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J.-F. Henri / Accounting, Organizations and Society 31 (2006) 529558 531

choice level. The RBV rests on the principle that

competitiveness is a function of the strength,

expert exploitation, and leveraging of speciWc

internal resources and capabilities controlled by aWrm (Lengnick-Hall & WolV, 1999). These

resources and capabilities are distinctive, valuable,

and must be protected from imitation, adoption, or

substitution by competitors to create a sustainable

competitive advantage (Barney, 1991; Wernerfelt,

1984). They support strategic choices by providing

the competitive advantage necessary to materialize

these choices. MCS must be aligned with capabili-

ties to be eVective and consistent with strategic

choices. Hence, the notion of strategic choice itself

may not be directly traceable to MCS. Instead, the

relationship should be examined between capabili-

ties and MCS, rather than between strategic choice

and MCS.

Second, the traditional role of MCS in the

implementation of strategy is commonly recog-

nized (e.g. Andrews, 1971; AnsoV, 1965; Anthony,

1965). Following the work of Simons (Simons,

1990, 1991, 1994, 1995), several studies have exam-

ined a more active role of MCS in the formulation

of strategy and the implementation of strategic

change (e.g. Abernethy & Brownell, 1999; Bisbe &

Otley, 2004; Chenhall & LangWeld-Smith, 2003).Another line of research describes how the organi-

zations balance the traditional and more active

roles of MCS (e.g. Ahrens & Chapman, 2004;

Chapman, 1998; Dent, 1987; Haas & Kleingeld,

1999). However, less attention has been devoted to

the eVects of dynamic tension resulting from the

balance use of MCS in various ways. Notable

exceptions are the work of Chenhall and Morris

(1995) and Marginson (2002). While the former

has examined the joint eVect of organic processes

and formal MCS on performance, the latter hasused the model of Simons to report some trade-oVs

resulting from the various uses of MCS. A more

complete understanding of the relationships

between MCS and strategy requires the integration

in the theoretical and empirical analyses of both

traditional and more active roles of MCS, as well

as the tension resulting from those uses.

Building on the work of Simons, this study aims

to examine, from a resource-based perspective,

how the use of MCS by top management team can

act as an antecedent to organizational capabilities

leading to strategic choices. SpeciWcally, this study

focuses on the traditional feedback role of MCS to

support the implementation of strategy (diagnos-tic use) and the more active role of MCS associ-

ated with the signals sent throughout the Wrm to

focus organizational attention, stimulate dialogue

and support the emergence of new strategies

(interactive use). These two types of use work

simultaneously but for diVerent purposes. Collec-

tively, their power lies in the tension generated by

their balanced use which simultaneously reXects a

notion of competition and complementarity.

Hence, three speciWc research questions are

investigated in this study: (i) To what extent do the

diagnostic and interactive uses of MCS contribute

speciWcally to the creation and maintenance ofcapabilities leading to strategic choices? (ii) To

what extent do the diagnostic and interactive uses

of MCS act in combination to produce dynamictension which contributes to the creation and

maintenance of these capabilities? (iii) To what

extent does the use of MCS contribute to organiza-

tional performance? A theoretical model is devel-

oped and tested with empirical data gathered from

a survey.

The remainder of this paper is organized as fol-lows. The next section brieXy examines the

resource-based view and the use of MCS following

the model of Simons. Thereafter, a theoretical

model is developed and a set of hypotheses is pre-

sented. The next two sections include a description

of the survey design, the analysis of the data using

structural equation modelling and a discussion of

the results. The Wnal section presents the theoreti-

cal contributions, practical implications, limita-

tions and insights for future research.

Theoretical framework

DeWnition of constructs

Resource-based view and capabilitiesThe RBV conceptualizes Wrms as bundles of

resources heterogeneously distributed across Wrms,

and that resource diVerences persist over time

(Amit & Schoemaker, 1993; Wernerfelt, 1984).


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532 J.-F. Henri / Accounting, Organizations and Society 31 (2006) 529558

Resources that are valuable, rare, inimitable and

non-substitutable lead to the achievement of sus-

tainable competitive advantage that cannot be eas-

ily duplicated by competitors (Barney, 1991).Resources include various elements that can be

used to implement value-creating strategies: spe-

ciWc physical assets (e.g., specialized production

facilities, geographic location), human resources

(e.g., engineering experience, expertise in chemis-

try), organizational assets (e.g., management skills,

superior sales force), and competencies (e.g., minia-

turization, imaging) (Barney, 1991; Eisenhardt &

Martin, 2000; Teece, Pisano, & Shuen, 1997).2

Capabilities forge a link between resources and

permit their deployment (Day, 1994). They are the

organizational processes by which Wrms synthesize

and acquire knowledge resources, and generate

new application from those resources (Kogut &

Zander, 1992). Formally stated: The Wrms pro-

cesses that use resourcesspeciWcally the processes

to integrate, reconWgure, gain and release

resourcesto match and even create market

change. Dynamic capabilities thus are the organi-

zational and strategic routines by which Wrms

achieve new resource conWgurations as market

emerge, collide, split, evolve, and die. (Eisenhardt

& Martin, 2000, p. 1107).Innovation, organizational learning, market ori-

entation and entrepreneurship are recognized as

primary capabilities to reach competitive advan-

tage, to match and create market change. Past

research suggests that each of these four capabili-

ties is adequate to oVer strengths, but is not suY-

cient to develop sustained advantages. Only

collectively can they help a Wrm to be uniquely

competitive (Bhuian, Menguc, & Bell, 2005; Hult &

Ketchen, 2001; Hurley & Hult, 1998; Ireland et al.,

2001). Hence, this paper investigates the inX

uenceof MCS on each of these four capabilities.

First, innovativeness refers to the notion of the

organizations openness to new ideas, products

and processes, and its orientation toward innova-

tion (Hurley & Hult, 1998). Innovation is consid-

ered by many scholars and managers to be critical

for Wrms to compete eVectively in domestic and

global markets, and one of the most important

components of aW

rms strategy (Hitt, Ireland,Camp, & Sexton, 2001). Firms that have a greater

capacity to innovate are able to develop a competi-

tive advantage, achieve corporate renewal and

achieve higher levels of performance (Danneels,

2002; Hurley & Hult, 1998).

Second, organizational learning refers to the

development of insights, knowledge and associa-

tions among past actions, the eVectiveness of these

actions, and future actions (Fiol & Lyles, 1985). An

organizations ability to survive and grow is based

on advantages that stem from capabilities that rep-

resent collective learning (Nevis, Dibella, & Gould,

1995). Learning is considered to be an important

facilitator of competitive advantage by improving

a Wrms information processing activities at a faster

rate than rivals do (Baker & Sinkula, 1999).

Third, market orientation refers to the organi-

zational emphasis on customers expressed needs

and on the development of long-term thinking

based on customers latent needs (Slater & Narver,

1998; Slater & Narver, 1999). It speciWcally relates

to three components, namely customer orientation,

competitor orientation and inter-functional coor-dination. Market orientation eVectively and

eYciently creates the necessary behaviors for the

creation of superior value for customers, and thus,

continuous performance for the business (Kohli &

Jaworski, 1990; Narver & Slater, 1990).

Fourth, entrepreneurship refers to the ability of

the Wrm to continually renew, innovate, and con-

structively take risks in its markets and areas of

operation (Miller, 1983; Naman & Slevin, 1993).

Entrepreneurial actions entail creating new

resources or combining existing resources in newways to develop and commercialize new products,

move into new markets, and/or service new custom-

ers (Hitt et al., 2001). Entrepreneurship is identiWed

as a critical organizational process that contributes

to Wrm survival and performance (e.g., Barringer &

Bluedorn, 1999; Hitt et al., 2001; Miller, 1983).

Use of management control systemsMCS are deWned as formalized procedures and

systems that use information to maintain or alter

2 The resources must be distinguished from factors of produc-

tion which are undiVerentiated inputs available in disaggregate

form in factor markets, such as land, unskilled labour and capi-

tal.


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patterns in an organizational activity (Simons,

1987). This deWnition includes planning systems,

reporting systems, and monitoring procedures that

are based on information use. In this study, onecomponent of MCS is examined, namely the per-

formance measurement systems (PMS). The latter

represent a set of metrics used to quantify actions

(Neely, Gregory, & Platts, 1995). These metrics can

be Wnancial or non-Wnancial, internal or external,

short or long term as well as ex post or ex ante.

