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[1] S. Clarke and L. Holdsworth, “Flexibility in the workplace: implications of flexible work arrangements for individuals, teams and organisations,” ACAS, 2017. [2] D. Leithead, “Flexibility in the workplace: A blessing or a curse?,” London, United Kingdom, 2019. [3] L. Lesnard and M. Y. Kan, “Investigating scheduling of work: a two-stage optimal matching analysis of workdays and workweeks,” J. R. Stat. Soc. Ser. A, vol. 174, no. 2, pp. 349–368, 2011. [4] E. Munch, “The irresistible peak-hour: Instrumental and axiological rationales of work hours’ synchronisation,” Transp. Res. Interdiscip. Perspect., vol. 3, Dec. 2019. [5] E. Munch, “Social norms on working hours and peak times in public transport,” Time Soc., vol. 29, no. 3, Aug. 2020. [6] F. Klein, S. Drews, I. Savin, and J. van den Bergh, “How work patterns affect leisure activities and energy consumption: A time-use analysis for Finland and France,” Energy Res. Soc. Sci., vol. 76, Jun. 2021. [7] UK Office for National Statistics [ONS], “Employment and Labour Market - Table EMP01 SA: Full-time, part-time and temporary workers (seasonally adjusted) [dataset],” 2020. [8] F. Friis and T. Haunstrup Christensen, “The challenge of time shifting energy demand practices: Insights from Denmark,” Energy Res. Soc. Sci., vol. 19, pp. 124–133, Sep. 2016. [9] International Energy Agency [IEA], “Global EV Outlook 2020,” Paris, France, Jun. 2020. [10] T. Boßmann and I. Staffell, “The shape of future electricity demand: Exploring load curves in 2050s Germany and Britain,” Energy, vol. 90, pp. 1317–1333, 2015. [11] R. Shi, S. Li, P. Zhang, and K. Y. Lee, “Integration of renewable energy sources and electric vehicles in V2G network with adjustable robust optimization,” Renew. Energy, vol. 153, pp. 1067–1080, Jun. 2020. [12] S. Carroll, C. Walsh, M. Burgess, M. Harris, S. N. King, and L. Bunce, “Assessing the viability of EVs in daily life,” 2013. [13] S. Hardman et al., “A review of consumer preferences of and interactions with electric vehicle charging infrastructure,” Transp. Res. Part D Transp. Environ., vol. 62, pp. 508–523, Jul. 2018. [14] J. H. M. Langbroek, J. P. Franklin, and Y. O. Susilo, “When do you charge your electric vehicle? A stated adaptation approach,” Energy Policy, vol. 108, pp. 565–573, Sep. 2017. [15] A. P. Robinson, P. T. Blythe, M. C. Bell, Y. Hübner, and G. A. Hill, “Analysis of electric vehicle driver recharging demand profiles and subsequent impacts on the carbon content of electric vehicle trips,” Energy Policy, vol. 61, pp. 337–348, Oct. 2013. [16] P. Morrissey, P. Weldon, and M. O’Mahony, “Future standard and fast charging infrastructure planning: An analysis of electric vehicle charging behaviour,” Energy Policy, vol. 89, Feb. 2016. [17] J. Torriti, “Understanding the timing of energy demand through time use data: Time of the day dependence of social practices,” Energy Res. Soc. Sci., vol. 25, pp. 37–47, Mar. 2017. [18] D. Southerton, “`Squeezing Time’: Allocating Practices, Coordinating Networks and Scheduling Society,” Time Soc., vol. 12, no. 1, pp. 5–25, Mar. 2003. [19] E. Shove, F. Trentmann, R. Wilk, F. Trentmann, and R. Wilk, Time, Consumption and Everyday Life. Routledge, 2009. [20] J. L. Ramírez-Mendiola, P. Grünewald, and N. Eyre, “Linking intra-day variations in residential electricity demand loads to consumers’ activities: What’s missing?,” Energy Build., vol. 161, pp. 63–71, Feb. 2018. [21] M. K. Gerritsma, T. A. AlSkaif, H. A. Fidder, and W. G. J. H. M. van Sark, “Flexibility of Electric Vehicle Demand: Analysis of Measured Charging Data and Simulation for the Future,” World Electr. Veh. J., vol. 10, no. 1, Mar. 2019. [22] UK Department for Transport [DfT], “National Travel Survey: England 2018,” 2019. [23] G. Walker, “The dynamics of energy demand: Change, rhythm and synchronicity,” Energy Res. Soc. Sci., vol. 1, pp. 49–55, Mar. 2014. [24] G. Mattioli, E. Shove, and J. Torriti, “The timing and societal synchronisation of energy demand. Working Paper.,” 2014. [25] M. Jalas, “The Everyday Life Context of Increasing Energy Demands: Time Use Survey Data in a Decomposition Analysis,” J. Ind. Ecol., vol. 9, no. 1–2, pp. 129–145, Feb. 2008. [26] E. Shove, “Converging Conventions of Comfort, Cleanliness and Convenience,” J. Consum. Policy, vol. 26, no. 4, pp. 395–418, Dec. 2003. [27] A. Warde, S.-L. Cheng, W. Olsen, and D. Southerton, “Changes in the Practice of Eating: A comparative analysis of Time-use,” Acta Sociol., vol. 50, no. 4, pp. 363–385, Dec. 2007. [28] S. Chatzitheochari and S. Arber, “Lack of sleep, work and the long hours culture: evidence from the UK Time Use Survey,” Work. Employ. Soc., vol. 23, no. 1, Mar. 2009. [29] B. Anderson and J. Torriti, “Explaining shifts in UK electricity demand using time use data from 1974 to 2014,” Energy Policy, vol. 123, pp. 544–557, Dec. 2018. [30] J. Torriti, “A review of time use models of residential electricity demand,” Renew. Sustain. Energy Rev., vol. 37, pp. 265–272, Sep. 2014. [31] P. Grünewald and M. Diakonova, “The specific contributions of activities to household electricity demand,” Energy Build., vol. 204, p. 109498, Dec. 2019. [32] A. Satre-Meloy, M. Diakonova, and P. Grünewald, “Cluster analysis and prediction of residential peak demand profiles using occupant activity data,” Appl. Energy, vol. 260, Feb. 2020. [33] T. Schwanen and M. Dijst, “Travel-time ratios for visits to the workplace: the relationship between commuting time and work duration,” Transp. Res. Part A Policy Pract., vol. 36, no. 7, pp. 573–592, Aug. 2002. [34] G. Mattioli, J. Anable, and K. Vrotsou, “Car dependent practices: Findings from a sequence pattern mining study of UK time use data,” Transp. Res. Part A Policy Pract., vol. 89, pp. 56–72, Jul. 2016. [35] J. L. Ramírez-Mendiola, P. Grünewald, and N. Eyre, “Residential activity pattern modelling through stochastic chains of variable memory length,” Appl. Energy, vol. 237, pp. 417–430, Mar. 2019. [36] J. Torriti, R. Hanna, B. Anderson, G. Yeboah, and A. Druckman, “Peak residential electricity demand and social practices: Deriving flexibility and greenhouse gas intensities from time use and locational data,” Indoor Built Environ., vol. 24, no. 7, pp. 891–912, Aug. 2015. [37] K. Ellegård, “A time-geographical approach to the study of everyday life of individuals – a challenge of complexity,” GeoJournal, vol. 48, no. 3, pp. 167–175, 1999. [38] L. Lesnard, “Optimal matching and social sciences - Working paper,” Obs. Sociol. du Chang. Lab. Sociol. Quant., 2006. [39] L. Lesnard, “Setting cost in optimal matching to uncover contemporaneous socio-temporal patterns,” Sociol. Methods Res., vol. 38, no. 3, pp. 389–419, 2010. [40] G. Mattioli, J. Anable, and P. Goodwin, “A week in the