The Effect of Leadership Style and Use of Performance Measures on Managerial

The Effects of Leadership Styles andUse of Performance Measures onManagerial Work-Related Attitudes

FRANK HARTMANN, DAVID NARANJO-GIL andPAOLO PEREGO

Department of Accounting, RSM Erasmus University, Rotterdam, the Netherlands and Department of Business Administration, Pablo de Olavide University, Seville, Spain

(Received: October 2000; accepted July 2009)

ABSTRACT In this paper we investigate the effects of superiors performance evaluationbehaviors on subordinates work-related attitudes. In response to critique on themultidimensional nature of the supervisory style construct in the RAPM literature, weargue that the two dominant dimensions underlying this construct are leadership styleand performance measure use. We develop and test a path model that allows us todisentangle the effects of leadership style (initiating structure and consideration) andperformance measure use (objective and subjective measures) on managerial work-related attitudes (goal clarity and evaluation fairness). We test our hypotheses usingsurvey data from 196 middle-level managers in 11 organizations. Results show that aninitiating structure leadership style affects subordinates work-related attitudes throughthe use of objective performance measures. Consideration leadership behavior insteadonly has a direct impact on work-related attitudes. These findings have importantimplications for management accounting research on superiors use of performancemeasures, and provide an explanation of some of the problematic findings in the literature.

1. Introduction

The managerial accounting literature suggests that the way in which managers

performance is evaluated by their supervisors is an important determinant of

their subsequent work-related attitudes (Hopwood, 1972; Otley, 1978; Merchant,

1985; Hartmann, 2005). A large body of literature has explored this effect by

analyzing the consequences of a construct called supervisory style. Studies

European Accounting Review

Vol. 19, No. 2, 275310, 2010

Correspondence Address: David Naranjo-Gil, Pablo de Olavide University, Carretera Utrera Km. 1,

41013 Sevilla, Spain. E-mail: [email protected]

European Accounting Review

Vol. 19, No. 2, 275310, 2010

0963-8180 Print/1468-4497 Online/10/02027536# 2010 European Accounting AssociationDOI: 10.1080/09638180903384601Published by Routledge Journals, Taylor & Francis Ltd on behalf of the EAA.

on supervisory style typically compare the effects of supervisors who rely strictly

on the achievement of budget-based performance measures, with the effects of

supervisors who make a more lenient use of budgetary measures, or who use

other than budget-based measures (Briers and Hirst, 1990; Kren, 1997). Although

supervisory style has been defined as a single construct in these studies, it in fact

captures two dimensions of the way in which supervisors evaluate performance.

A performance measure dimension relates to the characteristics of the perform-

ance indicators and metrics (e.g. budget-based or other) that supervisors use. A

style dimension addresses the manner (e.g. rigid or lenient) in which supervisors

use those performance measures. As these two dimensions have always been

analyzed in conjunction, however, supervisory style studies have not provided

evidence on the separate effects of performance measure and style dimension.

Moreover, the implicit assumption that the use of certain performance measures

is related to a certain style of evaluation has never been tested (cf. Marginson

and Ogden, 2005). These problems are considered important causes of the

mixed and unsatisfactory evidence in this stream of literature (cf. Hartmann,

2000; Otley and Fakiolas, 2000; Pollanen and Otley, 2000; Noeverman et al.,

2005; Derfuss, 2009).

In this paper we develop and test a model of the relationships between super-

visory style and subordinate managers work-related attitudes to address these

concerns. We distinguish between the measure dimension and the style dimen-

sion of supervisory style to show their separate effects on work-related attitudes

of subordinate managers and to explore their relatedness. Based on early studies

on supervisors use of control systems (e.g. Hofstede, 1967; DeCoster and

Fertakis, 1968; Hopwood, 1973, 1974), we argue that the style in which supervi-

sors evaluate their subordinates may be seen as an expression of their general

leadership style. We draw upon the leadership literature (e.g. Yukl, 2005;

Schriesheim et al., 2006; Van Knippenberg et al., 2007) to examine the effects

of initiation of structure leadership and consideration leadership (cf. Bass,

1990) on work-related attitudes. We investigate the direct relationships

between leadership styles and work-related attitudes, but particularly analyze

whether these relationships are mediated by the use of performance measures.

Regarding the use of performance measures, we explore the use of objective

and subjective measures. We examine the effects of style and performance

measure use focusing on two work-related attitudes (goal clarity and evaluation

fairness) that are both immediate criterion variables of leadership style and

performance measure use as well as relevant predictor variables of subordinate

satisfaction and performance (cf. Landy, 1989; Briers and Hirst, 1990, p. 395;

Lau and Sholihin, 2005; Lau and Moser, 2008).

We believe that this study contributes to the management accounting literature

in the following three ways. First, we provide an explicit conceptualization of

the supervisory style construct that disentangles the relationship between the

evaluative focus of the supervisor (i.e. the measures dimension that captures

the use of specific performance measures) from the superiors way of handling

276 F. Hartmann et al.

the evaluation process (i.e. the style dimension that captures specific leadership

traits). Such a distinction explicitly tests Hopwoods initial argument (1972)

assuming a match between measures and style dimension that remained

largely unquestioned in prior literature (cf. Briers and Hirst, 1990). This analysis

is particularly warranted since the emphasis of later studies on evaluative style

has shifted to a narrow focus about performance measures use that neglected a

superiors style of evaluation. The joint investigation of both dimensions under-

lying the concept of supervisory style addresses a fundamental concern in the

management accounting literature about the construct validity of its central

variables (cf. Bisbe et al., 2007; Derfuss, 2009). Second, we explore the separate

and combined effects of leadership styles and the use of performance measures in

an integrated model combining insights from the management accounting and the

general management literature. Although a few prior studies in the supervisory

style tradition have addressed leadership style, they do not provide a proper

theoretical justification of the proposed relationship between these constructs.

Third, our paper contributes to ongoing management accounting research that

analyzes the effects of performance measures on managerial behavior (e.g.

Wentzel, 2002; Ittner et al., 2003; Moers, 2005; Lau and Tan, 2006; Lau and

Moser, 2008). We extend those studies by analyzing leadership styles as a

potentially important determinant of performance measures use in performance

evaluation. Taken together, our study contributes to the debate in management

accounting that is seeking the managerial antecedents and consequences of

performance-based evaluation (cf. Luft and Shields, 2003).

The remainder of this paper is structured as follows. Section 2 reviews the

relevant research literature, presents the constructs of the research model and

develops the hypotheses. Section 3 describes the empirical survey study.

Section 4 presents the results from the statistical analyses of the hypotheses.

Finally, Section 5 discusses the implications of the empirical results and provides

directions for future research.

2. Literature Review and Development of Hypotheses

Early studies on budgetary control documented that supervisors use of budgets

for performance evaluation could lead to dysfunctional managerial reactions (e.g.

Argyris, 1952; Hofstede, 1967). Hopwood (1972) and others examined whether

such dysfunctional reactions were the consequence of inherent properties of

budget-based performance measures, or rather of the way in which superiors

used these performance measures. Hopwood (1972) initially found that a

budget constrained evaluative style (i.e. a rigid emphasis on meeting short-

term budget targets) led to higher job-related stress, poorer working relationships

and more data manipulation than a profit conscious style (i.e. a more lenient use

of budget-based data) or a non-accounting style (i.e. using other than

budget-based measures, indicators or metrics). Subsequent studies either tried

to confirm the relationship between supervisory style and subordinates

Effects of Leadership Styles and Use of Performance Measures 277

dysfunctional behaviors (e.g. Otley, 1978), or explored whether the relationship

between supervisory style and outcome was contingent on the performance

evaluation context (e.g. Brownell and Hirst, 1986, Ross, 1994). These studies,

which are often collectively addressed as the RAPM literature, produced incon-

clusive evidence as consecutive studies simply failed to show consistent patterns

in the relationships between supervisory style and work-related attitudes (see, e.g.

Briers and Hirst, 1990; Hartmann, 2000 for extensive reviews).

Reviews of this literature more or less unitedly blame the supervisory style

construct itself for the lack of consistent findings across studies (e.g. Noeverman

et al., 2005). They point to the literatures inconsistent use of operational defi-

nitions and neglect of the constructs multidimensional nature (cf. Otley and

Fakiolas, 2000; Pollanen and Otley, 2000; Derfuss, 2009). Indeed, whereas the

original supervisory style typology in Hopwood (1972) combined a measure

dimension (i.e. the extent to which a budget-based metric was used or not) and

a style dimension (i.e. rigid or lenient evaluative manner), later studies used

the construct in different and apparently ad hoc ways (cf. Briers and Hirst,

1990; Otley and Fakiolas, 2000).1 Brownell (1983) and Hirst (1987), for

example, used only two categories of supervisory style, which they label as

high and low budget emphasis. In doing so, they focused on the measure dimen-

sion and disregarded the style dimension. Similar procedures were followed in

related studies (e.g. Hirst, 1983; Brownell, 1985; Govindarajan and Gupta, 1985).

