Web Survey Bibliography
The presentation focuses – next to the discussion on opportunities and limitations of mobile market research (mmr) - on an overview of core results of mobile market research studies conducted by evolaris during the past 3 years.
At first the paper will give a definition of mobile market research i.e. using mobile phone devices and technologies like SMS, MMS, mobile internet, GPS, pattern recognition and cameras to collect data from respondents. Advantages will be outlined and empirically affirmed e.g. speed of reactions and better reach of special target-groups as well as limitations like issues of usability, costs and representativeness. However upcoming trends like i-phone and flat rates for data-transfer will argue against some provisos.
In the following part of the presentation a short synopsis of the mobile phone distribution, spread of technological features and usage as basis for potential target groups will help to encircle potential target groups to research e.g. SMS usage, current mobile internet usage and forcast.
Next, different types of mobile market research methods will be discussed: Researching by SMS / MMS / WAP i.e. mobile internet and location based information (e.g.) is on the proof. Strengths, weaknesses and legal restrictions of each approach are presented side by side. SMS research for instance has the benefit of potentially reaching all mobile phone users since every device is equipped with it. On the contrary responding by SMS might be less convenient and even faulty due to limited characters, lack of visibility of questions and code words which have to be remembered. MMS adds the assistance of showing multimedia material to respondents but sets limits to amount of questions as well as SMS do.
More detailed the use of mmr in qualitative research is shown by an example using mobile blogging in trend research. Comparing the usage of mobile phones with paper&pencil diaries documents the usefulness especially for younger, technical-affine targets groups. Immediate availability of posted contributions is another benefit of the mobile method.
Coming to the main part of the presentation, the use of a mobile survey application and workflow of mobile surveys from sending out invitations in form of wap-pushes, presenting the survey in a user-friendly way to analyse data is depicted. Differences and similarities to web surveys are presented by a case study done for Vodafone live, a mobile entertainment platform researching customer satisfaction. Results of a web are compared with a mobile survey showing higher and quicker response by the latter. Reasons for this will be summarized e.g. lack of fraction of the research medium. However, the data shows differences between both methods. Possible reasons like psychographic variaton of respond-groups are discussed. Further areas of application for mmr like advertising testing and evaluation of mobile marketing campaigns are sketched by case studies.
Finally: The most relevant learnings from until now conducted mobile surveys will be presented to the audience. This includes answers and indications to the following questions:
How do respondents feel about this kind of method? Figures of post assessments illustrate a high acceptance in special younger target groups between about 16 and 26 years with specific technological-friendly attitudes.
How high are response rates and which variables influence them? We got response rates from 1% to 23% and finishing quotes from 63% to 84%.
How long should a wap-questionnaire be? Results document that even 26 questions do not result to higher dropout rates, considering however the set-up and target-group of research, in this case students.
What about the speed of getting data and feedback? Our results show rates from 53% to 73% of sample in total within the first hour of sending out invitations. Thus suggesting respondents participate immediately or not at all.
How is the influence of the presentation, layout and display of scales? Even though scales can only be depicted vertically on most of mobile phones in wml and xhtml, we couldn’t find a bias by flipping scales at split half of sample.
Comparison to other methods i.e. web and CATI shows differences especially looking at the more “emotional” items.
The presentation will close with an outlook to future trends in mobile phone technology like NFC, mobile TV / DVB-H, 2D-Codes and some ideas on how to get best use of it in market research.
General online research (GOR) 2008 (abstract)
Web survey bibliography (4086)
- Displaying Videos in Web Surveys: Implications for Complete Viewing and Survey Responses; 2017; Mendelson, J.; Lee Gibson, J.; Romano Bergstrom, J. C.
- Using experts’ consensus (the Delphi method) to evaluate weighting techniques in web surveys not...; 2017; Toepoel, V.; Emerson, H.
- Mind the Mode: Differences in Paper vs. Web-Based Survey Modes Among Women With Cancer; 2017; Hagan, T. L.; Belcher, S. M.; Donovan, H. S.
- Answering Without Reading: IMCs and Strong Satisficing in Online Surveys; 2017; Anduiza, E.; Galais, C.
- Ideal and maximum length for a web survey; 2017; Revilla, M.; Ochoa, C.
- Social desirability bias in self-reported well-being measures: evidence from an online survey; 2017; Caputo, A.
- Web-Based Survey Methodology; 2017; Wright, K. B.
- Handbook of Research Methods in Health Social Sciences; 2017; Liamputtong, P.
- Lessons from recruitment to an internet based survey for Degenerative Cervical Myelopathy: merits of...; 2017; Davies, B.; Kotter, M. R.
- Web Survey Gamification - Increasing Data Quality in Web Surveys by Using Game Design Elements; 2017; Schacht, S.; Keusch, F.; Bergmann, N.; Morana, S.
- Effects of sampling procedure on data quality in a web survey; 2017; Rimac, I.; Ogresta, J.
- Comparability of web and telephone surveys for the measurement of subjective well-being; 2017; Sarracino, F.; Riillo, C. F. A.; Mikucka, M.
- Achieving Strong Privacy in Online Survey; 2017; Zhou, Yo.; Zhou, Yi.; Chen, S.; Wu, S. S.
