Leveraging technological knowledge transfer by using fuzzy linear programming technique for multiattribute group decision making with fuzzy decision variables

Autor: Yasemin Claire Erensal, Y. Esra Albayrak
Přispěvatelé: Doğuş Üniversitesi, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü, TR132156, TR12175, Belirlenecek
Rok vydání: 2009
Předmět:
Zdroj: Journal of Intelligent Manufacturing. 20:223-231
ISSN: 1572-8145
0956-5515
DOI: 10.1007/s10845-008-0220-3
Popis: Despite the importance of knowledge transfer for firms involved in foreign direct investment activities, this area has not received appropriate attention from the perspectives of both the knowledge transferor (i.e., MNC parent) and the knowledge recipient. To fill in the gap in the current literature we propose a model to understand the links between criteria complicating the transfer of knowledge and preferences that the company has to focus. This model is based on both the existing literature as well as views of company representatives and provides a useful methodology for identifying decision making problems on the transfer of knowledge. In this paper, we investigate the fuzzy linear programming technique (FLP) to analyze these links and for multiple attribute group decision making (MAGDM) problems with preference information on criteria. To reflect the decision maker's subjective preference information and to determine the weight vector of attributes, the technique for order preference by similarity to ideal solution (TOPSIS) developed by Hwang and Yoon (1995) and the linear programming technique for multidimensional analysis of preference (LINMAP) developed by Sirinivasan and Shocker (Psychometrica 38:337-369, 1973) are used.
Databáze: OpenAIRE
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