ISSN: 2226-3624
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The study is essential in identifying the mechanisms of applying the Islamic economy and their impact on reducing administrative corruption in Libyan Islamic banks. The researcher used the questionnaire as a tool for the study. The study population was limited to the employees of the Libyan republic and oasis banks, which numbered 550 male and female employees. The data were analyzed by SPSS and SMART-PLS. Three hundred questionnaires were distributed to the employees of these banks, 235 questionnaires were retrieved, and 76% and 230 questionnaires met the conditions. Where the study sample was selected by random sample method, and arithmetic averages were used to find out the level of respondents' response to the paragraphs of the study variables. The results of the study showed that there was a strong positive effect with a statistical significance at a significant level (??0.05) between the application of the rules of Islamic economics and the reduction of administrative corruption, in addition to the existence of a positive effect between legal, financial controls and the use of Islamic financing mechanisms and government intervention on the reduction of administrative corruption, with his banishment: Bribery and exploitation of public office. The study highlights future research, which is, conducting more studies on applying the rules of the Islamic economy to other Libyan banks and comparing the results due to its positive impact on the state's national economy—analyzing and evaluating the practice of the rules of the Islamic economy on the Libyan Islamic banks.
Bagozzi, R. P., & Yi, Y. (1989). The degree of intention information as a moderator of the attitude-behavior relationship. Social Psychology Quarterly, 52(4), 279-299
Barclay, D., Higgins, C., & Thompson, R. (1995). The partial least squares (PLS) approach to casual modeling: personal computer adoption ans use as an Illustration.
Barlett, M. S. (1950). Extensions of Quenouille's test for autoregressive scheme. J. Roy. Statist. Soc., B, 12, 108-115.
Bentler, P. (1990). Comparative fit indexes in structural models. Psychological bulletin
Bentler, P., & Bonett, D. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological bulletin, 88(3),588-606.
Bollen, K. (1989). Structural Equations with latent variables. New York: Wiley.
Bontis, N., Booker, L. D., & Serenko, A. (2007). The mediating effect of organizational reputation on customer loyalty and service recommendation in the banking industry. Management decision, 45(9), 1426-1445.
Bowerman, B. L., & O'connell, R. T. (1990). Linear statistical models: An applied approach. Brooks/Cole.
Chin, W. W. (1980). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295-336.
Chin, W. W. (2010). How to write up and report PLS analyses. In Handbook of partial least squares (pp. 655-690). Springer, Berlin, Heidelberg
Chou, C. P., & Bentler, P. M. (1995). Estimates and teste in structrural equestion modeling: Conceps, issues and application. Thousand Oaks, CA: Sage. P. 37-54.
Cohen, J. (1983). The cost of dichotomization. Applied psychological measurement, 7(3), 249-253.
De Vaus, D. (2002). Analyzing social science data: 50 key problems in data analysis. Sage.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation model with unobservable variables and measurement error. Journal of Marketing Research 18 (1), 39-50.
Ghozali, H. I., Fuad, J., & Seti, M. (2005). Structural equation modeling. Program LISRAL 8.54. Semarang, Indonesia, Badan Penerbit University Diponegoro
Hair Jr, J., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014). Partial least squares structural equation modeling (PLS-SEM) An emerging tool in business research. European Business Review, 26(2), 106-121.
Hair, J. F., Anderson, R. E., Black, W. B., & Tatham, R. L. (2010). Multivariate Data Analysis: Prentice Hall.
Hair, J. F., Anderson, R. E., Black, W. B., Babin, B., & Tatham, R. L.(2006). Multivariate Data Analysis. Auflage, Upper saddle river. (Seven, Ed.).
Hair, J. F., Anderson, R. E., Tatham, R. L. & Black, W. C. (1998). Multivariate Data Analysis (5th ed.), New Jersey, Prentice-Hall.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19(2), 139-152.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2012). Partial least squares: the better approach to structural equation modeling?. Long Range Planning, 45(5-6), 312-319.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2017). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long range planning, 46(1-2), 1-12.
Hughes, T. P., Bellwood, D. R., Baird, A. H., Brodie, J., Bruno, J. F., & Pandolfi, J. M. (2011). Shifting base-lines, declining coral cover, and the erosion of reef resilience: comment on Sweatman et al.(2011). Coral Reefs, 30(3), 653-660.
Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31-36.
Kline, R. B. (2005). Principle and practice of structural equation modeling, 2nd edn Guilford Press, New York.
MacCallum, R. C., & Austin, J. T. (2000). Applications of structural equation modeling in psychological research. Annual review of psychology, 51(1), 201-226.
Mallinckrodt, B., Abraham, W. T., Wei, M., & Russell, D. W. (2006). Advances in testing the statistical significance of mediation effects. Journal of Counseling Psychology, 53(3), 372.
Menard, D. P., Rossum, D. V., Kar, S., & Quirion, R. (1995). Alteration of calcitonin gene related peptide and its receptor binding sites during the development of tolerance to ? and ? opioids. Canadian journal of physiology and pharmacology, 73(7), 1089-1095.
Menard, S. (2000). Coefficients of determination for multiple logistic regression analysis. The American Statistician, 54(1), 17-24.
Myers, R. H., (1990). Classical and modern regression with applications (Vol. 2). Belmont, CA: Duxbury press.
O'brien, R. M. (2007). A caution regarding rules of thumb for variance inflation factors. Quality & quantity, 41(5), 673-690.
Pallant, J. (2010). SPSS Survival Manual, 4th edn, Maidenhead.
Peterson, R. A., & Kim, Y. (2013). On the relationship between coefficient alpha and composite reliability. Journal of Applied Psychology, 98(1), 194.
Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior research methods, 40(3), 879-891.
Ramayah, T., Kamel, R., & Oh M. S. (2011). Modeling users' acceptance of Internet banking in Malaysia. In E-adoption and Socio-Economic Impact: Emerging Infrastructure Effects by Sushil K. Sharma, IGI Global publisher, Chapter 1pp.1-23.
Sarstedt, M., Ringle, C. M., Henseler, J., & Hair, J. F. (2014). On the emancipation of PLS-SEM: A commentary on Rigdon (2012). Long range planning, 47(3), 154-160.
Sekaran, U. (2003). Research methods for business: A skill-building approach (4th ed.). Joh Wilwy & Sons.
Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate Statistics (5th ed). California State University. Northridge. Boston: Allyn and Bacon.
In-Text Citation: (Aboud et al., 2023)
To Cite this Article: Aboud, Y. A. A., Hussin, M. F. A. @, & Hamdan, M. N. (2023). Applying of Islamic Economic Principals and Its Impact on Reducing Administrative Corruption in Libyan Islamic Banks. International Journal of Academic Research in Economics and Management and Sciences, 12(1), 149–165.
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