-tion. Selecting core and peripheral components sitesmaximizes variation in the external environmentfactors of Table 1 (subject to the limitation that thestudy occurs within a single industry), allowinginvestigation of the relation between these con-textual factors and ABC system evaluations. Inaddition to traditional manufacturing sites, the ser-vice parts distribution groups of both firms areincluded. We were unable to match a contiguousstamping and assembly plant that was included forone firm; thus, the sample includes eleven sites fromone firm and ten sites from the other firm.A final factor in selecting sites is the perceived

success of the ABC project. We wish to study sitesthat represent the full range of implementationoutcomes. One firm adopted ABC in 1991 andconsequently had fewer ABC projects from whichto choose. Meeting the first two criteria for siteselection virtually exhausted the population ofABC sites; thus, it is unlikely that we were directedtoward exceptional projects. The second firmadopted ABC in 1989 and had over 150 ABCmodels at the inception of our study. To guard

5 Anderson (1995) provides evidence of the highly charged

political environment of prototype projects.


against the firm directing us to relatively successfulprojects, we examined an independent assessmentof ABC project success. In a related study weconducted a survey of eight division-level ABCmanagers; assessments of 50 ABC implementationprojects. Seven of the proposed sites were coveredby the survey. Responses to questions related toABC project outcomes indicate that the seven sitesspan the full range of evaluations.Selection of qualified informants about local ABC

implementation projects is guided by the literatureon organizational change and evidence on respon-dent eects in ABC system evaluation. McGowanand Klammers (1997) finding that managerscharged with using the ABC system hold dierentopinions about the system compared to those whodevelop the ABC data suggests two groups ofrespondents. The organizational literature goes fur-ther, arguing that organizational change is a processof changing the beliefs and behaviors of individuals(Marcus & Weber, 1989). Although key individualsmay play a disproportionate role in convincing oth-ers to adopt an innovation, it is rare that a singleindividual can unilaterally adopt innovations onbehalf of an organization. Moreover, the beliefs andbehaviors of individuals toward a particular inno-vation are shaped by their unique, individual cir-cumstances within the organization.6 We attempt toobtain full participation from two populations ofcritical informants: ABC system developers and thesites management team (e.g. the plant manager andfunctional managers who report to the plant man-ager), and measure individual characteristics(Table 1) that are hypothesized to influence theserespondents evaluations of ABC7

3.3. Data collection

Each research site was visited for two daysbetween March and November of 1995. Surveyswere mailed to the site one week before the visitand respondents brought the completed survey tothe interview, or, if they were not available for aninterview, mailed it to the researchers. Similarsurveys were administered to ABC developers andmanagers. Survey questions about individualmotivation, organizational circumstances and theABC project were developed from establishedscales in the organizational and information sys-tems literatures (e.g. Davis, 1989; Davis, Bagozzi& Warshaw, 1989; Jaworski & Young, 1992;McLennan, 1989; Robinson, Shaver & Wrights-man, 1991; Seashore, Lawler, Mirvis & Cammann,1983; Van de Ven & Ferry, 1980). At times wordingchanges were necessary to fit the organizationalcontext and the specifics of ABC system develop-ment. Questions dealing with the implementationprocess were based on information gathered in thefirm-level study of ABC implementation and, whereapplicable, by using question structures that aresimilar to related scales (e.g. for involvement in sys-tem design, scales for task involvement wereused). A survey pre-test administered to ten corpo-rate and divisional ABC employees at each firm, allwith experience implementing ABC, was used torevise the survey questions. We received 265 surveys 176 management surveys and 89 ABC developersurveys (Table 2).8

The profiles of the respondents do not diervisibly between firms. Company 2 uses slightly lessexperienced people as ABC system developers

6 See Pedhazur and Schmelkin (1991) for a discussion of

respondent eects associated with factors such as age, gender,

and educational attainment, as well as a variety of personality

traits. Weick (1995) describes individual processes of interpret-

ing, or making sense of the environment.7 Although some have argued that eective use of ABC

requires involvement of employees at the lowest level of the

organization, the firms of this study have not disseminated

ABC data to this audience. Thus we have no basis for investi-

gating the associations between workers attitudes and ABC

system outcomes and were discouraged from doing so by both

firms. Production workers are occasionally included in the sur-

vey population as ABC system developers when they served on

development teams.

