1932

Abstract

Digitalization has opened up a wealth of new goods and services with strong consumer appeal alongside potential emission-reduction benefits. Examples range from shared, on-demand electric mobility and peer-to-peer trading of electricity, food, and cars to grid-responsive smart appliances and heating systems. In this review, we identify an illustrative sample of 33 digital consumer innovations that challenge emission-intensive mainstream consumption practices in mobility, food, homes, and energy domains. Across these domains, digital innovations offer consumers a range of potentially appealing attributes from control, choice, and convenience to independence, interconnectedness, and integration with systems. We then compile quantitative estimates of change in activity, energy, or emissions as a result of consumers adopting digital innovations. This novel synthesis of the evidence base shows clear but variable potential emission-reduction benefits of digital consumer innovations. However, a small number of studies show emission increases from specific innovations as a result of induced demand or substitution effects that need careful management by public policy. We also consider how concurrent adoption of digital consumer innovations across mobility, food, homes, and energy domains can cause broader disruptive impacts on regulatory frameworks, norms, and infrastructures. We conclude by arguing for the importance of public policy in steering the digitalization of consumer goods and services toward low-carbon outcomes.

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2020-10-17
2024-03-28
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Literature Cited

  1. 1. 
    Int. Gov. Panel Clim. Change (IPCC) 2014. Summary for policymakers. Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change O Edenhofer, R Pichs-Madruga, Y Sokona, E Farahani, S Kadner et al.1–30 Cambridge, UK/New York: Cambridge Univ. Press
    [Google Scholar]
  2. 2. 
    Ivanova D, Stadler K, Steen-Olsen K, Wood R, Vita G et al. 2016. Environmental impact assessment of household consumption. J. Ind. Ecol. 20:526–36
    [Google Scholar]
  3. 3. 
    Allwood JM, Dunant CF, Luptoin RC, Cleaver CJ, Serrenho ACH et al. 2019. Absolute Zero: Delivering the UK's Climate Change Commitment with Incremental Changes to Today's Technologies. Cambridge, UK: Univ. Cambridge
    [Google Scholar]
  4. 4. 
    Moran D, Wood R, Hertwich E, Mattson K, Rodriguez JFD et al. 2020. Quantifying the potential for consumer-oriented policy to reduce European and foreign carbon emissions. Climate Policy 20:S28–38
    [Google Scholar]
  5. 5. 
    van de Ven D-J, González-Eguino M, Arto I 2017. The potential of behavioural change for climate change mitigation: a case study for the European Union. Mitig. Adapt. Strateg. Glob. Change 23:853–86
    [Google Scholar]
  6. 6. 
    Brown D, Hall S, Davis ME 2019. Prosumers in the post subsidy era: an exploration of new prosumer business models in the UK. Energy Policy 135:110984
    [Google Scholar]
  7. 7. 
    Schot J, Kanger L, Verbong G 2016. The roles of users in shaping transitions to new energy systems. Nat. Energy 1:16054
    [Google Scholar]
  8. 8. 
    Socolow RH. 1978. Saving Energy in the Home: Princeton's Experiments at Twin Rivers Cambridge, MA: Ballinger
  9. 9. 
    Gardner GT, Stern P. 1995. Environmental Problems and Human Behavior Boston: Allyn & Bacon
  10. 10. 
    Stern PC. 2002. Changing behavior in households and communities: What have we learned?. New Tools for Environmental Protection: Education, Information, and Voluntary Measures T Dietz, PC Stern 201–11 Washington, DC: Nat. Acad. Press
    [Google Scholar]
  11. 11. 
    Stern PC, Janda KB, Brown MA, Steg L, Vine EL, Lutzenhiser L 2016. Opportunities and insights for reducing fossil fuel consumption by households and organizations. Nat. Energy 1:16043
    [Google Scholar]
  12. 12. 
    Dietz T, Gardner GT, Gilligan J, Stern PC, Vandenbergh MP 2009. Household actions can provide a behavioral wedge to rapidly reduce US carbon emissions. PNAS 106:18452–56
    [Google Scholar]
  13. 13. 
    Creutzig F, Fernandez B, Haberl H, Khosla R, Mulugetta Y, Seto KC 2016. Beyond technology: demand-side solutions for climate change mitigation. Annu. Rev. Environ. Resour. 41:173–98
    [Google Scholar]
  14. 14. 
