cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Abdullah
Contact Email
abdullahkhudori62@gmail.com
Phone
+6283117646123
Journal Mail Official
contact.jurnalreturn@gmail.com
Editorial Address
STAI Kuningan Jalan Raya Susukan, Cipicung, Kuningan, Jawa Barat
Location
Kab. kuningan,
Jawa barat
INDONESIA
Return : Study of Management, Economic and Bussines
Published by PT. Publikasiku Academic Solution
ISSN : 29640121     EISSN : 29633699     DOI : 10.57096
Core Subject : Economy,
Economics, Econometrics & Finance
The Journal RETURN is a double blind peer-reviewed academic journal and open access to social and scientific fields. The journal is published monthly by PT. Publikasiku Academic Solution. The Jurnal RETURN provides a means for sustained discussion of relevant issues that fall within the focus and scopes of the journal which can be examined empirically. The journal publishes research articles covering all aspects of social sciences, ranging from Economic, management and Bussines. Published articles are articles from critical and comprehensive research, studies or scientific studies on important and current issues, or reviews of scientific books
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Bisnis, Menejemen, dan Akutansi (Lain-Lain)
Articles 326 Documents
 29   30   31   32   33 
Human-AI Collaboration in Small Enterprises: Balancing Automation and Human Input Azzahra, Adelia; Ridzki, Mohamad Maulana
Return : Study of Management, Economic and Bussines Vol. 4 No. 12 (2025): Return: Study of Management, Economic and Business
Publisher : PT. Publikasiku Academic Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57096/return.v4i12.443

Abstract

Industry 5.0 emphasizes human-centric collaboration between artificial intelligence and human workers, yet small enterprises face unique challenges in AI adoption due to limited resources and technical expertise. This research examines the dynamics of human-AI collaboration in small enterprises, identifying implementation challenges, success strategies, and measurable impacts on productivity and employee satisfaction. A qualitative case study approach was employed, involving semi-structured interviews with 10 AI integration specialists and small enterprise owners (10-50 employees), analysis of 7 organizational case studies, and document reviews of industry reports (2020-2024). Data were analyzed using NVivo 12 software following Braun and Clarke’s thematic analysis framework. Analysis revealed five major themes: skill gaps affecting 68% of interviewed enterprises, employee resistance driven by job security concerns (54%), technical infrastructure barriers (72%), productivity improvements ranging from 15-35% with average 34.3%, and critical importance of human oversight in decision-making (92% consensus). Small enterprises implementing AI with gradual integration strategies reported 28% average productivity increase, 17.8% revenue growth, and 22% improvement in employee satisfaction within 12 months. The 3-year cumulative ROI reached 184% despite initial implementation costs averaging 3-5x software licensing fees. Effective human-AI collaboration in small enterprises requires balanced integration strategies emphasizing employee training (15-20% of budget), transparent policies, gradual implementation (6-12 months), and maintaining human judgment in critical decisions (80-95% of strategic tasks). AI serves most effectively as a complementary tool handling 70-85% of routine, data-intensive tasks while humans retain control over strategic, creative, and interpersonal functions. The research validates Industry 5.0’s human-centric paradigm and provides quantified benchmarks for small enterprise AI adoption.
Implementation of Competency-Based Performance Management System for Employees of PLTMG MPP Manokwari 2 Dedi, Selmi; Astuti, Windhi; Lotte, Luckhy Natalia Anastasya; Saptomo, Yulius Heri
Return : Study of Management, Economic and Bussines Vol. 5 No. 3 (2026): Return: Study of Management, Economic and Business
Publisher : PT. Publikasiku Academic Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57096/return.v5i3.445

Abstract

Human resources are a major factor in determining organizational success. Competency-based performance management is essential as it connects employees' knowledge, skills, and attitudes to the achievement of strategic organizational goals. PLTMG MPP Manokwari 2, as an electricity provider in West Papua, faces significant human resource challenges, including employees working outside their fields of expertise, which impacts suboptimal performance achievement. This study aims to analyze the implementation of a competency-based performance management system for employees at PLTMG MPP Manokwari 2 in Manokwari Regency. The research employed a qualitative descriptive approach with data collected through observation, interviews, questionnaires, and documentation. Data analysis used the Miles & Huberman model (data reduction, data display, and conclusion drawing) and SWOT analysis to map strengths, weaknesses, opportunities, and threats. The findings indicate that performance planning, communication, and competency development have been applied relatively well, although competency measurement remains general and not detailed. SWOT analysis identified strengths in human resource quality and management support, weaknesses in competency indicators, opportunities from energy policy and technology, and threats from budget constraints and rigid work culture. The study concludes that competency-based performance management is being implemented but requires stronger indicators and more sustainable HR development programs.
Optimizing Sales Strategies in Financing Institutions Through Machine Learning–Based Next Best Offer Recommendation Soesilo, Daniel Gunawan; Susilo, Benny Setiawan; Setyobudi, Wahyu Tri
Return : Study of Management, Economic and Bussines Vol. 5 No. 3 (2026): Return: Study of Management, Economic and Business
Publisher : PT. Publikasiku Academic Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57096/return.v5i3.444

