Increasing web survey response rates in innovation research: An experimental study of static and dynamic contact design features

Web surveys have become increasingly central to innovation research but often suffer from low response rates. Based on a cost–benefits framework and the explicit consideration of heterogeneity across respondents, we consider the effects of key contact design features such as personalization, incentives, and the exact timing of survey contacts on web survey response rates. We also consider the benefits of a “dynamic strategy”, i.e., the approach to change features of survey contacts over the survey life cycle. We explore these effects experimentally using a career survey sent to over 24,000 junior scientists and engineers. The results show that personalization increases the odds of responding by as much as 48%, while lottery incentives with a high payoff and a low chance of winning increase the odds of responding by 30%. Furthermore, changing the wording of reminders over the survey life cycle increases the odds of a response by over 30%, while changes in contact timing (day of the week or hour of the day) did not have significant benefits. Improvements in response rates did not come at the expense of lower data quality. Our results provide novel insights into web survey response behavior and suggest useful tools for innovation researchers seeking to increase survey participation.

► This study examines the drivers of web survey response rates in a sample of over 24,000 scientists and engineers.
► Subjects were randomly assigned into conditions with different static and dynamic contact design features.
► Features included personalization, incentives, exact timing, delay between contacts, and change in features over the survey life cycle.
► Design features significantly increased the odds of a response by up to 48%.
► The paper concludes with detailed recommendations for survey researchers.