An empirical investigation of the relationship between strategic performance measurement systems, role clarity, psychological

empowerment and work outcomes

by

Matthew Hall

Department of Accounting and Business Information Systems The University of Melbourne

VIC 3010 mhal@unimelb.edu.au

April 2004

Please do not quote.

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An empirical investigation of the relationship between strategic performance measurement systems, role clarity, psychological

empowerment and work outcomes.

ABSTRACT

This study examines the effect of strategic performance measurement systems (PMS) on

managers’ role clarity, psychological empowerment, job satisfaction and managerial

performance. Data were collected using a survey of 83 strategic business unit managers from

Australian manufacturing organisations. Consistent with the need to define the underlying

theoretical properties of management accounting practices (Luft and Shields 2003), the study

identifies comprehensiveness as an information characteristic of strategic PMS. Results show

that strategic PMS is not directly associated with managerial performance. Rather, strategic

PMS has an indirect positive association with managerial performance through psychological

empowerment and role clarity. Results show that strategic PMS is positively associated with

all four dimensions of psychological empowerment (meaning, competence, self-determination

and impact), with dimensions of psychological empowerment positively associated with job

satisfaction and managerial performance. Further results show that strategic PMS is

positively associated with two dimensions of role clarity (goal clarity and process clarity),

which, in turn, is positively associated with psychological empowerment, job satisfaction and

managerial performance. The results indicate that the comprehensiveness of strategic PMS

provides performance information that improves managers’ psychological empowerment and

clarifies managers’ role expectations, which, in turn, improve managerial performance.

Keywords: strategic performance measurement systems, role clarity, psychological

empowerment, survey, managerial performance

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INTRODUCTION

Management accounting systems have developed a more strategic orientation aimed at

providing information to enhance the firm’s competitive position (Chenhall 2003; Ittner,

Larcker and Randall 2003). Organisations have developed more strategic performance

measurement systems (PMS) to provide managers and employees with information about

multiple dimensions of the firm’s operations (Fullerton and McWatters 2002; Lillis 2002).

PMS are evolving to include a more diverse set of performance measures (Malina and Selto

2001; Ittner et al. 2003) and performance measures that are linked to the strategy of the firm

and provide information about parts of the value chain (Nanni, Dixon and Vollman 1992;

Neely, Gregory and Platts 1995). The move towards more strategic PMS has been

popularised in techniques such as the balanced scorecard (Kaplan and Norton 1996), tableau

de bord (Epstein and Manzoni 1998) and performance hierarchies (Lynch and Cross 1992).

Prior research has focused primarily on the relationship between strategic PMS and

organisational outcomes, such as achievement of competitive strategic priorities,

organisational performance and share price returns (Chenhall 2003; Ittner et al. 2003).

Further research has focused on managers’ perceptions of the value of information from

strategic PMS. This research supports the role of strategic PMS in providing an overall

measure of business performance, which managers perceive as important and useful for

managing their businesses (Malina and Selto 2001). Other research has focused on the use of

multiple performance measures in performance evaluation judgements (Schiff and Hoffman

1996; Lipe and Salterio 2000, 2002; Moers 2004). This research has examined the potential

bias associated with weighting different types of performance measures when making

judgements about subordinate performance. Overall, prior research demonstrates links

between strategic PMS and organisational outcomes, and explores the way that strategic PMS

are used by superiors in performance evaluation judgements.

Although these studies provide insights into the role and effects of strategic PMS, there is

little empirical research examining the effect of strategic PMS on the work behaviour of

individuals in the organisation. Studies examining links between management control

systems and organisational outcomes assume that such systems affect the behaviour of

individuals within the organisation, which then facilitates the achievement of organisational

goals. However, as Chenhall (2003) notes, this assumption involves broad leaps in logic and

there is no compelling evidence to suggest that these links exist. Similarly, Covaleski, Evans,

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Luft and Shields {, 2003 #537} argue, in the context of budgetary research, that studies at the

organisational level of analysis remain somewhat limited because they are based upon

assumptions about, rather than a detailed investigation of, individual behaviour. In addition,

little is known about the nature of the relationship between strategic PMS and individual

behaviour. Shields et al. (2000) note that much management accounting research examines

the direct effects of control system components on work performance, however; few studies

examine whether control system components have indirect effects on work performance.

Researchers have argued that cognitive and motivational mechanisms can help explain the

relationship between management control systems and individual behaviour (Ilgen, Fisher and

Taylor 1979; Bonner and Sprinkle 2002). However, it is unclear whether the effect of

strategic PMS on work performance (if any) is direct, or indirect through cognitive and

motivational mechanisms. This is important because there can be theoretical differences

between direct- and indirect-effects models that can have practical implications (Shields et al.

2000). Based on this discussion, the primary purpose of this study is to investigate the nature

of the relationship between strategic PMS and work performance.

Although some research has attempted to define the theoretical properties of strategic

PMS (Malmi 2001; Chenhall 2003; Ittner et al. 2003), there is a lack of research that

investigates empirically the information characteristics of strategic PMS. Luft and

Shields (2003) argue that it is essential to define the underlying theoretical properties of

variables used to describe management accounting practices. However, little is known about

the attributes of strategic PMS and what distinguishes them from other PMS. As such, the

study also investigates empirically the information characteristics of strategic PMS.

The study uses data collected from a survey of strategic business unit (SBU) managers to test

hypothesised relationships between strategic PMS, role clarity, psychological empowerment,

job satisfaction and managerial performance. Results show that strategic PMS is not directly

associated with managerial performance. Rather, strategic PMS has an indirect positive

association with managerial performance through psychological empowerment and role

clarity. Results show that strategic PMS is positively associated with all four dimensions of

psychological empowerment (meaning, competence, self-determination and impact), with

dimensions of psychological empowerment positively associated with job satisfaction and

managerial performance. Further results show that strategic PMS is positively associated

with two dimensions of role clarity (goal clarity and process clarity), which, in turn, is

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positively associated with dimensions of psychological empowerment, job satisfaction and

managerial performance. As such, the study helps to explain why strategic PMS affect

organisational outcomes by showing that strategic PMS has positive effects on the behaviour

of individuals within the organisation. The study also indicates that cognitive and

motivational mechanisms help to explain the effect of strategic PMS on work performance.

This contributes to prior research which has examined the direct- and indirect-effects of

management control systems on work performance (Shields et al. 2000). The study also

extends the limited body of prior research that has examined the relationship between

management control system attributes and psychological empowerment (Spreitzer 1995;

1996; Smith and Langfield-Smith 2003) and role clarity (Chenhall and Brownell 1988).

Furthermore, the study identifies comprehensiveness as an information characteristic of

strategic PMS, which furthers our conceptual understanding of the nature and specific

information characteristics of strategic PMS. The study also develops and empirically

validates an instrument to measure the strategic PMS construct.

The remainder of the paper contains four sections: the next section reviews the related

literature and develops the theoretical model, including presentation of the hypotheses. The

research method, including sample selection and variable measurement, is then presented.

This is followed by presentation of the results. The final section discusses the results and

concludes the paper.

THEORY DEVELOPMENT AND HYPOTHESES FORMULATION

Role and motivational theories are used to examine the nature of the relationship between

strategic PMS and individual behaviour. The hypothesised relationships are illustrated in

Figure 1. In this section the literature that examines the relationships between these variables

is reviewed and the hypotheses are presented.

<insert Figure 1 here>

Strategic performance measurement systems

Luft and Shields (2003) argued that it is essential to define the underlying theoretical

properties of variables used to describe management accounting practices. The literature has

identified several important features of strategic PMS. These include a comprehensive and

diverse set of performance measures, the integration of measures with strategy and links to

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valued organisational outcomes, and the coverage of performance measures related to

different parts of the organisation (Neely et al. 1995; Malina and Selto 2001; Malmi 2001;

Ittner et al. 2003).

Drawing on these descriptions of strategic PMS, it is argued that an information characteristic

of strategic PMS is comprehensiveness; defined here as the extent to which a strategic PMS

provides managers with comprehensive performance information. It is argued that the

comprehensiveness of strategic PMS derives from the provision of performance measures that

describe the important parts of the SBU’s operations and the integration of measures with

strategy and the value chain.