Simons framework on the levers of control

(Simons, 1990, 1991, 1994, 1995) relies on the con-

cept of tension. The essence of MCS is to manage

the inherent organizational tension between creativeinnovation and predictable goal achievement.

More speciWcally, three kinds of inherent tension

must be reconciled and balanced to allow the eVec-

tive control of business strategy: (i) unlimited

opportunity versus limited attention, (ii) intended

versus emergent strategy, and (iii) self-interest and

desire to contribute. Managers use MCS as posi-

tive and negative forces to create dynamic tensionthat contributes to manage inherent organizational

tension.

The diagnostic use of MCS represents the tradi-

tional feedback role as MCS are used on an excep-

tion basis to monitor and reward the achievementof pre-established goals. Following a traditional

mechanistic notion of control, a diagnostic use

provides motivation and direction to achieve goals

by focusing on and correcting deviations from pre-

set standards of performance. The diagnostic use

comprises the review of critical performance vari-

ables (i.e., factors enabling the achievement of

intended strategy) to monitor and coordinate the

implementation of intended strategies. It repre-

sents a negative force for two reasons. On the one

hand, diagnostic use focuses on mistakes and nega-tive variances. On the other hand, the sign of the

deviation that is derived when outputs and goals

are compared is reversed in the feedback signal to

adjust the process.

The interactive use of MCS represents a positive

force as MCS are used to expand opportunity-

seeking and learning throughout the organization.

The interactive use focuses attention and forces

dialogue throughout the organization by reXecting

signals sent by top managers. It stimulates the

development of new ideas and initiatives and

guides the bottomup emergence of strategies by

focusing on strategic uncertainties (i.e., contingen-

cies threatening or invalidating underlyingassumptions of current strategies). When MCS are

used interactively, (i) the information generated is

a recurrent and important agenda for top manag-

ers; (ii) frequent and regular attention is fostered

throughout the organization; (iii) data are dis-

cussed and interpreted among organizational

members of diVerent hierarchical levels; and (iv)

continual challenge and debate occur concerning

data, assumptions and action plans.

Diagnostic and interactive uses of MCS, includ-

ing PMS, represent two complementary and nested

uses. They work simultaneously but for diVerent

purposes. While diagnostic use represents a mecha-

nistic control used to track, review and support the

achievement of predictable goals, interactive use is

an organic control system supporting the emer-

gence of communication processes and the mutual

adjustment of organizational actors. SpeciWcally, a

diagnostic use limits the role of PMS to a measure-

ment tool, while an interactive use expands its role

to a strategic management tool (Kaplan & Norton,

2001). According to Simons, diagnostic and inter-

active uses of MCS represent countervailing forcesused to balance the inherent organizational ten-

sion. Haas and Kleingeld (1999) point out that

diagnostic use of PMS may not be an end in itself

but a means necessary to initiate strategic dialogue

and interactive use of PMS. Referring to Argyris

and Schn (1978b), diagnostic use represents sin-

gle-loop learning and acts as a prerequisite for

interactive use and double-loop process. Thus, the

use of MCS (and PMS) ranges from mostly diag-

nostic to a combination of diagnostic and interac-

tive.The joint use of MCS in a diagnostic and inter-

active fashion to manage inherent organizational

tensions creates dynamic tension. Dynamic tension

denotes contradictory but interrelated elements

(Lewis, 2000). Formally stated, tension can be deW-

ned as two phenomena in a dynamic relationship

that involve both competition and complementar-

ity (English, 2001). The joint use of PMS in a diag-

nostic and interactive manner creates dynamic

tension reXecting competition (positive versus


6/30


negative feedback) and complementarity (focus on

intended and emergent strategies). The notion of

dynamic tension is not necessarily new in the aca-

demic literature, and is related to other terms suchas conXict, paradox, dilemma, and contrast

(English, 2001). For instance, some authors have

examined the paradox related to the propensity to

seek risk and innovation while simultaneously exe-

cuting a safe and incremental implementation (e.g.

Bourgeois & Eisenhardt, 1988; Cameron, 1986).

Other studies have examined conXicts in the use

and implementation of control and cost systems

(e.g. Barrett & Fraser, 1977; Chenhall, 2004;

Shank, Niblock, & Sandalls, 1973). As suggested

by the conXict literature, tension is not necessarily

negative but instead may be beneWcial to organiza-

tions (DeDreu, 1991; Nicotera, 1995). This study

investigates the inXuence of the dynamic tension

resulting from the joint use of PMS in a diagnostic

and interactive fashion on capabilities leading to

strategic choices.

Theoretical model and hypotheses

Fig. 1 presents a summary of the theoretical

model that reXects the relationships among two

PMS use (diagnostic and interactive), four capabil-ities (innovativeness, organizational learning, mar-

ket orientation and entrepreneurship), and

organizational performance. As previously men-

tioned, the aim of this paper is to understand the

speciWc and joint contributions of two complemen-

tary uses of PMS on capabilities and performance.

Consequently, the theoretical model considers the

individual eV

ect of diagnostic and interactive usesseparately, as well as their collective eVects. When

examined speciWcally, a diagnostic use is expected

to have a negative inXuence on the four capabili-

ties, while interactive use is expected to have a pos-

itive impact on these capabilities. Furthermore, the

balanced use of PMS in a diagnostic and interac-

tive fashion results in dynamic tension. This ten-

sion is expected to contribute positively to the four

capabilities by ensuring that positive eVects of

interactive use will be achieved and by expanding

these positive eVects. Lastly, PMS use is expected

to have an indirect eVect on organizational perfor-

mance through the four capabilities. These rela-

tionships are discussed speciWcally below.

Relationships between diagnostic use andcapabilities

In the management of inherent organizational

tension between creative innovation and predict-

able goal achievement, diagnostic use of PMS sup-

ports the attainment of pre-established goals.

Indeed, diagnostic use is described as a negative

force that creates constraints and ensures compli-ance with orders: [Diagnostic systems] constrain

innovation and opportunity-seeking to ensure pre-

dictable goal achievement needed for intended

strategies (Simons, 1995, p. 91). Traditional PMS

Fig. 1. Theoretical model.

Market

orientation

Entrepreneur-

ship

Innovative-

ness

Organizational

learning

CAPABILITIESPMS interactive use

PMS diagnostic use H1

(-)

Diagnostic * Interactive

Organizational

performance

H2

(+)

H4

(+)

Dynamic tension

H3

(+)


7/30


encourage conservatism and a playing it safe

attitude: Managers need to be encouraged to

identify deWned areas within which a degree of

experimentation and risk-taking might be beneW

-cial. Too often we stiXe creativity and learning by

insisting upon good performance from all activi-

ties (Otley, 1994, p. 297).

Relying on cybernetic logic and reXecting tradi-

tional control systems, diagnostic use of PMS may

not represent an adequate means to foster capabil-

ities of market orientation, entrepreneurship, inno-

vativeness and organizational learning. Diagnostic

use reXects two important features associated with

mechanistic controls: (i) tight control of operations

and strategies, and (ii) highly structured channels

of communication and restricted Xows of informa-

tion (Burns & Stalker, 1961). Globally, there is a

mismatch between the requirements of the four

capabilities and mechanistic use of control systems

(Chenhall & Morris, 1995; Galbraith, 1982).

First, diagnostic use is associated with tight con-

trol of operations and strategies through sophisti-

cated control systems. These systems include

action plans derived from strategies, detailed Wnan-

cial targets, comparison of actual outcomes with

targets, and explanation of variances. This formal

use of PMS provides a mechanistic approach todecision making resulting in organizational inat-

tention to shifting circumstances and the need for

innovation (Van de Ven, 1986). Furthermore, the

concept of organizational learning encompasses

the notion of single- and double-loop learning

(Argyris & Schn, 1978a). Diagnostic use repre-

sents single-loop learning but not the higher level

learning (double-loop), which is necessary for

innovative behaviors (Haas & Kleingeld, 1999).

Also, the four capabilities may create an organiza-

tional momentum leading to innovative excess,overzealous experimentation and diminished

returns. Diagnostic use of PMS is used to signal

when productivity and eYciency have fallen, and

when innovation needs to be curbed (Miller &

Friesen, 1982). Hence, PMS is used diagnostically

to limit the deployment of the four capabilities by

providing boundaries and restrict risk-taking.

Lastly, as a mechanistic control, diagnostic use has

been associated with several dysfunctional behav-

iors based on distortion of information: gaming,

smoothing, biasing, focusing, Wltering, and illegal

acts (Birnberg, Turopolec, & Young, 1983; Hofst-

ede, 1978; Simons, 1995). These distortions consti-

tute defensive routines that aim to reduce potentialembarrassment or threat, or to improve personal

interest. They consequently impede the potential

for learning and innovation (Argyris, 1990).

