-
e psycal
Matthew Hall *
ity and psychological empowerment. This result highlights the
role of cognitive and motivational mechanisms inexplaining the eect
of management accounting systems on managerial performance. In
particular, the results indicate
hensive PMS include a more diverse set of perfor-mance measures,
and performance measures thatare linked to the strategy of the rm
and provideinformation about parts of the value chain (Chen-hall,
2005; Malina & Selto, 2001; Nanni, Dixon, &
eserved.
* Tel.: +44 0 20 7955 7736; fax: +44 0 20 7955 7420.E-mail
address: [email protected]
Available online at www.sciencedirect.com
Accounting, Organizations and Soci0361-3682/$ - see front matter
2007 Elsevier Ltd. All rights rthat comprehensive PMS inuences
managers cognition and motivation, which, in turn, inuence
managerialperformance. 2007 Elsevier Ltd. All rights reserved.
Introduction
In recent years organizations have sought todevelop more
comprehensive performance mea-surement systems (PMS) to provide
managers
and employees with information to assist in man-aging their rms
operations (Fullerton & McWat-ters, 2002; Ittner, Larcker,
& Randall, 2003; Lillis,2002; Malina & Selto, 2001; Ullrich
& Tuttle,2004). Prior research indicates that more
compre-Department of Accounting and Finance, London School of
Economics and Political Science, Houghton Street,
London WC2A 2AE, United Kingdom
Abstract
This study examines how comprehensive performance measurement
systems (PMS) aect managerial performance.It is proposed that the
eect of comprehensive PMS on managerial performance is indirect
through the mediating vari-ables of role clarity and psychological
empowerment. Data collected from a survey of 83 strategic business
unit man-agers are used to test the model. Results from a
structural model tested using Partial Least Squares regression
indicatethat comprehensive PMS is indirectly related to managerial
performance through the intervening variables of role clar-The eect
of comprehensivsystems on role clarity, p
and manageridoi:10.1016/j.aos.2007.02.004erformance
measurementhological empowermentperformance
www.elsevier.com/locate/aos
ety 33 (2008) 141163
-
tionsVollman, 1992; Neely, Gregory, & Platts,
1995).Comprehensive PMS have been popularised intechniques such as
the balanced scorecard (Kaplan& Norton, 1996), tableau de bord
(Epstein &Manzoni, 1998) and performance hierarchies(Lynch
& Cross, 1992).
In this paper I examine how comprehensive PMSaect managerial
performance. Prior research hasfocused on the relation between
comprehensivePMS and organisational performance (perceivedor
actual) (Chenhall, 2005; Davis & Albright,2004; Hoque &
James, 2000; Ittner, Larcker, &Randall, 2003; Said,
HassabElnaby, & Wier,2003), and on the use of multiple
performance mea-sures in performance evaluation judgements(Banker,
Chang, & Pizzini, 2004; Lipe & Salterio,2000; Schi &
Homan, 1996). However, there islimited empirical research that
examines the behav-ioural consequences of comprehensive PMS
(Ittner& Larcker, 1998; Webb, 2004). Studies examininglinks
between management control systems andorganisational outcomes
assume that such systemsaect the behaviour of individuals within
the orga-nization, which then facilitates the achievement
oforganisational goals. However, as Chenhall (2003)notes, this
assumption involves broad leaps in logicand there is no compelling
evidence to suggest thatthese links exist. Similarly, Covaleski,
Evans, Luft,and Shields (2003) argue that studies at the
organi-sational level of analysis remain somewhat limitedbecause
they are based upon assumptions about,rather than a detailed
investigation of, individualbehaviour.
Further, there is little empirical research thatexamines whether
control system componentshave direct and/or indirect eects on work
perfor-mance (Shields, Deng, & Kato, 2000). This isimportant
because there can be theoretical dier-ences between direct- and
indirect-eects modelsthat can have practical implications
(Shieldset al., 2000). Psychological theories indicate
thatcognitive and motivational mechanisms are likelyto explain the
relation between comprehensivePMS and managerial performance
(Collins, 1982;Ilgen, Fisher, & Taylor, 1979; Luckett &
Eggleton,1991). As such, I examine how the relationbetween
comprehensive PMS and managerial
142 M. Hall / Accounting, Organizaperformance can be explained
by the interveningvariables of role clarity and
psychologicalempowerment.
Recent research indicates that the informationdimensions of
management accounting practices,such as PMS, are not captured
eectively by labelssuch as the balanced scorecard (Chenhall,
2005;Ittner, Larcker, & Randall, 2003). In particular,Ittner,
Larcker, and Randall (2003) argue thatresearchers need to devise
improved methods fordetermining what rms mean by contemporaryPMS.
As such, in this study, I draw on descrip-tions of PMS from the
performance measurementliterature to develop a denition of a
comprehen-sive PMS. Based on this denition, I develop aninstrument
to measure empirically the comprehen-sive PMS construct.
Data collected from a survey of strategic busi-ness unit (SBU)
managers are used to examinehow comprehensive PMS is related to
managerialperformance. I focus on SBU managers as theinformation
provided by comprehensive PMS isexpected to be useful at this
managerial levelbecause of SBU managers information require-ments.
The results show that comprehensivePMS is indirectly related to
managerial perfor-mance through the intervening variables of
roleclarity and psychological empowerment. Consis-tent with theory,
the results highlight the role ofcognitive and motivational
mechanisms inexplaining the eect of management accountingsystems on
managerial performance. In particular,the results indicate that
comprehensive PMS inu-ences managers cognition and motivation,
which,in turn, inuence managerial performance. Thiscontributes to
prior research that has examinedthe direct and indirect eects of
management con-trol systems on work performance (Shields et
al.,2000), and also extends the limited body of priorresearch that
has examined the eect of manage-ment control system attributes on
psychologicalempowerment (Smith & Langeld-Smith,
2003;Spreitzer, 1995, 1996) and role clarity (Chenhall
&Brownell, 1988). Finally, the study responds tocalls to
develop improved methods for examin-ing the attributes of
management accountingpractices by developing a reliable and valid
ins-trument to measure the comprehensive PMS
and Society 33 (2008) 141163construct.
-
integration of measures with strategy and across
empowerment (H5).