In their review of the use of the supervisory style construct in this literature, Otley

and Fakiolas (2000, p. 508) thus conclude a basic lack of understanding of the

overall meaning of the supervisory style construct, and of its dimensionality.

Based on a meta-analysis of supervisory style studies, Derfuss (2009) recently

confirmed that the variety in operational definitions of the supervisory style

construct explains many of the inconsistent findings across studies.

These problems seem to be especially associated with the constructs style

dimension. Whereas the use of performance measures has been broadly explored

in the management accounting literature and beyond (cf. Kren, 1997; Merchant

et al., 2003; Van der Stede et al., 2006), the style dimension has never been ana-

lyzed as a separate construct, as it also received less emphasis in RAPM studies

over time (cf. Hirst, 1983; Brownell, 1985; Govindarajan and Gupta, 1985). Due

to this limited attention, it has never become clear what the style dimension

exactly entails, whether it should be considered as a separate dimension of super-

visory behavior at all, and whether it can be meaningfully distinguished from lea-

dership style (cf. Marginson and Ogden, 2005, p. 443). Figure 1 depicts graphically

how the construct of supervisory style has been conceptualized in the RAPM

literature (panel A) and compares it with the approach proposed in this study

(panel B).

Indeed, the overlap of meaning between leadership style and supervisory style is

clearly implied in typical definitions of leadership as the process of influencing

others to understand and agree about what needs to be done and how to do it

and the process of facilitating individual and collective efforts to accomplish


shared objectives (cf. Yukl, 2005, p. 8). Moreover, as, for example, Bass (1990)

notes, the performance measurement and evaluation system represents an impor-

tant way in which leaders communicate performance expectations and strengthen

subordinate confidence and, thus, express their leadership (e.g. Seltzer and Bass,

1990; Pillai et al., 1999; Podsakoff et al., 2006). Therefore, the leadership literature

strongly suggests that leadership style also, or perhaps even especially, predicts the

behavior of supervisors when evaluating their subordinates performance.

The supervisory style literature itself acknowledges the relationship between

leadership style and supervisory style, but considers them as separate constructs.

A number of RAPM studies address the impact of the leadership styles initiation

of structure (IS) and consideration (C) on performance evaluation outcomes.

IS-leadership aims to direct subordinates with clear working instructions and

performance targets (Bass, 1981, 1990). C-leadership is concerned with the

promotion of subordinates well-being through supportive and pleasant relation-

ships (cf. Judge et al., 2004). Argyris early study (1952) already demonstrated

that subordinates felt less dysfunctional budget pressure when their superiors

were low on IS-leadership and high on C-leadership. Table A1 in the Appendix

provides an overview of theoretical models and main findings from subsequent

studies. Overall, the results seem to suggest that an IS-style (C-style) is related

Figure 1.


to the rigid (lenient) use of performance measures. Whether, however, this means

that leadership style is a causal antecedent of supervisory style, or rather that

leadership style and supervisory style are simply constructs with partially

overlapping meanings, has not been the subject of any analysis thus far.

In sum, extant literature on the relationship between leadership style and super-

visory style suffers from several limitations for several reasons. First, the unclear

and varying meaning across studies of Hopwoods original instrument (1972) to

measure supervisory style (RAPM) has resulted in a lack of consistency in

conceptualization and empirical support (Hartmann, 2000; Otley and Fakiolas,

2000). Early contingency studies developed the construct to reflect a supervisory

evaluation style that was related to, yet different from, general leadership style

(cf. Briers and Hirst, 1990). No explicit attempt has been made to understand

further whether managerial work-related attitudes are affected by the use of

certain performance measures as such, or rather by the leadership style that is

expressed by their use. Second, past leadership studies do not provide a proper

theoretical justification of the proposed relationship between leadership style

and supervisory style. In fact, prior studies are very much in disagreement

about the nature of the relationships between leadership styles since they are con-

ceptually posited as determinants of supervisory style (Merchant, 1984, 1985;

Marginson and Ogden, 2005), a consequence of supervisory style (DeCoster

and Fertakis, 1968), or moderator of supervisory style effects on manipulative

behavior (Merchant, 1990) and job-related tension (Hopwood, 1974). Third,

the empirical evidence from past leadership studies has limitations inherent to

the samples investigated (four studies collected data from a single organization)

and the empirical tests conducted (most studies showed univariate tests while

more recent statistical techniques would allow to more robustly assess construct

validity and relationships among latent variables using factor analysis and

structural equation modeling).

Our study will attempt to address the confusion in the extant literature. Below

we illustrate and motivate the choice of variables in our model, after which we

derive hypotheses about the relationships between leadership style, the use of

performance measures and work-related attitudes as outcome variables.

Leadership style. We use the Stogdill and Coons (1957) original typology of

leadership as consisting of the dimension initiating structure (IS-leadership)

and consideration (C-leadership). Although the leadership literature has devel-

oped alternative typologies over time, we use this original classification as it is

the only one used in previous supervisory style studies (cf. Otley and Pierce,

1995; Viator, 2001). Moreover, recent evidence in the leadership literature

confirms the validity of the initiating and consideration leadership traits as well

as their fundamental nature (Judge et al., 2004; Dionne et al., 2005). We

choose to address them separately as antecedents of the use of performance

measures. Although both traits may coexist in the same leader, prior research

that examined interacting effects of the two styles generated mixed findings

(cf. Bass, 1990).


Use of performance measures. Concerning the measure dimension of

supervisory style, we distinguish between the use of objective and subjective

performance measures for managerial performance evaluation. This choice is

based on recommendations from the reviews of the supervisory style literature

(e.g. Otley and Fakiolas, 2000; Noeverman et al., 2005) and is in line with the

wider performance evaluation literatures interest in the objectivesubjective

distinction (e.g. Moers, 2005), and prior literature in organizational behavior

(e.g. Bommer et al., 1995). We define objective performance measures, consist-

ent with these studies, as those measures which express performance in financial

and quantitative non-financial measures associated with formalized targets. In

doing so, we capture the essential measure characteristic of the original classifi-

cation (cf. Hopwood, 1972; Harrison, 1993; Hartmann, 2000). In contrast, a

performance appraisal relying on subjective performance measures is based on

the supervisors judgment of performance, using one or more qualitative

expressions of employees performance, such as work attitude, interpersonal

skills, communication and motivation.

Work-related attitudes. We investigate two work-related attitude variables that

have been central to the RAPM literature, as consequences of supervisory style

and antecedents of job satisfaction (Kahn et al., 1964), namely, goal clarity

and evaluation fairness (Briers and Hirst, 1990, p. 395). Goal clarity signifies

the lack of ambiguity managers in decentralized organizations may have about

their role, their objectives and the scope of their responsibilities (cf. Vancil,

1979; Sawyer, 1992). Goal clarity plays a central role in goal theory, which pre-

dicts that managerial perceptions of the specificity (as opposed to the vagueness)

of the working goals they have to achieve has a positive effect on their subsequent

motivation and effort (Hollenbeck and Klein, 1987, p. 214; Locke et al., 1989,

pp. 271272; Locke and Latham, 1990, p. 49). The evidence for goal clarity

as a relevant variable to assess the appropriateness of accounting performance

measures dates back to the study by Hopwood (1972) who found that an emphasis

on meeting the budget adds an important element of structure and clarity to the

job environment.

Evaluation fairness is concerned with the effect of (procedural) justice on

motivation and effort (Huseman et al., 1987; Cohen and Spector, 2001).

Empirical work suggests the importance of individuals perceptions of the fair-

ness of the performance evaluations they receive, for subsequent work-related

attitudes and behaviors (cf. Landy, 1989, pp. 389390). Perceived fairness of

evaluation criteria may also affect the acceptance of those criteria as working

goals, which is a prerequisite for the effectiveness of any form of target

setting (Earley et al., 1989). Recent management accounting studies (e.g. Lind-

quist, 1995; Libby, 1999; Wentzel, 2002; Lau and Tan, 2006; Lau and Moser,

2008; Lau et al., 2008) have paid increased attention to procedural fairness and

have found this form of fairness to be important in explaining the relationships

between accounting control systems and subordinates behaviors. The literature


in organizational behavior confirms the central role of procedural justice in

leadership effectiveness (e.g. Pillai et al., 1999; Tyler and De Cremer, 2005;

Van Knippenberg et al., 2007). In particular, recent findings indicate that

leader reward and punishment behaviors are strongly related to employees

perceptions of justice and conclude that examining the mediating effects of

justice ought to be one of the priorities for future research (Podsakoff et al.,

2006, p. 135).

