Web Survey Bibliography
Title The Mobile Web Only Population: Socio-demographic Characteristics and Potential Bias
Author Fuchs, M.; Metzler, A.
Year 2016
Access date 03.06.2016
Abstract
In recent years the use of mobile devices such as smart phones or tablet PCs to complete Web surveys has grown steadily. Thus, survey researchers are facing new challenges when designing Web survey questionnaires. Among others, screen sizes are considerably smaller for mobile devices as compared to desktop PC or notebooks. Also, mobile W
eb respondents are using touch screen data entry instead of a mouse. Accordingly, the question arises whether Web survey questionnaires should be optimized for mobile devices in order to avoid under representation of respondents using mobile devicesdue to difficulty arising from the small screen size and touch screen technology. Since most Web survey respondents still have a desktop PC or notebook available to access the internet optimizing questionnaires for mobile devices may not be necessary avoiding potential differential measurement error. In this paper we assess the so-called mobile Web only respondents who no longer have access to the internet using a desktop PC or notebook. It is assumed that this group is most likely underrepresented in Web surveys not optimized for mobile devises resulting in a potential bias. Using Eurobarometer data from 2012 to 2014 across 27 European countries we estimated the size of the mobile Web only population. Results indicate that the percentage of mobile Web onlys increased from 1.5 percent in 2012 to 6.2 percent in 2014 across Europe. A more detailed analysis indicated that the mobile Web only population is younger, more likely female, less educated, more often living in small or middle sized towns and more often single. Overall, results suggest that Web survey questionnaires should be optimized for mobile devices since exclusion or underrepresentation of the mobile Web onlys may cause considerable bias.
eb respondents are using touch screen data entry instead of a mouse. Accordingly, the question arises whether Web survey questionnaires should be optimized for mobile devices in order to avoid under representation of respondents using mobile devicesdue to difficulty arising from the small screen size and touch screen technology. Since most Web survey respondents still have a desktop PC or notebook available to access the internet optimizing questionnaires for mobile devices may not be necessary avoiding potential differential measurement error. In this paper we assess the so-called mobile Web only respondents who no longer have access to the internet using a desktop PC or notebook. It is assumed that this group is most likely underrepresented in Web surveys not optimized for mobile devises resulting in a potential bias. Using Eurobarometer data from 2012 to 2014 across 27 European countries we estimated the size of the mobile Web only population. Results indicate that the percentage of mobile Web onlys increased from 1.5 percent in 2012 to 6.2 percent in 2014 across Europe. A more detailed analysis indicated that the mobile Web only population is younger, more likely female, less educated, more often living in small or middle sized towns and more often single. Overall, results suggest that Web survey questionnaires should be optimized for mobile devices since exclusion or underrepresentation of the mobile Web onlys may cause considerable bias.
Access/Direct link Conference Homepage (abstract)
Year of publication2016
Bibliographic typeConferences, workshops, tutorials, presentations
Web survey bibliography - 2016 (264)
- Exploring Mode Effects Between Smartphone and Perso nal Computer Mode of Administration of a National...; 2016; Fahrney Wiant, K.; Richards, A.; Zimmer, S.; Mayclin, D.
- Response Order Effects on a Web Survey of Nurse Pra ctitioners ; 2016; Quintana, G.; Riley, L. E.
- Using Paradata to Identify Questions with High Resp ondent Burden for Improvement in Future Surveys ; 2016; Powell, R.Richards, A.Yu, S.Brackbill, R.
- Investigating Cognitive Effort of Response Formats in Web Surveys using Paradata ; 2016; Hoehne, J. K.; Schlosser, S.; Krebs, D.
- Assessing the Effects and Effectiveness of Attention-check Questions in Web Surveys: Evidence From a...; 2016; Vannette, D.
- Conducting Survey Experiments Using an Online Labor Market ; 2016; Fowler, S.; Willis, G. B.; Moser, R. P.; Townsend, R. L. M.; Maitland, A.; Sun, H.; Ferrer, R.; Berrigan...
- Mode Effect on Racial Sensitive Questions between W eb and Computer-assisted Self-interview ; 2016; Liu, M.; Wang, Y.; Lepkowski, J. M.
- A Test of Web/PAPI Protocols and Incentives for the Residential Energy Consumption Survey ; 2016; Biemer, P. P.; Murphy, J.; Zimmer, S.; Berry, J.; Lewis, K.; Shaofen, D.
- Mode Effects in American Trends Panel: Bayesian Analysis of a Cross-classified Item-person Mixed Model...; 2016; Gill, Je.; Kolenikov, S.; McGeeney, K.
- Mobile Device Use in Web Surveys Among College Students: Predictors and Consequences for Data Quality...; 2016; Beach, S.; Musa, D.; Strotmeyer, S.; Schlarb, J.
- Mode Effects on Subjective Well-being Research: Do they Affect Regression Coefficients? ; 2016; Sanchez Tome, R.; Roberts, C.; Staehli, M. E.; Joye, D.
- Effects of an Initial Offering of Multiple Survey Response Options on Response Rates; 2016; Steele, E. A.; Marlar, J.; Allen, L.; Kanitkar, K. N.
- How to Invite? Methods for Increasing Internet Surv ey Response Rate ; 2016; Huang, A. R.; Noel, H.; Hargraves, L.
- The Mobile Web Only Population: Socio-demographic Characteristics and Potential Bias ; 2016; Fuchs, M.; Metzler, A.
