Pub Date : 2024-10-23DOI: 10.1109/TEM.2024.3485751
Tao Wang;Chao Yu;Jun Huang;Hsin-Ning Su
In a world of swiftly changing technology and external challenges, predicting the role of core patents in technology systems' strength and power is vital. This research presents a method that combines robustness analysis of patent citation networks with core patent identification, assessing their global industrial technology innovation significance. It aims to identify patents key to network stability and external change adaptation, understanding their impact in dynamic tech environments. Using network robustness, the study examines connectivity, efficiency, and clustering in patent citation networks, assessing patent node importance based on structural feature changes postremoval. The study employs patents from five technological domains as case studies, ranking the importance of nodes and exploring how patent attributes affect these rankings. This research contributes by merging patent network robustness with valuation, supporting IP strategies and tech management policies, and offering insights into tech system complexity and dynamism.
{"title":"Robust Networks, Pivotal Patents: Identifying and Assessing Key Technological Influencers","authors":"Tao Wang;Chao Yu;Jun Huang;Hsin-Ning Su","doi":"10.1109/TEM.2024.3485751","DOIUrl":"https://doi.org/10.1109/TEM.2024.3485751","url":null,"abstract":"In a world of swiftly changing technology and external challenges, predicting the role of core patents in technology systems' strength and power is vital. This research presents a method that combines robustness analysis of patent citation networks with core patent identification, assessing their global industrial technology innovation significance. It aims to identify patents key to network stability and external change adaptation, understanding their impact in dynamic tech environments. Using network robustness, the study examines connectivity, efficiency, and clustering in patent citation networks, assessing patent node importance based on structural feature changes postremoval. The study employs patents from five technological domains as case studies, ranking the importance of nodes and exploring how patent attributes affect these rankings. This research contributes by merging patent network robustness with valuation, supporting IP strategies and tech management policies, and offering insights into tech system complexity and dynamism.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15254-15277"},"PeriodicalIF":4.6,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142594978","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}
Pub Date : 2024-10-22DOI: 10.1109/TEM.2024.3484664
Peng He;Zhen-Song Chen;Abbas Mardani;Henry Xu
Given the increasing societal emphasis on corporate social responsibility (CSR), a critical strategic decision facing retailers is whether to introduce green products when distributing the manufacturer's nongreen ones. To address this issue, this article mainly considers two scenarios: the regular or green-supportive manufacturer. Furthermore, we develop four mathematical models to determine the retailer's green item introduction decisions. The research findings indicate that the manufacturer's CSR would significantly impact both firms’ pricing decisions and may change market distribution. Additionally, the retailer introducing green items will reduce the wholesale/retail prices of nongreen items but may foster an augmentation in overall demand. It is noteworthy that the retailer introducing green items does not necessarily cannibalize the sales of nongreen items; instead, it may even enhance their sales. Significantly, this strategy can benefit the green-supportive manufacturer if the greening cost is relatively low. These implications underscore that incentivizing manufacturers to care more about environmentally conscious consumers can serve as a viable strategy for promoting sustainable development initiatives.
