Authors: T. Aouam, A. Diabat, M. Boulmalf, A. Soufyane
Addresses: Department of Industrial Engineering, Faculty of Engineering and Applied Sciences, Al Hosn University, Abu Dhabi 38772, UAE. ' Engineering Systems and Management, Masdar Institute of Science and Technology, P.O. Box 54224, Abu Dhabi, UAE. ' Department of Computer Science, School of Science and Engineering, Al Akhawayn University, Ifrane 53000, Morocco. ' Faculty of Engineering and Applied Sciences, Al Hosn University, Abu Dhabi 38772, UAE
Abstract: While local distribution companies (LDCs) are responsible for the procurement and delivery of natural gas to their customers, regulators oversee the retail pricing of natural gas. The cost of service is the common regulation method but provides arguably little incentive for an LDC to optimally manage procurement activities. Taking variance as a measure of risk, we model and solve the LDC|s procurement problem in face of two linear incentive contracts: the cost based contract, where the LDC|s compensation is linear in the procurement cost and a benchmark based contract, where the LDC|s compensation is linear in the difference between the procurement cost and a preselected benchmark. We conclude that the level of cost reduction effort chosen by the LDC is the same under the two contracts. However, the LDC has less incentive to hedge against price risk and consequently the fee to consumers has a higher variance when a benchmark is used. We argue that using futures prices, on which public information is available to consumers and regulators, in incentive contracts is a suitable regulation scheme. Finally, we formulate the regulator|s problem as a bi-level optimisation model, study the sensitivity of its optimal solution to various parameters and provide some insights and policy recommendations.
Keywords: natural gas regulation; incentive contracts; risk management; principal agent; mean-variance modelling; local distribution companies; LDCs; procurement cost; price risk; futures prices.
International Journal of Applied Decision Sciences, 2009 Vol.2 No.1, pp.57 - 73
Published online: 20 May 2009 *Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article