Value of more sophistication : capital investment decision-making with competitive dynamics in the mining industry

In many mining markets, one of the central business planning decisions faced by firms is where, when, and by how much to expand their production capacity. Appropriate investment planning methodology is important to both the mining industry and the wider economy. Currently, new mine investment decisions are most often based on the classic project evaluation methodology of discounted cash flow analysis (DCF) applied to the individual potential projects, which is flawed in its inadequate consideration of risk and flexibility, of impact on the profit of the firm, and of competitive dynamics in oligopoly markets. More sophisticated methods that account for these complexities have been proposed in academic literature; however, their value in realistic market settings has been little demonstrated in past literature and they are rarely adopted in practice. This thesis compares four investment decision paradigms of increasing scope and complexity in a three-firm mineral commodity market, based primarily on the firm-level cash flow NPV outcome in Monte Carlo simulations of the market. The analysis is conducted for various market scenarios of different demand growth patterns, volatility, demand elasticity, and supply structure. Simulation results show that in almost all scenarios, the game theoretic and option-based best-firm-NPV policies outperform the positive-mine-NPV policy substantially for all firms, regardless their market and cost position. However, the difference between the best-firm-NPV policy and the positive-firm-NPV policy is often small, depending on the scenario. Overall, the evaluation conducted in this thesis contributes to our understanding of how useful having more sophisticated investment decision methods might be to the firms and under what market conditions.

Department dc:contributor.department

Massachusetts Institute of Technology. Engineering Systems Division.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2014

Author dc:creator

• Li, Yuanjian Carla

Advisor dc:contributor.advisor

• Frank R. Field, III, Randolph Kirchain and Richard Roth.

• Engineering Systems Division.
• Technology, Management, and Policy Program.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/95584

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/95584