Machine Learning Adoption based on the TOE Framework: A Quantitative Study

Anne Zöll, Verena Eitle and Peter Buxmann

Publications of Darmstadt Technical University, Institute for Business Studies (BWL) from Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL)

Abstract: The increasing use of machine learning (ML) in businesses is ubiquitous in research and in practice. Even though ML has become one of the key technologies in recent years, organizations have difficulties adopting ML applications. Implementing ML is a challenging task for organizations due to its new programming paradigm and the significant organizational changes. In order to increase the adoption rate of ML, our study seeks to examine which generic and specific factors of the technological-organizational-environmental (TOE) framework leverage ML adoption. We validate the impact of these factors on ML adoption through a quantitative research design. Our study contributes to research by extending the TOE framework by adding ML specifications and demonstrating a moderator effect of firm size on the relationship between technology competence and ML adoption.

Date: 2022-07-07
New Economics Papers: this item is included in nep-big and nep-cmp
Note: for complete metadata visit http://tubiblio.ulb.tu-darmstadt.de/133079/
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Persistent link: https://EconPapers.repec.org/RePEc:dar:wpaper:133079

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