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A systems approach in examining optimization opportunities and dynamics of the global steel industry.
- Source :
- Information Knowledge Systems Management; 2008, Vol. 7 Issue 4, p401-427, 27p, 9 Charts, 7 Graphs
- Publication Year :
- 2009
-
Abstract
- This paper takes a systems perspective in exploring and analyzing optimization possibilities and market dynamics of the global steel industry. To assess and improve this industry's performance, two analytical approaches are used. First, a multiple regression analysis was applied to determine the important relationships among world crude steel producers, international trading blocs and key countries to quantify the historical correlations in the steel industry. Next, game theory models are applied to study global steel industry dynamics and to quantify and compare historical production data in order to determine optimal approaches that could be employed to gain market share by key countries and players. In order to gain an in-depth understanding of interplay among various system's players within this complex global steel industry, the paper discusses protectionism, quotas, tariffs, exports, imports, capacity, substitution, specialization, mergers and cooperation, among other strategies used historically within the industry. A geographical survey of the global steel industry data is presented in multiple chart formats. Strengths, weaknesses, opportunities and threats to the industry players are compared. Implications of the analytical findings for the US, European, and Asian competitors in the global steel industry are outlined and recommendations that would lead to optimization of global steel industry operations are suggested. [ABSTRACT FROM AUTHOR]
- Subjects :
- STEEL industry
MARKET share
SWOT analysis
ECONOMIC competition
REGRESSION analysis
Subjects
Details
- Language :
- English
- ISSN :
- 13891995
- Volume :
- 7
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- Information Knowledge Systems Management
- Publication Type :
- Academic Journal
- Accession number :
- 45726698