{"title":"Should a Retailer Introduce Green Items in Socially Responsible Supply Chains? A Game-Theoretic Analysis","authors":"Peng He;Zhen-Song Chen;Abbas Mardani;Henry Xu","doi":"10.1109/TEM.2024.3484664","DOIUrl":"https://doi.org/10.1109/TEM.2024.3484664","url":null,"abstract":"Given the increasing societal emphasis on corporate social responsibility (CSR), a critical strategic decision facing retailers is whether to introduce green products when distributing the manufacturer's nongreen ones. To address this issue, this article mainly considers two scenarios: the regular or green-supportive manufacturer. Furthermore, we develop four mathematical models to determine the retailer's green item introduction decisions. The research findings indicate that the manufacturer's CSR would significantly impact both firms’ pricing decisions and may change market distribution. Additionally, the retailer introducing green items will reduce the wholesale/retail prices of nongreen items but may foster an augmentation in overall demand. It is noteworthy that the retailer introducing green items does not necessarily cannibalize the sales of nongreen items; instead, it may even enhance their sales. Significantly, this strategy can benefit the green-supportive manufacturer if the greening cost is relatively low. These implications underscore that incentivizing manufacturers to care more about environmentally conscious consumers can serve as a viable strategy for promoting sustainable development initiatives.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15224-15235"},"PeriodicalIF":4.6,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595098","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}
Pub Date : 2024-10-22DOI: 10.1109/TEM.2024.3485088
Baoqiang Zhan;Yongli Li;Chuang Wei;Chong Wu;Eric W. T. Ngai
Firms increasingly rely on the third-party platforms to manage customer complaints. In this article, we explore the impact of complaints on firms’ idiosyncratic risk by considering both the valence and channel characteristics of complaints. Through textual analysis, complaints are categorized into four types based on the intersection of two dimensions: the valence (mild or severe) of the complaint and the channel (firm or platform) through which the complaint is lodged. Empirical analysis is conducted to test the hypotheses. The results reveal that firms’ idiosyncratic risk rises after severe complaints but decreases after mild complaints. Moreover, while mild platform-channel complaints increase risk, severe platform-channel complaints reduce risk. This study highlights the disparate impacts of the channel and valence of complaints on manufacturing and service firms. This research contributes to the literature on online complaints and the marketing–finance interface, offering valuable insights for firms seeking to mitigate their idiosyncratic risk through complaint management strategies.
{"title":"Evaluating the Impact of Complaints on Firms’ Idiosyncratic Risk: The Roles of Valance and Channel","authors":"Baoqiang Zhan;Yongli Li;Chuang Wei;Chong Wu;Eric W. T. Ngai","doi":"10.1109/TEM.2024.3485088","DOIUrl":"https://doi.org/10.1109/TEM.2024.3485088","url":null,"abstract":"Firms increasingly rely on the third-party platforms to manage customer complaints. In this article, we explore the impact of complaints on firms’ idiosyncratic risk by considering both the valence and channel characteristics of complaints. Through textual analysis, complaints are categorized into four types based on the intersection of two dimensions: the valence (mild or severe) of the complaint and the channel (firm or platform) through which the complaint is lodged. Empirical analysis is conducted to test the hypotheses. The results reveal that firms’ idiosyncratic risk rises after severe complaints but decreases after mild complaints. Moreover, while mild platform-channel complaints increase risk, severe platform-channel complaints reduce risk. This study highlights the disparate impacts of the channel and valence of complaints on manufacturing and service firms. This research contributes to the literature on online complaints and the marketing–finance interface, offering valuable insights for firms seeking to mitigate their idiosyncratic risk through complaint management strategies.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15333-15348"},"PeriodicalIF":4.6,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600373","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}
Entrepreneurs traditionally use “learning-by-doing” and “learning-by-thinking” as alternative approaches to iteratively build business models for their new ventures. However, both approaches face criticism in how they address novelty and uncertainty, which are crucial to successful entrepreneurship. While generative AI (GenAI) is increasingly used in entrepreneurial tasks, the practices through which it becomes a learning resource for entrepreneurs remain unexplored. Based on a qualitative study, we present a process model that illustrates how entrepreneurs incorporate GenAI into business model design through five resourcing practices. These practices transform GenAI into a valuable resource for facilitating learning during the design process. This approach, which we term “learning-by-conversing,” introduces a generative startup methodology to complement the lean startup model. We distinguish two modes of learning by conversing—reflexive learning and confirmatory learning—based on how novice and experienced entrepreneurs engage with it. By proposing a learning approach that integrates GenAI with entrepreneurial efforts, we bridge the “thinking” versus “doing” debate in business model generation and deepen our understanding of GenAI's role in entrepreneurship.
