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This paper aims to explore the effect of subsidiary autonomy on knowledge transfers during captive offshoring to emerging markets.

Five longitudinal cases of captive R&D and manufacturing offshoring to emerging markets.

The propositions entail the dual effect of operational subsidiary autonomy on primary knowledge transfer and reverse knowledge transfer. For newly established subsidiaries, operational subsidiary autonomy has a mainly negative effect on primary knowledge transfer and a mainly positive effect on reverse knowledge transfer and local collaboration activities increase this effect. Strategic subsidiary autonomy is mainly negative for primary and reverse knowledge transfer.

Limitations concerning the applied exploratory case study approach suggest that further research should test the identified relationships using surveys, after the initial pilot study.

A gradual increase of operational subsidiary autonomy as the subsidiary capability level increases is beneficial to ensure primary knowledge transfer. Allowing subsidiaries to collaborate locally within the confines of their mandates benefits reverse knowledge transfer.

This paper extends the secondary knowledge transfer concept to include knowledge flows with local collaboration partners, not only other subsidiaries and clarifies the distinction between operational and strategic autonomy concerning local collaboration. A subsidiary asserts operational autonomy when its collaboration with local partners relates to its existing mandate. A subsidiary asserts strategic autonomy when it collaborates with local partners beyond this mandate.

Operations strategy/global operations/value chain.

BA/Master level – the case can be applied to support operations strategy discussions related to the link between context, configuration and capabilities, and particularly to discuss internationalization strategy and global operations.

The case examines how Gabriel, a Danish textile company, transformed itself from being a traditional textile manufacturer to becoming an innovative virtual servi-manufacturer. The case covers the main milestones in Gabriel's recent history, explores the main reasons for the transformation that started in the late 1990s and studies how this transformation towards becoming a virtual servi-manufacturer was dealt with. The case closes with the sections examining the role of innovation activities in the newly transformed company.

The case is expected to build an understanding of the organisational and operational implications of the journey towards the virtual production company. While the case is broad in its scope, it provides an opportunity to go into details on a number of interrelated topics: operations strategy; global production networks; communication and coordination; interdependencies; and outsourcing and offshoring. The story of Gabriel illustrates a highly successful globalization journey and its underlying dynamics. The case highlights how the operations configuration and the relationships between key parties do not stay constant over time. They rather shift and adapt to internal and external stimuli. The case explores these stimuli in retrospect and describes how the company attempts to reconcile market requirements with its operations configurations and capabilities.

Teaching note.

Operations strategy/global operations/value chain.

BA/Master level – The case can be applied to support operations strategy discussions related to the link between context, configuration, and capabilities, and particularly to discuss internationalization strategy and global operations.

The case is initiated with an overview of the wider corporate and industrial context, which are included to supply contextual information pertinent to the understanding of competitive requirements and strategic choices of the company. The case then moves into establishing an understanding of the operationalization of these requirements and choices through a discussion of the structural configuration and organizational capabilities.

The case it expected to build an understanding of the fit between competitive priorities and their operationalization within structural and infrastructural decision areas.

Teaching note.

The purpose of this paper is to determine how companies develop and acquire competences to capture the benefits of Industry 4.0 (I4.0) technologies. The authors argue that this is a fundamental and often overlooked prerequisite for industrial transformation.

The authors conduct a process study of 33 small- and medium-sized companies engaged in the transformation of a manufacturing industry from the different perspectives of manufacturers or manufacturing solution providers.

Key findings indicate a strong link between the specific competence development approach, the specific intricacies of the application domain and the process outcomes. On this basis, a competence development framework is proposed.

The conclusions are drawn from a Danish population of companies in the manufacturing industry and are based on particular contingencies, such as low volume/high mix, high skill, low tech and high cost. However, the findings are believed to be applicable across different sets of contingencies where the need to combine legacy and emerging technologies is present, and where the human factor is central to leveraging technology beyond predefined supplier specifications.

In a time of extraordinary investments in the manufacturing of technologies in support of digital transformation, the development of strategic and operational competences to support these investments is lagging behind. This paper develops a conceptual outset for closing this gap.

