Application Of Random Regret Minimization Model With Convexity-Concavity Parameter For Binomial Mode Choice Analysis

In 2008 Random Regret Minimization (RRM) theory was developed, which facilitated the development of the voting behavior theory (choice behavior), in which a state of choice behavior minimizes regret that may arise from the selection. RRM theory has a different approach than its counterparts which is...

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Main Author:	Surbakti, Medis Sejahtera
Format:	Thesis
Language:	English
Published:	2017
Subjects:	T Technology
Online Access:	http://eprints.usm.my/45786/1/Application%20Of%20Random%20Regret%20Minimization%20Model%20With%20Convexity-Concavity%20Parameter%20For%20Binomial%20Mode%20Choice%20Analysis.pdf
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spelling	my-usm-ep.457862021-11-17T03:42:16Z Application Of Random Regret Minimization Model With Convexity-Concavity Parameter For Binomial Mode Choice Analysis 2017-04 Surbakti, Medis Sejahtera T Technology TA Engineering (General). Civil engineering (General) In 2008 Random Regret Minimization (RRM) theory was developed, which facilitated the development of the voting behavior theory (choice behavior), in which a state of choice behavior minimizes regret that may arise from the selection. RRM theory has a different approach than its counterparts which is known as Random Utility Maximization (RUM), that are developed based on the economic theory which emphasizes the use of rationality in the selection process. This thesis study aims to demonstrate differences in the results in the analysis of RUM and RRM in the case of the mode choice process. In this study concavity and convexity parameters were used, which can determine the tendency of passengers regarding selecting the attributes of the chosen mode. Research was done by sampling of passengers on the Bandung-Jakarta route, where the passenger can select two modes of transport, namely rail and bus travel. From the questionnaire given to 1200 respondents, 633 and 386 Revealed Preference and Stated Preference questionnaire were obtained respectively. RP Model for mode choice between Bandung to Jakarta with usiness/work trip was affected by the access to the train station or travel bus pool. RRM model with concave and convex parameter has better performance than RUM model when the passenger chooses the risky choice (Work or Business trip). The result of VoT for RRM is Rp. 15,710/hour. This VoT are below the normal VoT, which is about Rp. 20,000/hour, but slightly above RUM VoT. This suggests that RRM 2014 provide estimates that is more or less the same as the existing RUM models. This study concludes that the value of 2017-04 Thesis http://eprints.usm.my/45786/ http://eprints.usm.my/45786/1/Application%20Of%20Random%20Regret%20Minimization%20Model%20With%20Convexity-Concavity%20Parameter%20For%20Binomial%20Mode%20Choice%20Analysis.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Kejuruteraan Awam
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	T Technology T Technology
spellingShingle	T Technology T Technology Surbakti, Medis Sejahtera Application Of Random Regret Minimization Model With Convexity-Concavity Parameter For Binomial Mode Choice Analysis
description	In 2008 Random Regret Minimization (RRM) theory was developed, which facilitated the development of the voting behavior theory (choice behavior), in which a state of choice behavior minimizes regret that may arise from the selection. RRM theory has a different approach than its counterparts which is known as Random Utility Maximization (RUM), that are developed based on the economic theory which emphasizes the use of rationality in the selection process. This thesis study aims to demonstrate differences in the results in the analysis of RUM and RRM in the case of the mode choice process. In this study concavity and convexity parameters were used, which can determine the tendency of passengers regarding selecting the attributes of the chosen mode. Research was done by sampling of passengers on the Bandung-Jakarta route, where the passenger can select two modes of transport, namely rail and bus travel. From the questionnaire given to 1200 respondents, 633 and 386 Revealed Preference and Stated Preference questionnaire were obtained respectively. RP Model for mode choice between Bandung to Jakarta with usiness/work trip was affected by the access to the train station or travel bus pool. RRM model with concave and convex parameter has better performance than RUM model when the passenger chooses the risky choice (Work or Business trip). The result of VoT for RRM is Rp. 15,710/hour. This VoT are below the normal VoT, which is about Rp. 20,000/hour, but slightly above RUM VoT. This suggests that RRM 2014 provide estimates that is more or less the same as the existing RUM models. This study concludes that the value of
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Surbakti, Medis Sejahtera
author_facet	Surbakti, Medis Sejahtera
author_sort	Surbakti, Medis Sejahtera
title	Application Of Random Regret Minimization Model With Convexity-Concavity Parameter For Binomial Mode Choice Analysis
title_short	Application Of Random Regret Minimization Model With Convexity-Concavity Parameter For Binomial Mode Choice Analysis
title_full	Application Of Random Regret Minimization Model With Convexity-Concavity Parameter For Binomial Mode Choice Analysis
title_fullStr	Application Of Random Regret Minimization Model With Convexity-Concavity Parameter For Binomial Mode Choice Analysis
title_full_unstemmed	Application Of Random Regret Minimization Model With Convexity-Concavity Parameter For Binomial Mode Choice Analysis
title_sort	application of random regret minimization model with convexity-concavity parameter for binomial mode choice analysis
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Kejuruteraan Awam
publishDate	2017
url	http://eprints.usm.my/45786/1/Application%20Of%20Random%20Regret%20Minimization%20Model%20With%20Convexity-Concavity%20Parameter%20For%20Binomial%20Mode%20Choice%20Analysis.pdf
_version_	1747821565880303616

Application Of Random Regret Minimization Model With Convexity-Concavity Parameter For Binomial Mode Choice Analysis

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