Survey data collection

With the application of probability sampling in the 1930s, surveys became a standard tool for empirical research in social sciences, marketing, and official statistics.[1] The methods involved in survey data collection are any of a number of ways in which data can be collected for a statistical survey. These are methods that are used to collect information from a sample of individuals in a systematic way. First there was the change from traditional paper-and-pencil interviewing (PAPI) to computer-assisted interviewing (CAI). Now, face-to-face surveys (CAPI), telephone surveys (CATI), and mail surveys (CASI, CSAQ) are increasingly replaced by web surveys.[2]

Modes of data collection

There are several ways of administering a survey. Within a survey, different methods can be used for different parts. For example, interviewer administration can be used for general topics but self-administration for sensitive topics. The choice between administration modes is influenced by several factors, including 1) costs, 2) coverage of the target population, 3) flexibility of asking questions, 4) respondents’ willingness to participate and 5) response accuracy. Different methods create mode effects that change how respondents answer. The most common modes of administration are listed under the following headings.[3]

Mobile surveys

Mobile data collection or mobile surveys is an increasingly popular method of data collection. Over 50% of surveys today are opened on mobile devices.[4] The survey, form, app or collection tool is on a mobile device such as a smart phone or a tablet. These devices offer innovative ways to gather data, and eliminate the laborious "data entry" (of paper form data into a computer), which delays data analysis and understanding. By eliminating paper, mobile data collection can also dramatically reduce costs: one World Bank study in Guatemala found a 71% decrease in cost while using mobile data collection, compared to the previous paper-based approach.[5]

SMS surveys can reach any handset, in any language and in any country. As they are not dependent on internet access and the answers can be sent when its convenient, they are a suitable mobile survey data collection channel for many situations that require fast, high volume responses. As a result, SMS surveys can deliver 80% of responses in less than 2 hours [6] and often at much lower cost compared to face-to-face surveys, due to the elimination of travel/personnel costs.[7]

Apart from the high mobile phone penetration,[8][9] further advantages are quicker response times and the possibility to reach previously hard-to-reach target groups. In this way, mobile technology allows marketers, researchers and employers to create real and meaningful mobile engagement in environments different from the traditional one in front of a desktop computer.[10][11] However, even when using mobile devices to answer the web surveys, most respondents still answer from home.[12][13]

Online surveys

Online (Internet) surveys are becoming an essential research tool for a variety of research fields, including marketing, social and official statistics research. According to ESOMAR online survey research accounted for 20% of global data-collection expenditure in 2006.[1] They offer capabilities beyond those available for any other type of self-administered questionnaire.[14] Online consumer panels are also used extensively for carrying out surveys but the quality is considered inferior because the panelists are regular contributors and tend to be fatigued. However, when estimating the measurement quality (defined as product of reliability and validity) using a multitrait-mutlimethod approach (MTMM), some studies found a quite reasonable quality [15][16] and even that the quality of a series of questions in an online opt-in panel (Netquest) was very similar to the measurement quality for the same questions asked in the European Social Survey (ESS), which is a face-to-face survey.[17]

US Navy 030618-N-2893B-001 Information Technician 1st Class Annette Leasure takes a few minutes to fill out the BUPERS Online Uniform Survey Questionnaire

Some studies have compared the quality of face-to-face surveys and/or telephone surveys with the one of online surveys, for single questions, but also for more complex concepts measured with more than one question (also called Composite Scores or Index).[18][19][20] Focusing only on probability-based surveys (also for the online ones), they found overall that the face-to-face (using show-cards) and web surveys have quite similar levels of measurement quality, whereas the telephone surveys were performing worse. Other studies comparing paper-and-pencil questionnaires with web-based questionnaires showed that employees preferred online survey approaches to the paper-and-pencil format. There are also concerns about what has been called "ballot stuffing" in which employees make repeated responses to the same survey. Some employees are also concerned about privacy. Even if they do not provide their names when responding to a company survey, can they be certain that their anonymity is protected? Such fears prevent some employees from expressing an opinion.[21]

Advantages of online surveys

Key methodological issues of online surveys

These issues, and potential remedies, are discussed in a number of sources.[22][23]

Telephone

Mail

Face-to-face

Mixed-mode surveys

Researchers can combine several above methods for the data collection. For example, researchers can invite shoppers at malls, and send willing participants questionnaires by emails. With the introduction of computers to the survey process, survey mode now includes combinations of different approaches or mixed-mode designs. Some of the most common methods are:[28]

