Journal of Economic and Social Research 10(1) 2008, 35-72 The Effect of Competition, Just In Time Production and Total Quality Management on the Use of Multiple Performance Measures: An Empirical Study Melek Eker* & Fikri Pala” Abstract. This paper is an empirical investigation into the use of multiple performance measures in manufacturing organizations. Specifically, the relationship between multiple performance measurement system and competition factors, JIT practices and TQM practices is examined through the data collected from 122 manufacturing firms from the Turkish top 500 companies in 2005.
The results show there is a linear relationship between using multidimensional performance measurement system and the firms that have high market position are those that are using JIT and TQM more than others. JEL Classification Codes: D29, M29. Keywords: Multiple Performance Measures, Competition, Just in Time Production (JIT), Total Quality Management (TQM), Factor Analysis, Multi-nominal logistic Regression Analysis. 1. Introduction Performance measurement is a concept of modem business administration history.
The organizations in the market have to identify with concepts such as “dynamism”, “scarce resources” and “complexity” and have to show high performance to survive thereby needing to measure and to evaluate their performances accurately. This means for firms that performance measurement is more than a systematic action, but today, performance measurement and evaluation system is the most important managerial tool for organizations. Nowadays, because of high specialization, division of labour and high competition, it’s clear that performance should be thought more ‘ Department of Management, Uludag University, Bursa. Department of Management, Uludag University, Bursa. 36 Melek Eker & Fikri Pala elaborately as a concept and discussed not in a result-focused but in a process-focused way. (Albright, 2006:157-174; Yasin and et al. , 2005: 323). In this context, it will be possible to state two types of criteria conteming the performance measurement in organizations. These are financial and nonfinancial performance criteria. Financial criteria evaluate the performance in terms of monetary assets gained and therefore attach importance to the result.
On the other hand, a non-financial criterion evaluate the performance in terms of units or divisions and work processes in a company and highlights the actions that provide final financial result and enable its sustainability. It’s possible to separate performance criteria theoretically, but both are linked practically. In fact, firms are organizations in business to make a profit, but today it is possible to argue that there are various functions in organizations and therefore financial performance is likely to be affected much more by non-financial processes.
Hence, performance measurement has to have a structure containing both flnancial and non-financial criteria. (Wruck and Jensen, 1998:401^23). Due to its effect on how successful firms are, performance measurement system has to contain accurate and reliable information, which is so critical to business organizations because of its roles in future planning, evaluation of targets and actual results, and decision-making matters affecting employees are all based on the strength of the information contained in performance measurement evaluative processes.
However, the more important point needing to be noted here is that generally the meaning of performance for organizations has become limited to only profitability or financial incomes. Undoubtedly, firms are profltbased organizations, but more than that, they have to be sustainable. Making profitability sustainable depends on managers’ abilities to see all developments in and around firms and evaluate them according to future results.
So, this underlines that the concept of performance should not be confined only to financial results, but also should have a wide meaning including the non-financial criteria as well. Balanced Scorecard (BSC) is a performance measurement model, which was proposed as a result of this obligation. Three reasons for using multiple performance measures are: (1) perceived limitations in traditional accounting-based measures, (2) ‘ Fisher (1995) ndicates that many firms believe that financial measures are too historical and “backward-looking”, lack predictive ability to explain future The Effect of Competition, Just In Time Production and Total Quality 37 Management on the Use of Multiple Performance Measures: An Empirical Study increasing competitive pressure and (3) applying new management techniques like TQM and JIT needed for non-financial measures (Itner and Larcker, 1998: 217-218).
Performance should therefore not be interpreted only as profit-focused activities but also as non-financial activities directed toward obtaining or following profit process. This kind of new comprehension on performance measures points to changing perception of firms toward performance. In this context, improvements in information technology make it easy to observe internal and external business processes, consequently making it possible to apply BSC. (Donovan, 1-3).
