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Manuscript ID : 537167 Visit : 164 Page: 39 - 54

Article Type: Original Research

Using Delphi, AHP and TOPSIS Methods for Evaluating and Ranking Investment Projects in Multiple Portfolio

Subject Areas : Industrial Management

GhorbanAli Mohammadi 1 , Fereshteh Behbahani 2 , Soraya Esfandiyarpour 3

1 - Associate professor, Industrial Engineering Dept. Qom University of Technology, Qom, Iran
2 - Master of Art student of Industrial Engineering,system management and Efficiency, IslamicAzad University, Persian Golf International Branch, Khoramshahr,
3 - Lecturer, Ramhormoz Branch, Islamic Azad university, Ramhormoz, Iran

Received: 2015-12-08 Accepted : 2016-07-18 Published : 2016-08-25

Keywords:

Abstract :

Accepting a kind of suitable strategies for supply chain achievement is one of the requirements of a manufacturing company. Organizations to implement the different strategies of the supply chain are required to use information systems. In this regard, this research respecting the different strategies of the supply chain (lean and agile) and information systems strategies (efficiency and flexibility) attempt to examine the effect of these categories on supply chain performance and company. The methodology and the nature of this research is descriptive-survey. The sample population of this research is made up of nisoc’s managers and experts that are more than 2043 persons. By applying the Cochrane's formula, the sample population of this research determined as 231 persons that 222 questionnaires completed and received. In this research, content validity and structure validity have been used and total questionnaire Cronbach's alfa is equal to 0/955 which indicates the high level of reliability. Because of measuring the effect of some dependent and independent variables simultaneously, structure equations method (confirmation factor analysis) and Pierson coefficient test have been used. Results indicate, in term of the correlational coefficient, that the effect of all variables over supply chain performance of the company has been in a high level, but by applying the independent t correlational test and Pierson the main hypothesis and 3 sub-hypotheses confirmed. 

References:


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  2. Beamon, B. M., & ware, T.M. (1998). A process quality model for the analysis, improvement and control of supply chain systems. Logistics Information Management, 11(2), 105-113.
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    20.
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_||_

  1. Ahmadi, H. (2007). Supply Chain Management, Third Edition, Tehran, published by the Center for Education and Industrial Research of Iran.
    2.
  2. Beamon, B. M., & ware, T.M. (1998). A process quality model for the analysis, improvement and control of supply chain systems. Logistics Information Management, 11(2), 105-113.
    3.
  3. Esfandmaz, S., (2011). The application of information systems to improve supply chain integration with SCOR model approach (Case Study: Office of supplies and goods of NISOC in Ahvaz), dr. Mahmoud Alborzi, Islamic Azad University, Ahvaz Science and Research.
    4.
  4. Groznik, A, Trkman, P. (2006). A case study of supply chain management in oil industry. Information Technology Interfaces. 28th International Conference on p, 531 – 536.
    5.
  5. Gunasekaran, A., Lai, K., Cheng, E. (2008). Responsive supply chain: a competitive strategy in a networked economy. OMEGA 36(4), 549-564.
    6.
  6. Gunasekaran, A., Patel, C., & Tirtiroglu, E. (2001). Performance measures and metrics in a supply chain environment. International Journal of Operation and Production Managemen, 21(1/2), 71-87.
    7.
  7. Haji jabari, A, Sarabadani, M. (2007). A Practical Guide of Implementing Performance Evaluation organization, center of Iran Training and Industrial Research, Tehran.
    8.
  8. Jones, P., Clarke-Hill, C., Hillier, D. & Comfort, D, (2005). The benefits, challenges & impacts of radio frequency identification technology (RFID) for retailers in the UK. Marketing Intelligence & Planning, 23 (4), 395-402.
    9.
  9. Lee, H.L. (2002). Aligning supply chain strategies with product uncertainties. California Management Review 44 (3), 105-119.
    10.
  10. Li, S. ,Ragu-Nathan, B., Ragu Nathan, T.S. , & Rao, S. S. (2006). The impact of supply chain management  practices on competitive advantage and organizational  performance. The International Journal of Management Science, OMEGA 34(2), 107-124.
    11.
  11. Lin C., Chiu, H., Chu., P. (2006). Agility index in the supply chain. International Journal of Production Economics 100 (2), 285-299.  
    12.
  12. Lou P, Zhou Z, Chen Y.P, Ai W. (2004). Study on Multi-Agent-Base Agile Supply Chain Management, Int J Adv Manu Techno, 23,197–203.
    13.
  13. Morteza poor, A. (2001). Necessary information and information systems for offer supply chain management (offer Supply Chain Case Study Researches of Education), Master thesis, dr. Teymoori, University of Iran Science and Technology.
    14.
  14. Motallebi, M. (2002). designing a supply chain information system (case study of Pars Mehr kam company), master's thesis, dr.baradaran Kazem zadeh, Tarbiat Modarres university
    15.
  15. Qrunfleh, S., (2012). Supply chain information systems strategy: Impacts on supply chain performance and firm performance.    
    16.
  16. Rhman seresht, H, Afsar, A. (2008). The effect of information sharing on competitive strategies and supply chain performance, Journal of information Technology Management, period 1 (1), 37- 48.
    17.
  17. Sahraiyan, R. (2004). the effect of information systems on supply chain improvement, PhD thesis, dr. Chaharsoughi, Tarbiat Modarres University.
    18.
  18. sourveloudis N. C, Valavanis K, P,. (2002). On the Measurement of Enterprise Agility, Journal of Intelligent and Robotic Systems, 33: 329–342.
    19.
  19. Vonderembse, M.A., Uppal, M., Huang, S.H., Dismukes, J.P. (2006). Designing supply chain: towards theory development. International Journal of Production Economics 100(2), 223-238.
    20.
  20. Wang, G., Huang, S.H., Dismukes, J.P. (2004). Product-driven supply chain selection using integrated multi-criteria decision-making methodology. International Journal of Production Economics, 91 (1), 1-15.
    21.
  21. Wicker, L, Bernon, M, Templar, S and Mena. C. (2009). Understanding The relationships between time and cost to improve supply chain performance. International Journal production Economics, 12, 641 –650.
    22.

 

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