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Call for Papers

SPECIAL ISSUE: Decision-Oriented Analytical Modelling for Digital, Resilient and Sustainable Supply Chains in the Era of Industry 5.0

Introduction

In recent years, supply chains have become increasingly difficult to manage in any conventional sense. They are no longer stable, linear systems, but evolving networks shaped by data flows, disruptions, and shifting operational priorities. Under such conditions, decisions are rarely straightforward. Trade-offs between efficiency, resilience, and sustainability are not only unavoidable, but often poorly understood.

At the same time, the rapid diffusion of technologies associated with Industry 4.0—and more recently Industry 5.0—has added another layer of complexity. Tools such as artificial intelligence, digital twins, blockchain, and IoT systems promise better visibility and coordination, yet they also introduce new forms of uncertainty. In many cases, organisations have access to more data than before, but not necessarily better ways to use it when making decisions.

There is still a gap between how these methods are developed and how they are actually used in practice. A large part of the existing literature continues to focus on technologies or performance indicators in isolation. Much less attention is given to how different capabilities, system conditions, and external pressures come together when decisions need to be made in practice.

This Special Issue is intended to bring that aspect back into focus. The emphasis is not simply on modelling for its own sake, but on how analytical approaches are used when choices have to be made—whether at the level of system design, operational adjustment, or long-term planning.

Scope of the Special Issue

The issue is open to work that engages seriously with decision problems in supply chain settings. Submissions are expected to go beyond descriptive accounts or purely conceptual discussions.

Topics may include (but are not restricted to):

  • Decision models used in the design or reconfiguration of supply chain systems

  • Approaches that deal with conflicting objectives, especially where sustainability and resilience are involved

  • Simulation or optimisation work that reflects real decision constraints rather than idealised settings

  • Decision-support tools that make use of data, but also address uncertainty and imperfect information

  • Questions around technology adoption, particularly where the decision process itself is not straightforward

  • Ways of evaluating capabilities or system performance that actually inform subsequent actions

Work that shows how results can be interpreted and used in practice will be viewed more favourably than work that stops at the modelling stage.

Thematic Structure

Rather than treating topics as isolated domains, the Special Issue is organised around recurring decision contexts.

Theme 1: Capability-Based Decision Modelling under Industry 5.0

  • Modelling supply chain capabilities (agility, integration, visibility) as decision variables

  • Industry 5.0 technologies in supporting adaptive and human-centric decisions

  • Capability development and its role in strategic and operational decision-making

Theme 2: Resilience and Decision-Making under Uncertainty

  • Modelling disruption propagation and response decisions

  • Decision frameworks under uncertainty (stochastic, fuzzy, hybrid approaches)

  • Integration of resilience into decision-support systems

Theme 3: Sustainability and Multi-Objective Decision Analysis

  • Trade-off analysis between environmental, economic, and social objectives

  • Decision models for circular economy and green supply chains

  • Sustainability-driven performance evaluation and prioritisation

Theme 4: Digital Technologies and Decision-Support Systems

  • AI, blockchain, IoT, and digital twins in supporting supply chain decisions

  • Data-driven decision-making and real-time analytics

  • Digital platforms for coordination, transparency, and control

Proposed Timeline

Manuscript Submission Deadline: August 2026

Peer Review Completion: October 2026

Final Decision Notification: December 2026

Publication: Upon acceptance

Guest Editors

  • Dr. Sharfuddin Ahmed Khan

Industrial Systems Engineering, University of Regina, Canada

Email: Sharfuddin.Khan@uregina.ca

  • Dr. Syed Mehmood Hassan

Digital Engineering Management, Royal Holloway, University of London, UK

Email: Syed.Hasan@rhul.ac.uk

  • Dr. Golam Kabir

Industrial Systems Engineering, University of Regina, Canada

Department of Industrial and Systems Engineering, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia

Email: Sharfuddin.Khan@uregina.ca