Risk Prediction and Measurement in Supply Chain

School: 
Supervisor: 
Professor Elizabeth Chang
Scientia Project Summary: 
To harness the unique power of chain management (SCM), organizations should tackle various associated risks such as disruptions, delays. This project focuses on operational risks which represents the uncertainty arising of the non-commitment of day-to-day operations. Shortage of data in forecasting possible operational failures is the main challenge here which can be addressed by harnessing the power of personal relationship based information. However, measuring the credibility of such information is vital as low credibility can be misleading. Thus the aim of this work is to measurement credibility of Personal Relationship based Information in SCM by using data analytic techniques.