Replication Data for: A Field Experiment on Workplace Norms and Electric Vehicle Charging Etiquettedoi:10.7910/DVN/NFPQLWHarvard Dataverse2020-07-301Asensio, Omar Isaac; Apablaza, Camila Z; Lawson, M. Cade; Walsh, Sarah Elizabeth, 2020, "Replication Data for: A Field Experiment on Workplace Norms and Electric Vehicle Charging Etiquette", https://doi.org/10.7910/DVN/NFPQLW, Harvard Dataverse, V1, UNF:6:yEP3Tbw1njAaGtmlGucEZg== [fileUNF]Replication Data for: A Field Experiment on Workplace Norms and Electric Vehicle Charging Etiquettedoi:10.7910/DVN/NFPQLWAsensio, Omar IsaacApablaza, Camila ZLawson, M. CadeWalsh, Sarah ElizabethHarvard DataverseAsensio, Omar IsaacAsensio, Omar Isaac2020-07-30Business and ManagementEarth and Environmental SciencesEngineeringSocial Scienceselectric vehicles, workplace charging, field experiments, sustainabilityThis dataset contains information from 3,395 high resolution electric vehicle charging sessions. The data contains sessions from 85 EV drivers with repeat usage at 105 stations across 25 sites at a workplace charging program. The workplace locations include facilities such as research and innovation centers, manufacturing, testing facilities and office headquarters for a firm participating in the U.S. Department of Energy (DOE) workplace charging challenge. The data is in a human and machine readable *.CSV format. The resolution of the data is to the nearest second, which is the same resolution as used in the analysis of the paper. It is directly importable into free software.event/transaction dataexperimental dataThe code, data definitions and protocols for scientific replication have been deposited to the Github repository https://github.com/asensio-lab/workplace-charging-experiment<a href="http://creativecommons.org/publicdomain/zero/1.0">CC0 1.0</a>station_data_dataverse.tab339524text/tab-separated-valuesUNF:6:yEP3Tbw1njAaGtmlGucEZg==This dataset contains information from 3,395 high resolution electric vehicle charging sessions. The data contains sessions from 85 EV drivers with repeat usage at 105 stations across 25 sites at a workplace charging program. The workplace locations include facilities such as research and innovation centers, manufacturing, testing facilities and office headquarters for a firm participating in the U.S. Department of Energy (DOE) workplace charging challenge. The data is in a human and machine readable *.CSV format. The resolution of the data is to the nearest second, which is the same resolution as used in the analysis of the paper. It is directly importable into free software. sessionId0.02590657.28190156779998981.05451498.01004821.03395.0.5487001.230338733UNF:6:EuHC7RGPZFTBPXWvJn7XCQ==kwhTotal3395.023.685.80962886597938160.02.89272724756535876.23.0.0UNF:6:SPvVBfYDKx3ozlKMazmgIg==dollars7.5.0.492561945852112943395.00.00.00.118268041237113490.0UNF:6:J/mE6+Jh2V4nHUoyr2vkJw==createdUNF:6:RD6bK6UWPFZ9dMpAU4aDhQ==endedUNF:6:BoO33bPQPT4ME6poVQDb4Q==startTime3395.00.0.13.74344624447719823.03.204369699882310.013.0UNF:6:22E/49OBDd0ur6qBr0vkDA==endTime3395.00.023.00.016.0.3.4067321611196616.455964653902786UNF:6:Erq0/jLeitAsjllrkU3Kig==chargeTimeHrs0.012555.238055561.50747191189612953395.02.8414876452270987.2.8088888890.0UNF:6:SR3cxhxeYLfAwGJPFFMo6Q==weekdayUNF:6:mwFiJ/ZAxp0ZOTmOgQlChA==platformUNF:6:l8ZshYHohi11eMeOe6BKUA==distance43.05929160.856910621.0238262.2330.011.4205709970839581065.018.652378180085847UNF:6:aC87gA2fBnSbJgFjFzOD4g==userId0.09.8345808E71.042767E7.2.6747715222316053E74.9241808E73395.05.742395346804128E7UNF:6:Vbn2X2PRvwdbR8TNX10q9w==stationId549414.0.257486.31040238755995505.00.0129465.0576789.67805596493395.0UNF:6:uLmZ8g4/pjhJ8LqTInDb9w==locationId503205.0978130.00.0255620.9938485955.629934.4606774693125372.03395.0UNF:6:6tGuwY0v7h/Fh/WpYhfayg==managerVehicle0.490851402176062550.59558173784977531.00.01.00.0.3395.0UNF:6:6ph67kjzq7Yzqg4uZF1r9Q==facilityType3.01.02.4285714285714280.0.3395.00.81120405853347064.0UNF:6:eFwiwLlvoqkik6NgDXpg9Q==Mon0.38544180920569421.00.03395.0.0.00.00.18144329896907216UNF:6:uzLs63MogtX5/JtCbHI7mQ==Tues.0.187039764359352020.00.00.03395.01.00.3900008875501081UNF:6:dOAGJbbqbAnkYs2OzG4zTA==Wed0.00.03395.00.40737872385587531.00.210014727540500880.0.UNF:6:4+v6zTC9mcGskJIaSBeS7Q==Thurs0.00.41191601710095250.00.00.216494845360825031.0.3395.0UNF:6:aDguX2vuHW+1VfQxwGRQRA==Fri0.00.0.1.03395.00.00.383973903580650260.17967599410898386UNF:6:F/sguVOhSSUOxNMj4B73ww==Sat1.00.133917611025634850.03395.00.00.018262150220913168.0.0UNF:6:kfCAeGuE83gCTXGHju1AOQ==Sun3395.01.0.0.00.00.083793279626106440.00706921944035348360.0UNF:6:AzH+n2BWwAOumin/6knrgg==reportedZip0.03395.00.45656873981522081.00.7039764359351948.0.01.0UNF:6:v0f/DTdVcZxivWrQzO7UmQ==