Understanding the dynamics of the data collection efficiency is key to developing strategies to increase response rates. In this article, we model data collection efficiency, specifically the number of completed interviews, number of contacts, ratio of completed interviews and contact attempts, and ratio of completed interviews and refusals per time unit in the field. We apply this concept to the first six rounds of the European Social Survey. The time course of efficiency for the surveys—148 country-round combinations—is analyzed using a multilevel repeated measurement model in which the weekly data collection efficiency measures are repeated measurements nested in the surveys. The results show that the data collection has four main characteristics over time: the initial efficiency, the initial increase in efficiency (speed), the initial decrease in speed, and the start of a tail when the efficiency levels off. The values of these characteristics seem to be linked with the length of the data collection period. Moreover, across all surveys, the analysis suggests that although most interviews are completed and most contacts established in the first weeks, the fieldwork becomes more productive at the end, with fewer but more successful contact attempts. The covariance parameters, however, show large differences between the surveys in terms of fieldwork dynamics. The results from a model with explanatory variables show that more interviewers, a good survey climate, and a nonindividual frame type lead to a higher efficiency, while higher percentages of refusal conversion slow down its decrease.

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