Comprehensive performance measurement systems
Recent research has emphasised the importanceof examining the
information dimensions of con-temporary PMS (Chenhall, 2005;
Ittner, Larcker, &Randall, 2003; Luft & Shields, 2003). The
per-formance measurement literature has identiedseveral important
characteristics of more compre-hensive PMS. Malina and Selto (2001)
argue thata comprehensive PMS consist of a parsimoniousset of
critical performance measures. Results oftheir study show that the
balanced scorecard wasconsidered comprehensive when it provided
anoverall measure of business performance. Onemanager stated that
the BSC is trying to give usa broader business set of measures of
success thanmore traditional nancial or market share. Itwraps a set
of things together that makes sense
tionsthe value chain) is expected to be useful for SBUmanagers
because their jobs require considerationof multiple aspects of the
SBUs operations andconsideration of strategic issues. Thus,
compre-hensive PMS is expected to provide importantinformation for
SBU managers to enhance theirrole clarity and psychological
empowerment,and, in turn, enhance managerial performance.
The theoretical model is shown in Fig. 1. For theThe remainder
of the paper contains four sec-tions: the next section develops the
theoreticalmodel, including presentation of the hypotheses.The
research method, including sample selectionand variable
measurement, is then presented. Thisis followed by presentation of
the results. The nalsection discusses the results and concludes
thepaper.
Theoretical development and hypotheses
formulation
A major premise behind the development ofmore comprehensive PMS
is that they can helpto improve managerial performance (Atkinson
&Epstein, 2000; Epstein & Manzoni, 1998; Kaplan
&Norton, 1996). Psychological theories indicatethat cognitive
and motivational mechanisms arelikely to explain the relation
between comprehen-sive PMS and managerial performance (Ilgenet al.,
1979). As such, comprehensive PMS is notexpected to have a direct
eect on managerial per-formance. Rather, comprehensive PMS is
expectedto have an indirect eect on managerial perfor-mance by: (1)
clarifying managers role expecta-tions, and (2) providing feedback
to enhancemanagers intrinsic task motivation (Collins,1982; Luckett
& Eggleton, 1991). Thus, theorypredicts that role clarity and
psychologicalempowerment are likely to mediate the relationbetween
comprehensive PMS and managerial per-formance. In particular,
comprehensive PMS areexpected to have positive eects on SBU
managersbehaviour. This is because the information pro-vided by
comprehensive PMS (information aboutthe important parts of the SBUs
operations, and
M. Hall / Accounting, Organizarole clarity path, I argue that
comprehensive PMSenhances role clarity (H1), and role clarity
enhancesmanagerial performance (H2). For the psychologi-cal
empowerment path, I argue that comprehensivePMS enhances
psychological empowerment (H3),and psychological empowerment
enhances mana-gerial performance (H4). I also propose a
positiveassociation between role clarity and psychological
H2
H5
H1
H4
H3
Managerial Performance
Role clarity
ComprehensivePMS
Psychologicalempowerment
Fig. 1. Theoretical model: comprehensive PMS, role
clarity,psychological empowerment and managerial performance.
and Society 33 (2008) 141163 143for managing the business
(Malina & Selto,
-
such, a more comprehensive PMS is one that pro-vides more
comprehensive performance informa-tion to managers, i.e., measures
that fullydescribe the SBUs operations and link to strategyand
across the value chain. In contrast, a less com-prehensive PMS is
one that provides less compre-
tions and Society 33 (2008) 1411632001, p. 70). Ittner, Larcker,
and Randall (2003)argue that a broad set of measures, or
measure-ment diversity, is an important feature of
morecomprehensive PMS. Ittner, Larcker, and Randall(2003, p. 717)
consider measurement diversity assupplementing traditional nancial
measureswith a diverse mix of non-nancial measures thatare expected
to capture key strategic performancedimensions that are not
accurately reected inshort-term accounting measures. Similarly,
Ull-rich and Tuttle (2004) and Henri (2006) argue thatcomprehensive
systems are designed to measureperformance in all the important
areas of the rm.These studies indicate that providing a broad set
ofmeasures that cover dierent parts of the organiza-tions
operations is an important aspect of morecomprehensive PMS.
The integration of measures with strategy andproviding
information about parts of the valuechain is also an important
feature of more compre-hensive PMS. Nanni et al. (1992) argue that
PMSthat integrate actions across functional boundaries,and focus on
strategic results, are critical in sup-porting the new
manufacturing and competitiveenvironments facing organizations. In
addition,the integration of measures with the strategy
andobjectives of the organization provides perfor-mance information
about progress on importantdimensions of performance (Kaplan &
Norton,1996; Malina & Selto, 2001; Malmi, 2001; Nanniet al.,
1992; Neely et al., 1995; Webb, 2004). Morecomprehensive PMS
provide an understanding ofthe linkages between business operations
and strat-egy (Chenhall, 2005).
Thus, the PMS literature indicates that there areseveral
important characteristics of comprehensivePMS, including providing
a broad set of measuresrelated to the important parts of the
organisation,the integration of measures with strategy and val-ued
organisational outcomes, and the integrationof measures across
functional boundaries and thevalue chain (Chenhall, 2005; Henri,
2006; Ittner,Larcker, & Randall, 2003; Malina & Selto,
2001;Malmi, 2001; Neely et al., 1995). Therefore, it isargued that
a comprehensive PMS provides per-formance measures that describe
the importantparts of the SBUs operations and integrates mea-
144 M. Hall / Accounting, Organizasures with strategy and across
the value chain. Ashensive performance information to
managers,i.e., measures that only partially describe theSBUs
operations and contain few (if any) linksto strategy and across the
value chain.
The way in which comprehensive PMS provideenhanced performance
information supplies thebasis for linking comprehensive PMS with
SBUmanagers role clarity and psychological empower-ment.
Individuals at higher levels in the organisa-tion, such as SBU
managers, obtain feedbackabout the results of operations and
work-relatedperformance from PMS (Collins, 1982; Luckett&
Eggleton, 1991). A more comprehensive PMSprovides richer and more
complete feedback aboutoperations and results to SBU managers
(Chen-hall, 2005; Kaplan & Norton, 2001; Malina &Selto,
2001), which is expected to have positiveeects on managers role
clarity and psychologicalempowerment.
Comprehensive PMS and role clarity
Role clarity refers to individuals beliefs aboutthe expectations
and behaviours associated withtheir work role (Kahn, Wolfe, Quinn,
Snoek, &Rosenthal, 1964).1 In this study I examine
whethercomprehensive PMS is related to two aspects ofrole clarity;
goal clarity (the extent to which theoutcome goals and objectives
of the job are clearlystated and well dened) and process clarity
(theextent to which the individual is certain abouthow to perform
his or her job) (Sawyer, 1992). Itis expected that more
comprehensive performanceinformation will help to clarify SBU
managers
1 Kahn et al. (1964) use the term role ambiguity, which refersto
uncertainty regarding parts of an individuals role. In thisstudy
the term role clarity is used. However, this is conceptuallyno
dierent from role ambiguity (Sawyer, 1992). Role clarity
isexpressed as the extent of certainty, rather than ambiguity,
of
role expectations.