Second, diagnostic use of PMS is associated

with highly structured channels of communication

and restricted Xow of information. However,

notions of communication and dialogue gravitate

towards the four capabilities. They rely on cross-

functional processes, and thus require the free Xow

of information and open channels of communica-

tion (Kohli & Jaworski, 1990). Diagnostic use

undercuts the commitment of organizational

actors to these cross-functional processes by rein-

forcing the existing lines of authority and responsi-

bility (Abernethy & Brownell, 1999). As

Vandenbosch (1999) argued, the discussion trig-

gered by the diagnostic use leads to corrective

action at best. At worst, it causes discussion to

gravitate towards unproductive topics, such as the

believability of the numbers or why things are not

better, and ultimately does not trigger any action.

Corrective actions are not suYcient to sustain such

capabilities; new ideas must be developed. Thesearguments lead to the following hypothesis:

Hypothesis 1. A diagnostic use of PMS tends to

negatively inXuence capabilities of market orienta-

tion, entrepreneurship, innovativeness and organi-

zational learning.

Relationships between interactive use andcapabilities

In the management of inherent organizational

tension between creative innovation and predict-able goal achievement, interactive use of PMS sup-

ports the development of ideas and creativity.

Indeed, interactive use has the power to represent a

positive trigger that fosters creative and inspira-

tional forces: senior managers use interactive

control systems to build internal pressure to break

out of narrow search routines, stimulate opportu-

nity-seeking, and encourage the emergence of new

strategic initiatives (Simons, 1995, p. 93). Accord-

ing to Dent (1990), curiosity and experimentation


8/30


can be fostered by control systems. Planning and

control systems could create new images of the

organization for employees as the organization

interacts with its environment. Thus, obsolete par-adigms and organizational attempts can be uncou-

pled (unlearning) and recoupled in diVerent ways

(learning).

Relying on organizational dialogue and signal-

ing, interactive use of PMS represents an adequate

means to foster capabilities of market orientation,

entrepreneurship, innovativeness and organiza-

tional learning. Interactive use reXects two impor-

tant features associated with organic controls: (i)

loose and informal control reXecting norms of

cooperation, communication and emphasis on get-

ting things done, and (ii) open channels of commu-

nication and free Xow of information throughout

the organization (Burns & Stalker, 1961). Globally,

there is a natural Wt between the requirements of

the four capabilities and organic use of control sys-

tems (Chenhall & Morris, 1995; Van de Ven, 1986).

Capabilities of innovativeness, organizational

learning, entrepreneurship and market orientation

lead to complexity and changes in product design.

This context requires the employment of experts in

the process of creation and implementation of new

product design (Burns & Stalker, 1961; Mintzberg,1979). The collaboration of experts and managers

from diVerent functional areas is needed to foster

innovation and new product development (Miller,

1988). Reciprocal interdependencies are then

expected from the people who need to be in close

contact (Galbraith, 1973). Also, this context of

complexity and change brings uncertainty and

ambiguity for the sub-ordinates as top manage-

ment is often redeWning goals and objectives

(Abernethy & Brownell, 1999). In those circum-

stances, additional pressure is imposed on theorganizations information processing capacity

and more interaction between top management

and sub-ordinates is required to increase the Xow

of information (Galbraith, 1973).

The interactional needs and the information

processing capacity necessary for the capabilities

are likely to be fostered by an interactive use of

PMS. Indeed, in providing an agenda and a forum

for the regular face-to-face debate and dialogue, an

interactive use allows top management to send sig-

nals that stimulate and concentrate organizational

attention toward top management preferences,

strategic uncertainties and organizational goals

and objectives (Simons, 1995). Considering thecharacteristics of integrativeness within PMS, top

management can provide an understanding of

causeeVect relationships between operations,

strategy and goal, as well as between various

aspects of the value chain (Chenhall, 2005). Also,

with a focus on dialogue and communication

between organizational actors of diVerent or iden-

tical hierarchical levels, the interactive use of PMS

acts as an integrative liaison device that breaks

down the functional and hierarchical barriers that

restrict the Xow of information (Abernethy &

Brownell, 1999; Abernethy & Lillis, 1995). Lastly,

by focusing regular attention on strategic uncer-

tainties, interactive use of PMS provide a lever to

Wne-tune analyses and actions, and alter strategy as

competitive markets change (Bisbe & Otley, 2004).

In terms of information processing activities,

Kohli and Jaworski (1990) identify three basic

components, namely intelligence generation, intel-

ligence dissemination, and responsiveness. Simi-

larly, Huber (1991) speciWes four processes:

knowledge acquisition, knowledge distribution,

information interpretation and organizationalmemory.3 Therefore, internal mechanisms must be

in place: (i) to ensure knowledge generation

throughout the organization, (ii) to communicate,

disseminate and sell this knowledge throughout

the organization, and (iii) to plan actions and coor-

dinate their implementation (Kohli & Jaworski,

1990). An interactive use of PMS has the power to

focus organizational attention on the speciWc stra-

tegic uncertainties for which knowledge must be

generated and causeeVect relationships under-

stood. PMS is an important formal mechanismused to collect information to develop capabilities

3 Intelligence generation, knowledge acquisition, and infor-

mation interpretation refer to the collection and assessment of

information. Intelligence dissemination and knowledge distri-

bution refer to the process by which information is shared

throughout the organization. Responsiveness is the action tak-

en in response to the knowledge gained and shared, while orga-

nizational memory refers to the means by which knowledge

becomes institutionally available and stored for future use

(Huber, 1991; Kohli & Jaworski, 1990).


9/30


(Chenhall, 2005). Moreover, by fostering organiza-

tional dialogue and debate, and encouraging infor-

mation exchange, interactive use contributes to

knowledge dissemination, information distributionand communication, and the emergence of strate-

gic actions (Haas & Kleingeld, 1999; Malina &

Selto, 2001; Simons, 1995). Hence, an interactive

use of PMS contributes to expanding the organiza-

tions information processing capacity and foster-

ing interaction among organizational actors.

Consequently, an interactive use fosters the

deployment of the four capabilities. Formally

stated:

Hypothesis 2. An interactive use of PMS tends to

positively inXuence capabilities of market orienta-

tion, entrepreneurship, innovativeness and organi-

zational learning.

Relationships between joint use of PMS andcapabilities

As illustrated by the previous two hypotheses,

interactive use of PMS stimulates opportunity-

seeking and fosters dialogue, while diagnostic use

creates constraints and ensures compliance with

orders. Together, diagnostic and interactive uses

create a dynamic tension which has two eVects: (i)ensuring that positive eVects of interactive use on

capabilities will be achieved; and (ii) expanding

these positive eVects of interactive use.

First, a diagnostic use of PMS ensures that the

positive eVects of interactive use on capabilities

will be achieved. In some circumstances, the poten-

tial beneWts of interactive use may vanish due to

insuYcient diagnostic use to set boundaries and to

highlight eVectiveness issues. This can produce a

loss of direction, wasted energy and a disruption of

continuity (Cameron, 1986; Chenhall & Morris,1995). Similarly, the potential beneWts of interac-

tive use can be lost due to excessive diagnostic use

which constrains innovation and risk taking. This

can produce stagnation, loss of energy and declin-

ing morale (Cameron, 1986; Chenhall & Morris,

1995).

More importantly, a diagnostic use of PMS

helps to increase the positive eVects of an interac-

tive use on capabilities. Indeed, beyond underlying

assumptions that conXict and tension are negative

and destructive, growing evidence from the conXict

literature suggests that they may be beneWcial to

individual and organizational performance, and

that avoiding and suppressing conX

ict reduces cre-ativity, decision quality, product development, and

communication (DeDreu, 1991; Nicotera, 1995).

ConXict and tension foster organizational dia-

logue, stimulate creativity, and focus organiza-

tional attention (Amason, 1996; Tjosvold, 1991;

DeDreu, 1991; English, 2001; VanSlyke, 1999).

These three elements, which have been presented

as positive eVects of interactive use on capabilities

(see Hypothesis 2), are ampliWed by the combina-

tion of diagnostic and interactive use. They are dis-

cussed more speciWcally below.