Themes identified in the performance measurement literature include a comprehensive set of

measures, coherence, balance, use of financial and non-financial measures, and the coverage

of measures (for example, see Neely et al. 1995; Kaplan and Norton 1996; Malina and Selto

2001; Lillis 2002). Malina and Selto (2001) found that a balanced scorecard was perceived as

comprehensive when it provided an overall measure of business performance. Similarly, a

manager interviewed as part of Malina and Selto’s (2001) study indicated that “the BSC is

trying to give us a broader business set of measures of success than more traditional financial

or market share. It wraps a set of things together that makes sense for managing the

business” (Malina and Selto 2001, p.70). Ittner, Larcker and Randall (2003) also argued that

a broad set of measures, or ‘measurement diversity’, is an attribute of strategic PMS.

‘Measurement diversity’ relates to supplementing traditional financial measures with a

diverse mix of non-financial measures that are expected to capture key strategic performance

dimensions that are not accurately reflected in short-term accounting measures. A common

theme is the use of a broad set of measures that cover different parts of the organisation’s

operations.

The integration of measures with strategy and providing information about parts of the value

chain is also an important part of strategic PMS. Nanni et al. (1992) argued that PMS that

integrate actions across functional boundaries, and focus on strategic results, are critical in

supporting the new manufacturing and competitive environments facing organisations. In

addition, the integration of measures with the strategy and objectives of the organisation

provides performance information about progress on important dimensions of

performance (Nanni et al. 1992; Neely et al. 1995; Kaplan and Norton 1996; Malina and Selto

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2001; Malmi 2001). Chenhall (2003) found that integration was an important attribute of

strategic PMS.

In summary, it is argued that an information characteristic of strategic PMS is

comprehensiveness; that is, the extent to which the PMS provides managers with

comprehensive performance information. Comprehensiveness derives from the provision of

performance measures that describe the important parts of the SBU’s operations and from the

integration of measures with strategy and across the value chain. It is the comprehensive

nature of strategic PMS that is expected to influence the behaviour of individuals in the

organisation.

Strategic PMS and managerial performance

Proponents of BSC-type strategic PMS have argued that these systems can enhance

performance (Kaplan and Norton 1996). This is achieved by focusing effort on achieving

goals, concentrating attention on critical processes, highlighting tradeoffs to ensure optimal

decisions, and helping managers learn about strategies and drivers of performance (Kaplan

and Norton 1996; Epstein and Manzoni 1998; Atkinson and Epstein 2000). Psychological

theories suggest that managers’ perform better when provided with goals and comprehensive

feedback regarding their performance. In particular, managers are more motivated and

perform better when provided with specific goals and specific feedback regarding their efforts

and performance (Ilgen et al. 1979; Locke, Shaw, Saari and Latham 1981). Strategic PMS

can provide comprehensive feedback on a range of performance measures to improve

performance.

Strategic PMS also provide relevant information for decision making. Linking performance

measures to strategy can result in actionable measures that managers can focus on to improve

performance. Integrating measures across the value chain can help managers understand

cross-functional relationships that may lead to improved problem solving and decision

making (Banker, Chang and Pizzini 2002). In this way, strategic PMS guide decision making

and help to evaluate past decisions (Malina and Selto 2001). Kren (1992) argued that

job-relevant information can improve performance because it provides managers with more

accurate predictions of environmental states, which in turn allows a better understanding of

decision alternatives and the most effective course of action. Kren (1992) found a positive

association between job-relevant information and managerial performance. This suggests that

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the comprehensive performance information from strategic PMS will provide more relevant

and specific information for decision making, resulting in improved managerial performance.

This leads to H1:

H1: There is a positive association between strategic PMS and managerial performance

Psychological empowerment

Psychological empowerment is a cognitive construct and refers to an individual’s intrinsic

task motivation (Thomas and Velthouse 1990). Psychological empowerment has been

defined theoretically and empirically as a set of four cognitions; meaning, competence,

self-determination, and impact (Thomas and Velthouse 1990; Spreitzer 1995). Meaning

refers to the value placed on work judged in relation to an individual’s own ideals or

standards. It relates to an individual’s intrinsic caring about a task (Thomas and Velthouse

1990). Competence refers to an individual’s belief in his/her capacity to perform a job with

skill (Thomas and Velthouse 1990). Self-determination refers to an individual’s perceptions

of the degree of choice they have in initiating and performing work behaviours (Thomas and

Velthouse 1990; Spreitzer 1995). Impact refers to the extent to which an individual believes

they can influence outcomes at work. It relates to the extent to which individuals can produce

intended effects in their work role (Thomas and Velthouse 1990).

SPMS and psychological empowerment

Collins (1982) argued that management accounting systems can be used to motivate

individuals to perform. Specifically, performance information can serve a motivational

function by providing feedback about task behaviour (Ilgen et al. 1979; Collins 1982; Luckett

and Eggleton 1991). Feedback theories suggest that performance information can improve

motivation by providing information about effort-performance expectancies (Ilgen et al.

1979). Strategic PMS proponents argue that these systems can communicate information

about strategic priorities and the direction of the firm (Kaplan and Norton 1996). The

comprehensiveness of strategic PMS is critical in providing individuals with information

about the direction and performance of the organisation, which should increase psychological

empowerment.

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Strategic PMS are expected to increase managers’ perceptions of each dimension of

psychological empowerment. Strategic PMS can make individuals’ jobs more meaningful as

comprehensive information about strategies and performance can help people make sense of

where the organisation is headed and how their role fits within the broader scope of the

organisation. Conger and Kanungo (1988) note that performance information strengthens

individuals’ perceptions of meaning and purpose.

Gist and Mitchell (1992) argued that competence perceptions are strengthened by providing

information that increases individuals’ understanding of task attributes, complexity and the

task environment. The comprehensiveness of strategic PMS can improve managers

understanding of their tasks and task environment. Performance information is fundamental

for reinforcing a sense of competence (Ilgen et al. 1979; Lawler 1992; Spreitzer 1995).

Thomas et al. (1993) found that executives who use relatively more information tend to feel

as though they have more control over issues affecting the organisation, which may reinforce

their sense of competence.

Strategic PMS can help individuals to take the initiative and can improve their ability to

initiate and complete tasks. Individuals require information about where the organisation is

headed in order to feel capable of taking the initiative (Kanter 1989). Similarly, employees

must have information about performance to direct and manage their own

performance (Lawler 1992). Strategic PMS can improve managers’ understanding of where

the organisation is headed, providing managers with the confidence to initiate and complete

tasks.

Individuals need performance information in order to make and influence decisions that are

consistent with the organisation’s priorities (Lawler 1992). Without knowledge of results,

individuals are unlikely to exert influence in their work area (Kraimer, Seibert and Liden

1999). Liden et al. (2000) argued that performance feedback increases impact by providing

information about the quality and effectiveness of an individual’s performance. Strategic

PMS can strengthen managers’ knowledge of strategies and organisational priorities and

therefore improve their ability to influence and act in ways that are consistent with those

priorities. Without comprehensive performance information, managers are unlikely to fully

understand the operations of their work unit, or the wider organisation, and therefore feel

unable to make an impact in their work area.

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Prior research shows a positive association between performance information and overall

psychological empowerment. Spreitzer (1995; 1996) found that access to performance

information was positively associated with psychological empowerment. Randolph (1995)

found that providing strategic and performance information helped to develop empowered

employees. In summary, strategic PMS are expected to positively influence managers’

perceptions of psychological empowerment, which leads to H2:

H2: There is a positive association between strategic PMS and the four dimensions of

psychological empowerment.

Psychological empowerment and managerial performance

Empowered individuals should perform better than those individuals who are less

empowered (Liden et al. 2000). Thomas and Velthouse (1990) argued that perceptions of

empowerment are directly linked to a range of behavioural factors, including activity,

concentration, initiative, resilience and flexibility, which, in turn, should improve

performance. Spreitzer (1995) argued that psychological empowerment has great potential to

contribute to managerial performance because the work processes of managers cannot be

completely structured by rules and procedures. Furthermore, higher levels of internal

motivation are related to greater work effectiveness (Hackman and Oldham 1980).

