Showing papers in "Journal of Manufacturing Technology Management in 2023"

Supply chain resilience and performance of manufacturing firms: role of supply chain disruption

Abstract: PurposeThe current study sought to investigate the moderating effect of supply chain disruptions (SCD) (supply chain – supply disruption, catastrophic disruption and infrastructure disruption) on the relationship between supply chain resilience (SCR) and supply chain performance (SCP) of manufacturing firms in Ghana.Design/methodology/approachThe quantitative research approach and explanatory research designs were utilised. A sample of 345 manufacturing firms were drawn from a population of 2,495 manufacturing firms in the Accra metropolis. The Partial Least Squares Structural Equation Modelling (PLS-SEM) was employed to accomplish the research objectives.FindingsFirst, the study revealed that SCR has a significant positive effect on SCP. Second, the authors found reasonable evidence to support that SCD have a significant positive moderating effect on the relationship between SCR and SCP, except for supply chain catastrophic disruption which had a negative impact. It can be concluded that the components of SCD have heterogeneous impact in the SCR and SCP nexus.Research limitations/implicationsThe study is limited to manufacturing firms in Ghana and does not make a distinction among resilience strategies.Practical implicationsIncreased SCR boost manufacturing companies' supply chains' performance and aid to lessen the adverse effects of SCD relating to infrastructure and supply. It implies that supply chain managers are able to reduce the effects of infrastructure and supply disruptions. Also, techniques that reduce the adverse impact of SCD relating to catastrophe would be beneficial for supply chain managers in Ghana and other countries with comparable economic environments.Originality/valueThe study provides a unique contribution on the moderating role of the dimensions of SCD (supply, infrastructure and catastrophic) on the nexus between SCR and SCP in a developing economy context in a dynamic changing environment. Policymakers would get better insights into instituting the required policies needed to revamp firms with weak supply chains as a result of supply chain disruption.

A deep attention based approach for predictive maintenance applications in IoT scenarios

Abstract: PurposeThe recent innovations of Industry 4.0 have made it possible to easily collect data related to a production environment. In this context, information about industrial equipment – gathered by proper sensors – can be profitably used for supporting predictive maintenance (PdM) through the application of data-driven analytics based on artificial intelligence (AI) techniques. Although deep learning (DL) approaches have proven to be a quite effective solutions to the problem, one of the open research challenges remains – the design of PdM methods that are computationally efficient, and most importantly, applicable in real-world internet of things (IoT) scenarios, where they are required to be executable directly on the limited devices’ hardware.Design/methodology/approachIn this paper, the authors propose a DL approach for PdM task, which is based on a particular and very efficient architecture. The major novelty behind the proposed framework is to leverage a multi-head attention (MHA) mechanism to obtain both high results in terms of remaining useful life (RUL) estimation and low memory model storage requirements, providing the basis for a possible implementation directly on the equipment hardware.FindingsThe achieved experimental results on the NASA dataset show how the authors’ approach outperforms in terms of effectiveness and efficiency the majority of the most diffused state-of-the-art techniques.Research limitations/implicationsA comparison of the spatial and temporal complexity with a typical long-short term memory (LSTM) model and the state-of-the-art approaches was also done on the NASA dataset. Despite the authors’ approach achieving similar effectiveness results with respect to other approaches, it has a significantly smaller number of parameters, a smaller storage volume and lower training time.Practical implicationsThe proposed approach aims to find a compromise between effectiveness and efficiency, which is crucial in the industrial domain in which it is important to maximize the link between performance attained and resources allocated. The overall accuracy performances are also on par with the finest methods described in the literature.Originality/valueThe proposed approach allows satisfying the requirements of modern embedded AI applications (reliability, low power consumption, etc.), finding a compromise between efficiency and effectiveness.

Drivers of green supply chain integration and green product innovation: a motivation-opportunity-ability framework and a dynamic capabilities perspective

Abstract: PurposeThis study provides an integrative model that facilitates green product innovation (GPI) by adopting dynamic capabilities theory and the motivation-opportunity-ability (MOA) framework. Drawing on dynamic capabilities theory, this study emphasizes green supply chain integration (GSCI), consisting of internal and external integration, as a dynamic capability that drives GPI. Moreover, this study analyzes the environmental conditions that benefit the development of dynamic capabilities using the MOA framework and focuses specifically on government support (GS) and market greenness (MG) as precursors to GSCI.Design/methodology/approachSurvey data were collected from 300 Chinese manufacturing firms. The proposed hypotheses were tested using hierarchical multiple regression analysis.FindingsThe regression analysis reveals that (1) GS and MG positively affect both internal and external integration and (2) internal and external integration positively affect GPI.Originality/valueIn explicating a model of GPI, this study extends the theoretical lens of dynamic capabilities beyond the intraorganizational level to the supply chain level. Moreover, this study enhances the understanding of dynamic capability development by considering the environmental conditions that represent motivation- and opportunity-based drivers of GSCI.

