اولویتبندی معیارهای ارزیابی عملکرد پروژههای کلان مشارکتی مدیریت شهری با BSC و FANP
محورهای موضوعی :
مدیریت صنعتی
Mojtaba Salehi
1
,
Atena Mozaffari
2
1 - Assistant Professor of Industrial Engineering, Payame Noor University
2 - M.Sc. Industrial Engineering, Payame Noor University
تاریخ دریافت : 1395/03/09
تاریخ پذیرش : 1395/10/28
تاریخ انتشار : 1395/11/04
کلید واژه:
BSC,
ارزیابی عملکرد,
Performance Evaluation,
MCDM,
MADM,
Fuzzy ANP,
پروژههای مشارکتی,
FANP,
Participatory Projects,
چکیده مقاله :
مشارکت عمومی- خصوصی به معنی ارائه منابع مالی توسط بخش خصوصی برای کمک در انجام پروژههای زیربنایی دولت در مقیاس بزرگ میباشد. پروژههای مشارکتی مدیریت شهری که نیاز به سرمایهگذاری بالا داشته و از لحاظ تکنولوژی و طراحی از پیچیدگی ویژه‌ای برخوردار هستند، عموماً از نوع پروژههای مشارکتی کلان هستند که لذا ارزیابی عملکرد این نوع پروژهها با توجه به تاثیرگذاری منطقهایشان ضروری است. این پژوهش به شناسایی و اولویتبندی معیارهای ارزیابی عملکرد پروژههای مشارکتی مدیریت شهری و استفاده از این معیارها برای ایجاد یک رویکرد جامع ارزیابی عملکرد می پردازد. معیارهای ارزیابی عملکرد برای دو پروژه سرای محله و مجموعه فرهنگی- ورزشی، از پروژههای اصلی مدیریت شهری تهران بهکمک سه پرسشنامهای که دارای ضریب آلفای کرونباخ 97% بود شناسایی شد و سپس این معیارها با توجه به ابعاد کارت امتیازی شامل مالی، مشتریان، فرآیندهای داخلی و رشد و یادگیری گروهبندی شد. سپس با استفاده از فرآیند تحلیل شبکه فازی، ساختار شبکهای برای نمایش و محاسبه وزن ارتباط معیارها و زیرمعیارها طراحی شد و به کمک روشهای TOPSIS، VIKOR و SAW دو پروژه سرای محله و مجموعه فرهنگی- ورزشی ارزیابی و رتبه بندی شدند. در ابعاد مالی، مشتریان، فرآیندهای داخلی پروژه سرای محله نسبت به مجموعه فرهنگی- ورزشی عملکرد بهتری را نشان داد ولی در بعد رشد و یادگیری نتیجه برای دو پروژه تقریبا یکسان بود.
چکیده انگلیسی:
The public-private partnership means providing financial resources to the private sector to assist the government in carrying out large-scale infrastructure projects. Usually, participatory projects of urban management that need high investment and have a great complexity in terms of technology and design are considered as participatory macro projects. So the performance evaluation of this kind of projects according to their regional influence is necessary. This study identifies and ranks the performance evaluation criteria of participatory urban management projects to use these criteria for creating a comprehensive approach for performance evaluation. The performance evaluation criteria are obtained for two major projects of Tehran urban management namely neighborhood house and cultural-sports complex by questionnaire with Cronbach’s Alpha = 0.97% coefficient. Then, these criteria are grouped based on the aspects of the Balanced Scorecard including financial, clients, internal processes and learning and growth. Then, using the fuzzy analysis network process, the network structure was designed to display and measure the weight of relationships between criteria and sub-criteria. Finally, two projects are evaluated and ranked by TOPSIS and VIKOR and SAW methods. In the financial, clients, internal processes aspects, neighborhood house project showed a better performance than cultural-sport complex, but in the growth and learning aspect, the result for two projects was almost identical.
منابع و مأخذ:
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Chung, S.H., Lee, A.H.L., & Pearn, W.L. (2005). Analytic Network Process (ANP) Approach for Product Mix Planning in Semiconductor Fabricator. International Journal of Production Economics, 96(1), 15-36.
