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International Transactions in Operational Research
Article . 2024 . Peer-reviewed
License: CC BY
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zbMATH Open
Article . 2025
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Multi‐stage stochastic frontier analysis for simple networks

Multi-stage stochastic frontier analysis for simple networks
Authors: Geraint Johnes; Mike Tsionas; Marwan Izzeldin;

Multi‐stage stochastic frontier analysis for simple networks

Abstract

AbstractWe develop a method for modelling multi‐stage production using stochastic frontier analysis. This approach is suitable for the analysis of costs or output where intermediate outputs become inputs into a subsequent stage of the production process, either within an organisation or in the form of a supply chain. Our focus is on higher education institutions in England, and the purpose is to assess the performance of our novel methods using Markov Chain Monte Carlo methods. Without taking into full account of the complexity of the ‘network’, key decisions cannot be made regarding intake quality, student/staff ratios, per‐student spending or academic reputation (the last of which involves costly decisions in terms of academic openings and the profile of candidates desired for any given university).

Country
United Kingdom
Keywords

330, stochastic frontier analysis, networks, Operations research, mathematical programming

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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).
BIP!Citations provided by BIP!
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!
3
Top 10%
Average
Average
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