the relationship between multiple measures based performance evaluation and managerial performance

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AINUN NA’IM

Gadjah Mada University, Indonesia CHONG M. LAU

The University of Western Australia MAHFUD SHOLIHIN Gadjah Mada University, Indonesia

ABSTRACT

The objective of this study is to investigate whether multiple measures-based performance evaluation affects managers’ performance; and if so, whether the effects are indirect through procedural fairness and trust . This study hypothesizes that multiple measures-based performance evaluation has indirect effects on managers’ performance through procedural fairness and trust. In addition, it also hypothesizes that procedural fairness has indirect effects on managers’ performance through trust.

In order to test these hypotheses, this study employs a path analytical model to analyze the data collected from 70 managers of various Indonesian manufacturing companies. The results indicate that the hypotheses are supported. The effects of multiple measures-based performance evaluation on managerial performance are partially mediated by procedural fairness and trust. This means that in addition to indirect effect via procedural fairness and trust, the use of multiple measures for performance evaluation in itself has a direct effect on managerial performance. With respect to the indirect effects of procedural fairness on managers’ performance, this study finds that trust fully mediates the effect of procedural fairness on managers’ performance. Hence it can be concluded that procedural fairness has no direct effects on managerial performance.

Key words: Managerial performance; Multiple measures; Performance evaluation; Procedural fairness; Trust

I. Introduction

Supervisory evaluative style (how superiors evaluate their subordinates) is an important topic in management accounting, which has earned special attention in the literature (Hartmann, 2000). Prior studies on this topic suggest that the basis of managerial performance evaluation used by superiors to evaluate their subordinates’ performance can affect the subordinates’ attitudes and behavior (Otley and Pollanen, 2000). Evidence from early research on supervisory evaluative styles (e.g., Hopwood, 1972 and Otley, 1978), however, suggests that the effects of performance measures on the subordinates’ attitudes and behavior may be indirect through some intervening variables. Their results suggest that the effects of performance measures used in performance evaluation on the subordinates’ attitudes and behavior is likely mediated by the subordinates’ perception of the fairness of the performance measures used and the extent of interpersonal trust, which the use of such performance measures promotes. However, these issues are not investigated nor resolved in prior management accounting studies.

Another important area in management accounting that has long been attracting the attention of management accounting researchers is organizational performance measurement. Otley (1999, p. 363) suggested that “…the measurement of the performance of business (and other) organisations has long been of central interest to both managers and management accounting researchers”. One of the recent developments in performance measurement, which stimulates scholars to study is the use of multiple performance measures which incorporate both financial and non-financial measures (e.g. Kaplan and Norton, 1992, 1996b; Ittner and Larcker, 1998a). However, most studies in this topic view from an organizational perspective (e.g. Hoque and James, 2000; Hoque et al., 2001) and there is a lack of empirical evidence on the effects of multiple measures usage on managers’ attitudes and behavior. Therefore, this study attempts to address this gap in the literature, by empirically investigating the behavioral consequences of the use of multiple performance measures for performance evaluation. It will respond to Otley’s (1999, p. 381) challenge that “…performance measurement practices need to be

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evaluated …from a social, behavioral and managerial perspective…” In addition, Atkinson et al. (1997) have also suggested that research in management accounting should address the issue of how performance measurement systems can produce desired behavior and outcomes. To respond to such concerns, this study is motivated to investigate empirically the effects of multiple measures usage on managers’ performance.

In studying the relationships between the multiple measures-based performance evaluation and managerial performance, this study is also motivated to investigate two other variables which are believed to act as intervening variables. These are procedural justice (procedural fairness) and interpersonal trust. These two important variables have generally been neglected in prior management accounting studies.

Lau and Lim (2002b) argue that procedural fairness is an important variable to be studied in management accounting research because of its effects on the organizational members’ attitudes and behavior. Milani (1975) and Kenis (1979) both suggested that subordinates’ perception of justice may be an important predictor of subordinates’ behavior and attitudes. Lindquist (1995, p.141) similarly contended that “fair procedures…lead to enhancements of satisfaction and performance. In addition, Libby (1999) found that a fair budgeting process could motivate subordinates’ performance. There are however, very few studies in management accounting on procedural fairness (Lau and Lim, 2002b). This study may therefore provide important additional evidence on the role of procedural fairness in management accounting literature.

The inclusion of interpersonal trust variable in this study is grounded in Handerson’s (1980) suggestion that to perform a successful performance evaluation, it is necessary to establish an environment where trust among members of the organisation can develop. Trust is an important feature in performance evaluation because increased trust among organizational members is likely to lead to improved communication (Merlinger, 1956; Read, 1962). Furthermore, in a trusting environment, people are likely to feel free to relate to one another. This may lead to openness among organizational members (Reina and Reina, 1999). Simmons (1981, p.243) suggested that “trust is the glue of effective, humane, and efficient organisations.” In the management accounting context, some researchers (e.g. Hopwood, 1972; Otley, 1978; Ross, 1994; Lau and Buckland , 2001) have investigated the role of trust in performance evaluation, which contrasted financial-based and non-financial-based performance evaluation. They found that trust was a contributing factor in influencing the relationships between the performance evaluative styles and managerial attitudes and behavior. This current study is intended to provide additional evidence as to whether, and in what role, trust also acts as an important factor in performance evaluation, which is based on multiple measures ( a mixed of financial and non-financial measures).

This study proposes that the relationship between multiple measures-based performance evaluation and managers’ performance is indirect through procedural fairness and interpersonal trust as modelled in Figure 1.

Insert Figure 1 about here

II. Theoretical background and hypotheses development

A. Linkage between multiple measures-based performance evaluation and subordinates’ performance

Extant literature suggests that there is a relationship between performance evaluation style that is based on accounting or financial data (budget emphasis) and subordinates’ attitudes and performance (Kren and Liao, 1988; Briers and Hirst, 1990; Lindsay and Ehrenberg, 1993; Otley and Fakiolas, 2000). Hence, multiple measures-based performance evaluation may also be associated with subordinates’ behavior (e.g. performance) because the multiple measurement system is capable of providing continuous signals and motivating breakthrough improvements in critical activities in such critical areas as product, process, customer and market development (Kaplan and Norton, 1993; Hoque et. al., 2001).

The multiple measurement system can provide continuous signals because it incorporates both financial and non-financial measures. Financial measures provide information on past performance and,

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“indicate whether the company’s strategy, implementation, and execution are contributing to bottom-line improvement” (Kaplan and Norton, 1992, p. 77). On the other hand, non-financial measures (e.g. customer, internal business process and innovation and learning perspectives) provide the information on the driver of future success (Kaplan and Norton, 1992, 1996a). In addition, a multiple measurement system also reflects the complexities of the work environment, which enable managers to recognize the various dimensions of their work (Atkinson et al., 2001).