-
tionsrole expectations and the appropriate behavioursfor
fullling those role expectations.
Several researchers argue that more comprehen-sive performance
information can help to improverole clarity. Collins (1982) argues
that managementaccounting systems can be used to inform
individ-uals about what is expected of them in their
role.Specically, comprehensive performance informa-tion can serve
to clarify individuals roles in theorganisation by making specic
the goals andappropriate behaviours associated with a work
role(Ilgen et al., 1979).
Comprehensive PMS can increase SBU manag-ers goal clarity by
providing information aboutthe organizations strategies and
operations, whichhelps them to better understand their own
rolewithin the organization. Access to comprehensiveperformance
information allows SBU managersto see the big picture and develop a
referencepoint for understanding their roles within
theirorganization (Bowen & Lawler, 1992; Lawler,1992). More
comprehensive PMS can help to clar-ify and communicate strategic
intent, and can cap-ture dierent dimensions of performance, which
isimportant in describing the organizations opera-tions (Kaplan
& Norton, 1996; Lynch & Cross,1992; Simons, 2000).
Performance feedback aboutbusiness unit operations increases
managers levelof certainty over the requirements of their workrole
(Kahn et al., 1964; King & King, 1990). Assuch, more
comprehensive PMS should improveSBU managers understanding of what
comprisestheir role and what is expected of them, and thusincrease
goal clarity.
Comprehensive PMS can increase process clar-ity by providing
performance information toimprove SBU managers understanding of
thedrivers of performance, the eect of their actionson parts of the
value chain, and the links betweendierent parts of the
organizations operations. Inparticular, more comprehensive PMS can
educateSBU managers about the economics of the busi-ness and the
drivers of costs, revenues and perfor-mance (Kaplan & Norton,
1996; Lynch & Cross,1992; Simons, 2000). Banker et al. (2004)
arguethat the integration of measures across the valuechain can
help individuals to understand cross-
M. Hall / Accounting, Organizafunctional relationships.
Similarly, Malina andSelto (2001) found that the balanced
scorecardwas important for managing the business whenperformance
information was comprehensive andintegrated. As such, more
comprehensiveperformance information is expected to improveSBU
managers understanding of their workrole and thus increase role
clarity, which leadsto H1.
H1: There is a positive relation between com-prehensive PMS and
role clarity.
Role clarity and managerial performance
Individuals require sucient information toperform tasks
eectively. A lack of informationregarding the goals of the job and
the most eec-tive job behaviours can result in eort that is
inef-cient, misdirected or insucient for the task(s),and thus
reduce job performance (Jackson &Schuler, 1985; Tubre &
Collins, 2000). SBU man-agers are likely to be more eective when
theyunderstand what needs to be done and how man-agerial functions
are to be performed. Empiricalresults indicate that role ambiguity
decreases workperformance (Abramis, 1994; Jackson &
Schuler,1985; Tubre & Collins, 2000). These argumentsand
evidence lead to H2:
H2: There is a positive relation between roleclarity and
managerial performance.
Comprehensive PMS and psychological
empowerment
Psychological empowerment refers to increasedintrinsic task
motivation manifested in a set offour cognitions; meaning (the
value placed onwork judged in relation to an individuals own
ide-als or standards), competence (an individualsbelief in his/her
capacity to perform a job withskill), self-determination (an
individuals beliefconcerning the degree of choice they have in
initi-ating and performing work behaviours), andimpact (the extent
to which an individual believes
and Society 33 (2008) 141163 145they can inuence outcomes at
work) (Spreitzer,
-
1995; Thomas & Velthouse, 1990).2 Higher levelsof meaning,
competence, self-determination andimpact reect higher intrinsic
task motivation(Thomas & Velthouse, 1990), and, therefore,
areexpected to result in more focused attention ontasks, greater
eort (intensity) and persistence dur-
146 M. Hall / Accounting, Organizationsing tasks, and improved
task strategies (Mitchell &Daniels, 2003; Pinder, 1998).
Providing adequate performance informationenhances the
development of psychologicalempowerment. Feedback theories from
psychol-ogy indicate that performance information canimprove
psychological empowerment by providinginformation about task
behaviour and perfor-mance (Collins, 1982; Ilgen et al., 1979;
Locke,Shaw, Saari, & Latham, 1981; Luckett &
Eggleton,1991). In particular, intrinsic task motivation
isincreased when managers are provided with feed-back about the
results of operations (Ilgen et al.,1979). The greater the amount
of information pro-vided on a job, the greater will be the
motivatingpotential of the job (Ilgen et al., 1979). This isbecause
performing a task without knowledge ofresults provides little
feedback to managers, whichis likely to be frustrating and
dissatisfying, thusreducing intrinsic motivation (Luckett &
Eggleton,1991).
The empowerment literature also supports thelink between
performance information and intrin-sic motivation. Providing
information about theperformance of the business is essential for
thedevelopment of empowerment (Bowen & Lawler,1992; Spreitzer,
1995, 1996; Quinn & Spreitzer,1997). In contrast, a lack of
information aboutperformance has adverse aects on feelings
ofempowerment (Chiles & Zorn, 1995). In supportof these
arguments, Spreitzer (1995, 1996) foundthat access to cost and
quality performance infor-mation is positively associated with
psychologicalempowerment.
2 Psychological empowerment is a motivational construct andis
therefore distinguished from objective structural factors, suchas
delegation of decision-making authority (Thomas & Velt-house,
1990). Delegation is likely to enhance psychologicalempowerment;
however, it is individuals cognitive interpreta-tions of such
structural factors that leads to stronger psycho-logical
empowerment, rather than some objective reality (Chiles
& Zorn, 1995; Spreitzer, 1996; Thomas & Velthouse,
1990).As such, SBU managers require informationabout the results of
SBU operations to feel intrin-sically motivated. The
characteristics of compre-hensive PMS (providing performance
measuresthat describe the important parts of the SBUsoperations and
integrating measures with strategyand across the value chain)
provide a rich and rel-atively complete picture of the performance
of thebusiness unit (Chenhall, 2005; Ittner, Larcker, &Randall,
2003; Kaplan & Norton, 2001; Malina& Selto, 2001). Such
information is essentialfor SBU managers because their jobs
requireconsideration of multiple aspects of the SBUsoperations and
consideration of strategic issues.As such, a more comprehensive PMS
providesthe performance information necessary for SBUmanagers to
develop higher levels of psychologicalempowerment. In contrast, a
less comprehensivePMS provides limited and inadequate perfor-mance
information, and thus is likely to limit thedevelopment of SBU
managers psychologicalempowerment.