Initiating Structure Leadership, Objective Performance Measures and Goal

Clarity

According to the pathgoal theory of leadership, an important objective for

leaders is to positively influence the subordinates expectancy to achieve

organizational goals (e.g. Wofford and Liska, 1993; House, 1996; Yukl, 2005;

Schriesheim et al., 2006). This motivation comes from increasing personal

payoffs to subordinates for goal attainment and clarifying the path towards

these goals (House, 1971, p. 324). The initiating structure leadership style is

particularly relevant in this theory, since IS-leadership aims to structure the

roles of their subordinates toward the attainment of organizational goals (Yukl,

2005). IS-leadership insists on meeting deadlines, decides in detail what will

be done and how it should be done, and establishes clear channels of communi-

cation and clear patterns of work organization (Bass, 1990). In contrast, leaders

low in this dimension are hesitant about taking initiatives in the group, make

suggestions only when members ask for it, and let members do the work the

way they think is best (Bass, 1990). Downey et al. (1975) found that leaders

initiating structure was significantly related to the employees expectation that

their performance would result in desired outcomes. A meta-analysis of 120

studies using pathgoal leadership theory by Wofford and Liska (1993) indicated

that initiating structure is positively related to role clarity, lending support to the

hypothesis that structured leaders enhance subordinate direction and expectancies

by clarifying the paths for work-goal attainment. Consistent with this line of

thought, we expect that a leader scoring high on the IS-dimension will also

have a positive effect on subordinates goal clarity (H1).

H1: IS-leadership style has a positive effect on goal clarity.

Pathgoal theory also emphasizes the use of performance measures as an important

source of information to subordinates about what is expected of them in their role

(Collins, 1982). The theory is built on the premise that performance measures

represent salient transaction exchanges that strengthen performance expectations

and subordinate confidence (Bass, 1990). As such, performance measurement

systems may serve individuals needs for knowledge about where the organiz-

ation is heading, in order to feel capable of taking initiatives, to allow them to

see the big picture, and to develop a reference point for understanding their


roles within the organization (Bowen and Lawler, 1992; Lawler, 1992). These

insights can be combined with the supervisory style literature to explore

whether specific performance measure use partially mediates the relationship

between a leadership style and work-related attitudes. In fact, Noeverman and

Koene (2000) argued that leadership that focuses on tasks, telling subordinates

what is expected of them and controls deviation from standard, will attach

high importance to quantitative measures of performance and deviations from

targets. Abernethy et al. (2007) find that supervisors high on IS-leadership

used more quantitative performance measures for compensation and promotion.

The empirical literature that investigates the appropriateness of objective

(accounting) performance measures suggests that its functional effects relate to

increased goal clarity (cf. Chapman, 1997; Hartmann, 2000; Luft and Shields,

2003).

Performance evaluation systems based on objective performance measures

enhance structure and clarity of the job environment, and enhance motivation

as they provide clear goals to subordinates (cf. Locke and Latham, 1990;

Hartmann, 2007). Budgetary control systems in particular act to buffer against

unpredictable market developments (cf. Merchant, 1984, p. 293), therefore

reducing ambiguity by shielding the managers immediate working environment

from its external context (cf. Olson and Rombach, 1996). In particular, objective

(accounting) performance measures may also educate managers about the

economics of the business, and the underlying drivers of costs, revenues and

performance, which helps to clarify and execute strategically relevant individual

actions (Malina and Selto, 2004). Recently, Marginson and Ogden (2005) and

Hartmann (2007) indeed confirm that the use of budgets as an antidote to role

ambiguity is a powerful influence on the managers budgeting behavior.

We therefore expect that the positive relationship between initiating structure

and goal clarity (H1) acts, at least partially, through the use of objective perform-

ance measures. This is formulated in H2.

H2: The positive effect of IS-leadership style on goal clarity is mediated

by the use of objective performance measures.

We choose not to develop a hypothesis about the potential relationship between

subjective measures and goal clarity. On the one hand, it can be argued that in

some situations subjective performance measures better account for subordi-

nates performance dimensions that are not easily expressed in objective goals

(see, e.g. Locke and Latham, 1990; Luckett and Eggleton, 1991). In contrast,

subjective performance measures have been shown to introduce severe biases

in performance ratings (cf. Moers, 2005) which may in fact reduce goal

clarity. Because of these opposite effects, we choose not to derive a directional

hypothesis for the potential intervening effect of subjective measures on the

relationship between IS-leadership and goal clarity. Rather, we will add a

control path to our model to account for this potential mediation.


Consideration Leadership, Subjective Performance Measures and Evaluation

Fairness

The social exchange view of leadership considers leadership style and its effects in

terms of the social relationships created between supervisors and subordinates

(e.g. Song et al., 2009). Good social relationships involve investment in the sub-

ordinates welfare by trust and enhancing fairness (cf. Van Knippenberg et al.,

2007). In line with this argument, C-leaders have been shown to develop a work

atmosphere of mutual trust, respect for subordinates ideas and consideration of

subordinates feelings (Tosi et al., 1994). C-leadership involves empowerment,

allowing subordinates a voice in decision-making processes, supporting them

for thinking on their own, treating them equitably through individualized consider-

ation (see, e.g. Judge et al., 2004). It encourages good superiorsubordinate

relationships and two-way communication (Podsakoff et al., 1995). These are

instrumental to enhance the control the individual has over what happens on the

job which can increase effort and performance (cf. Ashkanasy and Gallois,

1994). Van Knippenberg et al. (2007) name fairness as the crucial factor in

these processes. When followers perceive that they can influence the outcomes

of decisions that are important to them and that they are participants in an equitable

relationship with their leader, their perception of procedural fairness is likely to be

enhanced (cf. Bass, 1990; Pillai et al., 1999). We therefore posit that consideration

positively affects evaluation fairness which we express in H3.

H3: C-leadership style has a positive effect on evaluation fairness.

Regarding C-leadership and evaluation fairness, Noeverman and Koene (2000)

argued and found that considerate leaders that emphasized interpersonal aspect

rely more on qualitative aspects of performance evaluation, such as subordinates

explanations of their performance and possibility to improve it. Managers may

judge that the effort in their work is fairly represented in the outcomes in

terms of subjective performance dimensions, since these outcomes are mostly

determined by factors within their control. A recent study by Lau and Moser

(2008) provides evidence that performance appraisals based on subjective criteria

are positively linked to evaluation fairness. Subjective performance evaluation

allows subordinates to be in a better position to seek explanations about their

appraisals and to submit alternative interpretations. Following this line of reason-

ing, a consideration leadership style increases the likelihood for potential unfair

appraisals to be properly discussed, explained and rectified. In response to the

perception of a social exchange based on open communication and subjective

performance measures, subordinates are likely to reciprocate with corresponding

high levels of procedural justice (cf. Song et al., 2009). Therefore, we expect that

the positive relationship between consideration and evaluation fairness (H3) acts

through the use of subjective performance measures. Overall, we propose the

following hypothesis.


H4: The positive effect of C-leadership style on evaluation fairness is

mediated by the use of subjective performance measures.

We choose not to develop a hypothesis about the potential relationship between

objective performance measures and evaluation fairness. The reason is that

existing evidence on the effects of objective performance measures on evalu-

ation fairness reveals opposite effects. On the one hand managers may value

objectivity positively, which may enhance their agreement with the criteria

used in their evaluation. In an experimental setting, Lindquist (1995)

demonstrates the relevance of fairness to the acceptability of budgetary goals.

In contrast, the supervisory style literatures central claim has always been

that objective (i.e. accounting) performance measures reduce evaluation fair-

ness, since superiors put an emphasis on attaining potentially uncontrollable

targets (cf. Earley, 1985; Locke and Latham, 1990; Ross, 1994). Since we

cannot judge the relative strengths of these opposite effects and studies have

shown mixed results about the relationship between objectivity and fairness

(cf. Hartmann and Slapnicar, 2009), we do not develop a directional

prediction. In our empirical analysis we will again add a control path to

account for potential mediation.

Our research model, depicting the four hypotheses, is outlined in Figure 2.

Figure 2. Research model and expected significant paths.


3. Method

Sample

To test the hypotheses, we gathered data through a questionnaire survey that we

conducted in the Netherlands. A sampling method was followed that had been

successful in previous accounting survey-based research, based on the selection

of participating organizations first and managers within those organizations sub-

sequently (cf. Young, 1996). This method provides an acceptable approach to

random sampling in situations where full random sampling is not economically

feasible, and would result in large non-response bias (e.g. Pedhazur and

Pedhazur, 1991, p. 319; Brownell, 1995). The method ensured variation in the

key independent variables by selecting organizations from various types of

industries, reducing the risk of drawing inferences from potential idiosyncrasies

of single organizations (Pedhazur and Pedhazur, 1991, p. 320). Initially 12

organizations were approached and asked to take part in the study. Eleven

organizations eventually agreed to further participate in the research study.

