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Journal : Maneggio

Emotional Labor in Service Work: Its Impact on Satisfaction and Performance Kusuma, Berilian Ayu
Maneggio Vol. 3 No. 2 (2026): APRIL- MJ
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/zjkyqw42

Abstract

Emotional labor has become a critical component in service-oriented organizations, where employees are required to regulate their emotions to meet organizational expectations and enhance customer satisfaction. While emotional labor can improve service quality and performance, it also poses risks to employee well-being, particularly when poorly managed. This study aims to analyze the impact of emotional labor strategies—surface acting, deep acting, and genuine acting—on employee satisfaction and performance. The research adopts a qualitative approach using a systematic literature review and document analysis of recent peer-reviewed studies. Data are analyzed through thematic and qualitative content analysis to identify key patterns related to emotional regulation, employee well-being, and performance outcomes. The findings reveal that surface acting leads to emotional exhaustion, burnout, and reduced job satisfaction and performance, whereas deep acting and genuine acting contribute to higher satisfaction, lower stress, and improved service performance. The discussion highlights the importance of organizational support, emotional intelligence, and service climate in moderating these effects. In conclusion, effective management of emotional labor requires a shift toward human-centered practices that promote authentic emotional engagement and sustainable performance..
Human-AI Collaboration in Management: Its Impact on Efficiency and Performance Kusuma, Berilian Ayu
Maneggio Vol. 3 No. 2 (2026): APRIL- MJ
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/pq1ds311

Abstract

ABSTRACT Human–AI collaboration has emerged as a transformative approach in modern management, combining the computational power of artificial intelligence with human intuition, creativity, and ethical judgment. This study aims to analyze the impact of human–AI collaboration on organizational efficiency and performance, with a focus on collaboration design, trust, and organizational context. The research adopts a qualitative approach using a systematic literature review and document analysis of recent peer-reviewed studies. Data are analyzed through thematic and qualitative content analysis to identify key patterns related to efficiency, decision quality, and performance outcomes. The findings reveal that human–AI collaboration enhances efficiency through task automation, predictive analytics, and reduced cognitive load, while also improving decision-making accuracy and consistency. However, the effectiveness of this collaboration depends on role complementarity, trust in AI, employee capability, and supportive organizational culture. The discussion highlights that balanced integration between human and AI capabilities is essential to achieve sustainable performance improvements. In conclusion, human–AI collaboration serves as a strategic enabler of organizational performance when supported by appropriate design, governance, and human resource development.