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Nilashi, M., Zakaria, R., Ibrahim, O., Abd. Majid, M.Z., Mohamad Zin, R., & Farahmand, M. (2015). MCPCM: A DEMATEL-ANP-Based Multi-criteria Decision-Making Approach to Evaluate the Critical Success Factors in Construction Projects. Arab J Sci Eng, vol(40), 343-361.
Opricovic, S., & Tzeng, G.H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, vol (156), 445–455
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Pilevari, N. (2015). Performance Evaluation of electronic banking by combining BSC and fuzzy network analysis (case study of Tehran Pasargad Bank). financial literacy of securities analysis Journal, 8 (28), 105-117.
Rabbani, A., Zamani, M., Yazdani-Chamzini, A., & Zavadskas, E. K. (2014). Proposing a new integrated model based on sustainability balanced scorecard (SBSC) and MCDM approaches by using linguistic variables for the performance evaluation of oil producing companies. Expert Systems with Applications, 41(16), 7316–7327.
Razmi, J. Mina, H., & Nasrollahi, M. (2014). Product performance evaluation based on the Balanced Scorecard with a new approach. Journal of Industrial Engineering, 48 (2), 177-188.
Saremi, M., Mousavi, S., & Sanayei, A. (2009). TQM consultant selection in SMEs with TOPSIS under fuzzy environment. Expert Systems with Applications, 36(2), 2742-2749.
Sepehrian, A., & Parhizkar, M.M. (2010). Performance evaluation of major projects with BSC, Sixth International Conference on Project Management, 1-11.
Tjader, Y., H. May, J., Shang, J., G. Vargas, L., & Gao, N. (2014). Firm-level outsourcing decision making: A balanced scorecard-based analytic network process model. Int. J. Production Economics, 147, 614–623.
Wu, H.Y., Lin, Y.K., & Chang, C.H. (2011). Performance evaluation of extension education centers in universities based on the balanced scorecard. Evaluation and Program Planning, vol (34), 37-50.
Yuan, J., Skibniewsk, M.J., Li, Q., & Zheng, L. (2010). Performance Objectives Selection Model in Public-Private Partnership Projects Based on the Perspective of Stakeholders. Journal Of Management In Engineering, 26(2), 89-104.
Yuksel, I., & Dagdeviren, M. (2010). Using the fuzzy analytic network process (ANP) for Balanced Scorecard (BSC): A case study for a manufacturing firm. Expert Systems with Applications, (37), 1270-1278.
Zebardast, E. (2010). Application of analytical network process in urban and regional planning. Fine Arts journal, 41, 79-90.
Zrghambroujeni H., Abrahimi, M., & Mirfakhredini F. S. (2013). Performance evaluation hotel services with fuzzy Balanced Scorecard approach. Journal of Tourism Management Studies, 8 (22), 25-50.
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Ansari, H., & Davari, K. (2009). Estimates of rainfall data with fuzzy technique. Iran Water Resources Research, 6 (1), 39-47.
Anvaryrostmi, A.A., Heshmati, M.R., Shaverdi, M., & Bashiri, W., (2012). Performance evaluation using fuzzy network analysis and process Balanced Scorecard (Case Study: Isfahan Petrochemical Company). Journal of Industrial Management, Faculty of Humanities, Islamic Azad University, Sanandaj, 7 (21), 9-22.
Ariyannejad M.G., & Safakish, M. S. (2008). Multi-criteria decision making. Boroujerd and Tousirkan: Islamic Azad University.
Chou, J.S., & Pramudawardhani, D. (2015). Cross-country comparisons of key drivers, critical success factors and risk allocation for public-private partnership projects. International Journal of Project Management, 1-15.
Chou, J. S., & Pramudawardhani, D. (2015). Cross-country comparisons of key drivers, critical success factors and risk allocation for public-private partnership projects. International Journal of Project Management, 33(5), 1136-1150.
Chung, S.H., Lee, A.H.L., & Pearn, W.L. (2005). Analytic Network Process (ANP) Approach for Product Mix Planning in Semiconductor Fabricator. International Journal of Production Economics, 96(1), 15-36.
Dorudian, H., Farahani, M.E., & Safahi, SH. (2007). A review of the project performance evaluation and introduction of evaluation methods in the end of project. Fourth International Conference on Project Management, 1-13.
