Handbook of Web Surveys. Jelke Bethlehem

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style="font-size:15px;">      39  Pierzchala, M. (2006), Disparate Modes and Their Effect on Instrument Design. Paper presented at the 2006 International Blaise Users Conference, Papendal, the Netherlands (at http://www.blaiseusers.org/2006/Papers/207.pdf).

      40 Pierzchala, M. (2016), Blaise 5—Is Worth the Wait. Paper presented at the 2016 International Blaise Users Conference, The Hague, the Netherlands (at http://blaiseusers.org/2016/papers/plen2_3.pdf).

      41 Quetelet, L. A. J. (2010), Lettre à S.A.R. le Duc Régant de Saxe Coburg et Gotha sur la Théorie des Probabilités, Appliquée aux Sciences Morales at Politiques (1846). Kessinger Pub Co., Brussels, Belgium.

      42 Quetelet, L. A. J. (2012), Sur l'Homme et le Développement de ses Facultés, Essai de Physique Sociale (Edit. 1835). Hachette Livre‐BNF, Paris, France.

      43 Righi, P., Barcaroli, G., & Golini, N. (2017), Quality Issues When Using Big Data in Official Statistics. In: Petrucci, A. & Verde, R. (eds.) IProceedings of the Conference Statistics and Data Science: New Challenges, New Generations, FUP Scientific Cloud for Books.

      44 Roos, M., Jaspers, L., & Snijkers, G. (1999), De Conjunctuurtest via Internet. Report H4350‐99‐GWM, Statistics Netherlands, Data Collection Methodology Department, Heerlen, the Netherlands.

      45 Roos, M. & Wings, H. (2000), Blaise Internet Services Put to the Test: Web‐surveying the Construction Industry. Proceedings of the 6th International Blaise Users Conference, Kinsale, Ireland.

      46 Saris, W. E. (1998), Ten Years of Interviewing Without Interviewers: The Telepanel. In: Couper, M. P., Baker, R. P., Bethlehem, J. G., Clark, C. Z. F., Martin, J., Nicholls II, W. L., & O'Reilly, J. M. (eds.), Computer Assisted Survey Information Collection. Wiley, New York, pp. 409–430.

      47 Schaefer, D. R. & Dillman, D. A. (1998), Development of a Standard E‐mail Methodology: Results of an Experiment. Public Opinion Quarterly, 62, pp. 378–397.

      48 Snijkers, G., Tonglet, J., & Onat, E. (2004), Projectplan Pilot e‐PS. Internal Report H3424‐04‐BOO, Development and Support Department, Division of Business Statistics, Statistics Netherlands, Heerlen, the Netherlands.

      49 Snijkers, G., Tonglet, J., & Onat, E. (2005), Naar een Elektronische Vragenlijst voor Productiestatistieken. Internal Report, Development and Support Department, Division of Business Statistics, Statistics Netherlands, Heerlen, the Netherlands.

      50 Utts, J. M. (1999), Seeing Through Statistics. Duxburry Press, Belmont, CA.

      51 Wells, C. & Thorson, K. (2015), Combining Big Data and Survey Techniques to Model Effects of Political Content Flows in Facebook. Social Science Computer Review, 35, pp.1–20.

      52 Witte, J. C., Amoroso, L. M., & Howard, P. E. N. (2000), Method and Representation in Internet‐based Survey Tools. Social Science Computer Review, 18, pp. 179–195.

      53 Yates, F. (1949), Sampling Methods for Censuses and Surveys. Charles Griffin & Co, London, U.K.

      2.1 Introduction

      The Internet is one of the data collection tools available for conducting surveys. It is a relatively new method. At first sight, it is an attractive mean of data collection because it offers a possibility to collect a large amount of data in a short time period at low cost. Therefore, web surveys have quickly become very popular. Due to the large diffusion of mobile devices connected to Internet, when sending a web survey, it is possible that the invitation and even the completion takes place on a mobile device like a tablet or, especially, a smartphone. Thus, in fact, a web survey becomes a mobile web survey. In this handbook we use the term web surveys, and web surveys only when we want to stress the importance of mobile devices we use the term mobile web survey.

      The methodology of web surveys is not yet fully developed. Nevertheless, a lot of experiments and scientific discussion about the theory of web surveys are now in the literature. They are useful, because one can determine the advantages and the problems in doing a web survey. Therefore, the statistical studies described in this handbook are important for the future of web surveys and for those who are interested in learning about web surveys and how to run them.

       By mail using paper questionnaire forms.

       By telephone. The interviewer can use a paper form or a computer program for computer‐assisted interviewing (computer‐assisted telephone interviewing [CATI]).

       Face‐to‐face. The interviewer can use a paper form or a computer program for computer‐assisted interviewing (computer‐assisted personal interviewing [CAPI]).

      Web surveys resemble mail surveys. Both modes of data collection rely on visual information transmission. Note that telephone surveys and face‐to‐face surveys use oral information transmission. Furthermore, there are no interviewers involved in data collection. Data collection is based on self‐administered interviews.

      Of course, a web survey is a computer‐assisted form of data collection (like CAPI and CATI). Therefore, sometimes it is given name CAWI (computer‐assisted web interviewing). Web survey questionnaires can include features like automatic routing through the questionnaire and automatic checking for inconsistencies. These features are not possible for mail survey questionnaires.

      Like for any other survey, also web survey respondents have to be contacted first and invited to participate in the survey. In general, the following approaches are possible:

       Send an e‐mail or an SMS (cell text message) with a link to the website containing the survey questionnaire. The link may include a unique identification code. The unique code ensures that a respondent will complete the questionnaire only once. It also ensures that only selected individuals complete the questionnaire. Example 2.1 describes a web survey that applied this approach. At the time being, e‐mail and SMS can be read on mobile devices. Consequently, the questionnaire could be completed on mobile devices as well, or alternatively the contacted individual can postpone the completion when he will access to a laptop. This is a challenging situation because factors like the environment and contest where the invitation to the survey (i.e., the e‐mail or the SMS) is received and the time lag between the invitation and the possibility to use a laptop for completion and other factors are requiring special attention.

       Send a letter by ordinary mail inviting the potential respondents to go to the survey website. The letter contains the address (URL) of the website and a unique code. Again this guarantees that only the proper individuals participate in the survey.

       Catch potential survey participants on the Internet when they are visiting a website. They are invited to click on a link or button to start the survey. They may be directed to a different website containing the survey, or the survey starts as a newly opened window (pop‐up window) on the screen. The web survey may also be embedded in websites visited by the individual.

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