Table A2 in the Appendix contains descriptive statistics on the sample. To main-

tain anonymity and avoid selection bias, in each organization an official was

asked to select respondents (cf. Brownell, 1995, p. 33). Selectors were asked

to select a diverse and large sample of responsibility center managers, across

functional areas and positions in the organizational hierarchy, including line

and staff managers, and of a single (Dutch) nationality.2 In total, a sample of

250 managers was selected. The sample size per organization ranged from 9 to

56 managers, reflecting the organizations size and responsibility center structure.

The response rate (196 usable questionnaires, 78.4%) compares favorably to

earlier and similar studies (Van der Stede et al., 2005). A test for potential

non-response bias was conducted, comparing mean scores on variables for

early and late respondents. The results of this analysis showed no evidence of

systematic non-response above chance. Table 1 contains descriptive statistics

of the respondents.

The average respondents age was 46.2 years. Respondents had, on average,

worked with their present employers for 17.9 years, and had been for 5.8 years

in their present positions. The average number of persons in the respondents

area of responsibility, which includes both the respondents department and

sub-departments, was 60.6 employees. On average, the respondents span of

control, as measured by the number of employees under direct supervision,

amounted to 8.8 persons.

Variable Measurement

The questionnaire was pre-tested with five faculty colleagues, four external

reviewers with senior management positions and eleven contact persons in the

participating organizations, after which it was field-tested with four potential

respondents in two firms. Minor alterations were made in each step. Several


procedures from Dillman (2000) were taken to optimize the response rate, such as

the promise of strict anonymity, the use of high-quality printing with hand-

written signatures, the use of pre-stamped envelopes and separate cards to

request the studys results, and the inclusion of a pen as token. Wording of the

items in the questionnaire is provided in Table A3 in the Appendix.

Leadership behavior was measured with a 16-item instrument based on the

leadership behavior description questionnaire (Stogdill, 1963). The validity of

the instrument has been demonstrated by a recent meta-analysis (Judge et al.,

2004). The scale consists of five-point, fully anchored scales that measure respon-

dents agreement with eight statements concerning consideration behavior, and

eight items concerning initiating structure behavior. Respective sample items

are My supervisor treats his employees as equal and My superior determines

in detail what should be done and how it should be done. None of the 16

items implicitly or explicitly referred to the use of performance measures for

the periodic evaluations. Instead, they expressed the leadership style in which

supervisors manage the activities of their subordinates.

The use of objective performance measures (UOPM) was measured with nine

items, drawing on the scale by Hirst (1981, 1983) and following the definition of

Harrison (1992). Respondents were asked to indicate the type of performance

measures their subordinate relied upon for respectively general performance

evaluation purposes, monetary rewards and non-monetary rewards. Three items

referred to the use of financial performance measures, three items related to

the use of quantitative performance measures and three items addressed the

Table 1. Descriptive statistics

Theoretical Actual

Variables Min Max Min Max Mean Std. dev.

Initiating structure leadership style 1.00 5.00 1.52 4.86 3.35 0.69Consideration leadership style 1.00 5.00 1.59 5.00 3.85 0.64Use of objective performance measures 1.00 5.00 1.00 4.88 3.00 0.81Use of subjective performance measures 1.00 5.00 1.00 5.00 3.89 0.74Goal clarity 1.00 5.00 1.87 5.00 3.90 0.56Evaluation fairness 1.00 5.00 2.02 5.00 3.80 0.61Job satisfaction 1.00 5.00 1.90 5.00 3.90 0.68

Control variables:Task uncertainty 0.00 5.00 1.63 4.89 3.45 0.69Environmental uncertainty 0.00 5.00 0.00 5.00 2.68 1.10Size (no. of employees) 1.00 700.00 60.57 97.65Span of control (no. of employees) 1.00 72.00 8.81 8.99Age (years) 31.00 61.00 46.20 6.85Tenure function (years) 1.00 42.00 5.80 5.62Tenure organization (years) 1.00 41.00 17.91 10.42Public organizations (dummy variable) 0.00 1.00 0.00 1.00 0.44 0.49


use of performance targets for managerial performance evaluation. Sample items

are When evaluating my performance, my superior relies on financial infor-

mation (quantitative information, preset targets) and My monetary rewards

depend to a large extent on performance expressed through financial figures

(quantitative figures, preset targets). UOPM was subsequently derived as a

reflective construct, combining the scores about reliance on quantitative (finan-

cial and non-financial) measures and associated targets. We operationalized the

use of subjective performance measures (USPM) with three items relating to

the use of subjective judgment by the superior in evaluating managerial perform-

ance, that were formulated in line with the items on the other dimensions. Sample

items are When evaluating my performance, my superior relies on subjective

judgments and My monetary rewards depend to a large extent on performance

as subjectively perceived by my superior.

Goal clarity was measured using a scale that combined three items from

Steers taskgoal attributes questionnaire (1976) that measures goal specificity

(cf. Kenis, 1979) and five items from the Rizzo et al. (1970) and House (1971)

instrument for role ambiguity. A sample item is I know exactly what is expected

of me in this job. The combined set of questions instrument was expected to have

greater construct validity than either of its two constituting instruments, since it

combines a more objective goal characteristic (specificity) and a more subjec-

tive goal characteristic (ambiguity). Evaluation fairness was measured with nine

items derived from the scales by Hopwood (1972), Otley (1978) and Dunk

(1990), and from definitions of fairness in the psychology and accounting litera-

tures (e.g. Landy et al., 1978; Landy and Farr, 1980; Govindarajan, 1984;

Emmanuel et al., 1990). For each of the nine statements, subjects were asked

to indicate their level of agreement on five-point fully anchored scales. A

sample item is I am very satisfied with the way I am evaluated.

We included a number of control variables ( job satisfaction, public organiz-

ation, seniority, size and uncertainty). In order to check whether goal clarity

and evaluation fairness are proximal antecedents of subordinate satisfaction,

we measured job satisfaction using an instrument developed by Kahn et al.

(1964) which has been applied in a budgetary context by Hopwood (1973) and

Swieringa and Moncur (1975). The five items included in the instrument relate

to different concepts underlying job satisfaction, such as satisfaction with the

job, satisfaction with the employing organization and the propensity to leave.

The public organization variable was a dummy variable that reflected whether

a sampled organization belongs to the not-for-profit sector, to account for poss-

ible differences between profit and non-profit sectors. The seniority variables

measured the respondents age, and tenure in the job and in the organization,

allowing the test for tenure effects. Prior studies have demonstrated that demo-

graphic characteristics of dyadic members as well as the length of dyadic

relationships tend to influence leadermember exchange qualities (e.g. Dienesch

and Liden, 1986; Vecchio and Bullis, 2001). Age is commonly controlled in

studies involving job attitude dependent variables. There is a tendency for


older employees to have more favorable attitudes (Hanlon, 1986; White and

Spector, 1987). The size variable measured managers span of control (in

terms of the number of subordinates under direct and indirect supervision) and

the number of employees in a managers organization. Span of control is included

as control variable because prior studies about leadership (e.g. Cogliser and

Schriesheim, 2000; Schriesheim et al., 2006) found that when work unit increases

in size, low-quality leadermember exchange increases; that is, relationships

between managers and staff become less positive, which in turn affects staff

performance. Size affects the formality of controls and the use of performance

measures in incentive schemes. For this reason, it is widely included as control

variable in management accounting studies (cf. Chenhall, 2003; Merchant

et al., 2003). Finally, we controlled for environmental uncertainty and task

uncertainty (cf. Chapman, 1997) as they may have contingent direct effects on

leadership (cf. Bass, 1981, pp. 593596) or may interact with variables in the

model.3

4. Data Analysis and Results

We test the research model using Partial Least Squares (PLS), a multivariate

analysis technique for testing structural models (Chin, 1998). PLS is a general

method for the estimation of path models involving latent constructs indirectly

measured by multiple indicators (Chin and Newsted, 1999). This tool is primarily

intended for causal-predictive analysis in which the problems explored are complex

and theoretical knowledge is scarce. Because this technique uses a component-

based approach to estimation, it places minimal demands on sample size and

residual distributions, something not generally achievable with covariance-based

structural equation modeling techniques such as LISREL or AMOS. Finally, PLS

is robust for small to moderate sample sizes (e.g. Chenhall, 2005; Hall, 2008). In

our research model, all variables are constructs specified with reflective indicators.

A PLS model is analyzed using SmartPLS (version 2-M3) and interpreted in two

stages: (1) the assessment of the reliability and validity of the measurement

model, and (2) the assessment of the structural models. This sequence ensures

that the constructs measures are valid and reliable before attempting to draw

conclusions regarding relationships among constructs (Barclay et al., 1995).