Kaplan and Norton (1996b) argued that multiple measures might function as the cornerstone for future success because, “…combining the financial, customer, internal process and innovation, and organizational learning perspectives…helps managers understand …many interrelationships. This understanding can helps managers …and ultimately lead to improved decision making and problem solving” (Kaplan and Norton, 1992, p. 79). Kaplan and Norton (1993, 1996a) provide evidence that companies which use the multiple measurement system can operate in a more efficient way. In addition, Hoque and James (2000) empirically found that the use of multiple measures performance evaluation was associated with organizational effectiveness. It is likely that increased organizational effectiveness was caused by improved managerial performance. The improved managerial performance was likely due to managers’ improved decision making and problem solving arising from the use of multiple measures performance. Hence, it is proposed in this study that the use of multiple measures is positively associated with managerial performance.

However, as proposed in Figure l, the relationships between multiple measures usage and managers’ performance may be indirect via procedural fairness and interpersonal trust. The theoretical supports for these expectations are provided in the following sections.

B. Linkage between multiple measures-based performance evaluation and procedural fairness

Folger and Konovsky (1989) define procedural justice as the perceived fairness of the means used to determine the amount of reward or compensation the employees receive. In the context of performance evaluation, procedural fairness is likely to be the concern of both the subordinates and the superiors. Subordinates usually consider performance evaluation to be very important, because it is often linked to the reward system that will determine their remunerations and promotions (Lau and Lim, 2002a). Due to the importance of performance evaluation, subordinates normally expect that the procedures used for evaluating their performance should be fair. High procedural fairness is also an important concern of the superiors and the organizations as a whole. There is much evidence, which indicates that the implementation of procedures perceived by subordinates as unfair is detrimental to the organizations’ interest (e.g. Friedland et al., 1973; Thibaut et al., 1974; Lissak, 1983; Kanfer et al., 1987; Greenberg 1987). Based on their review of procedural justice research, Lind and Tayler (1988, p. 179) concluded that, “organizations that ignore procedural justice concerns run the risk of engendering negative organizational attitudes …and… lower performance.” Since the perception of unjust procedures can negatively affect organizations, superiors are likely to maintain high procedural fairness in conducting performance evaluations. It is likely that the adoption of multiple measures, instead of solely financial measures in subordinate performance evaluation, may be viewed as fair by subordinates for the following reasons.

Performance evaluation that takes into accounts both financial and non-financial indicators relies on more than one aspect or dimension of subordinates’ performance. Multiple measures-based performance evaluation views subordinates’ performance in a broad scope. Kaplan and Norton (1996a) argue that multiple measures-based evaluation considers both lagging and leading indicators, and both short and long-terms objectives. It also includes both external measures and internal measures of critical business processes, innovation, and learning and growth. In addition, it provides a balance in terms of the outcome measures - the results from past efforts - and the measures that drive future performance. Finally, this form of evaluation balances objective and easily quantified outcome measures, with subjective and somewhat judgmental performance drivers of the outcome measures. Subordinates are likely to regard such balances in performance evaluation as fair. For example, it is possible that in a certain period, such as in the research stage of developing a product, subordinates may produce unsatisfying financial results. Such innovative acts, however, may lead to a better organizational performance in the long term. Therefore, if a subordinate is evaluated based only on financial performance measures, the evaluation may view the subordinate as a poor performer. Such an unbalanced evaluation may lead the subordinate to perceive the evaluation

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process as unfair. On the other hand, if the performance evaluation also considers the performance in terms of research and innovation, the subordinate is likely to perceive that the evaluation process is fair.

Based on the above argument, it is possible to conclude that subordinates whose performance is evaluated based on both financial and non-financial measures are likely to perceive the evaluation procedures in their organization as fair. Consequently, in this study, it is proposed thatmultiple measures-based performance evaluation is positively associated with procedural fairness.

C. Linkage between procedural fairness and subordinates’ performance

Extant literature in legal, political and organizational contexts suggest that procedural fairness affects performance (e.g. Earley and Lind, 1987; Earley, 1984; Cornelius, 1985; Alexander and Ruderman, 1987; Folger and Konovsky, 1989; McFarlin and Sweeney, 1992). Based on an extensive review of the literature on the relationships between procedural justice and performance-behavior in various settings, Lind and Tayler (1998) conclude that procedural justice does affect performance.

In a management accounting context, Libby (1999) also found that performance was affected by participation (voice) and explanation. Both voice and explanation are parts of procedural fairness. In the same vein, Wentzel (2002) and Little et al. (2002) found that procedural fairness affected managerial performance.

Hence, overall, the literature suggests an association between procedural fairness and managers’ performance. Additionally, expectancy theory also suggests that when subordinates perceive that the procedures used to evaluate their performance are fair, they will have the motivation to perform better (Vroom, 1964; Porter and Lawler, 1968). With fair performance evaluation procedures, the results of performance evaluation are likely to reflect subordinates’ performance accurately. Therefore, subordinates will be motivated to perform better. This is likely to lead to improved performance. In contrast, when subordinates perceive that the performance evaluation procedures are unfair, they will not be motivated to perform well because with unfair evaluation procedures, it is possible that good performance may be evaluated as poor performance (Vroom, 1964; Porter and Lawler, 1968). Consequently, subordinates are likely to perform poorly when unfair performance evaluation procedures are employed.

In conclusion, the discussion above suggests that multiple measures-based performance evaluation may be associated with the subordinates’ performance (section a). However, the discussion also indicates that multiple measures-based performance evaluation may also be positively related to procedural fairness (section b). Procedural fairness, in turn, may be related to subordinates’ performance (section c). There is, therefore, theoretical support for the existence of indirect effects on the relationship between the use of multiple measures-based performance evaluation and subordinates’ performance via procedural fairness. Accordingly, the following hypothesis is tested:

H1: There is an indirect relationship between multiple measures-based performance evaluation and subordinates’ performance through procedural fairness.

D. Linkage between multiple measures-based performance evaluation and interpersonal trust

Zand (1997) argues that a company’s reward system can encourage trust as long as the reward system is collaborative, integrative and “win-win”. Win-win reward systems means, “one person’s gain is a gain for other person as well, and one person’s loss is also loss for the other.” (Zand, 1997, p. 118). In line with Zand’s (1997) argument, Whitener et al. (1998) contend that performance evaluation and reward systems can facilitate managerial trustworthy behavior, which, in turn, can affect the trust of subordinates to their superiors. Therefore, it is necessary for organizations to design their performance evaluation systems in such a way which facilitates the enhancement of the subordinates’ trust in their superiors. Performance evaluation which is based on multiple measures is likely to be one of such means because such evaluation is likely to promote the subordinates’ trust in their superiors for the following reasons.

