Innovation Overview - Concepedia

Principles

Definition

Innovation is the academic concept and field of study concerned with the generation, development, and implementation of novel ideas, processes, products, or systems that yield value or effect significant change within a specific context. This field investigates the antecedents, characteristics, dynamics, and consequences associated with introducing and diffusing new forms, analyzing their impact on structures, practices, and outcomes across various domains.

Ontological type

Core Dimensions

Theoretical Foundations

Outcomes and Impact

Key developments

Key Figures

Systemic Learning Paradigm era

Bruce Kogut [1] is a prominent scholar affiliated with the University of Pennsylvania [2] and Boston University [3] during the late 20th century. His central contribution in this era is articulated in Knowledge of the Firm, Combinative Capabilities, and the Replication of Technology [4], a theory that shows how firms create value by integrating knowledge across boundaries through combinative capabilities to replicate technology, thereby clarifying how knowledge flows shape innovation trajectories. This work foregrounds the knowledge of the firm and its combinative capabilities [4] as engines of learning and replication, linking micro-level capabilities to macro-level systemic change. Together with the institutional settings of the era, Bruce Kogut [1]'s arguments helped explain how external knowledge flows contribute to sustained, path-dependent R&D trajectories.

Ecosystems and Triple Helix era

Thomas W. Valente [1] is a prominent scholar whose work in this era is associated with the University of California, San Francisco [2] and Johns Hopkins University [3]. In 2003 his paper Diffusion of innovations [4] advanced the diffusion of innovations framework by detailing how ideas travel through social networks, offering methodological tools and empirical insights that support cross-sector collaboration in ecosystem-centered innovation. Valente's diffusion-centric approach clarifies how network structure and social influence shape knowledge flows across sectors, a contribution foundational to open innovation practices and platform-enabled ecosystems of universities, industry, and government [1]. By emphasizing the roles of opinion leaders and lasting community ties, his work also informs longitudinal case studies and governance analyses that map knowledge exchange and scaling of novel capabilities across institutions in this era [1].

State-Facilitated Digital Platforms era

Daron Acemoğlu [1] is associated with Harvard University [3] and the Massachusetts Institute of Technology [4] in this era. His key contributions in this era include The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment [5], which analyzes how automation affects growth, factor shares, and employment and argues why these dynamics matter for state-led platform governance and investment strategies. Pascual Restrepo [2] is associated with Harvard University [3] and the Massachusetts Institute of Technology [4] in this era. Restrepo's contributions center on The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment [5], emphasizing automation's effects on labor demand and inequality and explaining why these dynamics matter for platformized innovation governance and public–private orchestration.