Abstract
Agricultural supply chain (ASC) plays a vital role for sustainability as it is the main source of food supply. ASC encounters more sources of risk due to seasonality, perishability, and weather conditions, which makes the global food security system complex. This paper develops an optimization model for a perishable product supply chain to decide the optimal risk management strategy that maximizes the decision maker's expected profit under demand and price uncertainty. A base-case scenario is considered to show the impact of risk management strategy on performance improvement. The expected profit of the decision maker is obtained for different combination of strategies, and sensitivity analysis is performed to show the impact of perishability on the percentage of improvement from the base case scenario. The results show that backup supplier strategy is very effective during the yield disruption, but it is not as effective during harvest disruption. Hence, a single approach is inadequate to provide solution in all types of risk scenarios; thus, the combination of approaches is most effective.
Highlights
The economy of a country depends on agriculture as it is the primary source of food supplies
The existing literature has researched on Agricultural supply chain (ASC) risk management to a very limited extent, in the field of perishability in risk management modelling
This study develops an optimization model by analysing the effectiveness of risk management strategies on the performance of the agricultural supply chain under demand and price uncertainty together
Summary
The economy of a country depends on agriculture as it is the primary source of food supplies. Behzadi et al (2017) considered exponential perishability function in a two-stage stochastic programming model They provided optimal strategy for mitigating the risks in ASC, but they didn’t consider demand and price uncertainty in their model. This paper develops a model that helps the ASC planners to select suitable strategies considering perishability with demand and price uncertainties to maximize his expected profit. The paper design optimal strategy while analysing the effectiveness of risk management (both robust and resilient) strategies, and compared the performance improvement of different strategies under price and demand uncertainty in the line of Behzadi et al (2017)’ s work. We have applied the model to a perishable product supply chain to analyse the effectiveness of robust/resilient strategies under harvest time and yield disruptions considering demand and price uncertainty.
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