Table 3.

Overview of CS user characteristics, breakdown by selected articles

Spatial categoryYearAuthorAge (in years)Gender male femaleProfessionIndustryEducation
Employees and remote workersFreelancersEntrepreneursStart-upsSmall and midsized organizationsRetiredUnemployedStudentsDigital nomadsInformation technologyCreativeEducationManagement and businessArchitectureAuthor and translationHealthLawTourism and hospitalityScienceMarketing and salesLow education (pre-university)High education (bachelor’s or higher)
Urban2023Pan et al.xxx
2023Rådman et al.25–34xxxxxx
2022Ayodele et al.20–2975.6% 24.4%xxxx22.2%77.8%
2022Clifton and Reuschke> 35"more women than men"xxxxxxxxxxxx
2022Konecka-Szydłowska and Czupich"young people" (p. 293)xxxx
2021Appel-Meulenbroek et al.av. 29 (CZ) av. 33 (GER) av. 35 (NL)52.0% (CZ) 48.0% (CZ) 57.0% (GER) 43.0% (GER) 68.0% (NL) 32.0% (NL)xxxxxx0% (CZ) 8% (GER) 14% (NL)100% (CZ) 92% (GER) 86% (NL)
2021Buchnik and Frenkelav. 31.564.0% 36.0%xxxxxx26.0%74.0%
2021Cruz et al.32–3857.1% 42.9%xxxxxxxxxxxx
2021Lashani and Zacherav. 35.7
2021Rodríguez-Modroñoav. 32.50% 100%xxxxx
2020Grazian"very young" (p. 1005)xxxxxxxx
2020Rese et al.< 4050.0% 50.0%xxx
2020Zhao et al.25–4067.0% 33.0%xxxxxxxxxxx
2019Waldenav. 31.765.2%* 34.8%*xxxxxxx
2017Brown36.8% 63.2%xxxxx15.8%84.2%
Total (#) urban12101010106512127738432111745
Non-urban2022Flipo et al.26–5551% 49%xxxxxxxx
2022Konecka-Szydłowska and Czupichxxxxxx
2021Hölzel and de Vries"age distribution is broader" (p. 12)xxxx
2021Merrell et al.xxxx
2020Tremblay and Scaillerez
Total (#) non-urban213231200012102110011100
Notes:

*Authors calculated the percentages based on absolute numbers given

Source(s): Authors’ own work

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