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

► 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 betwee...

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Vydáno v:	Research policy Ročník 42; číslo 1; s. 273 - 286
Hlavní autoři:	Sauermann, Henry, Roach, Michael
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Amsterdam Elsevier B.V 01.02.2013 Elsevier Sequoia S.A
Témata:	Benefits Careers Contact Cost benefit analysis Customization Data quality Dynamic tests Dynamics Experiment Experiments Heterogeneity Incentives Innovation Innovations Internet Life cycle engineering Life cycles Personalization Polls & surveys R&D Reminders Research & development Research methods Respondents Response bias Response rates Scientists Strategy Studies Survey data Survey timing Time measurements Web surveys Wording Incentives Personalization Web surveys Experiment Response rates Response bias Survey timing
ISSN:	0048-7333, 1873-7625
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Abstract	► 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. 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.
AbstractList	► 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. 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. 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. All rights reserved, Elsevier 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. [PUBLICATIONABSTRACT] 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. [PUBLICATION ABSTRACT]
Author	Roach, Michael Sauermann, Henry
Author_xml	– sequence: 1 givenname: Henry surname: Sauermann fullname: Sauermann, Henry email: henry.sauermann@mgt.gatech.edu organization: Georgia Institute of Technology, College of Management, 800 W. Peachtree St., Atlanta, GA 30308, USA – sequence: 2 givenname: Michael surname: Roach fullname: Roach, Michael email: michael_roach@kenan-flagler.unc.edu organization: University of North Carolina, Chapel Hill, Kenan-Flagler Business School, Chapel Hill, NC 27599, USA
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Snippet	► 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... Web surveys have become increasingly central to innovation research but often suffer from low response rates. Based on a cost-benefits framework and the...
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SubjectTerms	Benefits Careers Contact Cost benefit analysis Customization Data quality Dynamic tests Dynamics Experiment Experiments Heterogeneity Incentives Innovation Innovations Internet Life cycle engineering Life cycles Personalization Polls & surveys R&D Reminders Research & development Research methods Respondents Response bias Response rates Scientists Strategy Studies Survey data Survey timing Time measurements Web surveys Wording
Title	Increasing web survey response rates in innovation research: An experimental study of static and dynamic contact design features
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