ارزیابی عملکرد به کمک فرآیند تحلیل شبکه‌ای فازی(FANP) و کارت امتیازی متوازن(BSC) (مطالعه موردی: شرکت پتروشیمی اصفهان)
محورهای موضوعی :
مدیریت صنعتی
Ali Asghar Anvari Rostami
1
,
Mohammad Rasoul Heshmati
2
,
Maisam Shaverdi
3
,
Vahab Bashiri
4
1 - Professor of Department of Accounting, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran
2 - M.A Student in Business Management, Ferdowsi University of Mashhad, Mashahad, Iran
3 - M.A in Industrial Management, Member of Young Researchers Club, Ilam Branch, Islamic Azad University, Ilam, Iran
4 - M.A in Accounting, Imam khomeini international university, Qazvin, Iran.
تاریخ دریافت : 1396/10/20
تاریخ پذیرش : 1396/10/20
تاریخ انتشار : 1391/08/01
کلید واژه:
ارزیابی عملکرد,
Performance Evaluation,
مدیریت استراتژیک,
Balanced scorecard (BSC),
strategic management,
Analytic network process (ANP),
کارت امتیازی متوازن(BSC),
فرآیند تحلیل شبکه‌ای(ANP),
ارزیابی فازی,
Fuzzy evaluation,
چکیده مقاله :
کارت امتیازی متوازن(BSC) به عنوان یک ابزار ارزیابی استراتژیک، روشی جهت تعیین عملکرد تجاری با استفاده از شاخصهای پیشرو برپایه ی دورنما و استراتژی ها است. این موضوع در مرور ادبیات این مقاله اشاره شده است که با وجود اینکه ابعاد مفهومی و نظری کارت امتیازی متوازن به خوبی بررسی شده است اما این روش ناکارایی هایی در اجرای کمی داشته و برخی مسائل باید دوباره حل شوند. موضوع این مقاله، ابعاد سنجشی و ارزیابی کارت امتیازی متوازن را پوشش می‌دهد. در این پژوهش رویکرد کارت امتیازی متوازن با فرآیند تحلیل شبکه ای فازی(FANP) جهت سطح عملکرد تجاری شرکت پتروشیمی اصفهان برپایه ی دورنما و استراتژی آن ادغام شده است. علت ترکیب این دو مدل وجود رابطه متقابل بین شاخص های اثرگذار کارت امتیازی متوازن بر هم است که ANP فازی این مشکل را برطرف می کند. جهت طراحی مدل ابتدا لیستی از شاخصهای مرتبط با استفاده از مرور ادبیات موجود استخراج و سپس توسط کارشناسان شرکت پتروشیمی اصفهان بررسی و مدل نهایی پیشنهاد گردید. نتایج حاکی از آن است که شاخص مالی مهمترین شاخص در شرکت مزبور است. مدل پیشنهادی نشان داده که شاخص های عملکردی می تواند با ابعاد مختلف کارت امتیازی متوازن به کمک تکنیک ANP فازی ادغام شود.
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. It has been revealed in the review of relevant literature that despite the satisfying levels achieved in the 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. In the scope of the study, BSC approach was integrated with fuzzy ANP technique so as to determine the performance level of Isfahan Petrochemical Company on the basis of its vision and strategies. The reason for combining these methods is a reciprocal relation between effective indexes in BSC that fuzzy ANP solves this problem. For designing model, the first list of related indexes are extracted and then they are studied by experts of Isfahan Petrochemical Company and final model is designed. Proposed model has shown that performance indicators with different structures included in BSC approach can be consolidated with the help of fuzzy ANP technique
منابع و مأخذ:
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Cheng, C. H. (1997). Evaluating naval tactical missile systems by fuzzy AHP based on the grade value of membership function. European Journal of Operational 96: 343–350.
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Kahraman, C., Ertay, T., & Buyukozkan, G. (2006). A fuzzy optimization model for QFD planning process using analytic network approach. European Journal of Operational Research. 171: 390–411.
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Kaplan, R. S., & Norton, D. P. (1996). Balanced Scorecard Sirket Stratejisini Eyleme _Istanbul: Sistem Yayınları (Translation: Serra Egeli).
