THE IMPLEMENTATION OF EMPLOYEE WORK CULTURE STRATEGY THROUGH THE USE OF ARTIFICIAL INTELLIGENCE IN THE RECRUITMENT PROCESS IN MANUFACTURING COMPANIES
DOI:
https://doi.org/10.53067/ijomral.v4i2.337Keywords:
Artificial Intelligence, Work Culture, Hiring, Manufacturing Companies, Human Resource Management, Digital TransformationAbstract
This study aims to examine the implementation of employee work culture strategies through the use of Artificial Intelligence (AI) in the recruitment process in Indonesian manufacturing companies. The use of AI in the recruitment process is seen as an essential innovation to improve efficiency, objectivity, and speed of employee selection. The data for this study was collected through interviews, observations, and documentation in manufacturing companies from October to December 2024, utilising a qualitative approach. The study's findings indicate that AI has the capacity to expedite the selection process, enhance the precision of candidate selection, and positively influence the work culture of new employees by fostering increased discipline and motivation. However, there are challenges in the form of reduced social interaction that affect the cultural adaptation process. The main supporting factors are technological readiness and HR training, while employee resistance and limited data are obstacles that need to be managed strategically. The integration of AI with a humanistic work culture development strategy is recommended in this study to ensure the effective and sustainable execution of digital transformation. These findings contribute to the development of human resource management in the industrial era 4.0, especially in the context of manufacturing companies in Indonesia
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References
Armstrong, M., & Taylor, S. (2020). Armstrong's Handbook of Human Resource Management Practice (15th ed.). Kogan Page.
Badan Pusat Statistik. (2023). Statistik Indonesia 2023. Jakarta: BPS.
Binns, R., Veale, M., Van Kleek, M., & Shadbolt, N. (2020). ’It's Reducing a Human Being to a Percentage’: Perceptions of Justice in Algorithmic Decisions. CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3313831.3378947
Boxall, P., Purcell, J., & Wright, P. (2022). The Oxford Handbook of Human Resource Management. Oxford University Press.
Chen, Y., Wang, L., & Zhang, H. (2024). Artificial Intelligence as a Cultural Mediator in Human Resource Management: Insights from Manufacturing Industries. Journal of Business Research, 154, 112-124. https://doi.org/10.1016/j.jbusres.2023.112124
Creswell, J. W., & Poth, C. N. (2023). Qualitative Inquiry and Research Design: Choosing Among Five Approaches (5th ed.). SAGE Publications.
Elo, S., & Kyngäs, H. (2020). The qualitative content analysis process. Journal of Advanced Nursing, 62(1), 107-115.
Hasibuan, M. S. P. (2021). Manajemen Sumber Daya Manusia. Jakarta: Bumi Aksara.
Huang, L., Zhao, Y., & Li, X. (2024). Cultural Integration in AI-Driven Human Resource Management: A New Paradigm. Journal of Management Analytics, 11(1), 45–61. https://doi.org/10.1080/23270012.2023.2198754
Kim, S., & Park, J. (2021). The Role of Artificial Intelligence in Enhancing Recruitment Decision-Making: Evidence from Manufacturing. Human Resource Management Review, 31(3), 100754. https://doi.org/10.1016/j.hrmr.2020.100754
Kurniawan, A., & Hidayat, R. (2023). Integrasi Budaya Kerja dengan Teknologi AI dalam Proses Rekrutmen: Studi pada Perusahaan Manufaktur Skala Menengah di Indonesia. Jurnal Manajemen dan Organisasi, 10(1), 50-65.
Luthans, F. (2021). Organisational Behavior (14th ed.). McGraw-Hill Education.
Marler, J. H., & Boudreau, J. W. (2022). An evidence-based review of e-HRM and strategic human resource management. Human Resource Management Review, 32(2), 100844. https://doi.org/10.1016/j.hrmr.2021.100844
Muller, T., & Schneider, F. (2021). Synergising Artificial Intelligence and Organizational Culture: A Case Study in German Manufacturing. International Journal of Human Resource Management, 32(14), 3015-3035. https://doi.org/10.1080/09585192.2020.1737212
Nasution, S. (2022). Metode Penelitian Naturalistik Kualitatif. Bumi Aksara.
Nguyen, H. T., Wang, Y., & Tran, P. Q. (2023). Integrating AI and Organizational Culture in Recruitment: A Case Study of High-Tech Firms. Journal of Human Resource and Sustainability, 11(1), 34-48. https://doi.org/10.3390/jhres11010034
Nugroho, B., & Santoso, D. (2023). Efektivitas Penggunaan AI dalam Proses Seleksi Karyawan dan Implikasinya terhadap Budaya Organisasi. Jurnal Teknologi dan Manajemen Sumber Daya Manusia, 7(2), 89-102.
Rahmawati, S., Prasetyo, L., & Wulandari, T. (2022). Pengaruh Penerapan AI pada Rekrutmen terhadap Kesesuaian Budaya Kerja Karyawan di Industri Manufaktur. Jurnal Sumber Daya Manusia dan Manajemen, 11(3), 213-226.
Robbins, S. P., & Judge, T. A. (2021). Organisational Behavior (18th ed.). Pearson.
Schein, E. H. (2020). Organisational Culture and Leadership (5th ed.). Wiley.
Sugiyono. (2023). Metode Penelitian Kualitatif, Kuantitatif, dan R&D. Alfabeta.
Sutrisno, E. (2023). Manajemen Sumber Daya Manusia di Era Digital. Prenadamedia Group.
Tan, J., & Li, Q. (2022). Challenges and Opportunities of AI in Recruitment: A Cross-Cultural Perspective. Human Resource Development International, 25(4), 320-338. https://doi.org/10.1080/13678868.2022.2040913
Upadhyay, A. K., & Khandelwal, K. (2022). Artificial Intelligence in Human Resource Management: A Review and Research Agenda. Journal of Management Development, 41(5), 455–472. https://doi.org/10.1108/JMD-06-2021-0161
Wijaya, D., & Utami, R. (2021). Peran HR dalam Menyesuaikan Algoritma AI dengan Budaya Kerja Lokal di Perusahaan Manufaktur. Jurnal Manajemen Sumber Daya Manusia Indonesia, 8(4), 150-162.
Wijaya, D., & Utami, R. (2021). Peran HR dalam Menyesuaikan Algoritma AI dengan Budaya Kerja Lokal di Perusahaan Manufaktur. Jurnal Manajemen Sumber Daya Manusia Indonesia, 8(4), 150-162.
Wulandari, T., & Pratama, R. (2022). Pengaruh Budaya Kerja terhadap Produktivitas Karyawan di Industri Manufaktur Indonesia. Jurnal Psikologi Industri dan Organisasi, 11(1), 33-46
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