Abstract
Multi-criteria production theory (MCPT) is a generalization of traditional production theories which has been developed in order to integrate concerns of modern management science and economics, in particular sustainability and environmental protection. Such as traditional production theory lays a foundation for cost (and revenue) theory, MCPT can be utilized to expand the knowledge regarding the theory and practice of non-financial performance evaluation, which is of major importance with distinct, conflicting objectives. Based on decision theory, the main idea behind MCPT is the capability to distinguish technologically determined inputs and outputs of a production system’s activity from its desired or undesired impacts on (artificial or natural) environments. The idea is formalized by multiple value functions. The paper clarifies the basic assumptions of MCPT in comparison to those of traditional production theories. For the special cases of linear and of monotonic value functions, two main theorems of MCPT are proven. Their application provides fruitful insights into some procedures and pitfalls of non-financial performance evaluation, especially those regarding ecological economics and data envelopment analysis. The main topics that are discussed address undesirable products and factors, hierarchies of performance evaluations, problems of non-monotonic value functions as well as the rationality of ‘technically inefficient’ production.
Highlights
A one-dimensional measurement of sustainability would presuppose the possibility to aggregate the needs of the present and of all future generations by some kind of welfare function
This paper considers a specific concretization, which is called multicriteria production theory (MCPT), where each of the individual value functions is defined on the relevant inputs and outputs
In their review of multi-criteria decision making (MCDM) and multi-attribute utility theory (MAUT) and their outlines of interesting future research questions, Wallenius et al (2008, pp. 1337 and 1343) wrote: Data envelopment analysis (DEA) has grown in importance and its relationship with multiple objective linear programming (MOLP) has been explored. (...) data envelopment analysis (DEA) and multi-objective linear programming (MOLP) usually have different purposes: DEA is used for performance measurement, whereas MOLP is used for decision aiding choice
Summary
A one-dimensional measurement of sustainability would presuppose the possibility to aggregate the needs of the present and of all future generations by some kind of welfare function. Fruitful insights can be gained, namely into such phenomena as ‘rational inefficiencies’ (Fandel 2009) and into some well-known ‘pitfalls and protocols in DEA’ (Dyson et al 2001), e.g. regarding the selection of relevant inputs and outputs (Afsharian et al 2016) or the treatment of undesirable factors (Wojcik et al 2017) Some of these topics are of particular importance for environmental performance measurement—one of the main strands of research within recent DEA literature, as current surveys show (Liu et al 2013a, b; Lampe and Hilgers 2015).
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