Web Survey Bibliography
When conducting surveys on trade fairs and during events like concerts or sales promotions, two key challenges for the executing market research agency are: being mobile, i.e. being independent from technical infrastructure, and transforming the data of a large number of interviews quickly and efficiently into meaningful charts. Both goals can be reached by data collection via mobile telecommunication devices like mobile phones or PDA’s. Also when conducting mystery shopping projects or consumer studies in real usage occasions (e.g. in bars or at the beach) this way of collecting data has proven its worth.
Thinking about surveys on trade fairs, market researchers might be challenged to make first results accessible while fieldwork is still being continued (e.g. after the end of the second day of the fair). These insights might be used to further optimize the client’s presentation on the fair.
To face challenges like this, isi has developed a process and a technical infrastructure, in which the collected interview data will be transformed into meaningful charts in real-time, i.e. right after having completed an interview. These charts are accessible for the client anytime and anywhere via an online reporting tool.
With software that is optimized for mobile devices, an online questionnaire is developed. The data is collected by means of mobile phones or PDA’s using the 3G technology. Each dataset is stored in a database on a secure web server. An online reporting tool uses these datasets to visualize the results in charts which can be accessed by the client anywhere and everywhere.
The visualization of results is not even limited to the “total perspective”: The online tool allows making use of selection criteria to get deep insights into opinions and preferences of certain target segments (e.g. only females between 30 and 40 years).
In an isi case study, this approach will be depicted and the advantages of its high degree of automation will be pointed out.
General online research (GOR) 2008 (abstract)
Web Survey Bibliography - Conference proceedings (240)
- Unintentional mobile respondents; 2012; Peterson, G.
- Sensitive topics in PC Web and mobile web surveys: Is there a difference?; 2012; Mavletova, A. M., Couper, M. P.
- Metering mobile usage. Insights from global Arbitron mobile trends panel; 2012; Verkasalo, H.
- Is „chapterisation“ a viable alternative to traditional progress indicators ?; 2012; Spicer, R., Dowling, Z.
- An experimental investigation of the effects of noncontingent and contingent incentives in recruiting...; 2012; Lavrakas, P. J., Dennis, J. M., Peugh, J., Shand-Lubbers, J., Lee, E., Peugh, J., Charlebois, O., Murakami...
- The smart(phone) way to collect survey data; 2011; Stapleton, C.
- The next CAPI evolution - completing web surveys on cell-enabled iPads; 2011; Dayton, J., Driscoll, H.
- Self-administered mobile surveys; 2011; Bosnjak, M.
- Online survey research: Findings, Best practices, and future research; 2011
- Moving forward, building an ethics community (Panel statement); 2011; Kenneally, E. et al.
- In search of a new approach to measure newspaper audiences in Canada: The journey continues; 2011; Crassweller, A., Rogers, J., Graves, F., Gauthier, E., Charlebois, O.
- Effects of response format on requalification for recontact studies; 2011; Thomas, R. K.
- A meta-analysis of experiments manipulating progress indicators in Web surveys; 2011; Callegaro, M., Villar, A., Yang, Y.
- Blend, balance, and stabilize respondent sources; 2011; Eggers, M., Drake, E.
- Mode Effect or Question Wording? Measurement Error in Mixed Mode Surveys; 2011; de Leeuw, E. D., Hox, J., Scherpenzeel, A.
- Using a fillable PDF together with SAS ® for questionnaire data; 2010; Donald, E.
- There is an app for that! A review of smartphone apps for marketing research; 2010; Michelson, M.
- The state of online research in the U.S.; 2010; Miller, J.
- Function follows form: Effects of response format on self-reported individuals and household disability...; 2010; Falcone, A. E., Thomas, R. K.
- Address-based sampling. Merits, design & implementation, and review of field statistics; 2010; Fahimi, M.
- A framework for understanding and applying ethical principles in network and security research; 2010; Kenneally, E., Bailey, M., Maughan, D.
- Restructuring and innovations on the survey “capacity of collective tourist accommodation”...; 2010; Santoro, M. T., Staffieri, S.
- An Analyze of the Zero Price Effect on Online Business Performance - An Research Based on the Mobile...; 2010; Liu, Y., Yuan, P.
- Dealing with Nonresponse in Survey Sampling: an Item Response Modeling Approach; 2010; Matei, A.
- Web survey design and usability; 2010; Karakoyun, F., Kurt, A. A.
- Response format effects on measurement of employment; 2009; Thomas, R. K., Dillman, D. A., Smyth, J. D.
- Getting data for (business) statistics: What's new? What's next?; 2009; Snijkers, G.
- Response Mode and Bias Analysis in the IRS’ Individual Taxpayer Burden Survey; 2009; Brick, J. M., Contos, G.,Masken, K.,Nord, R.
- Survey Mode Effects in Two Military Surveys; 2009; Yang, M., Falcone, A. E., Milan, L. M.
- Web based macroseismic survey: fast information exchange and elaboration of seismic intensity effects...; 2009; De Rubeis, V., Sbarra P., Sorrentino, D., Tosi, P.
- The representativeness of the LISS panel ; 2009; Knoef, M., de Vos, K.
- Sample factors that influence data quality; 2008; Gailey, R., Teal, D., Haechrel, E.
- An online panel as a platform for multi-disciplinary research; 2008; Scherpenzeel, A.
- Visual Design Effects on on Respondents Behaviour in Web-Surveys. A Design Experiment; 2008; Greinöcker, A.
- Effects of Privacy Assurances on the Online Measurement of Psychological Constructs; 2008; Witzki, A., Kramer, J.
- Effects of AJAX Technology in Online Questionnaires; 2008; Lütters, H., Westphal, D., Heublein, F.
- How Web 2.0 Technologies Can Become a Valuable Part of Online Research; 2008; Jaron, R.
- Respondent Authenticity - A biometrical approach to authenticate panelists; 2008; Wachter, B., Bender, C.
- Visual Analogue Scales Versus Categorical Scales: Respondent Burden, Cognitive Depth, and Data Quality...; 2008; Funke, F.,Reips, U. -D.
- Not Mixed-Mode but Switch-Mode; 2008; Höglinger, M., Abraham, M., Arpagaus, J.
- The Impact of Cognitive and Computer Skills on Data Quality in Computer Assisted Self Administered Questionnaires...; 2008; Brecko, B. N., Vehovar, V.
- Optimal Contact Strategy in a Mail-and-Web Mixed Mode Survey; 2008; Holmberg, A., Lorenc, B., Werner, P.
- 10 Years of Meinungsplatz.de: Success in the Collection of Data for Targeted Audiences, Such as the...; 2008; Weyergraf, O.
- Self-selection in Online Access Panels: No “Little Difference” in the Recruiting Process...; 2008; Wirth, T.
- Selectivity or Usefulness of Online-Surveys? A Comparison with Data from a Local Population Survey; 2008; Kroll, S., Hüfken, V., Reuband, K.H.
- Mobile Market Research; 2008; Maxl, E.
- Flexible and High-Speed Market Research through Mobile Data Collection & Online Reporting Tool; 2008; Haag, J., Volkmer, H.P.
- Online vs. Offline in Mobile Surveys; 2008; Neubarth, W., Maier, U.
- Gender-of-Interviewer Effects in Video-Enhanced Web Surveys. Results from a Randomized Field-Experiment...; 2008; Fuchs, M.
- The Online Use of Randomized Response Measurements; 2008; Snijders, C., Weesie, J.