نوع مقاله : مقاله پژوهشی
نویسندگان
1 عضو هیات علمی دانشگاه علامه طباطبایی
2 دانشجوی دکتری مدیریت تولید و عملیات دانشگاه علامه طباطبایی
چکیده
برای ارزیابی عملکرد زنجیره تامین. وجود مدلی جامع در کنار دادههای قابل اعتماد، راه گشاست. این
امر به بهبود کل زنجیره کمک می کند. در این مقاله از مدلی متناسب با ماهیت شبکهای و چند مرحلهای
زنجیره تامین استفاده شده که عملکرد کل زنجیره را در قالب یک مدل ریاضی و با استفاده از شاخصهای
مالی، دانشی، مشارکت و پاسخگویی زنجیره تامین، ارزیابی می کند. در بخش اول، شاخصها در سه سطح
استراتژیک، فرایندی و عملیاتی درنظر گرفته شده و با تحلیل عاملی، تائید آن بررسی میگردد. در بخش
دوم از مدل تحلیل پوششی دادههای شبکهای استفاده میشود. این مقاله حاصل تحقیقی مرتبط با
زنجیره های تامین شرکتهای داروسازی پذیرفته شده در بورس اوراق بهادار تهران است و 111 نفر از
کارشناسان و مدیران ارشد به عنوان نمونه مورد سوال قرار گرفته اند. نتایج اجرای تحقیق نشان میدهد که
0 مهم ترین سطح عملکردی است و سطح فرآیندی و عملیاتی به ترتیب دارای / سطح استراتژیک با وزن 89
0 می باشند. همچنین تعداد 4 زنجیره از 89 زنجیره مورد مطالعه دارای عملکرد یک بوده و / 0 و 99 / وزن 89
0 است. / کمترین میزان عملکرد مشاهده شده 44
کلیدواژهها
عنوان مقاله [English]
A model for supply chain performance evaluation using by network data envelopment analysis model (Case of: Supply chain of pharmaceutical companies in Tehran Stock Exchange
نویسندگان [English]
- Laya Olfa 1
- ahanyar BamdadSoofu 1
- Maghsoud Amir 1
- Mostafa Ebrahimpoor Azbari 2
1
2
چکیده [English]
For performance evaluation of supply chain, having a comprehensive
model with reliable data is useful. This can help to improve the entire
chain. In this paper a model is presented, according to the nature of
network and multi-stage supply chain, that able to evaluate the
performance of the entire chain in the form of a mathematical mode
land using the financial, knowledge, participation and response
measures of the supply chain. In the first part, Indicator sat three
levels; strategic, process and operational, considered and survey the
model verification with Factor Analysis. In the second part, Network
data envelopment analysis model is used. This paper is the result of
research related to supply chain of pharmaceutical companies in
Tehran Stock Exchange and 115 expert sand senior executive shave
been questioned as sample. There search results show that strategic
level with a weight of 0.98 is the most important performance level
and Process and operational levels are respectively 0.97 and 0.87
weight. 4chainsof 28 chains studied, have a complete performance and
0.43 is the lowest observed performance.
کلیدواژهها [English]
- supply chain Performance evaluation
- Performance indicators
- factor analysis
- Network data envelopment analysis
.) مدل های سنجش، انتشارات مرکز آموزش و تحقیقات صنعتی ایران، ) 5088
2. محمدی رنجبرانی، داریوش، مدرس یزدی، محمد، رویکرد مصداقی سنجش عملکرد زنجیره
عرضه همراه با مطالعه موردی در صنعت خودرو، فصلنامه دانش مدیریت، سال 51 ، شماره
.)5081( ،537- 21 ، زمستان 81 ، ص 21
3. Bhagwat, Rajat., Sharma, Milind Kumar, Performance measurement of
supply chain management :A balanced scorecard approach, Computers &
Industrial Engineering53,43-62, (2007).
4. Bontis, N. (2002), The rising star of the chief knowledge officer, Ivey
Business Journal, Vol. 66, No. 4, pp. 20-5.
5. Bowersox D J, Closs D J, Cooper M B, supply chain logistics
management, McGraw-Hill, pp124-154, (2002),
6. Cao, Mei., Zhang, Qingyu., Supply chain collaboration: Impact on
collaborative advantage and firm performance, Journal of Operations
Management 29, 163–180 (2011).
7. Charnes A, Cooper WW, Rhodes E., Measuring the efficiency of decision
making units, European Journal of Operational Research; 2:429–440,
(1978).
8. Chen, C, Yan, H, Network DEA model for supply chain performance
evaluation, European Journal of Operational Research, Article in press,
(2011).
9. Chopra, S, Meindl, P., Supply Chain Management, Pearson Education,
(2007).
