Replication data and code: Invitation Messages for Business Surveys: A Multi-Armed Bandit Experiment

DOI

This replication package contains the experimental data and code from a study investigating how elements of a survey invitation message targeted to businesses influence their participation in a self-administered web survey. The experiment was conducted in collaboration with the German Business Panel (GBP) during its fifth survey wave, spanning from August 16, 2022, to November 25, 2022. A full factorial design was implemented, varying five key components of the email invitation. Unlike conventional experimental setups with static group assignments, the study employed adaptive randomization, wherein a Bayesian learning algorithm sequentially allocated more observations to invitation messages exhibiting higher survey starting rates. Over the 15-week experimental period, 738,598 invitation messages were distributed to business contacts, of which 176,000 were opened within one week. A total of 7,833 recipients initiated the survey, and 3,733 completed it. The dataset includes detailed records of message distribution, survey engagement metrics, and adaptive randomization adjustments, providing a comprehensive basis for analyzing the effectiveness of invitation design in business survey participation. Keywords: Adaptive Randomization, Reinforcement Learning, Nonresponse, Email Invitation, Web Survey, Firm Survey, Organizational Survey

Probability Sample - Simple random Sample

Web-based experimentExperiment.WebBased

Web-basiertes ExperimentExperiment.WebBased

Identifier
DOI https://doi.org/10.7802/2836
Source https://search.gesis.org/research_data/SDN-10.7802-2836?lang=de
Metadata Access https://datacatalogue.cessda.eu/oai-pmh/v0/oai?verb=GetRecord&metadataPrefix=oai_ddi25&identifier=d9caa936e45ab186132041858d064a40c74055defaa461b9e63fe1361ea4e3b2
Provenance
Creator Gaul, Johannes J.; Keusch, Florian; Rostam-Afschar, Davud; Simon, Thomas
Publisher GESIS Data Archive for the Social Sciences; GESIS Datenarchiv für Sozialwissenschaften
Publication Year 2025
Funding Reference [Collaborative Research Center (SFB/TRR) Project-ID 403041268 – TRR 266 Accounting for Transparency]
Rights Free access (without registration) - The research data can be downloaded directly by anyone without further limitations.; Freier Zugang (ohne Registrierung) - Die Forschungsdaten können von jedem direkt heruntergeladen werden.
OpenAccess true
Contact http://www.gesis.org/
Representation
Discipline Social Sciences
Spatial Coverage Germany; Germany