A machine learning method to predict the technology adoption of blockchain in Palestinian firms

Ihab K.A. Hamdan, Eli Sumarliah and Fauziyah Fauziyah

International Journal of Emerging Markets, 2021, vol. 17, issue 4, 1008-1029

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: Artificial intelligence; Machine learning; Blockchain; Bayesian network; Adoption intention; Palestine; SMEs (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eme:ijoemp:ijoem-05-2021-0769

DOI: 10.1108/IJOEM-05-2021-0769

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