8 To our knowledge 15 people (all managers) who were tar-

geted to complete a survey failed to do so. Of these, twelve were

managers who claimed to be unfamiliar with ABC either by

virtue of recently joining the plant or because their job respon-

sibilities did not cause them to use the system (e.g. five were

Personnel department managers). Three plant managers who

appeared qualified to complete the survey refused to do so

because of the time involved; however, even these managers

agreed to be interviewed and the interviews suggested that this

group included both advocates and opponents of the ABC

approach. The non-respondents were scattered across thirteen

of the 21 sites. In sum, we do not believe that this aspect of

non-response has induced significant bias in the data.


than does Company 1 evidenced by fewer yearson average with the company and in the depart-ment from which they joined the ABC project.There are no dierences between the firms in edu-cational attainment or ABC training developerstypically receive 30 hours of training in ABC andmanagers typically receive no ABC training.Managers have longer tenure with the firms thando ABC developers; however, by virtue of pro-motions and company transfers, tenure at the siteis not appreciably dierent between managers andABC developers.Interviews were conducted with 236 of the 265

survey respondents. Although most intervieweesreturned their surveys at the start of the interview,they did not provide their names in the body ofthe survey and specific survey responses were notdiscussed during the interview. Interviews fol-lowed a loose structure aimed at supplementingthe survey data. On average 10 interviews wereconducted at each plant, ranging in duration fromapproximately 30 minutes, for functional man-agers with little awareness of the ABC project, to 4hours for system developers with years of systemdesign and maintenance experience. With twoexceptions, all interviews were taped and transcribedfor content analysis.

4. Measurement of variables and process structure

4.1. Contextual variables

A limitation of having only two firms is thatorganizational factors that reflect firm character-istics (e.g. centralization, functional specialization)are confounded (e.g. Table 1, column 8, C1 vsC2). We investigate the stability of our modelacross firms; however, the research design doesnot permit us to distinguish among alternativeexplanations for firm eects. Studies that use alarge number of firms, each providing data onseveral implementation sites are needed to investi-gate the eect of firm characteristics on imple-mentation project outcomes. This study focuses onorganizational factors that are more local asa result of dierent products, processes and peopleat the sites.To explore research question 1.1, we examine

the significance of direct associations betweentwelve contextual factors (Table 1, column 8).Three variables hypothesized to influence indivi-duals evaluations of ABC are considered: (1) theextent to which the individual believes that changeis warranted (CHANGE) what the organiza-tional psychology literature terms felt need for

Table 2

Distribution of survey respondents by site and company

Number of respondents Number of respondents

Plant processes Total ABC developers Plant management

Company 1 Company 2 Company 1 Company 2

Core manufacturing

Major stampings 22 3 2 10 7

Contiguous stamping and assembly 14 0 4 0 10

Foundry 28 4 2 10 12

Engine manufacture 31 5 9 9 8

Engine manufacture 24 2 5 10 7

Transmission assembly 40 7 5 15 13

Secondary manufacturing

Parts assembly 19 3 2 7 7

Parts machining and assembly 19 4 4 5 6

Parts machining and assembly 18 2 3 8 5

Electronics assembly 27 6 2 12 7

Other: service parts distribution 23 10 5 5 3

Total 265 46 43 91 85


change; (2) individual commitment to the orga-nization (COMMIT); and (3) the extent to whichthe individual identifies with the values of theorganization (VALUES). Of the four variablesidentified as individual contextual factors in Table1, two are captured in these measures. A thirdfactor, ABC training received, was measured;however, because most managers receive no train-ing and most developers receive 3040 hours oftraining, this variable is confounded with otherfactors that dier between managers and ABCdevelopers (e.g. role involvement in the ABC sys-tem). A fourth factor the individuals knowl-edge of production processes and job experience,was explored in interviews only.Eight organizational contextual factors are

