“Digital Innovation Amid High Risk and High Uncertainty: How to Manage Unknowns”

CFP
Journal
online
SUBMISSION DEADLINE
31/05/2026
JOURNAL
Technology in Society
PUBLISHER
Elsevier
GUEST EDITORS
Ilaria Mancuso, Antonio Messeni Petruzzelli, Umberto Panniello, Kurt Matzler, Cristina Fernandes
POSTED ON
24/04/2026

DETAILS

Call for Papers – Special Issue: “Digital Innovation Amid High Risk and High Uncertainty: How to Manage Unknowns”

Journal: Technology in Society
Publisher: Elsevier
Impact Factor: 12.5 | CiteScore: 21.9
Submission deadline: 31 May 2026


Overview

This special issue explores how organizations manage digital innovation under conditions of high risk and high uncertainty, where “known unknowns” (risk) and “unknown unknowns” (uncertainty) coexist. It focuses on digital innovation—new products, services, processes, and business models enabled by digital technologies (e.g., AI, cloud, data analytics, platforms, ecosystems)—and how firms navigate volatility driven by pandemics, climate change, geopolitical instability, and rapid technological change.

The goal is to advance interdisciplinary theory and practice on how digital innovation can be governed, scaled, and leveraged without leading to “value missing” or “value slippage.”


Core Themes

1. The change in digital innovation

  • How digital technologies reshape organizations in VUCA (volatile, uncertain, complex, ambiguous) contexts (e.g., crises, climate shocks, geopolitical tensions).

  • Metrics and models for identifying and classifying change in complex digital environments (e.g., early‑warning indicators, scenario‑based analytics).

  • When digital technologies should be the subject (drivers of change) vs. the object (products to be optimized) of innovation efforts.

  • The role of managerial perception in framing situations as “risk” vs. “uncertainty” and how this influences innovation decisions.

2. Coping with digital change

  • Risk‑ vs. uncertainty‑aware strategies for managing digital transformation and innovation (e.g., experimentation, modularity, platform‑based design, portfolio approaches).

  • Reimagining digital business models (platforms, data‑based models, services‑as‑a‑service, ecosystems) to absorb shocks and capture emerging opportunities.

  • How platforms, ecosystems, and collaborations (with startups, incumbents, governments, academia) reduce risk and clarify uncertainty.

  • Dynamic capabilities and digital skills required to identify, integrate, and reconfigure resources under uncertainty (e.g., data‑driven decision‑making, AI literacy, design thinking).

  • Digital leadership and strategic agility: how digital‑literate leaders enable rapid pivoting, experimentation, and learning from failure.

  • Learning from failure: strategies to turn digital‑innovation failures into new opportunities via iterative learning, post‑mortems, and organizational redesign.

3. Broader impact of digital innovation

  • Moving from “risk/uncertainty management” (defensive, loss‑reduction) to “risk/uncertainty regulation” (proactive, value‑creation) in digital innovation.

  • Frameworks for assessing the full impact (economic, social, environmental, ethical) of digital change (e.g., impact‑weighted accounts, digital‑readiness indices).

  • How AI and big data analytics help detect and exploit opportunities within uncertain environments (e.g., predictive analytics, real‑time dashboards, scenario‑based simulations).

  • Balancing digital innovation with sustainability: aligning digital strategies with climate, equity, and long‑term resilience goals in high‑risk contexts.

4. Emerging theories and methods

  • New theoretical lenses to explain digital innovation effectiveness under risk and uncertainty (e.g., digital resilience, digital ambidexterity, ecosystem‑based views, digital‑risk theories).

  • Methodological approaches suited to extreme uncertainty:

    • Experimental/computational methods (e.g., simulations, ABM, RCTs in digital settings).

    • Case‑based and mixed‑methods designs that combine rich qualitative insights with quantitative causal analysis.

    • Big‑data and AI‑driven studies that incorporate counter‑factual reasoning and endogeneity control.

  • Identification of research gaps (e.g., micro‑foundations of digital risk perception, cross‑country comparisons, sector‑specific digital‑risk patterns).


Types of Contributions Welcome

  • Literature reviews and conceptual/theoretical papers that synthesize current knowledge on digital innovation under risk and uncertainty.

  • Empirical studies (qualitative, quantitative, mixed‑methods) across industries (public, private, non‑profit), regions, and organizational levels.

  • Action‑oriented research involving practitioners, platforms, and policy actors (e.g., design‑science, intervention‑based studies).


Guest Editors

  • Ilaria Mancuso (corresponding), Polytechnic University of Bari, Italy

  • Antonio Messeni Petruzzelli, Polytechnic University of Bari, Italy

  • Umberto Panniello, Polytechnic University of Bari, Italy

  • Kurt Matzler, University of Innsbruck, Austria

  • Cristina Fernandes, Faculty of Economics / CEFUP, University of Porto, Portugal


Submission Details

ServiceSetu Academics — Premier Platform for Academic Opportunities & Research Collaboration

Visit official website of the publisher

COMMENTS (0)

Sign in to join the conversation

SIGN IN TO COMMENT

Related Posts