Blockchain technology and circular economy in the environment of total productive maintenance: a natural resource-based view perspective

Abstract: PurposeTotal Productive Maintenance (TPM) could act as a practical approach to offer sustainability deliverables in manufacturing firms aligning with the natural resource-based view (NRBV) theory's strategic capabilities: pollution prevention, product stewardship and sustainable development. Also, the emergence of Blockchain Technology (BCT) and Circular Economy (CE) are proven to deliver sustainable outcomes in the past literature. Therefore, the present research examines the relationship between BCT and CE and TPM's direct and mediation effect through the lens of NRBV theory.Design/methodology/approachThe current study proposes a conceptual framework to examine the relationship between BCT, CE and TPM and validates the framework through the Partial Least Squares Structural Equation Modeling. Responses from 316 Indian manufacturing firms were collected to conduct the analysis.FindingsThe investigation outcomes indicate that BCT positively influences CE and TPM and that TPM has a significant positive impact on CE under the premises of NRBV theory. The results also suggest that TPM partially mediates the relationship between BCT and CE.Research limitations/implicationsThis research fills a gap in the literature by investigating the effect of BCT and TPM on CE within the framework of the NRBV theory. It explores the link between BCT, TPM and CE under the NRBV theory's strategic capabilities and TPM mediation.Practical implicationsThe positive influence of TPM and BCT on CE could initiate the amalgamation of BCT-TPM, improving the longevity of production equipment and products and speeding up the implementation of CE practices.Originality/valueThis research fills a gap in the literature by investigating the effect of BCT and TPM on CE within the framework of the NRBV theory. It explores the link between BCT, TPM and CE under the NRBV theory's strategic capabilities along with TPM mediation.

The mechanism of knowledge management process toward minimizing technical risks under green implementation network: a direct and configurational approach

Abstract: PurposeThe knowledge management (KM) sharing process plays an essential role in manufacturing under Green Implementation Network (GIN). This study aims to analyze the KM process of adopting a GIN to determine the relative importance of technical risk minimization. The proposed conceptual model was tested by considering two interrelated concepts (GIN and KM process).Design/methodology/approachPrimary data from manufacturing companies in Henan province, China, were collected through 276 questionnaires. PLS-SEM and fuzzy set qualitative comparative analysis (fsQCA) were applied to investigate the configurational path of minimizing the technical risk in the manufacturing process.FindingsThe findings showed that the GIN and KM processes minimize the technical risk. The fsQCA reported multiple configurational of GIN and KM processes validated toward technical risk reduction. The study's findings contribute to the existing body of knowledge on technical risk reduction in manufacturing concerns by investigating the complex intersection between GIN and KM process.Originality/valueThis research adds to current GIN and KM literature by focusing on the green process using a resource-based view (RBV) and socio-technical theories. The current study provides practical and theoretical justification for explaining the relationship between GIN and KM processes. Moreover, this study adds to the literature by providing evidence that KM is an essential manufacturing industry enabler in minimizing technical risk.

Does technological innovation matter in the nexus between supply chain resilience and performance of manufacturing firms in a developing economy?

Abstract: PurposeDespite the economic growth in Ghana, the manufacturing industry faces numerous challenges in their supply chains. The study aims to investigate the mediated-moderated role of supply chain technological innovation (SCTI) in the relationship between supply chain resilience (SCR) and supply chain performance (SCP) of manufacturing firms. By exploring this relationship, the study seeks to provide insights that can help manufacturing firms overcome the challenges they face and improve their overall supply chain performance.Design/methodology/approachThe quantitative research approach and explanatory research design were utilised. A sample of 345 manufacturing firms was drawn from a population of 2495 manufacturing firms in the Accra metropolis. Analysis of this study was performed using the Partial Least Squares Structural Equation Modelling (PLS-SEM).FindingsIt was revealed that SCTI positively mediates the nexus between SCR and SCP. However, we document that SCTI negatively moderates the nexus. It is instructive to advocate that a mere presence of a more enhanced SCTI is not enough to improve upon SCP of manufacturing firms, but should be a channel through which SCR can improve SCP.Practical implicationsThis study highlights the need for managers of firms to prioritise investment in technological innovation as a means of enhancing SCR and ultimately improving supply chain performance. By understanding the SCTI mediated-moderated relationship between SCR and SCP, supply chain managers, logistics managers, operation managers, as well as procurement managers can develop more effective strategies to optimise their operations. This study provides valuable insights for managers and policymakers in developing and implementing supply chain resilience strategies that take into account the important role of SCTI.Originality/valueThe originality of the study lies in exploring the mediated-moderated effect of technological innovation on the nexus between resilience and performance of supply chains in developing economies, where firms often face unique challenges such as infrastructure limitations, political instability and economic uncertainty. By investigating the interplay of SCTI between SCR and SCP, researchers can develop new insights and strategies to help navigate these challenges and achieve success.

Early adopters of Manufacturing-as-a-Service (MaaS): state-of-the-art and deployment models

Abstract: PurposeCloud Manufacturing (CM) is the manufacturing version of Cloud Computing and aims to increase flexibility in the provision of manufacturing services. On-demand manufacturing services can be requested by users to the cloud and this enables the concept of Manufacturing-as-a-Service (MaaS). Given the considerable number of prototypes and proofs of concept addressed in literature, this work seeks real CM platforms to study them from a business perspective, in order to discover what MaaS concretely means today and how these platforms are operating.Design/methodology/approachSince the number of real applications of this paradigm is very limited (if the authors exclude prototypes), the research approach is qualitative. The paper presents a multiple-case analysis of 6 different platforms operating in the manufacturing field today. It is based on empirical data and inductively researches differences among them (e.g. stakeholders, operational flows, capabilities offered and scalability level).FindingsMaaS has come true in some contexts, and today it is following two different deployment models: open or closed to the provider side. The open architecture is inspired by a truly open platform which allows any company to be part of the pool of service providers, while the closed architecture is limited to a single service provider of the manufacturing services, as it happens in most cloud computing services.Originality/valueThe research shoots a picture of what MaaS offers today in term of capabilities, what are the deployment models and finally suggests a framework to assess different levels of development of MaaS platforms.

