“Forecasting and Managing Complex Innovation Systems: From Multi-Strand Technologies to Strategic Convergence”

all for Papers – Special Issue: “Forecasting and Managing Complex Innovation Systems: From Multi-Strand Technologies to Strategic Convergence”

Journal: Technological Forecasting and Social Change
Publisher: Elsevier
Submission deadline: 01 May 2026

Overview

This special issue introduces "convergence forecasting" to address the evolution of transformative innovations (e.g., generative AI, quantum computing, mRNA vaccines) that rely on complex, multi-strand technological systems. Rather than focusing on isolated technology trajectories, this issue seeks research that models the systemic alignment—scientific, economic, regulatory, and infrastructural—required for breakthrough innovations to coalesce and scale.

Key Research Themes

• Convergence Forecasting: Developing new frameworks and methods to identify "inflection points" where multiple enabling technologies and stakeholder needs reach systemic readiness.

• System Maturity & Timing: Modeling cost convergence and asynchronous timelines of interdependent technologies to improve investment and strategic planning.

• Innovation Ecosystems: Analyzing the role of platforms, complementary assets, alliances, and regulatory dynamics in bridging the gap between early research and market transformation.

• Methodological Innovation: Encouraging longitudinal quantitative modeling, roadmapping enhancements, scenario building, and the use of AI/data-driven approaches to track systemic interdependencies.

Submission Details

• Submission window: Open now – 01 May 2026.

• Submission portal: https://www2.cloud.editorialmanager.com/tfs/default2.aspx

• Special Instructions: Select article type “VSI: Complex Innovation Systems” during the submission process.

Guest Editors

• Tucker J. Marion, Northeastern University (t.marion@northeastern.edu)

• David Deeds, University of St. Thomas (david.deeds@stthomas.edu)

• John H. Friar, Northeastern University (j.friar@northeastern.edu)

Why This Issue Matters

Current innovation theory often centers on single-firm capabilities or modular technology paths, leaving a gap in understanding why systemic innovations frequently stall. By shifting the focus to "convergence," this issue provides a novel platform for scholars and practitioners to map the long-range dynamics of technological interdependence. It aims to equip policymakers, firm strategists, and forecasters with the tools necessary to manage the complexity of high-potential, slow-building innovation systems.

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