Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Matching consumer segments to innovative utility business models

An Author Correction to this article was published on 12 March 2021

This article has been updated


Energy as a service, smart home opportunities and electrification of heat and transport can lead to new ways of switching supplier or choosing new energy contracts. Here, we used business model collaboration workshops to create archetypes of new utility business models, which were then tested with a representative sample of British energy consumers to explore their attractiveness to different segments of society. We show that some of these segments have a substantial appetite for new business models. However, the segments that choose these models are more likely to be affluent, educated homeowners. Without intervention, innovation in utility business models risks exacerbating existing social inequalities, as lower incomes, lower home ownership and low education result in lower preferences for, or no ability to engage with, new utility business models. We also find that institutional trust beyond the energy sector is a key driver of consumer segmentation.

Your institute does not have access to this article

Access options

Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Utility business model archetypes.
Fig. 2: Likelihood of adopting each archetype.
Fig. 3: Consumer segments.
Fig. 4: Probability of adoption of each archetype in each consumer segment.
Fig. 5: Trust across societal institutions by consumer segment.

Data availability

The relevant survey data, including all raw data, generated or analysed during this study are included in the Supplementary Data file. Data generated in the construction of business model archetypes are summarized in the Supplementary Information. The data that support the plots within this paper and other findings of this study are available from the corresponding author upon reasonable request.

Change history


  1. Schot, J., Kanger, L. & Verbong, G. The roles of users in shaping transitions to new energy systems. Nat. Energy 1, 16054 (2016).

    Google Scholar 

  2. Future Energy Scenarios (National Grid ESO, 2020);

  3. Retail Markets Monitoring Report CEER Report C17-MMR-83-02 (Council of European Energy Regulators, 2017):

  4. Hortaçsu, A., Madanizadeh, S. A. & Puller, S. L. Power to choose? An analysis of consumer inertia in the residential electricity market. Am. Econ. J. Econ. Policy 9, 192–226 (2017).

    Google Scholar 

  5. Sen, A., Nepal, R. & Jamasb, T. Reforming Electricity Reforms? Empirical Evidence from Asian Economies (Oxford Institute for Energy Studies, 2016);

  6. Van Beek, M, Holst, A & Keeble, J. Low Carbon, High Stakes—Do You Have the Power to Transform? (Accenture Strategy, 2015).

  7. Energy Market Investigation Final Report (Competition and Markets Authority, 2016).

  8. The Road Ahead: Gaining Momentum from Energy Transformation (PwC, 2014);

  9. Bryant, S. T., Straker, K. & Wrigley, C. The typologies of power: energy utility business models in an increasingly renewable sector. J. Clean. Prod. 195, 1032–1046 (2018).

    Google Scholar 

  10. Hawker, G., Bell, K. & Gill, S. Electricity security in the European Union—the conflict between national capacity mechanisms and the single market. Energy Res. Soc. Sci. 24, 51–58 (2017).

    Google Scholar 

  11. Parag, Y. & Sovacool, B. K. Electricity market design for the prosumer era. Nat. Energy 1, 16032 (2016).

    Google Scholar 

  12. Britton, J., Hardy, J., Mitchell, C. & Hoggett, R. Changing Actor Dynamics and Emerging Value Propositions in the UK Electricity Retail Market IGov Working Paper (2019);

  13. Burger, S., Chaves-Ávila, J. P., Batlle, C. & Pérez-Arriaga, I. J. A review of the value of aggregators in electricity systems. Renew. Sustain. Energy Rev. 77, 395–405 (2017).

    Google Scholar 

  14. Ward, A., Thomas, N. & Chazan, G. European utilities primed for consolidation in shift to renewables. Financial Times (27 June 2017).

  15. World Energy Investment (International Energy Agency, 2017).

  16. Hall, S. & Roelich, K. Business model innovation in electricity supply markets: the role of complex value in the United Kingdom. Energy Policy 92, 286–298 (2016).

