While BHM struggles with predicting new risks, NLP’s topic modeling can enhance its adaptability. The goal is to improve upon previous models by automating risk factor identification.
This research integrates the Bayesian Hierarchical Model (BHM) with Natural Language Processing (NLP) for dynamic risk prediction in supply chains.
Ts. Dr. Sarah Flora Samson Juan, researcher from the Faculty of Computer Science and Information Technology, UNIMAS, has been awarded RM68,000 under the Fundamental Research Grant Scheme (FRGS).
Dr. Sarah and her team’s innovative fusion of the BHM with NLP marks a significant advancement in supply chain risk management, providing a robust and dynamic toolset tailored for the complexities of the modern digital landscape.
Additionally, the research emphasizes the importance of adapting to post-COVID-19 economic challenges by harnessing digital tools. By merging BHM and NLP, the study offers a forward-thinking approach to supply chain risk management.
This not only aids industry leaders in navigating disruptions but also supports national policies that prioritize digital transformation. The combined method promises to streamline risk prediction, aligning with broader efforts to strengthen the global supply chain and enhance data-driven innovation in the manufacturing sector.
Ultimately, the project seeks to ensure resource continuity, minimize supply chain interruptions, and foster a new generation of digital talents tailored to industry needs.
Furthermore, the research’s alignment with governmental initiatives underscores its significance in national economic growth and resilience strategies.
The merging of traditional risk prediction models with advanced digital techniques represents a shift towards more proactive, data-informed decision-making in the supply chain industry.
As industries worldwide grapple with the aftermath of the pandemic, tools like the proposed NLPBHM algorithm become crucial in navigating uncertainties and ensuring business continuity.
The project also emphasizes capacity building, preparing the workforce for a digital future.
By bridging the gap between academia, industry, and policy-making, the study sets a precedent for holistic approaches to modern challenges, emphasizing collaboration, innovation, and adaptability in a rapidly evolving global landscape.
Reported by Seleviawati Tarmizi and Hamizan Sharbini