The research is based on the fundamental argument that to efficiently apply new technology, a strategic approach to the acquisition of new knowledge and skills is required. The empirical research demonstrates that new skills and knowledge are often assumed to follow automatically from the use of new technologies. However, we demonstrate that this perspective in fact limits the ability to capture the potential benefits ascribed to I4.0 technologies. The authors propose that the competence strategy needs to be expansive and cover not only the technological competences but also the organizational- and individual-level competences. These results add to our understanding of how the digital transformation of manufacturing companies unfolds.

This research proposes and demonstrates a framework that can be used to systematically address the idiosyncratic design of Internet of Things (IoT)-based solutions, and to match the explorative aspects of introducing a new technology to the exploitative needs, to improve the performance of production operations.

Due to the applied nature of this research, a design science research (DSR) framework was adopted in order to ensure both the rigor and applicability of the outcomes.

A process excellence perspective, operationalized through a business process management approach, is applied to scope the solution space according to its exploitative potential. The mapping of the information flow that needs to be established defines the technological infrastructure of the solution.

The theoretical generalizability of the proposed framework is limited by a testing sample of a single case. The research implications are related to a call for the contextualization of IoT applications. Further research will involve the application of this approach to a diverse range of industrial settings. While the domain is far from saturated, a framework that can facilitate such investigations has been provided.

The proposed framework provides practitioners with an approach to designing IoT solutions that can consistently address their needs for operational performance improvements.

This research proposes a framework that links the enabling of transparency via the integration of IoT in production operations to contextual characteristics and business potential. Furthermore, it highlights the developmental drivers of IoT solutions, which emerged during the empirical demonstration of this framework.

Significant transitions in firms (e.g. outsourcing) may impact the relative importance of production and inventory assets, affecting the hierarchical separation of planning decisions. The purpose of this paper is to contribute to planning literature by investigating how the production system and the planning environment influence the performance difference between hierarchical and monolithic planning. Further, it seeks to reduce the prevailing theory-practice gap in tactical planning.

Through an action research study, a monolithic model integrating tactical production planning decisions, subject to upstream supply chain constraints, with strategic investments decisions was developed, tested and implemented in a global OEM. Using the developed model and a measure of the capital cost of production assets relative to the cost of holding inventory, it is numerically examined how the production system and planning environment influence the performance of hierarchical and monolithic planning.

The research demonstrates the potential of integrating decisions and reveals significant performance differences between hierarchical and monolithic planning for firms with low capital cost relative to inventory holding cost.

The findings suggest a fit between planning processes, the production system and planning environment. Future research should empirically validate the findings and propositions.

The paper combine capital investments and production planning decisions, which usually transpire at different hierarchical levels and on different time-horizons, and investigates the consequences of hierarchical separation through a real-life validated case and numerical analysis.

This paper aims to investigate the impact of the strategic transformation of engineering to order company (ETO) at the level of the internal value-adding chain of operations on its position as a sub-supplier. The transformation is motivated and enabled by end-to-end business intelligence related to processes revolving around the product’s design, configuration and engineering. The investigation builds on case-based research following the company’s decision of converting its product portfolio to only one family of products, thus increasing process efficiency whilst at the same time enlarging its market reach by offering individualized and innovative products. By digitally integrating operations related to sales, product development and production preparation, the traditional trade-off between cost-effective solutions with high product variety and low lead-time is significantly reduced.

A design science research project has been conducted to create knowledge on the effects of integration across the value-adding chain of operations. Several design cycles illustrate how development based on business intelligence and available technological enablers for inter-operation integration influence the traditional approach towards supply chain pipeline selection strategies.

Relating to digital transformation, the consequences and means of adopting digital business intelligence for integrating several administrative and engineering operations in small-medium enterprises (SME) are studied. The product delivery performance of the SME is improved, thus, having ETO lead-time comparable to manufacturing to order company. The findings show how the adoption of state-of-the-art technological solutions for cross-operation digital integration challenges traditional supply chain, coordination models.

