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The study aims to examine a discrepant industrial case that demonstrates how to achieve economies of scale with additive manufacturing (AM), thereby expanding the scope of AM beyond high-variety, customised production contexts.

Abductive reasoning is applied to analyse a case of using AM to compete with conventional production, winning a contract to supply 7,700,000 products. Comparing this case to existing theories and contemporary practices reveals new research directions and practical insights.

Economies of scale were realised through a combination of technological innovation and the adoption of operations management practices atypical of AM shops (e.g. design for volume, low-cost resource deployment and material flow optimisation). The former improved AM process parameters in terms of time, cost and dependability; the latter improved the entire manufacturing system, including non-AM operations/resources. This system-wide improvement has been largely overlooked in the literature, where AM is typically viewed as a disruptive technology that simplifies manufacturing processes and shortens supply chains.

It is empirically shown that an AM shop can achieve economies of scale and compete with conventional manufacturing in high-volume, standardised production contexts.

This study aims to provide an overall framework that connects and explains a macro-perspective of the findings from the five studies of this special issue. Through this, we aim to answer two main questions: How can Lean and Industry 4.0 be integrated, and what are the outcomes for workers from such integration?

The special issue received 64 papers that were evaluated in multiple stages until this final sample of five papers that describe different facets of the integration between Lean and Industry 4.0 and their relationship with worker activities. In this introduction, we review the main findings of these five studies and propose an integrative view and associated propositions. A discussion provides directions to advance the field further.

The framework shows that when Lean and Industry 4.0 are integrated, companies will face two types of tensions, dialectical and paradoxical, which require different managerial approaches. By managing such tensions, the Lean-Industry 4.0 integration can help improve social performance, as well as develop systematic problem-solving and cumulative learning capabilities. Five important themes for this field of research are outlined: the importance of work routines, legitimation, competence, sense and mental flexibility.

This study brings a new theoretical perspective to the integration of Lean with Industry 4.0-related digital technologies. The results go beyond the usual view of improving operational performance and dig into the effects on workers. It also shows that the integration process relies on and can enhance human capabilities such as learning and problem-solving.

Lean remains popular in a wide range of private and public sectors and continues to attract a significant amount of research. However, most of this research is not grounded in theory. This paper presents and discusses different expert viewpoints on the role of theory in lean research and practice and provides guidelines for future research.

Seven experienced lean authors independently provide their views to the question “is Lean a theory?” before Rachna Shah summarizes the viewpoints and provides a holistic outlook for lean research.

Authors agree, disagree and sometimes agree to disagree. However, a close look reveals agreement on several key points. The paper concludes that Lean is not a theory but has plenty of theoretical underpinnings. Many lean-related theories provide promising opportunities for future research.

As researchers, we are asked to justify our research drawing on “theory,” but what does that mean for a practice-driven phenomenon such as lean? This paper provides answers and directions for future research.

This study focuses on (re-)introducing computer simulation as a part of the research paradigm. Simulation is a widely applied research method in supply chain and operations management. However, leading journals, such as the International Journal of Operations and Production Management, have often been reluctant to accept simulation studies. This study provides guidelines on how to conduct simulation research that advances theory, is relevant, and matters.

This study pooled the viewpoints of the editorial team of the International Journal of Operations and Production Management and authors of simulation studies. The authors debated their views and outlined why simulation is important and what a compelling simulation should look like.

There is an increasing importance of considering uncertainty, an increasing interest in dynamic phenomena, such as the transient response(s) to disruptions, and an increasing need to consider complementary outcomes, such as sustainability, which many researchers believe can be tackled by big data and modern analytical tools. But building, elaborating, and testing theory by purposeful experimentation is the strength of computer simulation. The authors therefore argue that simulation should play an important role in supply chain and operations management research, but for this, it also has to evolve away from simply generating and analyzing data. Four types of simulation research with much promise are outlined: empirical grounded simulation, simulation that establishes causality, simulation that supplements machine learning, artificial intelligence and analytics and simulation for sensitive environments.

This study identifies reasons why simulation is important for understanding and responding to today's business and societal challenges, it provides some guidance on how to design good simulation studies in this context and it links simulation to empirical research and theory going beyond multimethod studies.

The purpose of this paper is to further clarify the link between the theoretical and practical/real-life implications of a seminal topic in the strategic operations management field: Wickham Skinner’s strategic trade-offs model. This will help researchers, practitioners and students to realize the “everyday life” consequences of this highly influential model.

A theoretical analysis is made of previous research dealing with the strategic trade-offs model. Building on these investigations, a Popperian approach is used to logically develop the model, and the authors demonstrate how it can be empirically tested.

Previous investigations on Skinner’s model mainly focus on trade-offs between competitive capabilities (e.g. cost, quality, delivery) at the firm level. This paper demonstrates that the implications of this model necessarily should include consideration of the strategic trade-offs between the competitive characteristics of products/services that practitioners, students and the general public can observe.

While previous investigations have provided necessary clarifications, no paper has addressed the issue of the existence of strategic trade-offs between the competitive characteristics of products/services. This paper offers guidelines for researchers and practitioners on the way that the strategic trade-offs model can be conceptualized, understood and tested.

The objective of this research is twofold. First, we aim at identifying the pairwise relationships between Lean Production (LP) practices and Industry 4.0 (I4.0) technologies. Second, based on these results, we propose a framework for Lean Automation (LA) implementation, in which I4.0 technologies are integrated into LP practices.

