Web Survey Bibliography
Putting respondents first
This study shows in a number of ways that obtaining good quality sample and motivating potential respondents are major concerns of the market research industry. We asked our respondents to pick what they considered to be the biggest challenges the MR industry faces. Falling response rates followed by professional respondents and availability of sample were the top three – all of which sit firmly on the respondent side of the classic client-agency-respondent triangle. Such concerns seem to be acting as a spur towards more companies embracing mixed-mode research: two-fifths of MR companies surveyed now offer this. The reasons for doing mixed-mode are very diverse, but the more widely-cited reasons include the scope to improve response rates, sample coverage and representation, and to be more respondent friendly.
Putting cost second
It is often thought that market researchers conduct mixed-mode research to reduce fieldwork costs, by shifting a large proportion to the internet. This project has shown both in 2007 and 2006, this is an important consideration not the main reason. Of course, there can be more work involved with mixed-mode research, which can act to negate any cost savings.
Creative sampling
There seems to be a hope in the industry to make less use of client sample as respondents to our 2004 and 2005 studies said that they expected to use less of it. However, in 2007 client sample is still the most common sample source and has not shown any obvious decline. Although, by 2008 the use of access panels may overtake client sample, as their use has grown steadily over the last few years. It seems that market research companies are being creative in sourcing sample for their online research since the use of ‘other’ sample has gradually increased over the years.
Software unease
A notable minority of companies use custom-developed, rather than off-the-shelf software. We observed that a fifth of both CAPI and CATI users use their owndeveloped software as their principal tool. This seems surprising given the very large number of specialist software vendors and the high cost of development. It is perhaps indicative of an industry that is wary of the off-the-shelf solutions offered. This is further backed up by the observation that around a third of companies (it was a quarter in 2006) are planning to change their software over the next two years and just over two-fifths are unsure if they will be staying with the technology they have at present. The big companies are leading the shift, with almost half (47%) planning to change. These figures have shown a marked upswing since the 2006 study.
The most often cited reason for changing software is to seek ‘more flexibility, more capabilities or better functionality’ – which suggests frustration with a lack of this with the incumbent software. It could be a function of their being so much choice being available, causing unease that the grass is greener in someone else’s fields. The range of choice and difference in features offered is in striking contrast to, say, the office automation or database reporting marketplace, where there is practically no choice today. In contradiction with this assumption, ‘dissatisfaction or concerns with existing software’ was one of the least popular reasons for changing software.
Happy trackers
For the first time this year, we asked questions about continuous research. This is an area that is not at all well supported by most software, resulting in many ad hoc and poorly automated processes for many firms. We are astonished to note that the majority of respondents report they are largely satisfied with the software they use to manage trackers.
Going modal
As we have already noted, two-fifths of companies offer mixed-mode research as part of their offering, which is a substantial minority. In revenue terms, this remains a very thin slice of revenues. But the survey detects an upward swing in demand for multimodal data collection capabilities by research software buyers: 49% now demand ‘parallel’ mixed-mode capabilities. However, demand has remained flat for the more complex real-time switching kinds of multimodal data collection, which is clearly still a highly specialised activity. Though volumes remain small, the industry is building capacity in this area, and many practitioners look on it as one practical means to combat some of the respondent-centric problems like response and coverage. We look on this still as a growth area on a slow burn.
Web rules
Our survey also records that over two-fifths of revenues from quantitative research are now attributable to online research. This appears to be the biggest source of revenue for MR companies today in the countries we surveyed – which are from the developed economies. Our sampling method does not make this a robust global estimate, but it is nevertheless an interesting indication.
Nearly all market research agencies surveyed that offer quantitative research include online research as part of their offering.
Minority channels
Looking at Web, CATI and paper together, they are the source of 87% of quantitative revenues recorded. CAPI revenues (as a convenient proxy for level of activity) are surprisingly small – only 6% – even though a third of market research companies include CAPI research as one of their services. SMS as a research channel remains rare among those offered by MR companies and has negligible impact in revenue terms – there is no growth detected in 2007 over previous years.
Business as usual in the tab mills
As in our 2005 and 2006 studies, PowerPoint is easily the most favoured distribution tool, but our analysis shows that bulk cross-tab reporting, though now only used in a minority of projects, is waning little in popularity.
Web survey bibliography - Mobile phone surveys (305)
- Measuring Subjective Health and Life Satisfaction with U.S. Hispanics; 2017; Lee, S.; Davis, R.
- Device and Internet Use among Spanish-dominant Hispanics: Implications for Web Survey Design and Testing...; 2017; Trejo, Y. A. G.; Schoua-Glusberg, A.
- How to Design a Web Survey Using Spring Boot With MYSQL: a Romanien Network Case Study; 2017; Bucea-Manea-Tonis, Ro.; Bucea-Manea-Tonis, Ra.
- Analyzing Survey Characteristics, Participation, and Evaluation Across 186 Surveys in an Online Opt-...; 2017; Revilla, M.
- Data chunking for mobile web: effects on data quality; 2017; Lugtig, P. J.; Toepoel, V.
- Mobile-only web survey respondents; 2016; Lugtig, P. J.; Toepoel, V.; Amin, A.
- Development and Pilot Test of a Mobile Application for Field Data Collection; 2016; Chiappetta, L.; Kerr, M. M.
- Are Initial Respondents Different from the Nonresponse Follow-Up Cases? A Study of Probability-Based...; 2016; Zeng, W.; Dennis, J. M.
- A Feasibility Study of Recruiting and Maintaining a Web Panel of People with Disabilities; 2016; Chandler, J.