    Google Scholar 

  17. Roelich, K. et al. Towards resource-efficient and service-oriented integrated infrastructure operation. Technol. Forecast. Soc. Change 92, 40–52 (2015).

    Google Scholar 

  18. Helms, T. Asset transformation and the challenges to servitize a utility business model. Energy Policy 91, 98–112 (2016).

    Google Scholar 

  19. Helms, T., Loock, M. & Bohnsack, R. Timing-based business models for flexibility creation in the electric power sector. Energy Policy 92, 348–358 (2016).

    Google Scholar 

  20. White, L. V. & Sintov, N. D.Inaccurate consumer perceptions of monetary savings in a demand-side response programme predict programme acceptance. Nat. Energy 3, 1101–1108 (2018).

    Google Scholar 

  21. Eid, C., Codani, P., Perez, Y., Reneses, J. & Hakvoort, R. Managing electric flexibility from distributed energy resources: a review of incentives for market design. Renew. Sustain. Energy Rev. 64, 237–247 (2016).

    Google Scholar 

  22. Frei, F., Sinsel, S. R., Hanafy, A. & Hoppmann, J. Leaders or laggards? The evolution of electric utilities’ business portfolios during the energy transition. Energy Policy 120, 655–665 (2018).

    Google Scholar 

  23. Williams, B. & Waring, G. Consumer Engagement In The Energy Market 2018: Report on a Survey of Energy Consumers (GfK, 2018);

  24. Flores, M. & Waddams Price, C. The role of attitudes and marketing in consumer behaviours in the British retail electricity market. Energy J. 39, 153–179 (2018).

    Google Scholar 

  25. Hortaçsu, A., Madanizadeh, S. A. & Puller, S. L. Power to choose? An analysis of consumer inertia in the residential electricity market. Am. Econ. J. Econ. Policy 9, 192–226 (2017).

    Google Scholar 

  26. Defeuilley, C. Retail competition in electricity markets. Energy Policy 37, 377–386 (2009).

    Google Scholar 

  27. Waddams Price, C. Back to the future? Regulating residential energy markets. Int. J. Econ. Bus. 25, 147–155 (2018).

    Google Scholar 

  28. Loewenstein, G. Experimental economics from the vantage‐point of behavioural economics. Econ. J. 109, 25–34 (1999).

    Google Scholar 

  29. Frederiks, E. R., Stenner, K. & Hobman, E. V. Household energy use: applying behavioural economics to understand consumer decision-making and behaviour. Renew. Sustain. Energy Rev. 41, 1385–1394 (2015).

    Google Scholar 

  30. Simon, H. A. A behavioral model of rational choice. Q. J. Econ. 69, 99–118 (1955).

    Google Scholar 

  31. Pichert, D. & Katsikopoulos, K. V. Green defaults: information presentation and pro-environmental behaviour. J. Environ. Psychol. 28, 63–73 (2008).

    Google Scholar 

  32. Deller, D. et al. Fairness in Retail Energy Markets? Evidence from the UK (Centre for Competition Policy, 2018).

  33. Shafir, E., Simonson, I. & Tversky, A. Reason-based choice. Cognition 49, 11–36 (1993).

    Google Scholar 

  34. Hobman, E. V., Frederiks, E. R., Stenner, K. & Meikle, S. Uptake and usage of cost-reflective electricity pricing: insights from psychology and behavioural economics. Renew. Sustain. Energy Rev. 57, 455–467 (2016).

    Google Scholar 

  35. Eppler, M. J., Hoffmann, F. & Bresciani, S. New business models through collaborative idea generation. Int. J. Innov. Manag. 15, 1323–1341 (2011).

    Google Scholar 

  36. Rohrbeck, R., Konnertz, L. & Knab, S. Collaborative business modelling for systemic and sustainability innovations. Int. J. Technol. Manag. 63, 4–23 (2013).

    Google Scholar 

  37. Pieroni, M. P., McAloone, T. & Pigosso, D. A. Business model innovation for circular economy and sustainability: a review of approaches. J. Clean. Prod. 215, 198–216 (2019).