    Grubler A, Wilson C, Bento N, Boza-Kiss B, Krey V et al. 2018. A low energy demand scenario for meeting the 1.5°C target and sustainable development goals without negative emission technologies. Nat. Energy 3:515–27
    [Google Scholar]
  15. 15. 
    Ger. Advis. Counc. Glob. Change (WBGU) 2019. Towards our common digital future Rep., WBGU, Berlin, Ger.
  16. 16. 
    The World in 2050 (TWI2050) 2019. The Digital Revolution and sustainable development: opportunities and challenges Rep., Int. Inst. Appl. Syst. Anal. (IIASA), Laxenburg Austria:
  17. 17. 
    Frenken K. 2017. Political economies and environmental futures for the sharing economy. Philos. Trans. R. Soc. A 375:20160367
    [Google Scholar]
  18. 18. 
    Benkler Y. 2004. Sharing nicely: on shareable goods and the emergence of sharing as a modality of economic production. Yale Law J 114:273–358
    [Google Scholar]
  19. 19. 
    Acquier A, Daudigeos T, Pinkse J 2017. Promises and paradoxes of the sharing economy: an organizing framework. Technol. Forecast. Soc. Change 125:1–10
    [Google Scholar]
  20. 20. 
    Schuelke-Leech B-A. 2018. A model for understanding the orders of magnitude of disruptive technologies. Technol. Forecast. Soc. Change 129:261–74
    [Google Scholar]
  21. 21. 
    Kelly K. 2017. The Inevitable: Understanding the 12 Technological Forces that will Shape our Future. New York: Viking
    [Google Scholar]
  22. 22. 
    McKinsey & Co 2013. Disruptive technologies: advances that will transform life, business, and the global economy Rep., McKinsey Glob. Inst., San Francisco. https://www.mckinsey.com/∼/media/McKinsey/Business%20Functions/McKinsey%20Digital/Our%20Insights/Disruptive%20technologies/MGI_Disruptive_technologies_Full_report_May2013.pdf
  23. 23. 
    Kamargianni M, Li W, Matyas M, Schäfer A 2016. A critical review of new mobility services for urban transport. Transp. Res. Procedia 14:3294–303
    [Google Scholar]
  24. 24. 
    Int. Transp. Forum (ITF) 2016. Shared Mobility: Innovation for Liveable Cities Paris: ITF
  25. 25. 
    Richards TJ, Hamilton SF. 2018. Food waste in the sharing economy. Food Policy 75:109–23
    [Google Scholar]
  26. 26. 
    Harvey J, Smith A, Goulding J, Branco Illodo I 2020. Food sharing, redistribution, and waste reduction via mobile applications: a social network analysis. Ind. Mark. Manag. 88:43748
    [Google Scholar]
  27. 27. 
    Hargreaves T, Wilson C. 2017. Smart Homes and Their Users London: Springer
  28. 28. 
    Park E, Kim S, Kim Y, Kwon SJ 2018. Smart home services as the next mainstream of the ICT industry: determinants of the adoption of smart home services. Univers. Access Inf. Soc. 17:175–90
    [Google Scholar]
  29. 29. 
    Yang H, Lee W, Lee H 2018. IoT smart home adoption: the importance of proper level automation. J. Sens. 2018:6464036
    [Google Scholar]
  30. 30. 
    Int. Energy Agency (IEA) 2017. Digitalization and Energy Paris: IEA
  31. 31. 
    Burger SP, Luke M. 2017. Business models for distributed energy resources: a review and empirical analysis. Energy Policy 109:230–48
    [Google Scholar]
  32. 32. 
    Pettifor H, Wilson C, Bogelein S, Cassar E, Kerr L, Wilson M 2020. Are low-carbon innovations appealing? A typology of functional, symbolic, private and public attributes. Energy Res. Soc. Sci. 64:101422
    [Google Scholar]
  33. 33. 
    Nagy D, Schuessler J, Dubinsky A 2016. Defining and identifying disruptive innovations. Ind. Mark. Manag. 57:119–26
    [Google Scholar]
  34. 34. 
