Evaluating government's policies on promoting smart metering diffusion in retail electricity markets via agent-based simulation

Journal of Product Innovation Management

Volumn 28, Issue 2, 2011, Pages 169-186

  Zhang, Tao ^a   Nuttall, William J ^b  

^a UNIVERSITY OF NOTTINGHAM   (United Kingdom)

^b UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

AGENT BASED SIMULATION; AGENT-BASED MODEL; BREAK DOWN; ELECTRICITY MARKET; INNOVATION DIFFUSION; MARKET GAME; POLICY IMPLICATIONS; POLICY MAKING; POLICY OPTIONS; RETAIL ELECTRICITY MARKETS; SMART METERING; UNITED KINGDOM;

DIFFUSION; ELECTRIC INDUSTRY; ELECTRIC MEASURING INSTRUMENTS; ELECTRICITY; MULTI AGENT SYSTEMS; SALES;

COMMERCE;

EID: 79951790805     PISSN: 07376782     EISSN: 15405885     Source Type: Journal    
DOI: 10.1111/j.1540-5885.2011.00790.x     Document Type: Article

References (48)

1. Ajzen, I., 1985. From intentions to actions: A theory of planned behavior. In: Action control: From cognition to behavior, ed., J. Kuhl, and, J. Beckmann, 11-39. Heidelberg: Springer.
2. Ajzen, I., 1991. The theory of planned behaviour. Organizational Behaviour and Human Decision Processes 50: 179-211.
3. Ajzen, I., and, M. Fishbein,. 2005. The influence of attitudes on behavior. In The handbook of attitudes, ed., D. Albarraci, B. T. Johnson, and, M. P. Zanna, 173-221. Mahwah, NJ: Erlbaum.
4. Amendola, M., and, J.-L. Gaffard,. 1988. The innovative choice: An economic analysis of the dynamics of technology. Oxford: Blackwell.
5. Asher, A., 2007. Utility metering: A smarter approach. Utility Business (December).
6. Baker, L. C., 2001. Managed care and technology adoption in health care: Evidence from magnetic resonance image. Journal of Health Economics 20 (3): 395-421.
7. Bandura, A., 1986. Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.
8. Barabasi, A.-L., and, R. Albert,. 1999. Emergence of scaling in random networks. Science 286 (5439): 509-12.
9. Bass, F. M., 1969. A new product growth for model consumer durables. Management Science 15 (5): 215-27.
10. Compeau, D. R., C. A. Higgins, and, S. Huff,. 1999. Social cognitive theory and individual reactions to computing technology: A longitudinal study. MIS Quarterly 23 (2): 145-58.
11. Cutler, D. M., and, M. B. McClellan,. 1996. The determinants of technological change in heart attack treatment. Working Paper 5751. Cambridge, MA: National Bureau of Economic Research.
12. Davies, S., 1979. The diffusion of process innovations. Cambridge: Cambridge University Press.
13. Davis, F. D., 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 13 (3): 319-40.
14. De Bruyn, A., and, G. L. Lilien,. 2008. A multi-stage model of word-of-mouth influence through viral marketing. International Journal of Research in Marketing 25: 151-63.
15. DGCG Technical Steering Group. 2003. Metering for micro-generation. P02a Work Stream 4. London: Distributed Generation Co-ordinating Group.
16. Dixit, A. K., and, R. S. Pindyck,. 1994. Investment under uncertainty. Princeton, NJ: Princeton University Press.
17. Dodds, P. S., R. Muhamad, and, D. J. Watts,. 2003. An experimental study of search in global social networks. Science 301 (5634): 827-29. (Pubitemid 36962622)
18. Garcia, R., 2005. Uses of agent-based modelling in innovation/new product development research. Journal of Product Innovation Management 22 (5): 380-98. (Pubitemid 41348557)
19. Gray, W. B., and, R. J. Shadbegian,. 1998. Environmental regulation, investment timing, and technology choice. Journal of Industrial Economics 46 (2): 235-56.
20. Guardiola, X., A. Diza-Guilera, C. J. Perez, A. Arenas, and, M. Llas,. 2002. Modeling diffusion of innovations in a social network. Physical Review E 66: 026121.
21. Hall, B. H., and, B. Khan,. 2003. Adoption of new technology. Working paper, University of California, Berkeley.
