ارزیابی تولید چابک در گروههای مختلف صنایع کوچک و متوسط استان آذربایجان شرقی بر اساس قابلیتهای چابکی به روش TOPSIS فازی
محورهای موضوعی : مدیریت بازرگانی
سلیمان ایرانزاده
1
(عضوهیأت علمی(دانشیار) گروه مدیریت صنعتی ، واحدتبریز،دانشگاه آزاداسلامی،تبریز،ایران)
وحید فتاحی سرند
2
(عضو هیأت علمی(مربی) گروه مدیریت ،واحد شبستر،دانشگاه آزاد اسلامی،شبستر،ایران)
عبدالوحید طاحونی
3
(دانش آموخته کارشناسی ارشد گروه مدیریت، واحدتبریز،دانشگاه آزاداسلامی،تبریز،ایران)
کلید واژه: انعطاف پذیری, پاسخگویی, شایستگی, سرعت, تولید چابک, TOPSIS فازی,
چکیده مقاله :
عصر جدید اقتصاد جهانی با سرعتی بالا سبب شده تا راهبردهای عملیاتی شرکت تغییر کند. در این عصر، قیمت رقابتی و کیفیت بالا ضروری، اما عامل تعیین کننده موفقیت تجاری نسیتند، بلکه سرعت رسیدن به بازار و پاسخ سریع و منعطف به مشتری به عنوان یک اصل اساسی مورد توجه قرار گرفته است. به همین دلیل اهمیت سرعت و چابکی افزایش یافته و جانشین اولویت های رقابتی سابق شده است؛ بر همین اساس نیز هدف این مقاله ارزیابی تولید چابک در گروه های مختلف صنایع کوچک و متوسط استان آذربایجان شرقی بر اساس قابلیت های چابکی می باشد. جامعه آماری این تحقیق را کلیه شرکتهای صنایع کوچک و متوسط استان آذربایجان شرقی تشکیل می دهد. نمونه آماری با استفاده از رابطه تعیین حجم نمونه در جامعه های محدود، 610 شرکت تعیین شده است. به منظور جمع آوری داده ها در این تحقیق پرسشنامه محقق ساخته به کار رفته است که بعد از آزمون روایی و پایایی در بین جامعه آماری توزیع شده است. به منظور تجزیه و تحلیل داده ها در این تحقیق روش TOPSIS فازی به کار رفته است. نتایج تحقیق نشان می دهد که اکثر گروه های صنایع کوچک و متوسط بر اساس قابلیت های چابکی فاصله قابل توجهی با تولید چابک دارند.
The new era of high-speed global economy has caused companies to change operational strategies. In this era, competitive prices and high quality are essential, but not the determinant factors of commercial success; rather, the speed and flexibility to respond quickly to market and customer is regarded as a fundamental principle. Thus, the importance of speed and agility has increased and replaced previous competitive priorities; therefore, this paper evaluates agile manufacturing in small and medium industries of East Azarbaijan Province based on agility capabilities. The population of the study consists of all small and medium-sized firms of East Azarbaijan province. The sample was set 610 companies using the equation of determining the sample size of limited socities. In order to collect data in this study, a researcher made questionnaire was used, which was distributed among the subjects after testing its validity and reliability. In order to analyze the data in the study, fuzzy TOPSIS method was used. The results showed that most groups of small and medium industries based on the agile manufacturing capabilities have a considerable distance from agile manufacturing.