    Tellis GJ. 2006. Disruptive technology or visionary leadership. J. Prod. Innov. Manag. 23:34–38
    [Google Scholar]
  35. 35. 
    Govindarajan V, Kopalle PK. 2006. Disruptiveness of innovations: measurement and an assessment of reliability and validity. Strateg. Manag. J. 27:189–99
    [Google Scholar]
  36. 36. 
    Rogers EM. 2003. Diffusion of Innovations New York: Free Press
  37. 37. 
    Dotsika F, Watkins A. 2017. Identifying potentially disruptive trends by means of keyword network analysis. Technol. Forecast. Soc. Change 119:114–27
    [Google Scholar]
  38. 38. 
    Yan Z, Du K, Yang Z, Deng M 2017. Convergence or divergence? Understanding the global development trend of low-carbon technologies. Energy Policy 109:499–509
    [Google Scholar]
  39. 39. 
    Momeni A, Rost K. 2016. Identification and monitoring of possible disruptive technologies by patent-development paths and topic modeling. Technol. Forecast. Soc. Change 104:16–29
    [Google Scholar]
  40. 40. 
    Popp D. 2005. Lessons from patents: using patents to measure technological change in environmental models. Ecol. Econ. 54:209–26
    [Google Scholar]
  41. 41. 
    Kilkki K, Mäntylä M, Karhu K, Hämmäinen H, Ailisto H 2018. A disruption framework. Technol. Forecast. Soc. Change 129:275–84
    [Google Scholar]
  42. 42. 
    Martin E, Shaheen S. 2016. Impacts of car2go on vehicle ownership, modal shift, vehicle miles traveled, and greenhouse gas emissions: an analysis of five North American cities Work. Pap., Transp. Sustain. Res. Cent Berkeley, CA: https://tsrc.berkeley.edu/publications/impacts-car2go-vehicle-ownership-modal-shift-vehicle-miles-traveled-and-greenhouse-gas
  43. 43. 
    Nijland H, van Meerkerk J 2017. Mobility and environmental impacts of car sharing in the Netherlands. Environ. Innov. Soc. Transit. 23:84–91
    [Google Scholar]
  44. 44. 
    Jacobson SH, King DM. 2009. Fuel saving and ridesharing in the US: motivations, limitations, and opportunities. Transp. Res. Part D 14:14–21
    [Google Scholar]
  45. 45. 
    Canals Casals L, Martinez-Laserna E, Amante García B, Nieto N 2016. Sustainability analysis of the electric vehicle use in Europe for CO2 emissions reduction. J. Cleaner Prod. 127:425–37
    [Google Scholar]
  46. 46. 
    Hiselius LW, Svensson Å 2017. E-bike use in Sweden—CO2 effects due to modal change and municipal promotion strategies. J. Cleaner Prod. 141:818–24
    [Google Scholar]
  47. 47. 
    Bauer GS, Greenblatt JB, Gerke BF 2018. Cost, energy, and environmental impact of automated electric taxi fleets in Manhattan. Environ. Sci. Technol. 52:4920–28
    [Google Scholar]
  48. 48. 
    Harvard Business Review 2015. Tesla's not as disruptive as you might think. Harvard Bus. Rev. May 2015:22–23
    [Google Scholar]
  49. 49. 
    Zhang Y, Mi Z. 2018. Environmental benefits of bike sharing: a big data-based analysis. Appl. Energy 220:296–301
    [Google Scholar]
  50. 50. 
    Kim S-N. 2017. Is telecommuting sustainable? An alternative approach to estimating the impact of home-based telecommuting on household travel. Int. J. Sustain. Transp. 11:72–85
    [Google Scholar]
  51. 51. 
    Guerin TF. 2017. A demonstration of how virtual meetings can enhance sustainability in a corporate context. Environ. Q. Manag. 27:75–81
    [Google Scholar]
  52. 52. 
    Heard BR, Bandekar M, Vassar B, Miller SA 2019. Comparison of life cycle environmental impacts from meal kits and grocery store meals. Resour. Conserv. Recycl. 147:189–200
    [Google Scholar]
  53. 53. 
    Davies AR, Legg R. 2018. Fare sharing: interrogating the nexus of ICT, urban food sharing, and sustainability. Food, Cult. Soc. 21:233–54
    [Google Scholar]
  54. 54. 