See also

References

  1. 1 2 3 4 5 6 7 8 Vehovar, V.; Lozar Manfreda, K. (2008). "Overview: Online Surveys". In Fielding, N.; Lee, R. M.; Blank, G. The SAGE Handbook of Online Research Methods. London: SAGE. pp. 177–194. ISBN 978-1-4129-2293-7.
  2. 1 2 3 4 5 6 Bethlehem,, J.; Biffignandi, S. (2012). Handbook of Web Surveys. Wiley Handbooks in Survey Methodology. 567. New Jersey: John Wiley & Sons. ISBN 978-1-118-12172-6.
  3. Mellenbergh, G.J. (2008). "Surveys". In Adèr, H.J.; Mellenbergh, G.J. Advising on Research Methods: A consultant's companion. Huizen, The Netherlands: Johannes van Kessel Publishing. pp. 183–209. ISBN 978-90-79418-01-5.
  4. "Mobile-ready. Event driven. Feature rich. Online customer surveys". QuestBack. Archived from the original on 22 October 2015.
  5. Schuster, Christian; Perez Brito, Carlos. "Evaluating Cash Transfers in Guatemala". Magpi. Retrieved 27 November 2016.
  6. Global, OnePoint. "SMS surveys". OnePoint Global. Retrieved 27 June 2016.
  7. Selanikio, Joel. "Getting More Data for Less Money". Magpi. Retrieved 9 November 2016.
  8. Revilla, M., Toninelli, D., Ochoa, C., and G. Loewe (2015). “Who has access to mobile devices in an online opt-in panel? An analysis of potential respondents for mobile surveys”. In D. Toninelli, R. Pinter, and P. de Pedraza (eds), Mobile Research Methods: Opportunities and challenges of mobile research methodologies, pp. 119-139 (Chapter 8). London: Ubiquity Press. ISBN 978-1-909188-53-2. DOI: http://dx.doi.org/10.5334/bar.h. License: CC-BY 4.0.
  9. Callegaro, Mario (3 October 2013). "Do You Know Which Device Your Respondent Has Used to Take Your Online Survey?". Survey Practice. 3 (6) via www.surveypractice.org.
  10. "Mobile engagement becomes standard operating procedure". Survey Anyplace.
  11. "Reaching the Mobile Respondent: Determinants of High-Level Mobile Phone Use Among a High-Coverage Group" (PDF). Social Science Computer Review.
  12. Mavletova, Aigul; Couper, Mick P. (22 November 2013). "Sensitive Topics in PC Web and Mobile Web Surveys: Is There a Difference?". Survey Research Methods. 7 (3): 191–205. doi:10.18148/srm/2013.v7i3.5458 via ojs.ub.uni-konstanz.de.
  13. Toninelli, D. and M. Revilla (2016). "Smartphones vs PCs: Does the Device Affect the Web Survey Experience and the Measurement Error for Sensitive Topics? A Replication of the Mavletova & Couper’s 2013 Experiment." Survey Research Methods, 10(2):153-169. DOI: 10.18148/srm/2016.v10i2.6274
  14. 1 2 3 4 5 Dillman, D.A. (2006). Mail and Internet Surveys: The Tailored Design Method (2nd ed.). New Jersey: John Wiley & Sons. ISBN 978-0-470-03856-7.
  15. Revilla, Melanie; Ochoa, Carlos (14 December 2015). "Quality of Different Scales in an Online Survey in Mexico and Colombia". Journal of Politics in Latin America. 7 (3): 157–177 via journals.sub.uni-hamburg.de.
  16. "Revilla, M., and W.E. Saris (2015). “Estimating and comparing the quality of different scales of an online survey using an MTMM approach”. In Engel, U. (Ed), Survey Measurements: Techniques, Data Quality and sources of Error. Chapter 5, pp. 53-74. Campus. Frankfurt. New York. ISBN 9783593502809. Available at press.uchicago.edu".
  17. Revilla, Melanie; Saris, Willem; Loewe, Germán; Ochoa, Carlos (26 May 2015). "Can a non-probabilistic online panel achieve question quality similar to that of the European Social Survey?". International Journal of Market Research. 57 (3).
  18. Revilla, M. (2015). “Comparison of the quality estimates in a mixed-mode and a unimode design: an experiment from the European Social Survey”, Quality and Quantity. 2015, 49(3): 1219-1238. Published online first 13 of June 2014. DOI: 10.1007/s11135-014-0044-5
  19. Revilla, Melanie A. (30 December 2012). "Measurement invariance and quality of composite scores in a face-to-face and a web survey". Survey Research Methods. 7 (1): 17–28. doi:10.18148/srm/2013.v7i1.5098 via ojs.ub.uni-konstanz.de.
  20. Revilla, Melanie (31 December 2010). "Quality in Unimode and Mixed-Mode designs: A Multitrait-Multimethod approach". Survey Research Methods. 4 (3): 151–164. doi:10.18148/srm/2010.v4i3.4278 via ojs.ub.uni-konstanz.de.
  21. Schultz & Schultz, Duane (2010). Psychology and work today. New York: Prentice Hall. p. 40. ISBN 0-205-68358-4.
  22. Salant, Priscilla, and Don A. Dillman. "How to Conduct your own Survey: Leading professional give you proven techniques for getting reliable results." (1995).
  23. Kalton, Graham. Introduction to survey sampling. Vol. 35. Sage, 1983.
  24. Groves, R.M. (1989). Survey Costs and Survey Errors. New York: Wiley. ISBN 978-0-471-67851-9.
  25. J. Scott Armstrong and Terry S. Overton (1977). "Estimating Nonresponse Bias in Mail Surveys" (PDF). Journal of Marketing Research. 14: 396–402. doi:10.2307/3150783.
  26. J. Scott Armstrong (1975). "Monetary Incentives in Mail Surveys" (PDF). Public Opinion Quarterly. 39: 111–116. doi:10.1086/268203.
  27. J. Scott Armstrong (1990). "Class of Mail Does Affect Response Rates to Mailed Questionnaires: Evidence from Meta-Analysis (with a Reply by Lee Harvey)" (PDF). Journal of the Market Research Society. 32: 469–472.
  28. Groves, R.M.; Fowler, F. J.; Couper, M.P.; Lepkowski, J.M.; Singer, E.; Tourangeau, R. (2009). Survey Methodology. New Jersey: John Wiley & Sons. ISBN 978-1-118-21134-2.
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.