IEEE Transactions on Engineering Management最新文献

Data-Driven Identification of Industrial Clusters: A Patent Analysis Approach 数据驱动的产业集群识别：专利分析方法

IF 4.6 3区管理学

IEEE Transactions on Engineering Management Pub Date : 2024-11-07 DOI: 10.1109/TEM.2024.3493627

Wenguang Lin;Ting Wang;Zhizhen Chen;Renbin Xiao

{"title":"Data-Driven Identification of Industrial Clusters: A Patent Analysis Approach","authors":"Wenguang Lin;Ting Wang;Zhizhen Chen;Renbin Xiao","doi":"10.1109/TEM.2024.3493627","DOIUrl":"https://doi.org/10.1109/TEM.2024.3493627","url":null,"abstract":"Accurate identification of industrial clusters (IIC) serves as a reference for regional economic policymaking and enterprise development decision-making. Although data-driven methods have been extensively used in previous studies to support objective and effective work, both the data sources and research algorithms have significant shortcomings for IIC. To address these challenges, this article proposes a novel research framework that integrates patent mining and machine learning. Patents, with their quantifiable knowledge attributes and accessibility from public databases, are particularly suited for macrolevel analysis of innovation activities, providing robust support for identifying and analyzing clusters on a national scale, especially knowledge-intensive ones. This article introduces an improved density-based parameter adaptive algorithm designed to effectively carry out IIC based on the geographical location of patent applicants. Based on spatial cluster types defined by Markusen (1996), target clusters are classified using patent analysis. Four quantitative indexes–scale, output, efficiency, and quantity–are proposed to evaluate clusters based on their spatial structure and industrial organization. The practical application is demonstrated through a case study of China's flexible electronics industry. In addition, the Silhouette Coefficient index is employed to compare the effectiveness of the proposed algorithm against other methods. This article advances the theory of IIC, and provides foundation for scholars, calling for empirical research on industrial clusters from the perspective of individual enterprises. It also provides practical guidance for enterprises and policymakers on the application of IIC.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15422-15437"},"PeriodicalIF":4.6,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142679395","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}

引用次数: 0

Cyber Security for Cyber–Physical Systems in Critical Infrastructures: Bibliometrics Analysis and Future Directions 关键基础设施中网络物理系统的网络安全：文献计量学分析与未来方向

IF 4.6 3区管理学

IEEE Transactions on Engineering Management Pub Date : 2024-10-31 DOI: 10.1109/TEM.2024.3489273

Mahdad Pourmadadkar;Marianna Lezzi;Angelo Corallo

{"title":"Cyber Security for Cyber–Physical Systems in Critical Infrastructures: Bibliometrics Analysis and Future Directions","authors":"Mahdad Pourmadadkar;Marianna Lezzi;Angelo Corallo","doi":"10.1109/TEM.2024.3489273","DOIUrl":"https://doi.org/10.1109/TEM.2024.3489273","url":null,"abstract":"Cyber–physical systems (CPSs) are being increasingly connected to the physical world, making them attractive targets for cyber-attacks. The consequences of CPS cyber threats are even more drastic in critical infrastructures (CIs). This issue has triggered a surge in academic publications in this field within the past decade only. Recognizing the necessity of a comprehensive analysis of academic documents published on this topic, this article intends to conduct a bibliometric analysis of CPSs cyber security in CIs. Gathering a total of 1649 documents from the Scopus and Web of Science databases, a performance analysis is first carried out through a set of performance criteria. Then, a scientific mapping is performed based on keyword co-occurrence to visualize the knowledge area for further inference. As a result, seven thematic clusters were discovered and discussed in detail. Furthermore, an agenda for future research is identified based on the results of the bibliometric analysis, providing scope to advance the knowledge area. The outcomes of this article may be used by researchers and cyber security practitioners to have an illuminated and structured view of all the research conducted on CPSs cyber security in CIs and identify paths for further investigations on the topic.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15405-15421"},"PeriodicalIF":4.6,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142679394","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}

引用次数: 0

Catch-Up in Complex Products and Systems: A Fuzzy-Set Qualitative Comparative Analysis of China's Equipment Manufacturing Industry 复杂产品和系统的赶超：中国装备制造业的模糊集定性比较分析

IF 4.6 3区管理学

IEEE Transactions on Engineering Management Pub Date : 2024-10-30 DOI: 10.1109/TEM.2024.3488183

