Main Article Content

Abstract

This study discusses the influence of demographic and social class factors on customers' decisions to choose Islamic banks in Palopo City. On the customer's decision to choose an Islamic bank in the city of Palopo and prove the influence of these factors simultaneously. To provide answers to the problems stated above, the authors use a quantitative research approach with the variables used in this study are the independent variables, namely education, income, employment, dependents, and age as well as the dependent variable in the form of a customer's decision to choose an Islamic bank. This study took 100 respondents using the Non-Probability Sampling method as the sample. Data collection in this study used a questionnaire with regression analysis techniques through the F-test and t-test using the Software Statistical Product and Service Solutions (SPSS) 19.0. The results of the study show that education, income, employment, and age have a significant effect on the customer's decision to choose an Islamic bank in Palopo City. This is evidenced by obtaining a significance value of 0.000 or less than 5% (0.05). The results of the partial statistical test also show that the variables of education, income and employment have a significant positive effect, while the age variable has a significant negative effect on the customer's decision to choose an Islamic bank in Palopo City. Based on the beta regression coefficient, the highest coefficient value is the income variable of 7,060 with a significance level of 0.000. These findings indicate that income is the variable that has the most influence on the customer's decision to choose Islamic Banking among the other four variables. Based on the results of the simultaneous test it was concluded that the independent variables simultaneously represented by the variables of education, income, employment, dependents, and age have a significant effect on the dependent variable on customer decisions.


 

Keywords

Demographics Social Class Customer Decisions

Article Details

Author Biography

R Rahmi, Politeknik LP3i, Makassar

 

 

 

How to Cite
Rahmi, R. (2023). The Effect of Demographic Factors and Social Class on Customers’ Decisions to Choose Islamic Banks . Golden Ratio of Data in Summary, 3(1), 29–44. https://doi.org/10.52970/grdis.v3i1.308

References

  1. Alandejani, M. (2022). Does issuing islamic bonds through banks increase banking efficiency? Heliyon, 8(8), e10041. https://doi.org/https://doi.org/10.1016/j.heliyon.2022.e10041
  2. Albaity, M., Noman, A. H. M., Saadaoui Mallek, R., & Al-Shboul, M. (2022). Cyclicality of bank credit growth: Conventional vs Islamic banks in the GCC. Economic Systems, 46(1), 100884. https://doi.org/https://doi.org/10.1016/j.ecosys.2021.100884
  3. Alghababsheh, M., Abu khader, D. E., Butt, A. S., & Moktadir, M. A. (2022). Business strategy, green supply chain management practices, and financial performance: A nuanced empirical examination. Journal of Cleaner Production, 380, 134865. https://doi.org/https://doi.org/10.1016/j.jclepro.2022.134865
  4. Aliani, K., Al-kayed, L., & Boujlil, R. (2022). COVID-19 effect on Islamic vs. conventional banks’ stock prices: Case of GCC countries. The Journal of Economic Asymmetries, 26, e00263. https://doi.org/https://doi.org/10.1016/j.jeca.2022.e00263
  5. Ashraf, B. N., Tabash, M. I., & Hassan, M. K. (2022). Are Islamic banks more resilient to the crises vis-à-vis conventional banks? Evidence from the COVID-19 shock using stock market data. Pacific-Basin Finance Journal, 73, 101774. https://doi.org/https://doi.org/10.1016/j.pacfin.2022.101774
  6. Baizan, P. (2021). Welfare regime patterns in the social class-fertility relationship: Second births in Austria, France, Norway, and the United Kingdom. Research in Social Stratification and Mobility, 73, 100611. https://doi.org/https://doi.org/10.1016/j.rssm.2021.100611
  7. Beagan, B. L., MacLeod, A., Owen, M., Pride, T. M., & Sibbald, K. R. (2022). Lower-class origin professionals in Canadian health and social service professions: “A different level of understanding”. Social Science & Medicine, 309, 115233. https://doi.org/https://doi.org/10.1016/j.socscimed.2022.115233
  8. Bilgin, M. H., Danisman, G. O., Demir, E., & Tarazi, A. (2021). Economic uncertainty and bank stability: Conventional vs. Islamic banking. Journal of Financial Stability, 56, 100911. https://doi.org/https://doi.org/10.1016/j.jfs.2021.100911
  9. Dou, R., Li, W., Nan, G., Wang, X., & Zhou, Y. (2021). How can manufacturers make decisions on product appearance design? A research on optimal design based on customers’ emotional satisfaction. Journal of Management Science and Engineering, 6(2), 177–196. https://doi.org/https://doi.org/10.1016/j.jmse.2021.02.010
  10. El-Jardali, F., Alameddine, M., Dumit, N., Dimassi, H., Jamal, D., & Maalouf, S. (2011). Nurses’ work environment and intent to leave in Lebanese hospitals: Implications for policy and practice. International Journal of Nursing Studies, 48(2), 204–214. https://doi.org/https://doi.org/10.1016/j.ijnurstu.2010.07.009
  11. Ledhem, M. A. (2022). The financial stability of Islamic banks and sukuk market development: Is the effect complementary or competitive? Borsa Istanbul Review. https://doi.org/https://doi.org/10.1016/j.bir.2022.09.009
  12. Li, T., & Xie, Y. (2022). The evolution of demographic methods. Social Science Research, 107, 102768. https://doi.org/https://doi.org/10.1016/j.ssresearch.2022.102768
  13. Nilashi, M., Ahmadi, H., Arji, G., Alsalem, K. O., Samad, S., Ghabban, F., Alzahrani, A. O., Ahani, A., & Alarood, A. A. (2021). Big social data and customer decision making in vegetarian restaurants: A combined machine learning method. Journal of Retailing and Consumer Services, 62, 102630. https://doi.org/https://doi.org/10.1016/j.jretconser.2021.102630
  14. Prusiński, T. (2022). Factors promoting alliance quality: Differentiation of therapeutic alliance according to the formal aspects of the psychotherapeutic process and demographic variables. The European Journal of Psychiatry. https://doi.org/https://doi.org/10.1016/j.ejpsy.2022.11.002
  15. Raouf, H., & Ahmed, H. (2022). Risk governance and financial stability: A comparative study of conventional and Islamic banks in the GCC. Global Finance Journal, 52, 100599. https://doi.org/https://doi.org/10.1016/j.gfj.2020.100599
  16. Tiganis, A., Grigoroudis, E., & Chrysochou, P. (2023). Customer satisfaction in short food supply chains: A multiple criteria decision analysis approach. Food Quality and Preference, 104, 104750. https://doi.org/https://doi.org/10.1016/j.foodqual.2022.104750
  17. Wang, D., Luo, X. (Robert), Hua, Y., & Benitez, J. (2023). Customers’ help-seeking propensity and decisions in brands’ self-built live streaming E-Commerce: A mixed-methods and fsQCA investigation from a dual-process perspective. Journal of Business Research, 156, 113540. https://doi.org/https://doi.org/10.1016/j.jbusres.2022.113540

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