hypothesized to influence evaluations of the ABCsystem and management involvement in theimplementation process: (1) the extent to whichindividual performance is linked to rewards(REWARD)9 (2) the competitive environment(COMPETE); (3) the quality of existing informa-tion systems (INFOQUAL); (4) environmentalturbulence (TURB); (5) the likelihood of employeelayos (LAYOFF); (6) impediments to plantgrowth (NOGROW); (7) the perceived importanceof the plant to the company (IMPPLT); and (8)the perceived importance of cost reduction to theplant (IMPCOST). Advocates of ABC claim thatnew cost data are most valuable when competitionor limited growth prospects cause firms to focuson cost reduction. COMPETE, NOGROW andIMPCOST measure these motivations for adopt-ing ABC. Cost reduction eorts often producereductions in employment (Innes and Mitchell,1995). In a unionized environment with con-tractual employment guarantees, managers areoften reluctant or unable to reduce employeeheadcount. As a result, many of the prospectivebenefits of ABC systems may be unrealizable. Ameasure of the likelihood of layos (LAYOFF) is

used to capture this potential deterrent to ABCimplementation. In the same vein, the quality ofhistorical managementlabor relations (LABOR)is a ninth contextual factor that is hypothesized toinfluence the degree to which the local union sup-ports the ABC implementation project (but notmanagers evaluations of the ABC system). Evenin firms that face heightened competition, someoperations are less threatened than others. Selec-tion of core and peripheral component plantsmaximizes the observed range of competitionwithin each firm. The perceived importance of thesite (IMPPLT) to the firm is included as a poten-tial mitigating factor to external competition.Organizational theorists argue that there are limitsto the amount of change that an organization canabsorb. Site-specific turbulence (TURB) is a mea-sure of concomitant changes that compete withABC for management attention. Finally, within afirm, sites often have diverse legacy informationsystems that are more or less eective in meetingmanagers information needs. Adoption of newinformation technology such as ABC systemsdepends upon fit with and incremental improve-ment upon existing systems (Kwon & Zmud,1987). A measure of respondents beliefs about thequality of existing information systems (INFOQ-UAL) is used to examine how the current infor-mation environment influences managerscommitment to or evaluation of the ABC system.

4.2. Process variables related to ABCimplementation

Appropriate process variables for analysis andthe relation between process variables dependupon firm-specific ABC implementation strategies.Previous studies that consider the relation betweenprocess variables and ABC project outcomes testfor correlation between a wide range of possibleprocess variables without knowledge ex ante offirms implementation processes. As a result, teststhat pool firms with dierent implementationstrategies can not distinguish between relevantprocess factors that are not statistically correlatedwith ABC outcomes and irrelevant process fac-tors. The ABC implementation process variablesthat we consider are those identified in Table 1,

9 It is important to note that REWARD does not measure

the extent to which individuals believe that they will be rewar-

ded if they implement ABC or use ABC data. Rather,

REWARD measures general reward expectancy, because man-

agement control practices and incentives were not changed to

promote ABC use in any of the sites.


column 6. The hypothesized structure between theprocess variables (Fig. 1) was developed prior todata collection based on interviews at the corporatelevel and is described below.The general structure of the firms ABC imple-

mentation process is depicted inside of the boxlabeled ABC Implementation Process Factors inFig. 1. Specifically, firm-level managers committedthe company to ABC implementation prior to theABC project at the research sites. Respondentsopinions about the strength of this commitmentare measured by the variable, MSUPPORT. Themanagement awareness sessions that each firmused to introduce ABC to local managers wasintended to increase managers knowledge of ABCand to secure their involvement in the project.Respondents beliefs about whether local commit-ment was achieved are measured by the variable,MINVOLVE. The proposed relation betweenMSUPPORT and MINVOLVE reflects the direc-tion of influence described above. Both firmsassigned responsibility for implementing ABC tolocal management. Although corporate resourceswere available to augment or support the team,team members were selected and freed from otherresponsibilities (or not) by local managers. Localmanagers were also given discretion in the deci-sion to involve local union leaders in the project.The adequacy of resources committed to the ABCproject is measured with the variable, RESOUR-CES. The degree to which the union was aware ofand involved in the ABC project is measured bythe variable, USUPPORT. The proposed relationbetween MINVOLVE and both RESOURCESand USUPPORT reflects the gatekeeper role thatlocal managers are assigned. The proposed rela-tion between MSUPPORT and USUPPORTreflects a possible flow of influence from top man-agers of the firm, to the local union. Although topmanagers did not intervene directly in local unionaairs, at least one firm noted that the firmsdecision to implement ABC had become a nego-tiating point with labor at the national level.The proposed relation between MSUPPORTand RESOURCES reflects the support that thecorporate ABC group provided developmentteams after local management initiated an ABCproject.

