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dc.contributor.authorChatterjee, S.
dc.contributor.authorRana, Nripendra P.
dc.contributor.authorDwivedi, Y.K.
dc.contributor.authorBaabdullah, A.M.
dc.date.accessioned2021-05-07T22:12:28Z
dc.date.accessioned2021-05-20T13:38:06Z
dc.date.available2021-05-07T22:12:28Z
dc.date.available2021-05-20T13:38:06Z
dc.date.issued2021-09
dc.identifier.citationChatterjee S, Rana NP, Dwivedi YK et al (2021) Understanding AI adoption in manufacturing and production firms using an integrated TAM-TOE model. Technological Forecasting and Social Change. 170: 120880.en_US
dc.identifier.urihttp://hdl.handle.net/10454/18484
dc.descriptionYes
dc.description.abstractThis study aims to identify how environmental, technological, and social factors influence the adoption of Industry 4.0 in the context of digital manufacturing. The Industry 4.0 era has brought a breakthrough in advanced technologies in fields such as nanotechnology, quantum computing, biotechnology, artificial intelligence, robotics, the Internet of Things, fifth-generation wireless technology, fully autonomous vehicles, 3D printing and so on. In this study, we attempted to identify the socioenvironmental and technological factors that influence the adoption of artificial intelligence embedded technology by digital manufacturing and production organizations. In doing so, the extended technology-organization-environment (TOE) framework is used to explore the applicability of Industry 4.0. A conceptual model was proposed that used an integrated technology acceptance model (TAM)-TOE model and was tested using survey-based data collected from 340 employees of small, medium and large organizations. The results highlight that all the relationships, except organizational readiness, organizational compatibility and partner support on perceived ease of use, were found to be significant in the context of digital manufacturing and production organizations. The results further indicated that leadership support acts as a countable factor to moderate such an adoption.en_US
dc.language.isoenen_US
dc.rights© 2021 Elsevier. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license (https://creativecommons.org/licenses/by-nc-nd/4.0/)en_US
dc.subjectArtificial Intelligence
dc.subjectIndustry 4.0
dc.subjectManufacturing and production firms
dc.subjectTOE framework
dc.subjectTAM
dc.subjectLeadership support
dc.titleUnderstanding AI adoption in manufacturing and production firms using an integrated TAM-TOE modelen_US
dc.status.refereedYes
dc.date.Accepted07/05/2021
dc.typeArticle
dc.type.versionAccepted manuscript
dc.identifier.doihttps://doi.org/10.1016/j.techfore.2021.120880
dc.rights.licenseCC-BY-NC-ND
dc.date.updated2021-05-07T21:12:38Z
refterms.dateFOA2021-05-20T13:39:35Z
dc.openaccess.statusopenAccess


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