designing the balanced scorecard weight on syariah

SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG

DESIGNING THE BALANCED SCORECARD WEIGHT ON SYARIAH BANK BRANCHES THROUGH PERFORMANCE MEASUREMENT (AN EMPIRICAL STUDY ON BANK SYARIAH MANDIRI) UNGGUL PURWOHEDI State University of Jakarta, Indonesia IMAM GHOZALI Diponegoro University, Indonesia ABSTRACT The objective of the study is to design the appropriate weight for each balanced scorecard perspectives (financial, customer, internal-business process, and learning and growth). To achieve that objective, this study is trying to analyze the relationships between Balanced Scorecard perspectives with organizational and managerial performance. Therefore, this study has two hypotheses, first the BSC usage is positively associated with organizational performance. Secondly, the BSC usage is positively associated with managerial performance. In order to test the hypotheses, this study used the Structural Equation Model by AMOS 4.0. This study analyze managers in Bank Syariah Mandiri as the respondents. Fifty one respondents through out Indonesia were used in this study which are consists of branch mangers, operational managers and marketing managers. The questionnaires were sent by email. Using Structural Equation Modeling (SEM), the results of the study indicated that each perspective has different relationship to organizational and managerial performance, either positive or negative. Internal business perspective supported the first hypothesis, meanwhile, financial and internal business perspective supported second hypothesis. This study is also gives a recommendation related with weight design for each BSC perspectives.

Key words : Balanced Scorecard Weight, Organizational Performance, Managerial Performance

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SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG I. INTRODUCTION 1.1. Research Background The development of syariah banking has shown its great contribution to community. Syariah banking is an intermediary and trustee of other people’s money with the difference that it shares profit and loss with its depositors. Syariah banking introduces an element of mutuality between depositors and bank. Both of them have the same right in distributing the return. However, in practice, most syariah banks have an organizational set-up similar to their conventional counterparts. One of the most beneficial function in an organization is related to control system. Syariah banking control systems may be divided into internal and external. The former includes managerial remuneration and constitution of Board of Directors. The markets for corporate control and managerial labor, product market competition, juridical constraints, and exit and voice strategies are examples of external control (Dar & Presley, 2000). One of the control mechanism in organization is performance measurement. It contains the method of re-numeration packages for management. Including, incentives strategy includes salary incentives, share options, executive presentations and discussions, and active employment market for senior executives whose salary may be determined by past performance (Dar & Presley, 2000). The main focus on performance measurement issues is how to seek the best underlying measures in evaluating process. In the early of performance measurement, people tend to rely on financial measures especially accounting performance (Otley & Fakiolas, 2000). This began with Hopwood’s pioneering work on the role of accounting data in performance evaluation. Hopwood’s (1972) work identified three distinct evaluative styles used by senior managers in holding subordinates accountable for their performance. Conversely, a number of researchers argued that financial measures is insufficiently in evaluating performance. Hayes (1977) in Brownell (1982) has indicated that accounting information is less appropriate as a focal element in organizational control with increasing exposure of the organization, or subunits of it, to the environment. Ittner et. al (1997) denoted that the use of non-financial measures in performance evaluation has been on the increase. Such non-financial measures include market share, efficiency/productivity,


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SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG product quality, customer satisfaction and employee satisfaction. They also found that utilities and telecommunication firms in their study prefer to non financial measures than financial measures in the use of evaluating performance and reward system. Furthermore, the need for more non-financial measures in management accounting has been well articulated. In addition, there is evidence from surveys and interviews that executives value non-financial information better than financial measures (Schiff & Hoffman, 1996). In particular, many firms are implementing “Balanced Scorecard” system that supplement traditional accounting measures with non financial measures focused on at least three other perspectives-customers, internal business processes, and learning and growth (Kaplan & Norton 1992, 1996a,1996b,1996c)

.

