Advancing research on the systematic development of innovations in sustainable Product–Service Systems (PSS) is crucial, as existing studies focus primarily on isolated product- or service-based innovation methods. This lack of a holistic view limits the potential to achieve sustainability goals and competitive advantage that well-developed PSS models offer. This study addresses these issues by investigating how systematic innovation methods and tools derived from the Theory of Inventive Problem Solving (TRIZ) can resolve technical and physical contradictions throughout the life cycle of sustainable PSSs. The study’s findings demonstrate the effectiveness of systematic innovation methods and tools in supporting the development of PSS models, offering insights and mechanisms for companies to create innovative and sustainable PSS offerings. We also unveil unexplored systematic innovation strategies for PSS and propose a method that integrates TRIZ across the PSS life cycle, guiding practitioners and scholars to drive systematic innovation and enhance value creation.

Circular supply chains (CSC) have been hindered by complex barriers. There remains a lack of structured, actionable guidance to help organisations prioritise and overcome these barriers. This study innovates by addressing this gap by applying the Theory of Constraints (TOC), specifically the Prerequisite Tree (PRT) tool, to systematically identify and organise the intermediate objectives needed to transition from traditional to CSC. Until now there was a lack of studies applying TOC in the CSC context. The PRT was validated through a Delphi study with experts from academia and industry, which is another innovation of the study. The roadmap consists of 26 interrelated objectives that reflect key organisational, technological, and stakeholder-related dimensions for CSC implementation. The findings offer theoretical contributions, by introducing a systems-based approach to CSC research also offering a new way to validate PRT, and practical implications, providing companies with a structured decision-making tool to guide their circular transition.

Despite growing scholarly interest in supply chain management (SCM) and ecosystems, a significant gap remains in understanding the mechanisms that underlie the evolution of a supply chain ecosystem (SCE). This study empirically investigates how SCEs emerge and advance from transactional supply chains. By adopting a longitudinal case study approach, this study develops a two-stage SCE evolution model that identifies two distinct stages – modular SCE and generative SCE – and delineates the transitions between them. This study reveals that the platformization of supply chain functions is the key to transitioning from a transactional supply chain to a modular SCE and that platformization across domains is the key to transitioning from a modular SCE to a generative SCE. This study contributes to the body of knowledge in SCM and ecosystem by offering a holistic view of SCE evolution, clarifying the characteristics and boundary conditions of each stage, and explicating specific actions of platformization in these transitions. This study also provides SCM practitioners with guidelines for advancing their supply networks by transitioning to SCEs and adopting platforms.

This study examines how Kaizen operational practices contribute to Environmental, Social, and Governance (ESG) performance in manufacturing and proposes an integrative conceptual explanation of this relationship. Moving beyond an efficiency-focused view, Kaizen is conceptualised as a socio-technical system in which routines, people engagement, and learning mechanisms generate sustainability-oriented outcomes. The findings show that Kaizen consistently enhances environmental performance through resource optimisation, waste reduction, and emission control, and strengthens governance via improved transparency, accountability, and participatory decision-making. Social outcomes, however, are more contingent and depend on organisational context and managerial intent. Digital technologies—such as IoT, Big Data Analytics, and Artificial Intelligence—and organisational culture emerge as key mediating mechanisms. Based on qualitative content analysis of semi-structured interviews with experienced Kaizen practitioners, the study proposes a conceptual mechanism linking Kaizen practices to ESG outcomes through the joint mediation of digital transformation and organisational culture, offering both theoretical and managerial contributions.

SMEs require digital and process improvement capabilities to address the organisational challenges associated with growth and performance. However, the two primary approaches to developing these capabilities, ERP and Lean, are challenging for SMEs to adopt. Therefore, this paper aims to investigate the underlying mechanisms by which ERP and Lean, as digitally supported approaches to process improvement, can facilitate SME competitiveness and growth. A longitudinal study of an integrated ERP–Lean intervention was completed over nine years using a design science research methodology and the CIMO framework. The research contributes to the theoretical understanding of SMEs’ adoption of digital and process improvement capabilities by identifying four organisational transformation mechanisms: discipline, understanding, engagement and enabling bureaucracy. The study provides evidence for the transformative potential of an integrated ERP–Lean method in digital process improvement, which can be deployed to achieve productivity increases, improve quality and foster company growth.

