Sustainable Modern Agricultural Technology Assessment by a Multistakeholder Transdisciplinary Approach

Abstract

With the rise of emerging technology in the fourth industrial revolution, modern agricultural technologies are gradually adopted to increase the yield and efficiency. Meanwhile, they also may bring the negative effect to social and environment sustainable development. Ignoring the requirement of sustainability will have an impact on the development of the country and society. Besides, the uncertainty and multistakeholder on sustainable modern agricultural technology assessment (SMATA) have made this appraisal much more complex, including their entanglement with rapidly changing cultural norms and social relations. Thus, in order to address these concerns, this article develops a holistic multistakeholder transdisciplinary approach with supporting SMATA. More precisely, due to the uncertainty of environment and vague knowledge possessed by stakeholders, we first investigate the evaluation measure of SMATA by introducing <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$q$</tex-math></inline-formula> -rung orthopair fuzzy set ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$q$</tex-math></inline-formula> -ROFS). Second, group opinion of stakeholders is fused by developing a new transdisciplinary evaluation aggregation operator. Third, to achieve more robust weights of key factors, three extended best worst method models from three different comparative perspectives of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$q$</tex-math></inline-formula> -ROFS are established. The final weight of key factors is further obtained by utilizing the variable entropy method. Fourth, we design a new decision approach of SMATA by improving evaluation based on distance from average solution method. Finally, a modern agricultural project base of Xichang city in China is used to demonstrate the effectiveness and rationality of our proposed SMATA method, including the simulation experiments on sensitivity analysis and comparative analysis. These results provide some exploratory insight and guidelines of SMATA for government and organization.