Han Huang;Jie Xiong;Lu Xu;Zhe Yuan;Chun Liu

{"title":"Catch-Up in Complex Products and Systems: A Fuzzy-Set Qualitative Comparative Analysis of China's Equipment Manufacturing Industry","authors":"Han Huang;Jie Xiong;Lu Xu;Zhe Yuan;Chun Liu","doi":"10.1109/TEM.2024.3488183","DOIUrl":"https://doi.org/10.1109/TEM.2024.3488183","url":null,"abstract":"The rapid advancement of Chinese complex products and systems (CoPSs) enterprises marks their transition into a post-catch-up phase, challenging the conventional theories of catch-up. In this article, we employ a configurational approach to explore the intricate relationships between catch-up environments and strategies, specifically focusing on the distinct paths of state-owned enterprises (SOEs) and non-state-owned enterprises (non-SOEs) within the CoPS sector. Utilizing fuzzy-set qualitative comparative analysis with data sourced from the EU industrial research and development (R&D) investment scoreboard (2017–2020) and corresponding Chinese-listed companies, our research identifies diverse catch-up configurations for SOEs, characterized by “complexity adoption” and “complexity decipher” models. In contrast, non-SOEs encounter challenges in strategically adapting to environmental shifts, which affects their catch-up strategies. Our findings emphasize the critical role of strategic alignment with external conditions, technological learning, and resource utilization in achieving successful catch-up in CoPS. These configurations enable SOEs to effectively align internal resources with external opportunities, resulting in superior catch-up performance. In contrast, non-SOEs encounter significant obstacles in adapting to environmental changes and optimizing resource utilization, which hinders their ability to attain similar successes. Moreover, our study sheds light on specific challenges faced by non-SOEs in responding to environmental shifts. This enriched understanding provides valuable theoretical insights into the catch-up of latecomer CoPS enterprises and has practical implications for both policymakers and business practitioners.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15375-15389"},"PeriodicalIF":4.6,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142672015","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}

引用次数: 0

A Decision Framework With q-Rung Fuzzy Preferences for Ranking Barriers Affecting Clean Energy Utilization Within Healthcare Industry 利用 q 级模糊偏好排序影响医疗保健行业清洁能源利用的障碍的决策框架

IF 4.6 3区管理学

IEEE Transactions on Engineering Management Pub Date : 2024-10-30 DOI: 10.1109/TEM.2024.3488325

Raghunathan Krishankumar;Dhruva Sundararajan;Muhammet Deveci;K. S. Ravichandran;Xin Wen;Bilal Bahaa Zaidan

{"title":"A Decision Framework With q-Rung Fuzzy Preferences for Ranking Barriers Affecting Clean Energy Utilization Within Healthcare Industry","authors":"Raghunathan Krishankumar;Dhruva Sundararajan;Muhammet Deveci;K. S. Ravichandran;Xin Wen;Bilal Bahaa Zaidan","doi":"10.1109/TEM.2024.3488325","DOIUrl":"https://doi.org/10.1109/TEM.2024.3488325","url":null,"abstract":"In this article, we aim to rank barriers hindering clean energy adoption within the healthcare industry by proposing a new framework with q-rung orthopair fuzzy data (q-ROFD). Energy is paramount in health industry, and it is estimated by the World Health Organization that nearly a billion people are treated globally with limited/no electricity. United Nation strongly recommends cutting dependencies on fossil fuels, but to meet demand, clean energy is focused. Studies on clean energies reveal that direct adoption is tough, owing to diverse barriers and ranking these barriers will provide policymakers clarity on the strategic plans. Existing studies reveal gaps in uncertainty modeling by not adequately exploring orthopair variants, human intervention reduction by failing to methodically determine diverse decision parameters, consideration of subjective attitude and interactions among entities that are essential for experts and attributes, and accounting for attribute type and yielding ranks comparable with a human decision. Motivated by the gaps, in this article, a combined q-ROFD model is presented where weights of attributes are determined via criteria importance through intercriteria correlation and rank sum and experts’ weights are obtained by rank sum. A ranking algorithm is developed with CODAS formulation for determining the barriers’ grades with risk aversion trait. The significance of the study lies in rational ranking of barriers, reduced human intervention, and methodical determination of decision parameters. The usefulness of the model is testified via a case study of barrier ranking within the Indian healthcare industry and comparison/sensitivity studies reveal the pros and cons of the developed model.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15349-15362"},"PeriodicalIF":4.6,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142672124","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}