Hitherto studies have shown that the use of non-financial performance measures by the firms is directly related to such variables as market competition, computer aided production, new production techniques, the structure of firm (size, culture, technological situation and adopted strategy etc. ) and sector structure. The aim of this study is to determine whether the multidimensional performance measures are used or not by the manufactures of top 500 firms in Turkey and if they’re used, to define the relationship between multidimensional performance measures and. firm’s market position, market competitive density degree, JIT and TQM practices.
In this context, first the literature and the developed hypotheses on the subject will be reviewed and then the designation of sampling and factor analysis, descriptive statistics, multi-correlation and multinomial logistic regression analysis results will be described together with the results from our empirical study. 2. Literature Review and Hypotheses 2. 1. Literature Review Many factors contribute to why many firms prefer n’on-fihancial performance measures. In view of this, some researchers suggest that the preference for these measures on a large scale is related to the enterprises operational and competitive structure (Said, et. l. , 2003: 193-223), others suggest that this preference can be related to the JIT, TQM and CAM structure (Hoque, et. al 2001: 23-45). Similarly, while many reported that the use of multiple performance measures is relevant only to the strategic preference of managers (Malina and Selto, 2001:48; Govindarajan and performance, reward short-term or incorrect behaviour, provide little information on root causes or solutions to problems, and give inadequate consideration to difficult to quantify “intangible” assets such as intellectual capital. 38 Melek Eker & Fikri Pala
Gupta, 1985: 51-66), some reports demonstrate that an enterprise’s environmental conditions affect this preference. On this subject, for example. Hoque (2004) found that there was a meaningful relationship between environmental uncertainties and the preference for these measures. Chenhall and Morris (1986: 16-35) found that organizations prefer nonfmancial management accounting systems to cope with high environmental uncertainties effectively. The use of multiple performance measures and its positive effect on production performance are demonstrated in another section of the literature. For example.
Banker, Potter and Schroeder (1993: 33-55) stated that multidimensional performance measurement system reports presented to the personnel in production line was positively associated with the implementation of modem management techniques such as JIT, Team Work and TQM. However, Chenhall (1997: 187-206), Callen, et al. (2005: 271309), Itner and Larcker (1995: 1-34) examined the use of BSC together with the aforementioned modem techniques and argued that enterprises using the TQM/JIT and non-financial (production performance) measurements together have reached a higher performance than other firms without these measurements.
Additionally, many studies examine the positive contribution of multiple performance measures on the general enterprise performance from the fmancial perspective. For example, Davies & Albright (2004: 135-153) and Dilber et al (2005: 220) argued that there is a meaningful positive relationship between the use of BSC and high-level fmancial performance. In an empirical study by James, Hoque (2000: 1-17) demonstrates that the use of BSC increases general enterprise performance, but this increase is not associated with organization size, product life circle, or market position.
Lingle and Schiemann (1996: 56-61) found that enterprises managed by measurements reached a higher fmancial performance level, a higher industrial position and a higher level in the management process relative to enterprises that are not managed by measurements. Ittnera, Larckera and Randalb (2003: 715-741) indicated that the enterprises placing more emphasis on measurement and variety have acquired a much higher stock exchange income.
Perera, Harrison and Poole (1997: 557-572) argue that the use of non-financial measures show significant associations with customer focused strategy, but not the link to organizational performance. Apart from studies examining BSC effects on general enterprise performance, other studies have examined the enterprise’s suitable working The Effect of Competition, Just In Time Production and Total Quality 39 Management on the Use of Multiple Performance Measures: An Empirical Study conditions as an effective performance measurement tool in BSC.
For instance, Cavalluzzo and Ittnera (2004: 243-267) state that organizational factors such as willingness in the top management directed at the use of performance knowledge, decision making and training in the subject of performance measurement techniques have a positive effect on measurement system development and usage. Also, Moers (2005: 67-80) called significant attention to the positive relationship between the variety of performance measures and the degree of perfection with bias during the performance evaluation.
