Sains Malaysiana 51(12)(2022): 4161-4173

http://doi.org/10.17576/jsm-2022-5112-23

 

Factors Affecting Housing Price in Malaysia Using Structural Equation Modeling Approach

(Faktor Mempengaruhi Harga Rumah di Malaysia menggunakan Pendekatan Model Berstruktur Persamaan)

 

NORANI AMIT1,3,*, HASIMAH SAPIRI1 & ZAHAYU MD YUSOF1,2

 

1School of Quantitative Sciences, Universiti Utara Malaysia, 06010 Sintok, Kedah Darul Aman, Malaysia

2Institute of Strategic Industrial Decision Modelling, School of Quantitative Sciences, Universiti Utara Malaysia, 06010 Sintok, Kedah Darul Aman, Malaysia

3Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Cawangan Negeri Sembilan, 73000 Kampus Seremban, Negeri Sembilan, Malaysia

 

Diserahkan: 5 Mei 2022/Diterima: 6 September 2022


Abstract

House buyers are primarily concerned with house prices, on top of other aspects such as housing preferences, and housing financial. In Malaysia, the problem regarding housing issue is one that is regularly spoken due to sharp rise in housing prices which made that most houses are no longer affordable for most Malaysians. Thus, this study aims to identify the key factors influencing the price of houses in Malaysia. Data was collected by distributing a survey questionnaire to 245 respondents throughout the country. The data was then analyzed using the structural equation modelling (SEM) analysis via the IBM AMOS statistical software. The study instrument was evaluated using the exploratory factor analysis and confirmatory factor analysis techniques. The theoretical model was developed using the SEM technique. The findings derived are hoped to benefit policymakers, developers, urban planners, and contractors in developing strategies for materializing affordable house prices for homebuyers in Malaysia.

 

Keywords: Factor analysis; homebuyer; housing affordability; housing prices; structural equation modeling

 

Abstrak

Pembeli rumah amat mementingkan harga rumah selain aspek lain seperti pemilihan perumahan dan kewangan perumahan. Di Malaysia, masalah berkenaan perumahan seringkali diperkatakan berikutan kenaikan mendadak harga rumah yang menyebabkan kebanyakan rumah tidak lagi mampu dimiliki oleh kebanyakan rakyat Malaysia. Justeru, kajian ini bertujuan untuk mengenal pasti faktor utama yang mempengaruhi harga rumah di Malaysia. Data dikumpul dengan mengedarkan borang soal selidik kepada 245 responden di seluruh negara. Data tersebut kemudiannya dianalisis menggunakan analisis pemodelan berstruktur persamaan (SEM) melalui perisian statistik IBM AMOS. Instrumen kajian dinilai menggunakan teknik analisis faktor jelajah dan analisis faktor pengesahan. Model teori telah dibangunkan menggunakan teknik SEM. Penemuan yang diperoleh diharap dapat memberi manfaat kepada penggubal dasar, pemaju, perancang bandar dan kontraktor dalam membangunkan strategi untuk merealisasikan harga rumah mampu milik untuk pembeli rumah di Malaysia.

 

Kata kunci: Analisis faktor; harga rumah; pembeli rumah; pemodelan berstruktur persamaan; perumahan mampu milik

 

RUJUKAN

Abu, A., Hamdan, R. & Sani, N.S. 2020. Ensemble learning for multidimensional poverty classification. Sains Malaysiana 49(2): 447-459.

Anderson, T.W. & Rubin, H. 1956. Statistical inference in factor analysis. Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability. pp. 111-150.

Arbuckle, J.L. 2013. Amos 22 User Guide. Amos Development Corporation.

Awang, Z. 2012. A Handbook on SEM Structural Equation Modelling: SEM using AMOS Graphic. 5th ed. Kota Bharu: Universiti Teknologi MARA Kelantan.

Awang, Z., Lim, S.H. & Zainudin, N.F.S. 2018. Pendekatan Mudah SEM-structural Equation Modelling. Bandar Baru Bangi: MPWS Rich Resources.

Babakus, E. & Mangold, W.G. 1992. Adapting the SERVQUAL scale to hospital services: An empirical investigation. Health Services Research 26(6): 767.

Bakar, A.A., Osman, M.M., Bachok, S. & Ibrahim, M. 2016. Investigating rationales of Malaysia quality of life and wellbeing components and indicators. Procedia-Social and Behavioral Sciences 222: 132-142.

Bakhtyar, B., Zaharim, A., Sopian, K. & Monghimi, S. 2013. Housing for poor people: A review on low-cost housing process in Malaysia. WSEAS. Trans. Environ. Dev. 9: 126-136.

Bank Negara Malaysia. 2017. Imbalances in the property market. Box Article in 3rd Quarterly Bulletin.

Bian, H. 2011. Structural Equation Modelling with AMOS II.

Bryman, A. & Bell, E. 2007.  Business Research Method. Oxford: Oxford University Press.

Bajpai, N. 2011. Business Research Method. Delhi: Pearson Education India.

Bentler, P.M. 1990. Comparatives fit indexes in structural models. Psychological Bulletin 107: 238-246.

Byrne, B.M. 2001. Structural Equations Modeling with AMOS: Basic Concepts, Applications, and Programming. New Jersey: Lawrence Erlbaum Associates.

Chau, P.Y.K. & Hu, P.J.H. 2001. Information technology acceptance by individual professionals: A model comparison approach. Decision Sciences 32(4): 699-719.

