Factors Determinating Employee Confidence in the Management System Anti-Bribery at PLN UPT Kendari
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Abstract
This study aims to evaluate the effectiveness of the ISO 37001:2016 Anti-Bribery Management System (SMAP) at PLN UPT Kendari, especially in increasing employee confidence in the anti-bribery system. The research method used is a quantitative approach with multiple linear regression analysis to test the influence of policy understanding variables, clarity of reporting procedures, and the effectiveness of socialisation on employee confidence. The results showed that understanding policies and clarity of reporting procedures significantly and positively influenced confidence in SMAP. In contrast, the effectiveness of socialisation did not have a significant influence. An R-squared value of 68.2% indicates that this model can explain most of the variability of confidence in anti-bribery systems. The classical assumption test also supports the validity of this regression model. Based on the study results, it is recommended that PLN UPT Kendari increase the intensity of socialisation through a more interactive approach, strengthen continuous training, and simplify bribery reporting procedures. These steps are expected to improve the implementation of SMAP at PLN UPT Kendari and create a work environment with high integrity.
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How to Cite
Nelvia, H., Hasbullah, H., Amiruddin, A., & Syamsuddin, S. (2024). Factors Determinating Employee Confidence in the Management System Anti-Bribery at PLN UPT Kendari. ProBisnis : Jurnal Manajemen, 15(5), 956–962. Retrieved from https://ejournal.joninstitute.org/index.php/ProBisnis/article/view/769
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Nopriyanto Bahasoan, A., Yashari Soumena, F., & Arsyad, R. (2023). Migration Letters Identifying Increasing Poverty in Indonesia: Does the Human Development Index and Unemployment Affect Poverty in Indonesia? Migration Letters, 20(8), 585–605. https://doi.org/https://doi.org/10.59670/ml.v20i8.5430
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Sun, Y., & Wang, X. (2022). An asymptotically F-distributed Chow test in the presence of heteroscedasticity and autocorrelation. Econometric Reviews, 41(2), 177–206. https://doi.org/10.1080/07474938.2021.1874703
Ufere, N., Gaskin, J., Perelli, S., Somers, A., & Boland, R. (2020). Why is bribery pervasive among firms in sub-Saharan African countries? Multi-industry empirical evidence of organisational isomorphism. Journal of Business Research, 108, 92–104. https://doi.org/10.1016/j.jbusres.2019.09.060
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Vu, M. C. (2021). Tensions and Struggles in Tackling Bribery at the Firm Level: Perspectives from Buddhist-Enacted Organizational Leaders. Journal of Business Ethics, 168(3), 517–537. https://doi.org/10.1007/s10551-019-04235-3
Wang, Z., Liu, J., & Guan, X. (2022). Investigating the causal complexity of corruption in project-based organisations: a scenario analysis of bidding activity in the Chinese construction sector. Engineering, Construction and Architectural Management, 29(10), 3893–3916. https://doi.org/10.1108/ECAM-10-2020-0841
Xu, F., & He, Z. (2020). Testing slope homogeneity in panel data models with a multifactor error structure. Statistical Papers, 61(1), 201–224. https://doi.org/10.1007/s00362-017-0929-1
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Zimmermann, G., Pauly, M., & Bathke, A. C. (2020). Multivariate analysis of covariance with potentially singular covariance matrices and non-normal responses. Journal of Multivariate Analysis, 177, 104594. https://doi.org/10.1016/j.jmva.2020.104594
Bananuka, J., Kadaali, A. W., Mukyala, V., Muramuzi, B., & Namusobya, Z. (2019). Audit committee effectiveness, isomorphic forces, managerial attitude and adoption of international financial reporting standards. Journal of Accounting in Emerging Economies, 9(4), 502–526. https://doi.org/10.1108/JAEE-08-2018-0084
