dc.contributor	{"last":"Wichmann","first":"Johannes Dr.","role":"Researcher","affiliation":"AG Digitalisierung & Prozessmanagement","id":"orcid","id_value":"0000-0002-9877-1422"}
dc.contributor	{"last":"Gesk","first":"Tanja Sophie","role":"Researcher","affiliation":"AG Digitalisierung & Prozessmanagement","id":"orcid","id_value":"0000-0002-1337-5536"}
dc.contributor.author	{"last":"Leyer","first":"Michael Prof. Dr.","affiliation":"AG Digitalisierung & Prozessmanagement","id":"orcid","id_value":"0000-0001-9429-7770"}
dc.date.Submitted	01.11.2022
dc.date.accessioned	2022-11-03T18:57:39Z
dc.date.available	2022-11-03T18:57:39Z
dc.description	This dataset is used in an article with the following background: Rationale: Vaccinations provide adequate protection against many virus-related diseases. Nonetheless, many individuals refuse voluntary vaccinations, and their refusal could contribute to the spread of diseases. Previous research on the intention to vaccinate has been limited by focusing on a single target group. Objective: In this study, we develop an integrated theoretical framework incorporating the dual approach with relevant theories related to both disease and vaccination. Our objective is to examine the behavioral reasons for the decision to vaccinate or not. The adaptive appraisals concern aspects of vaccination and the non-adaptive appraisals concern aspects of COVID-19. The framework is applied to the much-discussed context of COVID-19 vaccination. Method: We investigate the intention to vaccinate of two target groups, unvaccinated individuals and twice-vaccinated individuals, with a partial squares structured equation model. Results: Our results show that unvaccinated individuals are driven in their intention to vaccinate by their attitude (toward vaccination); factors relating to the disease have no influence. In contrast, when deciding whether to be revaccinated, twice-vaccinated individuals balance factors relating to vaccination and factors relating to disease. Conclusions: We conclude that the proposed integrated theoretical model is appropriate for investigating diverse target groups and deriving implications.	de_DE
dc.description.version	1.0	de_DE
dc.identifier.doi	http://dx.doi.org/10.17192/fdr/146
dc.identifier.uri	https://data.uni-marburg.de/handle/dataumr/216
dc.language.iso	eng	de_DE
dc.publisher	Prof. Dr. Michael Leyer	de_DE
dc.rights	Creative Commons Attribution 4.0
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/
dc.subject	Betriebswirtschaftslehre	de_DE
dc.subject.classification	112-03 Betriebswirtschaftslehre	de_DE
dc.subject.ddc	650
dc.title	Data for an integrated model to predict the intention to vaccinate against Covid-19	de_DE
dc.type	Dataset	de_DE
dc.type	Model	de_DE
local.umr.fachbereich	FB02:Wirtschaftswissenschaft	de_DE

Data for an integrated model to predict the intention to vaccinate against Covid-19

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