“…ISM and fuzzy MICMAC approach for performance measurement factors ISM and fuzzy MICMAC method was selected because it enables the study of the diffusion of impacts through reaction paths and loops for developing a hierarchy of performance Vlajic et al (2013) In this article, a new method for vulnerability assessment, the VULA method, is presented The impact of supply chain performance drivers and value chain on companies: a case study from the food industry in Jordan Mazzawi and Alawamleh (2013) This research is conducted to study the supply chain performance drivers and the value chain and evaluate their implementation and their effect on companies A model for measuring technology capability in the agrifood industry companies De Mori et al (2016) This paper aims to focus on technology capability and develop a model for measuring agri-food industry companies Total factor productivity: a framework for measuring agri-food supply chain performance towards sustainability Gait an-Cremaschi et al (2017) This document develops two unique metrics, based on a total factor productivity indexing approach, to compare products in terms of their sustainability performance. Both metrics are adjusted to internalise food production's social and environmental externalities and consider the sustainability effects of the stages along the agri-food supply chains Agri-food supply chain performance: an empirical impact of risk Yeboah Nyamah et al (2017) The purpose of this paper is to examine the key risk components (probability and consequence) and their respective thresholds affecting agri-food supply chain operations in Ghana Measuring agri-food supply chain performance and risk through a new analytical framework: a case study of New Zealand dairy Moazzam et al (2018) This study provides how agri-food supply chain managers can employ a new analytical framework in conjunction with the SCOR model to understand the complicated performance measurement indicators applied across their relevant agri-food production systems and supply chains (continued ) measurement factors (Bhosale and Kant, 2016;Meena et al, 2017;Sharma et al, 2017). With integrated ISM and fuzzy MICMAC, the performance measurement factors are prioritized (Dube and Gawande, 2016;Shohan et al, 2019;Zhao et al, 2020), and metrics are selected.…”