Measurement Model

The measurement model in PLS is assessed in terms of individual item reliability,

construct reliability and discriminant validity. Individual item reliability is

considered adequate when an item has a factor loading that is greater than 0.707

on its respective construct (Carmines and Zeller, 1979). Those indicators with

very low values were deleted following an item trimming process (Barclay et al.,

1995; Chin, 1998).4 Construct reliability is assessed using the internal composite

reliability (ICR) (cf. Fornell and Larcker, 1981). As shown in Table 2, all ICRs


Table 2. Reliability coefficients and correlation matrix

Variables ICR Alpha 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14.

1. Initiatingstructure

0.873 0.828 0.732

2. Consideration 0.842 0.764 20.072 0.7193. UOPM 0.911 0.888 0.347 0.101 0.7314. USPM 0.809 0.671 0.172 20.001 20.051 0.7675. Goal clarity 0.880 0.841 0.162 0.234 0.366 20.012 0.7186. Evaluation

fairness0.907 0.881 0.056 0.592 0.169 0.053 0.289 0.745

7. Jobsatisfaction

0.835 0.736 0.129 0.390 0.280 0.061 0.436 0.390 0.750

8. Taskuncertainty

0.890 0.863 20.155 20.015 20.167 0.085 20.296 0.108 20.105 0.711

9. Env.uncertainty

0.808 0.691 0.116 0.067 0.364 0.036 0.140 0.005 20.078 0.119 0.721

10. Size 0.129 0.024 0.126 20.089 0.165 0.190 0.145 0.095 0.215

11. Span ofcontrol

0.124 20.081 0.058 20.082 0.087 20.024 0.135 20.065 0.177 0.051

12. Age 0.061 0.083 0.034 20.060 0.134 0.089 0.120 0.020 0.051 0.209 20.11613. Tenure

function0.084 0.013 0.129 20.058 0.096 0.019 0.106 20.098 0.123 0.018 0.073 0.316

14. Tenureorganization

0.023 20.028 0.027 20.013 0.118 0.011 0.131 20.142 20.008 0.036 20.042 0.623 0.232

15. Public sectororganization

20.199 20.044 20.277 20.217 20.158 0.051 20.339 0.113 20.346 0.056 20.176 20.015 20.197 0.012

The first two columns report the internal composite reliability (ICR) and Cronbachs alpha. Bold-faced elements on the diagonal represent the square root of the average varianceextracted (AVE). Off-diagonal elements are Pearson correlations among variables. n 196.Significant at 1% level (two-tailed).Significant at 5% level (two-tailed).Significant at 5% level (two-tailed).

exceeded 0.8, indicating satisfactory reliability of the constructs in the model

(Hulland, 1999). Additional support for reliability is provided by Cronbachs

alphas, with the minimum value at 0.67 for USPM. The average variance extracted

(AVE) by the latent constructs from their indicators exceeded the recommended

criterion of 0.50 for all variables (Fornell and Larcker, 1981). To assess whether

discriminant validity is sufficient, AVE should exceed the variance shared

between the construct and other constructs in the model (i.e. the squared correlation

between two constructs). For adequate discriminant validity, the diagonal elements

should thus be significantly greater than the off-diagonal elements in the corre-

sponding rows and columns (Barclay et al., 1995). As reported in Table 2, this con-

dition is satisfied. An examination of the cross-loading matrix (Table A4 in the

Appendix) shows additionally that no item loads more highly on another construct

than it does on the construct it is intended to measure. We therefore provide

evidence that the instruments used for this study to operationalize leadership

styles and performance measurement systems reliably and validly capture distinct

constructs, thereby enabling an interpretation of the structural model.

Table 2 displays no significant correlation between the two leadership styles,

suggesting independence of these two supervisory traits. Similarly, the two vari-

ables capturing reliance on objective versus subjective performance measures are

not significantly correlated. In line with prior research, it appears that the use of

objective performance measures is negatively associated with task uncertainty

and positively associated with environmental uncertainty (cf. Khandwalla,

1972; Simons, 1987). No significant correlations are found with regard to the

use of subjective performance measures. Goal clarity and evaluation fairness

show high levels of discriminant validity and are highly correlated with job

satisfaction, therefore confirming that these two work-related attitudes are signifi-

cant predictors of subordinate satisfaction.

Structural Model

Since PLS makes no distributional assumptions in its parameter estimation,

traditional parameter-based techniques for significance testing and model evalu-

ation are considered to be inappropriate (Chin, 1998). One consequence of the

comparison between covariance structure analysis modeling approaches (e.g.

LISREL) and PLS is that no proper overall goodness-of-fit measures exist for

models using the latter (Hulland, 1999). The structural model is evaluated exam-

ining the R2 values and the size of the structural path coefficients. Consistent with

Chin (1998), bootstrapping based on 500 runs is used to generate standard errors

and t-statistics. This allows us to assess the statistical significance of the path

coefficients. Table 3 reports the path coefficients, t-values observed with the

level of significance achieved and the proportion of explained variance of

the endogenous variables (R2) for the whole sample (n 196). Figure 3 showsthe significant path coefficients for the model (non-significant paths have been

omitted for presentation reasons).


The results of the structural model show that initiating structure leadership style

does not directly affect goal clarity (b 0.036, p . 0.10). As expected, initiatingstructure behavior is positively associated with the use of objective performance

measures (b 0.285, p , 0.01), which in turn is positively linked to goal clarity(b 0.285, p , 0.01). The results show a main effect between considerate

Table 3. PLS results

Paths from:

Paths to:

UOPM USPMGoal

clarityEvaluation

fairnessJob

satisfaction

Adjusted R2 for endogenous variables

0.264 0.126 0.271 0.434 0.400

Initiating structure 0.285(4.249)

0.181(2.356)

0.036(0.106)

0.065(0.802)

20.001(0.525)

Consideration 0.092(1.519)

20.075(0.083)

0.202(2.507)

0.599(11.908)

0.186(2.106)

UOPM 0.285(3.602)

0.154(1.937)

0.074(0.902)

USPM 0.048(0.630)

0.088(1.443)

0.002(0.138)

Goal clarity 0.250(3.038)

Evaluationfairness

0.201(2.145)

Control variables:Task uncertainty 20.092

(1.077)0.119

(1.420)20.258

(3.976)0.117(1.578)

20.021(0.228)

Environmentaluncertainty

0.278(3.827)

20.003(0.028)

20.064(0.854)

20.105(1.367)

20.102(1.367)

Size 0.053(0.849)

20.099(1.539)

0.136(1.815)

0.161(2.809)

0.090(1.730)

Span of control 20.054(0.830)

20.123(1.814)

0.088(1.030)

0.047(1.022)

0.049(0.868)

Age 20.055(0.751)

20.002(0.127)

0.088(0.863)

20.033(0.407)

0.021(0.264)

Tenure function 0.045(0.766)

20.089(0.860)

20.004(0.094)

0.028(0.554)

0.002(0.348)

Tenureorganization

0.038(0.424)

20.072(0.793)

0.025(0.508)

0.057(0.757)

0.015(0.176)

Publicorganization

20.112(1.541)

20.221(2.478)

20.050(0.702)

0.106(1.550)

20.319(4.511)

Each cell reports the path coefficient (t-value) obtained from PLS after 500 bootstrapping runs. Blankcells indicate that the path was not hypothesized within the model. n 196.Significant at 1% level (two-tailed).Significant at 5% level (two-tailed).Significant at 10% level (two-tailed).


leadership behavior and goal clarity (b 0.202, p , 0.05) and evaluationfairness (b 0.599, p , 0.01). Contrary to our expectations, results also indicatea significant path linking initiation of structure with the use of subjective

performance measures (b 0.181, p , 0.05), while a consideration leadershipstyle does not relate to both types of performance measures (b 0.092, p .0.10 and b 20.075, p . 0.10, respectively). Interestingly, we found asignificant path between objective performance measures and evaluation fairness

(b 0.154, p , 0.10), while the use of subjective performance measures is notassociated with the work-related attitudes investigated in the model. Consistent

with expectations, job satisfaction, which we added as a control variable, is

positively and significantly associated with goal clarity (b 0.250, p , 0.01)and evaluation fairness (b 0.201, p , 0.05).

We test the robustness of our findings by modeling the uncertainty variables in

interaction with the variables investigated rather than positing direct effects of

uncertainty variables only. For this purpose, we split the sample into two

subgroups partitioned at the mean score of respectively task and environmental

uncertainty and run the posited research model in PLS. This approach parallels

traditional moderated regression analysis by testing a model separately for

each subgroup (cf. Duxbury and Higgins, 1991) to verify whether the significance

of the paths changes in the presence of different situational variables. The

subgroup analyses confirm the results obtained with uncertainty introduced in

Figure 3. Partial Least Squares model: significant path coefficients.


the PLS model as control variables as direct effects only (data are not presented

here but are available from the authors). The results do not change also when a

three-groups test is performed that distinguishes low, medium and high level

of task and environmental uncertainty.5

5. Discussion and Conclusions

In this paper we provide an explicit conceptualization of the supervisory style

construct to address a central concern about this literature and to extend the

narrow focus on the measure dimension of supervisory style in recent RAPM

literature (cf. Otley and Fakiolas, 2000). Our objective was to disentangle the

measure and the style dimensions underlying the supervisory style construct

because the implicit assumption that the use of certain performance measures

is related to general leadership traits has never been tested. Moreover, as the

style and measure dimensions have always been tested simultaneously, the

question remained what dimension of supervisory style caused what outcome.

