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Aptisi Transactions on Management
Published by Pandawan Sejahtera Indonesia
ISSN : 26226812     EISSN : 26226804     DOI : 10.33050/atm
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Aptisi Transactions on Management (ATM) adalah jurnal ilmiah yang diterbitkan oleh APTISI (Asosiasi Perguruan Tinggi Swasta Indonesia), guna memfasilitasi hasil jurnal ilmiah Civitas Akademika dalam bidang teknologi informasi, komunikasi, dan manajemen dalam menghadapi era digital di Indonesia. ATM terbit tengah tahunan (2 kali dalam setahun, periode Januari dan Juli).
Arjuna Subject : -
Articles 219 Documents
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Advanced Predictive Models for the Startup Ecosystem Using Machine Learning Algorithms Febiansyah, Hidayat; Rahardja, Untung; Adiyarta, Krisna; Anderson, James; Kanivia, Aan
APTISI Transactions on Management (ATM) Vol 8 No 3 (2024): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v8i3.2345

Abstract

The startup ecosystem, characterized by its dynamism, presents significant challenges in predicting its future trajectory. Traditional analytical methods often fall short in comprehensively addressing the myriad factors that shape this ecosystem. This research aims to enhance the predictability of trends within the startup landscape by integrating the Technology Acceptance Model (TAM) with the advanced Random Forest algorithm. While existing literature has extensively explored the challenges startups face and the nuances of stakeholder interactions, the integration of TAM's constructs with key empirical attributes, specifically Investment Dynamics, Startup Metrics, Stakeholder Interactions, Entrepreneurial Challenges, and Technological Infrastructure, is a pioneering approach. Drawing from a comprehensive dataset that spans a diverse array of startups, this study operationalizes TAM's constructs in conjunction with the specified attributes. The subsequent application of the Random Forest algorithm offers a novel predictive methodology. Initial results highlight the superior predictive capabilities of this integrated model compared to traditional approaches. The findings provide insights into the intricate relationship between technological perceptions, as framed by TAM, and the tangible realities of the startup domain. The fusion of TAM with state-of-the-art machine learning signifies a groundbreaking direction in startup ecosystem research. This innovative approach offers stakeholders an enhanced analytical tool, ensuring more informed decision-making and a deeper grasp of the multifaceted nature of startup ecosystems.
Understanding Consumer Acceptance of AI in the Leisure Economy: A Structural Equation Modeling Approach Susilawati; Juliastuti, Dyah; Hardini, Marviola
APTISI Transactions on Management (ATM) Vol 8 No 3 (2024): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v8i3.2348

Abstract

This research examines the determinants of consumer acceptance of artificial intelligence (AI) in the leisure economy, using a structural equation model to analyze responses from 560 participants. The study focuses on several psychological factors: Perceived Ease of Use (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), Hedonic Motivation (HM), Perceived Value (PV), and Habit (HB), and their impact on Behavioral Intention (BI) to adopt AI technologies. Results indicate significant influence of six constructs (PE, FC, SI, PV, HM, HB) on BI, with the exception of one hypothesis. The research also assesses the role of Personal Innovativeness in enhancing the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model's predictive accuracy. This study contributes to understanding AI adoption in leisure, offering valuable insights for AI application development and marketing strategies in this sector.
Navigating the Challenges of Digital Transformation in Traditional Organization Maratis, Jerry; Ramadan, Ahmad; Rahmania Az Zahra, Achani; Ahsanitaqwim, Ridhuan; Bennet, Daniel
APTISI Transactions on Management (ATM) Vol 8 No 3 (2024): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v8i3.2349

Abstract

Digital transformation has become a critical strategy for traditional organiza- tions to maintain competitiveness in an increasingly technology-driven market. Technologies such as fintech, blockchain, artificial intelligence (AI), and cloud computing have significantly reshaped operational efficiency and customer en- gagement within these organizations. However, traditional organizations, characterized by their legacy systems and hierarchical structures, encounter various challenges in adopting these technologies. This study primarily aims to explore the key barriers that hinder digital transformation in traditional organizations and to propose effective strategies for overcoming these challenges. Utilizing a comprehensive literature review from 2018 to 2023, this research examines key studies on digital transformation in traditional business contexts. The find- ings reveal major challenges, including organizational inertia, skills gaps, de- pendency on outdated systems, and leadership deficiencies. To address these barriers, the study proposes strategies such as leadership development, work- force retraining, and investment in modern digital infrastructure. The results suggest that successful digital transformation requires a multifaceted approach, aligning technological adoption with organizational culture and sustainability goals. This research provides valuable insights for traditional organizations nav- igating the complexities of digital transformation.
The Future of Work: How Digital Tools are Transforming Human Resource Management Bist, Ankur Singh; Zakaria, Noor Azura; Anwar, Nizirwan; Ming, Li Wei; Jacqueline, Greisy
APTISI Transactions on Management (ATM) Vol 8 No 3 (2024): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v8i3.2355

