IEEE Transactions on Engineering Management最新文献

{"title":"Exploring the Challenges in Building Information Modeling (BIM) During the Design Phase: Evidence From Cross-Country Studies","authors":"Tássia Farssura Lima da Silva;Darli Rodrigues Vieira;Marly Monteiro de Carvalho","doi":"10.1109/TEM.2024.3461508","DOIUrl":"https://doi.org/10.1109/TEM.2024.3461508","url":null,"abstract":"Building information modeling (BIM) is transforming the construction life cycle. Nonetheless, there is a notable gap in research regarding the key challenges associated with BIM. This study aims to investigate the primary challenges in the design phase and their implications for project success. To address these objectives, cross-country case studies were conducted in four large engineering companies from the USA, Canada, Brazil, and United Arab Emirates. Data were collected through 23 semi-structured interviews with managers, engineers and directors, and content analysis was performed using NVIVO software. The resulting coding structure revealed the following categories: organizational and cultural issues, professional and knowledge issues, technological and operational issues, cost issues, BIM specific issues, design issues, data issues, and information and communication issues. The findings highlighted the most significant challenge as the lack of BIM knowledge or expertise. Additionally, an important enabler in the design phase is the accuracy of data provided by BIM, which enhances project management analysis. Finally, the BIM challenges and enablers influence various benefits dimensions, particularly on the efficiency.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434584","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":"Selecting-the-Best vs. Eliminating-the-Worst: An Experimental Investigation of Idea Evaluation Processes Under Cognitive Bias Conditions","authors":"Zhijian Cui;Vladimir Baraboshkin;Dilney Gonçalves","doi":"10.1109/TEM.2024.3459032","DOIUrl":"https://doi.org/10.1109/TEM.2024.3459032","url":null,"abstract":"The conventional wisdom in idea selection literature typically assumes that selecting-the-best ideas and eliminating-the-worst ideas represent the two sides of the same coin. In other words, selecting-the-best ideas from a pool of ideas should be equivalent to eliminating-the-worst ones until only the best remain. However, our explorative experimental investigation regarding the accuracy of these two idea evaluation processes indicates major differences. Specifically, our results suggest that the elimination process outperforms the selection process in terms of the probability of selecting the highest quality innovation ideas. Our text analysis further reveals that when participants are asked to do the selection or elimination tasks, their cognitive perception of each idea tends to focus on different aspects of the ideas, namely, the positive (pros) vs. negative (cons) sides of the same idea. We use a 2 × 2 experimental design by priming the participants with pros and cons information in selecting-the-best and eliminating-the-worst scenarios. Surprisingly, we find that with pros, the selection process outperforms the elimination process, whereas with cons, the efficacies of the two idea evaluation processes are equivalent. Additionally, we find that the efficacy of the selection process does not change whether the participant has pros or cons, yet the efficacy of the elimination process is significantly improved with cons compared to with pros. Based on analysis of the experimental data, we present and test an explanatory model in which the evaluation accuracy, measured in terms of the percentage of matches, is influenced by factors, such as the evaluation process, response duration, and the moderating effect of cognitive biases.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142368312","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":"The Logistics of Evacuating and Sheltering Medically Fragile Populations Under Pandemics","authors":"Diaz Rafael;Acero Beatriz;Behr Joshua;Juita-Elena Yusuf","doi":"10.1109/TEM.2024.3458901","DOIUrl":"https://doi.org/10.1109/TEM.2024.3458901","url":null,"abstract":"This article examines the logistics of evacuation and sheltering of medically fragile populations, who tend to have less capacity to safely manage rapidly shifting storm-induced conditions under a pandemic environment. Health awareness and the health and financial impacts of the pandemic have altered households’ evacuation and sheltering calculus. The timing and volume of evacuees have significant implications for configuring available transportation infrastructures and means and opening shelters and refuge of last resort as the storm materializes and degrades the built environment. This article asks five questions about the effect of medical fragility, health risk awareness, health and financial impacts of the pandemic, and the availability of noncongregate shelters on evacuation and sheltering behavior. The empirical analysis uses data from a survey of 2200 households conducted during the COVID-19 pandemic to gauge risk perceptions under the compound threat of a hurricane and pandemic. Takeaways from our findings have significant implications for managers and policymakers and indicate, first, that medically fragile households are more likely to evacuate than nonmedically fragile households. Second, households with health concerns about the pandemic are more likely to evacuate regardless of medical fragility. Third, the expected sheltering of these segments varies depending on the facilities provided by the authorities. Anticipating the behavior of population groups allows managers to deploy technology that supports effective resource configuration and coordination and provides effective emergency service during evacuation planning and execution.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443024","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":"Horizontal Integration Through Knowledge Sharing in the Supply Chain Under Uncertainty","authors":"Mostafa Jafari;Shayan Naghdi Khanachah;Peyman Akhavan","doi":"10.1109/TEM.2024.3459609","DOIUrl":"https://doi.org/10.1109/TEM.2024.3459609","url":null,"abstract":"A robust knowledge-sharing network is designed for horizontal integration under disruption risks and epistemic uncertainties by introducing a novel optimization model using a fuzzy robust possibilistic programming approach to optimize knowledge sharing among supply chain members with varying knowledge levels. In this article, we aim to identify an efficient knowledge-sharing network, thereby reducing costs and enhancing suppliers' knowledge levels. By challenging the common assumption that companies with higher knowledge levels are always the primary contributors and have more added value for cooperation, this study highlights their potential inefficiencies and higher sharing costs. The proposed model promotes the integration of diverse knowledge sources within the supply chain, emphasizing the importance of horizontal integration. It advocates for comprehensive knowledge sharing among suppliers and organizations to enhance supply chain efficiency, collaboration, and performance while reducing costs. Quantitative analysis demonstrates that knowledge sharing significantly increases supply chain integration, and the study endorses the use of multiobjective mathematical programming for optimal decision making in scheduling. The results emphasize the value of collaborating with closely aligned companies to minimize knowledge-sharing costs and enhance broader organizational collaboration. Furthermore, the introduced model proposes practical execution scheduling and knowledge-sharing processes, as evidenced by a case study, leading to effective execution scheduling, reduced costs, improved communication, strengthened collaboration, and increased supply chain efficiency. Overall, this article contributes to research in supply chain management and knowledge-sharing models, enabling them to navigate constraints and market dynamics to improve supply chain performance through effective knowledge sharing and collaboration.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142324242","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":"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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}