Improving residential housing project purchase by using integrated multi-attribute decision making and sentiment analysis technique

The residential house purchase decision making is highly complex due to reasons such as conflicting criteria which is hard to model, infrequent type of decisions, uncertain and irreversible decision outcomes, high investment, and long-term financial burden. Unlike many other types of purchasing, hou...

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Main Author:	Ahmad Taufik, Nursal
Format:	Thesis
Language:	eng eng eng
Published:	2021
Subjects:	HD28-70 Management Industrial Management HD61 Risk Management HF5001-6182 Business
Online Access:	https://etd.uum.edu.my/9820/1/permission%20to%20deposit-901794.pdf https://etd.uum.edu.my/9820/2/s901794_01.pdf https://etd.uum.edu.my/9820/3/s901794_02.pdf
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id	my-uum-etd.9820
record_format	uketd_dc
spelling	my-uum-etd.98202022-09-07T07:30:57Z Improving residential housing project purchase by using integrated multi-attribute decision making and sentiment analysis technique 2021 Ahmad Taufik, Nursal Omar, Mohd Faizal Mohd Nawi, Mohd Nasrun Awang Had Salleh Graduate School of Arts & Sciences Awang Had Salleh Graduate School of Art & Sciences HD28-70 Management. Industrial Management HD61 Risk Management HF5001-6182 Business The residential house purchase decision making is highly complex due to reasons such as conflicting criteria which is hard to model, infrequent type of decisions, uncertain and irreversible decision outcomes, high investment, and long-term financial burden. Unlike many other types of purchasing, housing purchase decision-making is riskier and sometimes even ‘traumatic’. It is often associated with feeling of regret and the possibility of loss among homebuyers. Typically, the Multi Attribute Decision Making (MADM) models are used to systematically assist and structure residential housing project selection decision making. However, the MADM models impose deficiencies in the evaluation process due to insufficient knowledge of homebuyers, ignorance of public opinions and limited sources of information. Furthermore, the application of MADM models requires homebuyer to rely on their evaluation experience which potentially led to an imprecise decision. Hence, this study developed an improved model by integrating MADM and three approaches of Sentiment Analysis to capture and rank criteria from public opinions through online reviews. Properties online forums and google reviews were selected to extract public opinions through online reviews. Three high-rise residential projects located in Malaysia were used as case projects for demonstrating the model development and validation of the proposed framework. Three Sentiment Analysis approach were considered; Lexicon, Machine Learning and hybrid. Based on the ranking established by the models, it shows that location, facility, and house attributes are the most important criteria in residential housing purchase decision making. In addition, classification using a hybrid MADM Sentiment Analysis approach outperforms the Lexicon approach with better accuracy. The developed model can assist homebuyer in making decision for the current practice. Moreover, it can be generalised to other related multi-criteria applications with the use of online public opinions as reference. 2021 Thesis https://etd.uum.edu.my/9820/ https://etd.uum.edu.my/9820/1/permission%20to%20deposit-901794.pdf text eng staffonly https://etd.uum.edu.my/9820/2/s901794_01.pdf text eng 2024-12-09 staffonly https://etd.uum.edu.my/9820/3/s901794_02.pdf text eng public other doctoral Universiti Utara Malaysia
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng eng
advisor	Omar, Mohd Faizal Mohd Nawi, Mohd Nasrun
topic	HD28-70 Management Industrial Management HD61 Risk Management HF5001-6182 Business
spellingShingle	HD28-70 Management Industrial Management HD61 Risk Management HF5001-6182 Business Ahmad Taufik, Nursal Improving residential housing project purchase by using integrated multi-attribute decision making and sentiment analysis technique
description	The residential house purchase decision making is highly complex due to reasons such as conflicting criteria which is hard to model, infrequent type of decisions, uncertain and irreversible decision outcomes, high investment, and long-term financial burden. Unlike many other types of purchasing, housing purchase decision-making is riskier and sometimes even ‘traumatic’. It is often associated with feeling of regret and the possibility of loss among homebuyers. Typically, the Multi Attribute Decision Making (MADM) models are used to systematically assist and structure residential housing project selection decision making. However, the MADM models impose deficiencies in the evaluation process due to insufficient knowledge of homebuyers, ignorance of public opinions and limited sources of information. Furthermore, the application of MADM models requires homebuyer to rely on their evaluation experience which potentially led to an imprecise decision. Hence, this study developed an improved model by integrating MADM and three approaches of Sentiment Analysis to capture and rank criteria from public opinions through online reviews. Properties online forums and google reviews were selected to extract public opinions through online reviews. Three high-rise residential projects located in Malaysia were used as case projects for demonstrating the model development and validation of the proposed framework. Three Sentiment Analysis approach were considered; Lexicon, Machine Learning and hybrid. Based on the ranking established by the models, it shows that location, facility, and house attributes are the most important criteria in residential housing purchase decision making. In addition, classification using a hybrid MADM Sentiment Analysis approach outperforms the Lexicon approach with better accuracy. The developed model can assist homebuyer in making decision for the current practice. Moreover, it can be generalised to other related multi-criteria applications with the use of online public opinions as reference.
format	Thesis
qualification_name	other
qualification_level	Doctorate
author	Ahmad Taufik, Nursal
author_facet	Ahmad Taufik, Nursal
author_sort	Ahmad Taufik, Nursal
title	Improving residential housing project purchase by using integrated multi-attribute decision making and sentiment analysis technique
title_short	Improving residential housing project purchase by using integrated multi-attribute decision making and sentiment analysis technique
title_full	Improving residential housing project purchase by using integrated multi-attribute decision making and sentiment analysis technique
title_fullStr	Improving residential housing project purchase by using integrated multi-attribute decision making and sentiment analysis technique
title_full_unstemmed	Improving residential housing project purchase by using integrated multi-attribute decision making and sentiment analysis technique
title_sort	improving residential housing project purchase by using integrated multi-attribute decision making and sentiment analysis technique
granting_institution	Universiti Utara Malaysia
granting_department	Awang Had Salleh Graduate School of Arts & Sciences
publishDate	2021
url	https://etd.uum.edu.my/9820/1/permission%20to%20deposit-901794.pdf https://etd.uum.edu.my/9820/2/s901794_01.pdf https://etd.uum.edu.my/9820/3/s901794_02.pdf
_version_	1747828678097633280

Improving residential housing project purchase by using integrated multi-attribute decision making and sentiment analysis technique

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