Leveraging technological knowledge transfer by using fuzzy linear programming technique for multiattribute group decision making with fuzzy decision variables
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 literatur...
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| Veröffentlicht in: | Journal of intelligent manufacturing Jg. 20; H. 2; S. 223 - 231 |
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| Abstract | 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. |
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| AbstractList | Issue Title: Special Issue on Manufacturing agents and fuzzy systems; Guest Editors: Ercan Öztemel, Harun Taskin and Cemalettin Kubat 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. [PUBLICATION ABSTRACT] 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. |
| Author | Erensal, Yasemin Claire Albayrak, Y. Esra |
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| CitedBy_id | crossref_primary_10_1007_s10845_011_0600_y crossref_primary_10_1007_s10845_010_0391_6 crossref_primary_10_1080_10429247_2020_1738879 crossref_primary_10_3390_su13020955 crossref_primary_10_1109_TEM_2021_3118028 crossref_primary_10_1109_TEM_2020_2980127 crossref_primary_10_1016_j_eswa_2012_05_056 |
| Cites_doi | 10.1016/S0165-0114(83)80083-9 10.1016/S1090-9516(97)90008-0 10.1057/palgrave.jibs.8490155 10.1002/smj.4250120908 10.1002/(SICI)1097-0266(199805)19:5<461::AID-SMJ953>3.0.CO;2-L 10.1007/BF02291658 10.1016/j.jwb.2003.08.009 10.1002/smj.206 10.1287/orsc.5.1.14 10.1111/j.1467-6486.1992.tb00686.x 10.2307/1885489 10.1287/mnsc.45.7.905 10.2307/2392402 10.1016/j.ins.2003.08.007 10.1006/obhd.2000.2893 10.1002/(SICI)1097-0266(200004)21:4<473::AID-SMJ84>3.0.CO;2-I 10.1016/S0019-9958(65)90241-X 10.1016/0263-2373(94)90005-1 10.2307/258980 10.1080/0305215041000168521 10.2307/2393553 10.2307/256729 10.2307/2393957 10.1016/S0165-0114(97)00377-1 10.1002/smj.4250171105 10.1002/smj.4250171106 10.5465/amr.1991.4279628 10.1016/j.fss.2005.02.018 10.1016/S0165-0114(83)80082-7 10.1093/oso/9780195092691.001.0001 10.1007/978-3-642-61580-1 10.1093/oso/9780198774846.001.0001 |
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| Keywords | Multiple attribute group decision making (MAGDM) Linear programming technique for multidimensional analysis of preference (LINMAP) Fuzzy linear programming technique (FLP) TOPSIS Knowledge transfer |
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| SubjectTerms | Business and Management Competitive advantage Control Decision making Foreign investment Fuzzy logic Knowledge Linear programming Linguistics Machines Manufacturing Mechatronics Preferences Processes Production Robotics Studies |
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