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Title: A decision support methodology to enhance the competitiveness of the Turkish automotive industry
Authors: Ulengin, F
Onsel, S
Aktas, E
Kabak, O
Ozaydin, O
Keywords: Decision support systems;Bayesian causal network;Competitiveness;Automotive industry;Turkey
Issue Date: 2013
Publisher: Elsevier
Citation: European Journal of Operational Research, 234(3), 789–801, 2013
Abstract: Three levels of competitiveness affect the success of business enterprises in a globally competitive environment: the competitiveness of the company, the competitiveness of the industry in which the company operates and the competitiveness of the country where the business is located. This study analyses the competitiveness of the automotive industry in association with the national competitiveness perspective using a methodology based on Bayesian Causal Networks. First, we structure the competitiveness problem of the automotive industry through a synthesis of expert knowledge in the light of the World Economic Forum’s competitiveness indicators. Second, we model the relationships among the variables identified in the problem structuring stage and analyse these relationships using a Bayesian Causal Network. Third, we develop policy suggestions under various scenarios to enhance the national competitive advantages of the automotive industry. We present an analysis of the Turkish automotive industry as a case study. It is possible to generalise the policy suggestions developed for the case of Turkish automotive industry to the automotive industries in other developing countries where country and industry competitiveness levels are similar to those of Turkey.
Description: This is the post-print (final draft post-refereeing) version of the article. Copyright @ 2013 Elsevier B.V. All rights reserved.
ISSN: 0377-2217
Appears in Collections:Business and Management
Brunel Business School Research Papers

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