Comprehensive PMS is expected to increaseSBU managers beliefs
regarding each dimensionof psychological empowerment: meaning,
compe-tence, self-determination and impact. Congerand Kanungo
(1988) argue that performanceinformation is likely to strengthen
individualsbeliefs of meaning and purpose, as managersbelieve they
are valued when they are providedwith the results of operations.
Further, Spreitzer(1995) argues that greater access to
performanceinformation is essential in enabling managers tobelieve
that their work is valuable. A more com-prehensive PMS provides a
rich and relativelycomplete picture of the performance of the
busi-ness units operations, which increases SBU man-agers ability
to judge the value of their work inthe context of the organizations
strategies andoperations. As such, a more comprehensive PMScan make
SBU managers believe their jobs aremore meaningful by helping them
to determinehow their work ts within the broader scope ofthe
organization. Without comprehensive infor-mation about performance,
SBU managers arelikely to place little value on their work
withinthe organization, and thus experience lower levels
and Society 33 (2008) 141163of meaning.
-
tionsGist and Mitchell (1992) argue that competencebeliefs are
strengthened by providing performanceinformation to individuals in
the organisation.This is because performance information
improvesindividuals ability to make assessments of theirperformance
capabilities. By providing informa-tion about business unit
operations, and links tostrategy and the value chain, a more
comprehen-sive PMS provides improved knowledge of results,which is
fundamental for reinforcing a sense ofcompetence (Gist &
Mitchell, 1992; Ilgen et al.,1979; Lawler, 1992; Spreitzer, 1995).
A less com-prehensive PMS provides inadequate knowledgeof results,
and therefore reduces SBU managersbelief in their ability to
perform tasks competently(Conger & Kanungo, 1988; Thomas &
Velthouse,1990).
Comprehensive PMS is expected to increaseself-determination. SBU
managers require infor-mation about where their organization is
headedin order to believe they are capable of taking theinitiative
(Kanter, 1989). Adequate knowledge ofresults is essential for
managers to be able to directand manage their own performance
(Lawler,1992). Managers need to understand how welltheir business
unit is performing to be condentenough to make decisions on their
own (Spreitzer,1995). A more comprehensive PMS provides a richand
relatively complete picture of the businessunits performance, which
increases SBU manag-ers condence to initiate and complete tasks
ontheir own, thus increasing self-determination. Aless
comprehensive PMS provides inadequate per-formance information, and
thus reduces SBUmanagers condence to initiate and regulate theirown
actions.
Comprehensive PMS is also expected toincrease impact. To have an
impact, managersneed to understand how their business unit is
per-forming (Spreitzer, 1995). Further, managersrequire adequate
performance information inorder to believe they can make and
inuence deci-sions that are consistent with the
organizationspriorities (Lawler, 1992). A more comprehensivePMS
strengthens SBU managers knowledge ofoperations and organisational
priorities, andtherefore improves managers ability to inuence
M. Hall / Accounting, Organizaand act in ways that are
consistent with those pri-orities, thus increasing impact. In
contrast, a lesscomprehensive PMS provides limited knowledgeof
organisational priorities and strategies. Withoutsucient knowledge
of results, managers are unli-kely to exert inuence in their work
area (Kraimer,Seibert, & Liden, 1999).
In summary, comprehensive PMS is expected tobe positively
related to each dimension of psycho-logical empowerment, which
leads to H3:
H3: There is a positive relation between com-prehensive PMS and
the four dimensions ofpsychological empowerment.
Psychological empowerment and managerial
performance
Empowered individuals should perform betterthan those
individuals who are less empowered(Liden, Wayne, & Sparrowe,
2000). This is becauseempowerment increases both initiation and
persis-tence of managers task behaviour (Conger &Kanungo, 1988;
Thomas & Velthouse, 1990). Inparticular, higher levels of
psychological empower-ment lead to greater eort and intensity of
eort,persistence, and exibility (Spreitzer, 1995; Tho-mas &
Velthouse, 1990), all of which are behav-iours that enhance
performance (Mitchell &Daniels, 2003; Pinder, 1998).
Each dimension of psychological empowermentis related to
behaviours that enhance managerialperformance. Individuals who
place more mean-ing, or care more, about their work put forth
moreeort and are more committed to their tasks, andthus likely to
persist in the face of obstacles or set-backs (Kanter, 1983; Liden
et al., 2000; Thomas &Velthouse, 1990). Individuals who believe
they canperform well on a task (i.e., feel competent) do bet-ter
than those individuals who think they will fail(Gist &
Mitchell, 1992). Competence results inmore eort, persistence in the
face of obstacles,and more initiative (Bandura, 1977;
Spreitzer,Kizilos, & Nason, 1997; Thomas & Velthouse,1990).
Spreitzer et al. (1997) and Liden et al.(2000) found that
competence was positively asso-ciated with work performance.
Self-determination
and Society 33 (2008) 141163 147results in more eort and
persistence, and greater
-
managers to determine and take actions to com-plete tasks, and
thus should increase self-determi-nation. A lack of role clarity is
likely to makeindividuals believe they are helpless and thusreduce
the impact they have in their work area
tered to SBU managers within Australian manu-facturing
organizations. I obtained a list of 1000
tions and Society 33 (2008) 141163exibility to adapt to changing
situations and cre-ate improved task strategies (Deci & Ryan,
1987;Thomas & Velthouse, 1990). Work performanceis enhanced
when managers believe they haveautonomy over how their work is to
be accom-plished (Miller & Monge, 1986). In relation toimpact,
individuals who believe they can inuenceoutcomes at work are more
likely to actually havean impact, and hence be more eective.
Impactresults in more eort and greater persistence inthe face of
obstacles (Abramson, Seligman, &Teasdale, 1978; Ashforth, 1989;
Spreitzer et al.,1997; Thomas & Velthouse, 1990). Spreitzeret
al. (1997) and Liden et al. (2000) found thatimpact was positively
associated with work perfor-mance. These arguments and evidence
lead to H4:
H4: There is a positive relation between the fourdimensions of
psychological empowerment andmanagerial performance.
