Sustainable Agri-Food Supply Chain Performance Measurement Model for GMO and Non-GMO Using Data Envelopment Analysis Method

Abstract

The increase in food demand in Indonesia is one of the consequences of the imbalance between population growth and declining food products. One of alternative technologies that can be used in plant breeding programs to increase agricultural production, in order to meet food demands, is genetically modified organism (GMO) technology. This technology presents a lot of pros and cons among the public-related impacts that will be accepted by consumers. The purpose of this study was to determine the level of sustainability between GMO and non-GMO foods. The performance measurement model for GMO and non-GMO foods was considered according to the seven issues of sustainability that represented environmental, social, and economic aspects. The assessment method was conducted by using Adjusted Profit (AP) with Total Price Recovery (TPR) indicators and Total Factor Productivity (TFP) by utilizing the Data Envelopment Analysis (DEA) Method. Assessments made on each supply chain component included agriculture, processing, and transport to wholesalers/retailers. This study used numerical examples of rice production in Indonesia. The research results found that the performance of non-GMO rice chain is better than GMO rice. It indicates that non-GMO rice is more sustainable. The results show that the proposed model can be applied to measure the sustainability of GMO and Non-GMO agri-food supply chain performance.