2026-10-14 https://api.researchdata.se/oai-pmh

oai:researchdata.se:doi-10-17045-sthlmuni-23703327/0 2023-07-19 subject:ssif:20105 subject:ssif:201 subject:ssif:2 principal:slug:stockholm-university

info:eu-repo/semantics/other http://purl.org/dc/dcmitype/Dataset https://doi.org/10.17045/STHLMUNI.23703327 Dataset for: Which Electric Vehicle Charging Station to Upgrade? Don´t Trust Your Judgment https://orcid.org/0000-0003-1717-7198 Inés Duce Gimeno Transport Systems and Logistics Transportteknik och logistik Electric vehicles need to be charged. For maximal efficiency the charging times should be as short as possible. In the US charging stations are classified as Level 1 charging 5 - 10 miles/h , Level 2  25 miles/h and Fast DCFC stations  150 - 1000 miles/h. We asked participants to select one of two upgrades of charging stations that would save most charging time for a vehicle. The alternatives were upgrading L1 (5miles/h) to L2 (25 miles/h) and L2 (25miles/h) to Fast (250 miles/h). 86% of the participants wanted to upgrade to a Fast station, which objectively saves less time than L1 to L2. The second study replicated the first study. 91% of the participants wanted to upgrade to the Fast (250) station. The third study offered alternatives with smaller objective efficiency differences than the earlier studies: upgrading L2 (30) to Fast (150) and Fast (150) to Fast (600). 68% of the participants preferred the second incorrect alternative. Verbal justifications showed that many participants seemed to assume that differences in charging time was proportional to charging time saved. The results illustrate the difficulty to process reciprocal variables and stress the need of using charging time saved when decisions are made about public electric charging stations. The three SPSS (.sav) datafiles in this dataset can also be opened with the free software Jamovi (https://www.jamovi.org/) https://creativecommons.org/licenses/by/4.0/ Stockholm University Stockholms universitet 2023-07-19T00:00:00Z