Augmented reality for industrial services provision: the factors influencing a successful adoption in manufacturing companies

Abstract: PurposeThis paper presents a model aiming to identify the factors influencing the adoption of augmented reality (AR) for industrial services.Design/methodology/approachThe study combines a literature analysis with an empirical study conducted exploring how five large industrial companies are introducing AR for supporting the provision of technical assistance and industrial services to their installed base.FindingsThe authors identify four categories (task, workforce, context and technology) that combine 18 factors that manufacturing companies should consider when introducing AR technology to support industrial services.Originality/valueThis paper systematises the fragmented literature on technology adoption and in particular those works related to the factors affecting the adoption of AR in industrial services. Based on literature and empirical evidence, the authors propose a novel framework that can help companies in the selection of AR solution based on their specific applications and situations. This study therefore contributes also to the existing literature on the adoption of I4.0 and digital technologies in industrial services.

Enabling supply chain efficacy through supply chain absorptive capacity and ambidexterity: empirical study from Middle East region - a moderated-mediation model

Abstract: PurposeThis study tries to examine how supply chain (SC) absorptive capacity (AC), SC ambidexterity, SC risk mitigation and supply chain agility (SCA) affect SC efficacy (SCE) in manufacturing firms (MFs) in the Middle East region.Design/methodology/approachUsing a quantitative approach through a survey-based study, 1,004 questionnaires were distributed to the MFs that are listed in the chambers of the industries of Jordan, Egypt, Saudi Arabia and Bahrain in the Middle East region, with 239 useable and valid responses retrieved for analysis, representing a 23.8% response rate. The main respondents were chief executive managers, operations managers, managers and logistics managers from both mid and top levels. The conceptual model was tested by using a hypothesis-testing deductive approach. The findings are based on covariance-based analysis and structural equation modeling (SEM) using partial least squares-SEM (PLS-SEM) software.FindingsThis study illustrates a significant relationship between SC AC, SC ambidexterity, SC risk mitigation and SCA on SCE. Further, the findings indicate that there is a significant effect of SC risk mitigation as a mediating factor in the relationship between SC AC, and SC ambidexterity on SCE directly and indirectly, as well through a moderating effect of SCA in these relations. Finally, there is a significant direct and indirect effect of SCA in the relationship between SC AC and SC ambidexterity on SCE as a moderating factor.Originality/valueThis study presents theoretical and empirical insights that both SC risk mitigation and SCA are proper logistics features for mediating and moderating extends the literature by adding a positive role of SC AC and SC ambidextrousness in mitigating SC risks. However, this study adds up the SC literature by evidencing moderating role of SCA between the absorptive capacities, ambidexterity on SCE. Such findings of this study can provide insightful implications for managers and practitioners at different levels in and efficacy among MFs (MFs, stakeholders and policymakers regarding the importance of using the three mentioned enablers on SCE) in MFs, particularly in the Middle Eastern firms and in developing countries in general East region.

Circular supply chain practices and corporate sustainability performance: do ethical supply chain leadership and environmental orientation make a difference?

Abstract: PurposeThis study draws insight from the leader-member exchange theory to examine the link between supply chain ethical leadership and circular supply chain practices. This study further draws on the contingent theory to explore the interactive effect of environmental orientation and circular supply chain practices on corporate sustainability performance.Design/methodology/approachThis study uses a quantitative research approach where partial least square structural equation modelling (SMART PLS) is used to analyse survey data gathered from 122 managers of small and medium enterprises in Ghana.FindingsThis study reports that there is a significant positive relationship between ethical supply chain leadership and circular supply chain practices. The findings further reveal that internal environmental orientation and external environmental orientation moderate the relationship between circular supply chain practices and corporate sustainability performance.Originality/valueThis study sheds light on ethical supply chain leadership's influence on circular supply chain practices. The study also offers an empirical argument to explain contradictory relationships between circular supply chain practices and corporate sustainability performance by applying the contingency roles of internal and external environmental orientation.

Technology, lean, quality and human resource practices in manufacturing: how does size as a contingency factor matter?

Abstract: PurposeTaking its outset in operations management (OM) contingency research, this paper aims to investigate how firm size, as one of the most powerful explanatory factors, influences the implementation and performance impact of four key manufacturing practices.Design/methodology/approachThree large-scale surveys from three different points in time, with a total of 1880 observations from varied geographical regions, are used to offer generalizable evidence on how firm size influences the implementation and performance outcome of technology, lean, quality and human resource practices.FindingsThe four manufacturing practices positively enhance performance: quality and lean practices produce the most consistent effects, while technology and human resource practices turn more beneficial in the latest sample. Furthermore, the authors offer robust support for the selection and mediation models (larger firms generally invest more in the four practices and, through that, achieve higher performance), while finding no evidence for the moderation model (smaller firms can equally benefit if they possess the resources to invest in these practices).Originality/valueAs manufacturing practices are continuously evolving, their performance impact cannot be guaranteed in any context. Size is a frequently used contingency variable in OM studies, but results are contradictory in terms of its impact on the implementation and performance outcomes of manufacturing practices. This study manages to ease these contradictions.