Abstract

This study examines the transformative role of digital tools in reshaping key functions of Human Resource Management (HRM), including recruitment, training, performance management, and employee engagement. Employing a mixed-method approach, it integrates quantitative survey data with qualitative insights from HR professionals to assess the impact of digital technologies on HR functions. The results indicate a 35% improvement in recruitment effi ciency, enhanced employee development, and significant advances in perfor- mance management through the adoption of digital tools. Moreover, digital engagement platforms have reduced employee turnover, particularly in remote work environments. Despite these benefits, challenges such as resistance to change and digital skill gaps persist, requiring attention for successful imple- mentation. The study contributes to academic literature by addressing these challenges and offering practical guidance for organizations. Future research should explore the long-term effects of digital transformation and the role of emerging technologies like blockchain in further revolutionizing HRM prac- tices.
Addressing Regulatory Risks in Fintech through Decentralized Technologies Fahrudin, Rifqi; Dwi Yulian, Firdaus; Yadi Fauzi, Ahmad; Wilson, Ashley; Kuusk, Taavi
APTISI Transactions on Management (ATM) Vol 8 No 3 (2024): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v8i3.2356

Abstract

The fintech industry, characterized by rapid innovation and disruption of traditional financial services, faces significant regulatory challenges that can hinder its growth and sustainability. Managing these regulatory risks is crucial to ensuring compliance and maintaining trust within the industry. Decentralized technologies, particularly blockchain, have emerged as potential solutions for enhancing regulatory compliance through increased transparency, security, and automation. This study aims to analyze the role of decentralized technologies in addressing regulatory risks in the fintech sector. Utilizing the SmartPLS method for data analysis, the research examines the relationships between decentralized technology adoption, compliance automation, and regulatory risk mitigation. The findings reveal that decentralized technologies significantly reduce regulatory risks by automating compliance processes and enhancing transparency. These insights offer valuable implications for fintech companies and regulators, suggesting that the integration of decentralized technologies can be a strategic approach to managing regulatory challenges in the industry.
Responsible Environmental Management: Sustainable Strategy Models for the Future Lukita, Chandra; Wahyudin Anugrah, Rio; Aulia Anjani, Sheila; Fitriani, Anandha; Mkhize, Thabo
APTISI Transactions on Management (ATM) Vol 8 No 3 (2024): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v8i3.2358

Abstract

The aim of this study is to explore the relationship between responsible en- vironmental management and business performance, emphasizing sustainable strategy models that enhance both environmental sustainability and profitability in modern organizations. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS, data were collected from 150 medium to large organizations across multiple industries, including manufacturing, retail, and energy sectors, all of which have implemented formal environmental man- agement initiatives. The findings reveal a statistically significant positive impact of responsible environmental management on both environmental sustainability (β = 0.72, p < 0.01) and business performance (β = 0.65, p < 0.01). Addi- tionally, environmental sustainability was found to positively influence business performance (β = 0.54, p < 0.01). These results validate the relevance of models such as the Triple Bottom Line and Circular Economy, providing action- able insights for companies aiming to enhance competitiveness while achieving sustainability goals. This study highlights the practical implications for busi- ness leaders and policymakers, particularly in fostering sustainable practices that align with both regulatory demands and long-term profitability. Future research is recommended to explore the longitudinal impacts of these strategies across different sectors and regulatory environments.
Sustainable Management Strategies to Enhance Business Competitiveness in the Technology Sector Abudaqa, Anas; Geraldina, Ira; Rakhmansyah, Mohamad; Miftah, Mohammad; Dlamini, Sipho
APTISI Transactions on Management (ATM) Vol 8 No 3 (2024): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v8i3.2359