- A Meta-Analysis of the Effects of Incentives on Response Rate in Online Survey Studies; 2017; Mohammad Asire, A.
- Telephone versus Online Survey Modes for Election Studies: Comparing Canadian Public Opinion and Vote...; 2017; Breton, C.; Cutler, F.; Lachance, S.; Mierke-Zatwarnicki, A.
- Examining Factors Impacting Online Survey Response Ratesin Educational Research: Perceptions of Graduate...; 2017; Saleh, A.; Bista, K.
- Usability Testing for Survey Research; 2017; Geisen, E.; Romano Bergstrom, J. C.
- Paradata as an aide to questionnaire design: Improving quality and reducing burden; 2017; Timm, E.; Stewart, J.; Sidney, I.
- Fieldwork monitoring and managing with time-related paradata; 2017; Vandenplas, C.
- Interviewer effects on onliner and offliner participation in the German Internet Panel; 2017; Herzing, J. M. E.; Blom, A. G.; Meuleman, B.
- Interviewer Gender and Survey Responses: The Effects of Humanizing Cues Variations; 2017; Jablonski, W.; Krzewinska, A.; Grzeszkiewicz-Radulska, K.
- Millennials and emojis in Spain and Mexico.; 2017; Bosch Jover, O.; Revilla, M.
- Where, When, How and with What Do Panel Interviews Take Place and Is the Quality of Answers Affected...; 2017; Niebruegge, S.
- Comparing the same Questionnaire between five Online Panels: A Study of the Effect of Recruitment Strategy...; 2017; Schnell, R.; Panreck, L.
- Nonresponses as context-sensitive response behaviour of participants in online-surveys and their relevance...; 2017; Wetzlehuetter, D.
- Do distractions during web survey completion affect data quality? Findings from a laboratory experiment...; 2017; Wenz, A.
- Predicting Breakoffs in Web Surveys; 2017; Mittereder, F.; West, B. T.
- Measuring Subjective Health and Life Satisfaction with U.S. Hispanics; 2017; Lee, S.; Davis, R.
- Humanizing Cues in Internet Surveys: Investigating Respondent Cognitive Processes; 2017; Jablonski, W.; Grzeszkiewicz-Radulska, K.; Krzewinska, A.
- A Comparison of Emerging Pretesting Methods for Evaluating “Modern” Surveys; 2017; Geisen, E., Murphy, J.
- The Effect of Respondent Commitment on Response Quality in Two Online Surveys; 2017; Cibelli Hibben, K.
- Pushing to web in the ISSP; 2017; Jonsdottir, G. A.; Dofradottir, A. G.; Einarsson, H. B.
- The 2016 Canadian Census: An Innovative Wave Collection Methodology to Maximize Self-Response and Internet...; 2017; Mathieu, P.
- Push2web or less is more? Experimental evidence from a mixed-mode population survey at the community...; 2017; Neumann, R.; Haeder, M.; Brust, O.; Dittrich, E.; von Hermanni, H.
- In search of best practices; 2017; Kappelhof, J. W. S.; Steijn, S.
- Redirected Inbound Call Sampling (RICS); A New Methodology ; 2017; Krotki, K.; Bobashev, G.; Levine, B.; Richards, S.
- An Empirical Process for Using Non-probability Survey for Inference; 2017; Tortora, R.; Iachan, R.
- The perils of non-probability sampling; 2017; Bethlehem, J.
- A Comparison of Two Nonprobability Samples with Probability Samples; 2017; Zack, E. S.; Kennedy, J. M.
- Rates, Delays, and Completeness of General Practitioners’ Responses to a Postal Versus Web-Based...; 2017; Sebo, P.; Maisonneuve, H.; Cerutti, B.; Pascal Fournier, J.; Haller, D. M.
- Necessary but Insufficient: Why Measurement Invariance Tests Need Online Probing as a Complementary...; 2017; Meitinger, K.
- Nonresponse in Organizational Surveying: Attitudinal Distribution Form and Conditional Response Probabilities...; 2017; Kulas, J. T.; Robinson, D. H.; Kellar, D. Z.; Smith, J. A.
- Theory and Practice in Nonprobability Surveys: Parallels between Causal Inference and Survey Inference...; 2017; Mercer, A. W.; Kreuter, F.; Keeter, S.; Stuart, E. A.
- Is There a Future for Surveys; 2017; Miller, P. V.
- Reducing speeding in web surveys by providing immediate feedback; 2017; Conrad, F.; Tourangeau, R.; Couper, M. P.; Zhang, C.
- Social Desirability and Undesirability Effects on Survey Response latencies; 2017; Andersen, H.; Mayerl, J.
- A Working Example of How to Use Artificial Intelligence To Automate and Transform Surveys Into Customer...; 2017; Neve, S.
- A Case Study on Evaluating the Relevance of Some Rules for Writing Requirements through an Online Survey...; 2017; Warnier, M.; Condamines, A.
- Estimating the Impact of Measurement Differences Introduced by Efforts to Reach a Balanced Response...; 2017; Kappelhof, J. W. S.; De Leeuw, E. D.
- Targeted letters: Effects on sample composition and item non-response; 2017; Bianchi, A.; Biffignandi, S.