Factors Determining Compliance Behavior of Business Zakat among SMEs: A Logistic Regression Analysis Approach

Abstract

The dearth of study on the factors determining compliance behavior of business zakat among SMEs are hardly found in literature and empirical evidence as well. Due to that, this study aims to identify the relationship between factors determining compliance behavior of business zakat among SMEs. 276 questionnaires managed to be collected from SMEs in Selangor. Logistic regression analysis was presented to predict compliance behavior of business zakat among SMEs from selected factors determining. Six factors were identified and included in the model; religious practices, level of knowledge, length of business operation, government incentives, organization factors and law enforcement. The findings of logistic regression analysis revealed that full model which considered all the six factors are significant and perform well in explaining the factors determining compliance behavior of business zakat among SMEs. Four factors (religious practices, level of knowledge, organizational factors and government incentives) significantly predict compliance behavior of business zakat among SMEs. Based on the analysis, this study will hopefully shed some light to help zakat organization in implementing strategies to attract more Muslim entrepreneurs to comply pay business zakat, especially among SMEs.


Research paper


Keywords: Zakat, Business Zakat, Compliance Behavior, Logistic Regression Analysis


Reference to this paper should be made as follows: Khamis, M. R., & Kamarudin, M. F. (2022). Factors Determining Compliance Behavior of Business Zakat among SMEs: A Logistic Regression Analysis Approach. Journal of Entrepreneurship, Business and Economics, 10(2S2), 71–108.

Published
Oct 28, 2022
How to Cite
KHAMIS, Mohd Rahim; KAMARUDIN, Mohd Faizal. Factors Determining Compliance Behavior of Business Zakat among SMEs: A Logistic Regression Analysis Approach. Journal of Entrepreneurship, Business and Economics, [S.l.], v. 10, n. 2S2, p. 71-108, oct. 2022. ISSN 2345-4695. Available at: <https://scientificia.com/index.php/JEBE/article/view/190>. Date accessed: 05 dec. 2022.