Our results indicate that a combination of the style and measure dimensions

underlying supervisory style reflect two separate motivational mechanisms

between a leader and his subordinate (cf. Judge et al., 2004; Song et al.,

2009). The first mechanism involving initiating structure of a leader confirms

the central logic of pathgoal leadership theory. IS-leaders rely more on objec-

tive performance measures to increase personal payoffs to subordinates for work

goal attainment, by making the path to these payoffs clearer and by enhancing the

structure of the job environment (House, 1996; Yukl, 2005). The full mediation

occurring between initiation of structure and evaluation fairness (control path)

suggests that objective performance measurement systems enhance perceptions

of organizational justice. Thus, it seems that the positive effect of objectivity

on fairness dominates a potential negative effect that has been a central claim

in the supervisory style literature (Hartmann, 2000). By clearly communicating

expectations and setting objective standards in performance evaluation

procedures, IS-leaders are more effective in enhancing fairness among their

subordinates (cf. Van Knippenberg et al., 2007).

The second mechanism through which leader behavior affects work-related

attitudes focuses instead on socio-emotional aspects in leadersubordinate

dyads. Supervisors high on consideration leadership style significantly affect

evaluation fairness directly, regardless of whether subjective or objective

performance measures are used in performance evaluation. A considerate

leader creates social exchange relationships (i.e. focused on trust and affective

commitment) with direct consequences on evaluation fairness (predicted main

effect), as well goal clarity (control path) (cf. Tyler and De Cremer, 2005;

Song et al., 2009).

Overall, our findings indicate that consideration style is more strongly related

to work-related attitudes, whereas initiating structure is more strongly correlated

with leader performance criteria. Based on our findings, we question the recent


claim of Marginson and Ogden (2005) that subordinates react to budget-based

performance measures irrespective of a supervisors leadership style. Indeed, lea-

dership style and performance measure use are related. Moreover, our analysis

suggests that the use of specific performance measures may be less effective

because they are less compatible with specific leadership traits.

Further, our study extends the limited evidence available in accounting

research on the determinants and effects of subjective performance measures

(e.g. Ittner et al., 2003; Gibbs et al., 2004; Moers, 2005). Despite initiating

leaders appear to rely on subjective performance measures in performance

appraisals (control path), no significant paths are found that link the use of

subjective performance measures to work-related attitudes. This may be

explained by Moers (2005) finding that subjective performance measures result

in more lenient and compressed overall performance ratings, with potential

detrimental effects on goal setting and fairness. Another explanation is that super-

visors may adjust objective performance measures either to compensate for

deficiencies in the performance measures (economic explanation) or because of

the social influences that result from the social context in subjective adjustments

occur (behavioral explanation). The interaction between objective and subjective

performance appraisal requires further investigation.

In sum, our path model addresses the inconclusive findings from earlier studies

on leadership style and supervisory style. In particular, the specification and vali-

dation of the constructs tested in our PLS model show that leadership behaviors

and the use of performance measures are related, yet distinct constructs. This

analysis thus helps to clarify the confusion around the concept of supervisory

style and therefore addresses a fundamental concern in the management account-

ing literature about the construct validity of the variables investigated (Bisbe

et al., 2007; Derfuss, 2009). Moreover, Hopwoods initial argument (1972)

that assumed a matching between measure and style dimension of supervisory

style remained largely unquestioned in previous studies. In this study, we explore

the separate and joint effects of leadership styles and the use of performance

measures in an integrated model that combines insights from the management

accounting (Hopwood, 1974; Merchant, 1985, 1990; Marginson and Ogden,

2005) and the general management literature (e.g. Judge et al., 2004; Rynes

et al., 2005). The study generally contributes to the literature in management

accounting that is seeking the managerial antecedents and consequences of

performance-based evaluation (cf. Luft and Shields, 2003). In addition, our find-

ings have implications in the management literature since we attempt to introduce

insights from leadership, justice and goal-setting theories in the same study (cf.

Judge et al., 2004). Our mediating model adds to the debate on the relationship

between leadership style and RAPM and contributes to the discussion in an

area that is known for its modest use of theory (cf. Hartmann, 2000).

Some limitations of the current study should be noted. First, the study is not

immune to traditional weaknesses associated with the survey method used

regarding internal and external validity. However, we feel that the survey was


the appropriate method given the constructs of interest. Moreover, the care taken

in the design of the empirical study, in obtaining the sample of respondents, in the

design and pretests of the questionnaire, and in the follow-up procedures may

have provided effective controls against many reliability and validity threats

normally associated with survey research (cf. Van der Stede et al., 2005).

Second, the fact that the sample has not been strictly randomly selected requires

care when drawing inferences from this studys results, although the sampling

method was carefully designed to eliminate any obvious bias. In addition,

sampling from multiple respondents in different organizations might have

introduced bias in the analysis, even though our tests of independence in the

observations were satisfactory. Third, the cross-sectional nature of the study

requires care when interpreting the statistical associations as causal relationships.

Given our results and the strengths and weaknesses of the current study, the

following directions for further research seem worth exploring. First, we

acknowledge that the conceptual model tested in this study is not exhaustive.

Additional explanatory and control variables could be investigated concerning

the effects of leadership style on managerial behavior. For instance, informal

aspects of control embedded in an organizational culture could be examined in

combination with formal performance measurement system to assess their

relationships with specific leadership traits and their effectiveness in eliciting

favorable subordinates reactions. The role of business strategy formulation

and implementation in shaping leaders evaluative criteria would also be

another fruitful avenue of research. Second, the effects of performance measure-

ment were examined in terms of subordinates attitudes and responses. An

alternative level of analysis would be the superior, and a related question

would be whether superiors evaluative behaviors could be explained in terms

of context and leadership behavior. Third, in this paper we contrast the use of

objective performance measures with the use of subjective performance

measures, but alternative typologies of performance measures should be explored

(e.g. OConnor et al., 2007). Finally, future research may adopt alternative classi-

fications of leadership behavior that capture elements of leadership theories not

addressed in this study (e.g. Schriesheim et al., 2006).

Acknowledgements

The authors would like to thank the participants at the 2nd AIMA World Confer-

ence on Management Accounting Research, Monterrey, California (May 2005),

the 3rd EIASM Conference on Performance Measurement and Management

Control, Nice (September 2005), the AAA Management Accounting Section

Midyear Meeting, Clearwater Beach, Florida (January 2006), the 31st EAA

Annual Congress, Rotterdam (April 2008), as well as the Editor, Salvador

Carmona, and two anonymous reviewers for their helpful comments and

suggestions on earlier versions of the paper.


Appendix

Table A1. Summary of survey-based studies linking leadership style with supervisory evaluative style

StudyLeadership style

dimension

Relation between leadershipstyle and supervisory

evaluative style (constructused)

Research method andsample Empirical findings and statistical method

DeCoster andFertakis(1968)

InitiationConsideration

Supervisory evaluative style(Budget Pressurea) asdeterminant of leadershipstyle

Questionnaire survey ineight firmsn 31 supervisorscompleted the Budget

Pressure Questionnairen 90 subordinatescompleted the LBDQquestionnaireb

Spearman rank order correlation betweenInitiation and Budget Pressure r 0.445 (p, 0.01)

Spearman correlation between Considerationand Budget Pressure r 0.367 (p , 0.02)

Hopwood(1973,Chap. 8;1974)


Leadership style asdeterminant of supervisoryevaluative style (BudgetConstrained, ProfitConscious, Non-accountingStylec)

Questionnaire survey andcase study in one firm

n 126 cost centermanagers completed theLBDQ and the BC, PC andNA style questionnaire forn 26 supervisorsc

Pairwise MannWhitney U-test for Initiation:BC vs. NA p , 0.0; PC vs. NA p , 0.05Pairwise MannWhitney U-test forConsideration:

BC vs. NA p , 0.05; PC vs. NA p , 0.05

(Continued)

Effects

of

Lea

dersh

ipS

tylesa

nd

Use

of

Perfo

rma

nce

Mea

sures

29

7

Table A1. Summary of survey-based studies linking leadership style with supervisory evaluative style

StudyLeadership style

dimension

Relation between leadershipstyle and supervisory

evaluative style (constructused)

Research method andsample Empirical findings and statistical method

Merchant(1984)


Leadership style asdeterminant of supervisoryevaluative style (BudgetEmphasis)

Questionnaire survey innineteen firms

N 170 profit centermanagers

No significant relationship betweenConsideration and Budget Emphasis

Merchant(1985)


Leadership style asdeterminant of supervisoryevaluative style (AccountingControls: Use of Net IncomeTargets and Budget ExpenseTargets on DiscretionaryProgram Decision-making)

Questionnaire survey inone firmN 54 profit centermanagers

Spearman rank order correlations are all notsignificant

Merchant(1990)

Consideration Leadership style asmoderator of the relationshipbetween supervisoryevaluative style (AccountingControls: Use of Net IncomeTargets and Budget ExpenseTargets on DiscretionaryProgram Decision-making)d

and manipulative behavior

Questionnaire survey inone firm

N 54 profit centermanagersd

Not significant interaction. High considerationleaders do not lessen the tendency for budgetpressure to induce manipulative behavior

29

8F

.H

artm

an

net

al.

