SDN-10.7802-2836

Property	Value
?:about	<https://data.gesis.org/gesiskg/resource/Methodenforschung> <https://data.gesis.org/gesiskg/resource/Unternehmen> <https://data.gesis.org/gesiskg/resource/enterprise> <https://data.gesis.org/gesiskg/resource/methodological_research>
?:abstract	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 (xsd:string)
?:archivedAt	<https://data.gesis.org/sharing/%23%21Detail/10.7802/2836>
?:category	Business Administration (en) Business Administration (de)
?:citationString	Gaul, Johannes J., Keusch, Florian, Rostam-Afschar, Davud, & Simon, Thomas (2025): Replication data and code: Invitation Messages for Business Surveys: A Multi-Armed Bandit Experiment. GESIS, Cologne. Data File Version 1.0.0, https://doi.org/10.7802/2836 (en) Gaul, Johannes J., Keusch, Florian, Rostam-Afschar, Davud, & Simon, Thomas (2025): Replication data and code: Invitation Messages for Business Surveys: A Multi-Armed Bandit Experiment. GESIS, Köln. Datenfile Version 1.0.0, https://doi.org/10.7802/2836 (de)
?:conditionsOfAccess	Free access (without registration) (en) Freier Zugang (ohne Registrierung) (de)
?:currentVersion	1.0.0, https://doi.org/10.7802/2836 (xsd:string)
?:dataCollection	Selbstausfüller:CASI(Computerunterstützte Selbstbefragung) (de) Self-administered questionnaire:CASI(Computer-assisted Self-interview) (en)
?:dateCreated	2025 (xsd:gyear)
?:dateModified	2025-01-01 (xsd:date)
?:datePublished	2025 (xsd:gyear)
?:doi	10.7802/2836 ()
?:endDate	2022-01-01 (xsd:date)
?:funder	<https://data.gesis.org/gesiskg/resource/Collaborative_Research_Center_%28SFB.TRR%29_Project-ID_403041268_%E2%80%93_TRR_266_Accounting_for_Transparency>
?:hasFulltext	true (xsd:boolean)
is ?:hasPart of	<https://data.gesis.org/gesiskg/resource/>
?:linksQuestionnaire	<https://access.gesis.org/sharing/2836/6552>
?:measurementTechnique	Longitudinal (panel study) (en) Längsschnitt (Panelstudie) (de)
?:name	Replication data and code: Invitation Messages for Business Surveys: A Multi-Armed Bandit Experiment (xsd:string)
?:principalInvestigator	Gaul, Johannes J. (xsd:string) Keusch, Florian (xsd:string) Rostam-Afschar, Davud (xsd:string) Simon, Thomas (xsd:string)
?:provider	<https://data.gesis.org/gesiskg/resource/University_of_Mannheim> <https://data.gesis.org/gesiskg/resource/University_of_Mannheim%2C_IZA%2C_GLO%2C_NeSt> <https://data.gesis.org/gesiskg/resource/ZEW%2C_University_of_Mannheim%2C_NeSt>
?:publicationType	SowiDataNet\|datorium (en)
?:publisher	<https://data.gesis.org/gesiskg/resource/GESIS%2C_Cologne> <https://data.gesis.org/gesiskg/resource/GESIS%2C_K%C3%B6ln>
?:selectionMethod	Probability Sample - Simple random Sample (en) Wahrscheinlichkeitsauswahl - Einfache Zufallsauswahl (de)
?:sourceInfo	GESIS, Cologne. Data File Version 1.0.0, https://doi.org/10.7802/2836 (en) GESIS, Köln. Datenfile Version 1.0.0, https://doi.org/10.7802/2836 (de) GESIS-SowiDataNet\|datorium (xsd:string)
?:spatialCoverage	<https://data.gesis.org/gesiskg/resource/Germany>
?:startDate	2022-01-01 (xsd:date)
?:thematicCollection	Replication material (en) Replikationsmaterial (de)
rdf:type	<https://schema.org/Dataset>
?:variableMeasured	All legal entities active in Germany as defined by the Federal Statistical Office in the statistical business register (xsd:string)