In Annals of operations research
Fake news and disinformation (FNaD) are increasingly being circulated through various online and social networking platforms, causing widespread disruptions and influencing decision-making perceptions. Despite the growing importance of detecting fake news in politics, relatively limited research efforts have been made to develop artificial intelligence (AI) and machine learning (ML) oriented FNaD detection models suited to minimize supply chain disruptions (SCDs). Using a combination of AI and ML, and case studies based on data collected from Indonesia, Malaysia, and Pakistan, we developed a FNaD detection model aimed at preventing SCDs. This model based on multiple data sources has shown evidence of its effectiveness in managerial decision-making. Our study further contributes to the supply chain and AI-ML literature, provides practical insights, and points to future research directions.
Akhtar Pervaiz, Ghouri Arsalan Mujahid, Khan Haseeb Ur Rehman, Amin Ul Haq Mirza, Awan Usama, Zahoor Nadia, Khan Zaheer, Ashraf Aniqa
2022-Nov-01
Artificial intelligence, Disinformation, Effective decision making, Fake news, Machine learning, Misinformation, Supply chain disruptions
