دانلود مقاله ISI انگلیسی شماره 362
ترجمه فارسی عنوان مقاله

کاربرد فرایند شبکه تحلیلی فازی (ANP) برای کارت امتیازی متوازن (BSC) : مطالعه موردی شرکت تولیدی

عنوان انگلیسی
Using the fuzzy analytic network process (ANP) for Balanced Scorecard (BSC): A case study for a manufacturing firm
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
362 2010 9 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Expert Systems with Applications, Volume 37, Issue 2, March 2010, Pages 1270–1278

ترجمه کلمات کلیدی
مدیریت استراتژیک - ارزیابی عملکرد - کارت امتیازی متوازن - فرایند شبکه تحلیلی فازی () - متغیر زبانی - ارزیابی فازی - کارت امتیازی متوازن - منطق فازی - سیستم ارزیابی عملکرد -
کلمات کلیدی انگلیسی
Strategic management, Performance evaluation, Balanced Scorecard BSC, Analytic network process ANP, Linguistic variable, Fuzzy evaluation,
پیش نمایش مقاله
پیش نمایش مقاله  کاربرد فرایند شبکه تحلیلی فازی (ANP) برای کارت امتیازی متوازن (BSC) : مطالعه موردی شرکت تولیدی

چکیده انگلیسی

Balanced Scorecard (BSC), which is used as a strategic evaluation tool, is a method of determining business performance using lagging and leading indicators on the basis of vision and strategies. The method suggests that business performance should be evaluated not only by using financial indicators but also simultaneously considering non-financial indicators. It has been revealed in the review of relevant literature that despite the satisfying levels achieved in conceptual and theoretical dimension of Balanced Scorecard, the method has some deficiencies in terms of implementation on a quantitative basis and that there remain some problems to be resolved. Subject of this study covered the measurement and evaluation dimension of BSC. In the scope of the study, BSC approach was integrated with fuzzy ANP technique so as to determine the performance level of a business on the basis of its vision and strategies. Proposed model has shown that performance indicators with different structures included in BSC approach can be consolidated with the help of fuzzy ANP technique.