引用次数: 0

Can the Input of Data Elements Improve Manufacturing Productivity? Effect Measurement and Path Analysis 数据元素的输入能否提高生产率？效果测量和路径分析

IF 4.6 3区管理学

IEEE Transactions on Engineering Management Pub Date : 2024-10-28 DOI: 10.1109/TEM.2024.3487232

Yang Liu;Zuo Yuxiao

{"title":"Can the Input of Data Elements Improve Manufacturing Productivity? Effect Measurement and Path Analysis","authors":"Yang Liu;Zuo Yuxiao","doi":"10.1109/TEM.2024.3487232","DOIUrl":"https://doi.org/10.1109/TEM.2024.3487232","url":null,"abstract":"We first used text analysis methods to define and measure the level of data element input. We qualitatively demonstrated that data element input can improve total factor productivity (TFP) by constructing a new classical economic growth model by adding data elements. On this basis, we built a translog stochastic frontier model to incorporate data elements into the production function and TFP measurement model. Using data from Chinese manufacturing listed companies from 2010 to 2023, we quantitatively measured and dynamically evaluated the impact of data element input on manufacturing TFP and the role of technical efficiency and technological progress. The results revealed the following: 1) Data element input as a whole is beneficial for improving manufacturing TFP, but the main path is the improvement of technical efficiency. Additionally, data processing and application significantly improve TFP, whereas data acquisition does not. 2) The impact of digitalization on the current industrial structure has not affected technological progress, but it has restricted improvements in technical efficiency. Data elements are increasingly becoming the critical material basis for the manufacturing industry's digital transformation. In this context, this study has the following practical value: 1) It helps better identify the critical path of data elements to empower manufacturing industry TFP to implement more targeted digital transformation in practice; and 2) it contributes to a more comprehensive understanding of the impact of digitalization on the manufacturing industry structure to fully leverage the positive role of data elements in enhancing enterprise productivity.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15320-15332"},"PeriodicalIF":4.6,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600230","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}

引用次数: 0

A Taxonomy-Based Data Model for Assessing Engineering Skills in an Organizational Context 基于分类标准的数据模型，用于评估组织背景下的工程技能

IF 4.6 3区管理学

IEEE Transactions on Engineering Management Pub Date : 2024-10-25 DOI: 10.1109/TEM.2024.3486812

João Gregório;Russell Miller;Ioannis Afxentiou;Jean Laurent-Hippolyte;Paul Morantz

{"title":"A Taxonomy-Based Data Model for Assessing Engineering Skills in an Organizational Context","authors":"João Gregório;Russell Miller;Ioannis Afxentiou;Jean Laurent-Hippolyte;Paul Morantz","doi":"10.1109/TEM.2024.3486812","DOIUrl":"https://doi.org/10.1109/TEM.2024.3486812","url":null,"abstract":"A taxonomy-based data model is proposed to create a knowledge system for managing engineering skills within an organization, motivated by the need to balance organizational expertise requirements and availability. The model, adapted from the “European Skills, Competences, Qualifications, and Occupations” framework, is designed to categorize and evaluate skills relevant to the engineering department of the National Physical Laboratory. This allows extraction of quantitative data on individual staff members' skills and competency levels, and the necessary skills for specific Job Title and Job Role combinations. It distinguishes between “Job Titles,” official job designations, and “Job Roles,” unofficial designations categorizing staff according to their work areas, allowing the model to conform with inherent organizational rigiditiy. The model can cross-reference information using specific queries, such as extracting skills from specific individuals and assessing if they meet their current job functions. This model enhances existing skill management frameworks by allowing for a traceable pathway for skill allocation, allowing for future expansion by including other departments. Integrating validation procedures to assess staff skills, such as the inclusion of proof attached to skills, can also be considered. It offers operational benefits like enhanced capability planning, informed staff development, optimized resource allocation, and improved training programmes.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15363-15374"},"PeriodicalIF":4.6,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142672166","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}

引用次数: 0

Modeling and Simulation Analysis of Influencing Factors of MES Implementation in Zero Defect Management Enterprises in Digital Transformation 数字化转型中零缺陷管理企业实施 MES 的影响因素建模与仿真分析

IF 4.6 3区管理学

IEEE Transactions on Engineering Management Pub Date : 2024-10-24 DOI: 10.1109/TEM.2024.3486282

