Developing a Service Management Framework in the Agricultural Supply Chain with Fuzzy Weighted Average

The main objective of this research is to create a comprehensive and adaptable framework for assessing performance in agricultural supply chains and develop two improving approaches. The most relevant performance measures are selected to assess the current status of services in agricultural supply chains (ASCs). The contribution of this research is related to the selection of key performance indicators (KPIs) and approaches for enhancing ASC performance. The proposed framework comprises performance measurement and a service selection process. Two approaches have been developed based on the selected KPIs of services in ASC to identify which services require improvement. The proposed approaches are robust and versatile tools for agricultural managers to strategize and enhance their supply chains. A case study is also presented from Iran. For this region, selection approaches prioritize agricultural services such as postproduction consulting, financial support, mechanization, business consulting, and input supply. The framework shows that these services should be improved in order to better meet the needs of the region under study.