10. Cook, Wade D., Zhu, Joe., Bi ,Gongbing., Yang, Feng., Network DEA:
Additive efficiency decomposition, European Journal of Operational
Research 207, 1122–1129, (2010).
11. Cooper, M., Lambert, D., Pagh, J., Supply chain management: more
than a new name for logistics. The International Journal of Logistics
Management, 8 (1), 1–14, (1997).
12. ECR, 2010, http://www.ecrnet.org.
13. Estampe, Dominique, Lamouri, Samir, Paris, Jean-Luc, Brahim-Djelloul,
Sakina, A framework for analysing supply chain performance
evaluation models Production Economics, (2011).
14. Fare, R., Grosskopf, S., Network DEA, Socio-Economic Planning
Sciences 34, 35–49, (2000).
مدلی جهت ارزیابی عملکرد زنجیره تامین با... 25
15. Folan. P, Browne. J., The Development of an Extended Enterprise
Performance Measurement System, Production Planning and Control,
(2005).
16. Gunasekaran, A., Patel, C., McGaughey, R.E., A framework for supply
chain performance measurement, International Journal of Production
Economics 87 (3), 333–347, (2004).
17. Gowen, Charles R. Tallon, and William J., "Enhancing supply chain
practices through human resource management", Journal of
Management Development, Vol. 22 No. 1, pp. 32-44, (2003).
18. Holweg, M, The three dimensions of responsiveness, International
Journal of Operations & Production Management, 25, 603–622, (2005).
19. Kao, C., Hwang, S.N., Efficiency decomposition in two-tage data
envelopment analysis: An application to non-life insurance companies in
Taiwan. European Journal of Operational Research 185 (1), 418–429,
(2008).
20. Kuwaiti, M, Performance measurement process: definition and
ownership, International Journal of Operations & Production Management
Vol.24 No. 1, pp.121-139, (2004).
21. Lan, Y, C,. Unhelkar, B, Global integrated supply chain systems,
Published in the United States of America by Idea Group Publishing,
p.272, (2006).
22. Liang, L., Cook, W.D., Zhu, J, DEA models for two-stage processes:
Game approach and efficiency decomposition, Naval Research Logistics
55, 643–653, (2008).
23. Lin, Li-Hung., Hsieh, Ling-Feng, A performance evaluation model for
international tourist hotels in Taiwan -An application of the relational
network DEA, International Journal of Hospitality Management 29,p.14-
24, (2010).
24. Luo, X., Wu, C., Rosenberg, D., & Barnes, D., Supplier selection in agile
supply chains: An information-processing model and an illustration,
Journal of Purchasing & Supply Management, 15, 249- 262, (2008).
25. Lynch, R.L., Cross, K.F., Measure Up-The Essential Guide to measuring
Business performance, Mandarin, london, (1991).
26. Morgan, Chris, "Supply network performance measurement: future
challenges?" The International Journal of Logistics Management. Vol. 18
No. 2, pp. 255-273, (2007).
27. Neely, A., Gregory, M. and Platts, K, Performance measurement system
design, International Journal of Operations and Production
Management, Vol. 25 No 12, pp. 1228-1263, (2005).
28. Pinches, G. & others, "The Hierarchical of Financial Ratios", Journal of
Business, Oct 1975.
22 مطالعات مدیریت صنعتی، سال دهم، شماره 22 ، پاییز 19
29. Sheu, C., Yen, H.R., Chae, D., Determinants of supplier-retailer
collaboration: evidence from an international study, International
Journal of Operations and Production Management 26 (1), 24–49, (2006).
30. SCOR 2010, http://www.supply-chain.org.
31. Seetharaman, A., Sooria, H, H, B, Z. and Saravanan, A, S., Intellectual
capital accounting and reporting in knowledge economy, Journal of
Intellectual capital, vol.3, No.2, pp. 128-148, (2002).
32. Sullivan J, P, H. and Sullivan S, P, H, Valuing intangible companies: an
intellectual capital approach, Journal of Intellectual capital, vol.1, No.4,
pp.328-340, (2000).
33. Sveiby, K.E, Methods for Measuring Intangible Assets, Available at:
http://www.sveiby.com/articles/, (2005).
34. Tai, Wei-Shen , Chen, Chen-Tung, A new evaluation model for
intellectual capital based on computing with linguistic variable, Expert
Systems with Applications 36, 3483–3488, (2009).
35. You, F., Grossmann, I. E, Optimal design and operational planning of
responsive process supply chains, Process system engineering: Vol., pp.
107–134, (2007).
36. Xu, Jiuping, Li, Bin, Wu, Rough data envelopment analysis and its
application to supply chain performance evaluation, Production
Economics 122, p.628–638, (2009).