Abstract

Digital transformation in the financial services industry makes companies use more data for decision-making. One example is the use of a Machine Learning–based Next Best Offer (NBO-ML) system to help increase sales performance. This study looks at how Data Quality, Model Interpretability, Organizational Readiness, and Privacy Concerns affect the performance of the NBO-ML system and how this system enhances Sales Effectiveness. This research uses a quantitative method and collects data from internal employees who are involved in developing and using the NBO-ML system. The results show that Model Interpretability and Organizational Readiness are very important for improving NBO-ML performance. This means the model must be clear and easy to understand, and the organization must be ready to adopt AI technology. On the other hand, Data Quality and Privacy Concerns do not directly affect system performance, suggesting that these factors may operate in different ways. The performance of the NBO-ML system strongly influences Sales Effectiveness and acts as a bridge between technological factors and business outcomes. Overall, this study shows that explainable models and Organizational Readiness are critical for deriving business value from machine learning–based recommendation systems in the financial services industry.
AnalysisAnalysis of Gold Price Fluctuations in Indonesia in the Third Quarter of 2025 of Gold Price Fluctuations in Indonesia in the Third Quarter of 2025 Magfiroh, Diana; Komarudin, Komarudin
Return : Study of Management, Economic and Bussines Vol. 4 No. 10 (2025): Return: Study of Management, Economic and Business
Publisher : PT. Publikasiku Academic Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57096/return.v4i10.448

Abstract

This study examines the fluctuations of domestic gold prices in Indonesia during the third quarter of 2025, which were influenced by complex interactions between global and domestic macroeconomic factors. Gold plays a crucial role as an investment instrument and hedge asset, making it important to understand the determinants of its price movements, particularly in emerging markets such as Indonesia. This research aims to analyze the influence of external factors, including world gold prices, rupiah exchange rates, global inflation, and global interest rates, on domestic gold price fluctuations. This study employs a quantitative approach using time series data for the period July–September 2025. The analysis methods include multiple linear regression (OLS) to examine the simultaneous effects of variables, the GARCH model to analyze volatility patterns, and the Granger causality test to identify causal relationships among variables. The results indicate that world gold prices and rupiah exchange rates have a significant and dominant influence on domestic gold prices, while global interest rates also show a meaningful effect. In contrast, global inflation does not have a significant direct impact. Furthermore, gold price volatility exhibits a clustering pattern, indicating that periods of high volatility tend to be followed by similar conditions. In conclusion, domestic gold price movements in Indonesia are strongly driven by external macroeconomic factors, particularly global gold prices and exchange rate dynamics. This study contributes to the literature by integrating regression, volatility, and causality analysis within a specific quarterly context. The findings imply that investors and policymakers should closely monitor global economic indicators to manage risks and formulate effective strategies in responding to gold market fluctuations
The Effect of Geographic Expansion Strategy and Fintech Integration on Operational Efficiency and Business Scalability of On-Demand Service Platform Companies (A Study of Gojek and Grab in Indonesia) Sutrisna, Dwi Winahyo
Return : Study of Management, Economic and Bussines Vol. 5 No. 3 (2026): Return: Study of Management, Economic and Business
Publisher : PT. Publikasiku Academic Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57096/return.v5i3.449

Abstract

Background: The rapid growth of on-demand service platforms in Indonesia, particularly Gojek and Grab, has transformed the digital economy landscape. However, the strategic mechanisms through which geographic expansion and fintech integration jointly influence operational efficiency and business scalability remain underexplored. Objective: This study analyzes the impact of geographic expansion strategies and fintech integration on the operational efficiency and business scalability of on-demand service platform companies in Indonesia, focusing on Gojek and Grab. Methods: The research employs a systematic literature review approach, synthesizing findings from academic journals, industry reports, and official documents. The analysis integrates literature on geographic expansion, two-sided platforms, fintech ecosystems, and digital business scalability. Results: The findings reveal that rapid expansion supported by disruptive technology has enabled both platforms to enter new markets, strengthen their economic contribution, and transform consumer behavior. Fintech integration through services such as GO-PAY, OVO, and GrabPay significantly improves operational efficiency through accelerated transactions, expanded financial access, and digital process automation. Furthermore, the development of digital ecosystems and innovative collaboration between fintech providers and digital banks enhances business scalability and sustainability. Conclusion: This study concludes that strategic geographic expansion and fintech integration are mutually reinforcing drivers of platform competitiveness. The findings underscore the importance of ecosystem development and digital infrastructure in supporting the growth of the on-demand services industry in Indonesia. The research contributes theoretically to digital platform literature and offers practical implications for platform managers and policymakers.
The Impact of Dynamic Capabilities on Digital Transformation: A Study in “A” Conglomeration’s Non-Bank Financial Institutions Fiona, Fiona; Pambudi, Aloysius Anandyo; Wahyudi, Samuel Dicsky; Maulida, Mira
Return : Study of Management, Economic and Bussines Vol. 5 No. 3 (2026): Return: Study of Management, Economic and Business
Publisher : PT. Publikasiku Academic Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57096/return.v5i3.450