    Google Scholar 

  38. Burnet, F. Take Charge: An Analysis of the Domestic Electric Vehicle Tariff Market (Citizens Advice, 2019);

  39. Hahnel, U. J., Herberz, M., Pena-Bello, A., Parra, D. & Brosch, T. Becoming prosumer: revealing trading preferences and decision-making strategies in peer-to-peer energy communities. Energy Policy 137, 111098 (2020).

    Google Scholar 

  40. Retail Research into Customer Switching and Supply Disintermediation: Final Report: Disintermediation (ESP Consulting, 2018);

  41. Brown, D. Business models for residential retrofit in the UK: a critical assessment of five key archetypes. Energy Effic. 11, 1497–1517 (2018).

    Google Scholar 

  42. Davis, F. D. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13, 319–340 (1989).

    Google Scholar 

  43. Curtius, H. C., Künzel, K. & Loock, M.Generic customer segments and business models for smart grids. der markt 51, 63–74 (2012).

    Google Scholar 

  44. Fell, M. J., Shipworth, D., Huebner, G. M. & Elwell, C. A. Public acceptability of domestic demand-side response in Great Britain: the role of automation and direct load control. Energy Res. Soc. Sci. 9, 72–84 (2015).

    Google Scholar 

  45. Venkatesh, V. & Davis, F. D. A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag. Sci. 46, 186–204 (2000).

    Google Scholar 

  46. Rogers, E. M. Diffusion of Innovations 4th edn (The Free Press, 1995).

  47. Ajzen, I.The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50, 179–211 (1991).

    Google Scholar 

  48. Pavlou, P. A. Consumer acceptance of electronic commerce: integrating trust and risk with the technology acceptance model. Int. J. Electron. Commer. 7, 101–134 (2003).

    Google Scholar 

  49. Agarwal, R. & Prasad, J. A conceptual and operational definition of personal innovativeness in the domain of information technology. Inf. Syst. Res. 9, 204–215 (1998).

    Google Scholar 

  50. Agnew, S. & Dargusch, P. Consumer preferences for household-level battery energy storage. Renew. Sustain. Energy Rev. 75, 609–617 (2017).

    Google Scholar 

  51. Xu, X., Chen, C. F., Zhu, X. & Hu, Q. Promoting acceptance of direct load control programs in the United States: financial incentive versus control option. Energy 147, 1278–1287 (2018).

    Google Scholar 

  52. Sütterlin, B. & Brunner, T. A. & Siegrist, M.Who puts the most energy into energy conservation? A segmentation of energy consumers based on energy-related characteristics. Energy Policy 39, 8137–8152 (2011).

    Google Scholar 

  53. Albert, A. & Rajagopal, R. Smart meter driven segmentation: what your consumption says about you. IEEE Trans. Power Syst. 28, 4019–4030 (2013).

    Google Scholar 

  54. Moon, N. & McHugh, S. Energy Market Investigation. Technical Report on a Survey Conducted for the Competition and Markets Authority by GfK NOP (GfK, 2015).

  55. Littlechild, S. Promoting competition and protecting customers? Regulation of the GB retail energy market 2008–2016. J. Regul. Econ. 55, 107–139 (2019).

    Google Scholar 

  56. Mazur, C., Hall, S., Hardy, J. & Workman, M. Technology is not a barrier: a survey of energy system technologies required for innovative electricity business models driving the low carbon energy revolution. Energies 12, 428 (2019).

    Google Scholar 

  57. Barton, C. Home Ownership and Renting: Demographics Briefing Paper Number CBP 7706 (House of Commons Library, 2017).

  58. Stenner, K., Frederiks, E. R., Hobman, E. V. & Cook, S. Willingness to participate in direct load control: the role of consumer distrust. Appl. Energy 189, 76–88 (2017).