Dynamic tension between diagnostic and inter-

active use of PMS stimulates organizational dia-

logue (Dent, 1987). It provides the opportunity for

dialectically styled interactions by providing a

means to debate vigorously opposing positions

(Chenhall, 2004). More speciWcally, dynamic ten-

sion provides valuable information that increases

Xexibility, innovation, and improvement. It stimu-

lates continual communication concerning strategic

issues and promotes mutual understanding. Ten-

sion also encourages open and lively discussions,

and helps employees group their ideas and actions(Amason, 1996; DeDreu, 1991; Tjosvold, 1991).

Moreover, creativity is enhanced by dynamic

tension, which leads organizational members to

integrate seemingly opposed elements (VanSlyke,

1999). Tension triggers the identiWcation of alter-

native ways of doing things by supporting the

identiWcation and synthesis of a variety of view-

points (Chenhall, 2004). Finally, dynamic tension

resulting from the balanced use of PMS in a diag-

nostic and interactive fashion contributes to focus-

ing organizational attention. Indeed, tensionmakes underlying issues explicit and helps groups

to deWne their boundaries. Thus, it provides the

motivation and strength to deal with tough prob-

lems. Tension also fosters involvement and

empowerment by providing incentives for diVerent

groups to pull together toward a common goal

(Amason, 1996; DeDreu, 1991; Tjosvold, 1991).

To summarize, the joint eVect of a balanced use

of PMS diagnostically and interactively constitutes

countervailing forces that create dynamic tension.


10/30


This tension ensures the achievement of the posi-

tive eVects of interactive use on capabilities.

Dynamic tension also increases these positive

eV

ects by fostering organizational dialogue, stimu-lating creativity, and focusing organizational

attention. Formally stated:

Hypothesis 3. The dynamic tension resulting from

a balanced use of PMS in a diagnostic and interac-

tive fashion tends to positively inXuence the capa-

bilities of market orientation, entrepreneurship,

innovativeness and organizational learning.

Relationships between PMS, capabilities andorganizational performance

Following the resource-based view of the Wrm,

unique resources and capabilities lead to a sus-

tained competitive advantage, which in turn con-

tributes to performance diVerences among Wrms.

Market orientation, organizational learning, inno-

vativeness, and entrepreneurship constitute four

capabilities that are valuable, hard to duplicate,

and non-substitutable. They are considered to be

key drivers of organizational transformation and

strategic renewal by manipulating resources into

new value-creating strategies (e.g., Bhuian et al.,

2005; Danneels, 2002; Eisenhardt & Martin, 2000;Hitt et al., 2001; Ireland et al., 2001). Empirically,

previous studies provide evidence showing that

these four capabilities contribute positively to per-

formance (e.g., Hult & Ketchen, 2001; Lee, Lee, &

Pennings, 2001; Naman & Slevin, 1993; Narver &

Slater, 1990; Spanos & Lioukas, 2001).

Diagnostic and interactive use of PMS, as well as

the dynamic tension resulting from their balanced

use, have been linked to capabilities of market ori-

entation, organizational learning, innovativeness,

and entrepreneurship (Hypotheses 13). Thesecapabilities are expected to lead to organizational

performance. Thus, the use of PMS can be expected

to have indirect implications for performance by

inXuencing the deployment of capabilities which

are considered to be valuable, hard to duplicate,

and non-substitutable. Hence, diagnostic and inter-

active use of PMS and the dynamic tension result-

ing from their balanced use inXuence the four

capabilities, which in turn increase performance.

Therefore, the following hypotheses are proposed:

Hypothesis 4a. The diagnostic and interactive use

of PMS have an indirect eVect on organizational

performance through their contribution to capa-

bilities of market orientation, entrepreneurship,innovativeness and organizational learning.

Hypothesis 4b. The dynamic tension resulting from

a balanced use of PMS in a diagnostic and interac-

tive fashion has an indirect eVect on organizational

performance through its contribution to capabili-

ties of market orientation, entrepreneurship, inno-

vativeness and organizational learning.

No speciWc hypotheses supporting a direct rela-

tionship between PMS use and performance have

been formulated. Despite the fact that prior

research has examined the relationship between

MCS and performance using a notion ofWt to the

context of the organization (e.g., Govindarajan,

1988; Govindarajan & Fisher, 1990; Perera, Harri-

son, & Poole, 1997; Sim & Killough, 1998), and

despite the fact that another line of research has

supported a positive relationship between the

design of PMS (increased reliance on non-Wnancial

information) and performance (e.g. Baines & Lang-

Weld-Smith, 2003; Davila, 2000; Said, Elnaby, &

Wier, 2003; Scott & Tiesen, 1999), the exact nature

of the relationship between the use of PMS and per-formance remains ambiguous. Theoretical support

and prior empirical evidence in the literature are

insuYcient to justify a direct relationship between

PMS use and performance at an organizational

level (Bisbe & Otley, 2004). Also, recent studies

using the Simons framework did not Wnd empirical

evidence supporting a direct relationship between

the interactive use of MCS and performance (Aber-

nethy & Brownell, 1999; Bisbe & Otley, 2004).

Furthermore, according to the resource-based

view, information and control systems are gener-ally not a source of competitive advantage for two

reasons: (i) they lead Wrms to fully realize the ben-

eWts of the resources they control but do not gen-

erate sustainable rents, and (ii) they can be readily

transferred (Barney et al., 2001). Hence, following

this line of reasoning, PMS use may not contrib-

ute directly to performance, but instead contribute

indirectly through capabilities. On the other hand,

the accounting literature has demonstrated the

ways in which the use of MCS aVects their role


11/30


and functioning as well their impact within the

organizations (e.g., Abernethy & Brownell, 1999;

Ahrens & Chapman, 2004; Bisbe & Otley, 2004;

Chapman, 1998; Chenhall & Morris, 1995;Simons, 1995). From a theoretical standpoint and

following resource-based logic, it could be argued

that the use of PMS in a joint diagnostic and inter-

active fashion has a positive impact on perfor-

mance. Indeed, the balance between diagnostic

and interactive use may be considered as a capa-

bility. In this regard, the ability to reach a balance

between two opposing uses of PMS which, simul-

taneously, try to stimulate innovation while

searching for predictable achievements represents

a capability that is valuable, distinctive, and

imperfectly imitable. The ability to manage the

combination of diagnostic and interactive use

depending on various internal and external factors

is complex and may not be readily transferred.

These opposing views from the RBV and MCS lit-

erature combined with the absence of substantive

empirical evidence preclude the formulation of

any hypotheses. Nevertheless, in order to contrib-

ute to this debate and to expand current literature,

the links between diagnostic and interactive use of

PMS and dynamic tension versus performance

will be tested. Since a large proportion of the rela-tionships between PMS use and performance is

expected to come indirectly through the four

capabilities (Hypothesis 4), the direct eVects (if

any) are expected to be relatively small.

Validation of the modelVarious internal and external contextual factors

interact together to cause uncertainty. As the level

of uncertainty varies, diVerent forms of communi-

cation are necessary to mobilize and integrate

information (Chapman, 1997). Environmentalcontext, organizational size and organizational

culture4 are important contextual factors which

inXuence the role of PMS (e.g. Bhimani, 2003;

Chenhall, 2003; Henri, in press; Hoque & James,

2000). These variables also suggest conXicting

implications and potential tension (Dent, 1987;

Quinn & Cameron, 1983).5 While size favors

bureaucratic formalization, the complex and

changing environmental context calls for Xuidity

andX

exibility in the management practice (Dent,1987). On the other hand, following the competing-

values model, there are likely to be simultaneous

pressures for control values fostering order and

formality and Xexibility values reXecting adapt-

ability and responsiveness (Quinn & Cameron,

1983; Quinn & Kimberly, 1984). As the diagnostic

and interactive use of PMS fulWll diVerent roles,

their use and the dynamic tension emerging from

their balanced use might vary depending on the

level of uncertainty. In order to validate the

robustness of the theoretical model, sub-group

analyses are used to assess cross-sample validation

and to reinforce the hypothesis tests. Splitting the

sample at the median for each contextual variable,

two sub-samples will be created and compared.

Methododology

Research design

Data were collected through a structured ques-

tionnaire sent to one member of top management

teams (CEO, COO, CFO, or senior vice-presidents).

The survey implementation followed four steps: pre-

notiWcation, initial mailing, Wrst follow up, and sec-

ond follow up. To generate early interest, the Wrst

step was to notify respondents in the form of a let-

ter, phone call or e-mail. A mail-out package includ-

ing a cover letter, the questionnaire and a business

reply envelope was then sent to every contact name.

In a few cases, the questionnaire was sent by fax or

e-mail. The Wrst follow up consisted of a postcard

reminder which was sent to every respondent, while

the second was a phone call or replacement ques-tionnaire sent only to those who had not answered.