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Kaplan, R. S., & Norton, D. P. (1996). Using the balanced scorecard as a strategic management systems. Harvard Business Review. 74: 75–85.
Kocel, T. (2005). Is_letme Yoneticiligi. _Istanbul: Arıkan Yayınları.
Lee, A. H. I., Chen, W. C., & Chang, C. J. (2008). A fuzzy AHP and BSC approach for evaluating performance of IT department in the manufacturing industry in Expert Systems with Applications. 34: 96–107.
Leung, L. C., & Cao, D. (2000). On consistency and ranking of alternatives in fuzzy European Journal of Operational Research. 124: 102–113.
Leung, L. C., Lam, K. C., & Cao, D. (2006). Implementing the balanced scorecard using the analytic hierarchy process and the analytic network process. Journal of the Operational Research Society. 57: 682–691.
Meade, L. M., & Sarkis, J. (1999). Analyzing organizational project alternatives for agile manufacturing processes: An analytical network approach. International Journal of Production Research. 37: 241–261.
Mikhailov, L. (2004). A fuzzy approach to deriving priorities from interval pairwise comparison judgments. European Journal of Operational Research. 159: 687–704.
Miles, R. E., & Snow, C. C. (1978). Organizational strategy, structure and process. New York: McGraw-Hill. PP 87-88.
Ravi, V., Shankar, R., & Tiwari, M. K. (2005). Analyzing alternatives in reverse logistics for end-of-life computers: ANP and balanced scorecard approach. Computers and Industrial Engineering. 48: 327–356.
Saaty, T. L. (1980). The analytic hierarchy process. New York: McGraw-Hill. Pp 67.
Saaty, T. L. (1996). Decision making with dependence and feedback: The analytic network process. Pittsburgh: RWS Publications. pp 88-90.
Saaty, T. L., & Takizawa, M. (1986). Dependence and independence: From linear hierarchies to nonlinear networks. European Journal of Operational Research. 26: 229–237.
Seen, Z. (2001). Bulanık Mantık ve Modelleme Ilkeleri. Istanbul: Bilge Kultur Sanat Yayınları. Seen, Z. (2003). Modern Mantık. Istanbul: Bilge Kultur Sanat
Yayınları. Sohn, M. H., You, T., Lee, S-L., & Lee, H. (2003). Corporate strategies, environmental forces, and performance measures: A weighting decision support system using the k-nearest neighbor technique. Expert Systems with Applications. 25: 279–
Tolga, E., Demircan, M. L., & Kahraman, C. (2005). Operating system selection using fuzzy replacement analysis and analytic hierarchy process. International Journal of Production Economics. 97: 89–117.
Ulgen, H., & Mirze, S. K. (2004). Is letmelerde Stratejik Yonetim. Istanbul: Literatur Yayınları.
Van Laarhoven, P. J. M., & Pedrycz, W. (1983). A fuzzy extension of Saaty’s priority Fuzzy Sets and Systems. 11: 229–241.
Yuksel, I., & Dagdeviren, M. (2007). Using the analytic network process ANP in a SWOT analysis—A case study for a textile firm. Information Sciences. 177: 3364–3382.
Zadeh, L. A. (1965). Fuzzy sets. Information and Control. 8: 338–353.
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Abran, A., & Buglione, L. (2003). A multidimensional performance model for consolidating balanced scorecards. Advances in Engineering Software. 34: 339–349.
Bozdag, C. E., Kahraman, C., & Ruan, D. (2003). Fuzzy group decision making for selection among computer integrated manufacturing Systems. Computers in 51: 13–29.
Buckley, J. J. (1985). Fuzzy hierarchical analysis. Fuzzy Sets and Systems. 17: 233–247.
Chang, D. Y. (1992). Extent analysis and synthetic decision, optimization techniques and applications (Vol. 352). Singapore: World Scientific. Pp 17.
Cheng, C. H. (1997). Evaluating naval tactical missile systems by fuzzy AHP based on the grade value of membership function. European Journal of Operational 96: 343–350.
Deng, H. (1999). Multicriteria analysis with fuzzy pairwise comparison. International Journal of Approximate Reasoning. 21: 215–231.
