Web Survey Bibliography
Incentives are material and nonmaterial inducements and rewards that are offered to respondents in exchange for their participation in studies. This chapter explains the advantages and disadvantages of using incentives in Web-based studies and describes the types of incentives that are available. Moreover, the chapter seeks to develop evidence-based guidelines for short-term, as well as long-term, use of incentives to attain the goal of collecting high-quality data in a cost-conscious manner. Although a number of theoretical frameworks have been proposed to explain how incentives work (e.g., for an overview of theoretical accounts, see Singer, 2002), the focus of this chapter is pragmatic rather than theoretical. By handing out incentives to respondents, researchers can increase the likelihood of people participating in Web-based studies, and incentives may improve the quality of respondents responses. In particular, incentives can increase the response and the retention rates in a study. The response rate is the number of people who call up the first page of a study divided by the number of people who were invited or were aware of and eligible to take part in this study. The retention rate is the number of respondents who stay until the last page of a study relative to the number of respondents who have called up the first page of this study. Moreover, there is the hopebut not yet many datathat incentives will also increase other facets of data quality such as the completeness, consistency, and elaborateness of participants answers. However, using incentives might also entail undesirable effects. First, incentives might increase the response and retention rates at the expense of other facets of data quality, for example, more items are skipped; response styles occur more often; or answers to open-ended questions are shorter. It is possible that groups who are offered an incentive will answer less conscientiously than groups without incentives because the incentives might reduce the intrinsic motivation to perform the task (Heerwegh, 2006). Howeverat least in offline surveyssometimes the opposite has been found to be the case (Singer, Van Hoewyk, & Maher, 2000). Singer (2002) found that people who are rewarded for their participation would continue to give good information (p. 168). The second potential undesirable effect of incentives is that they might attract a particular type of respondent and thereby bias sample composition (e.g., poorer people may be more responsive than richer people to monetary incentives; Groves & Peytcheva, 2008). The third possible effect is that incentives might actually reduce the response and retention rates by alienating intrinsically motivated volunteers (see Deci, 1971). Finally, incentives might bias the study results, for example, by altering the mood of the respondents (Singer, 2002) or by altering respondents attitude to the researcher. There is the risk that to earn an incentive, people with little motivation will fill in meaningless data to get to the end of a survey quickly. When no incentive is promised, bored people usually abandon the study prematurely, so they are easily identifiable. Moreover, when offering incentives, researchers need to follow ethical guidelines as well as legal regulations (see chap. 16, this volume). Because the laws pertaining to the use of incentives differ across some countries, particular care is necessary with international studies. Finally, in studies with ad hoc recruitment of respondents, incentives might induce some people to fill out and submit the questionnaire many times, and it is not always possible to detect skillful fraud. To weigh whether incentives can be recommended despite possible drawbacks, researchers need to know how large the desirable and undesirable effects are. (PsycINFO Database Record (c) 2010 APA, all rights reserved). (from the chapter)
Mendeley Homepage (abstract)
Web Survey Bibliography - Book section (329)
- The Effects of Errors in Paradata on Weighting Class Adjustments: A Simulation Study; 2013; West, B. T.
- Using Paradata to Study Response to Within-Survey Requests; 2013; Sakshaug, J. W.
- Paradata for Coverage Research ; 2013; Eckman, S.
- Tips for Evaluating Online Effectiveness; 2013; Stevenson, S. C.
- Paradata in web surveys; 2013; Callegaro, M.
- Incentive effects; 2013; Goeritz, A.
- The E-Interview in Qualitative Research; 2013; Bampton, R., Cowton, C., Downs, Y.
- Methodological Considerations of Qualitative Email Interviews; 2013; Nehls, K.
- Best Practice in Online Survey Research with Sensitive Topics; 2013; Kays, K., Keith, T. L., Broughal, M. T.
- Research Intentions are Nothing without Technology: Mixed-Method Web Surveys and the Coberen Wall of...; 2013; Ganassali, S., Rodriguez-Santos, C.
- Reducing Response Burden for Enterprises Combining Methods for Data Collection on the Internet; 2013; Vik, T.
- Measuring Wages Worldwide: Exploring the Potentials and Constraints of Volunteer Web Surveys; 2013; Steinmetz, S., Raess, D., Tijdens, K., de Pedraza, P.