    Sullivan RK, Marsh S, Halvarsson J, Holdsworth M, Waterlander W et al. 2016. Smartphone apps for measuring human health and climate change co-benefits: a comparison and quality rating of available apps. JMIR mHealth uHealth 4:e135
    [Google Scholar]
  55. 55. 
    Behav. Insights Team (BIT) 2017. Evaluating the Nest Learning Thermostat. Rep., BIT London:
  56. 56. 
    Laidi R, Djenouri D, Ringel M 2019. Commercial technologies for advanced light control in smart building energy management systems: a comparative study. Energy Power Eng 11:283–302
    [Google Scholar]
  57. 57. 
    Hsu CL, Lin JCC. 2016. An empirical examination of consumer adoption of Internet of Things services: network externalities and concern for information privacy perspectives. Comput. Hum. Behav. 62:516–27
    [Google Scholar]
  58. 58. 
    Beaudin M, Zareipour H. 2015. Home energy management systems: a review of modelling and complexity. Renew. Sustain. Energy Rev. 45:318–35
    [Google Scholar]
  59. 59. 
    Sivasakthivel T, Murugesan K, Sahoo PK 2014. A study on energy and CO2 saving potential of ground source heat pump system in India. Renew. Sustain. Energy Rev. 32:278–93
    [Google Scholar]
  60. 60. 
    Jacobs P, Leidelmeijer K, Borsboom W, van Vliet M, de Jong P 2015. Energiesprong: Transition Zero Rep., Energiesprong, The Hague, Neth.
  61. 61. 
    Fremstad A. 2017. Does Craigslist reduce waste? Evidence from California and Florida. Ecol. Econ. 132:135–43
    [Google Scholar]
  62. 62. 
    Kelly J, Knottenbelt W. 2016. Does disaggregated electricity feedback reduce domestic electricity consumption? A systematic review of the literature Paper presented at the 3rd International NILM Workshop Vancouver, BC: Canada, May 14–15
  63. 63. 
    Fares RL, Webber ME. 2017. The impacts of storing solar energy in the home to reduce reliance on the utility. Nat. Energy 2:17001
    [Google Scholar]
  64. 64. 
    Morstyn T, Farrell N, Darby SJ, McCulloch MD 2018. Using peer-to-peer energy-trading platforms to incentivize prosumers to form federated power plants. Nat. Energy 3:94–101
    [Google Scholar]
  65. 65. 
    Mwasilu F, Justo JJ, Kim EK, Do TD, Jung JW 2014. Electric vehicles and smart grid interaction: a review on vehicle to grid and renewable energy sources integration. Renew. Sustain. Energy Rev. 34:501–16
    [Google Scholar]
  66. 66. 
    Andersen LM, Hansen LG, Lynge Jensen C, Wolak FA 2017. Using real-time pricing and information provision to shift intra-day electricity consumption: evidence from Denmark Work. Pap., Dep. Econ., Stanf. Univ Stanf., CA: https://web.stanford.edu/group/fwolak/cgi-bin/sites/default/files/into_versus_away_paper.pdf
  67. 67. 
    Srivastava A, Van Passel S, Laes E 2018. Assessing the success of electricity demand response programs: a meta-analysis. Energy Res. Soc. Sci. 40:110–17
    [Google Scholar]
  68. 68. 
    Winther T, Gurigard K. 2017. Energy performance contracting (EPC): a suitable mechanism for achieving energy savings in housing cooperatives? Results from a Norwegian pilot project. Energy Effic 10:577–96
    [Google Scholar]
  69. 69. 
    Overholm H. 2015. Spreading the rooftop revolution: What policies enable solar-as-a-service. Energy Policy 84:69–79
    [Google Scholar]
  70. 70. 
    Creutzig F, Roy J, Lamb WF, Azevedo IML, Bruine de Bruin W et al. 2018. Towards demand-side solutions for mitigating climate change. Nat. Clim. Change 8:268–71
    [Google Scholar]
  71. 71. 
    Cramer J, Krueger AB. 2016. Disruptive change in the taxi business: the case of Uber. Am. Econ. Rev. 106:177–82
    [Google Scholar]
  72. 72. 
