# STRUCTURAL EQUATION MODELING MULTIGROUP INDIRECT EFFECTS ON BANK MORTGAGE PAYMENT TIMELINESS

• Ulfah Maisaroh Department of Statistics, Faculty of Mathematics and Natural Science, University of Brawijaya, Indonesia
• Adji Achmad Rinaldo Fernandes Department of Statistics, Faculty of Mathematics and Natural Science, University of Brawijaya, Indonesia
• Atiek Iriany Department of Statistics, Faculty of Mathematics and Natural Science, University of Brawijaya, Indonesia
Keywords: Indirect Effect, Moderation, Mortgage, Structural Equation Modeling

### Abstract

Structural Equation Modeling (SEM) is a multivariate statistical method that is used to thoroughly explain the relationship between latent variables simultaneously. Until now, SEM continues to grow in research. This research was conducted to examine the indirect effect on the timeliness of paying bank mortgages with a multi-group moderation approach. Analysis to identify factors that influence the timeliness of paying bank mortgages is an important step for banks before extending credit to prospective customers. The data used in this research is secondary data from research grants from National Competitive Basic Research. The data scale used is the Likert scale for exogenous, mediating endogenous, and pure endogenous variables. While the moderating variable uses a dummy variable. The results of the study show that the indirect effect of Capacity and Capital on Pay on Time for Bank Mortgage customers has a significant effect, both on non-current collectibility status and current collectibility status. This is evidenced by the Sobel test value greater than (1.96) on the indirect effect test, and the p-value of the Wald test is smaller than (0.05) on the moderation indirect effect test. Mediator variable is able to increase the effect of exogenous variables on endogenous variable Customers with current collectibility status have a stronger influence on timely payments than customers with non-current collectibility status.

### References

S. Wright, “The Method of Path Coefficient,” The Annals of Mathematical , vol. 5, no. 3, pp. 161-215, 1934.

Solimun, A. A. R. Fernandes and Nurjannah, Metode Statistika Multivariat Pemodelan Persamaan Struktural (SEM), Malang: UB Press, 2017.

Solimun, Nurjannah, L. Amaliana and A. A. R. Fernandes, Metode Statistika Multivariat Generalized Structured Component Analysis (GSCA) Pemodelan Persamaan Struktural (SEM), Malang: UB Press, 2019.

A. H. Ngah, S. Gabarre, b. Eneizan and N. Asri, “Mediated and Moderated Model of The Willingness to Pay for Halal Transportation,” Journal of Islamic Marketing, pp. 1-21, 2020.

D. Komunikasi, “Bank Indonesia,” SHPR TRIWULAN I 2023: PERKEMBANGAN HARGA PROPERTI RESIDENSIAL MENINGKAT TERBATAS, 17 Mei 2023. [Online]. Available: https://www.bi.go.id/id/publikasi/ruang-media/news-release/Pages/sp_2513023.aspx.

R. F. Levant, M. C. Parent, E. R. McCurdy and T. C. Bradstreet, “Moderated Mediation of The Relationship Between Masculinity Ideology Outcome Expectations, and Energy Drink Use,” Health Psychology, vol. 34, no. 11, pp. 1100-1106, 2015.

T. A. Tristanto, Nugraha, I. Waspada, Mayasari and P. Kurniati, “Sustainability Performance Impact of Corporate Performance in Indonesia Banking,” Journal of Eastern European and Central Asian Research, vol. 10, no. 4, pp. 668-678, 2023.

J.-H. Cheah, S. Amaro and J. L. Roldán, “Multigroup Analysis of More Than Two Groups in PLS-SEM: A Review, Illustration, and Recommendations,” Journal of Business Research, vol. 156, 2023.

J. R. Edwards and L. S. Lambert, “Methods for Integrating Moderation and Mediation: A General Analytical Framework Using Moderated Path Analysis,” Psychological Method, vol. 12, no. 1, pp. 1-22, 2007.

M. Aboelmaged, “Direct and Indirect Effects of Eco-Innovation, Environmental Orientation and Supplier Collaboration on Hotel Performance: An Empirical Study,” Journal of Cleaner Production, vol. 184, pp. 537-549, 2018.

J. F. Hair, W. C. Black, B. J. Babin and R. E. Anderson, Multivariate Data Analysis A Global Perspective, 7th ed., Boston: Pearson, 2010.

Z. Hikmah, H. Wijayanti and M. N. Aidi, “Selection of The Best SEM Model to Identify Factors Affecting Marketing Performance in The ICT Industry,” BAREKENG: Journal of Mathematics and Its Applications, vol. 17, no. 2, pp. 1149 - 1162, 2023.

B. M. Byrne, Structural Equation Modeling with AMOS, London: Routledge, 2010.

R. Johnson and D. Wichern, Applied Multivariate Statistical Analysis, 6th ed., London: Pearson, 2014.

S. Haryono and P. Wardoyo, Structural Equation Modeling untuk Penelitian Manajemen Menggunakan AMOS 18.00, Jawa Barat: Badan Penerbit PT. Intermedia Personalia Utama, 2012.

E. Ryu, “Multiple-group Analysis Approach to Testing Group Difference in Indirect Effects,” Behavior Research Methods, vol. 47, pp. 484-493, 2015.

W. Chan, “Comparing Indirect Effects in SEM: A Sequential Model Fitting Method Using Covariance-Equivalent Specifications,” Structural Equation Modeling: A Multidisciplinary Journal, vol. 14, no. 2, pp. 326-346, 2007.

A. A. Esubalew and A. Raghurama, “Commercial Bank Financing to Micro, Small, and Medium Enterprises (MSMEs): The Mediating and Multigroup Effect Analysis,” Journal of Small Business & Entrepreneurship, pp. 1-29, 2020.

K. A. Bollen, Structural Equations with Latent Variables, New York: Wiley, 1989.

Published
2023-12-19
How to Cite
[1]
U. Maisaroh, A. Fernandes, and A. Iriany, “STRUCTURAL EQUATION MODELING MULTIGROUP INDIRECT EFFECTS ON BANK MORTGAGE PAYMENT TIMELINESS”, BAREKENG: J. Math. & App., vol. 17, no. 4, pp. 2359-2366, Dec. 2023.
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Articles