Exploring the Parameters of Agility & Resilience in Food Supply Chain

Abstract

Agility and Resilience are the two most talked concepts of handling supply chain risk management. Agility is unexpected and ad hoc alteration to any unforeseen events which are happening at a particular time. It also means the ability to quickly respond to the unpredictable changes which can occur in the supply chain. Resilience is defined as ability to survive despite the weathering changes which can occur for any events of risk at any time in the supply chain. There are several of approaches which discusses means tomeasure supply chain performance correlated to discreet variables like agility and resilience. In our approach to this paper, we have arrived at mathematical regression model using Augmented Dickey Fuller Model under assumption that supply chain is a discreet time series function and it follows a stochastic process. The paper discusses the approach to arrive at weightage factor using a curve-fitting technique for the independent variables effecting agility and resilience. In the mathematical construct using a non-linear regression analysis technique,the weightage factors are studied over the standard Likert’s scale of 0-10. This relative scalar measurement provides input to the curve-fit to arrive at weights to the regression model. The weights of each of the independent variables are considered in the stationary time-dependent regression model to understand the delta of the measured variables, in our case agility and resilience.