The target population consisted of 2175 Cana-

dian manufacturing Wrms listed in Scotts 2002

database with primary and secondary SIC codes in

4 Organizational culture is deWned here as the shared values

that interact with an organizations structures and control sys-

tems to produce behavioural norms Uttal and Fierman (1983).

5 Dent (1987) also proposed task unpredictability as an

important contextual factor in a context of tension on the de-

sign of MCS. Since the current study examines phenomena at

an organizational level and task unpredictability is an individ-

ual-level construct, the latter is not included in the analyses.


12/30


the range of 2139. These Wrms were either inde-

pendent companies or SBUs. However, the lack of

a contact name for the top management teams in

several cases reduced the number of usableW

rms inthe target population to 1692. The Wrms were large

enough to ensure that organizational and strategy

variables applied (Miller, 1987), and to ensure that

a formal PMS was in place (Bouwens & Abern-

ethy, 2000). Thus, the Wrms selected in the sample

respected the following two criteria: (i) sales were

at least $20 million Canadian; and, (ii) each had at

least 150 employees.

Current literature reports that a sample size vary-

ing between 100 and 200 cases, or between 5 and 10

subjects per estimated parameter, is adequate for

small-to-medium size structural equation models

(Anderson & Gerbing, 1988; Bentler & Chou, 1987).

In the present case, a total of 383 Wrms participated

to the study giving a response rate of 24%, which is

similar to the 1525% range reported in similar

recent studies (e.g., Baines & LangWeld-Smith, 2003;

Lee et al., 2001; Spanos & Lioukas, 2001).6 More-

over, a ratio of 6.17 subjects per parameter was

obtained, which is adequate to test the proposed

model. Appendix 1 presents the statistics of the

respondents in terms of position, experience, size

(number of employees) and industry classiWcation.To test whether the respondents diVered from

the non-respondents, a two-step analysis was con-

ducted. Respondents were Wrst compared with

non-respondents in terms of sample characteristics

(size, location, industry). Next, early and late

respondents were compared to detect any diVer-

ence in the mean score of each variable.7 Using

chisquare statistics, no signiWcant diVerences

(p > 0.01) were found between the size, locationand industry of respondent Wrms and non-respon-

dentW

rms. A comparison of the means of the vari-ables found little diVerence between early and late

respondents. The t-value for only one variable issigniWcant (organizational learning, tD2.27,

p < 0.05), but this is not believed to be a seriousproblem considering its isolated eVect. While there

is unlikely to be a systemic bias due to diVerences

between respondents and non-respondents, the

generalization of results related to organizational

learning should be made with caution.

Measurement of constructsAll measures are drawn from existing instru-

ments. Descriptive statistics of the constructs and

correlation matrix are presented in Table 1.

Appendix 2 shows the questionnaire items, Cron-

bach Alpha for each construct, and statistics from

a conWrmatory factor analysis (Wrst- and second-

order loadings, and goodness-of-Wt indices8).

Interactive and diagnostic uses of PMS are mea-

sured using an adapted version of the Van-

denboschs (1999) instrument. Developed originally

to measure the use of executive support systems(EES), this instrument is based on several dimen-

sions, notably score keeping (diagnostic) and atten-

tion-focusing (interactive). The choice of this

instrument is justiWed by its development based on

theories of accounting control, including Simons

(1990), before its adaptation to a management-

information context. Furthermore, EES is used as a

surrogate for accounting and management infor-

mation and is restricted to the accounting, manage-

ment and control information provided. Thus,

PMS and EES have common base that allow theadaptation of the instrument to our speciWc con-

6 The response rate was calculated as the percentage of usable

returned questionnaires in relation to the number of question-naires sent, after adjusting for the Wrms which had closed, ended

manufacturing activities or moved, or for which the contact

person had left the organization. As discussed in Appendix 3, to

assess interrater reliability for survey items, duplicate surveys

were sent to a second member of the top management team in

the Wrms that originally returned the questionnaire. Twenty-one

questionnaires were returned. For those 21 Wrms having two

diVerent respondents, a mean score has been computed.7 Early respondents correspond to the managers that have

Wlled out the questionnaire before the Wrst follow-up. Late

respondents correspond to the managers that have Wlled out the

questionnaire after the second follow-up.

8 The indices used to assess the model are among the most

frequently reported, namely NNFI (non-normed Wt index), CFI

(comparative Wt index), and RMSEA (root mean square error

of approximation). The threshold values recommended are (i)

NNFI> 0.90 Tabachnick & Fidell (2001), (ii) CFI> 0.95 Hu &

Bentler (1995), and (iii) RMSEA < 0.l0 (Browne & Cudeck

(1993).


13/30


text. Two items were added to the interactive

dimension to better reXect its use in a context of

MCS. All Wrst- and second-order loadings are sig-niWcant (p < 0.01), the Cronbach Alpha coeYcientsexceeded common cut-oV level of 0.70 (Nunnally,

1967), and the goodness-of-Wt indices respected the

recommended threshold values.

Dynamic tension is operationalized as a product

term between diagnostic and interactive use. A

product term can be treated as a variable without

any theoretical meaning (to test an interaction) or as

a construct based on a theoretical justiWcation (Cor-

tina, Chen, & Dunlap, 2001). In this study, the prod-

uct term is treated as a construct having its owntheoretical meaning. Several procedures are avail-

able to create and test multiplicative terms within

structural equation models. The seminal work of

Kenny and Judd (1984) provides the foundation for

these procedures. Among various approaches, Jac-

card and Wan (1995) propose a procedure having

the same logic as Kenny and Judd but simpler to

implement and adapted for the latest versions of

LISREL. Essentially, all possible cross products of

the existing indicators are used as indicators of the

latent product.9 Although this procedure is one of

the most technically robust, it is also one of the most

complicated ones (Cortina et al., 2001).10Four diVerent validated scales are used to mea-

sure internal capabilities. The well-established

MKTOR instrument developed by Narver and

Slater (1990) is used to measure market orientation.

The instruments proposed by Naman and Slevin

(1993) and Hult (1998) are respectively used to

measure entrepreneurship and organizational

learning. Finally, following Hurley and Hult (1998),

the instrument developed by Burke (1989) is used

Table 1

Descriptive statistics and correlation matrix

Notes: The scores of diagnostic and interactive uses have been centered. Before centering, the mean scores (standard deviations) fordiagnostic and interactive were, respectively, 5.63 (0.98) and 5.07 (1.05). SigniWcant at the 0.05 level; SigniWcant at the 0.01 level.

Market

orientation

Entrepre-

neurship

Innova-

tiveness

Organizational

learning

Diagnostic

use1Interactive

use1Dynamic

tension

Performance

Descriptive statisticsNo. of items used 13 9 5 4 4 7 3

Theoretical range 17 17 17 17 17 17 17

Minimum 2.80 1.80 1.80 1.00 4.60 4.00 3.20 1.00

Maximum 6.90 6.70 7.00 7.00 1.50 2.00 18.40 7.00

Mean 5.02 4.20 5.42 5.45 0 0 0.63 4.57

Standard deviation 0.76 0.86 0.89 0.99 0.99 1.02 1.69 1.33

Median 5.10 4.20 5.60 5.50 0.10 0.10 0.20 4.70

Correlation matrix (Pearson)Market orientation 1.0

Entrepreneurship 0.461 1.0

Innovativeness 0.515 0.617 1.0

Organizationallearning

0.598

0.430

0.516

1.0

Diagnostic use 0.384 0.080 0.174 0.264 1.0

Interactive use 0.414 0.188 0.236 0.381 0.642 1.0

Dynamic tension 0.151 0.021 0.024 0.059 0.452 0.301 1.0

Performance 0.303 0.123* 0.136 0.167 0.236 0.192 0.012 1.0

9 Organizational tension has four latent indicators as the

cross-products of the two indicators of diagnostic use (du1 and

du2) and the two indicators of interactive use (iu1 and iu2). Spe-

ciWcally, the four indicators are: (i) du1 iu1, (ii) du1 iu2, (iii)

du2 iu1, and (iv) du2 iu2. Moreover, with this approach, sev-

eral parameters are constrained to equal values determined by

various equations, namely the variance of the latent product,

the paths from the latent product to its indicators, and the error

variances of these indicators.10 To validate our results and provide a sensibility analysis, the

single-indicator approach suggested by Ping (1995) has also

been used. It has provided similar results and conclusions.