It is possible at the time the performance evaluation was conducted, a particular short-term

quantitative performance measure of subordinates’ performance may be unsatisfactory. However, it is also possible that if the subordinates’ performance is viewed from a long-term perspective, which considers other indicators, either financial or non-financial, the subordinates’ performance may be beneficial to the organization’s success (Kaplan, 1983, Johnson and Kaplan, 1991). Since multiple measures usage is likely to consider various factors and facets of performance that are important to organizational success,

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subordinates may perceive superiors who employ multiple measures in performance evaluation as having

ability in conducting performance evaluation, which, in turn, may lead subordinates to trust their superiors more.

It is also possible that superiors who evaluate subordinates solely on short-term quantitative indicators may be regarded by subordinates as lacking in ability in evaluating their performance properly. The subordinates may think that the superiors do not understand performance measurement because of the lack of recognition given to other aspects of performance. In contrast, superiors who consider both short-term and long-term perspectives, and both financial and non-financial measures (multiple measures), are likely to be viewed by the subordinates as having ability in conducting performance evaluations. This may lead to higher trust toward the superiors. Subordinates may perceive such superiors to have trustworthy behavior (Mayer et al., 1995).

Superiors who evaluate subordinates using multiple measures may also be perceived by subordinates as superiors who demonstrate concerns because the use of multiple measures may “…reflect the complexities of the work environment and (consider) the variety of contributions that employees make” (Atkinson et al., 2001, p. 407) (parentheses added). It is possible that a subordinate may achieve below target for a certain performance indicator but easily obtain above target for other indicators (Lipe and Salterio, 2002). This may cause subordinates to feel that their careers are protected. In turn, this may lead subordinates to view their superiors as acting benevolently in evaluating the subordinates’ performance. The higher the perception of benevolence, the higher the perception of trustworthy behavior is likely to be (Whitener et al., 1998). If subordinates perceive that the superior is trustworthy, they will trust their superior more. This will lead to higher subordinates’ propensity to trust (Mayer et al., 1995). With this in mind, it is reasonable to propose that there is a positive relationship between the use of multiple measures-based performance evaluation and trust in superiors.

E. Linkage between interpersonal trust and subordinates’ performance

Zand (1997) defines trusting behavior as a willingness to increase vulnerability to another person whose behavior cannot be controlled, in situations in which a potential benefit is much less than a potential loss if the other person abuses the vulnerability. Further, he suggests that two people who trust each other will greatly increase their problem solving effectiveness. This will increase their commitment to each other and they will experience greater satisfaction with their work and their relationships. People who trust each other can synchronize, help each other and work together constructively. Trusting behavior can improve decision quality and its implementation. It is likely that the higher the decision quality, the higher is the performance. Lippit (1982) argues that the existence of trust between organizational members can increase both problem solving and performance. Similarly, Reina and Reina (1999, p. 8) note that “directly or indirectly trust is related to individual, group, and organisational performance” (emphasis added).

In summary, based on the discussion above, multiple measures-based performance evaluation is expected to be positively related to trust in superiors (section d). Trust in superiors, in turn, is expected to be positively related to subordinates’ performance (section e). These relationships suggest therefore, that the effect of multiple measures-based performance evaluation on subordinates’ performance may be indirect through trust in superiors. The following hypothesis is therefore tested:

H2: There is an indirect relationship between multiple measures-based performance evaluation and subordinates’ performance through the subordinates’ trust in their superiors.

F. Linkage between procedural fairness and trust in superiors

Previous studies in various settings have shown that procedural fairness has a positive influence on trust. In a political setting, Lind and Tyler (1988) reported that U.S. citizens’ trust in their national government was highly correlated with the perceived fairness of the government’s decision-making procedures. Further analysis found that, trust judgments were much more strongly affected by procedural justice than by distributive justice. They also found that citizens’ trust in legal institutions was strongly related to procedural fairness. In the organizational arena, Konovsky and Pugh (1994) found a very high correlation between subordinates’ judgments of their superior’s procedural fairness and their trust in their supervisor. Other studies in the organizational area (e.g. Alexander and Ruderman, 1987; Folger and Konovsky, 1989; McFarlin and Sweeney, 1992 Korsgaard et al., 1995) and in a budgeting context (Magner and Welker,

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1994; Magner et al., 1995) have also demonstrated that perceptions of procedural fairness are positively related to trust in the leaders and decision makers. Hence, this study proposes that procedural fairness is positively associated with trust.

As previously discussed, procedural fairness is expected to be associated with managers’ performance (section c). Since procedural fairness is also expected to be positively related to trust (section f), and trust, in turn, may be related to managers’ performance (section e), it is therefore possible to conclude that the effect of procedural fairness on subordinates’ performance may be mediated by the intervening effect of trust. Accordingly, the following hypothesis is tested:

H3: There is an indirect relationship between procedural fairness and subordinates’ performance through trust.

III. Research method A. Data and sample

Data for this study were collected using a questionnaire survey sent to 229 managers working in organizations listed as manufacturing companies in the Jakarta Stock Exchange. The names of the companies were published in the Indonesian Capital Market Directory (2000). The managers were selected from various manufacturing companies. This approach avoids external validity problems and enhances the possibility of generalizing results (Chong and Bateman, 2000). Only those manufacturing companies employing more than 100 employees each were studied, as firms with fewer than 100 employees may not have formalized control systems, and are unlikely to have clearly defined areas of responsibilities (Brownell and Dunk, 1991). In addition, the selection of organizations with more than 100 employees is useful for the control of the size of the organizations (Lau and Lim, 2002a).

The manufacturing sector was selected for this study because it is the largest sector (52%) published in the Indonesian Capital Market Directory. It is very common in management accounting research to study a single sector, but involving a number of organizations (e.g. Simon, 1986; Brownell and Dunk, 1991; Lau et al., 1995; Libby and Waterhouse, 1996; Hoque and James, 2000; Lau and Lim, 2002a, b). Listed companies were selected because almost all the largest and most advanced Indonesian companies were listed in the Jakarta Stock Exchange. This permits the selected sample to include the largest and most advanced companies in Indonesia. Although the sample was derived from manufacturing organizations, it was not the intention of this study to investigate a particular function (e.g. manufacturing). In order to ascertain if the results are generalized across functional areas, following previous management accounting studies (e.g. Hopwood, 1972; Otley, 1978; Brownell, 1982; Brownell and Dunk, 1991; Otley and Pollenan, 2000; Lau and Lim, 2002b), this study selected samples from across functional areas.