Empowerment research has examined the relationship between overall psychological

empowerment and work performance, with results showing that higher levels of

psychological empowerment improve work performance (Spreitzer 1995; Koberg, Boss,

Senjem and Goodman 1999). However, recent research has examined the relationships

between the specific dimensions of psychological empowerment and work performance.

Spreitzer et al. (1997) found that, of the four dimensions of psychological empowerment, only

competence and impact were positively associated with work effectiveness. Similarly, Liden

et al. (2000) found that only competence and impact were positively associated with job

performance. Therefore, although prior research indicates that meaning and

self-determination are positively correlated with work performance, it does not support a

direct association of meaning and self-determination to work performance. As such, only

competence and impact are expected to influence managerial performance, which leads to H3.

H3: There is a positive association between the competence and impact dimensions of

psychological empowerment and managerial performance.

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Psychological empowerment and job satisfaction

Job satisfaction was one of the earliest anticipated outcomes of empowerment (Spreitzer et al.

1997). Meaning and self-determination are expected to improve job satisfaction. A sense of

meaning is considered necessary for individuals to feel satisfied at work. Having a job that

allows fulfilment of ones’ desired work values are likely to increase job satisfaction (Locke

1976). Low levels of meaning have been linked to feelings of apathy and lower work

satisfaction (Thomas and Velthouse 1990). Liden et al. (2000) argued that individuals who

feel their jobs are significant and worthwhile have higher levels of satisfaction compared to

those who feel their jobs have little value. Empirical research has found a positive association

between meaning and work satisfaction (Spreitzer et al. 1997; Liden et al. 2000).

Self-determination positively influences job satisfaction due to its effects on intrinsic

motivation. Individuals who have autonomy in determining their actions and behaviours find

work more interesting and rewarding, thus creating feelings of satisfaction with their job.

Higher levels of autonomy increases the amount of intrinsic rewards from work (Thomas and

Velthouse 1990). Self-determination improves job satisfaction as accomplishments can be

attributed more to the individual than to other persons (Liden et al. 2000). Empirical results

show a positive relationship between self-determination and job satisfaction (Spreitzer et al.

1997; Smith and Langfield-Smith 2003). Although prior research indicates that competence

and impact are positively correlated with job satisfaction, it does not support a direct

association of competence and impact to work performance (Spreitzer et al. 1997). As such,

only meaning and self-determination are expected to influence job satisfaction. Based on this

discussion, the following hypothesis is proposed:

H4: There is a positive association between the meaning and self-determination dimensions of

psychological empowerment and job satisfaction.

Job satisfaction and managerial performance

Prior research indicates a modest but positive correlation between job satisfaction and

individual performance (Vroom 1964; Organ 1977; Petty, McGee and Cavender 1984;

Hochwater, Perrewe, Ferris and Brymer 1999). However, there is still uncertainty regarding

the causal ordering of the job satisfaction-performance relationship. Some researchers argue

that satisfaction precedes performance (Schwab and Cummings 1970), while others argue that

performance precedes satisfaction (Lawler and Porter 1967). Recent theoretical research

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argues that happy and satisfied workers are likely to put forth more effort, perform more

extra-role behaviours, obtain more social support and valued positions in the organisation, and

be more successful in interpersonal relationships, which, collectively, should improve work

effectiveness (Staw, Sutton and Pelled 1994; Wright and Staw 1999). Thus, managers who

are more satisfied with their jobs are likely to put forth more effort and be more interested in

their work, leading to improved performance. This leads to H5:

H5: There is a positive association between job satisfaction and managerial performance.

Role clarity

Role clarity refers to an individual’s perceptions about the expectations and behaviours

associated with his/her role (Kahn, Wolfe, Quinn, Snoek and Rosenthal 1964).1 King and

King (1990) describe four forms of role clarity, or conversely, role ambiguity: (1) ambiguity

regarding what is required or uncertainty over the scope of responsibilities, (2) ambiguity

regarding how responsibilities are to be met or uncertainty about the role behaviours

necessary to fulfil responsibilities, (3) ambiguity regarding role senders or uncertainty about

whose expectations for role behaviours must be met, and (4) ambiguity regarding the

consequences of role behaviour or uncertainty about the effects of actions on well being, the

role set and the organisation. It is expected that strategic PMS will affect managers’

perceptions regarding the scope of their responsibilities and their required role behaviours.

Therefore, this study examines the clarity of expectations about the goals and objectives of a

work role (termed goal clarity) and clarity of the behaviours necessary to fulfil a work

role (termed process clarity).

Strategic PMS and role clarity

Management accounting systems can be used to prescribe normative role behaviour by

informing individuals about what is expected of them in their role (Collins 1982).

Specifically, performance information can serve a directional function by making specific the

goals and appropriate behaviours associated with a work role (Ilgen et al. 1979). In particular,

strategic PMS can be used to send signals about the preferences, values and types of

opportunities that individuals should exploit. This is achieved by focusing systematically on

1 Kahn et al. (1964) use the term role ambiguity, which refers to uncertainty regarding parts of an individual’s role. In this study the term role clarity is used. However, this is conceptually no different from role ambiguity (Sawyer 1992). Role clarity is expressed as the extent of certainty, rather than ambiguity, of role expectations.

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certain types of information and ignoring others. Each set of performance measures

communicates different priorities and allows employees to infer the strategic direction of the

organisation (Simons 2000). This enables the organisation to bring strategies to life and

communicate goals and business direction (Simons 2000).

Performance information is a key antecedent of role clarity. Lawler (1992) argued that

information about the organisation’s mission and performance is necessary for individuals to

know how to behave. Similarly, access to information about the organisation allows

individuals to see the ‘big picture’ and develop alternative frames of reference for

understanding their roles within the organisation (Bowen and Lawler 1992).

Strategic PMS can increase role clarity by (1) clarifying role expectations and (2) clarifying

the appropriate behaviours for fulfilling those expectations. Strategic PMS can clarify role

expectations by providing comprehensive information about the organisation’s strategies and

operations. This information should improve manager’s understanding of the goals and

objectives of their work role. Strategic PMS can clarify appropriate behaviours by providing

comprehensive performance information that improves managers’ understanding of the

drivers of performance, the effects of their actions on parts of the value chain, and links

between different parts of the organisation’s operations. Banker et al. (2002) argued that the

integration of measures across the value chain can help individuals to understand

cross-functional relationships. Similarly, Malina and Selto (2001) found that the balanced

scorecard was important for managing the business when performance information was

comprehensive and integrated. As such, the information provided by strategic PMS is

expected to improve managers’ understanding of their work roles and thus increase role

clarity. This leads to H6.

H6: There is a positive association between strategic PMS and role clarity.

Role clarity and psychological empowerment

Role clarity is proposed as an antecedent of psychological empowerment because unless

individuals have a clear sense of their responsibilities, and how to achieve them, they are

unlikely to believe that they have the necessary skills and abilities to perform tasks

adequately (i.e., feel empowered). Spreitzer (1996) argued that creating clear goals, tasks and

lines of responsibility improves empowerment in the workplace. Role clarity increases

intrinsic motivation to perform as it increases the expectation that effort will lead to

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performance and that performance will lead to outcomes (Jackson and Schuler 1985; Tubre

and Collins 2000).

Role clarity is expected to improve each dimension of psychological empowerment.

Spreitzer (1996) argued that it is only when individuals understand their roles that those roles

can take on personal meaning. Individuals with an understanding of their work goals and how

to achieve them can judge the value of their work and therefore experience higher perceptions

of meaning. Clear lines of responsibility and authority are related to perceptions of

confidence (Conger and Kanungo 1988). Similarly, clear task requirements and low

uncertainty are also related to feelings of competence (Gist and Mitchell 1992). Individuals

with clear work goals and an understanding of how to achieve those goals are likely to feel

that they can perform their job with skill and thus feel more competent. Individuals who are

uncertain of their role expectations are likely to hesitate or not take the initiative due to

feelings of uncertainty (Spreitzer et al. 1997). In contrast, individuals are likely to feel that

they have control over their work environment under high levels of role clarity. This creates

feelings of being able to determine and take actions to complete tasks, and thus increase

self-determination. A lack of role clarity is likely to make individuals’ feel helpless and thus

reduce their perceptions regarding the impact they have in their work area (Spreitzer et al.