Ghasemi, A.R. & Ahmadi, S.H. (2013). Evaluation of higher education institutions with Balanced Scorecard and multi-criteria decision-making methods. Journal of Medical Education, 6 (10), pp. 38-49.
Habibi A., Izyar, S., & Sarfarazi, A. (2014). Fuzzy multi-criteria decision-making. Tehran: Katibegil Publication
Ismail, S., & Harris, F. A. (2014). Challenges in implementing public private partnership (PPP) in Malaysia. Procedia -Social and Behavioral Sciences, 164, 5 – 10.
Malaki Vrke, Fatima. (2014). Extraction of infuntial key factors on project implementation of with public and private sectors partnership. Qazvin Islamic Azad University, A master's thesis of excutive management.
Mirfakhrodini, H., Tahari Mehrjardi, M.H. & Mirghafoori, H. (2012). Strategic assessment models using fuzzy techniques of network analysis process and fuzzy data envelopment analysis with the balanced scorecard approach. Management studies in Iran. 16 (2). 167-188.
Nilashi, M., Zakaria, R., Ibrahim, O., Abd. Majid, M.Z., Mohamad Zin, R., & Farahmand, M. (2015). MCPCM: A DEMATEL-ANP-Based Multi-criteria Decision-Making Approach to Evaluate the Critical Success Factors in Construction Projects. Arab J Sci Eng, vol(40), 343-361.
Opricovic, S., & Tzeng, G.H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, vol (156), 445–455
Özpeynirci, R., Yücenurşen, M., Apak, İ. & Polat, Y. (2015). A comparative analysis of accounting education’s effectiveness with the balanced scorecard method: Acase study of KMU. Procedia - Social and Behavioral Sciences 174, 1849-1858.
Pouriya, A.R., & Alizadeh Zvarm, A. (2014). Supplier selection problem using delphi hierarchical fuzzy-VIKOR hybrid model. Enterprise Resource Management Research, 4 (4), 23-48.
Pilevari, N. (2015). Performance Evaluation of electronic banking by combining BSC and fuzzy network analysis (case study of Tehran Pasargad Bank). financial literacy of securities analysis Journal, 8 (28), 105-117.
Rabbani, A., Zamani, M., Yazdani-Chamzini, A., & Zavadskas, E. K. (2014). Proposing a new integrated model based on sustainability balanced scorecard (SBSC) and MCDM approaches by using linguistic variables for the performance evaluation of oil producing companies. Expert Systems with Applications, 41(16), 7316–7327.
Razmi, J. Mina, H., & Nasrollahi, M. (2014). Product performance evaluation based on the Balanced Scorecard with a new approach. Journal of Industrial Engineering, 48 (2), 177-188.
Saremi, M., Mousavi, S., & Sanayei, A. (2009). TQM consultant selection in SMEs with TOPSIS under fuzzy environment. Expert Systems with Applications, 36(2), 2742-2749.
Sepehrian, A., & Parhizkar, M.M. (2010). Performance evaluation of major projects with BSC, Sixth International Conference on Project Management, 1-11.
Tjader, Y., H. May, J., Shang, J., G. Vargas, L., & Gao, N. (2014). Firm-level outsourcing decision making: A balanced scorecard-based analytic network process model. Int. J. Production Economics, 147, 614–623.
Wu, H.Y., Lin, Y.K., & Chang, C.H. (2011). Performance evaluation of extension education centers in universities based on the balanced scorecard. Evaluation and Program Planning, vol (34), 37-50.
Yuan, J., Skibniewsk, M.J., Li, Q., & Zheng, L. (2010). Performance Objectives Selection Model in Public-Private Partnership Projects Based on the Perspective of Stakeholders. Journal Of Management In Engineering, 26(2), 89-104.
Yuksel, I., & Dagdeviren, M. (2010). Using the fuzzy analytic network process (ANP) for Balanced Scorecard (BSC): A case study for a manufacturing firm. Expert Systems with Applications, (37), 1270-1278.
Zebardast, E. (2010). Application of analytical network process in urban and regional planning. Fine Arts journal, 41, 79-90.
Zrghambroujeni H., Abrahimi, M., & Mirfakhredini F. S. (2013). Performance evaluation hotel services with fuzzy Balanced Scorecard approach. Journal of Tourism Management Studies, 8 (22), 25-50.