Another key issue is defining precisely what “balance” is and the mechanisms through which “balance” promotes performance. A common view, perpetuated by early writings on the balanced scorecard concept (e.g. Kaplan & Norton 1992), is that “balance” is achieved by diverse measurement in the domains of financial performance, operational performance, performance for the customer, and learning and innovation. According to this view, multiple measures in each of several domains minimize the risk that information germane to business results will be lost. Critical issues in multidimensional measures is determining the best weight for each measures. Schiff and Hoffman (1996) reveal that non-financial measures may have a greater weight than financial measures for some types of performance judgments while the financial cues were used more heavily by the executives for the department performance judgments, this was not the case for the manager performance judgments. Ittner et.al.(1997) found that firms engaging in a prospector strategy rely more heavily on non financial measures in the CEO’s annual bonus contract than those following a defender strategy. Organizations are characterized as prospectors or firms that exhibit a differentiation strategy. These firms attempt to identify new product/service market opportunities, quickly adapt to changes in the external environment, and follow a “first-to-market” strategy. At the other extreme, organizations are characterized as defenders or firms that exhibit a cost leader strategy. These firms attempt to provide a stable set of products and services to a well defined portion of the total market while emphasizing improvements in current operating efficiencies in order to lower costs. Padang, 23-26 Agustus 2006

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SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG 1.2. Statement of the Problem

The problem of this research is there is still lack of evidence for managers to determine various performance measures which is effected to managerial or organizational performance, and these statement is supported by several findings on previous research. Lipe and Salterio (2000) found that supervisors tend to rely on common measures than unique measures in evaluating their subordinates, thus it is a subjective decision. Therefore, based on current condition, this study is attempting to answer the research question that is how to design the best performance measurement according to organizational and managerial performance. This study will be used by manager to justify the best weighting for each perspectives in Balanced Scorecard.

1.3. Objective of the Study

The main objective of this study is to design the appropriate weight for each Balanced Scorecard perspectives (in financial, customer, internal-business process, and learning and growth), while the specific objective of this study are as follows : 1. To examine the relationships between the Balanced Scorecard perspectives (financial, customer, internal-business process, and learning and growth) and managerial performance. 2. To examine the relationships between the Balanced Scorecard perspectives (financial, customer, internal-business process, and learning and growth) and organizational performance. 3. To examine the relationships of each Balanced Scorecard perspectives to organizational performance.

II. LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT 2.1 Literature Review This section will discuss about the theoretical framework of performance measurement. As indicated before, performance measurement issues is derived from Agency Theory which explains the contractual relationship between principal and


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SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG agent (Belkaoui, 2000). Thus, management, as an agent, tends to maximize their utility by implementing various effort such as management control system. Management Control System contains a variety of control mechanisms, including performance measurement, to align individual’s behaviors with the strategies and goals of the organization (Chenhall & Smith, 2003). Therefore, The Balanced Scorecard as one method of performance measurement clearly related to those background theories

2.1.1. Balanced Scorecard (BSC)

The usage of BSC has been implemented widespread in every organization either profit or non-profit organization such as hospital (Stefano, 2001). A survey conducted in the USA estimates that 60 percent of the fortune 1000 firms have experimented with BSC (Malmi, 2001). Lipe and Salterio (2002) had also conducted an experiment which resulted that logically organized performance measurement in Actually, The Balanced Scorecard (Kaplan & Norton,1996c) is another model which integrates financial and non financial strategic measures. It is distinct from other strategic measurement systems in that it contains outcome measures and the performance drivers of outcomes, linked together in cause-and-effect relationships (Kaplan and Norton,1996a; Kaplan and Norton, 1996c). Kaplan and Norton (1996c) assume the following causal relationship : measures of organizational learning and growthÆmeasures of internal business processesÆmeasures of the customer perspectiveÆfinancial measures. The measures of organizational learning and growth are therefore the drivers of the measures of the internal business processes. The measures of these processes are in turn the drivers of the financial measures. A good balance scorecard should have a mix of outcome measures (lag indicators) and performance drivers (lead indicators). An example of a lag indicator is increased turnover, while order execution time is a lead indicator.

The assumption that there is a cause and effect relationship is

essential because it allows the measurements in non-financial areas to be used to predict future financial performance. Thus the claim is that financial measures say something about past performance while non-financial measures are the drivers of future performance (Kaplan & Norton,1996c)


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SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG 2.2. Hypotheses Development 2.2.1. Designing The Weight in Each Balanced Scorecard Perspectives In designing the weight of BSC this study is using two methods. This study is attempting to determine the association of each Balanced Scorecard perspectives (financial, customer, internal business process and, learning and growth) with managerial and organizational performance. If there is an association, then through some statistical analysis, we can determine the highest significant perspectives up to the smallest one.

