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Creating Customer Loyalty Through Commitment to Quality of Service Model of Brady Cronin Susriyanti, Susriyanti; Krisna, Nandan Lima; Lusiana, Lusiana; Nardo, Rio
International Journal of Applied Management and Business Vol. 1 No. 1 (2023)
Publisher : ADPEBI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54099/ijamb.v1i1.458

Abstract

Purpose –This study aims to see how the effect of the service quality of the Brady Cronin model (quality of interaction, quality of the physical environment, quality of results) on customer loyalty directly or indirectly through commitment. Methodology/approaches – This Study used Quantitatif method. The Quistioner were distributing  to 200 customers of Bank Nagari in the city of Padang. Findings –It was found that the quality of the interaction and the quality of the physical environment in the service quality of the Brady Cronin model directly affected customer loyalty. Meanwhile, the quality of the results in the service quality of the Brady Cronin model does not directly affect customer loyalty. Indirectly, the three services of the Brady Cronin model of service quality affect customer loyalty through commitment. Novelty/values ​​–The quality of results that do not have a direct effect on loyalty indicates that customers have not got what they want. So it is important for Bank Nagari to improve the quality of results to increase customer loyalty in the future.
The Role of Algorithmic Management in HR Practices and Ethical Challenges Suryawan, Ryan Firdiansyah; Yusuf, Muhammad; Suhendah, Rousilita; Krisna, Nandan Lima; Kamar, Karnawi
Studi Ilmu Manajemen dan Organisasi Vol. 6 No. 3 (2025): Oktober
Publisher : Penerbit Goodwood

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/simo.v6i3.4642

Abstract

Purpose: This study aims to systematically explore the development of algorithmic management in HR practices, focusing on emerging ethical challenges. Methodology/approach: Using a Systematic Literature Review (SLR), this study analyzes findings from the past five years on the use of algorithms in managerial decision-making and their impact on workers' rights, justice, and welfare. Results/findings: While algorithms bring efficiency, they present significant ethical, social, and legal challenges. Organizations must balance technological efficiency with principles of fairness, transparency, and privacy protection. A collaborative approach between humans and technology, coupled with strict regulation, is essential. Conclusions: Algorithmic management in HR boosts efficiency but raises ethical concerns about fairness and transparency. Its success depends on creating accountable systems that balance technology with human values. Researchers advocate for human-technology collaboration, with algorithms as tools, not substitutes for human decision-making, and the integration of "responsible and explainable AI" to foster fairness and inclusivity. Limitations: The study’s focus on references from developed countries limits its applicability to developing countries like Indonesia. Additionally, most of the literature is conceptual and lacks long-term data. Contribution: The study suggests exploring contextual and participatory case studies across sectors and regions, along with both quantitative and qualitative research on algorithms’ impact on job satisfaction and employee rights. Further research on the role of national and international regulations is required.