Affiliations: [a] Finance and Accounting Research Center, Nanfang College, School of Accounting, Guangzhou, Guangdong, P. R. China
| [b] Department of Accounting, Chinese Culture University, Taipei, Taiwan
| [c] Department of Economics, Chinese Culture University, Taipei, Taiwan
| [d] Department of Intelligent Commerce, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan
Correspondence:
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Corresponding author. Sin-Jin Lin, Department of Intelligent Commerce, National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan. E-mail: annman1204@gmail.com.
Abstract: Blockchain technology holds considerable amount of potential for all types of industries by executing transactions in a verifiable, efficient, and permanent channel. It has been widely viewed as a standard requirement for making industry ready for the future, but when it comes to practical applications, it still arouses numerous risks/challenges that need to be addressed. Therefore, it is essential to address this gap and establish a comprehensive and effective practical framework to align the information technology revolution with sustainable value creation. The purpose of this research is to realize to what extent an enterprise legacy system’s transformation benefits a blockchain-based system and to minimize its specific risk through a hybrid fuzzy MRDM (multiple rule-based decision making) model that integrates data envelopment analysis with rough set theory (DEA-RST) and the fuzzy DEMATEL approach grounded on a questionnaire derived from domain experts. We aim to point out the inherent risks of blockchain-based technology adoption and to assist senior engineers in designing or adopting a suitable architecture for practical operation and planning of any future integration and development. The potential risk evaluation of business blockchain adoption reveals that the priority improvement sequence based on dimensions is smart contract risk, value transfer risk, and standard risk. Furthermore, law and regulation are the most critical criteria.