Role clarity and psychological empowerment
Finally, drawing on prior results, I hypothesizea positive
relation between role clarity and psycho-logical empowerment.
Unless SBU managers havea clear sense of their responsibilities and
how toachieve them, it will be dicult for them to knowif they have
the necessary skills and abilities to per-form their tasks
adequately (i.e., feel empowered).As such, role clarity is expected
to increase eachdimension of psychological empowerment; mean-ing,
competence, self-determination and impact.Spreitzer (1996) argues
that it is only when individ-uals understand their roles that those
roles cantake on personal meaning. Clear lines of responsi-bility
and clear task requirements are related tocompetence (Conger &
Kanungo, 1988; Gist &Mitchell, 1992; Kahn et al., 1964). SBU
managerswith clear work goals, and an understanding ofhow to
achieve those goals, are likely to believethey can perform their
job with skill and thus feelmore competent. Managers who are
uncertain oftheir role expectations are likely to hesitate andnot
take the initiative due to uncertainty, and thusexperience lower
levels of self-determination (Spre-
148 M. Hall / Accounting, Organizaitzer et al., 1997). High
levels of role clarity enableSBU managers of Australian
manufacturing rmsfrom a commercial mailing list provider. Due
tocost constraints, 400 managers were selected toform the sampling
frame for the study. I used afour-step implementation strategy
following therecommendations of Dillman (2000); telephonecalls to
check data accuracy3, a questionnairepackage with cover letter,
questionnaire andreply-paid envelope, a reminder postcard (senttwo
weeks after questionnaire package), and a fol-low-up phone call
(made two weeks after thereminder postcard). To encourage
completion ofthe questionnaire, participants were promised asummary
of the results and informed that their
3 The contact details of 31 of the 400 SBU managers couldnot be
conrmed because they had ceased employment with thecontact
organisation, the phone number was disconnected ordid not answer,
or the organisation had ceased operations. As(Spreitzer et al.,
1997). In contrast, individualswho understand their work roles are
more likelyto take actions and decisions that inuence resultsin
their work area (Sawyer, 1992). Prior researchshows that higher
levels of role ambiguity arerelated to lower levels of
psychological empower-ment (Smith & Langeld-Smith, 2003;
Spreitzer,1996). This analysis indicates that role clarity
willincrease each dimension of psychological empow-erment, which
leads to H5:
H5: There is a positive relation between roleclarity and the
four dimensions of psychologicalempowerment.
Research method
Sample selection and data collection
I collected data using a questionnaire adminis-such, the
questionnaire was sent to 369 SBU managers.
-
responses were anonymous. Participants were alsoprovided with a
practitioner article on PMS as atoken incentive (Davila, 2000;
Dillman, 2000).
Of the 369 distributed questionnaires, 83 werereceived, which
provides a response rate of22.5%.4 The response rate is similar to
thosereported in recent accounting (Baines & Lang-eld-Smith,
2003; Moores & Yuen, 2001) andnon-accounting (Gordon &
Sohal, 2001; Samson &Terziovski, 1999; Terziovski & Sohal,
2000) sur-veys of SBU managers in Australian manufactur-ing
organizations. Due to the relatively lowresponse rate, I
investigate the possibility of non-response bias. First, I compared
the SBU size
pany policy not to respond to voluntary surveys,which are
similar to the reasons for non-responsereported in other studies
(for example, Baines &Langeld-Smith, 2003; Chenhall, 2005;
Subraman-iam & Mia, 2003). These tests indicate that there isno
signicant non-response bias in the sample.
Demographic information was collected fromrespondents regarding
job tenure, company ten-ure, age, gender, SBU size (number of
employees),and main manufacturing industry. Table 1 reportsthe
descriptive statistics for the demographic vari-ables. The average
age of respondents was 46.84years with an average job tenure of
5.14 yearsand an average company tenure of 10.64 years.Average SBU
size was 336.13 employees. Eighty-two respondents were male and one
was female.Table 2 reports the manufacturing industry classi-cation
of respondents SBUs.
Table 1Descriptive statistics for demographic variables
Variable Minimum Maximum Mean St Dev
Job tenure(years)
1 25 5.14 5.95
Company tenure(years)
1 37 10.64 8.37
Age (years) 26 64 46.84 8.38SBU size (no.of employees)
10 4100 336.13 497.03
M. Hall / Accounting, Organizations and Society 33 (2008) 141163
149and industry representation of the 83 respondentsto the original
list of 1000 SBUs. An independentsamples t-test shows that the mean
sample SBUsize (X 336:13) is not signicantly dierent fromthe mean
original list SBU size (X 566:93)(t = 1.400, p > 0.10).
Furthermore, a v2-test showsthat the proportion of SBUs in each
industry cat-egory is not signicantly dierent between thesample
SBUs and original list SBUs (v2 = 5.981,degrees of freedom = 8, p
> 0.10). Second, I com-pared early respondents (rst 20%) to late
respon-dents (last 20%) for all constructs of interest(demographic
and model variables). Results (notreported) show that there are no
signicant dier-ences for any variables. In addition, during the
fol-low-up phone calls I discussed with approximately40
non-respondents their reason(s) for not com-pleting the
questionnaire. These reasons were timepressures, receiving too many
surveys, and com-
4 16 cases contained missing data: 14 cases with one
itemmissing, one case with two items missing, and one case withfour
items missing. Littles MCAR test revealed that themissing data were
missing completely at random (MCAR)(v2 = 4.424, degrees of freedom
= 516, p > 0.10). As the missingdata is MCAR, any imputation
method can be used (Hair,Anderson, Tatham, & Black, 1998). As
such, the data werereplaced using the expectationmaximisation (EM)
method inSPSS. The EM approach is an iterative two-stage process
wherethe E-stage makes the best estimates of the missing data and
theM-stage makes parameter estimates assuming the missing dataare
replaced. This occurs in an iterative process until thechanges in
the estimated parameters are negligible and themissing values are
replaced (Hair et al., 1998; Little & Rubin,1987). This process
resulted in a complete data set of 83
responses.n = 83.
Table 2Manufacturing industry classication
ANZSICa manufacturing industryclassication
Frequency %
21 Food, beverage and tobacco 8 9.6422 Textile, clothing,
footwear andleather
3 3.61
23 Wood and paper products 6 7.2324 Printing, publishing and
recordedmedia
3 3.61
25 Petroleum, coal, chemical andassociated products
12 14.46
26 Non-metallic mineral products 4 4.8227 Metal products 11
13.2528 Machinery and equipment 25 30.1229 Other 11 13.25
Total sample 83 100
a ANZSIC Australia and New Zealand Standard Industrial
Classication.
