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All Journal Novatio : Journal of Management Technology and Innovation
Yuda, Fardan Zeda Achmadi
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Decision Sciences, Operations Research & Management

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Building Resilience in High Technology Projects: An Integrated Multi Framework Risk Management Approach Mubarok, Ahmad; Yuda, Fardan Zeda Achmadi
Novatio : Journal of Management Technology and Innovation Vol. 3 No. 2 (2025): April 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/novatio.v3i2.860

Abstract

High-technology projects face rapidly evolving risks across technical, organizational, and regulatory domains, creating challenges that single-framework governance often cannot fully address. This study proposes an integrated multi-framework risk management approach, combining governance-level (e.g., ISO 31000), domain-specific (e.g., ISO/IEC 27005, NIST SP 800-53, NIST AI RMF), and execution-level tools (e.g., SAFe ROAM, NASA NPR 8000.4C). Unlike prior studies that apply frameworks in isolation, this research evaluates a layered integration model designed to improve risk coverage, mitigation speed, and compliance readiness. Using framework mapping, Fuzzy Multi-Criteria Decision Making (MCDM), House of Risk (HOR) analysis, and Monte Carlo simulations, the findings show that integrated governance achieves broader protection, reduces closure times for high-velocity risks, and raises audit pass rates above 90%. The novelty of this study lies in offering a practical governance blueprint that reconciles overlapping standards while tailoring protections for AI, cloud computing, and mission-critical systems. Beyond technical improvements, the model aligns organizational risk appetite with operational practices, fostering resilience and agility.
Strategic Valuation of Generative AI in Retail: A Real Options Approach to Managing Innovation Uncertainty Yuda, Fardan Zeda Achmadi; Wibowo, Untung Lestari Nur
Novatio : Journal of Management Technology and Innovation Vol. 3 No. 2 (2025): April 2025
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/novatio.v3i2.861

Abstract

Generative Artificial Intelligence (AI) is reshaping retail investment strategies, yet traditional evaluation tools such as Net Present Value (NPV) and Internal Rate of Return (IRR) struggle to capture uncertainty and flexibility. This study applies a binomial lattice real options model to assess Generative AI investments in retail, demonstrating that real options provide a more adaptive framework than conventional methods. The model evaluates multi-stage decisions pilot testing, regional scaling, and enterprise adoption and incorporates sensitivity analyses to account for adoption probabilities and volatility scenarios. Results indicate that real options modeling captures strategic flexibility by valuing managerial discretion, phased rollouts, and intangible benefits, which static NPV models overlook. This highlights its relevance for addressing retail-specific challenges such as data integration and organizational readiness. The study concludes that real options offer a superior framework for evaluating AI investments, supporting adaptive planning and long-term strategic value for retailers.
Beyond Technology: Strategies for Managing Digital Transformation in Traditional Sectors Zulfikri, Agung; Prayitno, Hadi; Yuda, Fardan Zeda Achmadi
Novatio : Journal of Management Technology and Innovation Vol. 2 No. 1 (2024): January 2024
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/novatio.v2i1.998

Abstract

Digital transformation has become a defining force in reshaping traditional industries, yet its successful implementation requires navigating complex technological, organizational, economic, and regulatory challenges. This study presents a narrative review aimed at synthesizing existing literature on change management strategies in digital transformation across sectors such as manufacturing, healthcare, agriculture, and energy. Literature was collected through databases including Scopus, Web of Science, PubMed, and Google Scholar, using targeted keywords such as digital transformation, traditional industries, change management strategies, Industry 4.0, and sustainability. The review analyzed empirical studies, case studies, and theoretical contributions published between 2015 and 2025. Findings reveal that technologies like artificial intelligence, Internet of Things, blockchain, and digital twin systems enhance operational efficiency and sustainability but face barriers related to resource constraints, cultural resistance, and fragmented regulatory frameworks. Organizational factors, particularly leadership vision and employee skills development, emerge as central to overcoming resistance and enabling adoption. Economic disparities between large firms and SMEs remain a significant challenge, while supportive public policies and international regulatory harmonization play critical roles in facilitating progress. The discussion highlights systemic social, economic, and political influences on digital adoption and underscores the importance of continuous training, public-private partnerships, and adaptive policies as strategies to address persistent challenges. The study concludes that digital transformation is both a technological and socio-economic imperative, requiring coordinated strategies and context-sensitive approaches to achieve sustainable and inclusive outcomes.
Co-Authors Hadi Prayitno, Hadi Mubarok, Ahmad Wibowo, Untung Lestari Nur Zulfikri, Agung