CALL FOR PAPERS | SPECIAL ISSUE

2026-09-16

Regenerative and Intelligent Pathways toward the Twin Transition in Industrial Engineering and Operations Management:

Integrating Organizational Transformation and Technological Innovation in Practice

                                     SUBMISSION DEADLINE - 30 NOVEMBER 2026

 

Motivation and Rationale

Industrial engineering and operations management are being reshaped by a twin transition in which digital transformation and sustainability transformation increasingly unfold together. Artificial intelligence, advanced analytics, digital twins, cyber-physical systems, automation and Industry 4.0/5.0 technologies are changing how organizations design, plan and control operations. At the same time, decarbonization, circularity, regenerative practices, resilience, social responsibility and human-centricity are redefining what constitutes operational excellence.

This transition is not merely technological. It requires organizations to redesign processes, develop new capabilities, reconfigure decision rights, integrate people and digital technologies, and manage tensions among efficiency, resilience, sustainability, autonomy, quality and innovation. Although the literature on digital and sustainable transformation has grown rapidly, evidence is still fragmented regarding how these transformations are implemented in real operational settings, which organizational mechanisms enable them, and under what conditions they generate measurable operational, environmental and social outcomes.

The Brazilian Journal of Operations & Production Management (BJO&PM) emphasizes applied research in operations and production management. Accordingly, this Special Issue seeks studies that move beyond technology-centred or purely conceptual discussions and provide rigorous empirical and applied evidence on organizational transformation and technological innovation in practice. Particular interest is placed on research conducted in manufacturing, services, supply chains, public operations and other complex contexts, including emerging economies and resource-constrained environments.

The Special Issue is associated with the XXXIII IJCIEOM 2027, whose central theme is 'Regenerative and Intelligent Pathways toward the Twin Transition in Industrial Engineering and Operations Management'. Accepted papers in this Special Issue must be presented at IJCIEOM 2027 by at least one author.

Objectives of the Special Issue

  • Advance empirical understanding of how organizations implement the twin transition in industrial engineering and operations management.
  • Examine the organizational capabilities, governance mechanisms, work practices and decision processes that enable or constrain technological and sustainable transformation.
  • Assess the operational, environmental, social and resilience outcomes of Industry 4.0/5.0, artificial intelligence and other digital technologies in real settings.
  • Investigate trade-offs, tensions and complementarities among efficiency, resilience, sustainability, human-centricity, quality and innovation.
  • Develop and validate applied methods, decision-support approaches and managerial interventions that help organizations operationalize the twin transition.
  • Generate context-sensitive and transferable implications for managers, policymakers and practitioners, with attention to emerging economies and complex operational environments.

Expected Methodological Orientation

The Special Issue prioritizes empirical, applied and practice-oriented contributions. Manuscripts should clearly connect a relevant operational problem to a robust theoretical or conceptual basis and demonstrate how the chosen method produces credible evidence or actionable decision support. Purely conceptual manuscripts and standalone literature reviews are not the main focus of this call unless they are directly combined with empirical validation or a substantive applied research component.

Suitable methodological approaches include, but are not limited to:

  • Single or multiple case studies, including longitudinal, comparative and process-based case research;
  • Survey-based empirical studies using regression, structural equation modelling, multilevel models, configurational approaches or other appropriate statistical techniques;
  • Action research, design science research, living labs and intervention-based studies conducted with organizations;
  • Field experiments, natural experiments and quasi-experimental designs that support causal or comparative inference;
  • Mixed-methods research integrating quantitative and qualitative evidence;
  • Qualitative studies using interviews, observations, archival material and rigorous coding approaches to explain organizational processes and capability development;
  • Simulation, optimization, operations research, multi-criteria decision-making and performance measurement models validated with real data or real decision contexts;
  • Machine learning, artificial intelligence, digital twin and analytics applications evaluated on operational data and linked to managerial or operational outcomes;
  • Cross-country, cross-sector and multi-organizational studies examining contextual contingencies in the twin transition.

