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This research deals with the evaluation of the efficiency of consumer freight package delivery. Model inputs include number of delivery and administrative employees, labor hours, operating costs, and number of deliver vehicles. Outputs include number of packages delivered, percent on-time, percent lost, percent damaged, revenue per package, and customer satisfaction. The methodology used to evaluate the efficiency of the decision-making units (DMUs) under consideration is data envelopment analysis (DEA) involving multiple criteria. The inclusion of additional criteria beyond basic DEA efficiency can improve discriminating power between DMUs and also tends to yield more reasonable weights on model inputs and outputs.