Abo-Sinna, M. A., & A. H. Amer (2005), Extensions of TOPSIS for multiobjective large-scale nonlinear programming problems, Applied Mathematics and Computation, No.162, pp.243–256
Agarwal, A., Shankar R. & Tiwari M.K. (2007), Modeling agility of supply chain, Industrial Marketing Management, Vol.36 Iss. 4, pp.443-457
Agrawal, V. P., V. Kohli & S. Gupta (1991), Computer aided robot selection: The multiple attribute decision making approach, International Journal of Production Research,No.29, pp.1629–1644
Arteta, B.M. & Giachetti, R.E. (2004), A measure of agility as the complexity of the enterprise system, Robotics and Computer-Integrated Manufacturing, Vol. 47, pp. 495-503
Baker, P.(2008), The design and operation of distribution centres within agile supply chains, International Journal of Production Economics, Vol. 111 Iss. 1, pp. 27-41
Bellman, R. E., & Zadeh, L. A. (1970), Decision-making in a fuzzy environment management. Science, Vol.17 No.4,pp.141-164
Brown, S. & Bessant, J. (2003), The manufacturing strategy-capabilities links in mass customization and agile manufacturing: an exploratory study, International Journal of Operations & Production Management, Vol. 23 No. 7, pp. 707-730
Burgess, T.F.(1994), Making the lean to agility: defining and achieving agile manufacturing through business process redesign and business network redesign, International Journal of Operrations & Prodaction Management, Vol. 14 No. 11, pp. 23-34
Charles, A., Lauras, M. & Van Wassenhove, L.(2010), A model to define and assess the agility of supply chains: building on humanitarian experience, International Journal of Physical Distribution & Logistics Management, Vol. 40 Iss. 8, pp. 675– 692
Chen, C. T. (2000), Extensions of the TOPSIS for group decision making under fuzzy environment, Fuzzy Sets and Systems, No.114, pp.1–9
Cheng, S., C.W. Chan & G. H. Huang (2003), An integrated multi-criteria decision analysis and inexact mixed integer linear programming approach for solid waste management, Engineering Applications of Artificial Intelligence, No.16, pp.543–554
Erande, A.S. & Verma, A.K. (2008), Measuring agility of organizations-a comprehensive agility measurement tool (CAMT), Proceedings of the 2008 IAJC-IJME International Conference. ISBN 978-1-60643-379-9
Gumus, A.T. (2009), Evaluation of hazardous waste transportation firms by using a two step fuzzy-AHP and TOPSIS methodology, Expert Systems with Applications, No.36, pp. 4067–4074
Gunasekaran, A., Mcgaughey, R. and Wolstencroft, V.(2001), Agile Manufacturing: The 21st Century Competitive Strategy, Elsevier, pp.25-49
Hormozi, A.M. (2001), Agile manufacturing: the next logical Step, Benchmarking: an International Gournal, Vol. 8 Iss.2, pp.132-143
Hwang, C. L., & K. Yoon (1981), Multiple attribute decision making: Methods and applications, Berlin: Springer
Jahanshahloo, G. R., F. H. Lotfi & M. Izadikhah (2006), Extension of the TOPSIS method for decision-making problems with fuzzy data, Applied Mathematics and Computation, Vol.18 No.2, pp.1544–1551
Jee, D. H., & K. J. Kang (2000), A method for optimal material selection aided with decision making theory, Materials and Design, No.21, pp.199–206
Karuppusiam, G., Balaji, M., Sudhakaran, R. & Ashwini, A.C. (2011), “TADS” approach in supply chain agility, International Journal of Current Science Research, Vol. 1, pp. 213-216
Kidd, P. (2000), two definitions of agility, available at: www.CheshireHenbury.com
Kumar .A; Motwani, J, Deependra, M. & Ganesh, J. (1995), A methodology for assessing time based competitive advantage of manufacturing firms, International Journal of Operations &Production Management, Vol. 15 Iss.2, pp. 36-53
Liao, H. C. (2003), Using PCR-TOPSIS to optimize Taguchi’s multi-response problem, The International Journal of Advanced Manufacturing Technology, No.22, pp.649–655
McGaughey, R. (1999), Internet Technology: Contributing to Agility in the Twenty-firse Century, International Journal of Agile Manufacturing system, pp. 7-13
Narasimhan, R., Swink, M. & Soo Wook, k.(2006), Disentangling leanness and agility: An empirical investigation, Journal of Operation Management, No. 24, pp. 440-457
Olson, D. L. (2004), Comparison of weights in TOPSIS models, Mathematical and Computer Modelling, No.40, pp.721–727
Opricovic, S. & G. H. Tzeng (2004), Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS, European Journal of Operational Research, No.156, pp.445–455
Percin, S.( 2008). Fuzzy multi-criteria risk-benefit analysis of business process outsourcing (BPO). Information Management & Computer Security, Vol.3, pp. 213-234
Poolton, J., Ismail, H.S., Reid, I.R. & Arokiam, C.(2006), Agile marketing for the manufacturing-based SME, Marketing Intelligence & Planning, Vol.24 No.7, pp.681-693
Sanchez, L.M. & Nagi, R. (2001), A review of agile manufacturing systems, International Journal of Production Research, Vol. 39 No. 16, pp. 3561-600
Shahi, B., & Rajabzadeh, A. (2005). Investigating Dimensions of Organizational Agility Assessment in Government Organizations with the Information Technology Approach. Second International Conference on Information and Communication Technologies Management, (In Persian).