The performance effects of supply chain agility with sensing and responding as formative capabilities

Abstract: PurposeThe study presents a conceptual model of a firm's supply chain agility (FSCA) as a formative construct formed by sensing and responding capabilities. Both construct validity and predictive validity of the model are tested by investigating nuanced effects of FSCA on business performance. The study aims to empirically validate the sensing-responding theoretical framework of Overby et al. (2006) and extend the emergent stream on sensing-responding frameworks for supply chain agility.Design/methodology/approachSurvey research is employed. Data are analysed using partial least squares technique and mediation tests by Hayes PROCESS macro.FindingsFSCA is established as a revised construct formed by the distinct capabilities of sensing and responding. The efficacy of utilizing FSCA as a formative 2nd order construct was established. In addition, FSCA is shown to affect business performance through mediations of cost efficiency and customer effectiveness, establishing its predictive validity.Originality/valueThis study contributes significantly to the literature on supply chain agility in terms of both theory and practice for cultivating supply chain agility. Drawing on resource-based view and resource-advantage theories, as reformulation of supply chain agility as a formative construct of sensing and responding capabilities, this research opens up new lines of inquiry on agility.

Robotising, but how? Evidence from the automotive sector in South Africa

Abstract: PurposeThis paper focuses on understanding firm-level determinants of industrial robots' adoption and how these determinants result in heterogenous processes of robotisation across firms within the same sector. The paper presents results from in-depth case studies of final assemblers in the South African automotive sector.Design/methodology/approachThe research has been conducted through multiple case studies with a focus on final assemblers. During the case studies, as well as before and after it, data coming from in-depth semi-structured interviews were triangulated with secondary data available from the international database on industrial robots' adoption and documents provided by firms and institutions.FindingsThis paper identifies three firm-level determinants of robotisation – i.e. modularity of the production process, flexibility in the use of technology and stability in product design. The results also showed that firms' robotisation depend on each of these determinants as well as their interdependence. The authors introduce a framework to study interdependence between these technology–organisational choices, which reveals heterogenous patterns of technology deployment and related managerial implications.Originality/valueThis research introduces a new framework on factors driving industrial robotisation – a key digital production technology – and offers empirical evidence of the heterogenous deployment of this technology. The authors identify two main manufacturing approaches to robotisation in the automotive sector: one in which the firm designs a robotised process around a certain product design – i.e. the German/American way and one in which the firm designs its product based on certain robotised processes – i.e. the Japanese way. These findings are valuable for both industry, operational research and the scientific community as they reveal heterogeneity on the “how” of robotisation and implications for manufacturing technology management.

Remote integration of advanced manufacturing technologies into production systems: integration processes, key challenges and mitigation actions

Abstract: PurposeThe study examines the remote integration process of advanced manufacturing technology (AMT) into the production system and identifies key challenges and mitigating actions for a smoother introduction and integration process.Design/methodology/approachThe study adopts a case study approach to a cyber-physical production system at an industrial technology center using a mobile robot as an AMT.FindingsBy applying the plug-and-produce concept, the study exemplifies an AMT's remote integration process into a cyber-physical production system in nine steps. Eleven key challenges and twelve mitigation actions for remote integration are described based on technology–organization–environment theory. Finally, a remote integration framework is proposed to facilitate AMT integration into production systems.Practical implicationsThe study presents results purely from a practical perspective, which could reduce dilemmas in early decision-making related to smart production. The proposed framework can improve flexibility and decrease the time needed to configure new AMTs in existing production systems.Originality/valueThe area of remote integration for AMT has not been addressed in depth before. The consequences of lacking in-depth studies for remote integration imply that current implementation processes do not match the needs and the existing situation in the industry and often underestimate the complexity of considering both technological and organizational issues. The new integrated framework can already be deployed by industry professionals in their efforts to integrate new technologies with shorter time to volume and increased quality but also as a means for training employees in critical competencies required for remote integration.

The “V” model for decision analysis of additive manufacturing implementation

Abstract: PurposeThis study aims to broaden the understanding of the additive manufacturing (AM) body of knowledge, presenting a model better suited to the current level of technological development that supports the decision to implement AM in industries, based on the experience of companies in the industry of orthopedic medical implants.Design/methodology/approachBased on the design-science research, the model for the decision to adopt the AM was designed and submitted to experts from the industry of orthopedic implants in Brazil for refinement. For the empirical test of the final model, interviews were used in a company that was considering implementing AM and in another that was not, to evaluate the model.FindingsThe model considers seven dimensions for decision analysis of AM implementation: legal constraints, financial, technological, operational, organizational, supply chain and external factors, being subdivided into 42 criteria that play a relevant role in the implementation decision. The analysis factor of each dimension and criteria are also presented.Originality/valueThe model seeks to be as complete as possible and can be used by various industrial productive sectors, incorporating the analysis of the requirements of health regulatory agencies, suitable for the analysis of the decision to implement AM for the manufacturing of medical implants, not found in other models.

Driving forces for industry 4.0 readiness, sustainable manufacturing practices and circular economy capabilities: does firm size matter?

