Data-Driven Innovation Models for Digital Ecosystem Development

Marcello M. Mariani

Data-Driven Innovation Models for Digital Ecosystem Development

Author(s)	Prof. Marcello M. Mariani
Country	Italy
Abstract	The rapid expansion of digital technologies has transformed traditional organizational structures into interconnected digital ecosystems in which organizations, customers, technology providers, platforms, public institutions, and other stakeholders continuously exchange data and digital services. Within these environments, data-driven innovation has emerged as a strategic mechanism for developing new products, services, processes, business models, and collaborative capabilities. This study examines data-driven innovation models for digital ecosystem development and proposes a conceptual framework connecting data generation, data integration, analytics, knowledge creation, collaborative innovation, digital platform development, and ecosystem performance. A conceptual and descriptive research design is adopted through a structured synthesis of secondary scholarly literature addressing data-driven innovation, digital platforms, business ecosystems, digital transformation, artificial intelligence, big data analytics, and organizational innovation. The analysis indicates that data-driven innovation can strengthen digital ecosystems by improving organizational responsiveness, enabling personalized services, facilitating collaborative product development, supporting predictive decision-making, and creating opportunities for new data-enabled business models. The findings demonstrate that data should not be considered merely an operational resource but as a strategic innovation asset capable of connecting multiple ecosystem participants and generating new forms of digital value. The proposed model emphasizes a continuous process in which data are generated and integrated across digital environments, transformed into knowledge through analytics, converted into innovative solutions, and evaluated through ecosystem-level performance indicators. The study concludes that effective data-driven innovation requires technological integration together with organizational readiness, collaborative governance, responsible data practices, and continuous innovation capabilities. Such an integrated approach can help organizations develop more adaptive, scalable, intelligent, and sustainable digital ecosystems.
Keywords	Data-Driven Innovation, Digital Ecosystems, Digital Transformation, Big Data Analytics, Digital Platforms, Artificial Intelligence, Innovation Models, Data Governance, Digital Business Models, Ecosystem Development
Field	Engineering
Published In	Volume 2, Issue 1, January-February 2020
Published On	2020-02-25

View / Download PDF File

About AIJARD Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+1-872-302-3851	editor@aijard.com

American International Journal of Advanced Research and Development

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

Data-Driven Innovation Models for Digital Ecosystem Development

Share this