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Matching consumer segments to innovative utility business models

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

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Abstract

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.

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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.

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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.

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References

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

    Article  Google Scholar 

  2. Future Energy Scenarios (National Grid ESO, 2020); https://www.nationalgrideso.com/document/173821/download

  3. Retail Markets Monitoring Report CEER Report C17-MMR-83-02 (Council of European Energy Regulators, 2017): https://www.ceer.eu/documents/104400/-/-/56216063-66c8-0469-7aa0-9f321b196f9f

  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).

    Article  Google Scholar 

  5. Sen, A., Nepal, R. & Jamasb, T. Reforming Electricity Reforms? Empirical Evidence from Asian Economies (Oxford Institute for Energy Studies, 2016); https://www.oxfordenergy.org/wpcms/wp-content/uploads/2016/02/Reforming-Electricity-Reforms-Empirical-Evidence-from-Asian-Economies-EL-18.pdf

  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); https://www.pwc.com/gx/en/utilities/publications/assets/pwc-the-road-ahead.pdf

  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).

    Article  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).

    Article  Google Scholar 

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

    Article  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); http://projects.exeter.ac.uk/igov/report-analysis-of-uk-electricity-system-actors/

  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).

    Article  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).

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  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).

    Article  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).

    Article  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).

    Article  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).

    Article  Google Scholar 

  23. Williams, B. & Waring, G. Consumer Engagement In The Energy Market 2018: Report on a Survey of Energy Consumers (GfK, 2018); https://www.ofgem.gov.uk/system/files/docs/2018/10/consumer_engagement_survey_2018_report_0.pdf

  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).

    Article  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).

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  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).

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  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).

    Article  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).

    Article  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).

    Article  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).

    Article  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).

    Article  Google Scholar 

  38. Burnet, F. Take Charge: An Analysis of the Domestic Electric Vehicle Tariff Market (Citizens Advice, 2019); https://www.citizensadvice.org.uk/Global/CitizensAdvice/Energy/Take%20Charge%20-%20EV%20tariff%20report.pdf

  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).

    Article  Google Scholar 

  40. Retail Research into Customer Switching and Supply Disintermediation: Final Report: Disintermediation (ESP Consulting, 2018); https://www.ofgem.gov.uk/system/files/docs/2018/07/retail_research_-_report_on_supply_disintermediation.pdf

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

    Article  Google Scholar 

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

    Article  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).

    Article  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).

    Article  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).

    Article  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).

    Article  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).

    Article  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).

    Article  Google Scholar 

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

    Article  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).

    Article  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).

    Article  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).

    Article  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).

    Article  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).

    Article  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).

    Article  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).

    Article  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).

    Article  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); http://www.scotlandscensus.gov.uk/

  69. Census 2011 (Office of National Statistics, 2017); https://www.nomisweb.co.uk

  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).

    Article  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).

    Article  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).

    Article  Google Scholar 

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Acknowledgements

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).

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Authors and Affiliations

Authors

Contributions

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.

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The authors declare no competing interests.

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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.

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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.

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Hall, S., Anable, J., Hardy, J. et al. Matching consumer segments to innovative utility business models. Nat Energy 6, 349–361 (2021). https://doi.org/10.1038/s41560-021-00781-1

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