life of a car: a nuanced view of possible EV charging regimes,” in ECEEE Summer Study, 2019, pp. 1105–1116. [41] J. Gershuny and O. Sullivan, “United Kingdom Time Use Survey, 2014-2015. [data collection]. UK Data Service. SN: 8128,” 2017. [42] L. Kaufman and P. J. Rousseeuw, Finding groups in data : an introduction to cluster analysis. Wiley, 2005. [43] P. J. Rousseeuw, “Silhouettes: A graphical aid to the interpretation and validation of cluster analysis,” J. Comput. Appl. Math., vol. 20, pp. 53–65, Nov. 1987. [44] Elexon Ltd., “Electricity User Load Profiles by Profile Class,” 2021. [Online]. Available: https://www.elexon.co.uk/operations-settlement/profiling/. [Accessed: 08-Dec-2021]. [45] F. Crawford, “Segmenting travellers based on day-to-day variability in work-related travel behaviour,” J. Transp. Geogr., vol. 86, p. 102765, Jun. 2020. [46] J. L. Ramírez-Mendiola, P. Grünewald, and N. Eyre, “The diversity of residential electricity demand – A comparative analysis of metered and simulated data,” Energy Build., vol. 151, pp. 121–131, 2017. [47] UK Office for National Statistics [ONS], “Households and Household Composition in England and Wales: 2001-2011,” London, United Kingdom, 2014. [48] UK Office for National Statistics [ONS], “Distribution of median and mean income and tax by age range and gender,” 2020. [49] K. Qian, C. Zhou, M. Allan, and Y. Yuan, “Modeling of Load Demand Due to EV Battery Charging in Distribution Systems,” IEEE Trans. Power Syst., vol. 26, no. 2, pp. 802–810, May 2011. [50] J. Y. Yong, V. K. Ramachandaramurthy, K. M. Tan, and N. Mithulananthan, “A review on the state-of-the-art technologies of electric vehicle, its impacts and prospects,” Renew. Sustain. Energy Rev., vol. 49, Sep. 2015. [51] K. H. Jansen, T. M. Brown, and G. S. Samuelsen, “Emissions impacts of plug-in hybrid electric vehicle deployment on the U.S. western grid,” J. Power Sources, vol. 195, pp. 5409–5416, 2010. [52] R. McCarthy and C. Yang, “Determining marginal electricity for near-term plug-in and fuel cell vehicle demands in California: Impacts on vehicle greenhouse gas emissions,” J. Power Sources, vol. 195, no. 7, pp. 2099–2109, Apr. 2010. [53] B. K. Sovacool and R. F. Hirsh, “Beyond batteries: An examination of the benefits and barriers to plug-in hybrid electric vehicles (PHEVs) and a vehicle-to-grid (V2G) transition,” Energy Policy, vol. 37, no. 3, pp. 1095–1103, Mar. 2009. [54] J. Anable, “‘Complacent Car Addicts’ or ‘Aspiring Environmentalists’? Identifying travel behaviour segments using attitude theory,” Transp. Policy, vol. 12, no. 1, pp. 65–78, Jan. 2005. [55] D. Aerts, J. Minnen, I. Glorieux, I. Wouters, and F. Descamps, “A method for the identification and modelling of realistic domestic occupancy sequences for building energy demand simulations and peer comparison,” Build. Environ., vol. 75, pp. 67–78, May 2014. [56] R. Galvin and M. Sunikka-Blank, “Schatzkian practice theory and energy consumption research: Time for some philosophical spring cleaning?,” Energy Res. Soc. Sci., vol. 22, pp. 63–68, Dec. 2016. [57] J. Palm, K. Ellegård, and M. Hellgren, “A cluster analysis of energy-consuming activities in everyday life,” Build. Res. Inf., vol. 46, no. 1, pp. 99–113, Jan. 2018. [58] D. Southerton and M. Tomlinson, “‘Pressed for Time’ – the Differential Impacts of a ‘Time Squeeze,’” Sociol. Rev., vol. 53, no. 2, pp. 215–239, May 2005.