Abstract: PurposeDespite just eight years remaining to meet the sustainable development goals (SDG, 2030), the manufacturing industry faces numerous challenges for small and medium-sized enterprises (SMEs). Some notable challenges include integrating sustainability, circular economy (CE), and industry 4.0 (I4.0) technologies in a productive manner. However, there is a paucity of evidence available on the role of institutional pressures and organizational resources to promote I4.0 and sustainability. To fill this void, this study develops and tests a model based on institutional theory and resource-based view (RBV) theory while also taking company size into view as a moderating construct.Design/methodology/approachTo test the study hypotheses and validate the model, data were obtained through a survey from 228 randomly selected SMEs manufacturing in China. Structured equation modeling and multigroup analysis were used to analyze the data.FindingsThe research findings indicate that institutional pressure has a positive effect on organizational resources (i.e., tangible and intangible), which are capable of orchestrating I4.0 readiness effectively. Also, I4.0 readiness has a positive effect on sustainable manufacturing practices and CE capabilities. Finally, firm size was revealed to be a significant moderator in driving overall integration.Practical implicationsBased on the findings, practical implications and future research directions are discussed.Originality/valueBased on the institutional and RBV theories, this research shows how SMEs could be influenced by different stakeholders to acquire and develop their resources and capabilities to accelerate I4.0 readiness that further enhances sustainable practices.

Role of leadership in the digitalisation of manufacturing organisations

Abstract: Purpose This study examines the moderating role of leadership behaviours on the relationship between Industry 4.0 (I4.0) maturity and operational performance in manufacturers. Design/methodology/approach For that, 189 leaders from manufacturing organisations located in India and Brazil that are undergoing I4.0 implementation were surveyed. The collected data was analysed using multivariate data techniques, which allowed to verify the validity of our research hypotheses. This study was grounded on the concepts from the socio-technical systems (STS) theory. Findings The findings indicated that task-oriented leadership behaviours positively moderate the relationship between technologies for digitalisation and operational performance. A similar effect was found for the interaction between change-oriented leadership behaviours and strategy for digitalisation. In turn, the moderating effects of relations-oriented and change-oriented leadership behaviours were negative when considering the I4.0 maturity dimensions of employee and culture for digitalisation and technology for digitalisation, respectively. Originality/value This study offers arguments to better understand the role of leaders' behaviours in the digitalisation of organisations. Changing behaviours is usually a long-term and time-consuming activity. The identification of the leadership behaviours that are more likely to support digitalisation allows companies to anticipate potential issues and prioritise efforts to assertively develop leaders.

Green supplier selection and environmental performance of firms in the Chinese manufacturing industry: the roles of behavior and outcome controls

Abstract: PurposeGreen supplier selection (GSS) is acknowledged as important governance in green supply chain management (GSCM). However, this paper argues that GSS is not a stand-alone GSCM governance mode that determines manufacturers' environmental performance but rather one that needs to be aligned with contractual governance, particularly contractual control and adaptation, to promote environmental performance effects. This paper adopts GSS as ex ante governance and introduces behavior and outcome controls as ex post contractual control and adaptation, respectively. Thus, this paper addresses how GSS affects environmental performance directly and indirectly through behavior and outcome controls within transaction cost economics (TCE) theory.Design/methodology/approachThis research model was tested on 300 Chinese manufacturing firms, and multiple regression analysis was used to validate our hypotheses.FindingsA direct relationship was observed between GSS and environmental performance. This direct relationship is positively mediated by behavior and outcome controls.Originality/valueThis paper develops and elucidates an integrative green supply chain process proceeding from the implementation of ex ante GSS and ex post contractual governance to the realization of environmental performance. Furthermore, this paper considers two different forms of contractual governance, specifically contractual control and adaptation, and explains how they can be implemented using behavior and outcome controls from the perspective of TCE theory.

Robot adoption and export performance: evidence from Chinese industrial firms

Abstract: PurposeAs a new research interest, robots have surpassed human performance across several aspects. In this research, the authors wish to investigate whether robot adopters perform better than non-adopters in terms of export behavior, especially when distinguishing between different types of firms.Design/methodology/approachThe authors try a new strategy to identify the extent of robot adoption by import data and compare the export trajectories of robot adopters and non-adopters by employing the propensity score matching-difference in difference (PSM-DID) method.FindingsThe authors find that robot adopters are more likely to enter export markets and improve subsequent export performance, as the gains from doing so can spread the reduction in variable production costs to a larger customer base abroad. But this rule does not always seem to work; for large-scale firms, robot adoption makes it easier to win export competition and increase market share, while small and medium-sized enterprises (SMEs) do not seem to enjoy any benefits from adoption. More importantly, robot adoption also leads to the fiercer market competition when improving the productivity of firms, which will threaten smaller non-adopters.Originality/valueThe findings provide new evidence for the scale bias of robotics and offer new insights into whether exporters or future exporters ought to adopt robots in production.HighlightsFirst, distinguishing from existing research, we explain the controversial results of previous work on robotics by providing evidence from export markets and using the concept of size bias, which helps to update the theoretical interpretation of robotics and provides new insights for current and future exporters to evaluate their robot adoption decisions.Second, we extend previous research by further considering the potential robotics threats faced by non-adopters, especially we record that export gains of robot adopters are partially at the expense of smaller non-adopters, which provides new evidence for the rationale of SME protection policies and supplements robotics theory with new knowledge, such as the competitive game of firms related to robot adoption.Third, to our knowledge, prior research tended to examine the economic effects of robotics through industry data provided by the IFR, this may lead to systematic bias due to the inability to distinguish the robot adoption intentions of different firms. In this respect, we try a new strategy through robot import data and further distinguish between robot adopters and non-adopters in the sample, which helps to mitigate the potential bias in the findings and provide a complement to the recently developed literature related to robotics.Finally, as we pointed out earlier, robot adoption could be an interesting research work for the Chinese export market, which helps us to obtain some special findings, such as in assessing whether the benefits of robots are equally appropriate for economies that previously had an advantage in terms of labor.

