Abstract
Decision-based production theory is a generalization of traditional production theories developed in order to integrate concerns of modern management science and economics, such as sustainability and environmental protection. The main idea is the distinction of technologically determined inputs and outputs of a production system’s activity from its desired or undesired impacts on (artificial or natural) environments, formalized by multiple value functions. The paper extends the literature on the generalization and theoretical foundation of data envelopment analysis (DEA) by decision-based production theory. It provides fruitful insights into some well-known pitfalls and protocols in DEA and is practically useful for the measurement of effectiveness in achieving different, often conflicting sustainability objectives. New results are concerned with hierarchies of DEA evaluations, undesired input and output objects, superfluous or inadequate disposability assumptions as well as problems of nonlinear value functions.
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