Automatic nested logit models with application to further education college demand in Northern Ireland

Discrete choice models are a particular class of models which are applied when analysing a decision maker's choice from a set of alternatives. One of the most commonly applied models is the Nested Logit (NL) model, where the set of alternatives are separated into groups or nests, with no overla...

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Main Author: McMinn, Ashley
Published: Queen's University Belfast 2017
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Online Access:http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.727758
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spelling ndltd-bl.uk-oai-ethos.bl.uk-7277582017-12-24T16:54:21ZAutomatic nested logit models with application to further education college demand in Northern IrelandMcMinn, Ashley2017Discrete choice models are a particular class of models which are applied when analysing a decision maker's choice from a set of alternatives. One of the most commonly applied models is the Nested Logit (NL) model, where the set of alternatives are separated into groups or nests, with no overlap. The Cross-Nested Logit (CNL) model allows for an overlap between nests, where each alternative belongs in part, to a particular nest. Alternatives which are grouped together are assumed to exhibit similar unobserved characteristics influencing each decision maker's choice. The analyst assigns each of the alternatives to a nest. This is known as the nesting structure. Given many alternatives, it becomes near impossible to analyse each one. There is also the additional complication that many of the nesting structures will output infeasible parameter estimates in terms of the nesting parameters. The approach developed in this thesis is autonomic in the sense that a nesting structure is empirically generated automatically, therefore removing the need for the analyst to impose a potentially infeasible nesting structure on the data. The Autonomic Nested Logit (ANL) and Autonomic Cross-Nested Logit {ACNL) models developed in this thesis, use a nesting structure that has been output from performing cluster analysis on the data. The number of clusters is determined using an observation weighted version of the cophenetic correlation coefficient. Given sufficient variables to segregate the data, these autonomic models show promising results. This autonomic approach is applied to data concerning a student's choice of Further Education campus in Northern Ireland in the academic year 2008/2009. The resulting model can act as a decision support tool to inform investment strategy regarding Further Education infrastructure in Northern Ireland.519.5Queen's University Belfasthttp://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.727758Electronic Thesis or Dissertation
collection NDLTD
sources NDLTD
topic 519.5
spellingShingle 519.5
McMinn, Ashley
Automatic nested logit models with application to further education college demand in Northern Ireland
description Discrete choice models are a particular class of models which are applied when analysing a decision maker's choice from a set of alternatives. One of the most commonly applied models is the Nested Logit (NL) model, where the set of alternatives are separated into groups or nests, with no overlap. The Cross-Nested Logit (CNL) model allows for an overlap between nests, where each alternative belongs in part, to a particular nest. Alternatives which are grouped together are assumed to exhibit similar unobserved characteristics influencing each decision maker's choice. The analyst assigns each of the alternatives to a nest. This is known as the nesting structure. Given many alternatives, it becomes near impossible to analyse each one. There is also the additional complication that many of the nesting structures will output infeasible parameter estimates in terms of the nesting parameters. The approach developed in this thesis is autonomic in the sense that a nesting structure is empirically generated automatically, therefore removing the need for the analyst to impose a potentially infeasible nesting structure on the data. The Autonomic Nested Logit (ANL) and Autonomic Cross-Nested Logit {ACNL) models developed in this thesis, use a nesting structure that has been output from performing cluster analysis on the data. The number of clusters is determined using an observation weighted version of the cophenetic correlation coefficient. Given sufficient variables to segregate the data, these autonomic models show promising results. This autonomic approach is applied to data concerning a student's choice of Further Education campus in Northern Ireland in the academic year 2008/2009. The resulting model can act as a decision support tool to inform investment strategy regarding Further Education infrastructure in Northern Ireland.
author McMinn, Ashley
author_facet McMinn, Ashley
author_sort McMinn, Ashley
title Automatic nested logit models with application to further education college demand in Northern Ireland
title_short Automatic nested logit models with application to further education college demand in Northern Ireland
title_full Automatic nested logit models with application to further education college demand in Northern Ireland
title_fullStr Automatic nested logit models with application to further education college demand in Northern Ireland
title_full_unstemmed Automatic nested logit models with application to further education college demand in Northern Ireland
title_sort automatic nested logit models with application to further education college demand in northern ireland
publisher Queen's University Belfast
publishDate 2017
url http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.727758
work_keys_str_mv AT mcminnashley automaticnestedlogitmodelswithapplicationtofurthereducationcollegedemandinnorthernireland
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