Insert Table 2.1 about here

2.2.2. The Linkage between Balanced Scorecard Usage with Organizational Performance

Several companies have already adopted the balanced scorecard. Their early experiences using the scorecard have demonstrated that it meets several managerial needs. First, the scorecard brings together, and a single management report, and many of company’s competitive agenda are related with: becoming customer oriented, shortening response time, improving quality, emphasizing teamwork, reducing new product launch times, and managing for the long term. Second, the scorecard guards against sub-optimization. It means that, the scorecard allows managers to see the whole aspect of company’s performance (Kaplan & Norton, 1992). The Balanced Scorecard supplemented traditional financial measures with criteria that measured performance from three additional perspectives-those are customers, internal business processes, and learning and growth. It therefore enabled companies to track financial results while simultaneously monitoring progress in building the capabilities and acquiring the intangible assets they would need for future growth (Kaplan & Norton, 1996). The study of Hoque and James (2000), revealed that BSC usage is associated with the increased organizational performance. Therefore, the first hypothesis is :


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SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG H1 : BSC usage in each perspectives (financial, customer, internal-business process, and learning and growth) is positively associated with organizational performance. Figure 2.1 First Theoretical Framework

BALANCED SCORECARD USAGE

ORGANIZATIONAL PERFORMANCE

2.2.3. The Linkage between Balanced Scorecard Usage with Managerial Performance

Effective measurement, however, must be an integral part of the management process. The Balanced Scorecard provides executives with a comprehensive framework that translates a company’s strategic objectives into a coherent set of performance measures. Much more than a measurement exercise, the balanced scorecard is a management system that can motivate breakthrough improvements in such critical areas as product, process, customer and market development (Kaplan & Norton, 1993). BSC affects the behavior of managers and employees, and helps organization deliver dramatically improved performance (Kaplan & Norton, 2001). Moreover, this concept is supported by Kald and Nilsson (2000) in their survey in several Nordic companies found that BSC as a model in measuring performance. BSC usage 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 & Norton,1993, Hoque, et.al.,2001; Ainun Naim, et.al., 2003) In addition, BSC usage also reflects the complexities of the work environment, which enable managers to recognize the various dimensions of their work.

Kaplan & Norton (1993,1996a,1996b,1996c) provide evidence that

companies which use the multiple measurement system can operate in a more efficient way. From the preceding statement, this study hypothesize that : Padang, 23-26 Agustus 2006

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SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG H2 : BSC usage in each perspectives (financial, customer, internal-business process and leaning and growth)

is

positively associated with managerial

performance Figure 2.2 Second Theoretical Framework

BALANCED SCORECARD USAGE

MANAGERIAL PERFORMANCE

III. RESEARCH METHOD 3.1. Data and Samples

The study is used primary data. For the primary data, this study will collect using questionnaire survey, sent to managers in each Bank Syariah Mandiri Branch. Managers are contains of branch manager, vice branch manager, and department manager. In 2005, Bank Syariah Mandiri has 51 branches through out Indonesia. The functional managers is selected for the following reasons : 1. They provide some degree of control over the seniority of the respondent across organization (Ainun Na’im, et.al., 2003). 2. They have been familiar with company’s strategy, whereas these knowledge is the main idea of Balanced Scorecard implementation. Questionnaires were sent to managers by e-mail.

3.2. Measurement Instruments 3.2.1. Organizational Performance Organizational performance was measured by appraising five dimensions of performance: return on investment, margin on sales, capacity utilization, customer satisfaction, and product quality. The instrument is conceptually consistent with Kaplan and Norton’s (1992) BSC theorizing. The procedure used by others (e.g., Hoque and James, 2000; Ainun Naim, et.al., 2003). Respondents were asked to indicate their organization’s performance compared to their competitors along the above five dimensions on a scale from 1 = below average to 5 = above average.


