Agricultural Supply Chain Risk Management Under Price and Demand Uncertainty

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.

Evaluation of the agri-food supply chain risks: the circular economy context

“…In the agri-food sector, they can cause lower yields, problems when collecting crops (harvesting), problems in supplying processing facilities due to closed or impassable roads. Some of the research investigating these risks is carried out by Ray (2021). Product features risks (Risk 2) include risks arising from different product characteristics, such as types of goods, appearances, assortment, demand, special requirements for the implementation of the processes of transshipment, storage and transport.…”

“…Not even the most comprehensive research in this field, some of which were carried out by Ray (2021) and Sharma et al (2020) simultaneously observe all the analyzed risk groups, nor analyze them from the perspective of different stakeholders. This study provides valuable insights into the basic requirements of each of the stakeholder groups and indicates the risks that each of them should focus on in the process of predicting, preventing, mitigating or eliminating the consequences thereof.…”

“…Risk analysis and management in agri-food supply chains has been the subject of numerous studies (e.g. Ali et al (2022), Wicaksono and Ill es (2022), Ray (2021)). In these studies, several groups of risks stand out as the main focus of research.…”

Effective Selection of Entities From Heterogeneous and Large Resources Using a Cooperative Neuro-Fuzzy System

“…Stand alone machine learning systems without any hybridization are also used in item evaluation and tracking in the food industry (Lukyamuzi, Ngubiri, & Okori, 2020), agricultural products (Ray, 2021), marble industries (Shukla, Jangid, Soni, & Kumar, 2019), evaluation of students performance (Aggarwal, Mittal, & Bali, 2021), smart cities for multi criteria decisions (Juneja, Juneja, Bali, & Mahajan, 2021), and customer value generation (Herrera, Carvajal-Prieto, Uriona Maldonado, & Ojeda, 2019), etc. Various other applications in the context of developing nations are discussed in (Omamo, Rodrigues, & Muliaro, 2020) that utilize the systems dynamics model.…”

Hybrid Computational Intelligence System for Fashion Design

“…An ontology-based garment recommendation is suggested in the work of (Ajmani, Ghosh, Mallik, & Chaudhury, 2013). Different researchers propose the use of advanced machine learning technologies in the context of developing countries (Omamo, Rodrigues, & Muliaro, 2020), modelling customer value generation (Herrera, Carvajal-Prieto, Uriona-Maldonado, & Ojeda, 2019), and supply chain risk management for products (Ray, 2021).…”