A machine learning method to predict the technology adoption of blockchain in Palestinian firms
International Journal of Emerging Markets
ISSN: 1746-8809
Article publication date: 8 December 2021
Issue publication date: 16 May 2022
Abstract
Purpose
The study aims to deliver a decision support system for business leaders to estimate the potential for effective technological adoption of the blockchain (TAB) with a machine learning approach.
Design/methodology/approach
This study uses a Bayesian network examination to develop an extrapolative system of decision support, highlighting the influential determinants that managers can employ to predict the TAB possibilities in their companies. Data were gathered from 167 SMEs in the largest industrial sectors in Palestine.
Findings
The results reveal perceived benefit and ease of use as the most influential determinants of the TAB.
Originality/value
This research is an initial effort to examine factors influencing TAB in the perspective of SMEs in Palestine using machine learning algorithms.
Keywords
Acknowledgements
Conflict of interests: None.
Corrigendum: It has come to the attention of the publisher that the article by Ihab K.A. Hamdan, Wulamu Aziguli, Dezheng Zhang, Eli Sumarliah, Fauziyah Fauziyah (2021), “A machine learning method to predict the technology adoption of blockchain in Palestinian firms”, published in the International Journal of Emerging Markets, Vol. 17 No. 4, pp. 1008-1029, https://doi.org/10.1108/IJOEM-05-2021-0769, incorrectly included Wulamu Aziguli and Dezheng Zhang as authors. Our guidelines make it clear that authors must meet all four of the authorship principles outlined by the International Council of Medical Journal Editors. This has now been corrected in the online version of the article. The authors sincerely apologize for this mistake.
Citation
Hamdan, I.K.A., Sumarliah, E. and Fauziyah, F. (2022), "A machine learning method to predict the technology adoption of blockchain in Palestinian firms", International Journal of Emerging Markets, Vol. 17 No. 4, pp. 1008-1029. https://doi.org/10.1108/IJOEM-05-2021-0769
Publisher
:Emerald Publishing Limited
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