Manuscript Number : IJSRST173335
Ranking Multi-Factor Criteria in A Make or Buy Decision Using Non-Additive Fuzzy Integrals
Authors(5) :-Emma Serwaa Obobisa, Chen Hai-bo, Henry Asante Antwi, John Osei Antwi, Stephany Abokzele Adongo In the past firms mostly focused on the cost aspect of make or buy, giving less emphasis on the other determinants of make or buy decisions. Using non-additive fuzzy integrals, we model and rank a collection of multi-factor criteria for make or buy decision. Four component factors classified as resource base, transaction cost, firm size and external factors were analyzed and ranked. We observed that among these variables tested firm's resource base emerged as the highest decision criterion for in make or buy decision over transaction costs. This implies that a firm's resources (FR), proxied by resource availability, innovative competence, share risk/expertise and market penetration were more dominant that cost elements such as supplier competition, buyer experience, volume uncertainty, production cost advantage and technology uncertainty.
Emma Serwaa Obobisa Make, Buy, Decision Multi, Factor, Fuzzy
Publication Details
Published in : Volume 3 | Issue 3 | March-April 2017 Article Preview
School of Finance and Economics, Jiangsu University, 301 Xuefu Road, Zhenjiang, Jiangsu, P.R. China
Chen Hai-bo
School of Finance and Economics, Jiangsu University, 301 Xuefu Road, Zhenjiang, Jiangsu, P.R. China
Henry Asante Antwi
School of Management, Jiangsu University, 301 Xuefu Road, Zhenjiang, Jiangsu, P.R. China
John Osei Antwi
School of Management and Economics, University of Electronic Science and Technology, Chengdu, P.R. China
Stephany Abokzele Adongo
School of Finance and Economics, Jiangsu University, 301 Xuefu Road, Zhenjiang, Jiangsu, P.R. China
Date of Publication : 2017-04-30
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 141-149
Manuscript Number : IJSRST173335
Publisher : Technoscience Academy
Journal URL : https://ijsrst.com/IJSRST173335
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