Yu Guo;Shan Liao;Shi Yin;Giulia Bruno;Deming Zhang

{"title":"Modeling and Simulation Analysis of Influencing Factors of MES Implementation in Zero Defect Management Enterprises in Digital Transformation","authors":"Yu Guo;Shan Liao;Shi Yin;Giulia Bruno;Deming Zhang","doi":"10.1109/TEM.2024.3486282","DOIUrl":"https://doi.org/10.1109/TEM.2024.3486282","url":null,"abstract":"Digital management system is widely used in the business activities of enterprises. Practice has proved that the implementation of the manufacturing execution system (MES) can better monitor and manage the production process, improve the production efficiency of enterprises, and effectively realize zero defect management (ZDM). Against this background, the influencing factors of implementing MES in ZDM enterprises in digital transformation were obtained by using the literature extraction-Delphi method, and the relationship between the factors was analyzed by using the system dynamics simulation model in this study. It is found that different from the existing research works on the implementation of MES in enterprises, staff preparation and level of information sharing are the most influential factors and play an important role in the implementation of MES in ZDM enterprises. Equipment preparation and client preparation followed closely, with supplier implementation team and scale infrastructure conditions playing a key role in providing capability support. This finding provides the direction for enterprises to improve the relevant implementation measures in time to ensure the effective implementation of MES in ZDM enterprises, and also provides a breakthrough for relevant researchers to find valuable research fields.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15306-15319"},"PeriodicalIF":4.6,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600372","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}

引用次数: 0

Editorial: Unveiling the Digital Transformation of Organizations Across Multiple Levels of Analysis 社论：从多个分析层面揭示组织的数字化转型

IF 4.6 3区管理学

IEEE Transactions on Engineering Management Pub Date : 2024-10-23 DOI: 10.1109/TEM.2023.3330042

Antonio Messeni Petruzzelli;Gianluca Murgia;Eva Panetti;Adele Parmentola

引用次数: 0

How Does Technological Crowding Affect Exploratory Innovation? Considering the Moderating Role of Technological Superiority 技术排挤如何影响探索性创新？考虑技术优势的调节作用

IF 4.6 3区管理学

IEEE Transactions on Engineering Management Pub Date : 2024-10-23 DOI: 10.1109/TEM.2024.3485235

Chia-Chi Chang;Phuong-Dung Thi Nguyen

{"title":"How Does Technological Crowding Affect Exploratory Innovation? Considering the Moderating Role of Technological Superiority","authors":"Chia-Chi Chang;Phuong-Dung Thi Nguyen","doi":"10.1109/TEM.2024.3485235","DOIUrl":"https://doi.org/10.1109/TEM.2024.3485235","url":null,"abstract":"This article anchors itself in knowledge network theory and rivalry theory to explore the antecedents of exploration by examining the possibility of technological crowding, that is, a firm position in crowded technological fields, as the enabler of firms’ exploratory innovation performance. For this purpose, we adopted regression analysis for panel data with fixed effects and considered the data of 4100 firm-year observations of Taiwanese listed companies in the electronics industry from 2000 to 2021. The findings suggest that technological crowding urges firms to pursue exploration to ease heightened competition intensity and crowd out their competitors. Recalling the literature on the competency trap phenomenon in which some dominant firms may exhibit technological superiority underperformance, we further propose that the dark side of technological superiority is more visible when firms are positioned in crowded technological areas. Specifically, firms with stronger combinatorial capabilities or greater technological prestige refrain from investing in exploration because they are tied with high couplings between their homogeneous knowledge elements and indulge themselves in existing success. Our findings remain robust after adjusting the window of research and using the negative binomial regression with fixed effects based on the alternative measure of exploratory innovation. This article contributes significantly to the literature on technological position and knowledge networks by shedding light on the critical role of technological crowding in propelling firms’ exploration efforts. Our results also offer significant implications for executives in dominant firms and policymakers to become more aware of the competency trap and seek ways to span technological boundaries.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15390-15404"},"PeriodicalIF":4.6,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142679345","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}

引用次数: 0

Robust Networks, Pivotal Patents: Identifying and Assessing Key Technological Influencers 强大的网络，关键的专利：识别和评估关键技术影响者

IF 4.6 3区管理学

IEEE Transactions on Engineering Management Pub Date : 2024-10-23 DOI: 10.1109/TEM.2024.3485751

Tao Wang;Chao Yu;Jun Huang;Hsin-Ning Su

引用次数: 0