Web Survey Bibliography
Title A Test of Web/PAPI Protocols and Incentives for the Residential Energy Consumption Survey
Author Biemer, P. P.; Murphy, J.; Zimmer, S.; Berry, J.; Lewis, K.; Shaofen, D.
Year 2016
Access date 06.06.2016
Abstract
The Residential Energy Consumption Survey (RECS), sponsored by EIA, collects data on householder behaviors and housing characteristics that affect current and long-term energy usage and cost. To build a more responsive and cost-effective data platform, EIA is considering moving the RECS from the current personal interview mode to a Web/PAPI mixed-mode survey design. This paper describes an experiment to test two incentive options and four data collection protocols arrayed in 2x4 factorial design. A national epsem sample of 9,650 households was selected and divided equally among the eight treatments. The two incentive treatments included a $5 prepaid incentive in the first questionnaire mailing but varied the promised incentive amount from $10 to $20 paid after the completed questionnaire is received. The four protocol treatments are: (a) CAWI (or Web only), (b) Choice (which gives respondents the simultaneous choice of responding by either PAPI or Web), (c) Choice+ (similar to the Choice protocol but adds a $10 bonus incentive if the respondent chooses to respond by Web) and (d) CAWI/PAPI (which initially offers the Web only option, but allows the choice of Web or PAPI in nonresponse follow-up invitations). The paper reports the results of the study including which data collection protocol/incentive structure combination provides the highest quality estimates based upon a total survey error analysis.
Access/Direct link Conference Homepage (abstract)
Year of publication2016
Bibliographic typeConferences, workshops, tutorials, presentations
Web survey bibliography - Biemer, P. P. (8)
- A Test of Web/PAPI Protocols and Incentives for the Residential Energy Consumption Survey ; 2016; Biemer, P. P.; Murphy, J.; Zimmer, S.; Berry, J.; Lewis, K.; Shaofen, D.
- Survey Quality Evaluation for Business Surveys; 2012; Biemer, P. P.
- Some issues in the application of latent class models for questionnaire design; 2011; Biemer, P. P., Berzofsky, M.
- Latent class analysis of survey error; 2011; Biemer, P. P.
- Pilot Development of a Smartphone-Enabled Full-Probability Panel; 2008; Hill, C., Biemer, P. P., Coombs, D., Eyerman, J.
- Introduction to survey quality; 2003; Biemer, P. P., Lyberg, L. E.
- Telephone Survey Methodology; 2001; Groves, R. M., Biemer, P. P., Lyberg, L. E., Massey, J. T., Nicholls II, W. L., Waksberg, J.
- Audio and Video Computer Assisted Self-Interviewing: Preliminary Tests of New Technologies for Data...; 1994; O'Reilly, J. M., Hubbard, M. L., Lessler, J. T., Biemer, P. P., Turner, C. F.