    King AA, Baatartogtokh B. 2015. How useful is the theory of disruptive innovation. MIT Sloan Manag. Rev. 57:77
    [Google Scholar]
  73. 73. 
    Ward JW, Michalek JJ, Azevedo IL, Samaras C, Ferreira P 2019. Effects of on-demand ridesourcing on vehicle ownership, fuel consumption, vehicle miles traveled, and emissions per capita in U.S. states. Transp. Res. Part C 108:289–301
    [Google Scholar]
  74. 74. 
    Clewlow RR, Mishra GS. 2017. Disruptive transportation: the adoption, utilization, and impacts of ride-hailing in the United States Rep. UCD-ITS-RR-17-07, Inst. Transp. Stud., Univ. Calif., Davis
  75. 75. 
    Rayle L, Dai D, Chan N, Cervero R, Shaheen S 2016. Just a better taxi? A survey-based comparison of taxis, transit, and ridesourcing services in San Francisco. Transp. Policy 45:168–78
    [Google Scholar]
  76. 76. 
    Erhardt GD, Roy S, Cooper D, Sana B, Chen M, Castiglione J 2019. Do transportation network companies decrease or increase congestion. Sci. Adv. 5:eaau2670
    [Google Scholar]
  77. 77. 
    Cheris A, Taylor C, Hayes J, Davis-Peccoud J 2017. Retailers’ Challenge: How to Cut Carbon Emissions as E-Commerce Soars San Francisco: Bain & Co.
  78. 78. 
    Goodchild A, Toy J. 2018. Delivery by drone: an evaluation of unmanned aerial vehicle technology in reducing CO2 emissions in the delivery service industry. Transp. Res. D 61:58–67
    [Google Scholar]
  79. 79. 
    Stolaroff JK, Samaras C, O'Neill ER, Lubers A, Mitchell AS, Ceperley D 2018. Energy use and life cycle greenhouse gas emissions of drones for commercial package delivery. Nat. Commun. 9:409
    [Google Scholar]
  80. 80. 
    Fulton L, Mason J, Meroux D 2017. Three revolutions in urban transportation: how to achieve the full potential of vehicle electrification, automation, and shared mobility in urban transportation systems around the world by 2050 Rep., Inst. Transp. Stud., Univ. Calif., Davis
  81. 81. 
    Baptista P, Melo S, Rolim C 2014. Energy, environmental and mobility impacts of car-sharing systems. Empirical results from Lisbon, Portugal. Procedia Soc. Behav. Sci. 111:28–37
    [Google Scholar]
  82. 82. 
    Bardhi F, Eckhardt GM. 2012. Access-based consumption: the case of car sharing. J. Consum. Res. 39:881–98
    [Google Scholar]
  83. 83. 
    Lane C. 2005. PhillyCarShare: first-year social and mobility impacts of carsharing in Philadelphia, Pennsylvania. Transp. Res. Rec. 1927:158–66
    [Google Scholar]
  84. 84. 
    Sprei F, Ginnebaugh D. 2015. Can car sharing facilitate a more sustainable car purchase? Paper presented at the Summer Study of the European Council for an Energy Efficient Economy (ECEEE), Toulon/Hyeres France: Jun 1–6
  85. 85. 
    McKinsey & Co 2016. Automotive revolution—perspective towards 2030: how the convergence of disruptive technology-driven trends could transform the auto industry Rep., McKinsey & Co., San Francisco. https://www.mckinsey.com/industries/automotive-and-assembly/our-insights/disruptive-trends-that-will-transform-the-auto-industry/de-de
  86. 86. 
    Hughes T. 2017. The effect of ride-sharing on the auto industry. Moody's Anal. Risk Perspect. 9:16–21
    [Google Scholar]
  87. 87. 
    Yu A, Wei Y, Chen W, Peng N, Peng L 2018. Life cycle environmental impacts and carbon emissions: a case study of electric and gasoline vehicles in China. Transp. Res. Part D 65:409–20
    [Google Scholar]
  88. 88. 
    Ling Z, Cherry CR, Yang H 2019. Emerging mini electric cars in China: user experience and policy implications. Transp. Res. Part D 69:293–304
    [Google Scholar]
  89. 89. 