In order to provide some degree of control over the seniority of the respondents across organizations, only functional heads were selected. The functional heads were selected as follows. Telephone calls were made to the secretary of each company to obtain the names of the functional heads. This method ensured that the functional heads would receive the questionnaires and that they would be the only ones who answered the questionnaires. In addition, to avoid bias, only a maximum of 4 managers were selected from each company. On average, each company provided the names of two managers.

Based on the Indonesian Capital Market Directory (2000), there are 146 manufacturing companies. One company has less than 100 employees. Hence, it was excluded from the sample. One company regarded itself as a service rather than a manufacturing organization. Consequently, this company was also excluded from the sample. Thirty two companies informed the researchers that it was their policies not to disclose the name of their managers. As a result, the researcher was able to obtain the names of 229 managers from 112 companies. Table 1 and Table 2 present the industry types of the targeted sample companies and the sample selection process, respectively.

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B. Survey administration

A questionnaire together with a prepaid return addressed envelope and a covering letter explaining the objectives of the research was mailed to each of the 229 intended respondents. As the instruments used to measure the variables examined in this thesis were developed in English, and English is not widely used in Indonesia, it was necessary to translate the instruments into Indonesian. The translation process involved three separate steps as recommended by Hofstede (1980). First, the researchers, who are Indonesian national and highly proficient in the Indonesian language, translated the questionnaire from English into Indonesian. Second, a university professor in Indonesia, who is bilingual and also an Indonesian national, translated the Indonesian version of the questionnaire back into English. Third, a cross-check of the latter English version with the original English version was performed. This third step was to ensure that the translation was accurately done, and was undertaken by one of the authors who speaks English. Only the Indonesian version of the questionnaire was used in the survey.

The questionnaires were mailed out in November 2001. A reminder letter was mailed after three weeks. Managers who did not respond to the questionnaire two weeks after the reminder letters were sent out, were contacted by phone. Out of the 229 questionnaires mailed, 83 responses (36%) were returned. Thirteen responses were excluded from the study because of the failure of the respondents to complete the whole questionnaire. As a result, there were 70 usable responses. Given that the survey was undertaken in Indonesia, such a response rate may be considered very high. Gudono and Mardliyah (2001) noted that response rates in Indonesia generally range from 10% to 16%.

C. Variables and their measurements

C.1. Multiple measures-based performance evaluation

The multiple measures-based performance evaluation was measured using a modified 20-item instrument developed by Hoque et al. (1997) and subsequently used by Hoque and James (2000) and Hoque et al. (2001). The questionnaire was modified because it was originally developed to measure organizational performance. In this study, it was used to measure individual employee performance. The 20 items were derived from Kaplan and Norton’s (1992) four dimensions of the Balanced Scorecard, namely financial, customer, internal-business-process, and organizational learning and growth perspectives. Whilst Hoque and James (2000) and Hoque et al. (2001) used a five-point Likert scale ranging from 1 (not at all) to 5 (a great extent), this study employed a seven-point Likert-type scale, ranging from 1 (never important) to 7 (always important), to provide respondents with the opportunity to identify more clearly where their responses fit on the continuum (Ross, 1994). The instrument asks respondents to indicate how much importance their superior attaches to the twenty items when their superiors evaluate their performance. Details of the instrument are presented in Appendix 1.a.

Following Hoque and James (2000) and Hoque et. al. (2001), a principal components analysis with varimax rotation was conducted to assess whether the 20 items could be grouped according to the four dimensions of the Balanced Scorecard. The result indicates that items 13 and 17, which were expected to load on the customer perspective, did not load into this perspective satisfactorily. Consequently, those two items were not included for further analyses. To test the reliability of the 18 remaining items, a reliability test was undertaken. The result of reliability test produced a cronbach alpha coefficient (Cronbach, 1951) of 0.95 for this instrument.

C.2. Procedural fairness

Procedural fairness was measured using a four-item, five-point Likert-type scale instrument developed by McFarlin and Sweeney (1992), and subsequently used by Lau and Lim (200a, 2002b). It asks respondents to rate the fairness of the procedures used to evaluate their performance, to communicate performance feedback, and to determine their pay increases and promotion ranging from 1(very unfair) to 5 (very fair). An overall measure of procedural fairness was obtained by summing up responses to the four individual items. Details of the instrument are presented in Appendix 1.b.

A reliability check for this measure in this study produced a cronbach alpha of 0.77, which is considered acceptable (Nunnaly, 1967; Chenhall and Morris, 1986). The factor analysis extracted only one factor with an eigenvalue greater than one (eigenvalue= 2.351; total variance explained=58.771%). This supports the unidimensional nature of this instrument.

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C.3. Trust in superiors

Trust was measured using a four-item instrument developed by Read (1962) to measure the level of trust held by subordinates in their superiors. This instrument had been used by Hopwood (1972), Otley (1978), Ross (1994), Magner and Welker (1994) and Magner et al. (1995). It asks the respondents to indicate to what extent they trust or have confidence in their superiors’ motives and intentions with respects to matters relevant to their career and status in the organization, ranging from 1 (to a very little extent) to 5 (to a very great extent). An overall measure of trust was obtained by summing up responses to the four individual items. Details of the instrument are presented in Appendix 1.c.

The cronbach alpha coefficient for this instrument in this study is 0.79, which is close to the 0.81 reported by Ross (1994). The factor analysis extracted only one factor with an eigenvalue greater than one (eigenvalue= 2.477; total variance explained=61.914%). This supports the unidimensional nature of this instrument.

C.4. Managerial performance

There are two instruments to measure managerial performance, namely Mahoney et al.’s (1963, 1965) and Govindarajan and Gupta’s (1985) instruments. While the former is a self-rating measure, the latter considers the expectation of top management. The Mahoney et al. (1963, 1965) instrument is much more established, and has been used extensively by many prior management accounting studies (e.g. Brownell, 1982; Brownell and Hirst, 1986; Govindarajan, 1986; Brownell and McInnes, 1986; Brownell and Dunk, 1991; Kren, 1992; Lau et al., 1995; Lau and Tan, 1998; Chong and Bateman, 2000; Lau and Lim, 2002a). Govindarajan (1986) and Brownell and McInnes (1986) both provided evidence of its reliability and its construct validity. Brownell (1982, pp. 17-18) contended that, “ the nine-dimensional structure of the measure clearly captures the multidimensional nature of performance without introducing the problem of excessive dimensionality.” Givindarajan (1986, p. 505) similarly noted that, “the Mahoney measure offered two advantages. First, independent assessments of reliability and validity of this measure have yielded satisfactory results in other studies. Second, this measure explicitly recognises the multidimensional nature of managerial performance, while at the same time, avoiding the problems inherent in measures with excessive dimensions.” Due to these advantages, Mahoney et al.’s (1963, 1965) instrument was selected in this study. Details of the instrument are presented in Appendix 1.d.

