kerostig | Tag : intellectual property https://kerostig.org/tag/intellectual-property/ Derniers appels à publications avec le tag 'intellectual property'. Mon, 05 Oct 2026 10:15:16 GMT https://validator.w3.org/feed/docs/rss2.html https://github.com/jpmonette/feed fr kerostig | Tag : intellectual property https://kerostig.org/public/favicon/android-chrome-96x96.png https://kerostig.org/tag/intellectual-property/ Notices : kerostig © 2026. Le texte des appels appartient à leurs éditeurs. <![CDATA[Ownership Heterogeneity and Knowledge Transfer: Access, Appropriation, and Governance across Organizational Forms]]> https://kerostig.org/call/springer-ownership-heterogeneity-and-knowledge-transfer-access-appropriation-and-governance-across-organizational-forms/ springer-ownership-heterogeneity-and-knowledge-transfer-access-appropriation-and-governance-across-organizational-forms Sat, 26 Sep 2026 22:23:50 GMT

James J. Chrisman, Mississippi State University

Hanqing (Chevy) Fang, Missouri University of Science and Technology

Silvio Vismara, University of Bergamo

Zhenyu Wu, University of Manitoba

This special issue examines how knowledge and technology transfer operate differently across diverse organizational forms, moving beyond the assumption that transfer follows a single institutional model. The call brings together fragmented literature on intellectual property, open innovation, family businesses, and cooperative structures to develop an integrated framework for understanding ownership's role in shaping what knowledge is transferred, retained, or commercialized.

The framework organizes ownership forms along three dimensions: access (who obtains knowledge and on what terms), appropriation (who captures economic returns), and governance (who decides how knowledge is used and protected). These dimensions help explain why knowledge flows differently through universities, private firms, state-owned enterprises, cooperatives, and other organizational structures.

Appel publié par The Journal of Technology Transfer. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

  • Locating and transitioning ownership forms: how family firms, employee-owned firms, SOEs, cooperatives, and platform cooperatives differ in what they transfer and to whom, and how transfer changes as firms professionalize, corporatize, or adopt foundation governance.
  • Hybrid and intermediate arrangements: dual-class structures, stakeholder boards, patent pools, and benefit-corporation statutes, and when such hybrids are stable.
  • University and public research transfer: how technology transfer offices, consortia, and open science initiatives allocate rights, and how policy reforms shift those allocations.
  • AI, data, and platforms: how the three dimensions operate where the asset itself blurs conventional boundaries between use, capture, and control.
  • Rights-based theory, measurement, and policy: work that formalizes the framework, specifies trade-offs, or informs organizational and policy design.

Timeline

  • September 30, 2027: Full paper submission deadline
]]> <![CDATA[The Non-Human Innovator: Agentic AI, Physical AI, and the Transformation of R&D Management]]> https://kerostig.org/call/wiley-the-non-human-innovator-agentic-ai-physical-ai-and-the-transformation-of-randd-management/ wiley-the-non-human-innovator-agentic-ai-physical-ai-and-the-transformation-of-randd-management Sat, 29 Aug 2026 11:29:31 GMT

Joon Mo Ahn, Korea University

Alberto Di Minin, Scuola Superiore Sant'Anna

Sungjoo Lee, Seoul National University

Ahreum Hong, Kyung Hee University

This special issue addresses how artificial intelligence systems function as autonomous innovators rather than tools within R&D management. As AI systems including large language models and physical AI become active participants in innovation processes, existing frameworks assuming human actors must be reconceptualized. The core challenge extends beyond how AI assists humans to how much cognitive work should be delegated to AI and what consequences this has for organizations, ecosystems, and intellectual property.

The special issue examines four interconnected themes: determining optimal levels of AI delegation; understanding how agentic and physical AI reshape innovation ecosystem architectures as autonomous actors; reconceptualizing absorptive capacity for evaluating AI-generated knowledge; and addressing IP ownership and inventorship when non-human systems generate patentable outputs. Collectively, these themes interrogate how the distinction between AI-as-tool and AI-as-innovator requires new governance mechanisms and strategic frameworks for innovation management.

Appel publié par R and D Management. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

  • Is there an inverted-U relationship between the degree of AI delegation in R&D and innovation performance, mirroring the over-search paradox?
  • How do firms determine the optimal breadth and depth of AI involvement across different stages of the R&D process? Specifically, under what conditions does algorithmic management enhance or hinder innovation performance?
  • What is the AI-era analogue of the NIH syndrome: how does uncritical acceptance of AI-generated knowledge erode internal expertise?
  • What governance architectures enable effective human–AI teaming while preserving accountability, creativity, and strategic judgment?
  • How do agentic AI systems alter the architecture of knowledge flows in open innovation ecosystems, and what new governance mechanisms are required?
  • How does the participation of autonomous AI agents change the logic of platform-based open innovation, including roles, incentives, and boundary conditions?
  • How do digital twins and AI-enabled simulation reshape the scope and speed of distributed experimentation across organisational boundaries?
  • What new forms of inter-organisational trust, contracting, and coordination are needed when AI agents act as innovation partners?
  • How must absorptive capacity (or dynamic capabilities) be reconceptualised when the primary external knowledge source is an AI system rather than a human partner?
  • What organisational routines and managerial processes enable firms to transform AI-generated knowledge into innovation value?
  • What individual competencies — technical, cognitive, and relational — distinguish high-performing innovators in human–AI contexts?
  • What learning mechanisms allow firms to continuously upgrade AI-related innovation capabilities over time, particularly in relation to exploration and exploitation?
  • How should inventorship and IP ownership be attributed when agentic AI systems autonomously generate patentable outputs, and what theoretical frameworks from open innovation research best capture this challenge?
  • What strategic logic governs firms' decisions to release model weights, training data, or fine-tuned AI capabilities into open-source commons?
  • How do trained model weights, fine-tuning data, and emergent AI capabilities constitute a new category of strategic asset, and how do firms govern access to and monetisation of these assets?
  • Under what regulatory and institutional conditions does the open-source AI movement accelerate versus impede innovation diffusion?

Timeline

  • May 30, 2026: PDW (paper development workshop) at R&D Management Workshop, Seoul, Korea
  • July 4, 2026: PDW at KOSIME summer conference, Jeju, Korea
  • December 1, 2026: Special Issue Submission Open
  • June 30, 2027: Deadline for SI Submission
  • July 1, 2028: Publication of SI Articles
]]>