The relationships described above reflect firm-specific implementation processes that have beenignored in previous research. However, findingthat these relations hold is simply evidence of facevalidity of the data rather than evidence on theproposed research questions. To explore researchquestion 1.2 we examine the eects of each processvariable on evaluations of the ABC system.Because implementing ABC is a local managementdecision, we explore research question 1.3 byexamining the association between contextual fac-tors and local managers involvement in the ABCproject (MINVOLVE).

4.3. Evaluation measures of the ABC system

As in previous studies we employ an overallevaluation of the ABC system (OVERALL) thatallows respondents to self-define the evaluationcriteria. However, as research question 2.1 indi-cates, this raises the question: What criteria areembedded in overall assessments of ABC sys-tems? Content analysis of 236 taped interviews isused to explore this question.10 Full text tran-scripts of the 236 interviews were searched for keywords related to ABC system evaluations. Searchresults yielded 129 respondents opinions.11 The129 respondents represent 20 of the 21 sites andare split in approximately the same proportion asthe survey respondents (Table 2) between the firmsand between ABC developers and managers. Afteridentifying discussions of ABC system evaluation,the transcripts were read by a researcher and aresearch assistant. Three evaluation criteriaemerged: (1) use of ABC data for cost reduction;(2) use of ABC data for process improvements;and, (3) improved accuracy of product cost infor-mation relative to the traditional cost system. The

10 An analysis software package designed for non-numerical,

unstructured data (NU.DIST1) was used. The researcher codes

interview passages related to constructs of interest and attri-

butes of the interviewee. The software uses these codes to create

a structured index that is useful for investigating systematic

response patterns.11 Some interviewees did not believe that they had sucient

knowledge about ABC systems to oer an opinion about sys-

tem eectiveness, while others were not asked to discuss the

issue.


researcher and research assistant independentlycoded the responses as belonging primarily to oneof the three categories. The codes were comparedand dierences were discussed and resolved.Although respondents occasionally combined thefirst and second criteria in their discussion, veryfew respondents discussed the third criterion inconjunction with either of the others. Conse-quently, we combine the first and second groupsto form two groups who dier in the way that theydefine an eective ABC system. In the first groupare 67 respondents who define eectiveness as useof ABC data in cost reduction or process improve-ments. In the second group are 47 respondents whobelieve that increased cost accuracy defines aneective ABC system.12

Contingency tables are used to evaluate theassociation between opinions about evaluationcriteria and: the respondents company; whetherthe respondent worked in a plant that faced sig-nificant external competition; whether the respon-dent was an ABC system developer; whether therespondent claimed to have received training inABC; and the respondents job title. Small samplesizes cause some contingency tables to haveobserved and expected counts that violate asymp-totic assumptions for normal chi-square estima-tions. Consequently, we use exact test proceduresthat do not impose distributional assumptions.Comparing dierences between respondents whoevaluated ABC system eectiveness based on usein cost reduction or process improvement withthose who base their opinion on improved accu-racy of cost data, respondents job title is the onlysignificant (p

Table 3

Summary statistics for manifest variables and latent constructsa

Latent construct Survey items Item Item Std. Cronbachs

(R=reverse coded item) 5=strongly agree, 1=strongly disagree N Mean Dev. std. alpha