Mahoney et al.’s instrument (1963, 1965) comprises eight dimensions of performance and a single overall performance rating. In order to ascertain that Brownell’s (1982, pp. 17-18) contention that, “ the nine-dimensional structure of the measure clearly captures the multidimensional nature of performance without introducing the problem of excessive dimensionality” holds, a regression analysis was conducted by regressing the overall performance rating onto the other eight items. The result indicates that the majority of the variation in the overall rating was explained by the eight items. An R2_{of 0.64 (p=0.001) was obtained.}

This value was considered favorable when compared with the R2_{of 0.55 in the overall rating as suggested}

by Mahoney et al. (1963, 1965). In addition, a factor analysis also revealed that the eight dimensions loaded satisfactorily on one factor. Following Kren (1992), in this current study, the measure of performance was obtained by summing up responses to the eight individual items of performance.

IV. Result and discussion

The study investigates whether multiple measures-based performance evaluation is associated with subordinates’ performance and if so, whether such relationships are indirect through procedural fairness and interpersonal trust. A path analysis is considered as an appropriate technique to investigate such relationships. Cohen and Cohen (1983, p.126) suggest that to assess the adequacy of regression models, the residuals of the estimated values of the regression should be tested. Therefore, before testing the hypotheses, tests were performed to ensure that the inherent assumptions of the regression models were satisfied. Tests undertaken included testing for the normality of residual, homogeneity of variance of residuals and the appropriateness of the linear models. The results of these tests indicate that the inherent assumptions of the models used were validated.

In addition, it is also important to conduct non-response bias test before analyzing the data as suggested by Oppenheim (1966). The test is undertaken to ascertain whether there are systematic

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differences between responses that came in early, and those which arrived late. In conducting these tests, the responses were divided into two groups based on their dates of arrival. The first half comprises the 50 percent of responses, which came in early, and the second half comprises the last 50 percent of responses received. These tests were performed by running t-tests to compare the mean of responses for each variable between the two groups. The results indicate that there are no significant differences between the early responses and the late responses for all the variables examined in this thesis. Based on these results, it can be concluded there is no non-response bias.

The zero-order correlations between the variables examined in this study are presented in Table 3. These results provide preliminary support for all the hypotheses. Multiple measures usage is positively associated with managerial performance. Additionally, Table 3 shows that both procedural fairness and trust are positively and significantly associated with managerial performance. The results also indicate that procedural fairness and trust are positively and significantly related to each other, suggesting that multicolinearity may exist. Therefore, in addition to the three inherent assumptions of regression models, the presence of multicolinearity was also assessed by performing tolerance and variance inflation factor (VIF) tests for each regression model. The results, presented in Table 4, indicate that multicolinearity among variables was not detected. Therefore, there is no problem with the regression models used in this study.

Insert Table 3 and 4 about here

Hypotheses testing

Hypothesis H1 states that there is an indirect relationship between multiple measures-based performance evaluation and subordinates’ performance through procedural fairness. Hypothesis H2 states that there is an indirect relationship between multiple measures-based performance evaluation and subordinates’ performance through the subordinates’ trust in their superiors. As indicated in Table 3, there is a significant zero order correlation between multiple measures-based evaluation and managerial performance. The indirect effects of multiple measures-based performance evaluation on subordinates’ performance consists of the following paths and are calculated as follows based on the values of the path coefficient in Table 5:

Path (1) MM – PF - MP 0.304 x 0.053 0.016

Path (2) MM – PF – T - MP 0.304 x 0.396 x 0.153 0.018

Path (3) MM – T – MP 0.263 x 0.153 0.040

Total indirect effect 0.074

Path (1) indicates the indirect effect exclusively via procedural fairness, which is 0.016. Paths (2) and (3) indicate the indirect effect through trust, which is 0.058. These results show that the relationship between multiple measures-based performance evaluation and subordinates’ performance comprises two effects. First, there is a direct effect of 0.244 (see Table 5) and second, there is an indirect effect of 0.074, which can be further decomposed into the portion attributable to procedural fairness (0.016) and the portion attributable to trust (0.058). Based on Bartol’s (1983) contention, those combined indirect effects may be considered meaningful because they exceed an absolute amount of 0.05.

Insert Table 5 about here

Table 6 presents a summary of the decomposition of the zero-order correlations into the direct, indirect and spurious effects. In order to assess whether the relationship is fully or partially mediated by procedural fairness and trust, Baron and Kenny’s (1986) approach is used. This approach argues that a full

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mediation exists if a significant relationship (i.e. a significant zero order correlation) between the independent variable and dependent variable becomes insignificant (i.e. an insignificant path coefficient) after controlling for the effects of the intervening variables. On the other hand, the mediation is only partial if the relationship between the independent and dependent variable is still significant after controlling for the effects of intervening variables (Nouri and Parker, 1998; Lau and Buckland, 2001).

Insert Table 6 about here

For this study, the relationship between multiple measures-based performance evaluation and subordinates’ performance is significant (r = 0.318; p<0.01, Table 3). After controlling for the indirect effects via procedural fairness (0.016) and trust (0.058), the path coefficient between multiple measures-based performance evaluation and managers’ performance is still marginally significant (0.244, p<0.056, Table 5). This means that procedural fairness and trust mediate partially the relationship between multiple measures-based performance evaluation and managers’ performance.

In summary, apart from an indirect effect via procedural fairness and trust, multiple measures-based performance evaluation itself has a positive and significant direct effect on managerial performance. Based on these results, hypotheses H1 and H2 are supported.

Hypothesis H3 states there is an indirect relationship between procedural fairness and subordinates’ performance through trust. The indirect effect and the spurious effect consist of the following paths and are computed as follows based on the values of the path coefficients in Table 5:

Path (4) PF – T – MP 0.396 x 0.153 0.061

Path (5) PF – MM – MP 0.304 x 0.244 0.074

Path (6) PF – MM – T – MP 0.304 x 0.263 x 0.153 0.012

Total indirect effect 0.147

Path (4) indicates the indirect effect exclusively via trust is 0.061. Paths (5) and (6) indicate a total spurious effect of 0.086. As the indirect effect via trust is in excess of an absolute amount of 0.05, it is considered meaningful (Bartol, 1983). Thus, Hypothesis H3 is supported.

Recall that there is a significant zero order correlation between procedural fairness and managerial performance (0.200; p<0.05, Table 3). After controlling for the indirect and spurious effects, the effect of procedural fairness on managerial performance is not significant (0.053; p<0.689, see Table 5). This means that trust mediates fully the relationship between procedural fairness and managerial performance.

