IEEE Transactions on Engineering Management最新文献

{"title":"Enabling the Integration of Industry 4.0 and Sustainable Supply Chain Management in the Textile Industry: A Framework and Evaluation Approach","authors":"Hamza Muhammad Dawood;Chunguang Bai;Syed Imran Zaman;Matthew Quayson;Cristian Garcia","doi":"10.1109/TEM.2024.3459922","DOIUrl":"https://doi.org/10.1109/TEM.2024.3459922","url":null,"abstract":"The value of Industry 4.0 technology in promoting sustainable development cannot be fully realized without considering the mutual influence between sustainable supply chain management (SSCM) and Industry 4.0. To our knowledge, the investment of Industry 4.0 technology and SSCM has not yet been studied from an integration perspective. This study aims to determine the enablers for integrating Industry 4.0 and SSCM and provide a theoretical framework and approach for evaluating those enablers. First, a human, technology, organization, and environment fit (HTOE-fit) theoretical framework is developed to identify and categorize 16 enablers. Second, Fuzzy-DEMATEL and Fuzzy-TOPSIS techniques are used to analyze the influence relationships between the enablers and then rank those enablers. The case of the textile industry in a developing economy has been investigated. Results showed that technology is the most essential aspect, and automation is the most important enabler in the textile industry. The theoretical implications are based on the HTOE-fit framework, which offers a novel approach for identifying critical enablers that are necessary for the successful integration of Industry 4.0 and SSCM, based on the above-mentioned four aspects. This study also identifies the mutual influence relationship among the enablers, which helps the textile companies in formulating investment and implementation paths for integrating Industry 4.0 and SSCM.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"14704-14717"},"PeriodicalIF":4.6,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142359711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation of Machine Learning for Enhancing Lean Manufacturing Practices for Metal Additive Manufacturing","authors":"Ema Vasileska;Aleksandar Argilovski;Mite Tomov;Bojan Jovanoski;Valentina Gecevska","doi":"10.1109/TEM.2024.3459645","DOIUrl":"https://doi.org/10.1109/TEM.2024.3459645","url":null,"abstract":"Metal additive manufacturing (AM), particularly laser powder bed fusion (LPBF), has emerged as a promising technology for rapidly producing intricate parts while minimizing material waste. However, the widespread adoption of AM has been hindered by the lack of adequate quality control measures. To address this challenge, a large number of machine learning (ML) applications have been proposed to improve the quality and productivity of AM processes. This study proposes the Lean concept as a guiding framework for classifying ML applications according to the Lean principles they support. Through a comprehensive review of literature studies, the research demonstrates the efficacy of this holistic approach, emphasizing ML's contributions to the Lean principles and the derived benefits to refine metal AM practices, improve efficiency, foster continuous improvement in LPBF, and finally bring value to the customer. The obtained results are particularly important for manufacturing engineers, quality control specialists, and decision-makers in the AM industry, as they provide actionable insights for enhancing process reliability, reducing waste, and achieving higher productivity.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"14836-14845"},"PeriodicalIF":4.6,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unlearn Success or Failure Beliefs?: How Do Big Data Analytic Capabilities Affect the Incumbents’ Business Model Innovation in Deep Uncertainty","authors":"Suqin Liao;Zaiyang Xie","doi":"10.1109/TEM.2024.3457874","DOIUrl":"https://doi.org/10.1109/TEM.2024.3457874","url":null,"abstract":"Research investigating the underlying mechanisms and boundary conditions under which Big Data analytic capabilities (BDACs) influence business model innovation (BMI) in incumbents remains largely underdeveloped. Drawing on the dynamic capabilities view (DCV), we developed a moderated multimediation model in which unlearning success beliefs and unlearning failure beliefs were theorized as the different mechanisms underlining why incumbents are more likely to engage in BMI under the influence of BDACs. We further proposed that deep uncertainty is an important boundary condition that affects such a relationship. Multisource data from a multiwave survey was analyzed using structural equation modeling to test the theoretical framework. The results indicated that BDACs positively affect incumbents’ BMI through not only unlearning success beliefs but also unlearning failure beliefs. Furthermore, the results provided evidence for that deep uncertainty positively moderates the mediation of unlearning success beliefs. Notably, although the moderating effect of deep uncertainty on the mediation of unlearned failure beliefs is negative, it is insignificant. Our study contributes theoretically to the research on BDACs, organizational unlearning, BMI, and DCV, while practical implications are also discussed.