It is clear that the bias mentioned here indicates a pre-cognitive accumulation directed at performance measurement. On the other hand, Krumwiede (1998: 239-278) suggested that organizations with higher quality information systems could implement new measurement systems comfortably relative to companies with less sophisticated information systems. Thus, he suggests that this highlights the linear relationship between opportunities for existing information systems and the success of implementation.
In addition, he draws attention to managers^ who are satisfied with information from the existing system that might not be willing to invest in new systems. This will give way to the development of a negative relationship between the system and its implementation. Briefly, these studies, within a framework related to literature conceming multidimensional performance measurement system, draw attention to the use of multiple performance measures by enterprises associated with the anager’s preference, specifically, the enterprise manager’s scientific level, organizational culture, environmental conditions, technological developments, new management techniques, enterprise performance and indirectly, stock exchange incomes. Our study considers the relationship between the four dimensions that occur in BSC (financial, customer, internal business processes, learning and growth); a) with the enterprise’s position in the market, b) with the level of competition in the market, c) with the JIT practices and d) with the TQM practices. 2. 2. Variables and Hypotheses 2. . 1. Balanced Scorecard BSC created firstly by Kaplan and Norton in 1992 at the end of pursuits on altemative planning, control and performance measurement system in 40 Melek Eker & Fikri Pala management accounting, is an efficient management tool (Kaplan and Norton: 1992). The target is to enable managers to obtain comprehensive viewpoint about overall business and in this way help them focus more on critical activities that are supposed to improve the organizational strategy of the firm (Wongrassamee, et. al. 2003: 18). In that way, BSC undertakes two crucial functions.
First is being a strategic guide for department managers. Second is being communication and strategic planning tool describing the link between financial and nonfinancial criteria as a guide for firms (Kaplan and Norton 1996; Kaplan and Atkinson, 1998: 367-375; Atkinson, Kaplan and Young: 2004; Simons: 2000). Using BSC provides some opportunities to managers on subjects like ability to evaluate changes around a firm, to determine and evaluate the processes of the aims of a firm, to check whether internal performance targets are achieved or not and sustaining the continuation of improvements, in the final analysis.
Four dimensions of BSC and derived indicators have created these opportunities. These four dimensions or perspectives will be explained briefiy. Financial performance measures; they are the focal point for the target and measures of other three perspectives in BSC. In this sense, financial performance measures can be considered as the outcome of operational activities (Rao: 2000). Therefore, each selected measure should be a part of the cause-and-effect relationship leading to an improvement in financial performance.
These measures are items such as sales amount, market share, new customers, new markets, cash now, return on capital, etc. (Morrow, 1992: 145). Customer performance measures; today, being customer-focused is one of important items for firms, so at the same time it’s a kind of important expression of vision and mission. In this sense specific measures reflecting critical factors like time, quality, cost should be determined. Customer satisfaction, improving costumer loyalty, gaining new customers, customer profitability, and market and customer shares in targeted scope are basic measures.
Internal operation measures; these are obtained from critical success factors which are effective on providing shareholder and customer satisfaction by focusing on work processes and activities (Keegan, Eiler and The Effect of Competition, Just In Time Production and Total Quality 41 Management on the Use of Multiple Performance Measures: An Empirical Study Jones, 1989: 45-49). But, the most important point here is that to create value for both customer and shareholder, it is necessary to define and measure an exact intemal operation value chain at the designing and development stage, production and commercializing (Eker, 2004:128).
These measures include the duration of presenting new product to the market, number of new products, sales percentage of new products, rate of defect, duration of production, production cost, just-in-time delivery, etc. Leaming and growth measures; making real the ideals related with financial, customer and intemal operations highly depend on the learning and growth capacity of an organization.
