Investigating the interaction of factors for implementing additive manufacturing to build an antifragile supply chain: TISM-MICMAC approach

Purpose The purpose of this paper is to provide a systematic analysis about the effects of additive manufacturing (AM) technology adoption on supply chain management (SCM) processes and SCM components in an engineer-to-order environment. Design/methodology/approach Based on two explorative case studies from the hearing systems industry, the impact of AM technology adoption on SCM processes and SCM components is investigated. General systems theory and the contingency approach serve as theoretical underpinning. Findings Not only the internal processes and management activities, e.g. in manufacturing and order fulfillment, of producers are affected by a changeover to AM, but also the SCM processes and components relating to the supply and demand side of a firm’s supply chain. Endogenous and AM technology-related factors are contingency factors that help to explain differing effects of AM technology adoption on SCM processes and SCM components. Research limitations/implications It is proposed that AM’s ability to economically build custom products provides the potential to alleviate the common dilemma between product variety and scale economies. Practical implications Manufacturing firms are encouraged to consider the potential effects of AM on SCM processes and SCM components when deciding whether to adopt AM technologies in the production of industrial parts. Originality/value The research adds to the widely unexplored effects that AM technology usage in customized parts production has on SCM processes and components. Moreover, the general lack of case studies analyzing the implications of AM technology adoption from a supply chain perspective is addressed. The resulting propositions may serve as a starting point for further research on the impact of AM in engineer-to-order supply chains.

Given the proclaimed importance of additive manufacturing (AM) for generating agile supply chains, this study draws on the dynamic capabilities view to investigate the enhancing effects of adopting this digital technology on supply chain agility (SCA). To this end, relevant pieces of evidence are systematically gathered from a sample of 101 high-quality peer-reviewed journal articles at the intersection of AM technology and supply chain management.This information is then analyzed and synthesized to holistically map the features of AM technology adoption that enhance SCA. As a result, 42 features of AM technology adoption are identified that enhance thirteen different dimensions of SCA. The derived map explicitly indicates which features of AM technology adoption enhance which dimensions of SCA. Hence, this map can be used as a strategic tool by managers and policymakers who wish to explore different ways of enhancing SCA via AM technology adoption. This would, in turn, enable the adopting firm to deal with erratic business environments and dynamic supply chains in an agile manner, and therefore gain a competitive advantage. Moreover, based on the identified “white space” in the derived map, multiple questions are put forward that form a research agenda for future research.

As a digital technology, the adoption of additive manufacturing (AM), otherwise known as 3D printing, affects the state of the supply chain, consequently affecting supply chain resilience. To investigate the subject matter from the industry’s viewpoint, an exploratory survey was conducted to collect quantitative and qualitative empirical data from a heterogeneous sample of experts in various companies with hands-on experience in AM technology adoption. The quantitative data analysis indicates that adopting AM technology affects the supply chain’s state to a moderate extent overall, which in turn is likely to moderately affect supply chain resilience. The qualitative data analysis elucidates how different adoption features of AM technology affect the supply chain’s state and identifies the barriers inhibiting these effects. Generic propositions are put forward to reflect the theoretical implications of the study. Moreover, an empirical framework is conceived that outlines the managerial implications of the study. This framework can be used by practitioners and academics seeking to understand to what extent and how AM adoption affects the supply chain’s state, a fundamental prerequisite for assessing the supply chain resilience outcomes of adopting this digital technology.

In this competitive era when there are unforeseeable changes and high levels of environmental instability in the market, supply chains are more focused on implementing dynamic strategies to get a rapid response with minimal cost. The purpose of this study is to propose a conceptual framework to analyse driving factors for the leagile strategy and further to provides empirical evidences of effectiveness of lean and agile supply chain strategies on risk management in term of creating a robust and resilient supply chain. Data were collected from 140 supply chain professionals working in the manufacturing industry for hypotheses testing via structural equation modelling. The findings of this study reveal that market orientation as an external force has a greater impact on driving the agile strategy as compared to lean, while the Quality management system as an internal force is highly related to developing lean supply chain strategies. Furthermore, lean and agile strategies also have a significant impact on the robust supply chain and the resilient supply chain. The suggested model would help organisations to understand and create an ideal supply chain by implementing the right combination of both supply chain strategies which in turn helps to create a robust and resilient supply chain.

This article analyzes the adoption of additive manufacturing (AM) technologies in Sweden. The data set consists of a recent and representative sample of Swedish AM users (companies, universities, and research institutes). The authors investigate two questions. First, what are the current applications of AM in Sweden (e.g., rapid prototyping [RP], production)? Second, what are the factors that can explain the variation in AM adoption among the users? Using a regression analysis technique, the main findings are as follows. (i) There is a variation among users' choice of AM application, and the majority of users are expanding their AM applications beyond RP. (ii) There are two factors that positively affect the decision of firms to expand classical RP and incorporate production and management as well. These two factors are using multiple AM technologies (as opposed to single fused deposition modeling technology) being small companies. The authors discuss the implication of these results.