22. Hegselmann, R., and, A. Flache,. 1998. Understanding complex social dynamics: A plea for cellular automata based modelling. Journal of Artificial Societies and Social Simulation 1 (3).
23. Hohnisch, M., S. Pittnauer, and, D. Stauffer,. 2008. A percolation-based model explaining delayed takeoff in new-product diffusion. Industrial and Corporate Change 17 (5): 1001-17.
24. Janssen, M. A., and, W. Jager,. 1999. An integrated approach to simulating behavioural processes: A case study of the lock-in of consumption patterns. Journal of Artificial Societies and Social Simulation 2 (2).
25. Janssen, M. A., and, W. Jager,. 2002. Simulating diffusion of green products: Co-evolution between firms and consumers. Journal of Evolutionary Economics 12 (3): 283-306.
26. Janssen, M. A., and, W. Jager,. 2003. Simulating market dynamics: Interactions between consumer psychology and social networks. Artificial Life 9 (4): 343-56.
27. Mathieson, K., 1991. Predicting user intentions: Comparing the technology acceptance model with the theory of planned behaviour. Information Systems Research 2 (3): 173-91.
28. Milgram, S., 1967. The small world problem. Psychology Today 1 (1): 60-7.
29. Mowery, D. C., and, N. Rosenberg,. 1982. Government policy and innovation in the commercial aircraft industry, 1925-75. In Government and technical progress: A cross-industry analysis, ed., R. R. Nelson, 163-77. New York: Pergamon Press.
30. Ofcom. 2001. Mobile number portability determination requests explanatory document.
31. Ofgem. 2001. Smart metering working group report. London: Ofgem.
32. Ofgem. 2006a. What is a smart meter? London: Ofgem.
33. Ofgem. 2006b. Domestic metering innovation. Consultation Document 20/06. London: Ofgem.
34. Ofgem. 2007. Domestic retail market report. London: Ofgem.
35. Perugini, M., and, R. P. Bagozzi,. 2001. The role of desires and anticipated emotions in goal-directed behaviour: Broadening and deepening the theory of planned behaviour. British Journal of Social Psychology 40 (1): 79-98.
36. Rogers, E. M., 1962. Diffusion of innovation. New York: Free Press.
37. Sauter, R., J. Watson, and, L. Hughes,. 2005. Metering, communication and control technologies for micro-generation. ESRC Sustainable Technologies Programme Working Paper Series 2005/1. Brighton, UK: University of Sussex.
38. Scott, J. P., 2000. Social network analysis: A handbook. London: Sage.
39. Stoneman, P., 2001. Financial factors and inter firm diffusion of new technology: A real options model. EIFC Working Paper No. 2001-08. Coventry, UK: University of Warwick.
40. Strang, D., and, S. A. Soule,. 1998. Diffusion in organizations and social movements: From hybrid corn to poison pills. Annual Review of Sociology 24: 265-90.
41. Valente, T. W., 1995. Network of models of diffusion of innovation. Cresskill, NJ: Hampton Press.
42. Vallerand, R. J., 1997. Toward a hierarchical model of intrinsic and extrinsic motivation. In Advances in experimental social psychology, ed., M. P. Zanna, 271-360. New York: Academic Press.
43. Vasey, G. M., 2007. SMART metering-Requires SMART technology. Issue Alert (European Edition).
44. Veneris, Y., 1990. Modeling the transition from the industrial to the informational revolution. Environment and Planning A 22 (3): 399-416.
45. Watts, D. J., and, P. S. Dodds,. 2007. Influentials, networks, and public opinion formation. Journal of Consumer Research 34: 441-58.
46. Watts, D. J., and, S. H. Strogatz,. 1998. Collective dynamics of "small-world" networks. Nature 393: 440-2.
47. Zhang, T., and, W. J. Nuttall,. 2007. An agent-based simulation of smart metering technology adoption. EPRG Working Paper 0727. Cambridge: University of Cambridge.
48. Zhang, T., and, D. Zhang,. 2007. Agent-based simulation of consumer purchase decision-making and the decoy effect. Journal of Business Research 60 (8): 912-22.