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Innovation in Business Management Exploring the Path to Competitive Excellence Sana, Eirene; Angelina Bisty, Alice; Husain, Abigail; Delhi, Ariana
APTISI Transactions on Management (ATM) Vol 8 No 1 (2024): ATM (APTISI Transactions on Management: January)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v8i1.2204

Abstract

In the realm of business management, the focal point has shifted towards innovation as a pivotal endeavor for attaining a competitive edge. This study aims to delve into the repercussions of innovation in business management and accentuate its pivotal role in forging pathways to competitive advantage. The Structural Equation Modeling (SEM) analysis, employing the SmartPLS tool, was employed to scrutinize data gathered from 150 respondents representing Micro, Small, and Medium Enterprises (UMKM) in Indonesia across four distinct sectors: fashion, furniture, home decoration, and services. The analysis reveals a noteworthy impact of innovation on various facets of business management, encompassing strategy, organizational operations, and marketing. These findings underscore that organizations adept at integrating innovation into their management practices can cultivate sustainable competitive advantages. Furthermore, the research spotlights critical factors influencing the implementation of innovation, including leader support, organizational culture, and the ability to navigate risk. This study furnishes invaluable insights for practitioners and decision-makers by underscoring the significance of innovation in fortifying competitive positions. The practical implications of these findings suggest that MSMEs fostering a culture of innovation, backed by leadership support and adept risk management, stand poised to enhance their performance and competitiveness within the increasingly intricate and dynamic markets.
A Structural Framework for Effective Time Management in Dynamic Work Environments Sana, Eirene; Jacqueline, Greisy; Nathalie, Julia; Maria, Lily; Callula, Brigitta
APTISI Transactions on Management (ATM) Vol 8 No 2 (2024): ATM (APTISI Transactions on Management: May)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v8i2.2256

Abstract

This paper presents a structural framework to enhance time management profi- ciency within dynamic work environments. The framework integrates prioritization techniques, task scheduling methods, delegation strategies, and technology utilization to optimize time allocation and productivity. The evaluation demonstrates significant improvements in time management efficiency and client satisfaction across various professional contexts.  For instance, by employing the eisenhower Matrix and Pareto Principle, project managers achieved a 20% im- provement in project completion times. The framework’s adaptability is further highlighted by a 25% reduction in project turnaround time in a marketing agency and a 30% increase in project visibility in a startup. These findings underscore the framework’s practical implementation as a holistic approach to managing time effectively and achieving long-term success. Continuous refinement, real- time feedback integration, and exploring the impact of emerging technologies are recommended for further enhancing the framework’s effectiveness. This research contributes valuable insights for organizations aiming to navigate the complexities of modern work environments.
Leadership Styles and Employee Engagement: A Management Perspective in the Service Industry Ming, Li Wei; Hernandez, Daniel; Kask, Rasmus; Sana, Eirene
APTISI Transactions on Management (ATM) Vol 8 No 2 (2024): ATM (APTISI Transactions on Management: May)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v8i2.2272

Abstract

This study delves into the relationship between leadership styles and employee engagement within the service sector. Employing a qualitative approach, the research involved in-depth interviews with 50 respondents from diverse service organizations. The findings underscore that transformational leadership, emphasizing inspiration and individual development, significantly impacts employee engagement. Transactional leadership, which centers on rewards and punishments, also influences engagement, albeit to a lesser degree. Conversely, laissez-faire leadership, characterized by minimal intervention and full autonomy for employees, exhibits the weakest impact. These findings emphasize the significance of deploying suitable leadership styles to bolster employee engagement and performance in service-oriented industries. The study offers practical insights for managers seeking to cultivate effective leadership strategies, thereby nurturing supportive and motivating work environments conducive to enhancing overall organizational performance. By comprehending the ramifications of different leadership approaches, managers can better steer their organizations toward success in industries reliant on human interaction. Thus, this research not only enriches the academic discourse on leadership and employee engagement but also furnishes pragmatic guidance for practitioners in the service industry to tailor leadership practices according to their organizational dynamics, fostering sustainable growth and success.
Analyzing the Influence of Artificial Intelligence on Digital Innovation: A SmartPLS Approach Harfizar; Wicaksono, Muhammad Wisnu; Hakim, Miftah Baidhowi; Wijaya, Fadly Hadi; Saleh, Taufikurrahman; Sana, Eirene
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 5 No 2 (2024): April
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v5i2.659

