This paper presents an analytic hierarchy process (AHP)-fuzzy inference system (FIS) model to aid decision-makers in the risk assessment and mitigation of overseas steel-plant projects. Through a thorough literature review, the authors identified 57 risks associated with international steel construction, operation, and transference of new technologies. Pairwise comparisons of all 57 risks by 14 subject-matter experts resulted in a relative weighting. Furthermore, to mitigate human subjectivity, vagueness, and uncertainty, a fuzzy analysis based on the findings of two case studies was performed. From these combined analyses, weighted individual risk soring resulted in the following top five most impactful international steel project risks: procurement of raw materials; design errors and omissions; conditions of raw materials; technology spill prevention plan; investment cost and poor plant availability and performance. Risk mitigation measures are also presented, and risk scores are re-assessed through the AHP-FIS analysis model depicting an overall project risk score reduction. The model presented is a useful tool for industry performing steel project risk assessments. It also provides decision-makers with a better understanding of the criticality of risks that are likely to occur on international steel projects.
To overcome profitability deterioration in executing steel price projects, companies are seeking overseas expansion, which increases market size while reducing profit certainty. Special purpose companies (SPCs) have been found to better manage these risks through tolling agreements which transfer the local pricing volatility risks (raw material, steel sales, licensing and income tax) to the project sponsor. The energy market has benefited from policy changes allowing the use of the tolling model, finding an increase in profitability for both project sponsors and SPCs through more effective risk sharing. While successes have been published in the energy, gas, and highway sectors, the tolling model’s efficacy has yet to be tested on the steel sector. As such, this research adds to the existing body of knowledge by testing the financial feasibility of using the tolling model on three million ton/year capacity steel projects. The data analyzed has been collected from “Company A”, a company with 50 years of domestic and 20 years international steel-iron plant project execution and operation experience. An economic analysis is performed on the best, most likely, and worst-case cost/revenue scenarios of a virtual project (which represents the average of all Company A projects) and two Company A projects under construction/operation. The findings support the use of the tolling model in volatile markets, showing a net present value (NPV) profitability increase of up to $940 versus the traditional project company model under worst case market conditions. However, the traditional project company model was found to be superior in best case market conditions. With these findings, international steel companies are able to consider alternative financing structures when executing projects in volatile markets, potentially resulting in greater project sponsor and SPC profit.
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