Chen, P.F., Chien, M.S. & Lee, C.C. 2011. Dynamic modeling of regional house price diffusion in Taiwan. Journal of Housing Economics 20(4): 315-332.

Daud, N.M., Nor, N.M., Ali, U.N., Yusof, M.A. & Munikanan, V. 2017. Affordable housing system: A review on issue of housing affordability. The Social Sciences 12(7): 1281-1287.

Deng, C., Ma, Y. & Chiang, Y.M. 2009. The dynamic behavior of Chinese housing prices. International Real Estate Review 12(2): 121-134.

Ehido, A., Awang, Z., Halim, B.A. & Ibeabuchi, C. 2020. Developing items for measuring quality of worklife among Malaysian academics: An exploratory factor analysis procedure. Humanities and Social Sciences Reviews 8(3): 1295-1309.

Etikan, I., Musa, S.A. & Alkassim, R.S. 2015. Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics 5(1): 1-4.

Groenland, E.A. & Stalpers, J. 2012. Structural equation modeling: A verbal approach. Nyenrode research paper series, Breukelen, The Netherlands: Nyenrode Business Universiteit 12(2).

Hair, J.F., Black, W.C., Babin, B.J. & Anderson, R.E. 2010. Multivariate Data Analysis: Overview of Multivariate Methods. Seventh Edition. Pearson Prentice Hall: Upper Saddle River, New Jersey: Pearson Education International.

Hair, J.F., Anderson, R.E., Tatham, R.L. & Black, W.C. 1995. Multivariate Data Analysis with Readings. 4th ed. New Jersey: Englewood Cliffs.

Hassan, G.F. 2011. The enabling approach for housing supply: Drawbacks prerequisites Egyptian experiences. Alexandria Eng. J. 50: 421-429.

Ismail, S. 2019. Rethinking Housing: Between State, Market and Society. Kuala Lumpur: Khazanah Research Institute.

Kim, J.O. & Mueller, C.W. 1978. Factor Analysis: Statistical Methods and Practical Issues. California: SAGE Publications.

Latif, N.S.A., Rizwan, K.M., Rozzani, N. & Saleh, S.K. 2020. Factors affecting housing prices in Malaysia: A literature review. International Journal of Asian Social Science 10(1): 63-67.

Loehlin, J.C. 2004. Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis. 4th ed. New Jersey: Lawrence Erlbaum Associates.

Marton-Williams, J. 1986. Questionnaire design. In Consumer Market Research Handbook, edited by Worcester, R. & Downham, J. New York: McGraw-Hill.

Meyers, L.S., Gamst, G.C. & Guarino, A.J. 2005. Applied Multivariate Research: Design and Interpretation. Thousand Oaks: Sage Publications.

Monkkonen, P., Wong, K. & Begley, J. 2012. Economic restructuring, urban growth, and short-term trading: The spatial dynamics of the Hong Kong housing market, 1992-2008. Regional Science and Urban Economics 42: 396-406.

Nayeri, M.D. & Rostami, M. 2018. Tehran housing price analysis: System dynamics approach. European Institute for Research and Development. 3rd International Academic Conference on Economics, Business and Social Science "Contemporary Academic Issues in Modern Society”.

Nunnally, J.C. 1978. An overview of psychological measurement. In Clinical Diagnosis of Mental Disorders: A Handbook, edited by Wohnan, B.B. Boston: Springer. pp. 97-146.

Osmadi, A., Kamal, E.M., Hassan, H. & Fattah, H.A. 2015. Exploring the elements of housing price in Malaysia. Asian Social Science 11(24): 26.

Ramayah, T., Lee, J.W.C. & Mohamad, O. 2010. Green product purchase intention: Some insights from a developing country. Resource Conversation and Recycling 54(12): 1419-1427. doi: http://dx.doi.org/10.1016/j.resconrec.2010.06.007

Razak, F.A. & Shahabuddin, F.A. 2018. Malaysian household income distribution: A fractal point of view. Sains Malaysiana 47(9): 2187-2194.

Sarkam, N.A., Razi, N.F.M., Mohammad, N.H., Jamil, N.I. & Kurniawati, L. 2022. Attitudes, security, and perceived ease of use influence the consumers' decision to use an e-payment system. System 12(3): 357-368.

Schumacker, R.E. & Lomax, R.G. 2004. A Beginner's Guide to Structural Equation Modeling, 2nd ed., edited by Riegert, D. New Jersey: Lawrence Erlbaum Associates.

Sean, S.L. & Hong, T.T. 2014. Factors affecting the purchase decision of investors in the residential property market in Malaysia. Journal of Surveying, Construction and Property 5(2): 1-13.

Tanguma, J. 2001. Effects of sample size on the distribution of selected fit indices: A graphical approach. Educational and Psychological Measurement 61(5): 759-776.

Yahaya, T., Idris, K., Suandi, T. & Ismail, I. 2018. Adapting instruments and modifying statements: The confirmation method for the inventory and model for information sharing behavior using social media. Management Science Letters 8(5): 271-282.

Zainol, Z. 2018. Structural Equation Modeling Using AMOS: A Step by Step Approach.ISBN: 978-967-16417-0-5

Zairul, M. 2013. Housing dilemma among young starters in Malaysia. Elixir Sustain 58: 14923-14926.

Zyed, Z.A.S. 2014. Assessment of housing affordability problems among younger working households in greater Kuala Lumpur. PhD dissertation. University of Malaya (Unpublished).

 

*Pengarang untuk surat-menyurat; email: norani@uitm.edu.my

 

 

   

sebelumnya