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"14718-14732"},"PeriodicalIF":4.6,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142368313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two-Phase Approach to International Logistics Hub Location: The Case of Yangtze River Delta","authors":"Xinfang Zhang;Chengliang Liu;Yan Peng","doi":"10.1109/TEM.2024.3458151","DOIUrl":"https://doi.org/10.1109/TEM.2024.3458151","url":null,"abstract":"An international logistics hub (ILH) is an important component of the modern integrated logistics system, and its location selection has always been a hot topic in logistics management. In this article, we aim in developing a two-phase location framework to determine the most preferred ILHs in the logistics network. First, a revised fuzzy C-means clustering algorithm is proposed to identify candidate ILHs from the perspective of microlevel evaluation. The evaluation index system is constructed by the proposed index screening model. Second, an adaptive gravity \u0000<italic>p</i>\u0000-median model is established to determine optimal ILHs and freight flow allocations from a macroplanning perspective. The optimization model takes into account the attractiveness of nodes, the distribution of logistics demand, and the total transportation cost between nodes in the network. Finally, the two-phase approach is applied to the location of ILHs in the Yangtze River Delta (YRD), China. Results show that five alternative locations are identified from 27 cities, and four optimal ILHs (Shanghai, Suzhou, Hangzhou, Ningbo) are determined from five candidate ILHs. The freight flow distribution shows that the share transshipped through them is 33.05%, 26.81%, 22.59%, and 17.55%, respectively. Furthermore, the optimized hub location in the case study is consistent with the practice situation in the YRD. These results illustrate the applicability and feasibility of the proposed two-phase approach for the logistics hub location. We also provide insights for planning logistics hubs and optimizing transportation networks in the YRD from the perspectives of megalopolis and national levels.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"14621-14639"},"PeriodicalIF":4.6,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142320396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the Effect of Generative AI on Social Sustainability Through Integrating AI Attributes, TPB, and T-EESST: A Deep Learning-Based Hybrid SEM-ANN Approach","authors":"Mostafa Al-Emran;Bassam Abu-Hijleh;AbdulRahman A. Alsewari","doi":"10.1109/TEM.2024.3454169","DOIUrl":"https://doi.org/10.1109/TEM.2024.3454169","url":null,"abstract":"The swift progress of generative artificial intelligence (AI) tools offers remarkable potential for revolutionizing educational methods and enhancing social sustainability. Despite its potential, understanding the factors driving its adoption and how that affects social sustainability remains underexplored. This study aims to address this gap by integrating AI attributes (“perceived anthropomorphism,” “perceived intelligence,” and “perceived animacy”) with the theory of planned behavior and the technology-environmental, economic, and social sustainability theory (T-EESST) to develop a theoretical research model. Utilizing a hybrid structural equation modeling and artificial neural network approach, we analyzed data collected from 1048 university students to evaluate the developed model. Our findings revealed that while perceived behavioral control has an insignificant impact on generative AI use, attitudes emerge as the most critical factor, further reinforced by the significant role of subjective norms. Perceived anthropomorphism, perceived intelligence, and perceived animacy were also found to influence students’ attitudes significantly. More importantly, the findings supported the role of generative AI in positively affecting social sustainability, aligning with the principles of T-EESST. This study's significance lies in its holistic examination of the interplay between technological attributes, motivational aspects, and sustainability outcomes, offering valuable insights for various stakeholders.