Dincer, O. (2004). Stratejik Yonetim ve Is letme Politikası. Istanbul: Beta Yayınları.
Eren, E.( 2002). Stratejik Yonetim ve _Is_letme Politikası. _Istanbul: Beta Yayınları.
Kahraman, C., Ertay, T., & Buyukozkan, G. (2006). A fuzzy optimization model for QFD planning process using analytic network approach. European Journal of Operational Research. 171: 390–411.
Kahraman, C., Ruan, D., & Dog˘an, I. (2003). Fuzzy group decision-making for facility location selection. Information Sciences. 157: 135–153.
Kaplan, R. S., & Norton, D. P. (1996). Balanced Scorecard Sirket Stratejisini Eyleme _Istanbul: Sistem Yayınları (Translation: Serra Egeli).
Kaplan, R. S., & Norton, D. P. (1992). The balanced scorecard: Measures that drive Harvard Business Review. 70: 71–79.
Kaplan, R. S., & Norton, D. P. (1996). Using the balanced scorecard as a strategic management systems. Harvard Business Review. 74: 75–85.
Kocel, T. (2005). Is_letme Yoneticiligi. _Istanbul: Arıkan Yayınları.
Lee, A. H. I., Chen, W. C., & Chang, C. J. (2008). A fuzzy AHP and BSC approach for evaluating performance of IT department in the manufacturing industry in Expert Systems with Applications. 34: 96–107.
Leung, L. C., & Cao, D. (2000). On consistency and ranking of alternatives in fuzzy European Journal of Operational Research. 124: 102–113.
Leung, L. C., Lam, K. C., & Cao, D. (2006). Implementing the balanced scorecard using the analytic hierarchy process and the analytic network process. Journal of the Operational Research Society. 57: 682–691.
Meade, L. M., & Sarkis, J. (1999). Analyzing organizational project alternatives for agile manufacturing processes: An analytical network approach. International Journal of Production Research. 37: 241–261.
Mikhailov, L. (2004). A fuzzy approach to deriving priorities from interval pairwise comparison judgments. European Journal of Operational Research. 159: 687–704.
Miles, R. E., & Snow, C. C. (1978). Organizational strategy, structure and process. New York: McGraw-Hill. PP 87-88.
Ravi, V., Shankar, R., & Tiwari, M. K. (2005). Analyzing alternatives in reverse logistics for end-of-life computers: ANP and balanced scorecard approach. Computers and Industrial Engineering. 48: 327–356.
Saaty, T. L. (1980). The analytic hierarchy process. New York: McGraw-Hill. Pp 67.
Saaty, T. L. (1996). Decision making with dependence and feedback: The analytic network process. Pittsburgh: RWS Publications. pp 88-90.
Saaty, T. L., & Takizawa, M. (1986). Dependence and independence: From linear hierarchies to nonlinear networks. European Journal of Operational Research. 26: 229–237.
Seen, Z. (2001). Bulanık Mantık ve Modelleme Ilkeleri. Istanbul: Bilge Kultur Sanat Yayınları. Seen, Z. (2003). Modern Mantık. Istanbul: Bilge Kultur Sanat
Yayınları. Sohn, M. H., You, T., Lee, S-L., & Lee, H. (2003). Corporate strategies, environmental forces, and performance measures: A weighting decision support system using the k-nearest neighbor technique. Expert Systems with Applications. 25: 279–
Tolga, E., Demircan, M. L., & Kahraman, C. (2005). Operating system selection using fuzzy replacement analysis and analytic hierarchy process. International Journal of Production Economics. 97: 89–117.
Ulgen, H., & Mirze, S. K. (2004). Is letmelerde Stratejik Yonetim. Istanbul: Literatur Yayınları.
Van Laarhoven, P. J. M., & Pedrycz, W. (1983). A fuzzy extension of Saaty’s priority Fuzzy Sets and Systems. 11: 229–241.
Yuksel, I., & Dagdeviren, M. (2007). Using the analytic network process ANP in a SWOT analysis—A case study for a textile firm. Information Sciences. 177: 3364–3382.
Zadeh, L. A. (1965). Fuzzy sets. Information and Control. 8: 338–353.