Artificial intelligence (AI) optimization capabilities are transforming healthcare supply chains (HSCs). However, the lack of clear guidance in academic literature on how to identify and adopt existing and emerging AI-based optimization techniques in HSCs is still an issue. This paper fills this gap by analysing 159 peer-reviewed articles published in the period from 2011 to 2025. The articles are coded to segment the research content into four structural categories: (1) the most prominent AI techniques in HSCs, (2) the possible AI techniques for HSCs, (3) the key success factors for AI implementation, and (4) the current scopes of AI-enhanced HSCs. The conceptual framework is developed on the basis of the results; these can guide the strategic implementation of AI-based optimization techniques to four key supply chain operations in the healthcare industry. The contributions and originality of this study are justified by synthesizing the studies on the use of AI in HSCs, by building a taxonomy of AI techniques in this application area, and by identifying the most important and, at the same time, least studied fields that require further research. The results and associated lessons learned aim to provide the academic community and practitioners with pragmatic guidelines to optimize HSCs using AI to enhance service delivery, decision-making, and overall operational efficiency.

This study advances the understanding of Lean Six Sigma 4.0 (LSS4.0) as a strategic framework for enhancing energy performance in industrial operations. A scoping review identified 29 barriers and 30 drivers, which were refined through focus group interviews into twelve critical barriers and seven key drivers. Empirical techniques, Fuzzy Delphi and Fuzzy DEMATEL, were applied to prioritize these factors and reveal their causal interrelations. Key results indicate that training and technical qualification influence at least five major barriers, including resistance to change and lack of standardization. At the same time, production cost reduction emerged as the most significant driver, overcoming capital investment constraints. These interdependencies informed the development of a research agenda, followed by a structured implementation roadmap aligned with the DMAIC cycle and tailored to varying levels of digital maturity. The roadmap incorporates operational and sustainability KPIs, such as cycle time reduction, energy consumption per unit, and carbon footprint, to guide continuous improvement under energy-efficiency goals. The study contributes both theoretically and practically by offering a replicable framework that supports the integration of LSS4.0 into diverse industrial contexts, bridging gaps in empirical evidence and providing actionable insights for organizations undergoing digital and sustainable transformation.

This article seeks answers to the question: how does geopolitical rivalry over strategically important industries impact the design of global supply chains? To answer this question, we examine how high technology firms responded to the United States (US) and Chinese government policies related to protecting national technological competitiveness. The study pays particular attention to how high technology firms moved sources of supply and production sites in response to protectionist government policies, and the new supply chain designs that emerged. The research question is examined through the lens of Resource Dependence, Resource Orchestration and Institutional Theory. A comparative case study design is used to contrast how high technology firms in the semiconductor and rare earth industries have responded to a technological rivalry between the US and China. Twenty-three interviews were conducted with senior managers and supply chain executives working at 13 semiconductors and eight rare earth metals companies, all of which had operations in the USA, China, or both. The comparative case analysis provides insights into the different actions that companies take to reconfigure their supply chains in response to geopolitical tensions. The study’s findings inform Geopolitical Resource Orchestration and Proactive Disruption Risk Mitigation frameworks, which outline potential mitigation measures that companies and policymakers can take to alleviate the impact of geopolitical tensions on global supply chains.

This study has a twofold purpose. First, it examines the paradoxical tensions fashion brands face when navigating overlapping environmental, social and economic issues. Second, it investigates whether, how and to what extent these brands manage such complexities. Using paradox theory, the research adopts an exploratory multiple case study approach, encompassing nine sneaker companies aiming to reduce virgin plastic use. The analysis identifies eleven tensions clustered into five categories: resource and product availability, process feasibility, product functionality, resource and product affordability, and product fashionability. The study then shows how these tensions can be reframed into operational responses, identifying fourteen actions that help mitigate paradoxical pressures linked to the urgent plastic challenge. This advances understanding in sustainable production and operations management and provides actionable insights for firms whose business models require addressing such grand challenges. While drawn from sneaker companies, these practices are transferable to other areas of the fashion industry.

As market trends shift towards mass customization, manufacturers face pressure to build flexibility. This often translates into more frequent changeovers, often viewed as non-value-adding. Yet existing research overlooks the broader impacts of changeovers and their potential business value. This research explores these impacts and how they can be managed to generate business value. Findings indicate that changeovers affecting manufacturing performance through product loss, resource use and downtime. In the process industry, cleaning operations can be a substantial cost factor, raising a single changeover’s cost to $3000. However, changeovers can also provide strategic advantages such as flexibility, which are crucial for market competitiveness. Therefore, the value of a changeover closely tied to how its impacts are managed. This research introduces a definition for changeover capability and proposes a novel changeover value map to help companies assess their position and identify key areas for improvement.