1997). In contrast, individuals who understand their work roles are more likely to take

actions and decisions that influence results in their work area (Sawyer 1992). Prior research

shows that higher levels of role ambiguity are related to lower levels of psychological

empowerment (Spreitzer 1996; Smith and Langfield-Smith 2003). This leads to H7:

H7: There is a positive association between role clarity and the four dimensions of

psychological empowerment.

Role clarity and job satisfaction

Kahn et al. (1964) argued that uncertainty about the expectations of a work role can lead to

tension, anxiety, fear, anger, hostility, futility and apathy. These feelings decrease an

individual’s satisfaction with their work role. Individuals are more satisfied with their jobs

when they are certain about their role expectations and the most appropriate way to perform

their work tasks. Prior research indicates that role ambiguity decreases job satisfaction (Kahn

et al. 1964; Jackson and Schuler 1985; Sawyer 1992; Abramis 1994; Breaugh and Colihan

1994). This discussion results in H8:

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H8: There is a positive association between role clarity and job satisfaction.

Role clarity and managerial performance

Cognitive and motivational theories suggest that role clarity will improve managerial

performance. From a cognitive perspective, individuals require sufficient information to

perform tasks effectively. A lack of information regarding the goals of the job and the most

effective job behaviours can result in effort that is inefficient, misdirected or insufficient for

the task(s), and thus reduce job performance (Jackson and Schuler 1985; Tubre and Collins

2000). From a motivational perspective, individuals require sufficient incentive to perform

tasks effectively. Role clarity strengthens the expectancy that effort will result in

performance, and therefore is expected to improve motivation, and consequently job

performance (Jackson and Schuler 1985; Tubre and Collins 2000). Empirical results indicate

that role ambiguity decreases work performance (Jackson and Schuler 1985; Abramis 1994;

Tubre and Collins 2000). This leads to H9:

H9: There is a positive association between role clarity and managerial performance.

The next section describes the research method.

RESEARCH METHOD

Sample and data collection

Data were collected by a questionnaire administered to 83 strategic business unit (SBU)

managers within large Australian manufacturing organisations. The SBUs were independent

companies or divisions of larger companies. Large manufacturing organisations were chosen

as examination of the strategic PMS construct requires that individuals have access to

relatively sophisticated PMS. Larger organisations are more likely to have developed

sophisticated PMS due to a greater availability of resources and a greater need for more

comprehensive systems (Chenhall 2003). In addition, the literature surrounding the

development of strategic PMS relates, primarily, to a manufacturing environment (Lynch and

Cross 1992; Nanni et al. 1992; Neely et al. 1995).

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A list of senior managers of the largest Australian manufacturing firms was obtained from a

commercial mailing list provider. From this list, 400 managers were selected, at random, to

form the sampling frame for the study. Prior to distributing the questionnaire, each manager

was contacted by telephone to ensure that the manager was still employed by the firm and that

the manager’s name and address details were accurate. Thirty-one managers could not be

contacted because they no longer worked for their firm, the phone number was disconnected

or did not answer, or the firm was no longer in operation. This resulted in a revised sampling

frame for the study of 369 managers. Managers were sent a questionnaire package by post,

fax or email. The explanatory letter indicated that the study was voluntary and that responses

were anonymous and would be treated with strict confidence. A recent practitioner article on

strategic PMS was included as a way of thanking the participant for his/her involvement in

the study. The inclusion of a token incentive is recommended by Dillman (2000) and has

been used successfully in prior management accounting research (Davila 2000). A

thankyou/reminder postcard was sent to participants approximately two weeks after the initial

distribution of the questionnaire. Finally, a follow-up phone call was made to respondents to

encourage completion of the questionnaire approximately two weeks after the reminder

postcard. If the manager had misplaced the original questionnaire, a replacement

questionnaire was sent.

Responses

Of the 369 questionnaires sent to participants, 83 were received, which provides a response

rate of 22.5%. The response rate compares favourably with recent accounting (Moores and

Yuen 2001; Baines and Langfield-Smith 2003) and non-accounting (Samson and Terziovski

1999; Terziovski and Sohal 2000; Gordon and Sohal 2001) surveys of business unit managers

in Australian manufacturing firms.

Non-response bias was assessed by a comparison of variable scores between the first 20% and

last 20% of respondents. There were no significant differences on any of the variables, which

provides no evidence of non-response bias. The follow-up phone calls were also used to

assess non-response bias. Discussions with approximately 40 non-respondents revealed that

the most common reason for not completing the questionnaire was that the manager was too

busy.2 Many managers indicated that they received too many surveys to have time to

2 This is not unexpected as the sample consists of very senior managers.

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complete them all3, or that it was company policy not to respond to voluntary surveys. In

addition, some managers were away overseas or interstate for an extended period and thus

were unavailable to complete the questionnaire. These reasons for not responding to the

survey are very similar to those reported in other studies of senior managers (for example,

(Baines and Langfield-Smith 2003; Chenhall 2003; Subramaniam and Mia 2003).

Demographic information was collected from respondents regarding tenure in current

position, tenure in company, age, gender, business unit size (number of employees), job title,

and main manufacturing industry. The average age of respondents was 46.84 years with an

average length of employment in their current position of 5.14 years and their company for

10.64 years. Average firm size was 336.13 employees (see Table 1). Eighty-two respondents

were male and one was female. Table 2 reports the job title, manufacturing industry

classification, and size of respondents’ firms.

Survey design and variable measurement

The questionnaire consisted of a series of multi-item constructs to measure each of the

variables. Established instruments were used to measure each variable, except for the

strategic PMS construct. Given the novelty of this instrument, the questionnaire was subject

to extensive testing prior to administration. During the development of the questionnaire it

was regularly reviewed by three senior management accounting academics. This resulted in a

series of adjustments and refinements to the wording of several items, and to the layout and

presentation of the questionnaire. The questionnaire was also pilot tested using four senior

managers, who were asked to complete the questionnaire and discuss over the telephone any

problems or concerns. This resulted in some minor changes to the wording of some items.

Discussion of the instruments used to measure each variable follows, with the wording of the

items used in the questionnaire provided in the Appendix. Descriptive statistics for each

variable are provided in Table 3.

Strategic performance measurement systems

Prior research relating to the types of performance measures in PMS has used instruments that

ask respondents to indicate the extent to which they use or find helpful a series of specific

performance measures (for example, Hoque and James 2000). A limitation of this type of 3 As the manager was typically the head of the organisational unit, they were usually the first point of contact for surveys that require responses from the organisation’s point of view, thus increasing the number of surveys that they receive. Several managers indicated that they received at least five surveys per week.

18

instrument is that it assumes that the performance measures contained in the instrument are

representative of the specific types of performance measures used by the firms in the sample.

Firms may use similar financial performance measures; however, non-financial and/or

strategic measures are likely to be unique to each firm (Lipe and Salterio 2000). As such, five

items were developed to measure the extent to which the PMS provided a variety of

performance information about the important parts of the SBU’s operations. To measure the

extent of integration of measures with strategy and across the value chain, four items were

taken from Chenhall (2003). These items describe how the PMS provides links to the

strategies and objectives of the business unit and links to the activities of other business units.

A second measure of strategic PMS was developed to assess the validity of the multi-item

measure. A forced-choice response format was used to ensure it was different from the

multi-item Likert-type measure, which is consistent with the principle of using

maximally-dissimilar forms of ratings (Campbell and Fiske 1959; Murphy and Davidshofer

1998). The second measure provided respondents with two descriptions of their PMS. One

description was designed to capture a “comprehensive” PMS, the other description a “partial”

or less comprehensive PMS. Respondents were asked to indicate which of the alternative

descriptions better represented their PMS. The comprehensive description was coded one (1)

and the partial description coded zero (0).

The multi-item strategic PMS scale was subject to an exploratory factor analysis. The results

of a principal components analysis with orthogonal rotation produced one factor with an

eigenvalue greater than one. As shown in Table 4, all factor loadings are above 0.70. The

factor analysis indicates that the nine items are representative of a single strategic PMS

construct. The Cronbach alpha for the strategic PMS scale is 0.9461, which demonstrates

sufficient internal reliability (Nunally 1978).

