Engineer-to-order (ETO) and configure-to-order (CTO) companies reuse modules across product variants while continuously maturing them through concurrent engineering processes. In this setting, readiness for module release depends not only on the module’s own state but also on the readiness of every revision it requires. Because modules are shared across variants, a readiness contradiction in one dependency can block release across multiple products. Previous research has addressed variant governance, change propagation analysis, and effectivity-enabled product structures, but has paid little attention to engineer-facing, explainable checks that diagnose present-state readiness contradictions across the product structure. To address this gap, this paper proposes a Revision Coherence Checking method that (i) maps enterprise evidence — lifecycle state, change-task completion, approvals, and effectivity rules — into canonical readiness states via an auditable interpretation layer, and (ii) checks coherence constraints over a product-structure dependency graph to identify violations where a module revision is treated as more ready than a required dependency. The method is operationalized through an interactive graph-based prototype that localizes blockers, exposes propagation paths, and supports prioritization using reuse impact. A case study at a European custom laser manufacturer, covering 24 product lines and 183,265 dependency relationships, identified 532 direct readiness contradictions not surfaced by the company’s existing PLM system. The results demonstrate that the method can detect and characterize coherence violations, enabling earlier detection of release blockers, reduced rework from late discovery of readiness mismatches, and more targeted engineering coordination. Overall, the study frames readiness coherence as a computable, structure-level property of revision-aware product structures, rather than an attribute of individual revisions, thereby providing a basis for diagnostic readiness reasoning in reuse-intensive, PLM-enabled engineering environments.

This study examines the design, application, and reporting of action research (AR) in operations management (OM) to identify recurring methodological weaknesses and propose strategies to strengthen AR as a practice-oriented, theory-generating methodology. A systematic review of 142 empirical AR studies published in leading OM journals was conducted using a coding framework grounded in methodological literature, focusing on four AR design dimensions: AR cycle completeness, clarification of the unit of analysis, use of comparison logic, and use of triangulation. The review reveals recurrent methodological weaknesses: incomplete cycles, inadequate specification of the unit of analysis, limited application of comparison logic, and limited use of researcher triangulation. To address these weaknesses, the study proposes four improvement strategies: extended cycle tracking, unit stratification, multi-context comparison, and AR-case study integration. Together, these strategies configure a design space for enhancing the rigour, transparency, and contribution of AR.

Stockouts are a significant issue for direct-to-consumer product suppliers, as demand for these products is often challenging to predict. However, the literature offers only limited guidance for companies to tackle this problem. To address this gap, this paper develops a decision framework for assessing when fast-track production is a viable response to stockouts. The framework integrates context, symptoms, feasibility and business case viability to provide a structured process that links lost sales estimation, replenishment lead times and investment evaluation. A case study demonstrates the framework's practical application and its value for managerial decision-making in capacity investment and design. Building on this, a profitability threshold model is introduced to identify the production line capacity that maximises benefit by balancing recovered sales against investment costs. The study contributes to production research by advancing knowledge on lost sales estimation, decision-making under uncertainty and differentiated supply chain strategies. It further shows how responsiveness can complement efficiency-oriented practices.

Purpose: This study explores the barriers to adopting Industry 4.0 technologies within the pharmaceutical manufacturing sector. Despite the potential for transformative benefits, the sector has been slow in embracing these technologies due to unique regulatory and operational challenges. This paper seeks to understand these challenges in greater depth by analyzing key obstacles that pharmaceutical companies face during their digital transformation efforts. Design/methodology/approach: A mixed-methods approach was employed, combining maturity assessments with insights from in-depth interviews with key stakeholders in the pharmaceutical industry. The study identifies and categorizes the main barriers to Industry 4.0 adoption, providing a sector-specific analysis. Findings: The primary barriers to Industry 4.0 adoption in pharmaceutical manufacturing were found to be "prioritization and strategic alignment," "technological challenges," and "financial constraints." Contrary to common assumptions in the literature, "regulatory and compliance challenges" were perceived as less impactful by stakeholders, as these are often ingrained in routine operations. Research limitations/implications: The research focuses on a single pharmaceutical manufacturing company, which may limit generalizability. However, as the company operates within the broader pharmaceutical industry as a contract development and manufacturing organization (CDMO), the findings could reflect broader industry dynamics. Practical implications: Pharmaceutical companies should prioritize overcoming strategic and technological barriers to facilitate Industry 4.0 adoption. Clear leadership direction, strategic alignment, and addressing interoperability challenges are critical for successful digital transformation in the sector. Originality/value: This study provides a novel contribution by offering a detailed analysis of barriers to Industry 4.0 adoption specific to the pharmaceutical manufacturing sector. It challenges the traditional view of regulatory hurdles as the primary obstacle, emphasizing the increasing integration of regulatory management into daily operations and shifting the focus toward overcoming technological and strategic challenges.