Measures of ABC implementation success

OVERALL: overall value of ABC 0.93

1 Despite the implementation challenges, I am convinced that ABC is the

right tool for helping us manage costs in this company

245 3.8 0.75

2 Overall, the benefits of ABC data outweigh the costs of installing a new

system

220 3.6 0.87

3 Supporting ABC is the right thing to do in this company 240 3.9 0.79

4 If I were asked to decide whether this company should continue

implementing ABC, I would vote to continue

240 3.9 0.92

5 In general ABC is a good thing for this company 244 4.0 0.70

ACCURACY: perceived accuracy of ABC data 0.65

1 (R) The ABC costs do not seem reasonable to me based on what I know about

this plant

223 3.8 0.81

2 The results from the ABC model matched my intuition about costs of

production

233 3.6 0.77

3 Data from the ABC model provides an accurate assessment of costs in

this plant

240 3.7 0.72

USE: perceived use of ABC data 0.70

1 Information from the ABC model has had a noticeable positive impact

on this plant

228 2.9 0.83

2 (R) I am reluctant to use ABC data in place of costs from the traditional

cost system

232 3.4 0.96

3 (R) The ABC model has not been used and has been gathering dust since it

was completed

233 3.5 0.97

4 Data from the ABC model are used for special costs studies 229 3.2 1.0

ABC implementation process variables

MSUPPORT: top management support 0.77

1 This companys top managers have provided visible support for the ABC

initiative

252 3.4 1.1

2 Support for implementing ABC in this company comes from both the

manufacturing operations and finance groups

254 3.2 1.0

3 Support for implementing ABC in this company is widespread 250 2.9 1.0

MINVOLVE: local management knowledge of and involvement in ABC 0.72

1 The managers of this plant are knowledgeable about the theory of ABC 243 3.4 0.80

2 Most managers of this plant are capable of using ABC data to reduce costs 238 3.1 1.0

(continued on next page)

S.W

.Anderso

n,S.M

.Young/Acco

unting

,Organiza

tionsandSociety

24(1999)525559

539

Table3(continued)

Latentconstruct

Survey

item

sItem

Item

Std.

Cronbachs

(R=reversecoded

item

)5=stronglyagree,1=stronglydisagree

NMean

Dev.

std.alpha

3Mostmanagersoftheplantwereinvolved

indetermininghowthei

departmentalexpenseswereallocatedto

activitiesandproducts

228

3.5

1.0

4When

thedevelopersoftheABCmodelmetwithlocalmanagers,

they

received

suggestionsfromthemanagers

205

3.4

0.91

USUPPORT:unionsupport

0.77

1Thelocalunionisreceptiveto

theconceptofABC

190

2.9

0.87

2Thelocalunionwasinvolved

indecisionsthata

ectedtheABCmodel

192

2.6.

0.99

RESOURCES:adequacy

ofresourcesfortheABCdevelopmentproject

0.63

1Thepeoplewhodeveloped

theABCmodelhadtheequipmentand

materialsneeded

todotheirjob

214

3.9

0.63

2Thepeoplewhodeveloped

theABCmodelhadaccessto

thepeople

fromwhomthey

needed

togetinform

ation

224

4.0

0.60

3TheABCdevelopmentprojectwasadequatelysta

ed

toinsure

completionofthetask

inthetimeallotted

210

3.3

0.90

Contextualvariables

COMPETE:competitiveenvironment

0.54

1Futuredem

andfortheproductsthatthisplantproducesisuncertain

264

2.6

1.0

2Competitivepressurescouldcausethisplantto

close

264

3.3

1.0

3Thisplanthashadalotofmanagem

entturnoverinrecentyears

263

3.3

0.98

4Thisplantfacescompetitionfromotherplantsinthiscompanyforbusiness

241

3.3

1.2

5Thisplantfacessti

competitionfromoutsidecompaniesforbusiness

264

3.8

0.97

INFOQUAL:quality

ofother

inform

ationsystem

s0.76

1Mostofthedatarequired

foragoodABCmodelarereadilyavailable

inthisplant

222

3.0

1.1

2Theplantsinform

ationsystem

sgenerallyprovidedatathatare

accurateandupto

date

246

3.0

1.0

3(R)

Theinform

ationsystem

softhisplantcontainmanydataerrors

238

2.8

1.0

TURB:environmentalturbulence

0.61

1Theworkingenvironmentatthisplantchangesconstantly

264

2.9

0.88

2Manufacturingprocessesatthisplantchangeallthetime

261

3.0

0.96

3New

managem

entprogramsareintroducedallthetimeinthisplant

265

3.5

0.82

LAYOFF:history

ofem

ployee

layo

s

0.70

1(R)