As a test of convergent validity, the scores on the multi-item strategic PMS scale4 were

correlated with the scores on the forced-choice strategic PMS scale. The point-biserial

correlation between the multi-item strategic PMS scale and forced-choice strategic PMS scale

is 0.66 (p<0.001), which provides support for the convergent validity of the multi-item

strategic PMS scale. In addition, the results of an independent samples t-test revealed that the

mean score on the multi-item strategic PMS scale was significantly higher for those

4 The overall score for each respondent on the multi-item strategic PMS scale was calculated as an average of the nine items.

19

respondents who indicated a “comprehensive” PMS (µ=5.507) compared to those who

indicated a “partial” PMS (µ=3.827) (t=7.867, p<0.001). This supports the ability of the

multi-item strategic PMS scale to distinguish between more and less comprehensive PMS.

The ability to assess the reliability of the multi-item scale led to its use in the hypotheses tests.

Psychological empowerment

Spreitzer (1995) developed a 12-item instrument to measure the four dimensions of

psychological empowerment: meaning, self-determination, competence and impact. The

instrument asks respondents to indicate the extent to which a variety of factors related to each

of the dimensions is evident in their jobs. Results from a confirmatory factor analysis

supported the internal reliability and convergent and discriminant validity of the

instrument (Spreitzer 1995). Spreitzer’s (1995) measure of psychological empowerment has

been used extensively in prior research (Fulford and Enz 1995; Spreitzer et al. 1997; Corsum

and Enz 1999; Koberg et al. 1999; Liden et al. 2000; Siegall and Gardner 2000).

Role clarity

Ilgen and Hollenbeck (1991) argued that research should explicitly define the aspects of role

clarity under examination. This study examines the clarity of expectations about the goals

and objectives of a work role and clarity of the behaviours necessary to fulfil a work role.

Sawyer’s (1992) measures of goal clarity and process clarity address the theoretical definition

of role clarity used in this study. Sawyer (1992, p.134) defined goal clarity as “the extent to

which the outcome goals and objectives of the job are clearly stated and well defined”.

Process clarity was defined as “the extent to which the individual is certain about how to

perform his or her job”. Sawyer (1992) provided support for the discriminant, convergent,

and construct validity of the goal clarity and process clarity scales. A subsequent study by

Beard (1999) provided further support for the instrument. As such, Sawyer’s (1992)

measures of goal clarity and process clarity are used in this study.

Job satisfaction

Job satisfaction was measured using a six-item instrument adapted from Rusbult and

Farrell (Rusbult and Farrell 1983). The instrument asked respondents to indicate the extent to

which they agree or disagree with six statements about their jobs. This scale has been used in

prior accounting studies (Ketchand and Strawser 1998; Smith and Langfield-Smith 2003) and

20

has demonstrated satisfactory internal reliability. This instrument was chosen over the

Minnesota Satisfaction Questionnaire due to its shorter length. It was considered desirable to

limit the length of the questionnaire as much as possible in an attempt to increase the response

rate to the survey.

Managerial performance

Managerial performance was measured using the nine-item scale developed by Mahoney et

al. (1965) This instrument asks managers to rate their performance on eight dimensions of

managerial performance; planning, investigating, coordinating, evaluating, supervising,

staffing, negotiating and representing, and an overall assessment of performance. This

instrument remains the dominant method of obtaining self-rated managerial performance data

in management accounting research (Brownell 1985; Kren 1992; Gul and Chia 1994; Chong

1996; Chong and Chong 2002; Wentzel 2002). Prior research reports Cronbach alphas of

0.8064 (Wentzel 2002) and 0.93 (Chalos and Poon 2000), supporting the internal reliability of

the scale.

Data issues

A small number of responses contained missing data. As such, the data was replaced using

the expectation-maximisation (EM) method in SPSS.5 The EM approach is an iterative

two-stage process where the E-stage makes the best estimates of the missing data and the

M-stage makes parameter estimates assuming the missing data are replaced. This occurs in

an iterative process until the changes in the estimated parameters are negligible and the

missing values are replaced (Little and Rubin 1987; Hair et al. 1998). This resulted in a

complete data set of 83 responses.

The maximum and minimum values for each item were within the theoretical range for each

item. Multivariate outliers were assessed using the Mahalanobis D2 measure, which revealed

the presence of one outlier. Visual inspection of the outlier did not reveal any patterns to

suggest that the case is unrepresentative so the case was retained (Hair et al. 1998).

Mardia’s (1970) test of multivariate kurtosis revealed that the data are multivariate

non-normal (t = 26.076, p < 0.001). As the data are multivariate non-normal, and the sample

5 Little’s MCAR test revealed that the missing data was missing completely at random (MCAR) (chi-square=4.424, degrees of freedom=516, p>0.10). As the data is MCAR, any imputation method can be used ((Hair, Anderson, Tatham and Black 1998)

21

size is well below the recommended minimum sample size of 200 for structural equation

modelling (SEM) (Kline 1998), Partial Least Squares (PLS) was chosen as the analytical

technique to test the hypotheses. PLS is described in the next section.

Partial Least Squares (PLS)

The latent variable modelling technique of PLS is increasingly being used to test path models

in accounting research (Ittner, Larcker and Rajan 1997; Vandenbosch 1999; Anderson,

Hesford and Young 2002; Chenhall 2003). PLS is a “second generation” multivariate

technique, which incorporates multiple dependent constructs, explicitly recognises

measurement error, and explicitly integrates theory with empirical data (Fornell 1982). PLS

makes no distributional assumptions about the data and is particularly suited to studies with

small sample sizes (Wold 1985).

PLS comprises a measurement model and a structural model. The measurement model

specifies relationships between observed items and latent variables. The structural model

specifies relationships between latent constructs. In PLS the measurement and structural

models are estimated simultaneously (Barclay, Thompson and Higgins 1995). However, the

PLS model is typically interpreted in two stages. First, the reliability and validity of the

measurement model is assessed. Second, the structural model is assessed (Barclay et al.

1995). This approach is recommended to maximise interpretability where research

instruments are less developed and/or theory is relatively tentative (Hair et al. 1998). It also

ensures that the researcher has reliable and valid measures of constructs before assessing the

nature of the relationships between constructs (Hulland 1999). As this study is using less

developed research instruments, the two-step approach is adopted. The objective of PLS is to

maximise variance explained, rather than fit, therefore no overall goodness-of-fit measures are

available.6 As such, prediction-orientated measures, such as R2, are used to evaluate PLS

models, with the interpretation of R2 being identical to that used in regression (Chin 1998).

As PLS makes no distributional assumptions, bootstrapping (100 samples) is used to test the

statistical significance of each path coefficient (Chin 1998). The next section reports the

results of the study.

6 Hulland (1999) notes that some PLS algorithms report goodness-of-fit statistics such as the Bentler-Bonnet normed fit index. These statistics are based on the assumption that the estimated model parameters are chosen to minimise the difference between the sample covariances and those predicted by the theoretical model. As PLS does not estimate model parameters in this way, this assumption is not warranted for PLS. Therefore, Hulland (1999) argues that such goodness-of-fit measures are meaningless in evaluating PLS models.

22

RESULTS

Measurement model

The results for the PLS measurement model were obtained from PLS Graph Version 3.0. The

PLS measurement model provides statistics (individual item loadings, average variance

extracted and composite reliability) that are used to assess the reliability and validity of

multi-item instruments.

The reliability of each item is assessed by examining the individual item loadings. The item

loading represents the correlation between each item and its construct (Chin 1998).

Hulland (1999) and Chin (1998) suggest that items with loadings of less than 0.50 should be

dropped. Inspection of the initial item loadings calculated in PLS revealed two items from the

managerial performance scale with loadings less than 0.50.7 Consistent with Hulland (1999)

and Chin (1998), these two items were removed as they add very little to the explanatory

power of the model while potentially biasing the estimates of the parameters linking the

constructs.8 The individual item loadings from the final PLS model are provided in Table 6.