Sharifi, H. & Zhang, Z. (1999), A methodology for achieving agility in manufacturing organization, International Journal of Production Economics, Vol. 62, pp. 7-22
Shih, H.-S., H.J. Shyur & L. E. Stanley (2007), An extension of TOPSIS for group decision making, Mathematical and Computer Modelling, Vol.45 No.7–8, pp.801–813
Vazquez-Bustelo, D., Avella, L. & Fernandez, E. (2007), Agility drivers, enablers and outcomes: Empirical test of an integrated agile manufacturing model, International Journal of Operations & Production Management, Vol. 27 No. 12, pp. 1303-1332
Vinodh, S., Devadasan, S.R., Vasudeva, R.B. & Ravichand, K.(2010), Agility index measurement using multi-grade fuzzy approach integrated in a 20 criteria agile model, International Journal of Production Research, Vol. 48 Iss.23, pp. 7159-7176
Vinodh, S., Prakash, N.H. & Selvan, K.E. (2011), Evaluation of agility in supply chains using fuzzy association rules mining. International Journal of Production Research, Vol. 1, Iss.11
Vinodh, S., Sundararaj, G., Devadasan, S.R., Maharaja, R., Rajanayagam, D. & Goyal, S.K. (2008), DESSAC: a decision support system for quantifying and analysing agility, International Journal of Production Research, Vol. 46 Iss.23, pp. 6759-6780
Vokurka, R. & Fliedner, G. (1998), The journey toward agility, Industrial Management & Data Systems, Vol. 98 No.4, pp.165-171
Wang, M. J. J., & T. C. Chang (1995), Tool steel materials selection under fuzzy environment, Fuzzy Sets and Systems, No.72, pp.263–270
Wang, Y.M. & T.M. Elhag(2006), Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment, Expert Systems with Applications, No. 31, pp.309–319
Wang,T.C & T.H,Chang(2007), Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment, Expert Systems with Applications, No. 33,pp870–880
White A, Daniel E.M. & Mohdzain, M. (2005), The role of emergent information technologies and systems in enabling supply chain agility, International Journal of Information Management, Vol. 25 Iss. 5, pp. 396 410
Yang, S.L. & Li, T.F. (2002), Agility evaluation of mass customization product manufacturing. Journal of Materials Processing Technology, Vol. 129, Iss.1-3, pp. 640-644
Yusuf, Y.Y. & Adeleye, E.O. (2002), A comparative study of lean and agile manufacturing with a related survey of current practices in UK, International Journal of Production Research, Vol. 40 No. 17, pp. 4545-62
Yusuf, Y.Y., Sarhadi, M. & Gunasekaran, A. (1999), Agile manufacturing: the drivers, concepts and attributes, International Journal of Production Economics, Vol. 62 Iss, 1/2, pp. 33-43
Zain, M., Rose, R.C, Abdullah, I. & Masrom, M. (2005), The relationship between information technology acceptance and organizational agility in Malysia, Information & Management, Vol. 42 Iss. 6, pp. 829–839
Zelbst, P.J., Green, K.W., Abshire, R.D. & Sower, V.E. (2010), Relationships among market orientation, JIT, TQM, and agility, Industrial Management & Data Systems,Vol.110 Iss.5,pp.637- 658
Zhang, Z. & Sharifi, H. (2000), A methodology for achieving agility in manufacturing organizations, International Journal of Operations & Production Management, Vol. 20 Iss. 4, pp. 496-512
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Abo-Sinna, M. A., & A. H. Amer (2005), Extensions of TOPSIS for multiobjective large-scale nonlinear programming problems, Applied Mathematics and Computation, No.162, pp.243–256
Agarwal, A., Shankar R. & Tiwari M.K. (2007), Modeling agility of supply chain, Industrial Marketing Management, Vol.36 Iss. 4, pp.443-457
Agrawal, V. P., V. Kohli & S. Gupta (1991), Computer aided robot selection: The multiple attribute decision making approach, International Journal of Production Research,No.29, pp.1629–1644
Arteta, B.M. & Giachetti, R.E. (2004), A measure of agility as the complexity of the enterprise system, Robotics and Computer-Integrated Manufacturing, Vol. 47, pp. 495-503
Baker, P.(2008), The design and operation of distribution centres within agile supply chains, International Journal of Production Economics, Vol. 111 Iss. 1, pp. 27-41
Bellman, R. E., & Zadeh, L. A. (1970), Decision-making in a fuzzy environment management. Science, Vol.17 No.4,pp.141-164