Thethreatoflayo

sorcutbacksto

hourlyworkersislow

264

2.4

0.99

2Thisplanthashadmajorcutbacksandlayo

sinrecentyears

264

2.3

1.1

NOGROW:impedimentsto

plantgrowth

0.71

1Gettingauthorizationto

hirenew

employeesforthisplantisdicult

263

4.0

0.93


2Wehavedicultygettingauthorizationto

hirereplacementsfor

employeeswhoretireorleavethisplant

263

3.6

1.1

LABOR:quality

oflaborrelations

0.87

1Atthisplanttheunionandmanagem

enthavesimilargoals

261

2.9

1.1

2(R)

Relationsbetweenlaborandmanagem

entneedto

beimproved

atthisplant

261

2.4

0.92

3Laborandmanagem

entinthisplantwork

welltogether

262

3.2

0.98

IMPPLT:importance

oftheplantto

company

0.78

1Thisplantisoneofthemostimportantmanufacturingsitesofthiscompany

241

4.0

0.87

2Thisplantproducesproductsthathaveamajorinfluence

onthiscompanys

profitability

264

4.4

0.70

3Thisplantiscriticalforthesuccessofthiscompany

262

4.0

1.0

IMPCOST:importance

ofcostreductionto

plant

0.40

1Thisplantscostreductioneortsareimportantto

thecompany

264

4.3

0.53

2Costreductionisthemostimportantobjectiveinthisplant

264

3.0

0.94

3(R)

Costreductionisnotamajorconcern

inthisplant

263

4.2

0.82

CHANGE:feltneedforchange

0.58

1Changesinthewaywework

inthisplantareneeded

265

3.8

0.85

2(R)

Thereisnoneedforthisplantto

changethewayitdoesthings

265

4.2

0.73

3Iwouldliketo

seechangesinplantpoliciesandprocedures

264

3.6

0.71

COMMIT:commitmentto

theorganization

0.73

1Iamproudto

work

forthiscompany

264

4.3

0.65

2(R)

Ifeelverylittleloyaltyto

thiscompany

264

4.2

1.0

3Iamproudto

work

forthisplant

264

4.2

0.77

4(R)

Ifeelverylittleloyaltyto

thisplant

265

4.1

1.1

VALUES:sharedorganizationalvalues

0.75

1Myvaluesandthevaluesofthiscompanyarequitesimilar

264

3.7

0.69

2Myvaluesandthevaluesatthisplantarequitesimilar

263

3.6

0.82

REWARD:reward

expectancy

0.84

1In

thisplant,highqualitywork

increasesmychancesforaraise,

abonus,orapromotion

264

3.6

1.0

2In

thisplant,financialrewardsaretied

directlyto

perform

ance

264

3.1

1.0

3Theabilityto

reduce

costsisrewarded

inthisplant

264

3.3

0.95

4In

thisplant,highperform

ance

isrecognized

andreward

263

3.3

0.92

aThistableprovidesthetextofthesurvey

item

sanddescriptivestatisticsforeach

oftheitem

sthatcomprise

thelatentconstructsusedinsubsequentanalysis.Item

responseindicatesthenumberofrespondentsthatcompletedthequestionoutofapossiblesampleof265respondents.Descriptivestatisticsandscalereliability(Cron-

bachsalpha)arereported

forthereducedsub-sampleof112respondentswhocompletedallquestions(e.g.withlistwisedeletionofmissingobservations).


an assessment, and (2) apprehension aboutrespondent anonymity. Understandably, itemswith the highest non-response are those related tomanagement-union relations, a politically sensitivetopic. Higher response rates for environmentalcontext variables, which depend on general plantknowledge alone, compared to ABC implementa-tion process variables, which require knowledge ofthe ABC project, suggests that inadequate knowl-edge may also explain dierential response rates.14

Earlier we argued that individuals are theappropriate unit of analysis for modeling thedeterminants of evaluations of ABC systemsbecause organizational theory suggests significantwithin-site variation in perceptions of contextualand process factors likely to influence theseassessments. The counter argument is that surveyscompleted by individuals who observe the sameABC system should be identical and that variationsimply reflects measurement error. Table 4 pre-sents evidence on the existence of respondenteects. Analysis of variance is used to estimate afixed eects, hierarchical linear model with firm,site, and respondent eects (Bryk & Raudenbush,1992). The hierarchical model nests respondentswithin sites and sites within firms. Joint F-tests on