Fornell and Larcker’s (1981) composite reliability score was calculated for each latent

variable. Composite reliability is a means of assessing the internal consistency of the items of

a latent variable (Chin 1998). In this study, all variables reported a composite reliability score

above 0.70 (see Table 5), which demonstrates adequate reliability. Cronbach’s (1951) alpha

statistics are provided for comparison.

7 The items are MP7 and MP8. Appendix 1 provides a description of each item. 8 A possible reason for low item loadings is that the construct to which the item (s) is linked is not unidimensional (Barclay et al. 1995) The dimensionality of the Mahoney et al. (1965) scale was examined using an exploratory factor analysis. The results of a principal components analysis with oblique rotation revealed two factors with eigenvalues greater than one. Items MP1-MP6 and MP9 load on the first factor, and MP7 and MP8 load on the second factor. Thus, in this study, the Mahoney et al. (1965) scale appears to capture two dimensions of managerial performance. The Cronbach alpha for the first dimension of managerial performance (items MP1-MP6 and MP9) is 0.824, and the Cronbach alpha for the second dimension of managerial performance (items MP7 and MP8) is 0.5083, which is well below the standard threshold of 0.70 for established instruments. This indicates that although MP7 and MP8 may form a second dimension of managerial performance, the internal reliability is very low. As such, items MP7 and MP8 are removed from the managerial performance scale and not used in further analysis.

23

The average variance extracted (AVE) measures the “amount of variance that is captured by

the construct in relation to the amount of variance due to measurement error” (Fornell and

Larcker 1981). The AVE can be interpreted as a measure of reliability for a construct and it is

recommended that the AVE should be greater than 0.50, which indicates that the construct

captures more variance in the items than measurement error (Chin 1998; Hair et al. 1998). As

shown in Table 6, the AVE for each construct is 0.50 and above. This indicates that each

construct accounts for 50% or more of the variance of its items.9

The AVE statistics can also be used to assess discriminant validity by calculating the square

root of the AVE statistics and comparing these to the correlations among the latent

variables (Chin 1998). This provides a test of whether more variance is shared between the

latent variable and its set of items than with other latent variables represented by a different

set of items (Chin 1998). Table 7 shows that the square roots of the AVEs are all larger than

their respective correlations, which demonstrates adequate discriminant validity. The next

section reports the tests of hypotheses.

Structural model

Table 7 reports the correlation matrix. It shows significant positive correlations between

strategic PMS and dimensions of psychological empowerment, role clarity, job satisfaction

and managerial performance. Table 8 reports the R2 for each endogenous variable. The

model explains substantial variation in the endogenous variables, particularly job

satisfaction (73.6%) and managerial performance (59.1%). However, the R2 for process

clarity is relatively low (3.3%).

Tests of hypotheses

The structural model was tested in PLS Graph Version 3.0. As PLS makes no distributional

assumptions, bootstrapping (100 samples with replacement) is used to test the statistical

significance of each path coefficient (Chin 1998). The standardised path coefficients and

t-values for each estimated path are shown in Table 8. H1 argued for a direct positive

association between strategic PMS and managerial performance. However, the relationship

9 As indicated earlier, items MP7 and MP8 were removed from the managerial performance scale due to low item reliabilities. As shown in Table 6, the AVE for the managerial performance construct is 0.50. If MP7 and MP8 are included in the managerial performance construct the AVE is reduced to 0.413, well below the threshold of 0.50. This provides further evidence that these two items should be removed from the managerial performance scale.

24

between strategic PMS and managerial performance is not significant (-0.002, p>0.05). Thus,

H1 was rejected.

The second part of the model argued that strategic PMS increases managerial performance

through its effect on psychological empowerment. Results show positive associations

between strategic PMS and three of the four dimensions of psychological empowerment;

namely meaning (0.278, p<0.01), competence (0.191, p<0.05) and impact (0.302, p<0.01).

There was a marginally significant positive association between strategic PMS and

self-determination (0.172, p=0.056). Thus, H2 was supported.

Psychological empowerment was expected to influence job satisfaction and managerial

performance. There is a positive association between competence and managerial

performance (0.199, p<0.05), however, the relationship between impact and managerial

performance is not statistically significant (-0.022, p>0.05). Therefore, H3 was partially

supported. Results show a positive association between meaning and job satisfaction (0.520,

p<0.01), and between self-determination and job satisfaction (0.238, p<0.05), which supports

H4. H5 was supported by the positive association between job satisfaction and managerial

performance (0.215, p<0.05). Therefore, psychological empowerment had a direct

association with managerial performance, and an indirect association through job satisfaction.

The third part of the model argued that strategic PMS would increase psychological strategic

PMS and goal clarity (0.435, p<0.01), and a marginally significant positive association

between strategic PMS and process clarity (0.181, p=0.054). Thus, there was support for H6.

H7 argued that role clarity would increase each dimension of psychological empowerment.

Results show positive associations between goal clarity and two dimensions of psychological

empowerment; meaning (0.434, p<0.01) and impact (0.329, p<0.01). Further results reveal

positive associations between process clarity and competence (0.380, p<0.01), impact (0.234,

p<0.01) and self-determination (0.490, p<0.01). As such, H7 was partially supported.

Overall, this analysis shows that higher levels of role clarity are associated with higher levels

of psychological empowerment.

Role clarity was expected to directly effect job satisfaction and managerial performance.

There is a positive association between goal clarity and job satisfaction (0.290, p<0.01), and

between goal clarity and managerial performance (0.368, p<0.05). However, process clarity

25

was not associated with job satisfaction or managerial performance. Therefore, there is partial

support for H8 and H9. An overview of the empirical model is provided in Figure 2.

<insert Figure 2 here>

The next section discusses the results of the study and concludes the paper.

DISCUSSION AND CONCLUSIONS

The primary purpose of this study was to investigate the relationship between strategic PMS

and individual behaviour. Data collected from a survey of 83 strategic business unit

managers were used to test hypothesised relationships between strategic PMS, role clarity,

psychological empowerment, job satisfaction and managerial performance. The results did

not support the view that strategic PMS is directly associated with managerial performance.

Rather, strategic PMS is indirectly associated with managerial performance through its effects

on psychological empowerment and role clarity.

The results suggest that strategic PMS serve two important functions. First, strategic PMS

increased intrinsic task motivation by increasing all four dimensions of psychological

empowerment (meaning, self-determination, competence and impact). This indicates that

strategic PMS, through the motivational function of feedback, can help improve managers’

intrinsic task motivation. The results are consistent with arguments that access to

comprehensive performance information is needed to develop empowered employees (Kouzes

and Posner 1987; Kanter 1989; Bowen and Lawler 1992; Randolph 1995; Quinn and

Spreitzer 1997). The results indicate that strategic PMS, in addition to other management

control system attributes (for example, performance-contingent rewards (Spreitzer 1995)), is

an important antecedent of psychological empowerment. Importantly, dimensions of

psychological empowerment were directly and indirectly associated with managerial

performance. Consistent with prior research (Spreitzer et al. 1997), competence was

positively associated with managerial performance. Meaning and self-determination had an

indirect positive association with managerial performance through job satisfaction. These

results are consistent with prior research, which suggests that there are different outcomes for

the dimensions of psychological empowerment (Spreitzer et al. 1997)

26

Second, strategic PMS helped to clarify managers work roles by increasing goal clarity and

process clarity. This indicates that strategic PMS, through the directional function of

feedback, can help improve managers’ understanding of the goals and objectives of their work

roles, and the most appropriate behaviours to fulfil their work roles. This supports the view

that PMS can communicate organisational priorities and performance information to

individuals (Simons 2000), which can help improve managers understanding of their own

work roles. The study indicates that organisations need to develop more comprehensive PMS

to communicate strategies and operational information to improve mangers understanding of

the goals and appropriate behaviours associated with their work roles.

