Abstract
Data envelopment analysis (DEA) is a methodology for evaluating the relative efficiencies of peer decision-making units (DMUs), in a multiple input/output setting. While it is generally assumed that all outputs are impacted by all inputs, there are many situations where this may not be the case. For example, in a food manufacturing setting, certain foods are exempt from nutrition labeling and as a result are not influenced by labeling resources. This chapter extends the conventional DEA methodology to allow for the measurement of technical efficiency in situations where only partial input-to-output impacts exist. The new methodology involves viewing the DMU as a business unit, consisting of a set of mutually exclusive subunits, each of which can be treated in the conventional DEA sense.
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