Abstract

This study investigates the influence of Artificial Intelligence (AI) on digital innovation using a SmartPLS approach, drawing insights from a dataset comprising 156 relevant observations. In the rapidly evolving digital landscape, AI has emerged as a powerful driver of innovation, reshaping organizational processes and outcomes across various sectors. Through a comprehensive analysis, the research explores the intricate relationships between AI adoption and digital innovation outcomes, addressing key questions regarding the extent to which AI influences process efficiency, product quality, and service creativity. The findings reveal significant correlations, highlighting the role of AI in enhancing organizational readiness, technological integration, and data quality. Moreover, the study identifies the critical importance of fostering an innovation culture and implementing effective change management strategies to leverage the full potential of AI-driven digital transformation. The robustness of the SmartPLS model is confirmed through substantial R-Square values and path coefficients, affirming the validity of the research hypotheses. Overall, this research contributes to a deeper understanding of the mechanisms through which AI influences digital innovation, offering actionable insights for businesses, policymakers, and researchers seeking to navigate and harness the potential of AI-driven digital transformation.
Analysis of User Perceptions on Interactive Learning Platforms Based on Artificial Intelligence Sana, Eirene; Fitriani, Anandha; Purwanti; Soetarno, Djoko; Yusuf, Maulana
CORISINTA Vol 1 No 1 (2024): February
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/corisinta.v1i1.12

Abstract

Education is one field that is increasingly adopting artificial intelligence (AI) technology in an effort to improve the learning experience. AI-based interactive learning platforms have become a significant trend in modern education. This research aims to analyze user perceptions of AI-based interactive learning platforms and identify factors that influence their acceptance of this technology. We conducted an analysis using the SmartPLS method to explore the relationship between variables that influence user perceptions of AI in education. Research data was collected through surveys given to educational participants using AI-based learning platforms. The results of this research include findings about the extent to which factors such as interaction quality, usability, and social factors influence user perceptions of AI-based learning platforms. The results of data analysis will provide valuable insight into how the educational community accepts and adopts AI technology in the learning process. It is hoped that this research will make a significant contribution to the understanding of the acceptance of AI technology in educational contexts, as well as provide guidance for the development of more effective interactive learning platforms. The findings of this research can also support decision making in implementing AI in educational settings.
Integrating Artificial Intelligence for Academically Challenged Students Education and Health Juliastuti, Dyah; Alexandrina, Elke; Sana, Eirene; Muti, Rifqa Nabila; Cesna, Galih Putra
International Transactions on Artificial Intelligence Vol. 4 No. 1 (2025): November
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v4i1.949

Abstract

Students with Intellectual and Developmental Disabilities (ID/DD) often experience overlapping medical and cognitive challenges that affect their academic participation and social interaction. Frequent absences, delayed progress, and limited communication skills highlight the urgent need for an integrated support system. Despite advancements in educational technology, most digital learning tools remain limited in addressing the dual educational and healthcare needs of ID/DD students. This study aims to identify existing gaps and propose a systematic framework for integrating Artificial Intelligence (AI) into education and health systems to enhance personalized learning and well-being for students with ID/DD. The study emphasizes the importance of combining health data with instructional design to achieve inclusive and adaptive learning experiences. A systematic literature review was conducted across multiple databases, including IEEE Xplore, ERIC, ACM Digital Library, and NFER, covering studies published between 2020 and 2025. The review process followed the PRISMA guideline and applied strict inclusion and exclusion criteria to ensure the validity of selected studies. The findings reveal that AI has been used to support ID/DD learners in various contexts, but most implementations remain fragmented, lacking integration between educational and medical data. The proposed AI-based framework connects these domains through data-driven decision-making, adaptive feedback, and intelligent reasoning mechanisms. This study contributes to the development of a holistic AI-driven model that supports individualized learning and health monitoring in line with SDG 3 (Good Health and Well-Being) and SDG 4 (Quality Education). Strengthening collaboration among educators, caregivers, and healthcare professionals can create more inclusive and effective educational ecosystems for ID/DD students.