Open-source 3-D printing materials database generator

Abstract: PurposeThis study aims to apply an open-source approach to protect the 3D printing industry from innovation stagnation due to broad patenting of obvious materials.Design/methodology/approachTo do this, first an open-source implementation of the first five conditions of an open-source algorithm developed to identify all obvious 3-D printing materials was implemented in Python, and the compound combinations of two and three constituents were tested on ten natural and synthetic compounds. The time complexity for combinations composed of two constituents and three constituents is determined to be O(n2) and O(n3), respectively.FindingsGenerating all combinations of materials available on the Chemical Abstracts Services (CAS) registry on the fastest processor on the market will require at least 73.9 h for the latter, but as the number of constituents increases the time needed becomes prohibitive (e.g. 3 constituents is 1.65 million years). To demonstrate how machine learning (ML) could help prioritize both theoretical as well as experimental efforts a three-part biomaterial consisting of water, agar and glycerin was used as a case study. A decision tree model is trained with the experimental data and is used to fill in missing physical properties, including Young's modulus and yield strength, with 84.9 and 85.1% accuracy, respectively.Originality/valueThe results are promising for an open-source system that can theoretically generate all possible combinations of materials for 3-D printing that can then be used to identify suitable printing material for specific business cases based on desired material properties.

A decision-support framework for selecting additive manufacturing technologies

Abstract: PurposeThis study provides an up-to-date review of additive manufacturing (AM) technologies and guidance for selecting the most appropriate ones for specific applications, taking into account the main features, strengths, and limitations of the existing options.Design/methodology/approachA literature review on AM technologies was conducted to assess the current state-of-the-art. This was followed by a closer examination of different AM machines to gain a deeper insight into their main features and operational characteristics. The conclusions and data gathered were used to formulate a classification and decision-support framework.FindingsThe findings indicate the building blocks of the selection process for AM technologies. Furthermore, this work shows the suitability of the existing AM technologies for specific cases and points to opportunities for technological and decision-support improvements. Lastly, more standardization in AM would be beneficial for future research.Practical implicationsThe proposed framework offers valuable support for decision-makers to select the most suitable AM technologies, as demonstrated through practical examples of its utilization. In addition, it can help researchers identify the limitations of AM by pinpointing applications where existing technologies fail to meet the requirements.Originality/valueThe study offers a novel classification and decision-support framework for selecting AM technologies, incorporating machine characteristics, process features, physical properties of printed parts, and costs as key features to evaluate the potential of AM. Additionally, it provides a deeper understanding of these features as well as the potential opportunities for AM and its impact on various industries.

How can lean tools support the innovation process of SMEs?

Abstract: PurposeAdopting lean principles can unleash several opportunities for firms seeking to increase the efficiency and effectiveness of their product development (PD) process. This study aims to investigate the implementation paths of lean tools in the innovation process of small and medium-sized enterprises (SMEs).Design/methodology/approachA set of 47 lean tools are identified from the literature and ascribed to the five lean thinking principles, i.e. Value, Map, Flow, Pull and Perfection. Their practical adoption – in terms of “when” and “how” – is then explored in a multiple case study of three SMEs in the manufacturing industry.FindingsSMEs adopt multiple lean tools in different phases of their innovation process. They are still at the beginning of the holistic adoption of lean PD, but some core lean tools, such as A3 reports and visual management, are adopted systematically. Results reveal that specific sets of lean tools and supporting principles are more valuable in certain phases of SMEs innovation process. Specifically, the lean tools concerning the principle of Value and Map can enable the phases of Innovation inputs, Concept development and Solution implementation; the ones ascribed to Flow and Pull the phases of Concept development, Testing and experimentation, and Solution implementation; the Perfection tools to the final phases of Testing and experimentation, Solution implementation and Market introduction.Practical implicationsResults provide a reference for SMEs already adopting lean tools in their production process to be extended to the PD process, especially when the delivery of new products is pivotal. Innovative SMEs could evaluate the introduction of specific lean tools in one or more definite phases of their PD process.Originality/valueThe study contributes to the literature on the complementarity between lean and innovation by studying the context of SMEs with a process perspective, thus unveiling the potential paths of a widespread application of lean innovation in SMEs.