    O'Keefe P, Caulfield B, Brazil W, White P 2016. The impacts of telecommuting in Dublin. Res. Transp. Econ. 57:13–20
    [Google Scholar]
  90. 90. 
    Wadud Z, MacKenzie D, Leiby P 2016. Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles. Transp. Res. A: Policy Pract. 86:1–18
    [Google Scholar]
  91. 91. 
    Bullock C, Brereton F, Bailey S 2017. The economic contribution of public bike-share to the sustainability and efficient functioning of cities. Sustain. Cities Soc. 28:76–87
    [Google Scholar]
  92. 92. 
    Bajzelj B, McManus W, Parry A 2019. Food Waste in Primary Production in the UK Banbury, UK: Waste Resour. Action Progr.
  93. 93. 
    Ipsos Mori 2016. Poll conducted for The Vegan Society—incidence of vegans research Rep., Ipsos Mori, London:
  94. 94. 
    Ferguson D. 2019. Food waste: how to get cheap grub and help save the planet. The Guardian July 6. https://www.theguardian.com/environment/2019/jul/06/food-waste-how-to-get-cheap-grub-and-help-save-the-planet
    [Google Scholar]
  95. 95. 
    Jungbluth N, Keller R, König A 2016. ONE TWO WE—life cycle management in canteens together with suppliers, customers and guests. Int. J. Life Cycle Assess. 21:646–53
    [Google Scholar]
  96. 96. 
    Kurnia S, Hill S, Rahim MM, Larsen K, Braun P, Samson D 2015. Open Food Network: the role of ICT to support regional food supply chains in Australia. arXiv:1606.01456 [cs.CY]
  97. 97. 
    Kurnia S, Rahim MM, Hill S, Larsen K, Braun P et al. 2017. Supporting regional food supply chains with an e-commerce application. Social Inclusion and Usability of ICT-Enabled Services J Choudri, P Tsatsou, S Kurnia 1–19 New York: Routledge
    [Google Scholar]
  98. 98. 
    McFarland K, Wittmayer JM. 2017. Hitting a policy wall: the transformative potential and limitations of community pick-up point schemes. Social Innovation and Sustainable Consumption ed. J Backhaus, A Genus, S Lorek, E Vadovics, JM Wittmayer, 72–85 London: Routledge
    [Google Scholar]
  99. 99. 
    Pérez-Neira D, Grollmus-Venegas A. 2018. Life-cycle energy assessment and carbon footprint of peri-urban horticulture. A comparative case study of local food systems in Spain. Landsc. Urban Plann. 172:60–68
    [Google Scholar]
  100. 100. 
    Fawcett T. 2014. Exploring the time dimension of low carbon retrofit: owner-occupied housing. Build. Res. Inf. 42:477–88
    [Google Scholar]
  101. 101. 
    Stuart E, Carvallo JP, Larsen PH, Goldman CA, Gilligan D 2018. Understanding recent market trends of the US ESCO industry. Energy Effic 11:1303–24
    [Google Scholar]
  102. 102. 
    Int. Energy Agency (IEA) 2018. Energy Efficiency Market Report Paris: IEA
  103. 103. 
    Hittinger E, Jaramillo P. 2019. Internet of things: Energy boon or bane. Science 364:326–28
    [Google Scholar]
  104. 104. 
    Coskun A, Kaner G, Bostan İ 2018. Is smart home a necessity or a fantasy for the mainstream user? A study on users’ expectations of smart household appliances. Int. J. Des. 12:7–20
    [Google Scholar]
  105. 105. 
    Moore S. 2016. The Disrupted Decade: 4 Disruptions that Will Shake Things Up for Energy Consumers London: Citiz. Advice
  106. 106. 
    Böcker L, Meelen T. 2017. Sharing for people, planet or profit? Analysing motivations for intended sharing economy participation. Environ. Innov. Soc. Transit. 23:28–39
    [Google Scholar]
  107. 107. 
    Spang ES, Moreno LC, Pace SA, Achmon Y, Donis-Gonzalez I et al. 2019. Food loss and waste: measurement, drivers, and solutions. Annu. Rev. Environ. Resour. 44:117–56
    [Google Scholar]
  108. 108. 