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SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG 3.2.2. Managerial Performance The performance measure developed by Mahoney et. al (1963,19650 was used in this study. This instrument is widely used by many researchers, such as Brownell and Mc Innes (1986); Merchant (1981); Kren (1992) and Frucot and Shearon (1991). This asks for ratings for each of eight dimensions of performance as follows: planning, investigating, coordinating, evaluating, supervising, staffing, negotiating, and representing. It also asks for a single overall rating, bearing in mind that different managerial positions re likely to require different mixes of the eight dimensions. 3.2.3. BSC Usage in Four Perspectives BSC Usage was measured using a 20-item scale similar to that developed by Hoque and James (2000). The instrument comprised items that incorporate Kaplan and Norton’s (1992) four dimensions of the BSC. It asked respondents to indicate the extent to which each item was used to assess their organization performance on a fully anchored, five point Likert scale ranging from 1 (not at all) to 5 (to a great extent). It is possible between performance indicators in BSC Usage have the same indicators in neither organizational nor managerial performance. It is happened because performance indicators in BSC Usage has not classified yet into specific objective, organizational or managerial. Previous studies also conducted in this condition and still, those studies have meaningful conclusions.

3.3. Statistical Method for Data Analysis 3.3.1. Structural Equation Modeling (SEM) This techniques is used to test the first and second hypothesis. Structural Equation Modeling (SEM) as a general statistical modeling technique, which is widely used in the behavioral sciences. Meanwhile, Hair, et.al (1998) defined SEM as a multivariate technique combining aspects of multiple regression (examining dependence relationship) and factor analysis (representing unmeasured concepts— factors—with multiple variables) to estimate a series of interrelated dependence relationships simultaneously. It can be viewed as a combination of factor analysis and regression or oath analysis. The interest in SEM is often on theoretical constructs, which are represented by the latent factors. The relationship between the theoretical constructs are represented by regression or path coefficients between the factors. The structural equation model implies a structure for the covariances Padang, 23-26 Agustus 2006

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SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG between the observed variable, which provides the alternative name covariance structure modeling. However, the model can be extended to include means of observed variables or factors in the model, which makes covariance structure modeling a less accurate name. In order to test the fit between model and data, several indicators are used. If we have a very large sample, the statistical test will almost certainly be significant. Thus, with large samples, we will always reject our model, even if the model actually describes the data very well. Conversely, with a very small sample, the model will always be accepted, even if it fits rather badly. Given the sensitivity of the chi-square statistics for sample size, researchers have proposed a variety of alternative fit indices to assess model fit. Several goodness-of-fit index that does not depend on the sample size or the distribution of the data. Jorekog and Sorbom (1989) have introduced two goodness-of-fit indices called GFI (Goodness of Fits) and AGFI (Adjusted GFI). The GFI indicates goodness-of-fit, and the AGFI attempts to adjust the GFI for the complexity of the model. Two other well known measures are the Tucker –Lewis Index TLI (Tucker & Lewis,1973), better known as the Non-Normed Fit Index or NNFI, and the Normed Fit Index or NFI. Both the NNFI and the NFI adjust for complexity of the model. A general structural equation model is composed of three parts (1) the structural part linking the latent variables. (2) the measurement part specifying the relationships between observed exogenous variables and its corresponding a latent exogenous constructs and (3) the measurement part specifying the relationship between observed endogenous variables and its corresponding latent endogenous constructs. The weighting design will be based on the results of the significance analysis from each BSC perspectives, in both performance measurement (managerial and organizational). Therefore, this paper will estimate the following structural model to examine the first hypothesis : ORGPERF = γ1 FINANCE + γ2 CUST + γ3 INTBUSS + γ4 LEARNGRO + ζ Furthermore, the second hypothesis will be examined through the following structural equation model : MANPERF = γ1 FINANCE + γ2 CUST + γ3 INTBUSS+ γ4 LEARNGRO + ζ


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SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG 3.4. Testing for Hypotheses In order to test the hypotheses, this study will be based on the SEM results. As stated above, the focus of this study’s hypotheses is to test whether BSC usage has positive association with organizational and managerial performance. Therefore, through analysis of perspective’s regression weight, this study will draw several results, which perspective has the positive association and which is not. If the regression weight shows the positive parameters therefore the hypotheses will be supported and vice versa. In Structural Equation Model, there is also probability of significance, but in this study the decision to accept or reject the hypotheses solely based on the parameters of each perspective’s regression weight