14/30


to measure innovativeness. All Cronbach Alpha

coeYcients exceeded the common cut-oV level of

0.70, all Wrst- and second-order loadings are signiW-

cant (p < 0.01), and the goodness-of-W

t indicesrespect the recommended threshold values.

Organizational performance is measured with a

subjective instrument using three indicators: (i)

sales volume; (ii) return on investment; and, (iii)

proWts. As several authors argue (e.g., Dess & Rob-

inson, 1984; Venkatraman & Ramanujam, 1987),

in terms of consistently providing valid and reli-

able performance assessment, neither objective nor

subjective measures are superior. The three path

loadings are signiWcant (p < 0.01), the CronbachAlpha coeYcient is 0.81, and the goodness-of-Wt

indices respect the recommended threshold values.

Lastly, the validation variables used to test

robustness of the model are measured as follows.

Organizational culture follows a competing-values

model (Quinn & Rohrbaugh, 1983) and is mea-

sured using the instrument designed by (Krakower

& Niwa, 1985).11 Govindarajans (1984) instru-

ment is used to assess environmental uncertainty,

while size is measured using the natural log of the

number of employees.

Validation of constructs

Besides the conWrmatory factor analysis (CFA)

discussed above to establish convergent validity,

several other procedures and tests were conducted

to establish the reliability and validity of con-

structs: pre-test of the questionnaire in three steps,

tests of convergence and discriminant validity, and

assessment of interrater reliability. Appendix 3

describes these elements and presents the main

results. Overall, based on the CFA and other tests,

all constructs reX

ect strong validity and reliability.

Structural equation model

The theoretical model discussed in this study

reXects two features that must be considered whenchoosing a statistical tool: (i) presence of multiple

and interrelated dependence relationships, and (ii)

presence of latent variables that cannot be

observed directly. Structural equation modeling

(SEM) represents a set of multivariate techniques

that allow the simultaneous study of several causal

relationships between endogenous and exogenous

variables (Mueller, 1996). Data collected from the

survey were analyzed with LISREL 8.52. Consider-

ing multivariate non-normality of the data and the

presence of a product term, maximum likelihood

estimates were used (Bentler & Chou, 1987; Cor-

tina et al., 2001). Furthermore, composite indices

and a partial disaggregation approach were used

to represent latent construct (Bagozzi & Heather-

ton, 1994).12 As Landis, Beal, & Tesluk (2000) sug-

gest, three indicators were used per latent construct

except for PMS use. Indeed, to minimize conver-

gence problems associated with the use of multipli-

cative terms in SEM, and to reduce the number of

parameters associated with the product term, two

indicators were used for PMS diagnostic and inter-

active use.Considering the presence of a product term

(dynamic tension) in the model, it is usually recom-

mended that variables involved in the creation of

the product term be centered prior to their forma-

tion (Cortina et al., 2001; Hartmann & Moers,

1999). Two main reasons justify the use of devia-

tion scores. First, they minimize identiWcation

11 Respondents were asked to distribute 100 points among the

four ideal cultural types (rational, hierarchical, developmental,

and group) along four dimensions. A score was compiled for

each cultural type by averaging the ratings obtained on the four

dimensions. An overall measure of culture was developed by

subtracting the mean score of the developmental and group cul-

ture (focus on Xexibility) from the mean score of the rational

and hierarchical culture (focus on control). By representing the

net value of the control/Xexibility dimension, the results reX-

ect the importance of control values for each organization.

12 Composite indices represent aggregates of items which are

used as manifest indicators of a latent construct. As suggestedby Hall, Snell, and Foust (1999), items parcelling presents sev-

eral advantages. First, it tends to provide results that are more

reliable and normally distributed, and to have values that are

more continuously distributed. Furthermore, by reducing

sources of contamination, composite indices contribute to the

overall Wt of the model. Finally, these indices are useful to re-

duce the number of parameters in the model and thus contrib-

ute to model identiWcation. Using a partial disaggregation

approach, each dimension is represented as a separate latent

variable indicated by composites of sub-scales. Several compos-

ites are formed for each dimension in which each composite is a

mean of items (Bagozzi & Heatherton, 1994).


15/30


problems caused by the correlation between the

variables and the products created from them. Sec-

ond, they allow the interpretation of the coeY-

cients obtained for the lower-order eV

ects (maineVects).13 Hence, PMS diagnostic and interactive

use were centered prior to the formation of the

product term.

Results

Structural equation models

Table 2 presents the results of two structural

equation models. Model A tests the speciWc rela-

tionships between diagnostic and interactive uses

of PMS, capabilities and performance (main

eVects). This model is used to speciWcally test

Hypothesis 1, 2 and 4a. Model B introduces the

dynamic tension resulting from a balanced use of

PMS in a diagnostic and interactive fashion (inter-

action term). This model is used to test Hypotheses

3 and 4b speciWcally, and to provide a complemen-

tary testing of Hypotheses 1, 2 and 4a. For both

models, goodness-of-Wt indices respect the recom-

mended threshold mentioned previously (see Foot-

note 7) and thus, reXect a good Wt of the data to themodel. Table 3 presents the results of six sub-group

analyses performed to validate the robustness of

the theoretical model using environmental uncer-

tainty, size and organizational culture as splitting

variables. Every model respects the recommended

threshold mentioned previously.

Hypothesis tests

Diagnostic and interactive use, and capabilities

As reX

ected by models A and B ofTable 2, diag-nostic use of PMS is signiWcantly and negatively

related to capabilities of market orientation, entre-

preneurship, innovativeness and organizational

learning (p < 0.05). The same negative and signiW-cant relationships are also suggested by the six sub-

group analyses (Table 3), providing strong support

for Hypothesis 1.

Furthermore, in both model A and B, there are

statistically signiW

cant positive relationshipsbetween interactive use of PMS and capabilities of

market orientation, entrepreneurship, innovative-

ness and organizational learning (p


16/30


but not signiWcant paths between the four capabili-

ties and performance. Hence, the indirect relation-

ship between diagnostic and interactive use of

PMS and performance is not supported. Hypothe-

sis 4b suggests an indirect eVect of dynamic tension

on performance through the four capabilities. The

absence of statistically signiWcant relationships

between the four capabilities and performance also

precludes the support of this hypothesis. The sameconclusion is also reXected in the sub-group analy-

ses where no signiWcant relationships are estab-

lished between the four capabilities and

performance.

In sum, Hypotheses 1 and 2 concerning the

direct relationship between diagnostic and

interactive use of PMS and capabilities of market

orientation, entrepreneurship, innovativeness and

organizational learning receive strong support.

The positive relationship suggested by Hypothesis

3 among dynamic tension resulting from the bal-

anced use of PMS in a diagnostic and interactive

fashion and the four capabilities receive partial

support in two sub-group analyses (high environ-

mental uncertainty and Xexibility values). The sign

of these relationships has been reversed in two sub-

group analyses (low environmental uncertainty

and control values). Lastly, the indirect relation-

ships between PMS use and performance proposedby Hypothesis 4 is not supported.

Discussion

First, the results of this study strongly suggest

that an interactive use of PMS fosters capabilities

of market orientation, entrepreneurship, innova-

tiveness, and organizational learning. Indeed, by

focusing organizational attention on strategic pri-

orities and stimulating dialogue, PMS contribute

Table 2

Results of the structural equation models

Note:SigniWcant at the 0.10 level; SigniWcant at the 0.05 level; SigniWcant at the 0.01 level.

Description of path and expected sign Model A Model B

Path coeYcient Z-statistics Path coeYcient Z-statisticsPMS diagnostic use!Market orientation () 3.838 1.984 5.011 2.118

PMS diagnostic use!Entrepreneurship () 5.957 2.037 8.606 2.179

PMS diagnostic use! Innovativeness () 5.817 2.034 7.525 2.176

PMS diagnostic use!Organizational learning () 5.717 2.003 7.367 2.136

PMS interactive use!Market orientation (+) 4.199 2.164 4.526 2.331

PMS interactive use!Entrepreneurship (+) 6.109 2.084 7.304 2.256

PMS interactive use! Innovativeness (+) 6.023 2.101 6.451 2.275

PMS interactive use!Organizational learning (+) 6.141 2.147 6.565 2.321

Dynamic tension!Market orientation (+) n/a n/a 0.009 0.328

Dynamic tension!Entrepreneurship (+) n/a n/a 0.030 0.731

Dynamic tension! Innovativeness (+) n/a n/a 0.030 0.909

Dynamic tension!Organizational learning (+) n/a n/a 0.063 1.547

Market orientation!