The Adoption of Additive Manufacturing Technology in Sweden

Building responsive and resilient supply chains: Lessons from the <scp>COVID</scp>‐19 disruption

PurposeThis paper investigates how the adoption of additive manufacturing (AM) impacts upstream supply chain (SC) design and considers the influence of drivers and barriers towards the adoption.Design/methodology/approachTen case studies investigating AM adoption by Original Equipment Manufacturers (OEMs) in five industries were conducted. This research is driven by a literature-based framework, and the results are discussed according to the theory of transaction cost economics (TCE).FindingsThe case studies reveal four patterns of AM adoption that affect upstream SC design (due to changes in supply base or types of buyer–supplier relationships): make, buy, make and buy and vertical integration. A make or buy decision is based on the level of experience with the technology, on the AM application (rapid manufacturing, prototyping or tooling) and on the need of control over production. Other barriers playing a role in the decision are the high initial investments and the lack of skills and knowledge.Originality/valueThis paper shows how different decisions regarding AM adoption result in different SC designs, with a specific focus on the upstream SC and changes in the supply base. This research is among the first to provide empirical evidence on the impact of AM adoption on upstream SCs and to identify drivers of the make or buy decision when adopting AM through the theoretical lens of TCE.

The use of Additive Manufacturing (AM) has become more widespread in recent years, covering different sectors. The increased interest in AM is due to the main benefits associated with its use, such as the possibility to produce even complex parts on demand and on the service site. These benefits have recently made researchers and practitioners hypothesize that AM can guarantee supply chain (SC) resilience, hence triggering their interest in AM as an emergency solution for SC disruptions. With the COVID-19 pandemic outbreak, this hypothesis has been confirmed to be true. In fact, AM has been shown to be very effective in guaranteeing the restoration and reconstruction of the SC, especially in the production of medical equipment (e.g., face masks, valves for respirators, etc.). However, to the best of the authors’ knowledge, the impact of AM on SC resilience has never been quantified before. Similarly, the potentialities of AM to guarantee the resilience of an SC outside of the medical sector have been barely treated (and never in a quantitative way). In this work, we aim to fill these two gaps. To do so, starting from the global supply chain of a company selling lighting equipment (available in the literature), we evaluated the potential of adopting AM as an emergency solution in guaranteeing SC resilience during the COVID-19 pandemic. Specifically, we considered 15 different scenarios where we considered the pandemic outbreak to be limited to the country of production as well as spread worldwide. From the results, the benefits of adopting AM, in terms of revenue, profit, service Level and lead time, were evident. Moreover, from the specific case considered we were also able to draw some general conclusions and suggest to SC managers when the use of AM would be beneficial.KeywordsAdditive manufacturingSupply chain resilienceCOVID-19

The emergence of additive manufacturing (AM) is expected to recon figure the traditional supply chain (SC) with more flexibility and agility, leading to opportunistic collaboration. The purpose of the work is to identify research dimensions based on AM-enabled supply chain management (SCM) taxonomy from the product, information and service flow point of view. This article uses a systematic literature review (SLR) on AM-enabled SCM. The literature from 116 peer-reviewed journal papers over 10 years (2010–2021) was comprehensively reviewed and assessed. The selected articles were characterized using (a) SC processes—upstream, manufacturing and downstream and (b) SC flows—goods and services, information and finance. This work provides a direction to scholars and academicians for identifying important SC implications of AM technology adoption. Practitioners can benefit by understanding several challenges involved in AM technology adoption and its implications on SC processes. This work adds new insights by identifying research dimensions based on AM-enabled SCM taxonomy.

The implications of additive manufacturing technology adoption for supply chain resilience: A systematic search and review

Black swan events such as the coronavirus (COVID-19) outbreak cause substantial supply chain disruption risks to modern companies. In today’s turbulent and complex business environment, supply chain resilience and robustness as two critical capabilities for firms to cope with disruptions have won substantial attention from both the academia and industry. Accordingly, this study intends to explore how digitalization helps build supply chain resilience and robustness. Adopting organizational information processing theory, it proposes the mediating effect of supply chain collaboration and the moderating effect of formal contracts. Using survey data of Chinese manufacturing firms, the study applied structural equation modelling to test the research model. Results show that digitalization has a direct effect on supply chain resilience, and supply chain collaboration can directly facilitate both resilience and robustness. Our study also indicates a complementary mediating effect of supply chain collaboration on the relationship between digitalization and supply chain resilience and an indirect-only mediation effect on the relationship between digitalization and supply chain robustness. Findings reveal the differential roles of digitalization as a technical factor and supply chain collaboration as an organizational factor in managing supply chain disruptions. Paradoxically, formal contracts enhance the relationship between digitalization and supply chain resilience but weaken the relationship between supply chain collaboration and supply chain resilience. The validation of moderating effects determines the boundary conditions of digitalization and supply chain collaboration and provides insights into governing supply chain partners’ behavior. Overall, this study enhances the understanding on how to build a resilient and robust supply chain.