IV.RESULTS AND DISCUSSION 4.1. Descriptive Statistics From the questionnaires that has been sent, total questionnaires return is 53 from the total population 100 managers throughout Indonesia (response rate 53 percent). From those number only 51 questionnaire was usable, according to completeness of analysis. The questionnaires is filled by managers in a branch. Usually each branch consists of three managers, there are branch manager, marketing manager and operation manager. Despite of that not every branch has three managers, this research is also consider each branch condition. It took a quite long to wait questionnaires return, on the other hand through e-mail this obstacles can be solved and it consider less costly. The following table 4.1 will describe some characteristics of the respondent in this study. Meanwhile, table 4.2 will show us some descriptive statistics related to respondent responses and theoretical measurement scale. The following table indicates that most of the actual range lies in the middle of measurement scale, thus it shows that most of the respondent answer around the neutral scale.

Insert Table 4.1 and 4.2 about here


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SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG 4.2. Full Structural Equation Modeling Analysis Using confirmatory factor analysis, learning & growth construct can not be identified. Thus, learning & growth construct exclude from the further analysis. Figure 4.1 draw the structural equation modeling between financial, customer and internal business process perspective to organizational performance. As a model, this structural model has fulfilled the goodness of fit criteria where most of the fit measures lies above 0.9 (TLI, IFI, CFI).

Insert Figure 4.1 about here The result from structural model between multiple measures based performance to managerial performance (figure 4.2) shows that the model support the goodness of fit assumption which has value of TLI, IFI, CFI for 0.940;0.950;0.950; respectively.

Insert Figure 4.2 about here

4.3. Hypotheses Testing This section dealing with the aim of this study which is determining the balanced scorecard’s weight. According to that, this study propose two hypotheses, the first one is there is a positively correlated between BSC usage and organizational performance, and the second hypothesis is there is a positively correlated between BSC usage with managerial performance. Thus, this study is attempting to analyze the correlation between BSC usage with two terminology of performance, then through structural modeling, this study is also able to analyze the effect among indicators which designing weight will be based on.


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SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG TABLE 4.3 RESULTS OF STRUCTURAL EQUATIONS MODELING BSC USAGE TO ORGANIZATIONAL PERFORMANCE Parameter Hypothesis 1 Financial Perspective Æ Organizational Perf. Customer Perspective Æ Organizational Perf. Int. Business Process Persp. Æ Organizational Perf. Goodness-of-fit statistics Chi-Square Probability df CMIN/DF NFI RMSEA TLI IFI RFI CFI

Estimate

P

Conclusion

- 0.251 - 0.031 0.011

0.249 0.929 0.959

H1 not supported H1 not supported H1 supported

397.368 0.000 224 1.774 0.903 0.124 0.944 0.955 0.880 0.954

Source : Primary data processed by AMOS 4.0 The following table presented the results in SEM between BSC usage and managerial performance.

TABLE 4.4 RESULTS OF STRUCTURAL EQUATIONS MODELING BSC USAGE TO MANAGERIAL PERFORMANCE Parameter Hypothesis 1 Financial Perspective Æ Managerial Perf. Customer Perspective Æ Managerial Perf. Int. Business Process Persp. Æ Managerial Perf. Goodness-of-fit statistics Chi-Square Probability df CMIN/DF NFI RMSEA TLI IFI RFI CFI

Source : Primary data processed by AMOS 4.0


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Estimate

P

Conclusion

0.093 -0.120 0.050

0.513 0.599 0.729

H2 supported H2 not supported H2 supported

556.858 0.000 318 1.751 0.892 0.123 0.940 0.950 0.871 0.950

SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG 4.4. Discussion The choice of using structural equation model in this study is solely based on the ease in determining the influenced indicator and measuring the influence effect. From the above figure, we can notice that learning and growth perspective doesn’t fit in confirmatory analysis phase, thus we excluded this construct in further analysis.