{"title":"Too Much AI Hype, Too Little Emphasis on Learning? Entrepreneurs Designing Business Models Through Learning-by-Conversing With Generative AI","authors":"Angelos Kostis;Johan Lidström;Sujith Nair;Jonny Holmström","doi":"10.1109/TEM.2024.3484750","DOIUrl":"https://doi.org/10.1109/TEM.2024.3484750","url":null,"abstract":"Entrepreneurs traditionally use “learning-by-doing” and “learning-by-thinking” as alternative approaches to iteratively build business models for their new ventures. However, both approaches face criticism in how they address novelty and uncertainty, which are crucial to successful entrepreneurship. While generative AI (GenAI) is increasingly used in entrepreneurial tasks, the practices through which it becomes a learning resource for entrepreneurs remain unexplored. Based on a qualitative study, we present a process model that illustrates how entrepreneurs incorporate GenAI into business model design through five resourcing practices. These practices transform GenAI into a valuable resource for facilitating learning during the design process. This approach, which we term “learning-by-conversing,” introduces a generative startup methodology to complement the lean startup model. We distinguish two modes of learning by conversing—reflexive learning and confirmatory learning—based on how novice and experienced entrepreneurs engage with it. By proposing a learning approach that integrates GenAI with entrepreneurial efforts, we bridge the “thinking” versus “doing” debate in business model generation and deepen our understanding of GenAI's role in entrepreneurship.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15278-15291"},"PeriodicalIF":4.6,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595091","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}
Engineering projects are vulnerable to opportunistic behavior due to their one-off and uncertain nature. Contractual governance is the crucial mechanism for matching the two key project characteristics, i.e., asset specificity and uncertainty, to curtail opportunism. However, the existing studies failed to agree on the above matching principle. In this article, we divide contractual governance into control, coordination, and adaptation from the functional perspective and employ machine learning to code actual contract texts. Based on the paired data from the text-mining results and survey, this study uses qualitative comparative analysis to investigate the aligning (or misaligning) combinations that lead to low (or high) opportunism. The results show that, for projects with low uncertainty, detailed contractual coordination is essential and it should be complemented by less detailed adaptation or detailed control. In such projects, low asset specificity reinforces the significance of contractual coordination alone. This study also finds the limitations of contractual governance in projects with high uncertainty, especially combined with low asset specificity, which necessitates other governance mechanisms. This study helps to resolve previous contradictory matching principles from the view of contract dimensions, contract measurement, and data analysis methods. Project managers can benefit from this study to effectively reduce opportunism and avoid disputes.
{"title":"The Opportunism-Inhibiting Effects of the Alignment Between Engineering Project Characteristics and Contractual Governance: Paired Data From Contract Text Mining and Survey","authors":"Chenglong Xu;Yongqiang Chen;Hongjiang Yao;Lihan Zhang","doi":"10.1109/TEM.2024.3480254","DOIUrl":"https://doi.org/10.1109/TEM.2024.3480254","url":null,"abstract":"Engineering projects are vulnerable to opportunistic behavior due to their one-off and uncertain nature. Contractual governance is the crucial mechanism for matching the two key project characteristics, i.e., asset specificity and uncertainty, to curtail opportunism. However, the existing studies failed to agree on the above matching principle. In this article, we divide contractual governance into control, coordination, and adaptation from the functional perspective and employ machine learning to code actual contract texts. Based on the paired data from the text-mining results and survey, this study uses qualitative comparative analysis to investigate the aligning (or misaligning) combinations that lead to low (or high) opportunism. The results show that, for projects with low uncertainty, detailed contractual coordination is essential and it should be complemented by less detailed adaptation or detailed control. In such projects, low asset specificity reinforces the significance of contractual coordination alone. This study also finds the limitations of contractual governance in projects with high uncertainty, especially combined with low asset specificity, which necessitates other governance mechanisms. This study helps to resolve previous contradictory matching principles from the view of contract dimensions, contract measurement, and data analysis methods. Project managers can benefit from this study to effectively reduce opportunism and avoid disputes.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15110-15124"},"PeriodicalIF":4.6,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524210","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}
Pub Date : 2024-10-18DOI: 10.1109/TEM.2024.3483750
Sundeep Singh Sondhi;Prashant Salwan;Suman Niranjan;Timothy Hawkins;Abhishek Behl;Vijay Pereira;Manlio del Giudice
The current business environment is witnessing significant changes due to changing customer preferences and an increasing desire for exclusive and experiential benchmarks. In light of these changes, it is crucial to analyze the convergence of open innovation (OI) in service and service delivery (SD) within the context of circular economy (CE) goals. The objective of this article is to examine the complex relationship between service innovation (SI) and service delivery innovation (SDI) while evaluating the preparedness of organizations to adopt CE practices. This article examines how innovative SD methods, viewed through the lens of service-dominant (S-D) logic, can develop dynamic capabilities to effectively address changing customer requirements. This, in turn, leads to enhanced satisfaction and customer loyalty. Based on survey data from a sample of 435 responses, this article examines the moderating role of SDI and its interplay with SI, and the integrated effect of both, using regression, structural equation modeling, and the Hayes Process model. The findings emphasize the significant impact of SDI, demonstrating its ability to both moderate and enhance the relationship between SI and the generation of value for consumers. It examines the need to place SDI separate from SI. This undertaking strengthens the collaboration of S-D logic with dynamic capabilities approach and enables the incorporation of OI paradigms with the requirements of CE practices. The main goal of this article is to direct the service sector toward a future that places a strong emphasis on value creation and sustainability.
{"title":"Exploring Open Innovation Dynamics: Service and Delivery Interplay in Circular Economy","authors":"Sundeep Singh Sondhi;Prashant Salwan;Suman Niranjan;Timothy Hawkins;Abhishek Behl;Vijay Pereira;Manlio del Giudice","doi":"10.1109/TEM.2024.3483750","DOIUrl":"https://doi.org/10.1109/TEM.2024.3483750","url":null,"abstract":"The current business environment is witnessing significant changes due to changing customer preferences and an increasing desire for exclusive and experiential benchmarks. In light of these changes, it is crucial to analyze the convergence of open innovation (OI) in service and service delivery (SD) within the context of circular economy (CE) goals. The objective of this article is to examine the complex relationship between service innovation (SI) and service delivery innovation (SDI) while evaluating the preparedness of organizations to adopt CE practices. This article examines how innovative SD methods, viewed through the lens of service-dominant (S-D) logic, can develop dynamic capabilities to effectively address changing customer requirements. This, in turn, leads to enhanced satisfaction and customer loyalty. Based on survey data from a sample of 435 responses, this article examines the moderating role of SDI and its interplay with SI, and the integrated effect of both, using regression, structural equation modeling, and the Hayes Process model. The findings emphasize the significant impact of SDI, demonstrating its ability to both moderate and enhance the relationship between SI and the generation of value for consumers. It examines the need to place SDI separate from SI. This undertaking strengthens the collaboration of S-D logic with dynamic capabilities approach and enables the incorporation of OI paradigms with the requirements of CE practices. The main goal of this article is to direct the service sector toward a future that places a strong emphasis on value creation and sustainability.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15511-15524"},"PeriodicalIF":4.6,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142753860","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}
Pub Date : 2024-10-18DOI: 10.1109/TEM.2024.3457520
Hong Zhang
This study investigates the transformative impact of artificial intelligence (AI) on human resource management (HRM) practices through a quantitative descriptive approach. Data were collected from 285 employees and 144 HR professionals across seven organizations using purposive sampling to explore AI's influence on recruitment, performance assessment, job satisfaction, and workforce planning. A key novelty of this research lies in its comprehensive analysis of AI's holistic influence on HRM dynamics, going beyond isolated aspects of AI implementation. Findings reveal that organizations leveraging AI in HR processes experience significantly higher recruitment efficiency and employee productivity compared to those without AI integration. Moreover, successful adaptation to AI in HR correlates with increased levels of employee job satisfaction and reduced turnover rates, highlighting AI's potential to enhance organizational performance and employee well-being. Additionally, positive perceptions of AI in HR positively correlate with elevated levels of organizational trust and employee engagement. These insights contribute to a nuanced understanding of AI's role in reshaping HRM strategies and fostering a supportive workplace environment conducive to sustainable organizational success. Practical implications are discussed to assist HR professionals and organizational leaders in effectively harnessing AI to optimize HR practices and adapt to evolving workforce dynamics.