Table 4

Analysis of company, plant and respondent eectsa

Variable p-Value on F-statistic on

firm eects

p-Value of F-statistic on

plant eects within firms

p-Value of F-statistic on

respondent eects within

plants, within firms

Model

adjusted (R2)

OVERALL 0.000 0.000 0.000 0.67

ACCURACY 0.016 0.000 0.000 0.45

USE 0.000 0.000 0.000 0.33

MSUPPORT 0.000 0.000 0.000 0.49

MINVOLVE 0.000 0.000 0.000 0.39

USUPPORT 0.844 0.000 0.000 0.65

RESOURCES 0.016 0.000 0.000 0.20

COMPETE 0.001 0.000 0.043 0.10

INFOQUAL 0.017 0.000 0.000 0.46

TURB 0.263 0.002 0.000 0.21

LAYOFF 0.124 0.000 0.000 0.49

NOGROW 0.407 0.000 0.000 0.48

LABOR 0.000 0.000 0.000 0.48

IMPPLT 0.423 0.000 0.000 0.53

IMPCOST 0.637 0.018 0.887 0.00

CHANGE 0.101 0.000 0.000 0.27

COMMIT 0.693 0.223 0.000 0.38

VALUES 0.005 0.000 0.000 0.67

REWARD 0.559 0.000 0.000 0.52

a For each dependent and independent variable, the p-values of F-statistics from an ANOVA model of nested firm, site and

respondent eects are reported. The estimated fixed eects model treats respondents as nested within sites, which are in turn nested

within firms. The model estimated for responses to items that comprise each construct (X) is:

X intercept 1 Firm 2 Site Firm 3 Respondent Site Firm "

The results indicate significant respondent eects for all but one variable. This supports the claim that evaluation of ABC systems is

significantly related to individual perceptions and that individuals are an appropriate unit of analysis (Bryk & Raudenbush, 1992;

Goldstein, 1987; Hannan, 1991).

14 The analysis treats as missing both items with no response

and selection of the Not Applicable response. Not Applic-

able was oered selectively as an option for some questions

related to ABC where we anticipated problems of inadequate

knowledge and wanted to guard against forcing a neutral

response of 3.


the significance of each eect indicates significantfirm, plant and respondent eects for all three mea-sures of ABC implementation eectiveness. Simi-larly, three of the four process variables diersignificantly at all three levels. F-tests of union sup-port evince plant and respondent eects, but notfirm eects. Eleven of the 12 contextual variablesshow strong evidence of respondent eects. There issignificant agreement about the importance of cost(IMPCOST) within a site; however, the importanceof cost diers significantly between sites of a firm.After site eects are included, there is no dierencebetween the firms in the importance attributed tocost. The overwhelming significance of respondenteects for these constructs is consistent with orga-nizational research that documents the importanceof unique, individual circumstances in shapingindividual beliefs about and behaviors toward aparticular innovation. The data support using indi-viduals as the unit of observation and argue againstdata reduction (e.g. averaging survey responses of asite), which would be appropriate if random mea-surement error was the primary source of with-insite disagreement (Goldstein, 1987; Hannan, 1991;Seidler, 1974; Rousseau, 1985).

5. The relation between evaluations of ABCsystems and contextual and process variables

Structural equation modeling (SEM) is used toinvestigate the correspondence of the data with Fig.1. SEM is amethod of assessing the correspondenceof a proposed set of associations and implied var-iance and covariance relationships with observedsample variances and covariances (Bollen, 1989). Amaximum likelihood fitting function is the basis forassessing goodness of fit.15 Maximum likelihoodestimates are presented for the coecients of the

measurement model, which relates the survey itemsto latent variables, and the structural model, whichrelates latent variables to one another. The relationbetween a latent variable, i, and a survey item thatcomprises it, xj, is: xj liji ij, where lij is theloading, or degree of association between the latentvariable and the manifest variable, and ij is mea-surement error associated with the survey item. Thelatent variable approach mitigates measurementerror in individual survey items and provides betterestimates of the relation between latent variables.None of the confidence intervals for correlations ofthe latent variables with one another includes thevalue of one; a necessary but insucient conditionfor the constructs to be distinct from one another(discriminate validity).