The remain construct is also have some modification, specifically in

indicator selection to fulfill goodness of fit requirements. Structural Equation Model for organizational and managerial performance showed that several perspective have positively correlation with performance. For detail analysis, the following analysis below should be considered. Hypothesis 1 which is stated that BSC usage in each perspectives (financial, customer, internal-business process and leaning and growth)

are

positively

associated with managerial performance. This hypothesis was not confirmed for financial and customer perspective with a path parameter estimate that was negative (-0.251 and –0.031, respectively) and statistically not significant. In the other hand, H1 is supported by internal business perspective which positive parameter with value 0.011. Hypothesis 2 which stated that BSC usage in each perspectives (financial, customer, internal-business process and leaning and growth) are positively correlated with managerial performance is supported enough by the findings. The regression weight for financial and internal business perspective indicates a positive association between those perspective to managerial performance (0.093 and 0.050) Only customer perspective has negative association to managerial performance.

4.5

Designing Balanced Scorecard’s Weight Based on results , this study will design the balanced scorecard weight

through according to loading factor each performance indicator.

Insert Table 4.5 about here

From the table above this study has already made some suggestion in designing balanced scorecard weight. Usually in practical area, decision in determining the appropriate weight in BSC solely based on expert judgment or using Padang, 23-26 Agustus 2006

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SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG Delphi techniques. Using Structural Equation Model, the result infer that the priorities of weight between performance perspective and performance (whether organizational or managerial) have the same priorities. Thus, those indicators as managers perceived have the same influence in their performance as an individual or as a overall company’s performance. Table 4.5 will be used by Bank Syariah Mandiri in determining the best percentage in their personal appraisal Sheet for branch managers across the country and also as an input in focusing the best corporate performance indicator.

V. CONCLUSIONS, RECOMMENDATIONS AND LIMITATIONS 5.1. Conclusions of the Study One of the main problem in implementing BSC is how to set up the best balanced which is reflected by weight determining. Usually, weights for every perspective will be based on expert judgment and delphi technique. Those methods seem to rely on the normative way (what should be ) not the positive way ( what’s the reality). Those techniques is also tends to focus on the small group of experts which is not always represent the whole employees.

5.2. Recommendations Consistent with the objective of this study, this study is trying to give a significant contribution in determining the best weight in BSC design. According to the results, both of performance have the same indicators priorities. For financial perspective, bank should prioritize return on investment first, then revenue growth and cost per customer. For the customer perspective bank should put the highest weight on new customer acquisition, market share, revenue per customer, customer retention rate, customer response time, length of cycle time in providing service, and number of customer complaints. The last, in internal-business perspective, the priorities were constructed as new revenue per sales person, selling contracts per sales person, profitability per customer, new product revenue, request fulfillment time, internal customer satisfaction, number of new product launches, and service error rate.


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SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG 5.3. Limitations of the Study There are several limitations in this study. This study seems to focus only in management accounting perspectives without any explanation from the strategic management view.

Another limitation is the scope of the study only for one

company and the usable respondent as not much if the study held to analysis through out the country. Therefore, the further study should extent the scope of the research and the amount of the respondent.