Operations and Supply Chain Management (OSCM) has continually evolved, incorporating a broad array of strategies, frameworks, and technologies to address complex challenges across industries. This encyclopedic article provides a comprehensive overview of contemporary strategies, tools, methods, principles, and best practices that define the field's cutting-edge advancements. It also explores the diverse environments where OSCM principles have been effectively implemented. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners.

Manufacturers increasingly face demands to provide sustainability evidence related to their products. While many ETO (engineer to order) firms use product configurators to support product specification, these remain decoupled from LCA/EPD (lifecycle assessment /environmental product declaration) tool chains, making variant-level footprints impractical in high-variety production. In this context, previous research does not provide detailed approaches to support the development of product configurators capable of performing LCA calculations and generating EPDs. This study develops a configuration-native approach for computing ISO 14040/44-aligned LCA results and EN 15804-structured EPD outputs at configuration time. The approach operationalizes a modular product-production architecture that links selectable attributes (materials, modules, routings, logistics, operating profiles, and end-of-life treatments) to stage-specific inventory parameters and impact factors, enabling additive, traceable aggregation across EN 15804 lifecycle stages. A case study at a large industrial circulation pump manufacturer is conducted to evaluate the usefulness of the proposed approach, which includes benchmarking outputs against a third-party EPD and assessing design sensitivities and uncertainty using Monte Carlo propagation and paired statistical tests. Results show that the proposed approach supports the development of configurators that can generate high-quality variant-specific LCAs and EPD-ready documentation, which enables more scalable environmental assessments and promotes greener product design decisions. Overall, the approach shifts sustainability assessments from post hoc evaluations to a dynamic configurator-integrated assessment across abstraction levels.

Engineer-to-order (ETO) manufacturers face persistent cost and complexity challenges driven by product variety, including duplicate components, redundant variants, and inconsistent procurement setups. Although enterprise resource planning (ERP) and product lifecycle management (PLM) systems contain detailed Bills of Materials (BOMs) and procurement records, they typically lack portfolio-wide support for systematic cross-product commonality analysis without substantial manual effort. Structured approaches to design reuse and modularization in ETO contexts exist, but lightweight portfolio-level analytics tools operating on exported enterprise data remain scarce, and companies often still rely on ad hoc spreadsheet analyses. This paper introduces product commonality analysis tools (PCATs) and develops and evaluates one such tool in an action-research collaboration with a European ETO laser manufacturer. The PCAT operates on exported enterprise data to provide interactive portfolio-level views of component reuse and cross-product consistency. Usefulness is evaluated through scenario-based think-aloud usability sessions and a functional comparison against Excel workarounds, standard ERP/PLM reporting, and vendor customizations. The results indicate that a lightweight PCAT can integrate into existing ERP/PLM workflows with minimal disruption and reduce the effort required to prepare reusable portfolio views for engineering and procurement reviews.

Despite the widespread interest in Industry 4.0 technologies, only a few empirical studies focus on augmented reality (AR) coupled with digital twins (DTs). Thus, little is known about the usefulness and challenges of these in manufacturing contexts. To address this gap in the literature, the present study conducts an action research study of a DT-based AR project in a process manufacturing company. Specifically, first, two DT-based AR applications for training new operators and live data visualizations, respectively, are developed. These applications are tested by relevant employees, who are subsequently interviewed. Through analysis of interview transcripts, four overall uses of DT-based AR are identified: (1) training of new staff; (2) data visualization; (3) plant design validation; and (4) maintenance. Furthermore, several challenges related to the use of this technology are identified, which are organized under four themes: (1) safety issues; (2) cost issues; (3) convenience issues; and (4) accessibility issues. These findings are organized into a model illustrating the relationships between the uses and challenges of DT-based AR in process manufacturing.

Logistics service providers (LSPs) face fierce competition despite increasing demand for third-party logistics (3PL). LSPs must tackle increasing costs and complexity, labor shortages, and scarce warehouse space while meeting individual customers' needs. Studies suggest modularity could provide LSPs a competitive edge, but few methods for modeling logistics service modules exist. Although there are numerous product design approaches, these are seldom applied to services. This study applies insights from product design literature to develop a top-down approach for modeling and modularizing warehouse services. To test the proposed approach, three case studies across seven warehouses were conducted at a world-leading LSP. The study shows the approach can identify and define warehouse service modules using the warehouse service variant master (WSVM) technique, which clarifies the variety of warehouse services in three domains: client, service, and resource. The study also suggests LSPs can reduce complexity by offering warehouse services from standardized service modules.