- Why Do Web Surveys Take Longer on Smartphones?; 2016; Couper, M. P.; J. J.Peterson, G. J.
- Web surveys for offline rural communities ; 2016; Gichohi, B. W.
- Pre-Survey Text Messages (SMS) Improve Participation Rate in an Australian Mobile Telephone Survey:...; 2016; Dal Grande, E.; Chittleborough, C. R.; Campostrini, S.; Dollard, M.; Taylor, A. W.
- Short and Sweet? Length and Informative Content of Open-Ended Responses Using SMS as a Research Mode; 2016; Walsh, E.; Brinker, J. K.
- Collecting Data from mHealth Users via SMS Surveys: A Case Study in Kenya; 2016; Johnson, D.
- Online Surveys are Mixed-Device Surveys. Issues Associated with the Use of Different (Mobile) Devices...; 2016; Toepoel, V.; Lugtig, P. J.
- Using Mobile Phones for High-Frequency Data Collection; 2015; Azevedo, J. P.; Ballivian, A.; Durbin, W.
- Who Are the Internet Users, Mobile Internet Users, and Mobile-Mostly Internet Users?: Demographic Differences...; 2015; Antoun, C.
- Mobile Research Methods: Opportunities and challenges of mobile research methodologies. ; 2015; Toninelli, D. (Ed.); Pinter, R.; de Pedraza, P.
- Web Surveys Optimized for Smartphones: Are there Differences Between Computer and Smartphone Users?; 2015; Andreadis, I.
- Usability of the ACS Internet Instrument on Mobile Devices; 2015; Horwitz, R.
- GreenBook Research Industry Trends Report; 2015; Murphy, L. (Ed.)
- Emerging Technologies: The Rise of Mobile Devices: From Smartphones to Smart Surveys; 2015; Buskirk, T. D.
- PayPal? An Incentive to Check-out?; 2015; Franklin, J.; Rasmussen, C.; Pruitt, J.; Waller, D.
- Designing Bonsai Surveys: The small but perfectly formed survey experience to meet the needs of the...; 2015; Puleston, J.
- Open narrative questions in PC and smartphones: is the device playing a role?; 2015; Revilla, M.; Ochoa, C.
- Recruiting Respondents for a Mobile Phone Panel: The Impact of Recruitment Question Wording on Cooperation...; 2015; Busse, B.; Fuchs, M.
- Internet Research in Psychology; 2015; Gosling, S. D., Mason, W.
- Are Tailored Outreach Efforts Too Costly? An Assessment of a Responsive Design Approach to Control Costs...; 2015; Epps, S. R.; Getman, D. P.; Hall, L. M.; Hunter, J. A.
- Evaluating Visual Design Elements for Data Collection and Panelist Engagement; 2015; Christian, L. M.; Harm, D.; Langer Tesfaye, C.; Wells, T.
- Does the use of mobile devices (tablets and smartphones) affect survey quality and choice behaviour...; 2015; Liebe, U., Glenk, K., Oehlmann, M., Meyerhoff, J.
- When it comes to mobile respondent experience and data quality, survey design matters; 2014; Mitchell, N.
- The Changing Landscape of Technology and its Effect on Online Survey Data Collection; 2014; Mitchell, N.
- The need of and the demand for completing surveys on mobile devices; 2014; Toninelli, D., Revilla, M., Ochoa, C.
- Survey participation via mobile devices in a probability-based online-panel: Prevalence, determinants...; 2014; Poggio, T., Bosnjak, M., Weyandt, K.
- Keeping Surveys Valid, Reliable, and Useful: A Tutorial; 2014; Greenberg, M. R., Weiner, M. D.
- Improving Response Rates and Questionnaire Design for Mobile Web Surveys; 2014; de Bruijne, M., Wijnant, A.
- Does Survey Mode Still Matter? Findings from a 2010 Multi-Mode Comparison; 2014; Ansolabehere, S., Schaffner, B. F.
- Nonresponse and Mode Effects in Self- and Interviewer-Administered Surveys; 2014; Atkeson, L. R.; Adams, A. N.; Alvarez, M. R.
- Do Web surveys facilitate reporting less favourable opinions about law enforcement?; 2014; Boivin, R., Cordeau, G.
- Question Grouping and Matrices in Web Surveys: Using Response and Auxiliary Data to Examine Question...; 2014; Bilgen, I., Stern, M. J.
- The Grouping of Items in Mobile Web Surveys; 2014; Mavletova, A. M., Couper, M. P.
- Moving answers with the GyroScale: Using the mobile device’s gyroscope for market research purposes...; 2014; Luetters, H., Kraus, M., Westphal, D.
- Students First Choice – the influence of mobile mode on results; 2014; Maxl, E.
- Device Effects: How different screen sizes affect answer quality in online questionnaires; 2014; Fischer, B., Bernet, F.
- Moving towards mobile ready web panels; 2014; Wijnant, A., de Bruijne, M.
- Online mobile surveys in Italy: coverage and other methodological challenges; 2014; Poggio, T.
- Comparison of Three Modes for a Crime Victimization Survey; 2013; Laaksonen, S., Heiskanen, M.
- Understanding Society Innovation Panel Wave 5: results from methodological experiments; 2013; Auspurg, K., Burton, J., Cullinane, C., Delavande, A., Fumagalli, L., Iacovou, M., Jaeckle, A., Kaminska...
- A Comparison of Results from a Spanish and English Mail Survey: Effects of Instruction Placement on...; 2013; Wang, K., Sha, M.
- Intra-individual variation of extreme response style in mixed-mode panel studies; 2013; Aichholzer, J.