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"14512-14524"},"PeriodicalIF":4.6,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Industry 4.0 Technologies Adoption and Sustainability Integration in Human Resource Management: An Analysis Using Extended TOE Framework and TISM","authors":"Abhyudaya Anand Mishra;Devendra Kumar Pathak","doi":"10.1109/TEM.2024.3456604","DOIUrl":"https://doi.org/10.1109/TEM.2024.3456604","url":null,"abstract":"The growing interest for Industry 4.0 Technologies (I4T) adoption and a pressing need for sustainability integration have witnessed the attention of human resource management (HRM) practitioners and researchers alike. Therefore, this study attempts to propose a unified model for I4T adoption and sustainability integration in HRM. Underscoring the importance of “people dimension” in HRM context, this study proposes an extended technology-organizational-environmental (TOE) (i.e., TOE dimensions along with “people dimension”) framework to identify enablers that facilitate I4T adoption and sustainability integration in HRM. Moreover, this study delineates the interrelationships among the identified enablers by employing total interpretive structural modeling (TISM) methodology and eventually proposes a seven-level hierarchical model. MICMAC analysis is carried out to classify these enablers based on their driving power and dependence. The findings reveal that enablers under “environmental dimension” attain highest driving power followed by enablers under “organizational,” “technological,” and “people” dimensions. To ensure the robustness of the proposed model, hypothesis testing (through \u0000<italic>t</i>\u0000-test) is utilized to validate all direct and significant transitive links. The findings of this research should assist practitioners and scholars in understanding and managing the crucial enablers of Industry 4.0 technologies led sustainable HRM. \u0000<italic>Managerial Relevance Statement:</i>\u0000 This study assists practitioners in identifying the decisive enablers that facilitate I4T adoption and sustainability integration in HRM. This study highlights the significance of the extended TOE framework, and the identified 17 decisive enablers are categorized under technological, organizational, environmental, and people (TOEP) dimensions. By utilizing the TISM-based hierarchical model developed in this study, practitioners predominantly need to emphasize on the key enablers (i.e., enablers under environmental and organizational dimensions) that drive the entire hierarchical model for achieving Industry 4.0 technologies-led sustainable HRM. Moreover, this study highlights the significance of the “people dimension” for I4T adoption and guides HR professionals to also emphasize on enablers under the “people dimension” while implementing I4T and sustainability in organizations. Managers can utilize the proposed TOEP framework for technology adoption in other people-centric domains.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"14688-14703"},"PeriodicalIF":4.6,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142359724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Empowering SMEs “Harnessing the Potential of Gen AI for Resilience and Competitiveness”","authors":"Elias G. Carayannis;Roman Dumitrescu;Tommy Falkowski;Nikos-Rigert Zota","doi":"10.1109/TEM.2024.3456820","DOIUrl":"https://doi.org/10.1109/TEM.2024.3456820","url":null,"abstract":"This study investigates how generative artificial intelligence (Gen AI) can enhance the resilience and competitiveness of small and medium enterprises (SMEs). The central question addressed is: How can SMEs leverage Gen AI to navigate challenges and capitalize on opportunities in an evolving digital landscape? We argue that Gen AI offers transformative potential for SMEs by automating processes, enhancing decision-making and fostering innovation, thereby improving their ability to adapt and thrive amidst market uncertainties. Through a comprehensive analysis of SMEs and Gen AI, this article underscores the importance of strategic AI integration, addresses the associated challenges, and provides policy recommendations to support SMEs in harnessing AI for sustainable growth. By exploring real-world examples and theoretical insights, we aim to equip SMEs with the directions, actions, and strategies necessary to succeed in the Gen AI era.