Purpose Configurators support product and service specification processes by automating tasks, such as producing quotes, operation plans and bills of materials. However, misalignment between configurator objectives and development processes poses threats to the success of configurator projects. To address such problems, this research presents a coordinated approach to improve configurator development and reduce the likelihood of project failure, through the use of coordinated performance assessment. Design/methodology/approach The suggested approach was developed by organizing existing configurator performance measurement methods, which were identified through a literature review. A longitudinal, action research–based case study was conducted on a large energy company that operates offshore oil and gas platforms in Denmark. The case study evaluates the usefulness of the proposed approach through a maintenance work configurator developed in the case company. Findings The case shows that early-stage co-scoping of a configurator and its performance metrics can ensure the alignment of configurator objectives and performance measures and can secure the data required to achieve comprehensive performance measurements. These measures, in turn, support the continuous improvement of the configurator in its subsequent development cycles. The results of the empirical case study suggest that the approach produces considerable benefits in cost reduction and improved efficiency in configurator development. Originality/value Existing approaches to configurator development and implementation place little emphasis on the derivation and decision-support capability of performance measures. To address this, the proposed approach provides a structured, integrated method to continuously guide the development and implementation of configurator projects through performance assessment.

Whereas prior research suggests a positive relationship between information technology (IT) investment and firms' performance, the benefits of IT remain less clear in the small and medium-sized enterprise (SME) context and arguably depend on organizational focus and technology fit. Using literature on IT business value, task technology fit, and entrepreneurial orientation (EO), we develop a model of the "entrepreneurial orientation and technology fit." Survey (n = 400) results and registry data of young Danish SMEs provide strong support for our conceptualization. While IT intensity has a positive effect on performance in low EO SMEs, its relationship is negative when EO increases. The otherwise negative association between IT complexity and performance is mitigated by higher EO. Surprisingly, findings show that low EO firms with low IT intensity not only perform worse but also have a negative return on invested capital (ROIC). The ROIC of high EO firms with high IT intensity is near zero.

Background: Industry 4.0 (I4.0) has gained significant attention in recent years, with the term Logistics 4.0 (L4.0) emerging in the logistics industry. However, L4.0 remains vague and lacks a unified definition or classification of related technologies. Existing studies defining L4.0 are mainly conceptual and speculative, rather than grounded in empirical research. To address this gap, this study contributes to defining L4.0 through the sub-area of Warehouse 4.0 (W4.0), focusing on the challenges of adopting I4.0 technologies in warehouses. Methods: Through the I4.0 and L4.0 literature, an initial classification of W4.0 technologies in third-party logistics (3PL) was developed. This was refined using a case study of a global logistics service provider (LSP) in the 3PL industry, through semi-structured interviews with stakeholders. Results: The empirical findings identify new application areas for I4.0 technology in 3PL warehouses, including horizontal and vertical system integration, big data, and cybersecurity, technologies that can enhance 3PL competitiveness. Conclusions: This study offers a structured classification of W4.0 technologies and insights into the application areas of W4.0 in 3PLs. It contributes practical insights into which I4.0 technologies are relevant for the 3PL warehouse industry and their potential application areas.

Discrepancies between enterprise resource planning (ERP)-denoted production capacities and actual performance remain a persistent challenge in manufacturing, particularly for low-runner products and manual production lines. Despite ERP systems’ crucial role in production planning and control (PPC), in practice, the accuracy of their data is often challenged by dynamic shop-floor realities, infrequent updates, and limited feedback mechanisms. Previous studies have largely focused on theoretical models or simulations, while empirical studies on low-runner production and the systemic consequences of ERP inaccuracies across departments are sparse. This study examines two manufacturing case studies—pharmaceutical and chemical sectors—to quantify ERP inaccuracies, identify root causes, and develop a theoretical model illustrating how inefficiencies propagate across the value chain. The findings reveal that insufficient production data, human-dependent updates, and manual corrections create a self-reinforcing negative feedback loop that undermines planning accuracy, operational efficiency, and digital transformation initiatives. This cycle prompts departments to rely on non-ERP sources, further fragmenting data management and exacerbating resource misallocation, scheduling delays, and interdepartmental misalignments. Greater automation and larger batch sizes improve ERP alignment, while sporadic production and manual processes worsen discrepancies. The proposed model highlights the need for real-time feedback loops, predictive analytics, and IoT-enabled solutions to enhance ERP responsiveness, supporting the transition toward intelligent, adaptive PPC systems in Industry 4.0. Through these findings, the study enriches current knowledge of the systemic inefficiencies characterising traditional ERP system setups and demonstrates the value of dynamic PPC systems enabled by Industry 4.0 technologies.