Cao, W., Cai, Z., Yao, X., & Chen, L. (2023). Digital Transformation to Help Carbon Neutrality and Green Sustainable Development Based on the Metaverse. Sustainability, 15(9), 7132. https://doi.org/10.3390/su15097132
Chan, F., Gibbs, C., Boratto, R., & Speers, M. (2021). Understanding transnational bribery: a corporate crime framework. Crime, Law and Social Change, 75(3), 221–245. https://doi.org/10.1007/s10611-020-09924-z
Cummins, M., & Gillanders, R. (2020). Are you greasing the Turbines? Corruption and access to electricity in Africa. Energy Policy, 137, 111188. https://doi.org/10.1016/j.enpol.2019.111188
Dávid-Barrett, E. (2019). Business unusual: collective action against bribery in international business. Crime, Law and Social Change, 71(2), 151–170. https://doi.org/10.1007/s10611-017-9715-1
Doss, C. R., & McFowland, E. (2022). Nonparametric Subset Scanning for Detection of Heteroscedasticity. Journal of Computational and Graphical Statistics, 31(3), 813–823. https://doi.org/10.1080/10618600.2022.2026779
Eremin, S. G. (2023). The legal justification for preventing corruption risks associated with the participation of state civil servants in the management of commercial organisations. Management Sciences, 13(1), 47–53. https://doi.org/10.26794/2304-022X-2023-13-1-47-53
Gomez-Trujillo, A. M., & Gonzalez-Perez, M. A. (2022). Digital transformation as a strategy to reach sustainability. Smart and Sustainable Built Environment, 11(4), 1137–1162. https://doi.org/10.1108/SASBE-01-2021-0011
Hauser, C. (2019). Fighting Against Corruption: Does Anti-corruption Training Make Any Difference? Journal of Business Ethics, 159(1), 281–299. https://doi.org/10.1007/s10551-018-3808-3
Hewa Wellalage, N., Locke, S., & Samujh, H. (2020). Firm bribery and credit access: evidence from Indian SMEs. Small Business Economics, 55(1), 283–304. https://doi.org/10.1007/s11187-019-00161-w
Islam, M. A., Cooper, B. J., Haque, S., & John Jones, M. (2022). Moral versus pragmatic legitimacy and corporate anti-bribery disclosure: evidence from Australia. Accounting Forum, 46(1), 30–56. https://doi.org/10.1080/01559982.2021.1925037
Ji, Z., Zhou, T., & Zhang, Q. (2023). The Impact of Digital Transformation on Corporate Sustainability: Evidence from Listed Companies in China. Sustainability, 15(3), 2117. https://doi.org/10.3390/su15032117
Khatatbeh, A. A. (2023). Quantifying the impact of ISO 9001 standard on the project and engineering management and success factors; A case of the construction industry. Engineering, Construction and Architectural Management, 30(6), 2564–2581. https://doi.org/10.1108/ECAM-07-2021-0656
Leal Filho, W., Eustachio, J. H. P. P., Caldana, A. C. F., Will, M., Lange Salvia, A., Rampasso, I. S., Anholon, R., Platje, J., & Kovaleva, M. (2020). Sustainability Leadership in Higher Education Institutions: An Overview of Challenges. Sustainability, 12(9), 3761. https://doi.org/10.3390/su12093761
Li, R., Xu, K., Zhou, Y., & Zhu, L. (2023). Testing the Effects of High-Dimensional Covariates via Aggregating Cumulative Covariances. Journal of the American Statistical Association, 118(543), 2184–2194. https://doi.org/10.1080/01621459.2022.2044334
Liao, K., Park, E. S., Zhang, J., Cheng, L., Ji, D., Ying, Q., & Yu, J. Z. (2021). A multiple linear regression model with multiplicative log-normal error term for atmospheric concentration data. Science of The Total Environment, 767, 144282. https://doi.org/10.1016/j.scitotenv.2020.144282
Lombardi, R., Trequattrini, R., Cuozzo, B., & Cano-Rubio, M. (2019). Corporate corruption prevention, sustainable governance and legislation: First exploratory evidence from the Italian scenario. Journal of Cleaner Production, 217, 666–675. https://doi.org/10.1016/j.jclepro.2019.01.214
