Human–AI Collective Intelligence in Demand Planning

Organizations often face challenges that limit the effective use and adoption of AIML in demand planning systems. To address this issue, we focus on the role of such systems that analyze demand forecasts to make inventory order decisions. This study investigates the...

The Human-Robot Duet: AI-Driven Warehouses

Teams of humans and robots have become commonplace in various industrial settings as companies pursue new ways to cut costs and increase efficiency. Although these collaborations have improved operational performance, they are far from realizing their full potential...

Advanced AIML Demand Forecasting

This research explores the effects of exogenous variables on AIML Predictive Algorithm Prophet, such as macroeconomic changes, population trends in relevant regions and disruptions, on the efficacy and accuracy of AIML forecasting algorithms for product demand in the...

Geographical and Industrial Concentrations in Supply Chains

This project researches the impact of Industrial and Geographical Concentrations of Upstream Industries on Supply Chain Performance. The industry might be competitive and contain many suppliers (low industrial concentration) and yet be concentrated in a few nations or...

Supply Chain Stability in Quantum Computing

Quantum computing is poised to revolutionize computational power, offering solutions to problems that were once considered impossible. Recognizing its strategic significance, the U.S. government has underscored the importance of quantum computing in maintaining...