Purpose The purpose of the paper is to investigate the impact of digitalized manufacturing (DM) on operational performance (OP) and the mediating role of supply chain resilience (SCRES) in this relationship. Design/methodology/approach The paper is based on 328 complete and useable responses to a questionnaire survey conducted from November 2022 to January 2023 among Danish manufacturers. Findings The paper reveals a positive association between companies’ adoption of DM and OP, with SCRES mediating this relationship. Additionally, the paper identifies a moderating positive effect of demand uncertainty on the DM-OP relationship, as well as a negative moderating effect of demand uncertainty on the mediating role of SCRES. Research limitations/implications The paper relies on responses from a single representative per company, exclusively from Danish respondents. Practical implications Companies and governments should invest in digital transitions and SCRES to enhance OP. Managers must ensure DM systems are flexible to adapt to demand fluctuations, leveraging technological capabilities for resilience. Policymakers should support flexible digital adoption while addressing supply-side challenges through resource security initiatives. Originality/value The paper is among the first to investigate the mediating role of SCRES on the relationship between DM and OP and how demand and supply uncertainty moderate the relationships.

This article presents a method (the cross-functional architecture matrix, CAM) for identifying the most business-critical architecture decisions for companies applying product architectures to support the design and production of customised and highly engineered products. Although the product architecture literature describes the value of product architectures and suggests concepts and methods for modelling product architectures, existing methods tend to focus on a select few parts of the value chain or a few functional disciplines despite engineer-to-order (ETO) companies being highly cross-functional. Furthermore, the literature suggests that the practical implementation of product architectures is hindered by the complexity of the architecture models and the large number of decisions involved in the implementation and maintenance of the architecture. In this article, we test the suggested method in a case of a company that designs manufacturing plants (usually an investment in excess of 200 M€) and where three major equipment systems were chosen. For each system, cross-functional architecture matrices were applied. In each case, we found that only five architecture decisions had to be made to achieve significant improvements in the system’s performance, including a 30% reduction in installation hours, 76% of commissioning activities moved from the site to workshop, a 6% faster time to production, and a 12% total cost reduction. Practitioners in ETO companies can use the CAM method to support their product architecture development, while researchers can utilise it for future studies on the implementation of product architectures across functional domains and value chains.

A significant part of traditional manufacturing companies' value propositions is provided through product-related services, such as transport, packaging, documentation, installation, and after-sales support. However, for many companies, it is challenging to manage such services. To address this issue, this paper investigates the usefulness of configurators in supporting this task. Specifically, product configurators are widely used in product development and sales processes in engineer-to-order (ETO) companies, where they have produced many benefits. To investigate the feasibility of product-related service configurators (PSCs) in manufacturing companies, this paper develops an approach to developing and implementing PSCs. The approach is tested in a case study to investigate its usefulness and the effects of applying PSCs. The study demonstrates the usefulness of the proposed approach and reveals three main types of benefits from PSCs: (1) increased product-related service cost transparency, (2) improved product-related service offerings based on customer characteristics, and (3) more standardised and structured product-related service specifications.

The theory of "dynamic capabilities" is often used to explain firms' transition towards greener production, typically under the name of "green dynamic capabilities" (GDCs). Such studies typically conceptualize GDCs as a single construct and, in rarer cases, as a group of noninteracting constructs. This study takes a different approach by conceptualizing GDCs as a set of constructs organized under three stages during which dynamic capabilities are applied (i.e., "sensing", "seizing", and "transforming"). The constructs "market orientation" (MO), "sustainability orientation" (SO), "technological orientation" (TO), and "green process innovation" (GPI) are used as proxies for GDCs to develop a model describing two distinct paths from MO to GPI. The model is investigated through a survey of Danish manufacturing firms (n = 337). The results confirm the hypotheses that SO and TO mediate the relationship between MO and GPI. Interestingly, there is no support for a direct relationship between MO and GPI, which implies that SO and TO fully mediate this relationship. Second, the results show that both mediation relationships are associated with competitive advantages in the form of increased product quality, whereas no support is found for effects on lead times and costs. Overall, the study adds to the understanding of GDCs by conceptualizing them as a set of constructs organized under three stages during which different GDCs are applied. This conceptualization offers future research a more nuanced operationalization of GDCs, which may lead to additional insights into their conditions and effects.