How to Create an Innovation Accelerator

Too many policy failures are fundamentally failures of knowledge. This has become particularly apparent during the recent financial and economic crisis, which is questioning the validity of mainstream scholarly paradigms. We propose to pursue a multi-disciplinary approach and to establish new institutional settings which remove or reduce obstacles impeding efficient knowledge creation. We provided suggestions on (i) how to modernize and improve the academic publication system, and (ii) how to support scientific coordination, communication, and co-creation in large-scale multi-disciplinary projects. Both constitute important elements of what we envision to be a novel ICT infrastructure called “Innovation Accelerator” or “Knowledge Accelerator”.

💡 Research Summary

The paper “How to Create an Innovation Accelerator” argues that many recent policy failures stem from systemic shortcomings in knowledge creation, a problem that became starkly visible during the recent financial and economic crises. The authors contend that fixing these failures requires more than disciplinary deepening; it demands a comprehensive redesign of the entire knowledge lifecycle—generation, dissemination, evaluation, and application—through a multidisciplinary approach and new institutional arrangements.

The first major proposal targets the academic publishing system, which the authors criticize for its pre‑publication, journal‑centric model that creates long delays, restricts access, and over‑relies on impact‑factor based metrics. They advocate a “fluid” publishing model that combines open‑access immediate release, post‑publication peer review, and a suite of multidimensional impact indicators (citations, downloads, social media mentions, data reuse, code adoption, etc.). This model aims to accelerate the diffusion of results while maintaining quality through continuous community scrutiny, and to reward researchers for a broader set of scholarly contributions.

The second, and central, contribution is the concept of an “Innovation Accelerator” – an ICT‑based platform designed to support large‑scale, multidisciplinary projects. The accelerator would provide (a) standardized repositories for data, code, and experimental protocols; (b) real‑time collaborative workspaces with version control and provenance tracking; (c) automated metadata generation and advanced search capabilities; and (d) a knowledge‑graph layer that maps researchers, institutions, and assets across domains. Leveraging AI‑driven matching algorithms, the system would suggest optimal collaboration partners, identify complementary expertise, and surface relevant resources. A contribution‑based incentive mechanism—potentially tokenized—would reward activities such as data sharing, code contribution, and peer review, thereby aligning individual motivations with collective progress.

Institutionally, the authors propose integrating the accelerator’s metrics into research evaluation and funding decisions. Instead of relying solely on journal impact, grant reviewers would consider data reuse rates, network centrality within the knowledge graph, openness of outputs, and collaborative breadth. Governance would be shared among academia, industry, and policy makers through a joint oversight committee, ensuring transparency, fairness, and adaptability.

The paper outlines expected benefits: faster knowledge circulation, enhanced capacity to tackle complex societal challenges through interdisciplinary teamwork, improved reproducibility and transparency, and a more efficient innovation ecosystem overall. It also acknowledges challenges such as upfront infrastructure costs, cultural resistance to open practices, and the need for robust standards that avoid rigidity. To mitigate these, the authors recommend pilot implementations, iterative feedback loops, and continuous refinement of both technical components and policy frameworks.

In sum, the authors present a compelling vision where a well‑designed ICT infrastructure—combined with reformed publishing practices and incentive structures—acts as an “Innovation Accelerator,” transforming the way knowledge is created, shared, and applied across disciplines. This paradigm shift promises to reduce the knowledge gaps that underlie many policy failures and to foster a more resilient, responsive scientific enterprise.