Dr. Zhang joined the Department of Marketing as a lecturer in August 2012. Prior to that he was a research fellow in the Intelligent Modelling & Analysis Research Group, School of Computer Science, University of Nottingham. He gained his PhD from the Electricity Policy Research Group, Judge Business School, University of Cambridge. His research interests are in the areas of complexity science and agent-based modelling for the energy market. During his post-doc period in Nottingham, Dr. Zhang led the agent-based simulation part in an EPSRC funded research project Future Energy Decision Making for Cities—Can Complexity Science Rise to the Challenge? He is an associate researcher of the ESRC Electricity Policy Research Group.
Zhang, T., Siebers, P. and Aickelin, U. (2012). A Three-Dimensional Model of Residential Energy Consumer Archetypes for Local Energy Policy Design in the UK. Energy Policy, 47, pp. 102-110.
Zhang, T. and Nuttall, W.J. (2012). An Agent-Based Simulation of Smart Metering Technology Adoption. International Journal of Agent Technologies and Systems, 4(1), pp.17-38
Zhang, T., Siebers, P. and Aickelin, U. (2011). Modelling Office Electricity Consumption: An Agent Based Approach. Energy and Buildings, 43(10), pp. 2882–2892.
Zhang, T. and Nuttall, W.J. (2011). Evaluating Government’s Policies on Promoting Smart Metering Diffusion in Retail Electricity Markets via Agent Based Simulation. Journal of Product Innovation Management, 28(2), pp.169-186.
Zhang, T. and Zhang, D. (2007). Agent-based simulation of consumer purchase decision-making and the decoy effect. Journal of Business Research, 60, pp. 912-922.
Zhang, T. (2010). A Review of Global Smart Metering Developments: Lessons for Smart Metering Policy in Liberalized Electricity Markets, in van Geenhuizen. M. and et al. (eds.): Energy and Innovation: Structural Change and Policy Implications, Ashland, OH: Purdue University Press.