Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Mobilní dotazník× | Longitudinální průzkum× | |
|---|---|---|
| Obor | Metodologie dotazníkových šetření | Metodologie dotazníkových šetření |
| Rodina | Process / pipeline | Process / pipeline |
| Rok vzniku≠ | Late 2000s–2010s (accelerated with smartphone adoption, ~2007–2015) | 1940s (panel survey tradition); longitudinal designs codified mid-20th century |
| Tvůrce≠ | Emerged from web survey methodology researchers (Couper, Buskirk, Toepoel, and others) | Established tradition; formalized in social science by Paul Lazarsfeld and colleagues (1940s panel studies) |
| Typ≠ | Quantitative / mixed data collection technique | Quantitative / mixed-methods survey design |
| Původní zdroj≠ | Toepoel, V., & Lugtig, P. (2014). What happens if you offer a mobile option to your web panel? Evidence from a probability-based panel of internet users. Social Science Computer Review, 32(4), 544–560. DOI ↗ | Menard, S. (2002). Longitudinal Research (2nd ed.). Sage Publications. ISBN: 978-0761922292 |
| Další názvy | smartphone survey, mobile web survey, mobile questionnaire, m-survey | panel survey, repeated-measures survey, longitudinal panel study, wave survey |
| Příbuzné≠ | 6 | 3 |
| Shrnutí≠ | A mobile survey is a self-report questionnaire designed and administered through smartphones or tablets, either via a mobile-optimized web browser or a dedicated app. As mobile devices became the dominant mode of internet access globally, surveys must be built for small screens, touch interaction, and variable connectivity. Mobile surveys are used across social science, public health, market research, and organizational studies when reaching respondents in their natural, everyday context is a priority. | A longitudinal survey collects structured questionnaire data from the same individuals or units at two or more distinct points in time. By tracking the same respondents across waves, researchers can distinguish genuine change from stable individual differences, establish temporal ordering between variables, and model trajectories of attitudes, behaviors, or outcomes in ways that a single cross-sectional snapshot cannot support. |
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