A Study on the Optimization of Corporate Innovation Management Models in the Digital Age

Qilin Tan

GBP Proceedings Series, 2026, vol. 32, 74-82

Abstract: Technological advancements have been fully integrated into all spheres of innovation processes, and currently, the innovation management structure of organizations is transitioning from a conventional closed paradigm to an open collaborative model. However, the existing management paradigm reveals significant structural flaws that hinder effective adaptation to the rapidly evolving digital environment. These deficiencies manifest across four critical dimensions: the decision-making process, organizational responsiveness, process management, and outcome updating mechanisms. Specifically, information remains disconnected from the decision-making process, bureaucratic organizational structures impede timely market responsiveness, process management lacks appropriate digital tools and methodologies, and the mechanism for updating outcomes has become obsolete over an extended period. In order to systematically eliminate these bottlenecks, it is necessary to implement simultaneous and coordinated actions from four complementary perspectives: the decision-making system, organizational form, tool chain, and co-creation mechanism. Accordingly, this study proposes the development of a novel management model that integrates the principles of data-driven decision-making, platform-based collaboration, dynamic monitoring, and rapid iteration. By leveraging digital technologies and fostering cross-functional synergy, the proposed model aims to enhance organizational agility, improve innovation efficiency, and ensure sustainable competitive advantage in the digital age. This research provides both theoretical insights and practical guidance for enterprises seeking to optimize their innovation management frameworks amid ongoing digital transformation.

Keywords: digitalization; corporate innovation management; management models; organizational change (search for similar items in EconPapers)
Date: 2026
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