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Article . 2010
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Quantitative modelling of benchmarking process

Authors: Tchangani, Ayeley;

Quantitative modelling of benchmarking process

Abstract

In this paper, we consider the problem of establishing a quantitative model allowing, given a set of production units (enterprises, plants, banks, university departments, etc.), to determine those units that can be considered as benchmarks in terms of production efficiency and to evaluate for a unit, that is not a benchmark the gap that separates it from the benchmarks. A production unit is considered here as a transformation centre that consumes resources (input items) of different nature (information, human resources, energy, money, etc.) to deliver some products (output items) of different nature as well (manufactured products, services, information, energy, etc.). This benchmarking problem is, therefore, a multicriteria ranking problem that necessitates sensitivity analysis process to determine which items a given unit must improve in order to become as efficient as benchmark unit(s). We propose in this paper to formulate this problem using satisficing games, an evaluation method, that is, based on two measures namely selectability measure (that measures production level) and rejectability measure (that is, related to resources consumption) for each unit or alternative. Units for which the selectability measure exceeds the rejectability one will be considered as satisficing units and the benchmark units are those satisficing units that are not dominated.

Country
France
Keywords

000, Analytic hierarchy process, Satisficing games, Group decision, Efficiency, Multicriteria ranking, Benchmarking, Production units, Autre

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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