Brown, S. & Bessant, J. (2003), The manufacturing strategy-capabilities links in mass customization and agile manufacturing: an exploratory study, International Journal of Operations & Production Management, Vol. 23 No. 7, pp. 707-730
Burgess, T.F.(1994), Making the lean to agility: defining and achieving agile manufacturing through business process redesign and business network redesign, International Journal of Operrations & Prodaction Management, Vol. 14 No. 11, pp. 23-34
Charles, A., Lauras, M. & Van Wassenhove, L.(2010), A model to define and assess the agility of supply chains: building on humanitarian experience, International Journal of Physical Distribution & Logistics Management, Vol. 40 Iss. 8, pp. 675– 692
Chen, C. T. (2000), Extensions of the TOPSIS for group decision making under fuzzy environment, Fuzzy Sets and Systems, No.114, pp.1–9
Cheng, S., C.W. Chan & G. H. Huang (2003), An integrated multi-criteria decision analysis and inexact mixed integer linear programming approach for solid waste management, Engineering Applications of Artificial Intelligence, No.16, pp.543–554
Erande, A.S. & Verma, A.K. (2008), Measuring agility of organizations-a comprehensive agility measurement tool (CAMT), Proceedings of the 2008 IAJC-IJME International Conference. ISBN 978-1-60643-379-9
Gumus, A.T. (2009), Evaluation of hazardous waste transportation firms by using a two step fuzzy-AHP and TOPSIS methodology, Expert Systems with Applications, No.36, pp. 4067–4074
Gunasekaran, A., Mcgaughey, R. and Wolstencroft, V.(2001), Agile Manufacturing: The 21st Century Competitive Strategy, Elsevier, pp.25-49
Hormozi, A.M. (2001), Agile manufacturing: the next logical Step, Benchmarking: an International Gournal, Vol. 8 Iss.2, pp.132-143
Hwang, C. L., & K. Yoon (1981), Multiple attribute decision making: Methods and applications, Berlin: Springer
Jahanshahloo, G. R., F. H. Lotfi & M. Izadikhah (2006), Extension of the TOPSIS method for decision-making problems with fuzzy data, Applied Mathematics and Computation, Vol.18 No.2, pp.1544–1551
Jee, D. H., & K. J. Kang (2000), A method for optimal material selection aided with decision making theory, Materials and Design, No.21, pp.199–206
Karuppusiam, G., Balaji, M., Sudhakaran, R. & Ashwini, A.C. (2011), “TADS” approach in supply chain agility, International Journal of Current Science Research, Vol. 1, pp. 213-216
Kidd, P. (2000), two definitions of agility, available at: www.CheshireHenbury.com
Kumar .A; Motwani, J, Deependra, M. & Ganesh, J. (1995), A methodology for assessing time based competitive advantage of manufacturing firms, International Journal of Operations &Production Management, Vol. 15 Iss.2, pp. 36-53
Liao, H. C. (2003), Using PCR-TOPSIS to optimize Taguchi’s multi-response problem, The International Journal of Advanced Manufacturing Technology, No.22, pp.649–655
McGaughey, R. (1999), Internet Technology: Contributing to Agility in the Twenty-firse Century, International Journal of Agile Manufacturing system, pp. 7-13
Narasimhan, R., Swink, M. & Soo Wook, k.(2006), Disentangling leanness and agility: An empirical investigation, Journal of Operation Management, No. 24, pp. 440-457
Olson, D. L. (2004), Comparison of weights in TOPSIS models, Mathematical and Computer Modelling, No.40, pp.721–727
Opricovic, S. & G. H. Tzeng (2004), Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS, European Journal of Operational Research, No.156, pp.445–455
Percin, S.( 2008). Fuzzy multi-criteria risk-benefit analysis of business process outsourcing (BPO). Information Management & Computer Security, Vol.3, pp. 213-234
Poolton, J., Ismail, H.S., Reid, I.R. & Arokiam, C.(2006), Agile marketing for the manufacturing-based SME, Marketing Intelligence & Planning, Vol.24 No.7, pp.681-693
Sanchez, L.M. & Nagi, R. (2001), A review of agile manufacturing systems, International Journal of Production Research, Vol. 39 No. 16, pp. 3561-600
Shahi, B., & Rajabzadeh, A. (2005). Investigating Dimensions of Organizational Agility Assessment in Government Organizations with the Information Technology Approach. Second International Conference on Information and Communication Technologies Management, (In Persian).
