Application of Analytic Network Method for Employee Bonus Determination Process
DOI:
https://doi.org/10.35335/jict.v15i2.179Keywords:
Analytic Network Process (ANP), Credit Risk, Employee Bonus System, Evaluation Criteria, HR Management, Reward SystemAbstract
Employee bonus system is one of the important strategies in human resource management (HRM) to improve employee motivation, performance, and loyalty. However, many companies face challenges in creating a fair, transparent, and effective bonus system, mainly due to reliance on traditional assessment methods that are subjective. This research aims to develop an employee bonus model based on the Analytic Network Process (ANP) method that is able to capture the relationship between criteria holistically. The research method involves data collection through observation, interviews, and literature study, and data analysis using ANP to evaluate criteria such as target achievement, productivity, work quality, initiative, teamwork, and attendance. The results showed that ANP was effectively able to produce objective and transparent prioritization calculations, with employee A03 (Dermawan) identified as the highest bonus recipient with a final score of 0.1632 (32.64%). The implications of this research suggest that the application of ANP can help companies design a more fair and strategic reward system, thereby increasing employee confidence in the bonus system. However, this research is limited to one case study and has not evaluated the long-term impact of the developed model. Future research is recommended to expand the coverage to various industry contexts and integrate advanced analytic technologies to improve the accuracy of the model.
References
Ahmed, T., Khan, M. S., Thitivesa, D., Siraphatthada, Y., & Phumdara, T. (2020). Impact of employees engagement and knowledge sharing on organizational performance: Study of HR challenges in COVID-19 pandemic. Human Systems Management, 39(4), 589–601. https://doi.org/10.3233/HSM-201052
Asadabadi, M. R., Chang, E., & Saberi, M. (2019). Are MCDM methods useful? A critical review of Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP). Cogent Engineering, 6(1), 1623153. https://doi.org/10.1080/23311916.2019.1623153
Cheema, S. M., Tariq, S., & Pires, I. M. (2023). A natural language interface for automatic generation of data flow diagram using web extraction techniques. Journal of King Saud University - Computer and Information Sciences, 35(2), 626–640. https://doi.org/10.1016/j.jksuci.2023.01.006
Chong, H. Y., & Diamantopoulos, A. (2020). Integrating advanced technologies to uphold security of payment: Data flow diagram. Automation in Construction, 114, 103158. https://doi.org/10.1016/j.autcon.2020.103158
Dabab, M. Y., & Fountain, R. (2020). An Assessment of the Decision-Making Units ’ Efficiency in Service Systems. Portland State University.
Ferraris, A., Erhardt, N., & Bresciani, S. (2019). Ambidextrous work in smart city project alliances: unpacking the role of human resource management systems. International Journal of Human Resource Management, 30(4), 680–701. https://doi.org/10.1080/09585192.2017.1291530
Hameed, A., Ramzan, M., Hafiz, M., Kashif Zubair, M., Ali, G., & Arslan, M. (2014). Impact of compensation on employee performance. International Journal of Business and Social Science, 5(2), 302–309.
Jahandarlashaki, K., Kojori, D. K., & ... (2024). Prioritize effective factors on fostering the culture of tax payment in Iranian economic enterprises with the help of the ANP network analysis process. … Journal of Nonlinear …, 15(6), 253–262. https://ijnaa.semnan.ac.ir/article_7887.html%0Ahttps://ijnaa.semnan.ac.ir/article_7887_c6f5464143069e20274ef4237d614c59.pdf
Kelechi Chidiebere Ihemereze, Nsisong Louis Eyo-Udo, Blessed Afeyokalo Egbokhaebho, Chibuike Daraojimba, Uneku Ikwue, & Ekene Ezinwa Nwankwo. (2023). Impact of Monetary Incentives on Employee Performance in the Nigerian Automotive Sector: a Case Study. International Journal of Advanced Economics, 5(7), 162–186. https://doi.org/10.51594/ijae.v5i7.548
Kornelakis, A. (2018). Why are your reward strategies not working? The role of shareholder value, country context, and employee voice. Business Horizons, 61(1), 107–113. https://doi.org/10.1016/j.bushor.2017.09.010
Master, E., Banking, O. F., In, P., & Apex, M. (2019). Effect of Reward System on Employee. Journal of Higher Education Service Science and Management (JoHESSM), 2(December).
Ngwa, W. T., Adeleke, B. S., Agbaeze, E. K., Ghasi, N. C., & Imhanrenialena, B. O. (2019). Effect of reward system on employee performance among selected manufacturing firms in the litoral region of Cameroon. Academy of Strategic Management Journal, 18(3), 1–16.
Reisi, M., Afzali, A., & Aye, L. (2018). Applications of analytical hierarchy process (AHP) and analytical network process (ANP) for industrial site selections in Isfahan, Iran. Environmental Earth Sciences, 77(14), 1–13. https://doi.org/10.1007/s12665-018-7702-1
Salehzadeh, R., & Ziaeian, M. (2024). Decision making in human resource management: a systematic review of the applications of analytic hierarchy process. Frontiers in Psychology, 15, 1400772. https://doi.org/10.3389/fpsyg.2024.1400772
Taherdoost, H., & Madanchian, M. (2023). Analytic Network Process (ANP) Method: A Comprehensive Review of Applications, Advantages, and Limitations. Journal of Data Science and Intelligent Systems, 1(1), 12–18. https://doi.org/10.47852/bonviewjdsis3202885
Venkatesh, V. G., Kang, K., Wang, B., Zhong, R. Y., & Zhang, A. (2020). System architecture for blockchain based transparency of supply chain social sustainability. Robotics and Computer-Integrated Manufacturing, 63, 101896. https://doi.org/10.1016/j.rcim.2019.101896
Wenzel, A. K., Krause, T. A., & Vogel, D. (2019). Making Performance Pay Work: The Impact of Transparency, Participation, and Fairness on Controlling Perception and Intrinsic Motivation. Review of Public Personnel Administration, 39(2), 232–255. https://doi.org/10.1177/0734371X17715502


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