In leaming and growth measures especially, it investigates and measures what sort of methods to be followed for increasing the growth of intemal operation methods, which measures are employee satisfaction, productivity and sustainability ofthe employees. 2. 2. 2. Market Competition One of the distinguishing factors of the use of multiple performance measures by the firms is the competition environment in the market. As the market competition increases, the firms are likely to need multidimensional performance measurement system more than before in rder not to lose their power and market share. Also, the measures included in multidimensional performance measurement system (BSC) are known to increase the level of competitiveness by monitoring the static and dynamic capabilities of the firms (Hoque, Mia and Alam, 2001: 26). If it’s considered that the world has become a single market in global scale, in such a condition, it’s necessary for a firm to have the capability of offering speedy customer service (reliability), high quality and low cost, different and new product/service in order to be dominant in its own sector.
Furthermore, all these need to be supported by total and coordinated organization efforts and also by performance measurement systems serving the same objectives within the organization. BSC is not only satisfied with following the financial performance of the firm, but it could also be functional by monitoring non-financial performances like customer satisfaction, renewal via quality production, which are essential to sustaining the competitive advantage (Otiey, 1999: 363-382; Howell and Soucy, 1987: 27; Trussel and Bitnet, 1998:441). 2 Melek Eker & Fikri Pala 2. 2. 3 Just-In-Time Production It is possible to observe that traditional performance measurement system is inconsistent with JIT system benefiting from technological innovations at a maximum level and also that it prevents or hides broadbased effectiveness of new production methods. In this sense, the restrictions of traditional measurement system in JIT environment might be listed as follows: Continuous development in production process is basic element in JIT manufacturing environment.
To reach this aim easily, it’s intended to make flow of production possible with minimal parties and decreasing stock levels to a minimum. Yet, production and productivity measures of traditional understanding have reported that the productivity is low when small-lot production is made (Drury, 1990: 40-41). For this reason, traditional accounting system suggests increasing batch capacity rather than decreasing lot size, which leads to raising stock levels, long supply process, ihcreasing cost and declining customer satisfaction (DonoVah, 2-3;
Mcnair, Lynch and Cross, 1990: 29). As in standard costing, appropriate operational control of traditional accounting system cannot be carried out in today’s production environment (Allott, 2000: 54-56; Cheatham and Cheatham: 1996; Ezzamel, 1992: 117). Besides, due to the reliability and consistency of manufacturing processes in JIT environment, deviations do not exist or exist in quite low level and it also leads to less use of deviation analyses. JIT manufacturing system changes will bring about changes in information requirements (Upton, 1998:110).
As it is known, normally traditional performance reporting is prepared monthly or weekly and cannot detect on time real reasons of processes that are not realized as expected. Yet, in JIT production system there is a possibility of short production cycle, so it requires information for the problems coming out in accordance with one-day or “real time” principal. In current production environment, direct labor cost is between 5%15% of total product cost.
In this sense, traditional accounting system is likely to exaggerate the importance of labor cost and – – The Effect of Competition, Just In Time Production and Total Quality 43 Management on the Use of Multiple Performance Measures: An Empirical Study ignores the control and measurement methods of increasing general production costs. Another limitation of traditional accounting system is its failure in reporting the criteria such as quality, reliability, supply duration, flexibility, and customer satisfaction (Johnson, 1990:63).
As a result of this, management and the employees are encouraged to focus only on costs rather than those critical success factors. Consequently, JIT production system is in need of a performance measurement system that will follow, measure and report critical success factors such as “production and delivery time”, “quality”, “flexibility”, “cost” “efficiency” and “continuous development”(Fullerton, 2003: 40; Mcllhattan, 1987: 25-26). In current environment, which is dominated by a flexible, dynamic, and process-oriented roduction understanding, JIT production system cannot perform its functions including result-focused traditional performance measurement system, measuring, evaluating and reporting of operational actions in order to be successful. Therefore, performance measurement system of a corporate using Just-in-time production system should support basic variations such as increasing product or service quality, continuous development and reducing the losses (Hendricks, 1994: 27).