Dimensions of role clarity were directly and indirectly associated with managerial

performance. Goal clarity was positively associated with managerial performance. This

indicates that an increased understanding of work goals provides important work-relevant

information and motivation to improve work performance (Jackson and Schuler 1985; Tubre

and Collins 2000). This suggests that for the relatively unstructured work roles of senior

managers, the establishment of clear goals and objectives improves managers’ work

performance. Role clarity had an indirect effect on work performance through psychological

empowerment and job satisfaction. Dimensions of role clarity were positively associated with

dimensions of psychological empowerment. This supports prior research which shows that

role clarity is an antecedent of psychological empowerment (Spreitzer 1996); however, this

study extends prior research by examining associations between two specific dimensions of

role clarity and each dimension of psychological empowerment. As such, the study furthers

our knowledge of the relationship between role clarity and psychological empowerment. The

results also support the use of more specific role constructs as advocated in prior

research (King and King 1990; Sawyer 1992). In addition, goal clarity was positively with

job satisfaction, which, in turn, was positively associated with managerial performance.

In summary, the results of the study indicate that strategic PMS, through its effects on role

clarity and psychological empowerment, improves managerial performance. Therefore, the

results are consistent with prior theoretical and empirical research, which emphasises the

mediating roles of cognitive and motivational mechanisms in explaining the relationship

between management control systems and work performance (Ilgen et al. 1979; Chenhall and

Brownell 1988; Bonner and Sprinkle 2002). This suggests that research examining the

individual performance effects of performance information (and management control systems

27

in general) should include, where theoretically justified, psychological variables that can help

to explain the relationship between performance information and work performance.

The second purpose of the study was to investigate empirically the information characteristics

of strategic PMS. Prior research has focused on the extent to which organisations use specific

types of performance measures (for example, Hoque, Mia and Alam 2001) or the relative

emphasis on financial and non-financial performance measures (Abernethy and Lillis 1995;

Perera, Harrison and Poole 1997). This study contributes to the literature by examining

empirically the information characteristics of strategic PMS, rather than the specific types of

performance measures used by organisations.

The study identified comprehensiveness as an information characteristic of strategic PMS.

The results suggest that the comprehensive nature of strategic PMS derives from the provision

of performance measures that describe the important parts of the SBUs operations and from

the integration of measures with strategy and across the value chain. Thus, it appears that in

developing more comprehensive PMS, business units develop a more complete set of

performance measures to describe the important parts of the business units’ operations and

seek to structure the PMS to provide information about strategies and different parts of the

value chain. This is consistent with prior research highlighting the important attributes of

strategic PMS (Nanni et al. 1992; Neely et al. 1995; Malina and Selto 2001; Ittner et al.

2003). The measurement of strategic PMS by reference to specific information

characteristics, rather than the mere existence of systems labelled ‘balanced scorecard’, is

consistent with defining the underlying properties of variables used to describe management

accounting practices (Ittner et al. 2003; Luft and Shields 2003). Thus, the study advances our

conceptual understanding of the underlying properties of strategic PMS.

The findings need to be interpreted in light of the strengths and limitations of the study. A

new instrument was developed to measure the strategic PMS construct. Although the

instrument was validated against an alternative measure, and exhibited satisfactory

measurement properties, future research could further refine and validate this instrument.

Based on prior literature, the study identified comprehensiveness as an information

characteristic of strategic PMS. However, there may be other information characteristics that

describe strategic PMS that were not captured in this study.

28

The study presents statistical associations that are consistent with the theory developed in the

study. However, the cross-sectional research design precludes any claims regarding causality

of relationships among the variables in the model. Longitudinal studies that examine the

levels of role clarity, psychological empowerment, job satisfaction and managerial

performance, before and after the introduction of strategic PMS, may help to resolve this

issue. The study used self-assessed performance ratings, which may introduce bias.

Although managers are considered the best judges of their own performance (Brownell 1995),

future research would benefit from confirmation of managers’ ratings using supervisor

ratings.

Despite these limitations, the findings of the study indicate that comprehensiveness is an

information characteristic of strategic PMS. The comprehensiveness of strategic PMS

improves managers’ role clarity and psychological empowerment, which, in turn, improve

managerial performance.

29

Table 1: Descriptive statistics for demographic variables Variable Minimum Maximum Mean St. Dev. Tenure in current position (years) 1 25 5.14 5.95

Tenure in company (years) 1 37 10.64 8.37

Age (years) 26 64 46.84 8.38

Firm Size (no. of employees) 10 4100 336.13 497.03

Table 2: Overview of demographic data

Panel A: Job title Frequency %

Managing Director 22 26.51 Chief Executive Officer 6 7.23 General Manager 32 38.55 Director of Operations 14 16.87 Other 9 10.84

Total sample 83 100

Panel B: ANZSICa Manufacturing industry classification Frequency %

21 - Food, beverage and tobacco 8 9.64 22 - Textile, clothing, footwear and leather 3 3.61 23 - Wood and paper products 6 7.23 24 - Printing, publishing and recorded media 3 3.61 25 - Petroleum, coal, chemical and associated products 12 14.46 26 - Non-metallic mineral products 4 4.82 27 - Metal products 11 13.25 28 - Machinery and equipment 25 30.12 29 - Other 11 13.25

Total sample 83 100

Panel C: Size of strategic business unit Frequency %

No. of employees 0-200 41 49.40 201-500 31 37.35 501-1000 8 9.64 1000+ 3 3.61

Total sample 83 100

a ANZSIC – Australia and New Zealand Standard Industrial Classification

30

Table 3: Descriptive statistics

Variable Minimum Maximum Mean Standard Deviation

Strategic PMS 1 6.89 4.657 1.289 Meaning 2 7 5.916 1.019 Competence 4 7 5.891 0.729 Impact 3 7 6.121 0.778 Self-determination 2.33 7 5.971 0.938 Managerial Performance 4 7 5.405 0.610 Job Satisfaction 1.5 7 5.311 1.305 Goal Clarity 3 7 5.963 0.829 Process Clarity 2.8 7 5.191 0.871

Table 4: Factor loadings for multi-item strategic PMS instrument from exploratory factor analysis (orthogonal rotation)

Item Factor loading

SPMS1 0.915 SPMS2 0.782 SPMS3 0.843 SPMS4 0.817 SPMS5 0.896 SPMS6 0.864 SPMS7 0.852 SPMS8 0.739 SPMS9 0.836

Eigenvalue 6.350 % variance explained 70.559%

Table 5: Composite reliability and Cronbach alpha statistics

Variable Composite Reliability Cronbach Alpha

Strategic PMS 0.955 0.946 Meaning 0.960 0.935 Competence 0.895 0.804 Impact 0.905 0.842 Self-determination 0.929 0.880 Managerial Performance 0.874 0.824 Job Satisfaction 0.957 0.943 Goal Clarity 0.905 0.868 Process Clarity 0.909 0.875

31

Table 6: Individual item loadings and average variance extracted (AVE) statistics from PLS measurement model

Variable (AVE) and item Loading Standard Error t-statistic

Strategic PMS (AVE=0.705) SPMS1 0.9201 0.0135 67.9938 SPMS2 0.7863 0.0754 10.4219 SPMS3 0.8371 0.0715 11.7104 SPMS4 0.8097 0.0562 14.4008 SPMS5 0.8961 0.0226 39.6354 SPMS6 0.8601 0.0614 14.0053 SPMS7 0.8589 0.0352 24.3975 SPMS8 0.7334 0.0707 10.374 SPMS9 0.8413 0.0356 23.6474 Meaning (AVE=0.889) MEAN1 0.9481 0.0169 56.2431 MEAN2 0.9606 0.0108 88.9984 MEAN3 0.9193 0.0226 40.7353 Competence (AVE=0.742) COMP1 0.868 0.0316 27.4732 COMP2 0.777 0.0793 9.8013 COMP3 0.9317 0.0117 79.6121 Impact (AVE=0.761) IMP1 0.8502 0.0337 25.262 IMP2 0.8807 0.0487 18.0918 IMP3 0.8856 0.0485 18.2589 Self-determination (AVE=0.813) SD1 0.9084 0.0696 13.0433 SD2 0.9458 0.0182 51.9311 SD3 0.8476 0.0475 17.8581 Managerial Performance (AVE=0.500) MP1 0.6538 0.0838 7.7995 MP2 0.568 0.1262 4.5014 MP3 0.7129 0.071 10.037 MP4 0.6902 0.0755 9.1404 MP5 0.7654 0.045 16.9953 MP6 0.7476 0.0507 14.7312 MP9 0.7861 0.0449 17.523 Job Satisfaction (AVE=0.788) JS1 0.9154 0.0229 39.9721 JS2 0.8007 0.0858 9.3307 JS3 0.8672 0.0401 21.6035 JS4 0.9194 0.0159 57.6592 JS5 0.9342 0.0163 57.162 JS6 0.882 0.0329 26.8206 Goal Clarity (AVE=0.655) GC1 0.7912 0.0461 17.1664 GC2 0.7927 0.0479 16.5663 GC3 0.7858 0.0741 10.6066 GC4 0.797 0.0599 13.3029 GC5 0.877 0.0345 25.3855 Process Clarity (AVE=0.667) PC1 0.7917 0.0537 14.7358 PC2 0.8133 0.0436 18.6541 PC3 0.8487 0.0418 20.3131

