Modelling the Risk Factors in Agriculture

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Purpose: The risk in agriculture is putting huge pressure on farmers life, which can be controlled with a proper risk management strategy. Therefore, this study aims to find out the key risk factors or drivers which affects the agriculture sector and how they are influencing each other.

Design/Methodology/Approach: By doing the extensive review of literature from various databases, we find out 12 risk factors involve in agriculture. Then, with the aids of empirical research by surveying farmers and experts, we validate the risk factors. Then, we develop a structure model with the help of interpretive structural modelling (ISM). The ISM model shows us which risk factors have the highest level of importance and needs to be controlled. Then, on the basis of their driving and dependency power, these risk factors are divided into four quadrants using the Matrice d' Impacts Croises – Multiplication Appliquee an un classement (MICMAC) method.

Finding: The ISM technique and empirical study help us to divide the risk factors on the basis of their driving power and dependency power. After that from continue analysis, we find out the interrelationships between these risk factors and how they affect the agriculture sector. Price variability is found to be a dependent risk factor while Climate, Environment regulations and Government policies and regulations are emerged as independent basic risk factors.

Research implications: This research will be very helpful for Agri business company in risk management strategy. This study is also helpful for Agri insurance company and Government while making the new policy for agriculture sector.

Originality/Value:  For the first-time key risk factors related to agriculture is addressed by using theoretical review and interpretive structure modelling (ISM).

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