Abstract

The increasing global demand for sustainable business practices has placed significant pressure on organizations, particularly within the technology sector, to adopt strategies that balance environmental, social, and economic goals. This study investigates the role of sustainable management strategies in enhancing business competitiveness in the technology industry. The research employs a mixed-method approach, integrating quantitative data from key performance indicators (KPIs) such as market share, operational efficiency, and innovation outcomes, with qualitative insights gathered from in-depth interviews with senior executives. The results demonstrate that companies adopting sustainability practices experience a measurable improvement in operational efficiency (10%) and market share (15%), confirming that sustainability serves as a critical enabler of competitive advantage. Qualitative findings further reveal that sustainability initiatives bolster brand differentiation, customer loyalty, and regulatory compliance, contributing to long-term success. These strategies not only help firms navigate evolving regulatory landscapes but also enhance their positioning as leaders in innovation and social responsibility. This study concludes that sustainable management strategies are essential not just for compliance, but for fostering long-term business resilience and market leadership in the fast-paced technology sector.
Enhancing Organizational Resilience through Digital Innovation in Manufacturing Fanani, Fajriannoor; Maratis, Jerry; Saiful Hadi, Muhammad; Magdalena, Lena; Ramirez, Santiago
APTISI Transactions on Management (ATM) Vol 8 No 3 (2024): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v8i3.2362

Abstract

This study explores the role of digital innovation in strengthening organizational resilience within the manufacturing sector. By analyzing the integration of advanced technologies such as AI, IoT, and automation, the research investigates how these innovations improve operational flexibility, risk management, and adaptability to disruptions. A qualitative approach, including interviews with industry leaders, is employed to assess the impact. Findings demonstrate that digital innovation significantly enhances resilience, allowing manufacturers to respond efficiently to market volatility and operational challenges. The study concludes with recommendations for strategic implementation of digital tools.
Leveraging AI-Powered Automation for Enhanced Operational Efficiency in Small and Medium Enterprises (SMEs) Andayani, Dwi; Indiyati, Dian; Mayang Sari, Meri; Williams, Jack; Yao, Goh
APTISI Transactions on Management (ATM) Vol 8 No 3 (2024): ATM (APTISI Transactions on Management: September)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v8i3.2363

Abstract

This study explores the potential of AI-powered automation in enhancing opera- tional efficiency within Small and Medium Enterprises (SMEs). The primary objective is to identify how automation tools driven by artificial intelligence (AI) can streamline business processes, reduce operational costs, and improve productivity. The methodology includes a quantitative analysis of SMEs that have implemented AI-based solutions, supported by qualitative interviews with key stakeholders. The Results indicate significant improvements in operational workflows, particularly in areas such as supply chain management, customer service, and financial operations. The findings demonstrate that SMEs adopting AI technologies experience reduced human error, faster decision-making pro- cesses, and improved customer satisfaction. However, challenges such as initial investment costs and technical expertise remain. The study concludes that with proper implementation and strategic planning, AI-powered automation can be a key driver of success for SMEs in competitive markets.
The Role of Cognitive and Affective Post-Purchase Dissonance as Mediating Variables between Perceived Impulsiveness and Repurchase Intention Octavianus, Steven; Aprillia, Ariesya
APTISI Transactions on Management (ATM) Vol 9 No 1 (2025): ATM (APTISI Transactions on Management: January)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v9i1.2374

Abstract

The study investigates whether cognitive and affective post-purchase dissonance mediate the relationship between perceived impulsiveness and repurchase intention. Using purposive sampling, data were collected from 220 respondents, predominantly women with bachelor’s degrees. The study applied Partial Least Squares Structural Equation Modeling (PLS-SEM) for data analysis. The findings indicate that cognitive and affective post-purchase dissonance do not function as mediators in the relationship between perceived impulsiveness and repurchase intention. Practical implications of the study suggest that companies, especially e-commerce platforms, should focus on minimizing post-purchase dissonance to enhance customer satisfaction and retention. Strategies such as streamlined product return policies and responsive customer service can play a vital role in achieving this. These measures can help address consumer doubts and negative emotions following impulsive purchases, fostering greater trust and loyalty. This research contributes to the understanding of consumer behavior in online retail but highlights the need for further exploration using mixed methods to better capture the emotional nuances of post-purchase dissonance. Additionally, expanding the scope to include diverse products and demographics could enrich future findings.

Page 18 of 22 | Total Record : 219

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