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All Journal Technomedia Journal IAIC Transactions on Sustainable Digital Innovation (ITSDI)
Murphy Mutie
Eesp Incorporation
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology

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Leveraging Artificial Intelligence Technology to Drive Product Innovation in Digital Business Development Risma Haris; Sheila Aulia Anjani; Sherli Triandari; Mitra Trima Dessincer Putri; Murphy Mutie
Technomedia Journal Vol 11 No 1 (2026): June
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v11i1.2690

Abstract

The rapid advancement of Artificial Intelligence (AI) has transformed digital businesses by enabling continuous product innovation to sustain competitiveness. This study aims to analyze the role of AI in driving product innovation and supporting digital business development. A quantitative explanatory approach was employed using a survey research design. Primary data were collected from business practitioners and organizational decision-makers who have implemented digital technologies and analyzed using Structural Equation Modeling-Partial Least Squares (SEM-PLS). The findings indicate that AI significantly enhances product innovation through predictive analytics, machine learning, and intelligent automation, enabling organizations to better understand customer needs, accelerate product development, and improve service quality. Furthermore, AI contributes to greater operational efficiency, stronger competitive advantages, and the development of more adaptive business models. In conclusion, AI serves as a strategic enabler of product innovation and digital business competitiveness, emphasizing the importance of integrating AI into long-term innovation strategies and digital transformation initiatives to achieve sustainable business growth.
Debt Crowdfunding Growth and MSME Credit Risk in Indonesia’s Sustainable Digital Economy Rizki Galang Rahmadan; Thomas Sumarsan Goh; Murphy Mutie
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 8 No 1 (2026): October
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v8i1.746

Abstract

Micro, Small and Medium Enterprises (MSMEs) in Indonesia often lack the collateral that banks require, and Peer-to-Peer (P2P) lending, the debt form of crowdfunding, has become a channel through which they raise capital in the digital economy. Lending now grows fastest outside Java, where platforms hold the shortest records on their borrowers. This study builds a monthly panel of 34 provinces from official statistics of the Financial Services Authority (Otoritas Jasa Keuangan/OJK) for December 2023 to December 2024 and estimates two-way fixed-effects models with standard errors clustered by province. The models test whether faster growth of outstanding loans is followed by a higher share of loans more than 90 days overdue (Tingkat Wanprestasi 90 Hari / TWP90) and whether this link differs between Java and the other regions. Outstanding loans rose by 29.1% to Rp 77.02 trillion, by 20.5% in Java and by 57.8% elsewhere, and MSMEs held 36.7% of the stock at the end of 2024. Current growth shows no significant link with TWP90. Growth three months earlier is followed by a lower TWP90 in Java, with a coefficient of −0.084 (p < 0.01), while outside Java the coefficient is only −0.011 (p = 0.079), and the gap between the two regions is significant (p < 0.01). Rapid P2P expansion was not associated with higher TWP90 during the study period, while the observed negative relationship between earlier loan growth and TWP90 in Java was substantially weaker outside Java. Platforms and regulators therefore need closer credit assessment where lending grows fastest if debt crowdfunding is to support MSME capital formation and the targets of Sustainable Development Goals 8 and 9. The evidence is associational and covers thirteen months, so longer panels with data specific to MSMEs are needed.
Co-Authors Mitra Trima Dessincer Putri Risma Haris Rizki Galang Rahmadan Sheila Aulia Anjani Sherli Triandari Thomas Sumarsan Goh