BSC meets the new management requirements because of its following qualifications: (1) focusing long term perspective instead of short term perspective; (2) performing data both in fmancial and non-financial/operational dimensions; (3) being timely and ready for usage instead of being prepared for terms; (4) being easy to understand and apply; (5) immediately answering/adapting the changes in the production process, (6) transforming the firm strategy to operational measures (Santari, 1987: 27). 2. 2. Total Quality Management TQM does produce value, through a variety of benefits: improved understanding of customers’ needs; improved customer satisfaction; improved intemal communication; better problem-solving; greater employee commitment and motivation; stronger relationships with suppliers; fewer errors; and reduced waste (Powell, 1995: 15-37). In order to get this value and to ensure the success of the system, the features of the performance measurement system of the businesses applying the system should be: (Kaydos, 1999: 150) 44
Melek Eker & Fikri Pala to focus the attention of managers on the satisfaction of foreign and domestic customers to produce assumptions on strategy to detect the unforeseen quality and wasting problems to provide objective information for priority-setting to receive support from managers and employees for further changes when they see concrete improvements in performance to increase the loyalty of employees by encouraging managers to delegate their authority Taking all these features into account, it is seen that BSC is in compliance with what is expected from a performance measurement system in the context of TQM.
Because there is a reciprocal relationship between BSC and TQM as the former makes the latter more efficient through its applications. Accordingly, BSC makes TQM more efficient in the following matters: (Kaplan and Norton, 2001:376) Firstly, it complements the intemal processes where the progressive elements with critical importance for the strategic success are found. TQM is implemented in many businesses; however, the effects of its implementation can be determined neither in financial terms nor in terms of the performance with respect to the customer, and the implementation remains limited to the department or unit level.
BSC, on the other hand, identifies the processes that are important for the strategy as well as the priorities in these processes. Moreover, it also determines whether the process developments focus on such important issues as cost-cutting, quality improvement and shortening of production cycle, or not. Secondly, BSC identifies the non-financial quality measures regarding the quality costs and prepares reports on a daily or real-time basis, and it can find out the real causes of the unfulfilled transactions (Sinclair and Zairi, 2000: 156-157).
Therefore, BSC proves to be a crucial resource, which provides continuous and acctirate feedback to managers and employees, in meeting customer expectations, improvement of processes and reporting of quality performance measures. Thirdly, BSC urges managers to develop business processes in order to achieve successful outputs for customers and shareholders, and to create value. Within this framework, a perpetual relationship between quality and the financial outputs is made possible. Based on the above studies, we posit that increasing application of JIT and TQM, as well as intense market competition, would prompt greater
The Effect of Competition, Just In Time Production and Total Quality 45 Management on the Use of Multiple Performance Measures: An Empirical Study multiple performance measures usage. Therefore, the following hypotheses are proposed: Hypothesis 1 : The greater emphasis on the use of multidimensional performance measurements by the management will be associated with a more intensely competitive environment. Hypothesis 2: The greater emphasis on the use of multidimensional performance measurements by the management will be related to a greater application of JIT.