V. Conclusions and limitations

The objectives of this study are (1) to investigate whether multiple measures-based performance evaluation affects managers’ performance; (2) if so, whether the effects are indirect through procedural fairness and trust. Consequently, this study hypothesizes that multiple measures-based performance evaluation has indirect effects on managers’ performance through procedural fairness and trust. In addition, it also hypothesizes that procedural fairness has indirect effects on managers’ performance through trust.

In order to test these hypotheses, this study employed a path analytical model to analyze the data collected from 70 managers of various Indonesian manufacturing companies. The results indicate that there is a significant association between multiple measures-based performance evaluation and managerial performance. Further analyses indicate that such relationships are indirect and mediated by procedural fairness and trust. The effects of multiple measures-based performance evaluation on managerial performance are partially mediated by procedural fairness and trust. This means that in addition to the indirect effect via procedural fairness and trust, the use of multiple measures for performance evaluation in itself has a direct effect on managerial performance (Baron and Kenny’s, 1986). With respect to the indirect effects of procedural fairness on managers’ performance, this study found that trust fully mediates the effect of procedural fairness on managers’ performance Hence it can be concluded that procedural fairness has no direct effects on managerial performance.

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Based on these results, the overall findings of this study are generally in accordance with expectations. That is, (1) multiple measures-based performance evaluation has indirect effects on managerial performance through procedural fairness and trust; (2) procedural fairness has indirect effects on managerial performance via trust.

As with other empirical studies, there are limitations associated with this study. First, there are limitations associated with the survey questionnaire method. These include low response rates and the possibility of respondents’ bias in filling in the questionnaire due to the lack of control from the researcher. Therefore, future studies could employ other methods (e.g. case study) in exploring the issues studied here. Second, although the sample of this study was selected from across functional areas, the number of responses from a particular area is small. Hence, analyses of the results on functional basis were not undertaken. Future research should investigate if variation across functional areas may influence the results. In addition, since the sample was selected from larger-sized organizations with more than 100 employees each, it is unclear if the results can be generalized to smaller-sized organizations with less than 100 employees. Finally, as this study only selected samples from the manufacturing sector and only among Indonesian managers, generalizing the results to non-manufacturing sectors and to other Asian countries should be made with caution. These limitations provide opportunities for future research to study these issues in other sectors and in other Asian and Western countries.

Notwithstanding the aforementioned limitations, this study, at best of our knowledge, is the first to explore the relationships between multiple measures usage in managerial performance evaluation and managerial performance. These results provide timely evidence, which may have important theoretical and practical implications for the adoption of multiple measures-based evaluation, which is gaining popularity in increasing number of organizations in both Asian and Western countries.

REFERENCES

Alexander, S and Ruderman, M. 1987. ‘The role of procedural and distributive justice in organizational behavior’. Social Justice Research, 1: 177-198.

Atkinson, A.A., Banker, R.D., Kaplan, R.S. and Young, S.M. 2001. Management Accounting. 3rd_edition.

New Jersey: Prentice Hall International, Inc.

Baron, R.M. and Kenny, D.A. 1986. ‘The moderator-mediator variable distinction in social psychological research: conceptual, strategic and statistical considerations’. Journal of Personality and Social Psychology, 51 (6): 1173-1182.

Bartol, K.M. 1983. ‘Turnover among DP personnel: a causal analysis’. Communications of the ACM, 26 (10): 807-811.

Briers, M. and Hirst, M. 1990. ‘The role of budgetary information in performance evaluation’. Accounting, Organizations and Society, 15 (4): 373-398.

Brockner, J. and Siegel, P. (1996). Understanding the interaction between procedural and distributive justice: role of trust. In R.M. Kramer and T.R. Tyler (eds.). Trust in organizations: frontiers of theory and research. London: SAGE Publications.

Brownell, P. 1982. ‘The role of accounting data in performance evaluation, budgetary participation, and organization effectiveness’. Journal of Accounting Research, 20 (1): 12-27.

Cohen, J. and Cohen, P. 1983. Applied multiple regression/correlation analysis for the behavioural sciences.2nd_{edition. New Jersey: Lawrence Erlbaum Associates.}

Cornelius, G.W. 1985. Evaluation fairness and work motivation, Master thesis, Champaign: University of Illinois.

Cronbach, L.J. 1951. ‘Coefficient alpha and the internal structure of tests’. Psychometrika, 16: 297-334. Duncan, O.D. 1966. ‘Path analysis: sociological examples’. American Journal of Sociology, 72: 1-16. Earley, P.C and Lind, E.A. 1987. ‘Procedural justice and participation in task selection: the role of control in

mediating justice judgments’. Journal of Personality and Social Psychology, 52 (6): 1148-1160. Earley, P.C. 1984. Informational mechanisms of participation influencing goal acceptance, satisfaction and

performance. Doctoral dissertation, Champaign: University of Illinois.

Folger, R. and Konovsky, M. A. 1989. ‘Effects of procedural and distributive justice on reactions to pay raise decisions’. Academy of Management Journal, 32 (1): 115-130.

(12)

Folger, R., Rosenfield, D., and Robinson, T. 1983. ‘Relative deprivation and procedural justification’. Journal of Personality and Social psychology, 45: 268 – 273.

Govindarajan, V. 1984. ‘Appropriateness of accounting data in performance evaluation: an empirical examination of environmental uncertainty as an intervening variable’. Accounting, Organizations and Society, 9 (2); 125-135.

Greenberg, J. 1987. ‘Reactions to procedural justice in payment distributions: do the ends justify the means’. Journal of Applied Psychology, 72:55-61.

Gudono and Mardliyah. 2001. ‘The effects of environmental uncertainty and decentralization on management accounting systems characteristics. Journal of Indonesian Accounting Research, 14 (1): 1 - 27.

Hair, J.R., Anderson, R.L., Tatham, R.E., and Black W.C. 1998. Multivariate data analysis with reading. Englewoods, N.J: Prentice-Hall International.

Handerson, R. 1980. Performance appraisal: theory and practice. Virginia: Reston.

Hartmann, G. H. 2000. ‘The appropriateness of RAPM: toward the further development of theory’.

Accounting, Organizations and Society, 25: 451 - 482.

Hartmann, G. H. and Moers, F. 1999. ‘Testing contingency hypothesis in budgetary research: an evaluation of the use of moderated regression analysis’. Accounting, Organizations and Society, 24: 291 – 315.

Hirst, M.K. 1981. ‘Accounting information and the evaluation of subordinate performance: a situational approach’. The Accounting Review, 56: 771-784

Hofstede, G.H. (1980). Culture’s consequences: international differences in work-related values. Beverly Hills, CA: Sage.

