Assessing blockchain readiness for circular economy integration in the Malaysian palm oil industry using AI-based methods

Ishak, Zurida and Abdullah, Mohd Hafizul Afifi and Tang, Xu Ying and Idris, Aizal Yusrina and Khamis, Shakiroh and Zolkafly, Ahmad Subhi (2026) Assessing blockchain readiness for circular economy integration in the Malaysian palm oil industry using AI-based methods. In: 2026 7th International Conference on Artificial Intelligence and Data Science (AiDAS), 2-3 September 2026, Universiti Malaysia Sabah, Sabah.

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Abstract

The Malaysian palm oil industry is experiencing a sustainability challenge brought about by the global market that requires traceability, transparent, and circular supply chains. Blockchain Technology (BCT) is extensively promoted as one of the major facilitators of supply chain integrity and Circular Economy (CE) integration. The areas prepared to adopt BCT, however, are not well comprehended especially through the lens of the top management which ultimately decides on technology adoption strategies. This paper suggests a combined Technology-Organization-Environment-Human (TOE-HOT) preparedness model to assess block-chain implementation in palm oil supply chain in Malaysia. Due to limited access to palm oil industry stakeholders, secondary data were used from previously published interviews with supply chain professionals. Twelve readiness factors were found, validated, and ranked using Natural Language Processing (NLP), Fuzzy Delphi Method (FDM), and Best Worst Method (BWM). To enhance decision-making accuracy, the AI-driven NLP approach will systematically extracting, categorising, and quantifying key readiness factors from unstructured textual data. The FDM and BWM used to strengthen the validation and prioritisation process. The proposed AI-assisted framework is using NLP to analyze unstructured textual evidence, thus reducing subjectivity to improve the reliability and consistency of the readiness assessment. The dominant themes of the NLP results were transparency, traceability, and security, whereas the most significant readiness factor was traceability identified in the BWM analysis. The policymakers can use the proposed framework as a practical guideline to formulate blockchain adoption strategies and digital transformation policies. Industry practitioners will benefit the policies to identify readiness gaps, prioritise strategic investments, and improve organisational preparedness for blockchain-enabled circular economy initiatives.

Item Type:	Proceeding Paper (Other)
Uncontrolled Keywords:	Blockchain Readiness Assessment, TOE-HOT Framework, Natural Language Processing (NLP), Fuzzy Delphi Method (FDM), Best-Worst Method (BWM)
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User:	Dr. Aizal Yusrina Idris
Date Deposited:	15 Oct 2026 14:51
Last Update:	15 Oct 2026 14:51
Queue Number:	2026-10-Q5616
URI:	http://irep.iium.edu.my/id/eprint/131952
Indexed In:	Google Scholar

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