Marginsonand Ogden(2005)

High taskLowconsideration LowtaskHighconsiderationcontinuum

Leadership style asdeterminant of supervisoryevaluative style (BudgetCommitment)

Questionnaire survey inone firm

N 221 junior executiveswith budgetresponsibilities across fivebusiness units

Pearson correlation between Leadership Styleand Budget Commitment r 0.25 (p , 0.01)Regression analysis with Budget Commitmentas dependent variable with three samples:Leadership Style significant only when RoleAmbiguity is minimal/absent

Kyj andParker (2008)

Consideration Leadership style andsupervisory evaluative style(Evaluative Use of Budgets)e

as independent antecedentsof budget participation

Questionnaire survey in 13firmsN 71 middle or upperlevel managers

Pearson correlation between Considerationand Evaluative Use of Budgets r 0.198 (p 0.100)

aBudget Pressure Questionnaire (BPQ).bTwo supervisors were rated by five subordinates, two by four subordinates, 18 by three subordinates and nine by two subordinates (DeCoster and Fertakis, 1968,p. 244). One composite subordinate score per supervisor was obtained by taking the average score.cBC Budget Constrained style, PC Profit Conscious style, NA Non-accounting style. One composite cost center head score per supervisor was obtained bytaking the average score.dSame variable and sample as Merchant (1985).eFrom Abernethy and Stoelwinder (1991).

Effects

of

Lea

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nd

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9

Table A2. Sample descriptives

Org. Sector Industry Main activity SampleUsable

responsesInterview

hours

A Private Chemicals Production 10 7 (70%) 7.5B Private Consumer electronics Production 34 29 (85%) 6.5C Private Consumer electronics Retail 27 19 (70%) 5.5D Private Automotive Production 15 11 (73%) 3.5E Private Electronic office

equipmentProduction 25 21 (88%) 9.0

F Private Food and drink Production 9 6 (67%) 6.0G Private Food and drink Production 24 17 (68%) 5.0H Public City development Project

development25 19 (76%) 4.5

I Public City administration Governmentalservices

15 12 (80%) 3.0

J Public Nationaladministration

Legal services 56 48 (86%) 3.5

K Public National government Defense 10 7 (70%) 3.5

Total 250 196 (78.4%) 57.5

Table A3. Survey items. The instruments that were included in the questionnaire arepresented below. The items are presented in full, whereas the introductory questions arepresented in abbreviated form. Items that are reverse coded contain the symbol (R).Items that were deleted to increase reliability and validity of the variables are labeledwith an asterisk

Variables (acronym)

1. Initiating structure leadership style (INI)How frequently does your direct superior engage in the behavior described by thefollowing items?a

Your direct superior . . .INI1 . . . takes care that everyone works at her/his best.INI2 . . . pushes for the completion of work on time.INI3 . . . asks that the employees follow standard rules.INI4 . . . keeps the work moving at a fast pace.INI5 . . . decides in detail what and how has to happen. INI6 . . . requires her/his employees to act for the welfare of the whole department. INI7 . . . needles her/his employees for greater effort.INI8 . . . criticizes poor work.

2. Consideration leadership style (CON)How frequently does your direct superior engage in the behavior described by thefollowing items?a

Your direct superior . . .CON1 . . . makes you feel at ease when talking to her/him.CON2 . . . is friendly and approachable.CON3 . . . keeps her/his employees in good standing with higher authority.CON4 . . . expresses her/his appreciation in case her/his people have worked well.

(Continued)


Table A3. Continued.

Variables (acronym)

CON5 . . . refuses to explain her/his actions. (R) CON6 . . . criticizes the people in her/his group in presence of others. (R) CON7 . . . changes the assigned work to her/his employees without consulting them. (R)CON8 . . . treats all group members as her/his equals.

3. Use of objective performance measures (UOPM)To what extent does your superior attach importance for your general evaluation to . . .b

UOPM1 . . . your performance expressed in quantitative numbers (like: indicators,production numbers, budgetary numbers)?

UOPM2 . . . your performance expressed in financial numbers (like: costs, cost prices,expenditures, profits, financial budgets)?

UOPM3 . . . your performance expressed in relation to earlier set goals or targets (like:production targets, budget or other targets)?

To what extent does your superior attach importance for your financial rewards to . . .b




To what extent does your superior attach importance for your non-financial rewards to . . .b




4. Use of subjective performance measures (USPM)To what extent does your superior attach importance for your general evaluation to . . .b

USPM1 . . . her/his personal and subjective appraisal about your performance (like: howhe/she sees you at work, her/his opinion about your commitment, motivationand effort at work)?

To what extent does your superior attach importance for your financial rewards to . . .b


To what extent does your superior attach importance for your non-financial rewards to . . .b


5. Goal clarity (GC)To what extent do you agree with the following statements?c

GC1 Clear, planned goals and objectives exist in my job.GC2 My work objectives are very clear and specific.GC3 I feel certain about how much authority I have.GC4 I know exactly what is expected of me in this job.GC5 I know how to divide my time over the different tasks in my job. GC6 I understand fully which of my work objectives are more important than others; I

have a clear sense of priorities on these goals.GC7 I think my work objectives are ambiguous and unclear. (R)

(Continued)


Table A3. Continued.

Variables (acronym)

GC8 I know what my responsibilities are.

6. Evaluation fairness (EF)To what extent do you agree with the following statements?c

EF1 The evaluation I receive is based on factors over which I have full control. EF2 It often happens that my superior holds me accountable for certain (negative)

results that I really cannot help. (R)EF3 The evaluation I receive is based on factors that I find relevant for my functioning.EF4 When evaluating my functioning, my superior often emphasizes aspects of my

work which I think are irrelevant. (R)EF5 The evaluation I receive is based on a complete picture of my true performance.EF6 Certain achievements and actions which I think are important in my functioning are

overlooked by my superior when she/he evaluates me. (R)EF7 In general, I think that my functioning and performance is evaluated in an honest

way.EF8 In general, I think that the criteria my superior uses to evaluate me are fair.EF9 I am very satisfied with the way in which I am evaluated.

7. Job satisfaction (JS)To what extent do you agree with the following statements?c

JS1 I would rather have some other job (either inside or outside this organization). (R)JS2 I have made a great deal of progress in this organizationJS3 My job gives me chance to do the things I am best of. JS4 I would certainly advise a friend to come and work for this organization.JS5 If I had the chance to do the same kind of work for the same pay, but in another

company, I would certainly stay here.

8. Task uncertainty (TU)To what extent do you agree with the following statements?c

TU1 In general I would say that my work is fairly routine. (R)TU2 People in this unit do about the same job in the same way most of the time. (R)TU3 Basically, unit members perform repetitive activities in doing their jobs. (R)TU4 My duties are repetitious. (R)TU5 There is a clearly known way to do the major types of work I normally

encounter. (R)TU6 There is a clearly defined body of knowledge of subject matter which can guide me

in doing my work. (R)TU7 There is an understandable sequence of steps that can be followed in doing my

work. (R)TU8 To do my work, I can rely on established procedures and practices. (R)

9. Environmental uncertainty (EU)Can you indicate to what extent the following factors influence the functioning and theperformance of your unit?d

EU1 Behavior and/or buying patterns of customers.EU2 Behavior and/or strategies of competitors.EU3 Technological developments in your profession.EU4 Behavior and/or strategies of your suppliersEU5 Legal and/or political developments.

aScale from 1 (never) to 5 (always).bScale from 1 (not important) to 5 (extremely important).cScale from 1 (strongly disagree) to 5 (strongly agree).dScale from 0 ( factor is not influencing my function) to 5 ( factor has a strong influence).


Table A4. Cross loadings

Variable Items 1. 2. 3. 4. 5. 6. 7. 8. 9.