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SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG Ittner, Cristopher D., David F. Larcker, and Marshall W. Meyer. 2003. ”Subjectivity and the Weighting of Performance Measures: Evidence From a Balanced Scorecard“. The Accounting Review. Vol. 78 (3). pp.725-758. Johnson, H. Thomas and Robert S. Kaplan.1991. Relevance Lost ; The Rise and Fall of Management Accounting. Harvard Business School. Kald, Magnus and Fredrik Nilsson.2000. ”Performance Measurement at Nordic Company“. European Management Journal. Vol. 18 (1). February. pp.113127. Kaplan, Robert S.1983.”Measuring Manufacturing Performance: A New Challenge for Managerial Accounting Research“. The Accounting Review. Vol.58 (4) pp.686-705. Kaplan, Robert S. and David P. Norton.1992. ”The Balanced Scorecard-Measures that Drive Performance“. Harvard Business Review. January-February. pp.71-79. Kaplan, Robert S. and David P. Norton.1993. ”Putting The Balanced Scorecard to Work“. Harvard Business Review. September-October. pp.134-142. Kaplan, Robert S. and David P. Norton.1996a. ”Linking the Balanced Scorecard to Strategy“. California Management Review. Vol. 39 (1). Fall. pp.53-79. Kaplan, Robert S. and David P. Norton. 1996b. ”Using The Balanced Scorecard As A Strategic Management System“. Harvard Business Review. JanuaryFebruary. pp.75-85. Kaplan, Robet S. and David P. Norton.1996c. Translating Strategy into Action: the Balanced Scorecard. Boston-Massachusets. Harvard Business School Press. Kaplan, Robert S. and Anthony A. Atkinson.1998. Advanced Management Accounting. 3rd Ed. Prentice Hall, Inc. Kaplan, Robert S. and David P. Norton. 2001. ”Transforming the Balanced Scorecard from Performance Measurement to Strategic management: Part II“. Accounting Horizons. Vol. 15 (2). June. pp.147-160. Kaplan, Robert S. and David P. Norton.2001. The Strategy Focused Organization. Harvard Business School Press. Kren, Leslie.1992. ”Budgetary Participation and Managerial Performance: The Impact of Information and Environmental Volatility“. The Accounting Review. July. pp.511-526. Lipe, Marlys Gascho and Steven E. Salterio. 2000. ”The Balanced Scorecard: Judgmental Effects of Common and Unique Performance Measures“. The Accounting Review. July. pp.283-298.


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SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG TABLE 2.1 SUMMARY OF THE PREVIOUS RESEARCH ON THE ASSOCIATION BETWEEN BSC USAGE AND PERFORMANCE Author Hoque (2000)

and

James

Hoque et.al. (2001)

Ainun Na’im (2003)

et.al.

Variables

Research Method

Result

Balanced Scorecard Usage , Organizational Size, Product LifeCycle Stage, Strength of Market Position, and Organizational Performance Performance Measures Usage, Intensity of Market Competition, Computer Aided Manufacturing, and Business Unit Size

Moderated Regressions Analysis, to see the relationship and moderated roles among those variables

Greater BSC Usage is associated with improved organizational performance

Multiple Regression Analysis, where Performance Measures Usage as dependent variable and the remains as independent variable

Multiple MeasuresBased Performance (MMBP) Evaluation, Procedural fairness, Interpersonal trust and Managerial Performance

Path Analysis, to see whether direct or indirect effect between MMBP and Managerial Performance

Greater emphasis on multiple measures for performance evaluation is associated with business facing high competition and making greater use of computer-aided manufacturing processes The use of multiple measures for performance evaluation has a direct effect on managerial performance


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SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG TABLE 4.1 CHARACTERISTICS OF RESPONDENTS N

%

20 13 18

39,3 25,4 35,3

51

100,0

47 4

92,2 7,8

51

100,0

6 22 23

11,8 43,1 45,1

51

100,0

15 23 7 3 3 51 Source : Primary data processed, 2004

29,4 45,1 13,7 5,9 5,9 100,0

Position 1. Branch Manager 2. Marketing Manager 3. Operation Manager

Sex 1. Male 2. Female

Experiences 1. =< 1 years 2. 1 – 3 years 3. > 3

1. 2. 3. 4. 5.

Age 27 – 35 36 -40 41 – 50 > 50 NA

TABLE 4.2 DATA CHARACTERISTICS Constructs

N

Financial perspective Customer perspective Internal-Business process Perspective Learning & Growth Perspective Organizational Performance Managerial Performance

51 51 51

3 8 16

15 34 36

11,06 25,18 26,9

Std Dev 2,68 4,39 5,10

51

4

10

7,47

1,41

2-10

51

13

23

17.57

2,44

5-25

51

27

41

33,69

3,47

9-45


Min

Max

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Mean

Theoretical Range 3-15 7-35 8-40

SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG Source : Primary data processed, 2004 FIGURE 4.1 Structural Equation Model between BSC Usage and Organizational Performance 0, .33 1

e30, .46

1 e2 0, .63 1 e1 0, .75 1 e40, .59 1 e50, .19 1 e60, .32 1 e70, .66 1 e80, .54 1 e90, .49 1 e10 0, .50 1 e110, .89 1 e120, .28 1 e130, .47 1 e140, .63 1 e150, .27 1 e160, .66 1 e170, .47 1 e18

