Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Aptisi Transactions on Management

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.
Risk Management Model for Compliance and Security in Blockchain Powered Payment Platforms Novalita Savitri, Agnes; Hardini, Marviola; Yao, Goh
APTISI Transactions on Management (ATM) Vol 9 No 2 (2025): ATM (APTISI Transactions on Management: May)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/atm.v9i2.2475

Abstract

Blockchain technology has revolutionized financial services by enabling decen- tralized, transparent, and tamper-resistant payment platforms. However, these innovations bring significant challenges related to regulatory compliance and security management, which threaten platform adoption and user trust. This study aims to develop and empirically validate a comprehensive risk management model that integrates both regulatory oversight and security auditing dimensions specific to blockchain-powered payment systems. A cross-sectional survey was conducted among 215 industry practitioners involved in blockchain payment platforms. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the study tested hypothesized relationships among regulatory over- sight, smart contract auditing, perceived compliance and security risks, risk mit- igation intent, and platform adoption intention. The results demonstrate that regulatory oversight and smart contract auditing significantly increase perceived compliance and security risks. These heightened risk perceptions positively in- fluence intentions to mitigate risks, which in turn significantly drive platform adoption. The model explains 58% and 42% of the variance in risk mitigation intent and platform adoption intention, respectively, confirming its strong ex- planatory power. This research contributes a validated, unified risk manage- ment framework that guides policymakers, platform operators, and auditors in addressing intertwined compliance and security risks. The findings support the advancement of safer, more trustworthy blockchain payment systems, fostering broader adoption and aligning with evolving regulatory landscapes.