Garuda - Garba Rujukan Digital

Cloud-Based Transportation Management System (TMS) Implementation for Distribution Efficiency in National E-Commerce Kasrim; Berilian Ayu Kusuma; Isah Fitriani
Maneggio Vol. 2 No. 5 (2025): OCTOBER-MJ
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/dc5de563

This study aims to analyze the implementation of a cloud-based Transportation Management System (TMS) in enhancing distribution efficiency within Indonesia’s national e-commerce sector using a Systematic Literature Review (SLR) approach. The adoption of cloud-based TMS has become an integral component of Indonesia’s digital logistics transformation, emphasizing efficiency, transparency, and sustainability. The findings indicate that TMS can reduce transportation costs by 15–25%, accelerate delivery times, and optimize route planning through real-time data integration. Economically, the system strengthens national competitiveness by improving productivity and fostering cross-sector collaboration among logistics providers, government bodies, and e-commerce enterprises. From a sustainability perspective, TMS contributes to carbon emission reduction and energy efficiency in transportation, aligning with the nation’s green logistics initiatives and net-zero emission targets. Nevertheless, its effectiveness remains dependent on digital infrastructure readiness, human resource competence, and policy support for cross-sector data interoperability. This research highlights that the successful adoption of cloud-based TMS requires collaborative governance and inclusive technological integration policies. Therefore, TMS serves as a strategic foundation for enhancing distribution efficiency, e-commerce competitiveness, and sustainable digital economic growth in Indonesia.

Corporate Social Responsibility (CSR) as an Instrument of Economic Justice Berilian Ayu Kusuma; Sri Wahyuni Jumadi; Pramidazzura Alifa Rifqi
Nomico Vol. 2 No. 9 (2025): Nomico - October
Publisher : PT. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/3znftz38

This study examines Corporate Social Responsibility (CSR) as a strategic instrument for achieving economic justice in the context of global corporate transformation. The research adopts a qualitative descriptive approach focusing on the economic institutional framework to analyze how CSR contributes to redistributive mechanisms, economic empowerment, and inclusive growth. Data were collected through semi-structured interviews with CSR managers from multinational companies in the energy, mining, and manufacturing sectors, complemented by secondary data from sustainability reports and global policy documents such as those by the OECD, UNDP, and GRI. The findings reveal that CSR has shifted from philanthropic activities toward a strategic economic mechanism capable of reducing inequality and fostering social inclusion. Firms that integrate CSR into their core economic strategy exhibit higher levels of supply chain resilience, stakeholder trust, and community welfare. The study also highlights that empowerment-based CSR programs, particularly those supporting local entrepreneurship and inclusive digitalization, significantly improve community income and business performance. Furthermore, CSR is found to drive long-term corporate transformation through sustainability-oriented innovation and stakeholder capitalism, aligning business profitability with distributive justice and institutional resilience. In conclusion, CSR functions not only as a moral obligation but also as a redistributive economic policy tool essential for achieving sustainable and equitable growth in the global economy.

Digital Behavior in Organizations: Employee–Customer Interaction in Platform Ecosystems Berilian Ayu Kusuma
TechTalent & Business Review Vol. 2 No. 1 (2026): TTBR-April 2026
Publisher : Asosiasi Peneliti dan Inovasi Nusantara (APIN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63985/ttbr.v2i1.106

The rapid development of platform-based organizations has transformed how employees and consumers interact within digital ecosystems, making digital behavior a critical factor in organizational performance. This study aims to analyze digital behavior and the interaction between employees and consumers within platform ecosystems and its implications for organizational outcomes. The research adopts a qualitative descriptive approach, utilizing data collected through semi-structured interviews, observations, and document analysis. Data were analyzed using thematic analysis, including data reduction, categorization, and interpretation to identify patterns of digital interaction. The findings indicate that employee digital behavior—such as remote collaboration, algorithmic coordination, and multi-platform engagement—significantly influences consumer experience. At the same time, consumer digital behavior, including engagement, feedback, and value co-creation, shapes service quality and organizational responsiveness. The interaction between employees and consumers is found to be reciprocal and dynamic, mediated by platform governance and digital technologies. Furthermore, effective management of digital interactions enhances organizational performance through improved productivity, customer satisfaction, and innovation. In conclusion, this study highlights that an integrated understanding of digital behavior in platform ecosystems is essential for optimizing employee–consumer interaction and achieving sustainable organizational competitiveness in the digital era

Emotional Labor in Service Work: Its Impact on Satisfaction and Performance Berilian Ayu Kusuma
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

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 Berilian Ayu Kusuma
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 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.

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