5.1. The relation between overall evaluations ofABC systems and process and contextual variables

Sample size limitations preclude estimating thefull model depicted in Fig. 1 simultaneously.Consequently, the analysis proceeds in three steps.In the first step the relation between contextualvariables and overall evaluation of the ABC sys-tem (OVERALL) is examined. Untabulatedresults indicate that the only contextual variablesthat exhibit significant (p

that are associated with evaluations of the ABCsystem or local managers involvement in the ABCproject in earlier steps (INFOQUAL andREWARD). An additional contextual variable, thequality of historical labor-management relations(LABOR), is considered a potential antecedent ofunion support of the ABC project.16 Table 5 pre-sents coecient estimates of the measurementmodel (Panel A) and structural equation model(Panel B) for the relation between ABC imple-mentation process variables, the limited set ofcontextual variables and respondents overall eva-luation of the ABC system. Reported results arebased on analysis of the covariance matrix for thesurvey items and a sample in which observationswith missing values are excluded (listwise dele-tion). Alternative treatments of missing values(e.g. pairwise deletion or imputation of missingvalues) do not alter the qualitative results. Boot-strapping methods (500 samples with replacement)are used to generate approximate p-values for thesignificance of total eects of the contextual andprocess variables on overall evaluations of theABC system (Stine, 1989).The standardized estimated loadings of survey

items on latent constructs in Panel A are sig-nificant at the p

Table5

MaximumlikelihoodestimationoftherelationbetweencontextualandprocessvariablesandoverallABCimplementationsuccess

PanelA:standardized

coe

cientsforthemeasurementmodelsa

Survey

item

OVERALL

MSUPPORT

MIN

VOLVE

USUPPORT

RESOURCES

INFOQUAL

REWARD

LABOR

10.90

0.91

0.64

0.72

0.61

0.57

0.80

0.79

20.76

0.64

0.60

0.88

0.71

0.81

0.67

0.74

30.88

0.68

0.60

0.46

0.79

0.66

0.95

40.90

0.69

0.89

50.86

PanelB:maximumlikelihoodestimatesofthecoe

cientsofthestructuralmodelt-statistics(inparentheses)b

Estimateddirecteects

Totaleects(approximatep-value)

OVERALL

MIN

VOLVE

USUPPORT

RESOURCES

Predictedeect

Estimatedeect

Independentvariables

MSUPPORT

0.20

0.30

0.19

0.17

+0.29

(1.68)*

(4.02)***

(1.63)

(2.33)**

(0.012)**

MIN

VOLVE

0.35

0.86

0.21

+0.10

(1.21)

(3.08)***

(1.47)

(0.735)

USUPPORT

0.34

+

0.34

(2.50)**

(0.016)**

RESOURCES

0.76

+

0.76

(2.58)***

(0.042)**

INFOQUAL

0.25

0.18

0

.23

(2.08)**

(1.92)*

(0.132)

REWARD

0.19

0.07

+0.19

(1.96)**

(0.87)

(0.042)**

LABOR

0.17

0.06

(2.00)**

(0.030)**

Modelfitstatistics

R2=0.56

R2=0.55

R2=0.39

R2=0.44

CFI=

0.932RMSEA=0.054,90%

C.I.=

[0.039,0.068]

aAllloadingsaresignificantat0.01(two-tail)level.

bThesample(N=112)includes

onlyobservationswithnomissingvalues.Theresultsare

qualitativelysimilarwhen

data

imputationmethodsare

employed.Two

measuresofoverallmodelfitare

provided:Bentlers(1989)ComparativeFitIndex

(CFI)andtheRootMeanSquare

ErrorofApproximation(RMSEA)withits90

percentconfidence

interval.Bootstrappingmethods(500sampleswithreplacement)areusedto

generateapproximatep-values(two-tail)forthesignificance

ofthetotal

eectsofcontextualandproceduralvariablesonOVERALL.Thep-valuesareapproximationsbecausebootstrappingmethodsdonotmakedistributionalassumptions.

***,**,*Statisticallysignificantatthep

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