32

PC4 0.8103 0.0563 14.395 PC5 0.8184 0.0399 20.4948

Table 7: Correlationsa and square root of average variance extracted (AVE) statisticsb

Strategic

PMS Meaning Competence Impact Self-

determinationManagerial

PerformanceJob

Satisfaction Goal

Clarity Process Clarity

Strategic PMS 0.840 Meaning 0.477 0.943 Competence 0.351 0.654 0.861 Impact 0.489 0.614 0.609 0.872 Self- determination 0.285 0.382 0.465 0.691 0.902 Managerial Performance 0.314 0.601 0.529 0.469 0.385 0.707 Job Satisfaction 0.424 0.773 0.574 0.575 0.556 0.588 0.888 Goal Clarity 0.434 0.595 0.552 0.619 0.465 0.637 0.693 0.809 Process Clarity 0.181 0.405 0.557 0.511 0.56 0.497 0.516 0.681 0.817 a All correlations above 0.20 are statistically significant (p<0.01, two-tailed). b Diagonal elements are the square roots of the AVE. Off-diagonal elements are the correlations between the latent variables calculated in PLS.

34

Table 8: Path coefficients and R2, PLS structural model Variable (R2)

Path to: Goal Clarity

Process Clarity

Meaning

Competence

Impact

Self-determination

Job Satisfaction

Managerial Performance

Strategic PMS 0.435 (5.761)***

0.181 (1.630)*

0.278 (2.871)***

0.191 (1.711)**

0.302 (2.890)***

0.172 (1.612)* -

-0.002 (0.022)

Goal Clarity (0.189) - -

0.434 (3.004)***

0.210 (1.390)

0.329 (2.387)***

0.056 (0.441)

0.290 (3.134)***

0.368 (1.954)**

Process Clarity (0.033) - -

0.059 (0.513)

0.380 (3.387)***

0.234 (2.435)***

0.490 (4.014)***

-0.025 (0.239)

0.039 (0.257)

Meaning (0.445) - - - - - -

0.520 (6.222)*** -

Competence (0.509) - - - - - - -

0.199 (1.648)**

Impact (0.475) - - - - - - -

-0.022 (0.135)

Self- determination (0.360) - - - - - -

0.238 (1.758)** -

Job Satisfaction(0.736) - - - - - - -

0.215 (1.873)**

Managerial Performance (0.562) - - - - - - - -

n = 83 Each cell reports the path coefficient (t-value). ***p<0.01, **p<0.05, *p<0.06 (all one-tailed)

35

Figure 1: Theoretical model

Strategic PMS

Managerial Performance

Role Clarity• Goal Clarity • Process Clarity

Psychological Empowerment

Job Satisfaction

CompetenceImpact

MeaningSelf-determination

H1

H2

H3

H4

H5

H6

H7H8

H9

36

Figure 2: Empirical model with standardised PLS path coefficients

All paths are positive and statistically significant (p<0.05), except Strategic PMS → Process Clarity and Strategic PMS → Self-determination (p<0.06). All tests are one-tailed.

0.434

0.329

0.238 0.490

0.234

0.380

0.199

0.290

0.368

0.215

0.435

Strategic PMS

Managerial Performance

Psychological Empowerment

Job Satisfaction

Competence

Impact

Meaning

Self-determination

Process Clarity

Goal Clarity

0.191

0.302

0.278

0.172

0.181

0.520

Role Clarity

37

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APPENDIX 1: SURVEY ITEMS Strategic PMS multi-item instrument (1=not at all, 7=to a great extent) Item Label The performance measurement system provides a broad range of performance information about different areas of the business unit The performance measurement system is produced in a fully documented form, which provides a record for evaluating performance It provides a diverse set of measures related to the key performance areas of the business unit It provides consistent and mutually reinforcing links between the current operating performance of your business unit and the long term strategies of the organization The performance measurement system provides information on different dimensions of the business unit’s performance It links together the activities of your business unit to the achievement of the goals of the organization It provides a variety of information about important aspects of the business unit’s operations It shows how the activities of your business unit affect the activities of other units within the organization The performance measurement system provides a range of measures that cover the critical areas of the business unit’s operations

SPMS1

SPMS2

SPMS3

SPMS4

SPMS5

SPMS6

SPMS7

SPMS8

SPMS9

SPMS2, SPMS4, SPMS6 and SPMS8 were taken from Chenhall (2003). The other items were developed for this study. Strategic PMS forced-choice instrument

Type of PMS Description

Comprehensive The performance measurement system consists of a diverse set of measures which capture the key performance areas of the business unit. It presents information about different aspects of the business unit’s operations, which provides a comprehensive and complete view of the business unit’s performance

Partial The performance measurement system provides measures which cover some, but not all, of the key performance areas of the business unit. It presents information that focuses on a few aspects of the business unit’s operations, which provides a partial view of the business unit’s performance

Psychological empowerment (1=strongly disagree, 7=strongly agree) Item Label Meaning The work I do is very important to me My job activities are personally meaningful to me The work I do is meaningful to me Competence I am confident about my ability to do my job

MEAN1 MEAN2 MEAN3

COMP1

45

I am self-assured about my capabilities to perform my work activities I have mastered the skills necessary for my job Self-determination I have significant autonomy in determining how I do my job I can decide on my own how to go about doing my work I have considerable opportunity for independence and freedom in how I do my job Impact My impact on what happens in my work area is large I have a great deal of control over what happens in my work area I have significant influence over what happens in my work area

COMP2 COMP3

SD1 SD2 SD3

IMP1 IMP2 IMP3

Role clarity (1=very uncertain, 7=very certain) Item Label Goal Clarity My duties and responsibilities The goals and objectives for my job How my work relates to the overall objectives of my work unit The expected results of my work What aspects of my work will lead to positive evaluations Process Clarity How to divide my time among the tasks required of my job How to schedule my work day How to determine the appropriate procedures for each work task The procedures I use to do my job are correct and proper Considering all your work tasks, how certain are you that you know the best way to do these tasks?

GC1 GC2 GC3 GC4 GC5

PC1 PC2 PC3 PC4

PC5

Job satisfaction (1=strongly disagree, 7=strongly agree) Item Label If I had to decide all over again, I would still choose the job I have now If a good friend of mine was interested in working in a job like mine for my employer, I would recommend it This job is my ideal job I like my job I am satisfied with my current job This is just like the job I wanted when I started in this job

JS1 JS2

JS3 JS4 JS5 JS6

Managerial performance (1=well below average, 7=well above average) Item Label Planning: Determining goals, policies, and courses of action such as work scheduling, budgeting, and programming Investigating: Collecting and preparing of information usually in the form of records, reports, and accounts (measuring output, record keeping, and job analysis) Coordinating: Exchanging information with people in the organisation other than my subordinates in order to relate and adjust procedures, policies and programs Evaluating: Assessment and appraisal of proposals or of reported/observed performance (e.g., employee appraisals, judging

MP1

MP2

MP3

46

financial performance and product inspection) Supervising: Directing, leading, and developing your subordinates Staffing: Maintaining the work force of your responsibility area (e.g., selecting and promoting your subordinates) Negotiating: Purchasing, selling, or contracting for products or services (e.g., contracting suppliers, collective bargaining) Representing: Advancing the general interests of my organisation through speeches, consultations, or contacts with individuals or groups outside the company Overall, how do you rate your performance?

MP4 MP5

MP6

MP7

MP8 MP9