1. INI INI1 0.704 0.098 0.197 0.056 0.055 0.179 0.112 20.083 0.026INI2 0.857 20.079 0.289 0.095 0.141 0.118 0.134 20.022 0.084INI3 0.682 20.069 0.314 0.183 0.195 20.035 0.083 20.317 0.086INI4 0.680 20.193 0.173 0.146 0.029 20.102 0.003 0.000 0.156INI7 0.764 0.045 0.249 0.143 0.116 0.071 0.147 20.127 0.084INI8 0.689 20.154 0.245 0.118 0.105 20.009 0.049 20.032 0.093

2.CON CON1 20.056 0.783 0.099 0.057 0.168 0.466 0.287 20.088 20.013CON2 20.163 0.778 20.034 0.049 0.163 0.457 0.194 0.016 0.055CON3 0.038 0.719 0.124 20.091 0.240 0.406 0.359 20.036 0.084CON7 20.025 0.593 0.056 20.013 0.134 0.415 0.230 0.032 0.036CON8 20.070 0.708 0.107 0.001 0.122 0.375 0.238 0.044 0.082

3. UOPM UOPM1 0.273 0.054 0.765 20.232 0.329 0.113 0.220 20.204 0.291UOPM2 0.182 0.073 0.668 20.265 0.349 0.065 0.217 20.205 0.333UOPM3 0.311 0.159 0.597 20.018 0.277 0.288 0.177 20.047 0.163UOPM4 0.275 0.027 0.797 0.098 0.185 0.093 0.205 20.097 0.312UOPM5 0.259 0.013 0.786 0.109 0.232 0.077 0.218 20.076 0.308UOPM6 0.280 0.096 0.607 0.249 0.193 0.190 0.218 0.018 0.213UOPM7 0.199 0.065 0.810 20.146 0.225 0.027 0.158 20.194 0.303UOPM8 0.254 0.066 0.803 20.111 0.273 0.025 0.197 20.177 0.291UOPM9 0.224 0.104 0.703 0.007 0.304 0.206 0.208 20.107 0.164

4. USPM USPM1 0.151 0.001 20.207 0.684 20.090 0.025 20.018 0.123 20.063USPM2 0.155 0.039 0.017 0.880 0.009 0.068 0.104 0.060 0.078USPM3 0.084 20.080 0.017 0.723 0.034 0.008 0.006 0.026 0.023

5. GC GC1 0.205 0.027 0.376 20.105 0.715 0.087 0.221 20.335 0.180GC2 0.102 0.027 0.299 20.078 0.721 0.100 0.189 20.367 0.086GC3 0.155 0.202 0.182 0.040 0.650 0.213 0.359 20.079 20.087GC4 0.125 0.230 0.283 0.054 0.837 0.248 0.443 20.200 0.143GC6 0.110 0.109 0.284 0.009 0.654 0.223 0.303 20.157 0.105GC7 0.069 0.278 0.201 20.054 0.755 0.272 0.301 20.195 0.154GC8 0.053 0.282 0.214 0.048 0.674 0.295 0.339 20.167 0.102

6. EF EF2 20.137 0.505 20.113 0.029 0.167 0.578 0.134 0.095 20.124EF3 0.074 0.356 0.187 0.098 0.193 0.751 0.249 0.056 0.059EF4 20.076 0.367 0.054 20.044 0.110 0.599 0.130 0.209 20.055EF5 0.136 0.378 0.254 20.003 0.316 0.752 0.329 20.014 0.055EF6 20.042 0.452 20.027 0.044 0.170 0.684 0.292 0.126 0.014EF7 0.141 0.476 0.182 0.009 0.198 0.846 0.328 0.094 0.009EF8 0.048 0.534 0.224 0.014 0.295 0.876 0.401 0.044 0.002EF9 0.110 0.449 0.162 0.151 0.235 0.816 0.370 0.083 0.036

7. JS JS1 0.035 0.228 0.122 20.154 0.255 0.268 0.564 0.042 0.011JS2 0.150 0.314 0.307 0.088 0.357 0.346 0.814 20.101 0.188JS4 0.132 0.334 0.208 0.105 0.317 0.308 0.784 20.096 0.085JS5 0.059 0.234 0.189 0.076 0.371 0.259 0.811 20.121 0.057

8. TU TU1 20.003 0.033 0.021 0.049 20.014 0.152 0.049 0.558 0.004TU2 20.060 0.076 20.046 0.087 20.221 0.160 20.025 0.705 0.075TU3 20.115 0.113 20.032 0.063 20.130 0.171 0.044 0.716 0.020TU4 20.068 0.048 20.039 0.088 20.120 0.219 20.055 0.730 20.134TU5 20.149 20.068 20.167 0.099 20.247 0.036 20.113 0.784 20.051TU6 20.175 20.077 20.207 0.063 20.263 0.029 20.148 0.801 20.014TU7 20.049 0.026 20.160 0.052 20.260 0.042 20.059 0.636 20.173TU8 20.167 20.118 20.125 20.022 20.215 20.024 20.123 0.724 20.119

9. EU EU1 0.109 0.018 0.288 20.095 0.027 20.053 0.051 20.112 0.760EU2 0.094 0.023 0.327 0.085 0.163 20.033 0.173 20.024 0.833EU3 0.041 0.103 0.174 0.022 0.079 0.105 0.043 20.004 0.541EU4 0.082 0.082 0.232 0.067 0.109 0.042 0.029 20.095 0.718


Notes

1The original instrument by Hopwood (1972) consists of eight items reflecting eight performance

criteria that superiors can use in performance evaluation. The central feature of his instrument

was to construct a contrast between a rigid evaluation based on meeting budgetary targets

(budget constrained style), and a more flexible evaluation based on longer term factors associ-

ated with efficient operation (profit conscious style). In contrast to Hopwoods derivation of

three classes of supervisory style, others have used the scale to derive a dichotomous (e.g.

high/low) measure, based either on ranks (Brownell, 1982) or on the absolute scores (Harrison,

1992, 1993). This resulted in a proliferation of instruments and labels, such as reliance on

accounting performance measures or RAPM (i.e. the extent to which superiors rely on, and

emphasize those performance criteria which are quantified in accounting and financial terms,

and which are preset targets; Harrison, 1993, p. 319), budget emphasis (e.g. Brownell, 1982;

Brownell and Dunk, 1991) or supervisory evaluation style (e.g. Harrison, 1992). Otley and

Fakiolas (2000) have classified four groups of studies that developed an alternative instrument

compared to the original developed by Hopwood (1972). They conclude that the measures

used in each group are different in their scope and intention, and that they are in no sense

interchangeable (Otley and Fakiolas, 2000, p. 506).2These managers would be in charge of a distinct area of responsibility, would have at least one func-

tional subordinate (cf. Hirst, 1983) and a separate budget, and would have experienced at least one

performance evaluation cycle. Although the selection by an official may have introduced some

selectors bias, we estimate that the chances for systematic bias across selectors are negligible.3Environmental uncertainty denotes the unpredictability in the actions of the customers, suppliers,

competitors and regulatory groups that comprise the external environment (Govindarajan, 1984,

p. 127). It was measured with five attributes about the respondents organizational environment.

These five attributes were derived from the scales used previously by Govindarajan (1984) and Mer-

chant (1990), and relate to the behavior of (1) customers, (2) competitors and (3) suppliers, as well

as to (4) the existence of technological developments in the field of work and (5) the occurrence of

legal and political developments. Task uncertainty denotes the lack of repetitiveness and the lack of

programmability of tasks. It was measured with an instrument developed by Withey et al. (1983),

which combines items from several existing instruments originally designed to measure the varia-

bility and analyzability of tasks faced by a subject (e.g. Perrow, 1967; Thompson, 1967).4After each deletion of an indicator, the model was re-estimated. In this manner, we eventually

removed two items from the initiating structure leadership style scale, three items from the

consideration leadership scale and one item respectively from goal clarity, evaluation fairness,

job satisfaction and environmental uncertainty scale.5We additionally performed the PLS analysis by removing the dummy measuring private/non-profit organizations and including instead a dummy for every single organization in our

sample. This analysis would reveal whether an organization may apply a performance evaluation

procedure that correlates all the observations from the same organizations, thereby violating the

assumption of independent observations. The significant paths of the PLS model with 10 dummy

variables are qualitatively the same as the one presented in the results above. Furthermore, we

computed with SPSS the intraclass correlation coefficient (ICC) and the within-group agreement

index (rwg) for the seven variables included in the conceptual model. The ICC represents the

amount of variance in the respondents scores that can be explained by membership to an organ-

ization. Bliese (2000, 2002) notes that the ICC is also defined as a measure of non-indepen-

dence. The rwg agreement index represents the interchangeability of respondents (i.e. it

attempts to determine whether observations from respondents in one organization are basically

identical to observations from respondents in another organization; cf. James et al., 1984).

Results (not presented here) show that ICC and agreement index values are on average

comprised of between 26 and 46% for the measured latent variables. This evidence points at

satisfactory within-organization variance to perform a PLS model at the individual level of

analysis that treats each respondents observation as independent.


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