- Using Web Surveys for Psychology Experiments: A Case Study in New Media Technology for Research; 2013; Peden, B. F., Tiry , A. M.
- The Distinctiveness of Online Research: Descriptive Assemblages, Unobtrusiveness, and Novel Kinds of...; 2013; Lanfrey, D.
- Sampling, Channels, and Contact Strategies in Internet Survey; 2013; Macrì, E., Tessitore, C.
- Survey Research; 2013; Abbott, M. L., McKinney, J.
- Large-Scale Analysis and Testing; 2013; Cao, M., Zhang, Q.
- True experimental data collection on the Internet; 2013; Reips, U. -D., Krantz, J. H.
- The Use of Mixed Methods in Organizational Communication Research; 2013; Salem, P. J.
- The Use of E-Questionnaires in Organizational Surveys; 2013; Brender-Ilan, Y., Vinitzky, G.
- Online Survey Software; 2013; Baker, J. D.
- Web Panels; 2012; Bethlehem, J., Biffignandi, S.
- Use of Response Propensities; 2012; Bethlehem, J., Biffignandi, S.
- Weighting Adjustment Techniques; 2012; Bethlehem, J., Biffignandi, S.
- The Problem of Self-Selection; 2012; Bethlehem, J.,Biffignandi, S.
- The Problem of Undercoverage; 2012; Bethlehem, J., Biffignandi, S.
- Mixed-Mode Surveys; 2012; Bethlehem, J., Biffignandi, S.
- Designing a Web Survey Questionnaire; 2012; Bethlehem, J., Biffignandi, S.
- Comparability of Survey Measurements; 2012; Oberski, D.
- Why People Agree to Participate in Surveys; 2012; Albaum, G., Smith, S. M.
- Unit Non-Response Due to Refusal; 2012; Stoop, I.
- Classification of Surveys; 2012; Stoop, I., Harrison, E.
- What Survey Modes are Most Effective in Eliciting Self-Reports of Criminal or Delinquent Behavior?; 2012; Kleck, G., Roberts, K.
- Non-Response and Measurement Error; 2012; Billiet, J., Matsuo, H.
- An Overlooked Approach in Survey Research: Total Survey Error; 2012; Bautista, R.
- Effects of Incentives in Surveys; 2012; Toepoel, V.
- Respondents Cooperation: Demographic Profile of Survey Respondents and Its Implication; 2012; Glaser, P.
- Costs and Errors in Fixed and Mobile Phone Surveys; 2012; Vehovar, V., Slavec, A., Berzelak, N.
- E-Mail Surveys; 2012; Mesch, G.
- Building Your Own Online Panel Via E-Mail and Other Digital Media; 2012; Toepoel, V.
- Innovation der Online-Datenerhebung für wissenschaftliche Forschungen. Das niederländische MESS-Projekt...; 2012; Das, M.
- Reliable Online Social Network Data Collection; 2012; Abdesslem, F. B., Parris, I., Henderson, T.
- Diasporas on the web: new networks, new methodologies; 2012; Crush, J., Eberhardt, C., Caesar, M., Chikanda, A., Pendleton, W., Hill, A.
- A Structural Analysis Based on Similarity between Fuzzy Clusters and Its Application to Evaluation Data...; 2012; Chiba, R., Furutani, T., Sato-Ilic, M.
- Online and Paper-Based: A Mixed-Method Approach to Conducting a Needs Assessment Survey of Physicians...; 2012; Olatunbosun, T., Wu, C., Grewal, G., Lynn, B.
- What Would You Do? Conducting Web-Based Factorial Vignette Surveys; 2012; Aviram, H.
- Web Surveys: Methodological Problems and Research Perspectives; 2012; Biffignandi, S., Bethlehem, J.
- Increasing Response Rate in Web-Based/Internet Surveys; 2012; Manzo, A. N., Burke, J. M.
- Using Internet Survey to Evaluate the Effects of E-Government: The Case of Taiwan's Tax Return Filing...; 2012; Huang, T., Chung, P. L., Naiyi, H.
- About Web Surveys ; 2012; Bethlehem, J., Biffignandi, S.
