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Erschienen in:
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2016 | OriginalPaper | Buchkapitel

Adoption Factors for Crowdsourcing Based Medical Information Platforms

verfasst von : Till Blesik, Markus Bick

Erschienen in: Knowledge Science, Engineering and Management

Verlag: Springer International Publishing

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Abstract

Platforms increasingly utilize crowdsourcing to offer knowledge intense services such as medical diagnostics while retaining low costs. The increased interest elevated the adoption of established theories for user acceptance, risk avoidance and motivational influencing factors. We propose a combination of elements from existing concepts, extended by newly identified factors, to postulate a novel theoretical model. Our analysis of a survey with 349 respondents reveals new constructs based on users’ perception of risks and features. We found that risks and features are significantly interrelated and both influence perceived usefulness, the technology acceptance model’s most important construct. Usefulness is diminished by perceived risks while it is increased by crowdsourcing features. Additionally, external motivation yields important influence factors. The revealed interrelations are discussed and should be accounted for in future research and implementations.

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Vorheriges Kapitel When IT Leveraging Competence Meets Uncertainty and Complexity with Social Capital in New Product Development
Nächstes Kapitel Crowd Label Aggregation Under a Belief Function Framework
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Metadaten
Titel
Adoption Factors for Crowdsourcing Based Medical Information Platforms
verfasst von
Till Blesik
Markus Bick
Copyright-Jahr
2016
Buch
Knowledge Science, Engineering and Management

Print ISBN: 978-3-319-47649-0

Electronic ISBN: 978-3-319-47650-6

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-47650-6_14

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