AccScience Publishing / IJOSI / Volume 8 / Issue 3 / DOI: 10.6977/IJoSI.202409_8(3).0005
ARTICLE

Predicting the impact of blockchain technology implementation in SMEs 

Divya D1* Arunkumar O N2
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1 Assistant Professor, Symbiosis Centre for Management Studies (SCMS), Symbiosis International (Deemed Univer-sity) (SIU), Bengaluru, Electronics City, Hosur Road, Bengaluru, Karnataka, India
2 Assistant Professor, Symbiosis Institute of Business Management (SIBM), Symbiosis International (Deemed Uni-versity) (SIU), Bengaluru, Electronics City, Hosur Road, Bengaluru, Karnataka, India.

In the last few years, blockchain technology, or BCT, has gained much traction. Small and medium-sized businesses (SMEs) struggle more than their larger counterparts when it comes to technological adaptation because they lack the technology infrastructure required to implement blockchain technologies. The major contribution of this paper is to predict the impact of blockchain technology implementation on the performance of SMEs. A multiple-output regres-sion model is utilized in this research to predict the impact of BCT on SMEs’ performance. The cost of implementing and maintaining blockchain technology, IT project management, compatibility, benefit over other available techno-logical options, and trialability are the independent variables that were consideredin the analysis. Software revision, sophistication level, innovation complexity, and observability are the dependent variables. Researchers and industry professionals can use the study to comprehend how implementing blockchain technology affects SMEs.

Submitted: 30 August 2023 | Revised: 18 November 2023 | Accepted: 5 July 2024 | Published: 30 December 2024
© 2024 by the Author(s). Licensee AccScience Publishing, USA. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC BY-NC 4.0) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Keywords
Blockchain Technology
SMEs
multiple output regression
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International Journal of Systematic Innovation, Electronic ISSN: 2077-8767 Print ISSN: 2077-7973, Published by AccScience Publishing