-
on the role of their PMS in providing performanceinformation.
For all nine items, respondents wereasked to indicate on a 7-point
Likert scale(1 = not at all to 7 = to a great extent) the extentto
which each characteristic was provided by theirbusiness units PMS.
The Appendix providesdetails of the explanatory statement and lists
theitems in the scale.
Because the scale has not been used in priorresearch, I
performed several tests to examine itspsychometric properties prior
to including thescale in the PLS measurement model. As reportedin
Table 3, the results of an exploratory factoranalysis show that the
nine-item scale is unidimen-sional, with each item loading on the
single factorabove 0.70. The Cronbach alpha for the nine-item
tions and Society 33 (2008) 141163Variable measurement
The questionnaire obtained information oncomprehensive PMS,
psychological empowerment,role clarity and managerial performance.
Estab-lished scales were used for each variable,
exceptcomprehensive PMS. The development of thequestionnaire
involved a review by three seniormanagement accounting academics
with experi-ence in survey design. I also pilot tested the
ques-tionnaire with four SBU managers (not part ofthe sample), who
completed the questionnaireand participated in a brief interview.
The reviewprocess and the pilot test resulted in minor changesto
the wording of some items and to the layout ofthe
questionnaire.
Ittner, Larcker, and Randall (2003) argue thatimproved methods
are needed for determiningwhat rms mean by contemporary PMS, such
asthe balanced scorecard. Prior research relating tocomprehensive
PMS has used scales that examinethe extent to which a PMS contains
a series ofspecic performance measures (for example,Hoque &
James, 2000). A limitation of this typeof instrument is that it
assumes that the perfor-mance measures contained in the instrument
arerepresentative of the specic types of performancemeasures used
by the rms in the sample. Firmsmay use similar nancial performance
measures;however, non-nancial and/or strategic measuresare likely
to be unique to each rm (Lipe & Salte-rio, 2000). In addition,
this type of scale may notcapture the strategic linkages of more
comprehen-sive PMS (Hoque & James, 2000). As such, Ideveloped a
new scale to capture the comprehen-sive PMS construct. The scale
consists of nineitems. Five items relate to the extent to which
thePMS provides a variety of performance informa-tion about the
important parts of the SBUs oper-ations. The remaining four items
were drawn fromChenhall (2005), and relate to the extent of
inte-gration of measures with strategy and across thevalue chain.
The explanatory statement indicatedthat we were interested in the
extent to which thePMS provides information about the operationsof
the respondents business unit. This was doneto help ensure that
when SBU managers were
150 M. Hall / Accounting, Organizaresponding to the statements,
they were focusedscale is 0.95; well above acceptable limits
(Nunally,1978). I also examined the extent to which the
scaleconverged with an alternative measure of the com-prehensive
PMS construct. Respondents were pro-vided with two descriptions of
a PMS (reproducedin the Appendix). The rst description related to
acomprehensive PMS (coded 1); the seconddescription related to a
partial or less compre-hensive PMS (coded 0). Respondents
indicatedwhich of the two descriptions better representedtheir PMS.
The use of a forced-choice responseformat is consistent with the
principle of usingmaximally-dissimilar forms of ratings when
assess-ing convergent validity (Campbell & Fiske, 1959;Murphy
& Davidshofer, 1998). The point-biserial
Table 3Factor loadings for nine-item comprehensive
performancemeasurement system (CPMS) scale from an exploratory
factoranalysis
Item Factor loading
CPMS1 0.915CPMS2 0.782CPMS3 0.843CPMS4 0.817CPMS5 0.896CPMS6
0.864CPMS7 0.852CPMS8 0.739CPMS9 0.836
Eigenvalue 6.350% Variance explained 70.559%n = 83.
-
correlation between the nine-item scale and the age or above
average on each item. The Mahoneyet al. (1965) scale is frequently
used to measuremanagerial performance in accounting studies(Chalos
& Poon, 2000; Chong & Chong, 2002;Marginson & Ogden,
2005; Otley & Pollanen,2000; Parker & Kyj, 2006; Wentzel,
2002). Severalresearchers argue that self-report measures of
per-formance are valid and tend to exhibit less bias
M. Hall / Accounting, Organizations and Society 33 (2008) 141163
151forced-choice scale is 0.66 (p < 0.001), which pro-vides
strong support for the convergent validityof the nine-item scale.5
In addition, an indepen-dent samples t-test shows that the mean
score onthe nine-item scale is signicantly higher for
thoserespondents who indicated a comprehensivePMS (X 5:507)
compared to those respondentswho indicated a partial PMS (X
3:827)(t = 7.867, p < 0.001). This supports the ability ofthe
nine-item scale to distinguish between moreand less comprehensive
PMS. The reliability andvalidity of the comprehensive PMS scale
isassessed further in the PLS measurement model.
Established scales are used to measure role clar-ity,
psychological empowerment, and managerialperformance, with their
psychometric propertiesassessed in the PLS measurement model.
Goalclarity and process clarity are measured with twove-item scales
drawn from Sawyer (1992).Respondents were asked to indicate on a
7-pointLikert scale (1 = very uncertain to 7 = very cer-tain) the
extent to which they were certain oruncertain about aspects of
their job.
Psychological empowerment is measured withSpreitzers (1995)
12-item scale, with three itemsfor each empowerment dimension:
meaning, com-petence, self-determination and impact. Respon-dents
were asked to indicate on a 7-point Likertscale (1 = strongly
disagree to 7 = strongly agree)the extent to which they agreed or
disagreed witheach item.
As respondents are anonymous, it is not possibleto obtain
supervisor ratings of managers perfor-mance. As such, managerial
performance is mea-sured by a self-rated nine-item scale developed
byMahoney, Jerdee, and Carroll (1965). The scaleassesses managerial
performance along eightdimensions related to planning,
investigating, coor-dinating, evaluating, supervising, stang,
negotiat-ing and representing, and also includes an
overallassessment of performance. Respondents wereasked to indicate
on a 7-point Likert scale (1 = wellbelow average to 7 = well above
average) theextent to which their performance was below aver-
5 I calculated the score for each respondent on the
nine-item
scale as an average of the nine items.than supervisor ratings
(Dunk, 1993; Marginson& Ogden, 2005; Parker & Kyj, 2006).
