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...
| Main Authors: | , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
AIP Publishing
2023
|
| Subjects: | |
| 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 |
| _version_ | 1825815244040044544 |
|---|---|
| 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 |
| collection | UMP |
| 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. . |
| first_indexed | 2024-03-06T13:10:37Z |
| format | Conference or Workshop Item |
| id | UMPir39145 |
| institution | Universiti Malaysia Pahang |
| language | English English |
| last_indexed | 2024-03-06T13:10:37Z |
| publishDate | 2023 |
| publisher | AIP Publishing |
| record_format | dspace |
| spelling | UMPir391452023-11-02T06:22:14Z 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 (Published) https://doi.org/10.1063/5.0113901 |
| 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 |
| title | 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_short | The probabilistic of abandoned project status using ordinal logistic regression analysis |
| title_sort | probabilistic of abandoned project status using ordinal logistic regression analysis |
| topic | TA Engineering (General). Civil engineering (General) TH Building construction |
| 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 |
| work_keys_str_mv | AT salamsaidahannisaa theprobabilisticofabandonedprojectstatususingordinallogisticregressionanalysis AT nurfarhayuariffin theprobabilisticofabandonedprojectstatususingordinallogisticregressionanalysis AT mohamadidrisali theprobabilisticofabandonedprojectstatususingordinallogisticregressionanalysis AT noramirwanramli theprobabilisticofabandonedprojectstatususingordinallogisticregressionanalysis AT salamsaidahannisaa probabilisticofabandonedprojectstatususingordinallogisticregressionanalysis AT nurfarhayuariffin probabilisticofabandonedprojectstatususingordinallogisticregressionanalysis AT mohamadidrisali probabilisticofabandonedprojectstatususingordinallogisticregressionanalysis AT noramirwanramli probabilisticofabandonedprojectstatususingordinallogisticregressionanalysis |