مقدمه انگلیسی

There are many strategic control techniques and methods aimed at evaluating – from a strategic management perspective – the results of the activities carried out by a business (Dinçer, 2004, Eren, 2002 and Ülgen and Mirze, 2004). One of the methods enabling periodical and systematic system controls is the Balanced Scorecard (BSC) system developed by Kaplan and Norton, 1992 and Kaplan and Norton, 1996a. Balanced Scorecard enables expression of the vision and strategies of a business in terms of performance indicators and thus ensures establishment of the framework required for strategic measurement and management system. While underlying that traditional financial indicators are important, BSC suggests that financial indicators prove to be insufficient in explaining the business performance when they only contain the information related with the incidents that have taken place in the past. In the light of this thought, Kaplan and Norton (1996b) proposed BSC system that enables integration of the measurements regarding the past business performance with the measurements regarding the elements that will bring future performances. Kaplan and Norton (1996a) presented four perspectives that need to be balanced in performance measurement: financial, customer, internal business process and learning and development perspectives. On the basis of this approach proposed by BSC, not only financial lagging indicators but also leading indicators such as customer, internal business process and learning and development perspectives are taken into consideration in strategic management process. Therefore, BSC acts as a strategic management system rather than an operational system that gives tactics only (Kaplan & Norton, 1996a). However, it is discussed that BSC approach has some deficiencies on a methodological basis (Abran and Buglione, 2003, Lee et al., 2008 and Leung et al., 2006). These deficiencies are in the method to be used in consolidating BSC perspectives or the performance indicators which act as different measurement units under each BSC perspective; the method to be adopted in determining the contribution to be made by each perspective on the performance (Abran and Buglione, 2003 and Lee et al., 2008); the relative weights or importance of the performance indicators under each perspective and; the method to be used in calculating the business performance with a holistic quantitative approach (Leung et al., 2006). There are some studies, though limited in number, that focused on such discussions related with the methodological aspect of BSC and tried to suggest possible answers for these discussions with the help of multi-criteria decision-making techniques (Lee et al., 2008, Leung et al., 2006, Ravi et al., 2005 and Sohn et al., 2003). Sohn et al. (2003) carried out a field study on 219 Korean businesses from different sectors and examined the relation between company strategies, environmental forces and BSC performance indicators. In the scope of the study; reactor, defender, analyzer and prospector business strategies (which are classified by Miles & Snow (1978)) and the environmental forces such as dynamism and hostility and heterogeneity were evaluated in terms of their effects on the weights of BSC indicators. Analytic Hierarchy Process (AHP) technique was applied to calculate the weights of 20 performance indicators belonging to four main perspectives of BSC. Ravi et al. (2005), on the other hand, examined the reverse logistics problem of computers by using analytic network process (ANP) technique and BSC approach. In the concerned study, a holistic model enabling selection of alternatives in reverse logistics operations was proposed. Explaining the reason why BSC prevails over other approaches as that BSC has an integrated structure enabling evaluation of the business performance on the basis of both financial and non-financial indicators, Lee et al. (2008) pointed out that conventional BSC fails to consolidate various performance indicators. They suggested fuzzy Analytic Hierarchy Process technique (a multiple-criteria evaluation technique) as a solution for this problem. They used fuzzy numbers in their study since many evaluation problems are fuzzy and vague by their nature and BAHP can eliminate such fuzziness and vagueness. The scope of their study was limited with the evaluation of the performances shown by information technology departments of Taiwan production industry. In the model proposed with BAHP technique, weights of the 14 performance indicators under the four main perspectives of BSC were calculated. Despite the high number of studies carried out on BSC framework, Leung et al. (2006) underlined in their study the lack of studies on how to correctly implement the BSC framework. In the light of this observation, they suggested a model aimed at facilitating the implementation of AHP technique, ANP technique (which is the successor of AHP) and BSC. In the proposed model, the relationships among BSC perspectives and the weights of each perspective were determined. An example was given in the study, which was related with rewarding manager performance. In the light of the studies carried out within the scope of BSC theoretical framework and the multiple-criteria evaluation techniques specified above; the main issue of our study was to enable determination of the business performance with a holistic approach and on the basis of the vision and strategies of the business and the perspectives and performance indicators of BSC. There are fundamental methodological and contextual differences between our study and the other studies in the literature. In the other studies in the literature (Lee et al., 2008 and Sohn et al., 2003); BSC perspectives and the weights of performance indicators were studied with AHP method according to orthogonality theory and with ANP method according to dependency theory (Leung et al., 2006 and Ravi et al., 2005). In AHP and ANP studies except for the study of Sohn et al. (2003), only the weights of BSC perspectives and performance indicators were calculated (Lee et al., 2008, Leung et al., 2006 and Ravi et al., 2005). In these studies, no relationship was established between BSC perspectives and performance indicators with the vision and strategies of the business on an analytical basis neither were the performance determined on the basis of such a relationship. Only the study carried out by Sohn et al. (2003) examined the effects of the strategies classified by Miles and Snow (1978) and of the environmental forces on performance indicators. The scope of the study of Sohn et al. (2003), on the other hand, did not cover evaluation of the business performance on the basis of the vision and strategies of the business. However, theoretical basis of BSC requires determination of performance indicators by taking into consideration the vision and strategies of the business (Kaplan & Norton, 1996b) as the vision has a leading function in the selection of business strategies and in the determination of business goals and objectives (Dinçer, 2004). The main contribution of our study has been the attempt to eliminate this deficiency in the related literature. This study proposed a systematic approach related with the evaluation of overall business performance on the basis of strategy-related BSC perspective and performance indicators. Thus, as suggested in the theoretical basis of BSC (Kaplan and Norton, 1992, Kaplan and Norton, 1996a and Kaplan and Norton, 1996b), early warning function that is related with the extent to which the business strategies are applied can be determined in terms of performance. In this study, AHP and ANP were used in developing analytical structure of BSC model, which are multiple-criteria decision-making methods. AHP is a multiple-criteria decision-making method developed by Saaty (1980). AHP is a method enabling evaluation of both qualitative and quantitative variables in evaluation problems together. ANP was also developed by Saaty (1996) to eliminate the deficiencies of AHP and to increase the functionality of the latter. The main reason behind the use of AHP and ANP in this study is that fundamental hypothesis and characteristics of these methods are in line with BSC structure. Fuzzy numbers were used since fuzzy set theory (Zadeh, 1965) is generally found to be better-suited to real life than the binary logic system. Binary logic – in other words classical logic, is based on certainty theory. However, real life is quite uncertain by its nature. The results obtained by evaluating a situation or a system related particularly with human factor and human thought from a certain and absolute perspective prove inadequate in reflecting the reality (Şen, 2001 and Şen, 2003).

نتیجه گیری انگلیسی

This study aimed to determine the performance level of a business on the basis of it is vision and strategies, by integrating BSC approach with fuzzy ANP technique. Proposed model has shown that different measurement units related with the performance indicators under BSC approach and performance indicators of different structures can be consolidated with fuzzy ANP technique. Besides, the proposed model has enabled determination of the business performance on the basis of its vision and the strategies pursued to achieve this vision. In this way, it is possible to evaluate from a strategic perspective the business performance according to not only past results but also leading indicators. The model proposed in the scope of this study was related with a production business; however, it can also be adapted to different businesses. Modifications may be required on the proposed system due to two reasons: firstly, the components constituting the analytical structure of the proposed model – namely, strategies, BSC perspectives and performance indicators – may vary depending on the business vision. Secondly, relationships or dependencies among BSC perspectives or performance indicators may also vary. Modifications and adaptations to be made due to these two reasons will enable the use of this model in other enterprises. In this study, only the interactions among BSC perspectives were considered and the business performance was determined on this basis. Future studies may expand the model by analyzing the inter-dependence of BSC perspectives and performance indicators under BSC perspectives.