Abstract

This study investigates how dynamic capabilities influence digital transformation within the Non-Bank Financial Institutions (NBFIs) sector of the “A” conglomerate. In Indonesia’s financial industry, digital transformation has become a strategic priority, but organizations still face several obstacles, including high technology investment costs, difficulties in adapting to digital systems, and regulatory compliance requirements. The research applies the Dynamic Capabilities (DC) framework together with the Technology-Organization-Environment (TOE) framework to analyze how both internal and external factors affect the implementation of digital transformation in NBFIs. The results show that technological capability and innovation play a major role in driving digital transformation, while organizational capability strengthens innovation development. In contrast, ecosystem capability and governance, risk, and compliance (GRC) factors do not demonstrate a significant influence. Overall, the findings offer useful insights for NBFIs in designing and implementing more effective digital transformation strategies.

Page 33 of 33 | Total Record : 326

 29   30   31   32   33 

Filter by Year

2022 2026


Reset
Filter By Issues
All Issue Vol. 5 No. 3 (2026): Return: Study of Management, Economic and Business Vol. 5 No. 2 (2026): Return: Study of Management, Economic and Business Vol. 5 No. 1 (2026): Return: Study of Management, Economic and Business Vol. 4 No. 12 (2025): Return: Study of Management, Economic and Business Vol. 4 No. 11 (2025): Return: Study of Management, Economic and Business Vol. 4 No. 10 (2025): Return: Study of Management, Economic and Business Vol. 4 No. 9 (2025): Return: Study of Management, Economic and Business Vol. 4 No. 8 (2025): Return: Study of Management, Economic and Business Vol. 4 No. 7 (2025): Return: Study of Management, Economic and Business Vol. 4 No. 6 (2025): Return: Study of Management, Economic and Business Vol. 4 No. 5 (2025): Return: Study of Management, Economic and Business Vol. 4 No. 4 (2025): Return: Study of Management, Economic and Business Vol. 4 No. 3 (2025): Return: Study of Management, Economic and Business Vol. 4 No. 2 (2025): Return: Study of Management, Economic and Business Vol. 4 No. 1 (2025): Return: Study of Management, Economic And Bussines Vol. 3 No. 12 (2024): Return: Study of Management, Economic And Bussines Vol. 3 No. 11 (2024): Return : Study of Management, Economic And Bussines Vol. 3 No. 10 (2024): Return : Study of Management, Economic And Bussines Vol. 3 No. 9 (2024): Return : Study of Management, Economic And Bussines Vol. 3 No. 8 (2024): Return : Study of Management, Economic And Bussines Vol. 3 No. 7 (2024): Return : Study of Management, Economic And Bussines Vol. 3 No. 6 (2024): Return : Study of Management, Economic And Bussines Vol. 3 No. 5 (2024): Return : Study of Management, Economic And Bussines Vol. 3 No. 4 (2024): Return : Study of Management, Economic And Bussines Vol. 3 No. 3 (2024): Return : Study of Management, Economic And Bussines Vol. 3 No. 2 (2024): Return : Study of Management, Economic And Bussines Vol. 3 No. 1 (2024): Return : Study of Management, Economic And Bussines Vol. 2 No. 12 (2023): Return : Study of Management, Economic And Bussines Vol. 2 No. 11 (2023): Return : Study of Management, Economic And Bussines Vol. 2 No. 10 (2023): Return : Study of Management, Economic And Bussines Vol. 2 No. 9 (2023): Return : Study of Management, Economic And Bussines Vol. 2 No. 8 (2023): Return : Study of Management, Economic And Bussines Vol. 2 No. 7 (2023): Return : Study of Management, Economic And Bussines Vol. 2 No. 6 (2023): Return : Study of Management, Economic And Bussines Vol. 2 No. 5 (2023): Return : Study of Management, Economic And Bussines Vol. 2 No. 4 (2023): Return : Study of Management, Economic And Bussines Vol. 2 No. 3 (2023): Return : Study of Management, Economic And Bussines Vol. 2 No. 2 (2023): Return : Study of Management, Economic And Bussines Vol. 2 No. 1 (2023): Return : Study of Management, Economic And Bussines Vol. 1 No. 4 (2022): Return : Study of Management, Economic And Bussines Vol. 1 No. 3 (2022): Study Of Management, Economic And Bussines Vol. 1 No. 3 (2022): Return : Study of Management, Economic And Bussines Vol. 1 No. 2 (2022): Return : Study of Management, Economic And Bussines Vol. 1 No. 1 (2022): Return : Study of Management, Economic And Bussines More Issue