Strategizing organizational capabilities for industrial digitalization – exploring managers' technological frames

Abstract: PurposeThis study draws on technological frames to provide an understanding of organizational processes of strategizing by exploring how strategizing organizational capabilities for industrial digitalization could be understood through managers' perceptions of digital technology applications. This study complements earlier research focused on industry outcomes by addressing technological frames to understand how strategizing organizational capabilities within industrial digitalization may provide insight into socio-cognitive aspects which may affect technology-induced organizational change.Design/methodology/approachThe single case study uses 14 in-depth interviews collected over two years (October 2020 to February 2022). The study follows an interpretative research design exploring managers' perceptions of industrial digitalization through a digitalization project.FindingsThe case study contributes to research by emphasizing socio-cognitive aspects through technological frames exploring how and why managers' perceptions of industrial digitalization affect strategizing organizational capabilities. The study contributes to practice by bringing attention to the disparate views of industrial digitalization. By illustrating how socio-cognitive aspects shape organizational capabilities, this study offers managers valuable insight into the relationship between an organization's capabilities, the individual and the shared structures affecting a digitalization project.Research limitations/implicationsThe case study is limited to Swedish manufacturing industries and is not aiming to be transferred or generalized to other industrial contexts or countries.Originality/valueThis study recognizes that strategizing organizational capabilities depends on managers' ability to illuminate the socio-cognitive aspects. Hence, the study contributes to practice by bringing attention to the disparate views among managers on the enhancement efforts made using digital technologies.

How do environmental taxes affect green process innovation? Evidence from the Chinese manufacturing industry

Abstract: PurposeThe absence of government intervention and market supervision cannot effectively promote green process innovation in manufacturing industries. As a new government regulation approach, environmental taxes provide a platform to internalize the externality of environmental pollution. This paper empirically investigates the impact of environmental taxes on green process innovation and the moderating effects of industry pollution heterogeneity and green credit.Design/methodology/approachThis research collects manufacturing industry data ranging from 2008 to 2020, resulting in a total of 351 observations. Time-individual, two-way fixed effect models are constructed to examine the hypotheses.FindingsThe results indicate environmental taxes have an inverted-U effect on green process innovation in manufacturing industries. Implementation intensity of the current environmental taxes on China's manufacturing industries does not reach an inflection point. Further analysis suggests that environmental taxes exert influence on the inverted-U relationship with low-pollution industries displaying a steeper curvilinear pattern than high-pollution industries. Moreover, the analysis shows that green credit plays a moderating role in the inverted-U relationship, as low green credit provides more limited stimulus than high green credit in terms of the effect of environmental taxes on green process innovation.Research limitations/implicationsThis study offers empirical evidence to accommodate negative externalities of corporate production and provides new perspectives in nudging corporate green-process innovation.Originality/valueThis paper verifies the effect of environmental taxes on green process innovation amid industry pollution heterogeneity by introducing an industrial-level analysis unit. This study improves the means by which environmental taxes are measured. Existing literature has narrowly used pollution discharge fees as a proxy for environmental taxes. The authors have summed up the taxes on vehicle and vessels, urban land use, urban maintenance and construction, vehicle purchases, waste gas, wastewater and solid waste to measure the effect of environmental taxes in this study.

Assessment of Sustainable Development Goals through Industry 4.0 and reconfigurable manufacturing system practices

Abstract: PurposeThe United Nation's Sustainable Development Goals (SDGs), introduced in 2015, connect several manufacturing strategies and promote sustainable practices in an organization. Manufacturing companies are struggling to meet changing market demands while also addressing social and biological issues. The current study aims to develop a framework that can assist practitioners and managers contribute to the attainment of the SDGs through the adoption of reconfigurable manufacturing system (RMS) practices and Industry 4.0 technologies.Design/methodology/approachAn extensive literature review was carried out to identify RMS-Industry 4.0 practices and their interconnection, as well as their contribution to achieving the SDGs. The stepwise weight assessment ratio analysis (SWARA) method was then used to compute the weights of the selected RMS-Industry 4.0 practices, whereas the weighted aggregated sum product assessment (WASPAS) method was used to prioritize performance metrics. The developed framework's robustness was tested using a sensitivity analysis across five different organizations.FindingsThe findings show that advanced technologies practices have the most importance, followed by customization and rapid adjustment of capacity and functionality practices. The sensitivity analysis revealed the robustness of the developed framework as well as its adaptability among the chosen organizations.Practical implicationsThis research will assist in the adoption of RMS and includes recent technologies that can help in the attainment of industrial SDGs. Managers will also be able to evaluate RMS in the context of industrial SDGs. Researchers and practitioners can now address the various RMS-Industry 4.0 practices while keeping the social and environmental aspects in mind.Originality/valueNo previous research has investigated the SDGs through the nexus effect of Industry 4.0 and RMS practices.

Industry 4.0 benefits, challenges and critical success factors: a comparative analysis through the lens of resource dependence theory across continents and economies

Abstract: PurposeEntering a new era of digital transformation, Industry 4.0 (I 4.0) promises to revolutionize the way business has been done, providing unprecedented opportunities and challenges. This study aims to investigate empirically and comparatively analyse the benefits, challenges and critical success factors (CSFs) of Industry 4.0 across four continents and developing and developed economies.Design/methodology/approachThis study used an online survey to explore the benefits, challenges and CSFs of developed and developing economies. In order to ensure the validity of the survey, a pilot test was conducted with 10 respondents. A total of 149 participants with senior managerial, vice-presidential and directorial positions from developed and developing economies spanning four continents were invited to take part in the survey.FindingsThe study ranks benefits, challenges and CSFs across economies and continents. Further, the benefit of Industry 4.0 helping to achieve organizational efficiency and agility differed across the developing and developed economies. Furthermore, the benefit improves customer satisfaction significantly differed across continents; in terms of challenges, Employee resistance to change had a higher proportion in developing economies. The future viability of I 4.0 also differed across the continents. Regarding CSFs, there was no difference across the developing and developed economies. Finally, change management and project management vary across the continents.Research limitations/implicationsThis study contributes to a balanced understanding of I 4.0 by providing empirical evidence for comparative analysis. Moreover, it extends the concept of resource dependence theory to explain how organizations in developing economies and developed economies deploy resources to manage external condition uncertainties to implement I 4.0. Furthermore, this study provides a structural framework to understand the specific benefits, challenges and CSFs of implementing I 4.0, which can be utilized by policymakers to promote I 4.0 in their economies or continents.Originality/valueTo the best of the authors’ knowledge, no studies have empirically demonstrated the comparative analysis of benefits, challenges and CSFs across economies and continents and distinguish an original contribution of this work.