The conclusions are drawn based on a single case. The limitations associated with case-based research call for further work to support generalization. Furthermore, the long-term influence of the effects of increased interoperability on supply chain coordination strategies requires further investigation.

As technological solutions evolve, new opportunities for supply chain management arise, which put into question the traditional understanding that complex supply chain pipeline characteristics should be handled by complexity reducing initiatives, which opens up new competitive opportunities for companies in high-cost countries.

Enabling the use of human resources towards expanding the business (rather than running it only) are aligned with the current economic and political situation in high-cost countries like Denmark and potentially releases skilled employees from repetitive and low value-adding work and reengages them in business development.

By embracing flexibility and volatility as an opportunity, this publication exemplifies how to move beyond hedging the supply chain volatility, but systematically enable the supply chain to deal with complexity efficiently.

This paper investigates how manufacturers can develop a learning-to-learn capability for enabling Industry 4.0 adoption.

This research design is guided by our research question: How can manufacturers develop a learning-to-learn capability that enables Industry 4.0 adoption? The authors adopt action research to generate actionable knowledge from a two-year-long action learning intervention at the Danish rooftop window manufacturer VELUX.

Drawing on emergent insights from the action learning intervention, it was found that a learning-to-learn capability based on lean was a core construct and enabler for manufacturers to adopt Industry 4.0 successfully. Institutionalizing an organizational learning scaffold encompassing the intertwined learning processes of systems Alpha, Beta and Gamma served as a significant way to develop a learning-to-learn capability for Industry 4.0 adoption (systematic problem-solving abilities, leaders as learning facilitators, presence of a supportive learning environment and Industry 4.0 knowledge). Moreover, group coaching is a practical action learning intervention for invoking system Gamma and developing leaders to become learning facilitators – an essential leadership role during Industry 4.0 adoption.

The study contributes to theory and practice by adopting action research and action learning to explore learning-to-learn as a core construct for enabling Industry 4.0 adoption and providing a set of conditions for developing a learning-to-learn capability. Furthermore, the study reveals that leaders are required to act as learning facilitators instead of relying on learning about and implementing Industry 4.0 best practices for enabling adoption.

Many factors have been identified that may drive a firm’s decision to offshore production activities. The actual performance effects of offshoring, however, depend on the extent to which these drivers are realized. Furthermore, the question is how risk management helps mitigating the risk involved in offshoring ventures, thus leading to better performance outcomes. The purpose of this study is to investigate the extent to which realized offshoring drivers and risk management mediate the relationship between offshoring experience and firm performance.

Data from the Global Operations Networks project, a cross-sectional survey administered in Denmark and Sweden, are used to test two hypotheses on the mediating role of realized offshoring drivers and risk management in the relationship between offshoring experience and firm performance. AMOS version 23 is used to perform the analyses.

The results demonstrate that realized offshoring drivers fully mediate the relationship between offshoring experience and firm performance. However, risk management does not mediate the relationship between offshoring experience and firm performance.

This study develops new theory on, and managerial insight into, the mediating role of realized offshoring drivers and risk management in the relationship between offshoring experience and firm performance.

The purpose of this paper is to investigate how management attention and supply chain complexity affect the decision-making process and cost estimation accuracy of supply chain design (SCD) decisions.

The research follows an embedded case study design. Through the lens of the behavioural theory of the firm, the SCD decision process and realised outcomes are investigated through longitudinal data collection across ten embedded cases with varying degrees of supply chain decision-making complexity and management attention.

The findings suggest that as supply chain decision-making complexity increases, cost estimation accuracy decreases. The extent to which supply chain decision-making complexity is readily recognised influences the selection of strategies for information search and analysis and, thus, impacts resulting cost estimation errors. The paper further shows the importance of management attention for cost estimation accuracy, especially management attention based on conflicting goals induce behaviours that improve estimation ability.

A framework proposing a balance between supply chain decision-making complexity and management attention in SCD decisions is proposed. However, as an embedded case study the research would benefit from replication to externally validate results.

The method used in this study can identify how supply chain complexity is related to cost estimation errors and how management attention is associated with behaviours that improve cost estimation accuracy, indicating the importance of management attention in complex supply chain decision-making.