Nopriyanto Bahasoan, A., Yashari Soumena, F., & Arsyad, R. (2023). Migration Letters Identifying Increasing Poverty in Indonesia: Does the Human Development Index and Unemployment Affect Poverty in Indonesia? Migration Letters, 20(8), 585–605. https://doi.org/https://doi.org/10.59670/ml.v20i8.5430
Ordieres-Meré, J., Prieto Remón, T., & Rubio, J. (2020). Digitalisation: An Opportunity for Contributing to Sustainability From Knowledge Creation. Sustainability, 12(4), 1460. https://doi.org/10.3390/su12041460
Owusu, E. K., Chan, A. P. C., Yang, J., & Pärn, E. (2020). Towards corruption-free cities: Measuring the effectiveness of anti-corruption measures in infrastructure project procurement and management in Hong Kong. Cities, 96, 102435. https://doi.org/10.1016/j.cities.2019.102435
Schiraldi, M. M., & Varisco, M. (2020). Overall Equipment Effectiveness: consistency of ISO standard with literature. Computers & Industrial Engineering, 145, 106518. https://doi.org/10.1016/j.cie.2020.106518
Shepherd, D. A., Parida, V., & Wincent, J. (2021). Bribery from a micro, demand-side perspective. Small Business Economics, 57(4), 1661–1680. https://doi.org/10.1007/s11187-020-00389-x
Stern, N., & Valero, A. (2021). Innovation, growth and the transition to net-zero emissions. Research Policy, 50(9), 104293. https://doi.org/10.1016/j.respol.2021.104293
Sun, Y., & Wang, X. (2022). An asymptotically F-distributed Chow test in the presence of heteroscedasticity and autocorrelation. Econometric Reviews, 41(2), 177–206. https://doi.org/10.1080/07474938.2021.1874703
Ufere, N., Gaskin, J., Perelli, S., Somers, A., & Boland, R. (2020). Why is bribery pervasive among firms in sub-Saharan African countries? Multi-industry empirical evidence of organisational isomorphism. Journal of Business Research, 108, 92–104. https://doi.org/10.1016/j.jbusres.2019.09.060
Velasco, R. B., Carpanese, I., Interian, R., Paulo Neto, O. C. G., & Ribeiro, C. C. (2021). A decision support system for fraud detection in public procurement. International Transactions in Operational Research, 28(1), 27–47. https://doi.org/10.1111/itor.12811
Vu, M. C. (2021). Tensions and Struggles in Tackling Bribery at the Firm Level: Perspectives from Buddhist-Enacted Organizational Leaders. Journal of Business Ethics, 168(3), 517–537. https://doi.org/10.1007/s10551-019-04235-3
Wang, Z., Liu, J., & Guan, X. (2022). Investigating the causal complexity of corruption in project-based organisations: a scenario analysis of bidding activity in the Chinese construction sector. Engineering, Construction and Architectural Management, 29(10), 3893–3916. https://doi.org/10.1108/ECAM-10-2020-0841
Xu, F., & He, Z. (2020). Testing slope homogeneity in panel data models with a multifactor error structure. Statistical Papers, 61(1), 201–224. https://doi.org/10.1007/s00362-017-0929-1
Xu, P., Chen, L., & Dai, H. (2022a). Pathways to Sustainable Development: Corporate Digital Transformation and Environmental Performance in China. Sustainability, 15(1), 256. https://doi.org/10.3390/su15010256
Xu, P., Chen, L., & Dai, H. (2022b). Pathways to Sustainable Development: Corporate Digital Transformation and Environmental Performance in China. Sustainability, 15(1), 256. https://doi.org/10.3390/su15010256
Yao, F., Xue, L., & Liang, J. (2022). Research on coupling coordination and influencing factors between Urban low-carbon economy efficiency and digital finance—Evidence from 100 cities in China’s Yangtze River economic belt. PLOS ONE, 17(7), e0271455. https://doi.org/10.1371/journal.pone.0271455
Zickar, M. J., & Keith, M. G. (2023). Innovations in Sampling: Improving the Appropriateness and Quality of Samples in Organizational Research. Annual Review of Organizational Psychology and Organizational Behavior, 10(1), 315–337. https://doi.org/10.1146/annurev-orgpsych-120920-052946
Zimmermann, G., Pauly, M., & Bathke, A. C. (2020). Multivariate analysis of covariance with potentially singular covariance matrices and non-normal responses. Journal of Multivariate Analysis, 177, 104594. https://doi.org/10.1016/j.jmva.2020.104594