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The probabilistic of abandoned project status using ordinal logistic regression analysis

The abandoned housing project leads to many negative impacts on the environment, Malaysian economy and society. The homebuyers are the victim in this matter since they are unable to own their dream house and need to pay for their existing rental house. Even worse, unfortunate homebuyers are not allo...

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Main Authors: Salam, Saidah An’nisaa, Nur Farhayu, Ariffin, Mohamad Idris, Ali, Noram Irwan, Ramli
Format: Conference or Workshop Item
Language:English
English
Published: AIP Publishing 2023
Subjects:
TA Engineering (General). Civil engineering (General)
TH Building construction
Online Access:http://umpir.ump.edu.my/id/eprint/39145/1/AIP%20PROCEEDING%200015_AN%27NISAA_WSCC2021.pdf
http://umpir.ump.edu.my/id/eprint/39145/7/The%20probabilistic%20of%20abandoned%20project%20status%20using%20ordinal%20logistic%20regression%20analysis.pdf
http://umpir.ump.edu.my/id/eprint/39145/
https://doi.org/10.1063/5.0113901
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spelling my.ump.umpir.391452023-11-02T06:22:14Z http://umpir.ump.edu.my/id/eprint/39145/ The probabilistic of abandoned project status using ordinal logistic regression analysis Salam, Saidah An’nisaa Nur Farhayu, Ariffin Mohamad Idris, Ali Noram Irwan, Ramli TA Engineering (General). Civil engineering (General) TH Building construction The abandoned housing project leads to many negative impacts on the environment, Malaysian economy and society. The homebuyers are the victim in this matter since they are unable to own their dream house and need to pay for their existing rental house. Even worse, unfortunate homebuyers are not allowed to cross over Malaysia and get other loans from the financial institution if they failed to pay for the abandoned housing loan. Therefore, the objective of this paper is to identify the factors that contribute to the abandoned housing projects and their impact on the nation, environment, and society. Through extensive literature review from the previous studies, several factors and impacts have been listed. A quantitative research methodology was conducted in data collection through a well-designed questionnaire which was based on the extensive literature review, semi-structured interviews, and discussions with the expert panels. The questionnaires had been distributed to 100 respondents from the population of housing development stakeholders such as developers, contractors, consultants, and authorities. After that, the data were analysed using the descriptive statistics of Ordinal Logistic Regression (OLR) method whereby the relationship between each factor that contributes to the abandoned housing project and the project status for 10 selected respondents from the interview session was obtained. Further, this study develops the Probabilistic Model of Abandoned Project Status (PMAPS) to show the relationship between the factors of abandoned housing projects and the probability of project status. The findings conclude that the main factors of abandoned housing projects are financial factors, followed by project participant factors, project management factors, market signal, procurement factors, and external factors. The PMAPS can predict the project status with regards to the problem (factors of abandoned housing project) faced in each project. These findings could assist the stakeholders involved in predicting their project status regards to the problem faced. It also can be a guide for the development practitioner to apply the appropriate mitigation plan to avoid project abandonment. . AIP Publishing 2023-05 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/39145/1/AIP%20PROCEEDING%200015_AN%27NISAA_WSCC2021.pdf pdf en http://umpir.ump.edu.my/id/eprint/39145/7/The%20probabilistic%20of%20abandoned%20project%20status%20using%20ordinal%20logistic%20regression%20analysis.pdf Salam, Saidah An’nisaa and Nur Farhayu, Ariffin and Mohamad Idris, Ali and Noram Irwan, Ramli (2023) The probabilistic of abandoned project status using ordinal logistic regression analysis. In: AIP Conference Proceedings; 2021 World Sustainable Construction Conference, WSCC 2021, 15 - 16 October 2021 , Virtual, Kuantan, Pahang. pp. 1-9., 2688 (030003). ISSN 0094-243X ISBN 978-073544483-6 https://doi.org/10.1063/5.0113901
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic TA Engineering (General). Civil engineering (General)
TH Building construction
spellingShingle TA Engineering (General). Civil engineering (General)
TH Building construction
Salam, Saidah An’nisaa
Nur Farhayu, Ariffin
Mohamad Idris, Ali
Noram Irwan, Ramli
The probabilistic of abandoned project status using ordinal logistic regression analysis
description The abandoned housing project leads to many negative impacts on the environment, Malaysian economy and society. The homebuyers are the victim in this matter since they are unable to own their dream house and need to pay for their existing rental house. Even worse, unfortunate homebuyers are not allowed to cross over Malaysia and get other loans from the financial institution if they failed to pay for the abandoned housing loan. Therefore, the objective of this paper is to identify the factors that contribute to the abandoned housing projects and their impact on the nation, environment, and society. Through extensive literature review from the previous studies, several factors and impacts have been listed. A quantitative research methodology was conducted in data collection through a well-designed questionnaire which was based on the extensive literature review, semi-structured interviews, and discussions with the expert panels. The questionnaires had been distributed to 100 respondents from the population of housing development stakeholders such as developers, contractors, consultants, and authorities. After that, the data were analysed using the descriptive statistics of Ordinal Logistic Regression (OLR) method whereby the relationship between each factor that contributes to the abandoned housing project and the project status for 10 selected respondents from the interview session was obtained. Further, this study develops the Probabilistic Model of Abandoned Project Status (PMAPS) to show the relationship between the factors of abandoned housing projects and the probability of project status. The findings conclude that the main factors of abandoned housing projects are financial factors, followed by project participant factors, project management factors, market signal, procurement factors, and external factors. The PMAPS can predict the project status with regards to the problem (factors of abandoned housing project) faced in each project. These findings could assist the stakeholders involved in predicting their project status regards to the problem faced. It also can be a guide for the development practitioner to apply the appropriate mitigation plan to avoid project abandonment. .
format Conference or Workshop Item
author Salam, Saidah An’nisaa
Nur Farhayu, Ariffin
Mohamad Idris, Ali
Noram Irwan, Ramli
author_facet Salam, Saidah An’nisaa
Nur Farhayu, Ariffin
Mohamad Idris, Ali
Noram Irwan, Ramli
author_sort Salam, Saidah An’nisaa
title The probabilistic of abandoned project status using ordinal logistic regression analysis
title_short The probabilistic of abandoned project status using ordinal logistic regression analysis
title_full The probabilistic of abandoned project status using ordinal logistic regression analysis
title_fullStr The probabilistic of abandoned project status using ordinal logistic regression analysis
title_full_unstemmed The probabilistic of abandoned project status using ordinal logistic regression analysis
title_sort probabilistic of abandoned project status using ordinal logistic regression analysis
publisher AIP Publishing
publishDate 2023
url http://umpir.ump.edu.my/id/eprint/39145/1/AIP%20PROCEEDING%200015_AN%27NISAA_WSCC2021.pdf
http://umpir.ump.edu.my/id/eprint/39145/7/The%20probabilistic%20of%20abandoned%20project%20status%20using%20ordinal%20logistic%20regression%20analysis.pdf
http://umpir.ump.edu.my/id/eprint/39145/
https://doi.org/10.1063/5.0113901
_version_ 1822923831948345344
score 13.235796

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