Journal of Manufacturing Technology Management最新文献

{"title":"Business networking orientation, green operations practices and firm performance","authors":"Chin-Chun Hsu, K. Tan, Brent A. Hathaway, S. Zailani","doi":"10.1108/jmtm-09-2022-0341","DOIUrl":"https://doi.org/10.1108/jmtm-09-2022-0341","url":null,"abstract":"PurposeThe authors apply social network theory and natural resource–based view to empirically examine a model of the relationships among business networking (BN) orientation, green operations practices and performance. A firm must achieve appropriate internal green operations practices to capitalize on its external BN orientation and thus be able to establish a competitive advantage and superior performance.Design/methodology/approachUsing survey data from 132 ISO 14001–certified manufacturing firms in Malaysia, all of which participate in environmental programs and sustainability activities, the authors explore the effects of two BN orientation facets (customer-oriented and supplier-oriented) on green operations practices (green purchasing, eco-design and regulatory practices) and their subsequent influence on environmental and economic performance.FindingsStructural equation modeling outcomes confirm only one BN orientation facet positively affects green operations practices, nor do the advantages affect economic performance directly. The results illustrate how environmental outcomes mediate the links between green operations practices and economic performance.Originality/valueDrawing on social network theory and natural resource–based view, authors propose internal green operations practices as a channel through which external BN orientation induces firm performance. Internal green operations practices determine a firm's ability to exploit its external BN orientation to achieve operational competencies and lead to superior performance. Rather than focusing on the social connections generated by external BN orientation itself, the authors recommend that firms address the core competencies contributing to their green operations practices and engage in network building.","PeriodicalId":16301,"journal":{"name":"Journal of Manufacturing Technology Management","volume":" ","pages":""},"PeriodicalIF":7.6,"publicationDate":"2023-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46515338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The “V” model for decision analysis of additive manufacturing implementation","authors":"Anderson Ferreira de Lima, Walter Cardoso Satyro, J. C. Contador, Marco Aurelio Fragomeni, R. F. Gonçalves, M. Martens, F. H. Pereira","doi":"10.1108/jmtm-10-2022-0377","DOIUrl":"https://doi.org/10.1108/jmtm-10-2022-0377","url":null,"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.","PeriodicalId":16301,"journal":{"name":"Journal of Manufacturing Technology Management","volume":" ","pages":""},"PeriodicalIF":7.6,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42056991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Strategizing organizational capabilities for industrial digitalization – exploring managers' technological frames","authors":"L. Carlsson","doi":"10.1108/jmtm-07-2022-0252","DOIUrl":"https://doi.org/10.1108/jmtm-07-2022-0252","url":null,"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.","PeriodicalId":16301,"journal":{"name":"Journal of Manufacturing Technology Management","volume":" ","pages":""},"PeriodicalIF":7.6,"publicationDate":"2023-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48523071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Supply chain resilience and performance of manufacturing firms: role of supply chain disruption","authors":"Zulaiha Hamidu, F. Boachie-Mensah, Kassimu Issau","doi":"10.1108/jmtm-08-2022-0307","DOIUrl":"https://doi.org/10.1108/jmtm-08-2022-0307","url":null,"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.","PeriodicalId":16301,"journal":{"name":"Journal of Manufacturing Technology Management","volume":" ","pages":""},"PeriodicalIF":7.6,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42908359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Augmented reality for industrial services provision: the factors influencing a successful adoption in manufacturing companies","authors":"Sara Aquino, M. Rapaccini, F. Adrodegari, G. Pezzotta","doi":"10.1108/jmtm-02-2022-0077","DOIUrl":"https://doi.org/10.1108/jmtm-02-2022-0077","url":null,"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.","PeriodicalId":16301,"journal":{"name":"Journal of Manufacturing Technology Management","volume":" ","pages":""},"PeriodicalIF":7.6,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48956396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Drivers of green supply chain integration and green product innovation: a motivation-opportunity-ability framework and a dynamic capabilities perspective","authors":"Hanna Lee","doi":"10.1108/jmtm-09-2022-0311","DOIUrl":"https://doi.org/10.1108/jmtm-09-2022-0311","url":null,"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.","PeriodicalId":16301,"journal":{"name":"Journal of Manufacturing Technology Management","volume":" ","pages":""},"PeriodicalIF":7.6,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43772263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Resilience, complexity and digital transformation: three case studies in the valves industry","authors":"Lino Codara, F. Sgobbi","doi":"10.1108/jmtm-05-2022-0214","DOIUrl":"https://doi.org/10.1108/jmtm-05-2022-0214","url":null,"abstract":"PurposeThis paper shows how the interplay between organisational resilience and environmental complexity justifies the existence of differentiated yet successful approaches to digital transformation.Design/methodology/approachA multi-case method is applied to test our research hypotheses by contrasting the digital transformation of three Italian companies in the valves industry.FindingsDifferent combinations of technological and organisational tools, hence diversified digital transformations, can be successful, provided that they are supported by a coherent set of resilience factors and allow for the implementation of strategic approaches aligned with the resilience capacity of the firm.Practical implicationsAwareness that resilience capacity shapes digital transformation and the strategies available to engage with external complexity should focus managers to invest in the alignment and the reinforcement of the factors underlying organisational resilience.Originality/valueMost literature so far focused on the antecedents to digital transformation. In contrast, this paper focuses on the transformation process and highlights how the resilience capacity of the firm affects the unfolding of digital transformation and the emergence of diversified yet successful paths. In addition, in contrast with a dichotomous approach to external complexity this paper shows that digital transformation involves a mix of complexity reduction and complexity absorption strategies.","PeriodicalId":16301,"journal":{"name":"Journal of Manufacturing Technology Management","volume":" ","pages":""},"PeriodicalIF":7.6,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48524166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A deep attention based approach for predictive maintenance applications in IoT scenarios","authors":"Roberto De Luca, Antonino Ferraro, Antonio Galli, M. Gallo, V. Moscato, Giancarlo Sperlí","doi":"10.1108/jmtm-02-2022-0093","DOIUrl":"https://doi.org/10.1108/jmtm-02-2022-0093","url":null,"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.","PeriodicalId":16301,"journal":{"name":"Journal of Manufacturing Technology Management","volume":" ","pages":""},"PeriodicalIF":7.6,"publicationDate":"2023-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43985341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Time for Change","authors":"","doi":"10.12968/s2514-9768(23)90372-8","DOIUrl":"https://doi.org/10.12968/s2514-9768(23)90372-8","url":null,"abstract":"","PeriodicalId":16301,"journal":{"name":"Journal of Manufacturing Technology Management","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134940320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In Depth","authors":"","doi":"10.12968/s2514-9768(23)90374-1","DOIUrl":"https://doi.org/10.12968/s2514-9768(23)90374-1","url":null,"abstract":"","PeriodicalId":16301,"journal":{"name":"Journal of Manufacturing Technology Management","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134940321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}