Measuring productivity of dairy industry companies: an approach with data envelopment analysis

Abstract

PurposeThis research had two main objectives: To measure the productivity of companies in the Colombian dairy industry and to identify efficient decision-making units (DMUs) that can be used as work sample in future case studies.Design/methodology/approachIn the measurement of productivity, financial variables were considered for a sample of 19 DMUs. Efficient companies were identified through the data envelopment analysis (DEAs) methodology with the VRS model oriented to inputs and outputs. The input variables analyzed were “current asset,” “property, plant and equipment,” “non-current liability” and “equity,” while the output variables were “revenue” and “profit.”FindingsFindings revealed that seven DMUs are efficient in the input and output orientation and that companies of different sizes and with or without quality certifications are efficient in the sample analyzed. Additionally, the benchmark efficient DMUs were identified for each of the non-efficient DMUs.Research limitations/implicationsThe implications for the research include the contribution to the theory, on the one hand, with the analysis of the current state of the literature on the use of DEA in the food sector, and on the other, with the use of DEA to measure the productivity of Colombian dairy industry companies and with the identification of a sample of efficient units that can be analyzed in future case studies.Originality/valueThis article is novel and pioneering because it measures for the first time the productivity of DMUs of the Colombian dairy industry, in addition to including the current state of the literature on the application of the DEA methodology in the food sector. These findings contribute to the consolidation of the theory and also provide inputs for researchers, practitioners, managers, and policy makers.