Evaluation Criteria for Selecting Suppliers in the Field of Research With Fuzzy Multi-Criteria Approach
محورهای موضوعی : Business StrategyHamidreza Feili 1 , Sina Namazi 2 , Jamshid Karimi 3 , Mohammad-Javad Sadeghi 4
1 - Department of Industrial Engineering, College of Engineering,
Karaj Branch, Islamic Azad University, Karaj, Iran
2 - Department of Industrial Engineering, College of Engineering,
Karaj Branch, Islamic Azad University, Karaj, Iran
3 - Department of Industrial engineering, College of Engineering,
Karaj Branch, Islamic Azad University, Karaj, Iran
4 - Department of Industrial Engineering, College of Engineering,
Karaj Branch, Islamic Azad University, Karaj, Iran
کلید واژه: TOPSIS, Multi-Criteria Decision-Making, fuzzy numbers, Keywords: Selecting of the Provider, Researches,
چکیده مقاله :
Abstract. Today, there is no specific method or criterion for selecting contractors in the researches’ field. Usually this selection is regarded as a matter of taste and as a result, there is no coordinated approach in the mentioned domain. Sometimes, after signing the contract, the inappropriate selection became clear. The managers are in direct need of a pattern for selecting the contractors. In the present research, the evaluation indexes of knowledge developers such as universities, knowledge-based companies, and research centers have been studied. For clarifying the process of the selection and by the help of the fuzzy TOPSIS method, we have considered four indexes as the general ones: 1) the price 2) the quality 3) the delivery time and 4) the work experiences. Finally, for better understanding, we have brought an example with 5 candidates and 5 determiners.
[1]Chen, C.T., (2000) “Extensions of the TOPSIS for group decision-making under fuzzy environment”, fuzzy sets and systems, 114, 1-9.
[2]Chu, T. C, (2002) “Selecting plant location via a fuzzy TOPSIS approach”, International journal of manufacturing technology 20, 859-864.
[3]Ertugrul, I., and Karakasoglu, N., (2009) “Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods”. Expert Systems with Applications, 36, 702–715.
[4]Howells, J., Gagliardi, D. and Malik K., (2008) “The growth and management of R&D outsourcing: evidence from UK pharmaceuticals”. R&D Management 38, 2.
[5]Klepper, R., and Jones, W. (2010) “Outsourcing information technology systems and services. Retrieved form”.
[6]Lacity, M. C., Khan Shaji, A., and Willcocks, L. P., (2006) “A review of the IT outsourcingliterature: Insights for practice”. Journal of Strategic Information Systems, 18(3), 130–146.
[7]Perechuda, K., Sobińska,M., (2012) “ Models of information and knowledge transfer in IT outsourcing projects”. Conference on Computer Science and Information Systems pp. 1165–1169.
[8]Sherehiy.B., Karwowski, W., Layer., K.J. (2007) “A review of enterprise agility: Concepts, frameworks, and attributes”, International Journal of Industrial Ergonomics 37 445–460.
[9]Wang, J. J., and Yang, D. L. (2007) “Using a hybrid multi-criteria decision aid method for information system outsourcing”. Computers and Operations Research, 34 3691-3700.
Yang, C., and Huang, J. B. (2000) “A decision model for IS outsourcing”, International Journal of Information Management, 20, 225-