Supply chain focuses on implementing dynamic strategies to get rapid response with minimal cost when there are unforeseeable changes and high level of environmental instability in the market. The purpose of this study is to provide empirical evidences of effectiveness of lean and agile supply chain strategies on risk management in term of creating robust and resilient supply chain. Moreover, this is the first study proposing a conceptual framework for the internal and external factors which drives the lean and agile strategies in manufacturing setups. Data were collected from 140 supply chain professional in the Pakistani manufacturing industry for hypotheses testing via structural equation modeling. The findings of this study reveals that as an external forces MO is more significantly related to agile strategy as compare to lean strategy, while as an internal force QM is also significantly related to both supply chain strategies. Furthermore lean and agile strategies are also having a direct impact on robust supply chain. While in terms of resilient supply chain, agile supply chain strategy is significantly related as compare to lean strategy.

PurposeThis study aims to analyse whether the presence of supply chain complexity (SCC) influences firms to improve their supply chain (SC) resilience and SC robustness capability. This study also examines an important paradox: whether investing in both exploitation and exploration practices is conflicting or complementary to enabling SC resilience and robustness in the presence of SCC.Design/methodology/approachThe authors used a survey-based approach to collect 242 useful responses from SC professionals of Pakistani firms, an important emerging economy context. The data were analysed with covariance-based structural equation modelling to statistically validate the model.FindingsThe analysis reveals several key findings: the presence of SCC has a direct, positive influence on SC resilience and SC robustness; while exploitation practices only partially mediate the nexus between SCC and SC resilience, they fully mediate the relationship between SCC and SC robustness; while exploration practices partially mediate the nexus between SCC and SC resilience, they do not mediate the relationship between SCC and SC robustness and SCC has a significant influence on SC resilience and SC robustness sequentially through exploitation and exploration (i.e. one after the other).Practical implicationsThese findings help to reconcile the exploitation versus exploration paradox in cultivating SC resilience and SC robustness in the presence of SCC. The findings assist SC managers in determining how to deploy their limited resources most effectively to enhance SC resilience and SC robustness while facing SCC.Originality/valueThe authors devise and empirically validate a unique framework that demonstrates how the presence of SCC works as a stimulus to build SC resilience and SC robustness.

PurposeThis systematic literature review analyzes the academic literature to understand SC risk and resilience across different organizational sizes and industries. The academic literature has well discussed the causes of supply chain (SC) risk events, the impact of SC disruptions, and associated plans for SC resilience. However, the literature remains fragmented on the role of two fundamental elements in achieving SC resilience: the firm's size and the firm's industry as firms' contingent factors. Therefore, it is important to investigate and highlight SC resilience differences by size and industry type to establish more resilient firms.Design/methodology/approachBuilding upon the contingent resource-based view of the firm, the authors posit that organizational factors such as size and industry sector have important roles in developing organizational resilience capabilities. This systematic literature review and analysis is based on the structural and systematic analysis of high-ranked peer-reviewed journal papers from January 2000 to June 2021 collected through three global scientific databases (i.e. ProQuest, ScienceDirect, and Google Scholar) using relevant keywords.FindingsThis systematic literature review of 230 high-quality articles shows that SC risk events can be categorized into demand, supply, organizational, operational, environmental, and network/control risk events. This study suggests that the SC resilience plans developed by startups, small and mdium-sized enterprises (SMEs), and large organizations are not necessarily the same as those of large enterprises. While collaboration and networking and risk management are the most crucial resilience capabilities for all firms, applying lean and quality management principles and utilizing information technology are more crucial for SMEs. For large firms, knowledge management and contingency planning are more important.Originality/valueThis study provides a comprehensive review of the literature on SC resilience plans across different organizational sizes and industries, offering new insights into the nature and dynamics of startups', SMEs', and large enterprises' SC resilience in different industries. The study highlights the need for further investigation of SC risk and resilience for startups, SMEs, and different industries on a more detailed level using empirical data. This study’s findings have important implications for researchers and practitioners and guide the development of effective SC resilience strategies for different types of firms.