In addition,prior research indicates that self-rated
subjectivemeasures of subordinate performance are highlycorrelated
with superiors subjective ratings of sub-ordinate performance and
objective measures ofsubordinate performance (Furnham &
Stringeld,1994; Heneman, 1974; Venkatraman & Ramanu-jam, 1987).
The reliability and validity of the scalesis examined in the PLS
measurement model.
Partial Least Squares regression
I use PLS regression analysis to test the hypoth-eses in this
study. PLS is a latent variable modellingtechnique that
incorporates multiple dependentconstructs and explicitly recognises
measurementerror (Fornell, 1982), and has been used in a num-ber of
accounting studies (Anderson, Hesford, &Young, 2002; Chenhall,
2004, 2005; Ittner, Larc-ker, & Rajan, 1997; Vandenbosch,
1999). PLS isparticularly suited to this study because it
makesminimal data assumptions and requires relativelysmall sample
sizes (Wold, 1985).6
PLS comprises a measurement model and astructural model. The
measurement model speci-es relations between observed items and
latentvariables. The structural model species relationsbetween
latent constructs. In PLS the measurementand structural models are
estimated simultaneously
6 Mardias (1970) test of multivariate kurtosis revealed thatthe
data are multivariate non-normal (t = 26.076, p <
0.001).However, unlike structural equation modeling techniques
suchas LISREL, PLS does not require normally distributed
data.Because PLS is a regression based technique, it requires
tencases for the most complex regression (Chin, 1998; Van-denbosch,
1999). In this study, the most complex regression isthat with
managerial performance as the dependent variable,with eight
independent variables, suggesting a minimum sample
size of 80 cases.
-
(Barclay, Thompson, & Higgins, 1995). However,the PLS model
is typically interpreted in twostages. First, the reliability and
validity of the mea-surement model is assessed. Second, the
structuralmodel is assessed (Barclay et al., 1995). Thisensures
that the constructs measures are reliable
removed from the scale and not used in further
scores for each variable are above 0.80, which dem-
152 M. Hall / Accounting, Organizations and Society 33 (2008)
141163analysis. The factor loadings from the nal PLSmeasurement
model are reported in Table 4.
I assess the reliability of each variable using For-nell and
Larckers (1981) measure of compositereliability and Cronbachs
(1951) alpha. As shownin Table 5, the composite reliability and
alpha
7 I obtained the PLS results using PLS Graph Version 3.0.8 An
exploratory factor analysis (oblique rotation) of the
managerial performance scale shows two factors with eigen-values
greater than one, with items MP1MP6 and MP9loading on the rst
factor, and items MP7 and MP8 loading ona second factor. Thus, the
low factor loadings for MP7 andMP8 arise because they do not form
part of a unidimensionaland valid before assessing the nature of
the rela-tions between the constructs (Barclay et al., 1995;Hair et
al., 1998; Hulland, 1999). As such, theresults from the measurement
model are presentedrst followed by an examination of the
hypothes-ised relations between the constructs.7
Results
Measurement model
Statistics from the PLS measurement model areused to examine the
psychometric properties of thevariables. First I examine the factor
loadings foreach variable. All items load on their
respectiveconstructs; however, two items from the manage-rial
performance scale have factor loadings below0.5 (Hulland, 1999)
(item MP7 = 0.461 and itemMP8 = 0.246). Low item loadings add very
littleto the explanatory power of the model whilepotentially
biasing the estimates of the parameterslinking the constructs
(Chin, 1998; Hulland, 1999).Further tests show that the reason the
two itemshave low factor loadings is because they do notform part
of a unidimensional managerial perfor-mance scale.8 As such, items
MP7 and MP8 aremanagerial performance scale (Barclay et al.,
1995).onstrates acceptable reliability (Nunally, 1978).Convergent
validity of the variables is assessed
by examining the average variance extracted(AVE) statistics.
Table 5 shows that the AVE foreach variable is 0.50 and above,
which demon-strates adequate convergent validity (Chin, 1998;Hair
et al., 1998).
The AVE statistic is also used to assess discrim-inant validity
by comparing the square root of theAVE statistics to the
correlations among the latentvariables (Chin, 1998). This tests
whether a con-struct shares more variance with its measures thanit
shares with other constructs (Fornell & Larcker,1981). Table 5
shows that the square roots of theAVEs (diagonal) are all greater
than the respectivecorrelations between constructs. In addition,
Table4 shows that each item loads higher on the con-struct it
intends to measure than on any other con-struct (Barclay et al.,
1995; Chin, 1998). The resultsof these two tests demonstrate
adequate discrimi-nant validity. Overall, the results from the
PLSmeasurement model indicate that each constructexhibits
satisfactory reliability and validity.
Tests of hypotheses
I estimate a structural model in PLS to test thehypotheses. In
addition to the hypothesized paths,I also include job tenure in the
structural model tocontrol for the endogeneity concern that more
ten-ured employees have access to more informationand also feel
more psychologically empowered(Chenhall & Moers, in press). The
objective ofPLS is to maximise variance explained rather thant,
therefore prediction-orientated measures, suchas R2, are used to
evaluate PLS models (Chin,1998). The R2 for each endogenous
variable isshown in Table 6. PLS produces standardised bsfor each
path coecient, which are interpreted inthe same way as in OLS
regression. As PLS makesno distributional assumptions,
bootstrapping (500samples with replacement) is used to evaluate
thestatistical signicance of each path coecient(Chin, 1998).9
9 Statistical signicance is determined using the reported
original PLS estimates and bootstrapped standard errors.
