American Journal of Advanced Multidisciplinary Research and Innovation

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A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Cross-Disciplinary Approaches to Innovation Management in the Digital Economy

Author(s) John E. Taylor
Country United States
Abstract The digital economy has fundamentally transformed the way organisations create value, develop products, deliver services, and compete in global markets. Rapid advances in Artificial Intelligence (AI), Big Data Analytics, Cloud Computing, Internet of Things (IoT), Blockchain, Digital Platforms, Industry 5.0, Machine Learning (ML), Digital Twins, and Generative Artificial Intelligence (GenAI) have accelerated innovation cycles and increased the need for agile, collaborative, and multidisciplinary innovation management strategies. Traditional innovation models, which often operate within functional or organisational boundaries, are no longer sufficient to address complex technological, economic, social, and environmental challenges. Consequently, cross-disciplinary approaches integrating engineering, management, information technology, economics, behavioural sciences, sustainability, and public policy have emerged as essential drivers of innovation in the digital era.
This study presents a comprehensive analysis of Cross-Disciplinary Approaches to Innovation Management in the Digital Economy. A qualitative analytical research methodology based on secondary data is employed to investigate digital innovation ecosystems, collaborative innovation frameworks, open innovation, digital entrepreneurship, knowledge management, and technology-enabled organisational transformation. The research evaluates how cross-disciplinary collaboration enhances organisational innovation capability, strategic decision-making, digital competitiveness, sustainability, and long-term business resilience.
The findings indicate that organisations adopting cross-disciplinary innovation management achieve higher levels of product innovation, process optimisation, digital transformation, customer engagement, operational efficiency, and knowledge sharing. Artificial Intelligence enhances strategic decision support, Machine Learning improves predictive business analytics, blockchain strengthens trust within innovation ecosystems, and cloud-based collaborative platforms facilitate global knowledge exchange. Furthermore, integrating sustainability principles into innovation strategies supports responsible digital transformation and contributes to achieving the United Nations Sustainable Development Goals (SDGs).
Despite these opportunities, significant challenges remain regarding organisational resistance to change, digital skills shortages, intellectual property management, cybersecurity, regulatory uncertainty, data governance, and interdisciplinary collaboration barriers. Future research should investigate explainable AI for innovation management, digital innovation governance, quantum-enhanced strategic analytics, federated knowledge ecosystems, and sustainable innovation measurement frameworks.
The study concludes that cross-disciplinary innovation management provides a transformative framework for organisations operating in the digital economy by fostering creativity, collaboration, technological advancement, organisational agility, and sustainable competitive advantage.
Keywords Innovation Management, Digital Economy, Cross-Disciplinary Research, Artificial Intelligence, Digital Transformation, Open Innovation, Knowledge Management, Industry 5.0, Digital Innovation, Sustainable Innovation.
Field Engineering
Published In Volume 2, Issue 3, May-June 2020
Published On 2020-06-15
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