{"title":"Exploring the Impact of AI on Human Resource Management: A Case Study of Organizational Adaptation and Employee Dynamics","authors":"Hong Zhang","doi":"10.1109/TEM.2024.3457520","DOIUrl":"https://doi.org/10.1109/TEM.2024.3457520","url":null,"abstract":"This study investigates the transformative impact of artificial intelligence (AI) on human resource management (HRM) practices through a quantitative descriptive approach. Data were collected from 285 employees and 144 HR professionals across seven organizations using purposive sampling to explore AI's influence on recruitment, performance assessment, job satisfaction, and workforce planning. A key novelty of this research lies in its comprehensive analysis of AI's holistic influence on HRM dynamics, going beyond isolated aspects of AI implementation. Findings reveal that organizations leveraging AI in HR processes experience significantly higher recruitment efficiency and employee productivity compared to those without AI integration. Moreover, successful adaptation to AI in HR correlates with increased levels of employee job satisfaction and reduced turnover rates, highlighting AI's potential to enhance organizational performance and employee well-being. Additionally, positive perceptions of AI in HR positively correlate with elevated levels of organizational trust and employee engagement. These insights contribute to a nuanced understanding of AI's role in reshaping HRM strategies and fostering a supportive workplace environment conducive to sustainable organizational success. Practical implications are discussed to assist HR professionals and organizational leaders in effectively harnessing AI to optimize HR practices and adapt to evolving workforce dynamics.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"14991-15004"},"PeriodicalIF":4.6,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524094","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}
Pub Date : 2024-10-17DOI: 10.1109/TEM.2024.3479775
R. Castagnoli;M. Cugno;S. Maroncelli;A. Cugno
The European Union recognizes Industry 5.0 as a cultural revolution that complements the fourth industrial revolution by requiring companies to implement a sustainable, resilient, and human-centric organization. This article critically analyzes the role of the human-centric approach in Industry 4.0 and 5.0 through a systematic literature review of 69 studies published between 2011 and December 2023. The results show that the human-centric approach 1) is underinvestigated in management and mainly ergonomically approached in engineering. Furthermore, it 2) enables response to the challenges of an aging population and increasing working age and improves response to acute events exogenous and endogenous to the firm. The human-centric approach also 3) positively impacts economic and social sustainability and 4) should be investigated through a transdisciplinary approach.
