Dr Tao Zhang

Dr Tao Zhang

Department of Marketing
Lecturer in Marketing and Sustainability

Contact details

Address
Room 119, Ash House
University of Birmingham
Edgbaston
Birmingham
B15 2TT

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.

Qualifications

PhD (Cantab)

Teaching

Dr. Zhang is the Director of Marketing PhD Programme and the module leader of Consumer Behaviour and Strategic Environmental Sustainability.

Research

  • Strategic Marketing
  • Consumer Behaviour
  • Innovation Management
  • Energy Markets
  • Complexity Science
  • Simulation and Modelling

Other activities

  • Researcher, the Intelligent Modelling & Analysis Research Group, School of Computer Science, University of Nottingham
  • Associate Researcher, the ESRC Electricity Policy Research Group, University of Cambridge

Publications

Journal Articles:

Esfahbodi, A., Zhang, Y, Watson, G. and Zhang, T. (2016). Governance Pressures and Performance Outcomes of Sustainable Supply Chain Management - An Empirical Analysis of the UK Manufacturing Industry, Journal of Cleaner Production, in press

Yu, Y., Wu, W., Zhang T.  and Liu, Y. (2016). Environmental catching-up, eco-innovation, and technological leadership in China's pilot ecological civilization zones, Technological Forecasting & Social Change, in press

Zhang, T., Siebers, P. and Aickelin, U. (2016). Simulating User Learning in Authoritative Technology Adoption:  An Agent Based Model for Council-led Smart Meter Deployment Planning in the UK. Technological Forecasting & Social Change, 106, pp. 74-84.

Xu, F.Y., Zhang, T., Lai, L.L. and Zhou, H. (2015). Shifting Boundary for price-based residential demand response and applications. Applied Energy, 164, pp. 353–370.  

Siebers, L.Q., Zhang, T. and Li, F. (2013). Retail positioning through customer satisfaction: an alternative explanation to the resource-based view. Journal of Strategic Marketing, 21(7), pp.559-587.

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.

Book Chapters:

Zhang, T. (2016). The Journey of Smart Metering in Great Britain: A Re-visit, in Heffron R.J., and Little G. (Eds): Delivering Energy Law and Policy in the EU and US: A Reader, UK: Edinburgh University Press.

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.