Hopwood, A. G. 1972. ‘An empirical study of the role of accounting data in performance evaluation’. Empirical research in accounting: selected studies, Supplement to Journal of Accounting Research, 10: 156-182.

Hoque, Z., Mia, L., Alam, M. 1997. ‘Competition, new manufacturing practice, changing in MAS and managerial choice of the “Balanced Scorecard” approach to performance measures: an empirical investigation’. Paper Presented at the 1997 European Accounting Association Annual Congress in Graz.

Hoque, Z. and James, W. 2000. ‘Linking balanced scorecard measures to size and market factors: impact on organizational performance’. Journal of Management Accounting Research, 12: 1-17.

Houqe, Z., Mia, L., and Alam, M. 2001. ‘Market competition, computer-aided manufacturing and use of multiple performance measures: an empirical study’. British Accounting Review, 33: 23 – 45. Institute for Economic and Financial Research. Indonesian Capital Market Directory 2000

Ittner, C., and Larcker, D. 1998a.’ Innovations in performance measurement: trends and research implications’. Journal of Management Accounting Research, 10: 205 – 238.

Ittner, D. and Larcker, F. 1998b. ‘Are nonfinancial measures leading indicators of financial performance? an analysis of customer satisfaction’. Journal of Accounting Research, 36, supplement: 1-46.

Johnson, H.T. and Kaplan, R.S. 1991. Relevance lost: the rise and fall of management accounting. Boston: Harvard Business School Press.

Kanfer, R., Sawyer, J., Early, P.C., and Lind, E.A. 1997. ‘Participation in task evaluation procedures: the effects of influential opinion expression and knowledge of evaluative criteria on attitudes and performance’. Social Justice Research, 1: 235-249.

Kaplan, R.S. 1983. ‘Measuring manufacturing performance: a new challenge for managerial accounting research’. The Accounting Review, 58 (4): 686-705.

Kaplan, R.S. and Atkinson, A. 1998. Advanced Management Accounting. New Jersey: Prentice-Hall. Kaplan, R. S. and Norton, D. P. 1992. ‘The balanced scorecard: measures that drive performance’. Harvard

Business Review. (January – February): 71-79.

Kaplan, R. S. and Norton, D. P. 1993. ‘Putting the balanced scorecard to work’. Harvard Business Review.

(September-October): 134-147.

Kaplan, R. S. and Norton, D. P. 1996a. The balanced scorecard: translating strategy into action. Boston, MA: Harvard Business School Publishing.

(13)

Kaplan, R. S. and Norton, D. P. 1996b.’ Linking the balanced scorecard to strategy’. California Management Review, 39, 1: 53-79.

Kaplan, R. S. and Norton, D. P. 1996c. ‘Using the balanced scorecard as a strategic management systems’.

Harvard Business Review. (January-February): 75-85.

Kenis, I. 1979. ‘Effects of budgetary goal characteristics on managerial attitudes and performance’. The Accounting Review, 54 (4): 707-721.

Konovsky, M.A. and Pugh, S.D. 1994. ‘Citizenship behavior and social exchange’. Academy of Management Journal, 37: 656 – 669.

Kren, L. 1992. ‘Budgetary participation and managerial performance: the impact of information and environmental volatility’. The Accounting Review, 67 (3): 511-526.

Lau, C. M. and Buckland, C. 2001. ‘Budgeting-role of trust and participation: research note’. Abacus, 37 (3): 369-388.

Lau, C. M. and Lim, E. 2002a. ‘The effects of procedural justice and evaluative styles on the relationship between participation and performance’. Advances in Accounting, 19: 139-160.

Lau, C.M and Lim, E.W. 2002b. ‘The intervening effects of participation on the relationship between procedural justice and managerial performance’. British Accounting Review, 34 (1): 55-78. Lau, C.M., Low, L.C., and Eggleton, I. 1995. ‘The Impact of reliance on accounting performance measures

on job-related tension and managerial performance: additional evidence. Accounting, Organizations and Society, 20 (5): 359-381.

Lau, C.M., Low, L.C., and Eggleton, I.R.C. 1997. ‘The interactive effects of budget emphasis, participation and task difficulty on managerial performance: a cross-cultural study’. Accounting, Auditing and Accountability Journal, 10 (2): 175-197.

Lau, C.M. and Tan, J. 1998. ‘The interactive effects of budget emphasis, participation and task difficulty on managerial performance: a cross-cultural study of the Singaporean and Australian financial service Sector’. Management Accounting Research, 9: 163-183.

Lawler, E.E. 1991. ‘The design of effective reward systems’. In Steers, R.M. and Porter, L. W. (eds).

Motivation and Work Behavior. New York: McGraw-Hill, Inc.

Leventhal, G.S., Karuza, J., and Fry, W.R. 1980. ‘Beyond fairness: a theory of allocation preferences’. In G. Mikula (ed). Justice and social interaction. New York: Springer Verlag.

Libby, T. 1999. ‘The influence of voice and explanation on performance in participative budgeting setting’.

Accounting, Organizations and Society, 24 (2): 125-137.

Lind, E.A. and Tyler, T.R. 1988. The social psychology of procedural justice. New York: Plenum Press. Lindquist, T.M. 1995. ‘Fairness as antecedent to participative budgeting : Examining the effects of

distributive justice, procedural justice and referent cognitions on satisfaction and performance’.

Journal of Management Accounting Research, 7: 122-147.

Lindsay, R. M. and Ehrenberg S. C. 1993. ‘The design of replicated study’. The American Statistician, 47 (3): 217-228.

Lippe, M.G. and Salterio, S.E. 2000. ‘The balanced scorecard: judgmental effects of common and unique performance measures’. The Accounting Review, 75, 3: 283-298.

Lippe, M.G. and Salterio, S.E. 2002. A note on the judgmental effects of the balanced scorecard’s information organization. Accounting, Organization and Society, 27: 531-540.

Lippit, G.L. 1982. Organizational renewal: a holistic approach to organizational renewal. Englewood Cliffs, NJ: Prentice Hall.

Lissak, R.I. 1983. Procedural fairness: how employees evaluate procedures. Doctoral dissertation. Champaign: University of Illinois.

Little, H.T., Magner, N., and Welker, R.B. 2002. ‘The fairness of formal budgetary procedures and their enactment’. Group & Organization Management, 27, 2: 209-225.

Magner, N and Welker, R.B. 1994. ‘Responsibility center managers’ reaction to justice in budgetary resource allocation’. Advances in Management Accounting, 3: 237-253.

Magner, N., Welker, R.B., and Campbell, T.L. 1995. ‘The interactive effect of participation and budget favorability on attitudes toward budgetary decision maker: a research note’. Accounting, Organizations and Society, 20 (7/8): 611-618.