-
MEA
0.497
tionsTable 4Factor loadings from nal PLS measurement model
Item CPMS GC PC
CPMS1 0.920 0.431 0.196
M. Hall / Accounting, OrganizaAlthough there is a positive
correlation betweencomprehensive PMS and managerial performance(see
Table 5), Table 6 shows that comprehensivePMS is not associated
with managerial perfor-mance (b 0:030; t 0:298; p > 0:10. As
PMS2 0.786 0.316 0.188 0.368CPMS3 0.837 0.280 0.135 0.404CPMS4
0.810 0.362 0.098 0.360CPMS5 0.896 0.365 0.190 0.352CPMS6 0.860
0.396 0.174 0.430CPMS7 0.859 0.380 0.134 0.435CPMS8 0.733 0.381
0.096 0.340CPMS9 0.841 0.361 0.142 0.398
GC1 0.349 0.787 0.532 0.450GC2 0.363 0.795 0.615 0.454GC3 0.265
0.786 0.530 0.426GC4 0.364 0.801 0.507 0.535GC5 0.399 0.875 0.566
0.535
PC1 0.203 0.586 0.795 0.295PC2 0.122 0.535 0.813 0.247PC3 0.115
0.590 0.847 0.363PC4 0.100 0.453 0.811 0.268PC5 0.185 0.596 0.817
0.450
MEAN1 0.457 0.559 0.366 0.949MEAN2 0.486 0.590 0.401 0.961MEAN3
0.405 0.534 0.375 0.918
COMP1 0.288 0.428 0.432 0.514COMP2 0.233 0.440 0.483 0.522COMP3
0.370 0.548 0.525 0.642
IMP1 0.502 0.538 0.353 0.619IMP2 0.346 0.545 0.540 0.490IMP3
0.413 0.535 0.461 0.481
SD1 0.264 0.400 0.455 0.334SD2 0.319 0.424 0.489 0.395SD3 0.183
0.430 0.572 0.302
MP1 0.262 0.412 0.302 0.529MP2 0.220 0.370 0.308 0.312MP3 0.244
0.385 0.342 0.258MP4 0.187 0.402 0.213 0.333MP5 0.223 0.509 0.394
0.540MP6 0.265 0.532 0.413 0.456MP9 0.170 0.511 0.449 0.500
CPMS, comprehensive performance measurement system; GC,
goaltence; IMP, impact; SD, self-determination; MP, managerial
performn = 83.N COMP IMP SD MP
0.407 0.475 0.269 0.319
and Society 33 (2008) 141163 153expected, this indicates that
comprehensive PMSdoes not have a direct eect on managerial
perfor-mance, but, instead, its eect on managerial per-formance is
fully mediated by the interveningvariables. The results from the
structural model,
0.318 0.419 0.226 0.2360.300 0.308 0.159 0.3050.158 0.382 0.201
0.2010.308 0.426 0.249 0.2380.261 0.379 0.281 0.3160.315 0.491
0.268 0.2510.159 0.307 0.175 0.2510.365 0.457 0.268 0.254
0.431 0.564 0.478 0.4810.498 0.538 0.473 0.5590.335 0.378 0.357
0.4300.457 0.517 0.244 0.5800.488 0.483 0.326 0.524
0.446 0.464 0.448 0.4480.488 0.408 0.501 0.3360.426 0.394 0.427
0.4140.357 0.339 0.455 0.3640.533 0.467 0.481 0.462
0.593 0.556 0.361 0.5830.632 0.648 0.407 0.5970.625 0.525 0.305
0.554
0.868 0.453 0.336 0.4710.777 0.566 0.403 0.3300.932 0.560 0.473
0.559
0.618 0.850 0.495 0.5190.480 0.881 0.644 0.3320.478 0.886 0.683
0.366
0.318 0.634 0.891 0.2480.474 0.657 0.938 0.3820.461 0.580 0.871
0.418
0.431 0.337 0.228 0.6640.294 0.276 0.236 0.5680.246 0.237 0.291
0.7010.280 0.289 0.138 0.6890.411 0.357 0.350 0.7680.460 0.372
0.298 0.7430.450 0.415 0.372 0.788
clarity; PC, process clarity; MEAN, meaning; COMP,
compe-ance.
-
reported in Table 6, indicate how role clarity andpsychological
empowerment act as interveningvariables in the relation between
comprehensivePMS and managerial performance.
For the role clarity path, there is a positive asso-ciation
between comprehensive PMS and goalclarity (b = 0.440, t = 4.668, p
< 0.01), and a weakpositive association between comprehensive
PMS
Table5
Descriptive
statistics,reliabilityandaveragevariance
extracted(AVE)statistics,andcorrelationsfrom
PLSmodel
Variable
Mean
Standarddeviation
Cronbachalpha
Compositereliability
AVE
Correlations
CPMS
GC
PC
MEAN
COMP
IMP
SD
MP
CPMS
4.657
1.289
0.946
0.955
0.705
0.840
GC
5.963
0.829
0.868
0.905
0.655
0.434
0.809
PC
5.191
0.871
0.875
0.909
0.667
0.182
0.681
0.817
MEAN
5.916
1.019
0.935
0.960
0.889
0.478
0.595
0.404
0.943
COMP
5.891
0.729
0.804
0.895
0.742
0.351
0.552
0.557
0.654
0.861
IMP
6.121
0.778
0.842
0.905
0.761
0.487
0.619
0.513
0.613
0.608
0.872
SD
5.971
0.938
0.880
0.929
0.811
0.281
0.466
0.567
0.381
0.472
0.691
0.902
MP
5.405
0.610
0.824
0.874
0.500
0.315
0.641
0.500
0.613
0.536
0.472
0.397
0.707
CPMS,comprehensive
perform
ance
measurementsystem
;GC,goal
clarity;
PC,process
clarity;
MEAN,meaning;
COMP,competence;IM
P,impact;SD,self-
determination;MP,managerialperform
ance.
Diagonalelem
entsarethesquarerootsoftheAVEstatistics.O-diagonalelem
entsarethecorrelationsbetweenthelatentvariablescalculatedinPLS.Allcorrelations
above
0.20
arestatisticallysignicant(p 0.10).
-
eects of management control systems on work
Table6
PLSstructuralmodel:pathcoe
cients,t-statistics
andR2
Dependentvariables
Independentvariables
Comprehensive
PMS
Goalclarity
Processclarity
Meaning
Competence
Self-determination
Impact
Jobtenure
R2
Comprehensive
PMS
0.121(1.365)*
0.016
Goalclarity
0.440
(4.668)***
0.050
(0.600)
0.200
Processclarity
0.184
(1.497)*
0.020
(0.237)
0.034
Meaning
0.256
(2.845)***
0.448
(3.153)***
0.052
(0.445)
0.143(2.100)**
0.442
Competence
0.167
(1.474)*
0.224
(1.594)*
0.374
(3.369)***
0.151(1.857)**
0.417
Self-determination
0.147
1.305)*
0.064
(0.492)
0.495
(4.171)***
0.143(1.647)**
0.375
Impact
0.292
(2.717)***
0.334
(2.607)***
0.233
(2.328)***
0.063(0.835)
0.480
Managerialperform
ance
0.030
(0.298)
0.380
(2.328)***
0.047
(0.311)
0.351
(2.350)***
0.113
(0.826)
0.107
(0.833)
0.129
(0.591)
0.027
(0.379)
0.513
n=83.Eachcellreportsthepathcoe
cient(t-value).Blankcellsindicatethat
thepathwas
nothypothesized
within
themodel.
*p