- Unintentional Mobile Respondents in Official Statis tics and Their Effect on Data Quality ; 2016; Bakker, J.
- Evaluating a Modular Design Approach to Collecting Survey Data Using Text Messages ; 2016; West, B. T.; Ghimire, D.; Axinn, W.
- Testing Web-Based Survey Measures of Gender Identity and Sexual Orientation Using Mark-All-That-Apply...; 2016; Brenner, P.; Bulgar - Medina, J.
- Mode and Eligibility Rates in a Dual-mode Web and Mail Survey ; 2016; Ventura, I.; Bilgen, I.; Stern, M. J.
- The Impact of Response Scale Direction on Survey Responses in a Mixed-mode Survey ; 2016; Hu, M.; Yan, T.; Keusch, F.
- Examining Trends in the Presence of Survey Mode Effects ; 2016; Hisako Kitada, H.; Lesser, V. M.
- Best Practice Instrument & Communications Evaluation: An Examination of the NSCH Redesign ; 2016; Higgins, W. B.; Welch, R.; Tortora, R. D.; Vladutiu, C. J.
- The Effect of Respondent Commitment and Tailored Fe edback on Response Quality in an Online Survey ; 2016; Cibelli Hibben, K.; Conrad, F. G.
- Effectiveness of Messaging to Encourage Response to the ACS ; 2016; Fulton, J.; Hunter Childs, J. E.; Morales, G.
- Reaching the Mobile Generation: Reducing Web Survey Non-response through SMS Reminders ; 2016; Kanitkar, K. N.; Marlar, J.
- The Effect of Using Text Messages for Survey Invitations and Reminders ; 2016; McGeeney, K.; Yan, H. Y.
- "Don't be Afraid ... We're Researchers!": The Impact of Informal Contact Language...; 2016; Foster, K. N.; Hagemeier, N. E.; Alamain, A. A.; Pack, R.; Sevak, R. J.
- Does Embedding a Survey Question in the Survey Invi tation E-mail Affect Response Rates? Evidence from...; 2016; Vannette, D.
- Safety First: Ensuring the Anonymity and Privacy of Iranian Panellists’ While Creating Iran...; 2016; Farmanesh, A.; Mohseni, E.
- Novel Methodology for Reaching a Statewide Represen tative Sample of Youth Ages 12-18 ; 2016; Freedner-Maguire, N.; ZuWallack, R. S.
- Communication Channels that Predict and Mediate Self-response ; 2016; Walejko, G. K.
- Encouraging Online Response among Hard-to-Survey Po pulations: Digital Advertising and Influencer Calls...; 2016; Bates, N.; Virgile, M.
- ...; 2016; Mccaffrey, K. M.; Otmany, J.; Hagedorn, S.
- Simulating a Census Environment to Test Online Self -response ; 2016; Vines, M.
- Using a Response Propensity Model to Allocate Non-c ontingent Incentives in a Web Panel ; 2016; Masterton, M.
- Promoting Participation in Web Surveys; 2016; Hupp, A.; Chan, W.
- Does Asking for Linkage Consent in the Beginning of the Questionnaire Affect Respondents' Answers...; 2016; Haas, G. C.; Eckman, S.
- Implications of Response Device Type for Sensitive Web Surveys: Examining Data Quality and Respondent...; 2016; C.; Richards, A.; C.; Peterson, K.; Smith, A. C.
- Influence of Multiple Factors on Response Rate; 2016; Chaney,B.H.; Chaney, B. H.; Kindlon, A.
- What’s Your Number? Evaluating the Success of Telep hone Number Acquisition Via Record Match,...; 2016; Linville, J. C.; Carley- R.; Carley- R.; Grant, D. B.; Carley- R.; Jans, M.; Carley- R.; Park, R.; Becker...
- Tracking the Representativeness of an Online Panel Over Time ; 2016; Klausch, L. T.; Scherpenzeel, A.
- Can Using a Mixed Mode Approach Improve the Representativeness and Data Quality in Panel Surveys?; 2016; Stern, M. J.
- Surveying American Indian and Alaska Native Parents : Identifying Characteristics of Survey Mode Preference...; 2016; Feeney, K.; Masters, F.
- The Impact of Scale Direction, Alignment and Length on Responses to Rating Scale Questions in a Web...; 2016; Keusch, F.; Liu, M.; Yan, T.
- Pre-election Surveys Using a Multi-modal Interviewing Strategy ; 2016; Redman, J.; Thompson, Sc.; Yost, B.
- Methods for Detecting Telescoping Error in a Cross- sectional Web Design Survey ; 2016; Shook-Sa, B. E.; Berzofsky, M.; Peterson, K.; Lindquist, C.; Krebs, C.
- Introduction Breakoffs, Questionnaire Breakoffs and Web Questionnaire Length: A Metastudy ; 2016; Cehovin, G.; Vehovar, V.
- Web Surveys Versus Other Survey Modes: An Updated Meta-analysis Comparing Response Rates ; 2016; Wengrzik, J.; Bosnjak, M.; Lozar Manfreda, K.
- The Effect of a Pre-due Date Reminder Letter on Non response in a Business Survey ; 2016; Hernandez, A. D.; Fan, C. C.; Tuttle, A.
- Adapting the Alternative Questionnaire Experiment for a Telephone Survey: Preparing for Changes to the...; 2016; Patten, E.; Brown, A.; Parker, K.
- Retrospective Measurement of Students’ Extracurricular Activities with a Self-administered Calendar...; 2016; Furthmueller, P.