Hypothesis 3: The greater emphasis on the use of multidimensional performance measurements by the management will be associated with a greater application of TQM. 3. Research Methodology 3. 1. The Nature of the Research This study depends on the data related to 430 manufacture firms of the top 500 in Turkey. The data forms were delivered between the dates of 01 January- 30 June by post and mailed to the top managers (general manager or vice general managers) of manufacture firms that participated in this study. The survey forms return rate was 28. 3% (122). The manufacturing activity of the firms is depicted in Table 1. 6 Melek Eker & Fikri Pala Table 1: Profile of respondents by manufacturing activity Manufacturing Activity Frequency 25 15 1 10 12 6 6 13 7 20 1 6 121 Percent 20,5 12,3 ,8 8,2 9,8 4,9 4,9 10,7 5,7 16,4 ,8 4,9 99,2 Valid Percent 20,7 12,4 ,8 8,3 . 9,1 5,0 5,0 10,7 Cumulative Percent 20,7 33,1 33,9 42,1 51,2 56,2 61,2 71,9 77,7 94,2 95,0 100,0 1 Textile, clothing and footwear 2 Food and allied products 3 Drink and tobacco 4 Construction 5 Petroleum and chemicals 6 Plastic products 7 Metal Wares 8 Machinery 9 Wood and paper products 10 Automotive and spare part 11 Glass products 12 Electronic products TOTAL 5,8 6,5 ,8 5,0 100,0 As can be seen from the table, manufacturing activity distribution was realised in the following order, 20,7% textile, clothing and footwear, 16,5% automotive and spare parts, 12,4% food and allied products and 10. 7% machinery sector. 3. 2. Data Collection Tools The survey form, which was developed to collect the research data, was comprised of three parts. In the first part, it is aimed at defining the usage level of JIT and TQM practices. Within this framework, participants were requested to designate their choose “not used”, “partly used”, “used”, “rather used” and “used at high level”.
The second part consisted of 5 questions, which were directed at defining the firm’s market situation and the competition level in the market. Within this framework, participants were requested to mark each term “very bad”, “bad”, “average”, “good” and “very good” for each denotation which occurred between 1 and 5. In the last section, the diversity of measurement is measured with an adapted version of the instrument used by Hoque and James (2000) and Hoque et al. (2001).
The aforementioned BSC approach was comprised of four sub-dimensions, such as “financial”, “customer”, “intemal business processes” and “leaming and growth” and a total of 20 items. The participants were requested to designate whether their firms used the aforementioned measures. For this, the likert scale, in which the choices between 1 and 5 were “not used at all”. The Effect of Competition, Just In Time Production and Total Quality 47 Management on the Use of Multiple Performance Measures: An Empirical Study “partly used”, “used”, “used rather a lot”, and “used very much”.
The reliability analysis was performed to test the consistency of BSC s survey results. The alpha coefficient was found to be 90%. No variable was negatively associated with the . total correlation. The data showed strong internal consistency. 3. 3. Data Analysis In this study, the data was entered into SPSS 13 for data analysis. Factor analysis, descriptive statistics, multi- correlation and multinomial logistic regression analysis were performed. 3. 3. 1 Factor Analysis Exploratory factor analysis was used to designate the factors which form the sub dimensions of BSC.
Firstly, KMO (Kaiser-Meyer-Olkin) sampling adequacy measure was calculated for determining the convenience of data for factor analysis. KMO varies from 0 to 1. This measure shows that sampling is convenient for factor analysis when it is close to 1 and it shows that sampling is not convenient for factor analysis when it is under 0. 50. In the analysis the KMO sampling sufficiency has been calculated as 0. 803, this shows that this sampling has sufficient size. We use basic components and varimax rotating technique to carry out factor analysis.
The obtained factor analysis results were examined, because the factor burden related to the market share measure in the second and third factors and the factor burden related to the employees’ satisfaction measure in the second and fourth factors that have almost the same burdens, analysis has been done again excluding these two variables. At the end of the analysis 5 factors have been determined whose Eigen value is above 1. Five factors explained 69. 857 % of the total variance. Factor 1 explained most proportion of the total variance (17. 098 %) and consisted of variables which contained “internal business processes measures”.
Factor 2 explained 14. 381% of the total variance and consisted of variables, which were related to “customer performance measures-I”. Factor 3 explained . 13. 582% of the total variance and consisted of variables, which were related to “financial performance measures”. Factor 4 explained 13. 495% of the total variance and factor 5 explained 11. 301% of the total variance and they consisted of variables, which were related to “learning and 48 Melek Eker & Fikri Pala growth measures” and “customer performance measures-II”, respectively. Table 2 shows groups of questions.
