Title: Dual investments subject to risk aversion and lead times: A case of mitigating supply risk of cellulosic biofuel production
Speaker: Dr. Chung-Li Tseng, Associate Professor at Business School, University of New South Wales in Australia
Time: 9:00 am, June 13, 2018
Venue: Zhuanghui Hall, Building 12, Wushan Campus
Introduction to the Speaker:
Chung-Li Tseng is currently an associate professor of operations management at the UNSW Business School, University of New South Wales in Australia. Prior to joining UNSW, he was on the faculty of the University of Maryland and the University of Missouri-Rolla in the US. He received his Ph.D. degree from the University of California-Berkeley and his M.S. from UC Davis. He has edited or co-edited several special issues of peer-reviewed journals. His published work has appeared in Operations Research, The Energy Journal, Energy Economics, European Journal of Operational Research, Construction Management and Economics, and other journals. He is a member of INFORMS and ASCE, and a senior member of IEEE. He is a past President of the Section on Energy, Natural Resources, and the Environment of the INFORMS. He is the Editor-in-Chief of the ASCE Journal of Energy Engineering (Impact Factor 1.94), and he has served on the Editorial Board of the ASCE Journal of Infrastructure Systems, the International Journal of Electronic Business Management, and the International Journal of Business Analytics. His research interests include operations management, financial engineering, and project management.
We consider the investment of a cellulosic biofuel facility using fast pyrolysis with corn stover as its main feedstock, whose supply is uncertain. To mitigate the supply uncertainty, the decision maker (DM) also considers investing in a land to grow a second crop as an alternative feedstock. Given these dual investments: one primary asset and another accessory asset for value-adding, this paper considers their optimal investment timings subject to lead time constraints. Using a real options approach, we value the dual investments considering nonzero lead times subject to uncertainties of biofuel price, land price, and feedstock yield. The optimal investment conditions are obtained using stochastic dynamic programming integrated with Monte Carlo simulations. Traditional investment rules take the format that an investment should proceed if the asset value exceeds some threshold value. Facing the dual investments, when the DM is risk averse, the traditional threshold rule may no longer hold true. Under some condition, the optimal decision is to alternately invest and not invest in the second crop over as many as five intervals of the biofuel price. When there are multiple investments to make, the DM's risk aversion may have an unintuitive effect on the optimal timing and sequence of the investments to be undertaken such that the traditional investment rule may not be optimal.