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Measurement of Interviewer Workload within the Survey and an Exploration of Workload Effects on Interviewers’ Field Efforts and Performance

Author

Listed:
  • Wuyts Celine

    (Centre for Sociological Research, Catholic University of Leuven, Parkstraat 45 - bus 3601, 3000Leuven, Belgium.)

  • Loosveldt Geert

    (Centre for Sociological Research, Catholic University of Leuven, Parkstraat 45 - bus 3601, 3000Leuven, Belgium.)

Abstract

Interviewer characteristics are usually assumed fixed over the fieldwork period. The number of sample units that require the interviewers’ attention, however, can vary strongly over the fieldwork period. Different workload levels produce different constraints on the time interviewers have available to contact, recruit and interview each target respondent, and may also induce different motivational effects on interviewers’ behavior as they perform their different tasks. In this article we show that fine-grained, time-varying operationalizations of project-specific workload can be useful to explain differences in interviewers’ field efforts and achieved response outcomes over the fieldwork period. We derive project-specific workload for each interviewer on each day of fieldwork in two rounds of the European Social Survey in Belgium from contact history and assignment paradata. Project-specific workload is measured as (1) the number of sample units which have been and remain assigned on any day t (assigned case workload), and (2) the number of sample units for which interviewer activity has started and not yet ceased on any day t (active case workload). Capturing temporal variation in interviewers’ workloads in a direct way, the time-varying operationalizations, are better predictors than are the interviewer-level operationalizations of typical (active or potential) workload that are derived from them, as well as the traditional total-count workload operationalization.

Suggested Citation

  • Wuyts Celine & Loosveldt Geert, 2020. "Measurement of Interviewer Workload within the Survey and an Exploration of Workload Effects on Interviewers’ Field Efforts and Performance," Journal of Official Statistics, Sciendo, vol. 36(3), pages 561-588, September.
    • Handle: RePEc:vrs:offsta:v:36:y:2020:i:3:p:561-588:n:6
    DOI: 10.2478/jos-2020-0029
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    References listed on IDEAS

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    4. Paul P. Biemer & Patrick Chen & Kevin Wang, 2013. "Using level-of-effort paradata in non-response adjustments with application to field surveys," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(1), pages 147-168, January.
    5. Tom Fangyun Tan & Serguei Netessine, 2014. "When Does the Devil Make Work? An Empirical Study of the Impact of Workload on Worker Productivity," Management Science, INFORMS, vol. 60(6), pages 1574-1593, June.
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