    Google Scholar 

  59. Perlaviciute, G. & Steg, L. Contextual and psychological factors shaping evaluations and acceptability of energy alternatives: integrated review and research agenda. Renew. Sustain. Energy Rev. 35, 361–381 (2014).

    Google Scholar 

  60. DECC Public Attitudes Tracker - Wave 1 Summary of Key Issues (Department of Energy and Climate Change, 2012).

  61. Demski, C., Butler, C., Parkhill, K. A., Spence, A. & Pidgeon, N. F. Public values for energy system change. Glob. Environ. Change 34, 59–69 (2015).

    Google Scholar 

  62. Sehic, S., Ashworth, P. & Harris, J. Understanding the Socio-Economic Challenges for Energy Storage Uptake (The University of Queensland, 2017).

  63. DECC Public Attitudes Tracking Survey—Wave 2 Questionnaire (Department of Energy and Climate Change, 2012).

  64. Consumer Engagement in the Energy Market Since the Retail Market Review. 2016 Survey Findings (Ofgem, 2016).

  65. Waring, B., Silk, A. & Waring, G. Consumer Engagement in the Energy Market 2017 (Ofgem, 2017).

  66. Henry, G. T. Practical Sampling (Sage, 1990).

  67. Households Below Average Income: An Analysis of the UK Income Distribution: 1994/95 to 2015/16 (Department for Work and Pensions, 2017).

  68. Scotland’s Census 2011 (National Records of Scotland, 2018);

  69. Census 2011 (Office of National Statistics, 2017);

  70. De Vellis, R. F. Scale Development: Theory and Applications (Applied Social Research Methods) Vol. 26 (Sage, 1991).

  71. Costello, A. B. & Osborne, J. W.Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis. Pract. Assess. Res. Eval. 10, 1–9 (2005).

    Google Scholar 

  72. Gorsuch, R. L. Factor Analysis 2nd edn (Lawrence Erlbaum Associates, 1983).

  73. Hair, J., Anderson, R., Tatham, R. & Black, W. Multivariate Data Analysis (Prentice Hall, 1998).

  74. Sarstedt, M. & Mooi, E. A Concise Guide to Market Research (Springer, 2014).

  75. Anable, J. Complacent car addicts or aspiring environmentalists? Identifying travel behaviour segments using attitude theory. Transp. Policy 12, 65–78 (2005).

    Google Scholar 

  76. Milligan, G. W. & Cooper, M. C. An examination of procedures for determining the number of clusters in a data set. Psychometrika 50, 159–179 (1985).

    Google Scholar 

  77. Hall, S., Mazur, C., Hardy, J., Workman, M. & Powell, M. Prioritising business model innovation: what needs to change in the United Kingdom energy system to grow low carbon entrepreneurship? Energy Res. Soc. Sci. 60, 101317 (2020).

    Google Scholar 

Download references


This research was partly funded by the Engineering and Physical Sciences Research Council (grant EP/N029488/1), Economic and Social Research Council (grant ES/M500562/1) and UK Research Councils (grants EPSRC EP/L024756/1 and NERC NE/G007748/1) as part of the UK Energy Research Centre (UKERC).

Author information

Authors and Affiliations



S.H. led the development of the Utility 2050 research process and led the literature review discussion and conclusions. J.A. led the survey design with input on business model characteristics and question generation from J.H., S.H., C.M., and M.W.; J.A. led the statistical analysis and segmentation exercise. M.W., C.M., J.A. and J.H. contributed substantive analysis, redrafting and editing. Y.M. aided early analysis and drafting.

Corresponding author

Correspondence to Stephen Hall.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Energy thanks Rachel Bray, Laura Olkkonen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Tables 1–8, Figs. 1–17, Note 1, Methods and references.

Reporting Summary

Supplementary Data

Source data for Figs. 2–5, cluster analysis, trust data, adoption data, raw survey data, data map and data supporting the supplementary figures.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Hall, S., Anable, J., Hardy, J. et al. Matching consumer segments to innovative utility business models. Nat Energy 6, 349–361 (2021).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

Further reading


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing