IEEE Transactions on Engineering Management最新文献_第10页

Enablers for Implementing Big Data Analytics in the Healthcare Industry: Prioritization, Classification, and Implications for Sustainable Competitive Advantages 医疗保健行业实施大数据分析的有利因素：优先顺序、分类及对可持续竞争优势的影响

IF 4.6 3区管理学

IEEE Transactions on Engineering Management Pub Date : 2024-07-22 DOI: 10.1109/TEM.2024.3416409

Anish Aman;Himanshu Gupta;Manjeet Kharub;Olivia McDermott

{"title":"Enablers for Implementing Big Data Analytics in the Healthcare Industry: Prioritization, Classification, and Implications for Sustainable Competitive Advantages","authors":"Anish Aman;Himanshu Gupta;Manjeet Kharub;Olivia McDermott","doi":"10.1109/TEM.2024.3416409","DOIUrl":"https://doi.org/10.1109/TEM.2024.3416409","url":null,"abstract":"In the face of an overwhelming influx of data, the healthcare sector is confronted with a critical question: How can it effectively leverage the capabilities of Big Data analytics (BDA) to attain a sustainable competitive advantage? This inquiry is not only timely but also crucial for an industry facing increasing demands amid constrained resources. To address this pivotal issue, the present study utilizes a composite of rigorous methodologies—including the best worst method, interpretive structural modeling, and interpretive structural—cross impact matrix multiplication—to assemble a hierarchical relationship among 4 main enablers and 12 corresponding subenablers. The study's findings reveal that “Technological” and “Organizational” enablers serve as key elements for successful BDA implementation, while “Socio-Cultural” and “Market and Customer” enablers play secondary yet important roles. This hierarchical structure serves as a foundational guide for policy formulation, enabling healthcare organizations to strategize with increased precision. The study strongly advocates for a strategic shift in policy: healthcare organizations should develop comprehensive frameworks that focus on these principal enablers and employ robust metrics for ongoing evaluation. By adopting this approach, organizations can more effectively harness BDA capabilities, thereby not only enhancing their competitive positioning but also improving operational efficiency and patient care outcomes. Through its rigorous methodological approach and actionable recommendations, this research contributes a significant academic reference to the rapidly expanding discourse on BDA-enabled healthcare.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141964798","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

Big Data Analytics Capability, Dynamic Capability, and Firm Performance: The Moderating Effect of IT–Business Strategic Alignment 大数据分析能力、动态能力与企业绩效：信息技术与业务战略一致性的调节效应

IF 4.6 3区管理学

IEEE Transactions on Engineering Management Pub Date : 2024-07-19 DOI: 10.1109/TEM.2024.3429648

Dong Wu;Xinyi Lin;Shivam Gupta;Arpan Kumar Kar

{"title":"Big Data Analytics Capability, Dynamic Capability, and Firm Performance: The Moderating Effect of IT–Business Strategic Alignment","authors":"Dong Wu;Xinyi Lin;Shivam Gupta;Arpan Kumar Kar","doi":"10.1109/TEM.2024.3429648","DOIUrl":"https://doi.org/10.1109/TEM.2024.3429648","url":null,"abstract":"As Big Data applications become popular, firms harness their Big Data analytics capabilities for environmental insights. Literature suggests a positive correlation between these capabilities and firm performance, with dynamic capability potentially mediating this relationship. However, the mechanism by which Big Data analytics capabilities transform into dynamic capabilities remains underexplored. Additionally, the role of information technology (IT)–business strategic alignment as a boundary condition is not well-defined. We aim to address these gaps by exploring the impact of Big Data analytics capabilities on firm performance, the mediating function of dynamic capability, and the moderating influence of IT–business strategic alignment. A survey of 352 firms was conducted. Findings revealed a positive impact of Big Data analytics capabilities on firm performance with dynamic capability mediating this effect. IT–business strategic alignment was found to enhance the relationship between Big Data analytics capabilities and dynamic capability, thereby influencing firm performance. We contribute in Big Data analytics capabilities and dynamic capabilities by revealing that consensus problems within multiagent system or Big Data analysis platforms impede the effective transformation of Big Data analytics capability into organizational capabilities. Besides, this article incorporates insights from dynamic capability theory by exploring key predictors of IT–business strategic alignment in overcoming consensus problems and improving the likelihood of success.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141965050","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

Teamwork Culture, Employee Stock Ownership Plan, and Firm Open Innovation: Empirical Evidence From Novel Measures Based on Machine Learning 团队合作文化、员工持股计划与企业开放式创新：基于机器学习的新测量方法提供的经验证据

IF 4.6 3区管理学

IEEE Transactions on Engineering Management Pub Date : 2024-07-19 DOI: 10.1109/TEM.2024.3431014

Xin Bao;Baiqing Sun;Meini Han;Han Lin;Qiping Wang

引用次数: 0

Pairing AI and Sustainability: Envisioning Entrepreneurial Initiatives for Virtuous Twin Paths 将人工智能与可持续性结合起来：构想创业计划，实现良性双生路径

IF 4.6 3区管理学

IEEE Transactions on Engineering Management Pub Date : 2024-07-18 DOI: 10.1109/TEM.2024.3428913

Francesco Paolo Appio;Federico Platania;Celina Toscano Hernandez

引用次数: 0

Online Information Serves Offline Sales: Knowledge Graph-Based Attribute Preference Learning 在线信息服务于离线销售：基于知识图谱的属性偏好学习

IF 4.6 3区管理学

IEEE Transactions on Engineering Management Pub Date : 2024-07-18 DOI: 10.1109/TEM.2024.3430380

Bin Zhu;Panpan Xu;Peijia Ren

{"title":"Online Information Serves Offline Sales: Knowledge Graph-Based Attribute Preference Learning","authors":"Bin Zhu;Panpan Xu;Peijia Ren","doi":"10.1109/TEM.2024.3430380","DOIUrl":"https://doi.org/10.1109/TEM.2024.3430380","url":null,"abstract":"The combination of online and offline shopping is becoming more common. We define the scenario where online information serves offline sales as online–offline scenario. Online and offline shopping each has its own advantages and challenges, making it necessary to integrate the strengths of both online and offline channels. Online platforms can discover consumers' attribute preferences through their online generated data. Since consumers maintain coherent attribute preferences over a period of time in both online and offline, offline salesmen can use the attribute preferences transferred from online platforms to create personalized marketing plans. In this online–offline scenario, it is crucial to learn consumer attribute preferences. We propose a knowledge graph-based multiattribute preference learning method (KG-APL), which integrates knowledge graph (KG) and multiattribute decision-making (MADM) theory. Based on MADM theory, KG-APL can learn multilevel attribute preferences in a data-driven way and provide an explanatory analysis for attribute preferences. The explanations rely on both the MADM theory and rich side information about product contained in the KG. Specifically, MADM describes the consumer's decision-making process and KG provides a hierarchical structure from products to attributes and subattributes. To verify its effectiveness and robustness, we use randomly generated data for experiments and real-life data for simulated decision making. Our article provides insight into the way of achieving integration between online and offline channels and offers theoretical and methodological support in enhance online–offline purchase services.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141964793","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

Cryptocurrency Price Bubble Detection Using Log-Periodic Power Law Model and Wavelet Analysis 利用对数周期幂律模型和小波分析检测加密货币价格泡沫

IF 4.6 3区管理学

IEEE Transactions on Engineering Management Pub Date : 2024-07-17 DOI: 10.1109/TEM.2024.3427647

Junhuan Zhang;Haodong Wang;Jing Chen;Anqi Liu

引用次数: 0

Unraveling the Drivers of Construction Safety Knowledge Sharing on Online Social Media in Engineering Management 揭示工程管理中在线社交媒体上建筑安全知识共享的驱动因素

IF 4.6 3区管理学

IEEE Transactions on Engineering Management Pub Date : 2024-07-17 DOI: 10.1109/TEM.2024.3430091

Wai Ki Sung;Yuying Wang;Le Wang;Xin Luo

{"title":"Unraveling the Drivers of Construction Safety Knowledge Sharing on Online Social Media in Engineering Management","authors":"Wai Ki Sung;Yuying Wang;Le Wang;Xin Luo","doi":"10.1109/TEM.2024.3430091","DOIUrl":"https://doi.org/10.1109/TEM.2024.3430091","url":null,"abstract":"Despite the construction engineering industry's efforts in training and safety through government and organizational investments, high accident rates persist, highlighting the need for improved construction safety management. Research has begun to focus on knowledge management using AI and internal organizational sharing, but the use of online social media for cross-organizational sharing remains underexplored. Our study delves into the role of social media in disseminating construction safety knowledge and the motivations behind this sharing. Employing the social cognitive model, we identified five key factors impacting online knowledge sharing: community identity, social awareness, knowledge sharing self-efficacy, altruism, and the intention to share knowledge. We gathered quantitative data through a survey with 741 valid responses, which revealed that community identity significantly boosts knowledge sharing self-efficacy and social awareness, and that self-efficacy, altruism, and the desire to share are strong predictors of knowledge sharing behavior. The study enriches the theoretical framework of knowledge sharing by offering new insights into the roles of social influence and altruism in knowledge-sharing behaviors. Practically, it advises construction industry professionals on strategies to promote knowledge sharing, especially on how to leverage online platforms and communities to improve the dissemination and uptake of safety knowledge.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142117890","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

Does Digital Transformation Stimulate Breakthrough Innovation? Evidence From Chinese Firms 数字化转型能否激发突破性创新？来自中国企业的证据

IF 4.6 3区管理学

IEEE Transactions on Engineering Management Pub Date : 2024-07-16 DOI: 10.1109/TEM.2024.3428728

Ziyang Wang;Chao Fang;Xiaoxiao Liu

{"title":"Does Digital Transformation Stimulate Breakthrough Innovation? Evidence From Chinese Firms","authors":"Ziyang Wang;Chao Fang;Xiaoxiao Liu","doi":"10.1109/TEM.2024.3428728","DOIUrl":"https://doi.org/10.1109/TEM.2024.3428728","url":null,"abstract":"Digital transformation (DT) strategies have become crucial for enterprises, playing a pivotal role in redefining their value propositions, evolving business models, and driving innovation. Despite this importance, the impact of DT on breakthrough innovations has not been thoroughly examined. This article addresses this gap by analyzing data from a sample of Chinese listed firms to examine how DT, across both technical and business dimensions, influences breakthrough innovation. Our findings indicate that DT positively impacts breakthrough innovation, predominantly driven by its technical aspect. To understand the mechanisms at play, we identify two key effects. First, the absorptive capacity effect describes how companies strengthen their ability to assimilate and integrate knowledge, thus further stimulating breakthrough innovation. Second, the government subsidies effect shows how firms undergoing DTs gain increased government backing, thereby enhancing breakthrough innovation. The tests of these mechanisms confirm their significant influence. Moreover, taking into account the institutional context, we find that DT fosters a more conducive environment for breakthrough innovation in high-tech industries and regions with low marketization. These findings present important implications for both research and practice in balancing technological adoption with innovation management.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141964796","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

Mapping the Complexity of Net Zero Transition Through a System of Digital Twin Systems 通过数字孪生系统绘制 "零净过渡 "的复杂图景

IF 4.6 3区管理学

IEEE Transactions on Engineering Management Pub Date : 2024-07-16 DOI: 10.1109/TEM.2024.3428641

Eleni Papadonikolaki;Chimay J. Anumba

{"title":"Mapping the Complexity of Net Zero Transition Through a System of Digital Twin Systems","authors":"Eleni Papadonikolaki;Chimay J. Anumba","doi":"10.1109/TEM.2024.3428641","DOIUrl":"https://doi.org/10.1109/TEM.2024.3428641","url":null,"abstract":"The upsurge of digitalization in many sectors has been associated with better environmental outcomes. Recent policy change and international convergence has shown Net Zero (NZ) vision as a means of controlling global greenhouse gas emissions. This article focuses on construction sector and the complex transition to NZ through digital twins (DTs). It does so via a system thinking approach, 53 interviews, and 2 focus groups with DT experts. The key factors of this dual “digital and green” transition are breaking down silos, collaborating across the supply chain and the need for a data-oriented approach in analyzing input, processing, and output of the DTs. Apart from unravelling the factors on how individual (asset) DTs can support NZ, their aggregates in a connected DT system of systems are also crucial to addressing the complexity of this transition at a larger scale. The article also offers new insights on the orchestrators of such system of DT systems and their governance mechanisms in meeting NZ. Additionally, one emergent finding relates to the evolution of associated concepts and terminologies. By identifying the complexity factors, this article also contributes to the management of increased risk that accompanies growing complexity.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141966224","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

Institutional Stance Filtering in Digitalization Opportunity-Making 数字化机遇制造中的机构立场过滤

IF 4.6 3区管理学

IEEE Transactions on Engineering Management Pub Date : 2024-07-16 DOI: 10.1109/TEM.2024.3428833

Nicola Barron;Mark Palmer;Robbie Quinn

引用次数: 0