Performance (+) 1.570 1.536 1.767 1.731

Entrepreneurship !Performance (+) 1.619 1.076 1.698 1.264

Innovativeness! Performance (+) 3.783 1.016 4.218 1.159

Organizational learning! Performance (+) 0.718 1.048 0.828 1.225

PMS diagnostic use!Performance () 3.832 0.760 6.102 0.893

PMS interactive use!Performance (+) 3.655 0.726 4.806 0.855

Dynamic tension!Performance (+) n/a n/a 0.081 2.438

Fit indices of the modelChi-square 284.012 571.250

DF 137 214

NNFI 0.972 0.948

CFI 0.978 0.956

RMSEA 0.0530 0.0661


17/30


Table3

Resultsofthesub-groupanalyses

Note:SigniWcantatthe0.10level;SigniWcantatthe0.05level;SigniWc

antatthe0.01level.

Descriptionofpathandexpectedsign

PathcoeYcients

Environmentalun

certainty

Size

Organizationalculture

(i)Low

(ii)High

(iii)Small

(

iv)Large

(v)Control

(vi)Flexibility

PMSdiagnosticuse!

Marketorientation()

6.902

2.752

2.295

4.059

2.794

4.291

PMSdiagnosticuse!

Entrepreneu

rship()

14.991

3.952

4.758

6.859

5.369

6.451

PMSdiagnosticuse!

Innovativen

ess()

13.618

3.665

3.728

6.436

4.40

6.518

PMSdiagnosticuse!

Organizationallearning()

10.763

4.123

3.700

6.181

4.547

6.079

PMSinteractiveuse!

Marketorie

ntation(+)

4.161

3.170

2.473

3.10

1.863

4.108

PMSinteractiveuse!

Entrepreneu

rship(+)

8.343

4.304

4.511

4.590

3.208

5.910

PMSinteractiveuse!

Innovativen

ess(+)

7.566

4.183

3.589

4.467

2.664

5.986

PMSinteractiveuse!

Organizatio

nallearning(+)

6.384

4.755

3.826

4.577

2.910

5.823

Dynamictension!

Marketorienta

tion(+)

0.132

0.028

0.018

0.138

0.283

0.077

Dynamictension!

Entrepreneurship(+)

0.151

0.092

0.011

0.176

0.253

0.085

Dynamictension!

Innovativeness

(+)

0.063

0.072

0.013

0.005

0.201

0.073

Dynamictension!

Organizationallearning(+)

0.290

0.129

0.051

0.045

0.381

0.157

Marketorientation!

Performance

(+)

0.273

1.482

0.744

0.721

1.1168

2.441

Entrepreneurship!

Performance(+)

0.029

0.472

0.267

1.256

1.199

4.032

Innovativeness!

Performance(+)

1.820

0.206

0.626

2.270

2.059

8.787

Organizationallearning!

Perform

ance(+)

0.111

0.102

0.150

0.878

0.566

0.833

PMSdiagnosticuse!

Performance()

6.618

0.190

0.477

5.785

1.753

5.470

PMSinteractiveuse!

Performance(+)

3.916

0.299

0.948

4.081

0.790

4.349

Dynamictension!

Performance(+)

0.010

0.182

0.133

0.025

0.003

0.129

Fitindicesofthemodel

Chi-square

449.846

467.961

522.492

3

43.160

373.931

478.892

DF

214

214

214

2

14

214

214

NNFI

0.926

0.937

0.938

0.944

0.938

0.937

CFI

0.938

0.947

0.947

0.952

0.947

0.946

RMSEA

0.068

0.071

0.081

0.056

0.064

0.072

Numberofcases

206

177

217

1

66

154

229


18/30


to the process of knowledge generation and dis-

semination, and foster collaboration throughout

the organization. These Wndings support Simons

(1990) model that views control systems as morethan mechanistic tools used to support strategy

implementation, but also powerful devices to stim-

ulate and manage the emergence of strategies

throughout the organization. These results are also

complementary to the empirical studies conducted

by Abernethy and Brownell (1999) and Bisbe and

Otley (2004) that also support the role of MCS in

an innovative and changing context. However,

while these two studies suggest a moderate eVect of

interactive use on the relationship between innova-

tion/strategic change and performance, the current

results provide evidence of a direct relationship

between interactive use and capabilities leading to

strategic choices and performance. This diVerence

can be explained in part by the focus of previous

studies on the interactive use of MCS while the

current study integrates also the diagnostic use as

well as the dynamic tension.

Second, the results of this study strongly suggest

that a diagnostic use of PMS exerts negative pres-

sure on capabilities of market orientation, entre-

preneurship, innovativeness, and organizational

learning. By creating constraints to ensure compli-ance with orders, diagnostic use has a negative

eVect on these four capabilities. This is coherent

with the model of Simons and other critics of

traditional mechanistic use of control systems.

Interestingly, in terms of correlations (Table 1),

capabilities are positively and signiWcantly corre-

lated with the diagnostic use of PMS (except for

entrepreneurship). Although there is no reason

that the sign of a beta coeYcient must be the same

sign as the correlation between two variables (Ben-

tler & Chou, 1987), this diV

erence needs to be dis-cussed. DiVering signs are usually taken as an

indicator of a negative suppression. This happens

when the sign of a regression weight of an indepen-

dent variable is the opposite of what would be

expected on the basis of its correlation with the

dependant variable (Tabachnick & Fidell, 2001).

The suppressor variable enhances the eVects of

other variables by suppressing irrelevant variance

to the prediction of an independent variable. This

would mean that from a univariate perspective, the

correlation coeYcient between diagnostic use and

capabilities is positive, but in a multivariate setting,

the interactive use acts as a negative suppressor fordiagnostic use. This is consistent with previous the-

oretical arguments suggesting complementarity

and competition between the diagnostic and inter-

active use of PMS. This also justiWes the integra-

tion of both types of PMS use in the theoretical

and empirical analyses.

The results suggest that diagnostic and interac-

tive uses of PMS contribute both speciWcally and

collectively to capabilities. In some circumstances,

a balanced use creates dynamic tension which

ensures that positive eVects of interactive use on

capabilities will be achieved, and that such tension

expands these positive eVects of interactive use by

fostering organizational dialogue, stimulating cre-

ativity, and focusing organizational attention. At

Wrst sight, the results did not reXect any signiWcant

relationship between dynamic tension and capabil-

ities. Ex post analyses revealed that the impact of

tension varies in opposite directions depending on

environmental uncertainty and organizational cul-

ture, which explains that, overall, no relationship

was reXected. The following theoretical arguments

are provided to tentatively explain these unex-pected results.

On the one hand, Wrms facing high environmen-

tal uncertainty and having Xexibility values appear

to beneWt from dynamic tension. In a context of

high environmental uncertainty reXecting constant

change and intense competition, Wrms require inno-

vation and creativity throughout the organization

(Miller, 1988; Miller, Drge, & Toulouse, 1988).

Crucial organizational capabilities need to be stim-

ulated as much as possible without neglecting orga-

nizational outcomes (Bourgeois & Eisenhardt,1988; Ghemawat & Costa, 1993). Dynamic tension

becomes one trigger to improve these capabilities.

Furthermore, the four capabilities are supported by

Xexibility values which reXect loose controls, lateral

communication and free Xow of information

(Burns & Stalker, 1961; Quinn & Cameron, 1983;

Quinn, 1988). This context is particularly suitable

for interactive use and positive conXicts which stim-

ulate dialogue and foster creativity.


19/30


On the other hand, the results suggest that Wrms

facing low environmental uncertainty and having

control values are negatively aVected by this kind

of tension. In a context where the environment ismore stable, capabilities for diVerentiation become

less critical and so may be the need for creative

conXicts to foster them (Porter, 1985). Also, Wrms

having control values reXect tight control, vertical

communication and restricted Xow of information

(Burns & Stalker, 1961). Hence, dynamic tension

may be less useful because operations are well

known, stability and conformity are valued, and

grass-roots initiatives are not speciWcally encour-

aged by top management (Quinn, 1988; Quinn &

Cameron, 1983). Dynamic tension disturbs organi-

zational routines where procedures, roles, and

internal processes are established and well known.

The structural coeYcients related to dynamic

tension are low, which implies that tension also

has negative eVects. As observed by Marginson

(2002), tension between diagnostic and interac-

tive uses can create possibilities for trade-oVs and

organizational bias. As Lewis (2000) suggests,

tension represents a double-edged sword. It may

serve to trigger change while simultaneously acti-

vating defensive routines that inhibit change.