Table 2: Rotated Component Matrix Factor Factor Factor Performance Measurement 1 3 2 Items Internal Business Measures ,839 Rate of material scrap loss Ratio of good output to total ,748 output at each Production process ,667 Manufacturing lead time ,613 Materials efficiency variance ,546 Labour efficiency variance Customer Performance Measures-I ,745 Customer response time ,694 Number of warranty claims ,662 On-time delivery ,609 Survey of customer satisfaction ,562 Number of customer complains Financial Performance Measures ,873 Sales growth ,827 Operating income ,576 Return-on-investment Learning and Growth Measures Number of new product launches Time-to-market new products Number of new patents Customer Performance Measures -II Percentage of shipments returned Due to poor quality Number of overdue deliveries Factor 4 Factor 5 ,831 ,824 ,736 ,774 ,742 The analysis carried out on performance measures was also performed respectively on competitive factors. According to this, alpha coefficient was calculated as 58% for competitive factors. KMO sampling adequacy measure was 0,561 therefore sampling was convenient for factor
The Effect of Competition, Just In Time Production and Total Quality 49 Management on the Use of Multiple Performance Measures: An Empirical Study analysis. Also, significant level of Bartlett test was calculated as 0,00. Consequently, both tests showed that factor analysis could be applied to data. In the factor analysis, principal component analysis and none rotation technique were used. At the end of the analysis 2 factors have been determined which have Eigen value above 1. Two factors explained 65. 972% of the total variance. Factor 1 explained most proportion of the total variance 38. 186% and Factor 2 explained 27. 786% of the total variance.
In the results of factor analysis the first factor is named firm’s market situation and the second factor as market competitive density level. Table 3: Rotated Component Matrix 1. Factor ,867 ,824 ,683 ,820 ,810 2. Factor Competition for Marketing Competition for Market Share Competition for New Product Development Competitors’ Power Number of Competitors in the Industry 3. 3. 2. Descriptive Statistics related to the Variables and Correlation Analysis In Table 4, the BSC and sub-dimension averages, minimum, maximum values and standard deviations of the firms are presented. The firm’s usage points of overall multidimensional performance measures are between 38 and 100; the average usage point was 74. 751.
When the BSC subdimensions were analysed, the financial measures were between 6 and 15 and the average was 12. 8525. The customer measures usage points were between 17 and 40 and the average was 30. 5656. The intemal business process measures usage points varied between 7 and 25 and the average was 18. 9174. The learning and growth measures usage points were between 4 and 20 and the average was 12. 6148. These average figures show us that the firms use the financial performance measures (86%), customer performance measures (76%), and intemal business processes measures (75%) at a rather high level and teaming and growth measures at a medium level. 50 Melek Eker & Fikri Pala
Table 4 : BSC and Sub Dimensions Averages, Minimum, Maximum Values Mean Standard Cronbach N Theoretical Minimum Maximum No deviation alpha of range items ,572 18,3639 2,40303 2,2 21,2 Competition 122 5 5-25 Factors 3,57 1,191 1 1 5 JIT 117 1-5 1,144 1 1 4,08 TQM 121 1-5 5 74,7951 12,64842 ,905 20-100 38 100 Overall 122 20 Multidimensional Performance Measures ,762 15 12,8525 2,07970 122 3 3-15 6 Financial Performance Measures 40 30,5656 5,46361 ,787 Customer 122 8-40 8 17 Performance Measures 18,9174 4,23396 ,849 Intemal Business 121 5-25 25 5 7 Measures 4 122 4 20 12,6148 3,88352 ,813 Learning and 4-20 Growth Measures Variable Table 5 shows a correlation matrix for all variables. As proposed, the overall use of multiple performance measures is positively and significantly correlated with firm’s market situation, market competitive density level, JIT and TQM practices and the correlations were 0,425 (p