Measuring productivity in agricultural supply chains under Malmquist index approach

Abstract

The paper seeks to evaluate the changes in efficiency and productivity of supply chain by integrating a supply chain developing an index applicable when supply chains desire to improve cost and compensations. The index is inspired by the Malmquist index as extended to productivity measurement by using both optimistic and pessimistic data envelopment analyses (DEA) simultaneously, which we refer to as the double frontiers data envelopment analysis. The Malmquist productivity index measured from the two different DEA points of view are geometrically averaged to generate an integrated Malmquist productivity index in order to determine the sources of the changes in the productivity of the different configurations of supply chain or decision making units. The model considers both economic and environmental factors by including the variables transport and handling costs, emission offset, inventory cost for lead-time, total truck kilometers, inventory costs, compensations and products shipped. The measurements were performed under the simulation of a supply chain configured as nonintegrated and integrated; to perform the results are computed using non-parametric mathematical programming. Hence, productivity change is decomposed into overall efficiency and cost technical change. Furthermore, overall efficiency change is decomposed into technical and efficiency change. These decompositions provide a clearer picture of the root sources of productivity change. Efficiency improvement efforts in supply chains should target the least efficient configurations identified in this paper. Practices in the most efficient supply chains should be further investigated to be replicated when possible. The paper provides a contemporary overview of supply chains efficiency and productivity measures for decision makers’ choice among different configurations.