To achieve that, a cross-sector survey was performed with 147 manufacturers that are undergoing a LP implementation aided by novel information and communication technologies from I4.0. Multivariate data analysis was applied in order to underpin the proposed framework for LA.

Findings indicate that I4.0 technologies are positively correlated with LP practices, providing evidence to bear the proposition of a LA framework that can potentially overcome traditional barriers and challenges of a LP implementation.

As previous studies have approached LA implementation from a narrow perspective or including a limited set of LP practices and I4.0 technologies, the proposition of an integrated framework unfolds a wider range of synergistic implementations that may corroborate to a holistic approach for continuous improvement in the Fourth Industrial Revolution era.

The purpose of this paper is to explore the adoption of lean practices by manufacturing companies in regions of low economic and technological development and to compare findings with previous studies from more developed regions highlighting important contextual differences. The paper uses the contingency theory to explore how contextual variables and scarce resources influence the adoption of lean practices.

A survey of 233 manufacturing firms was conducted in the State of Pará in the Amazon Region of Brazil.

The results demonstrate that six internal lean practices (single minute exchange of dies, human resource management, continuous flow, total productive maintenance, pull and statistical process control) and two external lean practices (supplier feedback and customer involvement) are implemented. However, the two external lean practices of just-in-time delivery by suppliers and supplier development were not implemented. Furthermore, from the 36 operating items comprised in eight lean practices that are being used, 13 were not implemented. As such, compared to developed regions, there is evidence for a more fragmented implementation in less developed regions. The results reveal empirical evidence explained by the contingency perspective, such as national, geographical, strategic context and culture.

There is broad evidence on lean implementation in developed and developing countries in the literature. However, little is known about lean implementation in poorer regions of developing counties. This is one of the first studies mapping lean implementation in a region with low economic and technological development. This has important implications for research and practice, especially to cross-country/cultural research on operation management.

Experiencing more frequent, system-wide disruptions, such as pandemics and geopolitical conflicts, supply chains can be largely destabilized by a lack of materials, services or components. Supply chain resilience (SCRES) constitutes the network ability to recover after and survive during such unexpected events. To enhance the understanding of SCRES as a system-wide quality, this study tests a comprehensive SCRES model with data from multiple industries.

The study proposes a theoretical framework conceptualizing SCRES as system quality, extending the classical proactive/reactive taxonomy by multiple system states consisting of the supply system properties, behaviors and responses to disruptions. Underlying hypotheses were tested using an online survey. The sample consists of 219 responses from German industries. Maximum likelihood structural equation modeling (ML-SEM) and moderation analysis were used for analyzing the survey data. The study was particularly designed to elaborate on supply chain theory.

Two pathways of parallel SCRES building were identified: proactive preparedness via anticipation and reactive responsiveness via agility. Both system responses are primarily built simultaneously rather than successively. The present study further provides empirical evidence on the central role of visibility and velocity in achieving comprehensive SCRES, while flexibility only exerts short-term support after a disruption. The study additionally points to potential “spillover effects” such as the vital role of proactive SCRES in achieving reactive responsiveness.

The present study confirms and expands existing theories on SCRES. While stressing the multidimensionality of SCRES, it theorizes the (inter-)temporal evolution of a system and offers practical guidelines for SCRES building in various industrial contexts. It thus supports the transformation toward more resilient and viable supply chains, contributing to the increasing efforts of middle-range theory building to achieve an overarching theory. The study also points to potential future research avenues.

Supply chains must rebuild for resilience to respond to challenges posed by systemwide disruptions. Unlike past disruptions that were narrow in impact and short-term in duration, the Covid pandemic presented a systemic disruption and revealed shortcomings in responses. This study outlines an approach to rebuilding supply chains for resilience, integrating innovation in areas critical to supply chain management.

The study is based on extensive debates among the authors and their peers. The authors focus on three areas deemed fundamental to supply chain resilience: (1) forecasting, the starting point of supply chain planning, (2) the practices of supply chain risk management and (3) product design, the starting point of supply chain design. The authors’ debated and pooled their viewpoints to outline key changes to these areas in response to systemwide disruptions, supported by a narrative literature review of the evolving research, to identify research opportunities.

All three areas have evolved in response to the changed perspective on supply chain risk instigated by the pandemic and resulting in systemwide disruptions. Forecasting, or prediction generally, is evolving from statistical and time-series methods to human-augmented forecasting supplemented with visual analytics. Risk management has transitioned from enterprise to supply chain risk management to tackling systemic risk. Finally, product design principles have evolved from design-for-manufacturability to design-for-adaptability. All three approaches must work together.

The authors outline the evolution in research directions for forecasting, risk management and product design and present innovative research opportunities for building supply chain resilience against systemwide disruptions.

The purpose of this paper is to reaffirm the suggestion that there are at least two distinct types of laws of trade-off that affect all firms and, in doing so, to contribute toward resolving the persistent trade-off debate in the literature.

Conceptual study using implicit deductive reasoning.

Two types of trade-offs are identified: “internal” can be understood following the dictates of the law of diminishing returns, while “external” can be modeled using the principle of energy conservation.

New insights are provided by discussing the impact of both laws of trade-off on the resource-based view of the firm, on new capabilities such as sustainability and innovativeness and on key strategic choices.

The study explains why trade-offs occur and outlines contextual factors that determine the “strength” of the trade-offs.

To the best of the authors’ knowledge, no previous study has attempted to investigate the topic of strategic trade-offs on the basis of the principle of energy conservation.