3.67

x1 4.351.20 .73 x21.00 3.04

x3

0, .66

finance

3.12

x4 3.43 x5 3.94 1.36 1.14 0, .24 x6 3.821.58 1.16 x7 3.45 cust .63 .85 x8 3.59 1.00 x9 3.82 x10 3.24

x113.55 x123.76 .30 .29 x133.76.34 0, .79 .36 x143.22 .56 intbuss x151.06 3.02 1.23 x163.06 1.00 x173.29 x18

-.25

.24

3.43 1 x21 3.65 1 1.00 0 .81 x22 1 3.67 .47 1 orgperf .47x233.33 .49x24 1 3.49 1

z1

-.03 .50

x25

.01 .31



0, .40

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Chi-squares = 397.368 Probability = .000 df = 224 CMIN/DF = 1.774 GFI = \gfi AGFI = \agfi NFI = .903 RMSEA = .124 TLI = .944 IFI = .955 RFI = .880 CFI = .954

0, .35 e210, .09 e220, .20 e230, .16 e240, .34 e25

SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG FIGURE 4.2 Structural Equation Model between BSC Usage and Managerial Performance 0, .34 1 e30, .46 1 e20, .63 1 e1 0, .76 1 e40, .60 1 e50, .20 1 e60, .32 1 e70, .66 1 e80, .53 1 e90, .48 1 e10 0, .50 1 e110, .89 1 e120, .28 1 e130, .47 1 e140, .63 1 e150, .27 1 e160, .66 1 e170, .47 1 e18

3.67 x1 4.351.19 0, .67 .73 x21.00 3.04 finance

x33.12 x43.43 x53.941.32 1.12 x63.821.54 0, .25 1.15 x73.45 cust .63 .85 x81.00 3.59 x93.82 x103.24 x113.55 x123.76 .30 .28 x133.76.34 0, .79 .36 x143.22 .56 intbuss x151.06 3.02 1.23 x161.00 3.06 x173.29 x18

3.84 1

x263.67 .09 0, .18 x27 1 3.94 1.00 .25 1 z2 .94 x283.80 1 .76 1 0 .81 x293.78 .63 -.12 1 manperf .90x303.51 1 .78 .50 .82x313.69 1 .63x323.71 1 x333.75 .05 1 Chi-squares = 556.858 .32 Probability = .000 x34 df = 318 CMIN/DF = 1.751 GFI = \gfi AGFI = \agfi NFI = .892 RMSEA = .123 TLI = .940 IFI = .950 RFI = .871 CFI = .950



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0, .14 e260, .17 e270, .14 e280, .19 e290, .25 e300, .37 e310, .14 e320, .24 e330, .19 e34

SIMPOSIUM NASIONAL AKUNTANSI 9 PADANG TABLE 4.5 DESIGNING BSC WEIGHT

Perspectives

Financial Perspective Customer Perspective Internal-Business Process

Performance Indicators

Loading Factor to Organizational Performance

Weight Priorities

Loading factor to Managerial Performance

Weight Priorities

Return-onInvestment (x1)

0.863

1

0.858

1

Revenue (x2)

0.657

3

0.661

3

Cost per Customer (x3)

0.717

2

0.719

2

Revenue per Customer (x4)

0.612

3

0.606

3

0.593

4

0.588

4

0.875

1

0.868

1

0.710

2

0.717

2

0.359

7

0.367

7

0.498

6

0.509

6

0.577

5

0.588

5

0.356

7

0.358

7

0.262

8

0.259

8

0.495

5

0.497

5

0.422

6

0.424

6

New Product Revenue (x15)

0.534

4

0.534

4

New Revenue per sales Person (x16)

0.876

1

0.873

1

0.802

2

0.804

2

0.791

3

0.791

3

Growth

Customer Retention Rate (x5) New Customer Acquisition Rate (x6) Market Share (x7) Number of Customer Complaints (x8) Length of Cycle time in Providing service (x9) Customer response time (x10) Number of New Product Launches (x11) Service Error Rate (x12) Request Fulfillment Time (x13) Internal Customer Satisfaction (x14)

Selling Contracts per sales person (x17) Profitability per customer (x18)



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