This means that the positive eVect of dynamictension discussed earlier may be reduced because

of the negative dynamics inherent to tension.

Hence, the net value of structural coeYcients is

positive but not necessarily high. More research

is needed to provide a deeper understanding of

the dynamic interplay between the positive and

negative eVects of tension resulting from

balanced use of PMS in a diagnostic and interac-

tive fashion.

The relationships between diagnostic and

interactive use of PMS, as well as dynamic ten-sion, and performance appear to be indirect.

PMS use inXuences the four capabilities which in

turn, inXuence organizational performance.

However, no clear support has been established

for Hypothesis 4. Indeed, despite a positive and

signiWcant correlation between performance and

each of the four capabilities (Table 1), no signiW-

cant relationships between capabilities and per-

formance has been established in the structural

models. This might be because of the restrictive

scope of the performance variable which is lim-

ited to the Wnancial dimension. Capabilities

inX

uence other dimensions of performance, suchas market development, customer satisfaction,

development of new products and market share,

which have not been captured in the current

analyses.

No speciWc hypothesis has been proposed for

the direct eVect of PMS use on organizational per-

formance. However, our evidence regarding the

direct eVect of PMS use on Wnancial performance

while not yet reXecting signiWcant results provides

interesting insights (Table 2). In fact, in some cir-

cumstances the impact of diagnostic use on per-

formance is presented as positive while interactive

use appears to negatively inXuence performance.

This would mean that even if diagnostic use works

against the deployment of capabilities, it may con-

tribute to organizational performance by moni-

toring goal achievement, restricting risk taking,

providing boundaries for innovation, and closely

monitoring variations in eVectiveness. Still, the

positive inXuence of interactive use on capabilities

may not be costless. Interactive use necessitates

activities that may be time consuming, such as

various meetings with superiors, sub-ordinatesand peers, as well as continual challenge to and

debate of data and underlying assumptions.

Moreover, important resource requirements may

be necessary to develop new ideas, support trial-

and-error processes, and coordinate grass-roots

initiatives.

Furthermore, results show that dynamic ten-

sion has a direct positive and signiWcant impact

on performance (0.081, p < 0.001). This relation-ship is observed particularly for Wrms facing high

environmental uncertainty and havingX

exibilityvalues (see Table 3). Assuming that the product

term is a good proxy for dynamic tension, this

suggests that dynamic tension may represent a

capability and a source of competitive advantage.

More speciWcally, the ability to reach a balance

between two opposing uses of PMS that simulta-

neously try to stimulate innovation while search-

ing for predictable achievements may represent a

capability which is valuable, distinctive, and


20/30


imperfectly imitable. This Wnding contradicts cur-

rent literature tied to a resource-based view which

states that control systems are not considered to

be a source of competitive advantage becausethey are readily transferred and they lead Wrms to

fully realize only the beneWts of internal resources

(Barney et al., 2001). More research is also needed

concerning the balanced use of PMS as an

organization capability.

Conclusion

The aim of this study was to examine, from a

resource-based perspective, how the use of one

management control system (PMS) can act as an

antecedent to capabilities supporting the material-

ization of strategic choices. Overall, the results

suggest that PMS used in an interactive (diagnos-

tic) fashion contribute positively (negatively) to

the deployment of capabilities of market orienta-

tion, entrepreneurship, innovativeness, and orga-

nizational learning. From their balanced use

emerges dynamic tension which also contributes

positively to capabilities in a context of high envi-

ronmental uncertainty and organizational culture

reXecting Xexibility values. Globally, dynamic ten-sion contributes to organizational performance

and their management may constitute a form of

capability.

This study contributes to current research at

the boundary between MCS and strategy in three

ways. First, it integrates a very inXuential frame-

work from the Weld of strategy, the resource-based

view, to a management accounting setting. Over

the last decade, RBV has become one of the stan-

dard theories to explain the source of competitive

advantage and the performance diV

erences amongWrms over time. This theoretical framework pro-

vides interesting insights into the dual roles of

MCS in the implementation and formulation of

strategies. Secondly, previous researches examin-

ing the relationship between MCS and strategy

content have provided ambiguous and contradic-

tory results. It has been argued that these ambigu-

ous results were partly attributable to the absence

of a theoretical framework founded on the

resource-based view and the limited attention

devoted to the dynamic tension resulting from

diVerent uses or roles of MCS. This paper has

moved the analysis from the strategic-choice levelto the capabilities level, and provides evidence for

relationships between MCS and capabilities. Also,

the attention devoted to the dynamic tension gen-

erated by the joint eVect of diagnostic and interac-

tive use allows a deeper understanding of the

complexity surrounding the use of MCS to stimu-

late innovation while enabling achievement of

predictable goals. Despite the current perspective

reXected by the resource-based view that control

systems do not represent a source of competitive

advantage, we suggest the opposite view and open

the debate concerning the role of MCS as a capa-

bility which is valuable, distinctive and imper-

fectly imitable.

Third, this study contributes to the emerging

line of research which provides empirical tests for

the model proposed by Simons (1995). The results

support the view of control systems as tools con-

tributing to the implementation of intended strat-

egies, but also as tools stimulating the emergence

of new strategies. This paper expands Simons

model in several ways. On the one hand, Simons

does not make an explicit distinction betweeninnovation and organizational learning, referring

to them rather indistinctly in his argumentation.

In this study, innovation and learning are pre-

sented as two speciWc capabilities, and market ori-

entation and entrepreneurship are added as

capabilities also inXuenced by an interactive use of

MCS to foster emergence of new strategies. On the

other hand, as previously mentioned, Simons

framework leaves relatively unanswered the ques-

tion why organizations combine diagnostic con-

trol interactive control. This paper addresses thisissue by examining the notion of dynamic tension

as the result of the use of PMS in a joint diagnos-

tic and interactive fashion to manage inherent

organizational tension between freedom to inno-

vate and predictable goal achievement. It is

argued that dynamic tension is used to ensure that

positive eVects of interactive use on capabilities

will be achieved and to expand those positive

eVects of interactive use.


21/30


This study also has important implications for

management practices. As Epstein (2002) indicates,

there is a need for managers to be aware of drivers

of value in organizations and the causal relation-ships critical to drive that value. This study reXects

the importance of capabilities as drivers of value

and also the potential of PMS to contribute to

these capabilities. Furthermore, the capabilities to

be developed with PMS are not limited to the

development and implementation ofWnancial and

non-Wnancial indicators. The signiWcant and dis-

tinctive eVect of PMS for the organization comes

from the balance between diagnostic and interac-

tive use by managers.

As with other empirical studies, this one is sub-

ject to potential limitations. First, four capabili-

ties leading to competitive advantage and

strategic renewal are discussed. Nevertheless,

other capabilities would have been plausible (e.g.,

alliancing, manufacturing Xexibility, etc.). Sec-

ond, only one control system was examined

(PMS) while other systems could provide similar

or diVerent conclusions (e.g. budget, project man-

agement, etc.). Third, performance is measured

using a subjective instrument and reXects only the

Wnancial dimension. Even if there is evidence in

favour of consistent results between objective andsubjective measurement, the results should be

interpreted with caution considering the potential

for bias. Fourth, the dynamic-tension variable is a

proxy based on the product term of diagnostic

and interactive use. Moreover, our methodologi-

cal design does not allow the distinction between

the positive and negative eVects of tension on

capabilities and performance. Only a net value

is available and used to examine the relationships.

Fifth, using the survey method to collect data cre-

ates the potential for bias due to commonresponse. Also, no clear-cut evidence of causality

can be established with survey data obtained

from cross-sectional analyses. Rather the evi-

dence must be considered consistent with theoret-

ical arguments and predicted relationships.

Finally, any generalizations taken from this

studys results to manufacturing organizations or

beyond cannot be made without considerable

caution because of the scope of the current sam-

ple (i.e., small-to-medium size manufacturing

Wrms) and the presence of non-response bias for

the organizational-learning variable.

The results of this study provide guidance forfuture research. The inXuence of PMS on capabili-

ties should be examined using a non-linear model.

The impact of diagnostic and interactive use may

diVer depending on various levels of capabilities.

Also, the model could be tested with control sys-

tems other than PMS. Furthermore, the results

suggest a positive inXuence of dynamic tension cre-

ated by the use of PMS in a joint diagnostic and

interactive fashion on capabilities and perfor-

mance. Future research could further investigate

the moderator inXuence of environmental uncer-

tainty and organizational culture on the

22. man control systems and strategy aos a resource based perspective 2006

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