    Geissinger A, Laurell C, Sandström C 2020. Digital disruption beyond Uber and Airbnb—tracking the long tail of the sharing economy. Technol. Forecast. Soc. Change 155:119323
    [Google Scholar]
  109. 109. 
    Hargreaves T, Wilson C. 2017. Control of smart home technologies. See Ref 2791–105
  110. 110. 
    Lamberton CP, Rose RL. 2012. When is ours better than mine? A framework for understanding and altering participation in commercial sharing systems. J. Mark. 76:109–25
    [Google Scholar]
  111. 111. 
    Wilson C, Crane L, Chryssochoidis G 2015. Why do homeowners renovate energy efficiently? Contrasting perspectives and implications for policy. Energy Res. Soc. Sci. 7:12–22
    [Google Scholar]
  112. 112. 
    Schanes K, Stagl S. 2019. Food waste fighters: What motivates people to engage in food sharing. J. Cleaner Prod. 211:1491–501
    [Google Scholar]
  113. 113. 
    Wainstein ME, Bumpus AG. 2016. Business models as drivers of the low carbon power system transition: a multi-level perspective. J. Cleaner Prod. 126:572–85
    [Google Scholar]
  114. 114. 
    Bocken NMP, Short SW, Rana P, Evans S 2014. A literature and practice review to develop sustainable business model archetypes. J. Cleaner Prod. 65:42–56
    [Google Scholar]
  115. 115. 
    Bonilla-Alicea RJ, Watson BC, Shen Z, Tamayo L, Telenko C 2020. Life cycle assessment to quantify the impact of technology improvements in bike-sharing systems. J. Ind. Ecol. 24:138–48
    [Google Scholar]
  116. 116. 
    Adner R. 2002. When are technologies disruptive? A demand-based view of the emergence of competition. Strateg. Manag. J. 23:667–88
    [Google Scholar]
  117. 117. 
    Roy R. 2018. Role of relevant lead users of mainstream product in the emergence of disruptive innovation. Technol. Forecast. Soc. Change 129:314–22
    [Google Scholar]
  118. 118. 
    Urry J. 2014. The problem of energy. Theory Cult. Soc. 31:3–20
    [Google Scholar]
  119. 119. 
    Greenblatt JB, Saxena S. 2015. Autonomous taxis could greatly reduce greenhouse-gas emissions of US light-duty vehicles. Nat. Clim. Change 5:860–63
    [Google Scholar]
  120. 120. 
    Int. Transp. Forum (ITF) 2015. Urban Mobility System Upgrade: How Shared Self-Driving Cars Could Change City Traffic Paris: ITF
  121. 121. 
    Lister K, Harnish T. 2011. The Shifting Nature of Work in the UK: Bottom Line Benefits of Telework San Diego, CA: Telework Res. Netw.
  122. 122. 
    Seto KC, Davis SJ, Mitchell RB, Stokes EC, Unruh G, Ürge-Vorsatz D 2016. Carbon lock-in: types, causes, and policy implications. Annu. Rev. Environ. Resour. 41:425–52
    [Google Scholar]
  123. 123. 
    Geels FW, Sovacool BK, Schwanen T, Sorrell S 2017. Sociotechnical transitions for deep decarbonization. Science 357:124244
    [Google Scholar]
  124. 124. 
    Geels FW. 2018. Disruption and low-carbon system transformation: progress and new challenges in socio-technical transitions research and the Multi-Level Perspective. Energy Res. Soc. Sci. 37:224–31
    [Google Scholar]
  125. 125. 
    Urry J. 2008. Governance, flows, and the end of the car system. Global Environ. Change 18:343–49
    [Google Scholar]
  126. 126. 
    Lund H, Kempton W. 2008. Integration of renewable energy into the transport and electricity sectors through V2G. Energy Policy 36:3578–87
    [Google Scholar]
  127. 127. 
    Sprei F. 2018. Disrupting mobility. Energy Res. Soc. Sci. 37:238–42
    [Google Scholar]
  128. 128. 
    Marikyan D, Papagiannidis S, Alamanos E 2019. A systematic review of the smart home literature: a user perspective. Technol. Forecast. Soc. Change 138:139–54
    [Google Scholar]
  129. 129. 
    Wilson C, Hargreaves T, Hauxwell-Baldwin R 2017. Benefits and risks of smart home technologies. Energy Policy 103:72–83
    [Google Scholar]
  130. 130. 