Topics of Interest

Topics include, but are not limited to, the following:

Organizational Transformation and Capabilities

  • Dynamic and operational capabilities for the twin transition;
  • Digital transformation, organizational redesign and business process reconfiguration;
  • Leadership, governance, culture, organizational learning and change management;
  • Technology adoption, implementation readiness and transformation maturity in operations.

Technological Innovation in Operations

  • Industry 4.0/5.0, artificial intelligence, generative AI, digital twins, IoT, robotics and cyber-physical systems;
  • Data-driven production planning, scheduling, quality management, maintenance and operational control;
  • Human-AI collaboration, augmented decision-making and intelligent decision-support systems;
  • Technology integration, interoperability and digital platforms in operations and supply chains.

Human-Centric and Responsible Operations

  • Human-centric production, workforce autonomy, skills, ergonomics and worker well-being;
  • Quality 5.0, human reliability and technology-enabled quality management;
  • Responsible AI, ethics, transparency and governance in operational decision-making;
  • Work design and organizational consequences of automation and intelligent technologies.

Sustainability, Circularity and Regeneration

  • Circular and regenerative production systems and supply chains;
  • Decarbonization, resource efficiency, energy transition and low-carbon operations;
  • ESG, sustainable performance measurement and responsible production and consumption;
  • Digital technologies as enablers of sustainability and circular economy practices.

Resilience and Complex Operational Environments

  • Operational and supply chain resilience, disruption management and recovery capabilities;
  • Risk, uncertainty, turbulence and adaptive operations;
  • Resilient and sustainable supply network design;
  • Twin-transition practices in SMEs, emerging economies and resource-constrained environments.

Applied Methods and Decision Support

  • Optimization, simulation and operations research for digital and sustainable transformation;
  • Multi-criteria and multi-objective decision-making for twin-transition trade-offs;
  • Predictive and prescriptive analytics, machine learning and data-driven decision support;
  • Performance measurement systems and empirical evaluation of transformation outcomes.

Submission and Review

Submissions should be written in English and comply with BJO&PM's standard submission categories and author guidelines. This Special Issue privileges Research Papers and Case Studies supported by clear scientific methodology, strong practical relevance and an original contribution to operations and production management. The main manuscript should be anonymized for blind review.

Journal portal: https://bjopm.org.br/bjopm

Authors should submit a separate title-page file containing the full name, e-mail address and institution of each author (institution names in English), together with author contributions according to the CRediT taxonomy. Authors should also identify the manuscript as intended for this Special Issue in the journal submission system.

Important Dates

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Accepted papers must be presented at IJCIEOM 2027 by at least one author. You may list up to 6 authors.

Guest Editors

  • Rodrigo Goyannes Gusmão Caiado — Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Brazil E-mail rodrigocaiado@tecgraf.puc-rio.br
  • Leonardo da Silva Ribeiro — Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Brazil; Brazilian Institute of CapitalMarkets (IBMEC), Brazil E-mail leonardoribeiro@esp.puc-rio.br
  • Cristina Gomes de Souza — Federal Center for Technological Education Celso Suckow da Fonseca (CEFET-RJ), Brazil. E-mail souza@cefet-rj.br
  • João Carlos Gonçalves dos Reis — Lusófona University, Portugal; NATO Joint Warfare Centre, Norway. E-mail reis.academic@gmail.com

Editorial Note for Accepted Papers

Suggested note for the first page of each accepted article: “This article is part of the Special Issue ‘Regenerative and Intelligent Pathways toward the Twin Transition in Industrial Engineering and Operations Management: Integrating Organizational Transformation and Technological Innovation in Practice’, associated with the XXXIII IJCIEOM 2027 – International Joint Conference on Industrial Engineering and Operations Management, held at PUC-Rio, Rio de Janeiro, Brazil, 14–16 June 2027. Guest Editors: Rodrigo Goyannes Gusmão Caiado, Leonardo da Silva Ribeiro, Cristina Gomes de Souza, and João Carlos Gonçalves dos Reis.”