Sharifi, H. & Zhang, Z. (1999), A methodology for achieving agility in manufacturing organization, International Journal of Production Economics, Vol. 62, pp. 7-22
Shih, H.-S., H.J. Shyur & L. E. Stanley (2007), An extension of TOPSIS for group decision making, Mathematical and Computer Modelling, Vol.45 No.7–8, pp.801–813
Vazquez-Bustelo, D., Avella, L. & Fernandez, E. (2007), Agility drivers, enablers and outcomes: Empirical test of an integrated agile manufacturing model, International Journal of Operations & Production Management, Vol. 27 No. 12, pp. 1303-1332
Vinodh, S., Devadasan, S.R., Vasudeva, R.B. & Ravichand, K.(2010), Agility index measurement using multi-grade fuzzy approach integrated in a 20 criteria agile model, International Journal of Production Research, Vol. 48 Iss.23, pp. 7159-7176
Vinodh, S., Prakash, N.H. & Selvan, K.E. (2011), Evaluation of agility in supply chains using fuzzy association rules mining. International Journal of Production Research, Vol. 1, Iss.11
Vinodh, S., Sundararaj, G., Devadasan, S.R., Maharaja, R., Rajanayagam, D. & Goyal, S.K. (2008), DESSAC: a decision support system for quantifying and analysing agility, International Journal of Production Research, Vol. 46 Iss.23, pp. 6759-6780
Vokurka, R. & Fliedner, G. (1998), The journey toward agility, Industrial Management & Data Systems, Vol. 98 No.4, pp.165-171
Wang, M. J. J., & T. C. Chang (1995), Tool steel materials selection under fuzzy environment, Fuzzy Sets and Systems, No.72, pp.263–270
Wang, Y.M. & T.M. Elhag(2006), Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment, Expert Systems with Applications, No. 31, pp.309–319
Wang,T.C & T.H,Chang(2007), Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment, Expert Systems with Applications, No. 33,pp870–880
White A, Daniel E.M. & Mohdzain, M. (2005), The role of emergent information technologies and systems in enabling supply chain agility, International Journal of Information Management, Vol. 25 Iss. 5, pp. 396 410
Yang, S.L. & Li, T.F. (2002), Agility evaluation of mass customization product manufacturing. Journal of Materials Processing Technology, Vol. 129, Iss.1-3, pp. 640-644
Yusuf, Y.Y. & Adeleye, E.O. (2002), A comparative study of lean and agile manufacturing with a related survey of current practices in UK, International Journal of Production Research, Vol. 40 No. 17, pp. 4545-62
Yusuf, Y.Y., Sarhadi, M. & Gunasekaran, A. (1999), Agile manufacturing: the drivers, concepts and attributes, International Journal of Production Economics, Vol. 62 Iss, 1/2, pp. 33-43
Zain, M., Rose, R.C, Abdullah, I. & Masrom, M. (2005), The relationship between information technology acceptance and organizational agility in Malysia, Information & Management, Vol. 42 Iss. 6, pp. 829–839
Zelbst, P.J., Green, K.W., Abshire, R.D. & Sower, V.E. (2010), Relationships among market orientation, JIT, TQM, and agility, Industrial Management & Data Systems,Vol.110 Iss.5,pp.637- 658
Zhang, Z. & Sharifi, H. (2000), A methodology for achieving agility in manufacturing organizations, International Journal of Operations & Production Management, Vol. 20 Iss. 4, pp. 496-512