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"14754-14774"},"PeriodicalIF":4.6,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142368311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FinTech for Supply Chain Operations: Platform Credit Financing","authors":"Sambit Brata Rath;Preetam Basu;Tsan-Ming Choi;Prasenjit Mandal","doi":"10.1109/TEM.2024.3453595","DOIUrl":"https://doi.org/10.1109/TEM.2024.3453595","url":null,"abstract":"Traditionally, in supply chain management, manufacturers such as \u0000<italic>Hewlett-Packard</i>\u0000 and \u0000<italic>Procter&amp;Gamble</i>\u0000 fund their downstream retailers through \u0000<italic>trade credit financing</i>\u0000 (TCF). Recently, with the advance of FinTech, platforms have also implemented innovative financing schemes called \u0000<italic>platform credit financing</i>\u0000 (PCF). Both TCF and PCF are risky, which expose the lender to operational risks. Motivated by these real-world practices, we model a three-echelon supply chain in which a capital-constrained retailer, exposed to operational risk, orders from the manufacturer and sells on an online platform. We explore TCF and PCF, and determine the retailer's optimal financing options based on her operational risk and the platform's referral fee for the product category. Our results show that PCF becomes profitable for all three entities when the retailer's operational risk level is high. This result justifies the successful adoption of PCF under a high operational risk scenario where it becomes challenging for the retailer to obtain financing through traditional modes. We also find that TCF may achieve a win-win-win outcome in the presence of a loss-averse lender or in the partial demand fulfillment scenario. To derive more insights and check for the robustness of core findings, we examine several extended cases.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"14789-14806"},"PeriodicalIF":4.6,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploiting the Potential of Invalid Patents as a Source of Technology Opportunities: Evidence From CCUS Technology","authors":"Weiwei Liu;Jingyi Yao;Kexin Bi","doi":"10.1109/TEM.2024.3456136","DOIUrl":"https://doi.org/10.1109/TEM.2024.3456136","url":null,"abstract":"Technology opportunity analysis is an important prerequisite for the successful implementation of technological innovation activities, which is not only the basis for obtaining the initiative of innovation but also the key to occupying the technological heights of the industry. Therefore, in this article, we propose a framework that serves the monitoring of development opportunities in a specific technology field. Unlike the current alternatives, the proposed approach considers the attributes of the patent itself. On the one hand, invalid patents are integrated into the study by contrasting their R&D trends with those of valid patents. On the other hand, the contribution of a single patent to a particular technology is taken into consideration by the construction of the patent value evaluation system. The framework introduces the latent Dirichlet allocation model to identify the technology topics involved in the patent. Then, a 3-D indicator system, including technical, legal, and economic dimensions, is constructed to evaluate the importance of patents. Finally, a measure for dividing the life cycle of a technology topic is proposed to visualize the trend of each technology topic. The result is a more holistic and richer landscape covering the entire life cycle of the targeted technology, from emerging to declining. A case study specializing in global carbon capture, utilization, and storage technology demonstrates this approach. The results of the analysis are highly consistent with current technology trends, suggesting that the method could serve as a useful reference tool for discovering technology opportunities and defining new R&D strategies.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"14571-14589"},"PeriodicalIF":4.6,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142320399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Project Portfolio Network Risk Propagation Modeling: A Risk Perception Perspective","authors":"Libiao Bai;Chenshuo Wang;Yichen Sun;Xiaoyan Xie;Tiantian Tang;Qi Xie","doi":"10.1109/TEM.2024.3455310","DOIUrl":"https://doi.org/10.1109/TEM.2024.3455310","url":null,"abstract":"Risks and resulting propagating accidents pose considerable threats to the stability of project portfolio network (PPN). To maintain PPN stability, a PPN risk propagation model considering risk perception is constructed. First, a PPN is developed to concurrently visualize the risk propagation paths and the risk perception diffusion paths. Second, modifications to the disaster spreading model are made to construct the PPN risk propagation model supporting more realistic simulations. The model is then applied to numerical simulations, yielding risk propagation mitigation measures. The results suggest that risk mitigation is facilitated by increased trust among project managers, moderate differences in initial project manager risk perceptions, a homogeneous PPN topology, and a tendency to allocate recovery resources based on node degree centrality. These findings guide enterprise administrators in risk decision-making, contributing to stable PPN operations.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"14608-14620"},"PeriodicalIF":4.6,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142320471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}