    Crowley J, Coutaz J. 2015. An ecological view of smart home technologies. Ambient Intelligence: 12th European Conference, AmI 2015, Athens, Greece, November 11–13, 2015, Proceedings B de Ruyter, A Kameas, P Chatzimisios, I Mavrommati 372–72 Cham, Switz: Springer
    [Google Scholar]
  131. 131. 
    Porter ME, Heppelmann JE. 2014. How smart, connected products are transforming competition. Harvard Bus. Rev. 92:6488
    [Google Scholar]
  132. 132. 
    Ford R, Pritoni M, Sanguinetti A, Karlin B 2017. Categories and functionality of smart home technology for energy management. Build. Environ. 123:543–54
    [Google Scholar]
  133. 133. 
    Seba T. 2014. Clean Disruption of Energy and Transportation Silicon Valley, CA: Clean Planet Ventur.
  134. 134. 
    van den Broek T, van Veenstra AF 2018. Governance of big data collaborations: how to balance regulatory compliance and disruptive innovation. Technol. Forecast. Soc. Change 129:330–38
    [Google Scholar]
  135. 135. 
    Graffy E, Kihm S. 2014. Does disruptive competition mean a death spiral for electric utilities. Energy Law J 35:1–44
    [Google Scholar]
  136. 136. 
    Morrow O. 2019. Sharing food and risk in Berlin's urban food commons. Geoforum 99:202–12
    [Google Scholar]
  137. 137. 
    Chies BM. 2017. Turning food “waste” into a commons. The case of Foodsharing (Germany) and Solidarity Fridge (Sweden). Proceedings of the XVI Biennal IASC-Conference (Practicing the Commons: Self-Governance, Cooperation and Institutional Change), Utrecht, The Netherlands, July 10–14. https://www.iasc2017.org/wp-content/uploads/2017/07/chies.pdf
    [Google Scholar]
  138. 138. 
    Int. Smart Grid Action Netw. (ISGAN) 2019. Smart grid case studies: innovative regulatory approaches with focus on experimental sandboxes Rep., Int. Energy Agency Paris:
  139. 139. 
    Creutzig F, Franzen M, Moeckel R, Heinrichs D, Nagel K et al. 2019. Leveraging digitalization for sustainability in urban transport. Glob. Sustain. 2:e14
    [Google Scholar]
  140. 140. 
    Cooper R, Timmer V. 2015. Local Governments and the Sharing Economy: A Roadmap Helping Local Governments Across North America Strategically Engage with the Sharing Economy to Foster More Sustainable Cities Vancouver, BC: One Earth
  141. 141. 
    Int. Transp. Forum (ITF) 2017. Shared Mobility: Simulations for Auckland Paris: ITF
  142. 142. 
    Kramer GJ. 2018. Energy scenarios—exploring disruption and innovation. Energy Res. Soc. Sci. 37:247–50
    [Google Scholar]
  143. 143. 
    Chrisafis A. 2016. French law forbids food waste by supermarkets. The Guardian Febr. 4. https://www.theguardian.com/world/2016/feb/04/french-law-forbids-food-waste-by-supermarkets
    [Google Scholar]
  144. 144. 
    Sprei F, Ginnebaugh D. 2018. Unbundling cars to daily use and infrequent use vehicles—the potential role of car sharing. Energy Effic 11:1433–47
    [Google Scholar]
  145. 145. 
    Leibowicz BD. 2018. Policy recommendations for a transition to sustainable mobility based on historical diffusion dynamics of transport systems. Energy Policy 119:357–66
    [Google Scholar]
  146. 146. 
    Millar C, Lockett M, Ladd T 2018. Disruption: technology, innovation and society. Technol. Forecast. Soc. Change 129:254–60
    [Google Scholar]
  147. 147. 
    Sochor J, Strömberg H, Karlsson ICM 2015. Implementing mobility as a service: challenges in integrating user, commercial, and societal perspectives. Transp. Res. Rec. 2536:1–9
    [Google Scholar]
  148. 148. 
    Wilson C. 2018. Disruptive low-carbon innovations. Energy Res. Soc. Sci. 37:216–23
    [Google Scholar]
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