(14)

Mahoney, T.A., Jerdee, T.H., and Carrol, S.J. 1963. Development of managerial performance: A Research Approach. Cincinnati: South Western Publishing.

Mahoney, T.A., Jerdee, T.H., and Carrol, S.J. 1965. ‘The jobs of management’. Industrial Relations, 4: 97-110.

Malmi, T. (2001). Balanced scorecards in Finnish companies: a research note. Management Accounting Research, 12 (2): 207-220.

McFarlin, D.B. and Sweeney, P.D. 1992. ‘Distributive and procedural justice as predictors of satisfaction with personal and organizational outcomes’. Academy of Management Journal, 35 (3): 626-637.

Merlinger, G. 1956. ‘Interpersonal trust as factor in communication’. Journal of Abnormal and Social Psychology, 52: 304-309.

Milani, K.W. 1975. ‘The relationship of participation in budget-setting to industrial supervisor performance and attitudes: a field study’. The Accounting Review, 50 (2): 274-284.

Norereklit, H. 2000. ‘The balance on balanced scorecard-a critical analysisi of some of its assumptions’.

Management Accounting Research, 11: 65 – 88.

Nouri, P. and Parker, J. 1998. ‘The relationship between participation and job performance: the roles of budget adequacy and organizational commitment’. Accounting, Organizations and Society, 23 (5-6): 467-483.

Nunnaly, J.C. 1967. Psychometric Theory. New York: McGraw-Hill.

Oppenheim, A.N. 1966. Questionnaire design and attitude measurement. New York: Basic Book.

Otley, D. T. 1978. ‘Budget use and managerial performance’. Journal of Accounting Research, 16 (1): 12-148.

Otley, D. 1999. ‘Performance management: a framework for management control systems research’.

Management Accounting Research, 10: 363-382.

Otley, D. T. and Fakiolas, A. 2000. ‘Reliance on accounting performance measures: dead end or new beginning?’ Accounting, Organizations and Society, 25: 497-510.

Otley, D and Pollenan, R.M. 2000. ‘Budgetary criteria in performance evaluation: a critical appraisal using new evidence’. Accounting, Organizations and Society, 25: 483 – 496.

Paese, P. 1985. ‘Procedural fairness and work group responses to performance evaluation procedures. Unpublished masters thesis. University of Illinois, Champaign.

Porter, L.W. and Lawler, E.E. 1968. Managerial attitudes and performance. Illinois: Richard D. Irwin. Read, W.H. (1962). ‘Upward communication industrial hierarchies’. Human Relations 15: 3 – 15.

Reina, D.S and Reina, M.J. 1999. Trust and Betrayal in the workplace: building effective relationships in your organization. San Francisco: Berrett-Koehler Publishers, Inc.

Ross, A., (1994). ‘Trust as a moderator of the effect of performance evaluation style on job related tension: a research note’. Accounting, Organizations and Society, 19 (7): 629-635.

Silk, S. 1998. ‘Automating the balance scorecard’. Management Accounting, May, 38-44. Simmons, R.H. 1981. Achieving Humane Organization. California: Daniel Spencer.

Simmon, R. 1986. Accounting control systems and business strategy: an empirical analysis. Accounting, Organizations and Society, 12 (4): 357-374.

Thibaut, J., Friedland, N. and Walker, L. 1974. ‘Compliance with rule: some social determinants’. Journal of Personality and Social Psychology, 30: 782-801.

Thibaut, J. and Walker, J. 1975. Procedural justice: a psychological analysis. New York: Wiley. Thibaut, J. and Walker, L. 1978. ‘A theory of procedure’. California Law Review, 66: 541– 566. Vroom, V.H. 1964. Work and motivation. New York: John Wiley & Sons, Inc.

Wentzel, K. 2002. ‘The influence of fairness perception and goal commitment on managers’ performance in a budget setting’. Behavioral Research in Accounting, 14: 247 – 271.

Whitener, E.M., Brodt, S.E., Kosgaard, M.A., and Werner, J.M. 1998. ‘Managers as initiators of trust: an exchange relationship framework for understanding managerial trustworthy behavior’. Academy of Management Review, 23 (3): 513 – 530.

Vaivio, J. 1999. ‘Exploring a “non-financial” management accounting change’. Management Accounting Research, 10: 409-437.

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Figure 1

The relationships between multiple measures-based performance evaluation and managerial performance, job satisfaction and job-related tension

Multiple

measures-based performance

evaluation

Interpersonal trust

Managerial performance Procedural

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Table 1. Industry types of targeted sample

Industry Type Number of Companies

Food and beverages 21

Tobacco 3

Textile mill products 8

Apparel and other textile products 15

Lumber and wood products 5

Paper and allied products 6

Chemical and allied products 8

Adhesive 4

Plastics and glass products 11

Cement 3

Metal and allied products 11

Fabricated metal products 3

Stone, clay, glass and concrete products 4

Machinery 2

Cable 6

Electrics and electronic equipment 5

Automotive and allied products 16

Photographic equipment 3

Pharmaceuticals 8

Consumer goods 4

Total 146

Table 2.

Sample selection process

Description Number of companies

Targeted company sample 146

Has less than 100 employees 1

Regarded itself as a service organisation 1

Will not disclose the name of their managers 32

Final company sample 112

Table 3.

Correlation matrix among variables

Procedural

fairness

Trust Managerial

performance

MM-based evaluation 0.304** 0.383** 0.318**

Procedural fairness 0.476** 0.200*

Trust 0.272*

** p<0.01 (1-tailed) * p<0.05 (1-tailed)

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Table 4. Multicolinearity detection with managerial performance as dependent variable.

Variable Colinearity statistics

Tolerance VIF

Constant n/a n/a

MM-based evaluation 0.834 1.199

Procedural fairness 0.756 1.322

Trust 0.711 1.404

Table 5. Path analysis results of managerial performance, multiple measures, procedural fairness, and trust.

Dependent variable

Independent variable

Path coefficient

t-value p-value

PF MM 0.304 2.629 0.011

T MM 0.263 2.434 0.018

PF 0.396 3.664 0.000

MP MM 0.244 1.944 0.056

PF 0.053 0.402 0.689

T 0.153 1.126 0.264

PF= Procedural fairness

MM= Multiple measures-based performance evaluation T= Trust

MP= Managerial performance

Table 6. Decomposition of the observed correlations (managerial performance)

Relations Observed

Correlation

Direct effect

Indirect effect

Spurious effect

MM / MP 0.318** 0.244+ _0.074

MM / PF 0.304** 0.304**

PF / T 0.476** 0.396** 0.080

MM / T 0.383** 0.263* 0.120

T / MP 0.272* 0.153 0.119

PF / MP 0.200* 0.053 0.061 0.086

** p<0.01 * p<0.05