Does the integration of lean production and Industry 4.0 in green supply chains generate a better operational performance?

Abstract: PurposeThe tightening of environmental measures and policies in various countries around the world is forcing manufacturing companies, particularly those that make up the automotive industry, to improve their production processes, through the implementation of approaches such as lean production (LP) and Industry 4.0 (I4.0) technologies, to reduce industrial waste. However, the literature indicates that the implementation of LP and I4.0 does not always lead to an improvement in the level of operational performance (OP). Therefore, this study analyzes the effects of the implementation of LP practices and I4.0 on a green supply chain (GSC) and the operational performance of manufacturing companies in the Mexican automotive industry.Design/methodology/approachA theoretical research framework consisting of six hypotheses was developed and validated by applying partial least squares structural equation modeling (PLS-SEM) and using a sample of 460 companies from the Mexican automotive industry.FindingsThe results show that the level of OP of manufacturing companies increases substantially with the implementation of LP and I4.0 practices, as well as a GSC.Practical implicationsManagers of manufacturing companies will be able to use the results of this study to improve their production systems and to demonstrate the effects of these practices on OP.Originality/valueThis study contributes to the literature on LP and I4.0 by providing robust empirical evidence of the positive effects of implementing these approaches on the GSC and OP of manufacturing companies.

Combining internal quality-oriented product design with external supplier involvement for enhancing operational performance: the moderating role of product modularity

Abstract: PurposeThe purpose of this study is to develop a moderated mediation model by which quality-oriented product design practices influence operational performance via supplier involvement under the different levels of product modularity.Design/methodology/approachThe authors use the multisource data from 268 manufacturing firms worldwide and apply regression and the PROCESS macro model to test the moderated mediation model.FindingsThe findings reveal that quality-oriented product design practices enhance operational performance directly and do so indirectly through promoting supplier involvement in quality improvement. In addition, this indirect effect is stronger when the level of product modularity is high.Originality/valueBy exploring the interaction effects of quality-oriented product design and product modularity, this study provides valuable insights into the ways in which manufacturing firms improve operational performance more effectively.

Driving smartness for organizational performance through Industry 4.0: a systems perspective

Abstract: PurposeThe internationalization of business has grown the production value chains and created performance challenges for industrial production. Industry 4.0, the digital transformation of industrial processes, promises to deliver performance improvements through smart functionalities. This study investigates how digital transformation translates to performance gain by adopting a systems perspective to drive smartness.Design/methodology/approachThis study uses qualitative research to collect data on the lived experiences of digital transformation practitioners for theory development. It uses semi-structured interviews with industry experts and applies the Gioia methodology for analysis.FindingsThe study determined that enterprise smartness is an organizational capability developed by digital transformation, it is a function of integration and the enabler of organizational performance gains in the Industry 4.0 context. The study determined that performance gains are experienced in productivity, sustainability, safety and customer experience, which represents performance metrics for Industry 4.0.Research limitations/implicationsThis study contributes a model that inserts smartness in the linkage between digital transformation and organizational outcomes to the digital transformation and production management literature.Practical implicationsThe study indicates that digital transformation programs should focus on developing smartness rather than technology implementations, which must be considered an enabling activity.Originality/valueExisting studies recognized the positive impact of technology on performance in industrial production. The study addresses a missing link in the Industry 4.0 value creation process. It adopts a systems perspective to establish the role of smartness in translating technology use to performance outcomes. Smart capabilities have been the critical missing link in the literature on harnessing digital transformation in organizations. The study advances theory development by contributing an Industry 4.0 value model that establishes a link between digital technologies, smartness and organizational performance.

Analyzing sustainable reverse logistics capability and triple bottom line: the mediating role of sustainability culture

Abstract: PurposeTo overcome the various pressures related to the environmental damage raised by production processes, enhancing sustainable reverse logistics (SRL) capability is a new road for manufacturing companies, as it facilitates them to have more sustainable operations by increasing different performance outputs. This study aims to investigate the relationship between the SRL capability and the triple bottom line (TBL) i.e. economic, social and environmental performance in the context of Turkey's manufacturing industry. The mediating role of sustainability culture has also been examined.Design/methodology/approachUsing survey data obtained from the Turkish manufacturing industry, the partial least square path modeling technique of structural equation modeling has been applied to test the research hypothesis.FindingsThe results of the study indicate that the SRL capability generates not only outstanding environmental and economic gains but also social benefits. The authors also find that sustainability culture is positively associated with environmental and social performance, yet not economic performance. In addition, the findings indicate sustainability culture mediates the relationship between SRL capability and social performance.Originality/valueThis study expands the frontier of managerial knowledge by highlighting the importance of SRL capability for sustainability and exhibiting evidence of the business value of enhancing SRL capability and sustainability culture.