{"title":"A New Research Agenda for Human-Centric Manufacturing: A Systematic Literature Review","authors":"R. Castagnoli;M. Cugno;S. Maroncelli;A. Cugno","doi":"10.1109/TEM.2024.3479775","DOIUrl":"https://doi.org/10.1109/TEM.2024.3479775","url":null,"abstract":"The European Union recognizes Industry 5.0 as a cultural revolution that complements the fourth industrial revolution by requiring companies to implement a sustainable, resilient, and human-centric organization. This article critically analyzes the role of the human-centric approach in Industry 4.0 and 5.0 through a systematic literature review of 69 studies published between 2011 and December 2023. The results show that the human-centric approach 1) is underinvestigated in management and mainly ergonomically approached in engineering. Furthermore, it 2) enables response to the challenges of an aging population and increasing working age and improves response to acute events exogenous and endogenous to the firm. The human-centric approach also 3) positively impacts economic and social sustainability and 4) should be investigated through a transdisciplinary approach.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15236-15253"},"PeriodicalIF":4.6,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10721234","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142594970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-16DOI: 10.1109/TEM.2024.3481439
Jiaming Ding;Anning Wang;Kenneth Guang-Lih Huang;Qiang Zhang;Shanlin Yang
Professional technical documents (PTDs) offer a wealth of information for R&D personnel and innovation management scholars. Recently, the increase in the categories and volume of PTDs has introduced new challenges for their automatic and accurate classification. Existing studies have focused on leveraging the semantic information of documents (i.e., titles and abstracts) for classification tasks. However, the standard label hierarchy of classification systems and the rich label semantic information have been generally ignored. In this paper, we propose a supervised learning-based classification model, designed to Make Full Use of Label Information (MFULI) for hierarchical multi-label PTD classification. Firstly, we deploy a Label-aware Supervised Contrastive Learning Module (LSCLM), which introduces the definition of label set similarity with the aim of improving document representation. Then, we propose a Hierarchy-aware Label Embedding Attentive Module (HLEAM) that dynamically incorporates label hierarchy information into the classification model. We evaluate our proposed model on two public patent datasets, namely USPTO-1 and WIPO-alpha. Experimental results show that our model outperforms other state-of-the-art classification models. Furthermore, we perform a series of ablation studies and analyses to demonstrate the necessity of each component of our model. This paper provides important theoretical contributions and practical implications for innovation and technology management. <p><i>Managerial Relevance Statement</i>—This study helps advance the field of R&D, innovation and technology management by introducing a novel supervised learning-based classification model for professional technical documents (PTDs). Our proposed approach, termed Making Full Use of Label Information (MFULI), is specifically designed for hierarchical multi-label PTD classification, addressing the challenges posed by the growing diversity and volume of PTDs. By integrating innovative components such as the Label-aware Supervised Contrastive Learning Module (LSCLM) and the Hierarchy-aware Label Embedding Attentive Module (HLEAM), MFULI significantly enhances document representation and classification accuracy. The experimental validation of the model on public patent datasets underscores its practical utility and superiority over other existing state-of-the-art models. For managers and practitioners in R&D, innovation and technology management, the implications of this research are profound. Our study provides significant contributions to the fields of technology and innovation management, engineering management, and automated document classification, yielding both theoretical insights and practical implications. The model's ability to effectively categorize large-scale PTDs aids in streamlining knowledge management processes, enhancing decision-making, and fostering more efficient innovation strategies. In summary, this research offers a robust and innovati
{"title":"Improving Large-Scale Classification in Technology Management: Making Full Use of Label Information for Professional Technical Documents","authors":"Jiaming Ding;Anning Wang;Kenneth Guang-Lih Huang;Qiang Zhang;Shanlin Yang","doi":"10.1109/TEM.2024.3481439","DOIUrl":"https://doi.org/10.1109/TEM.2024.3481439","url":null,"abstract":"Professional technical documents (PTDs) offer a wealth of information for R&D personnel and innovation management scholars. Recently, the increase in the categories and volume of PTDs has introduced new challenges for their automatic and accurate classification. Existing studies have focused on leveraging the semantic information of documents (i.e., titles and abstracts) for classification tasks. However, the standard label hierarchy of classification systems and the rich label semantic information have been generally ignored. In this paper, we propose a supervised learning-based classification model, designed to Make Full Use of Label Information (MFULI) for hierarchical multi-label PTD classification. Firstly, we deploy a Label-aware Supervised Contrastive Learning Module (LSCLM), which introduces the definition of label set similarity with the aim of improving document representation. Then, we propose a Hierarchy-aware Label Embedding Attentive Module (HLEAM) that dynamically incorporates label hierarchy information into the classification model. We evaluate our proposed model on two public patent datasets, namely USPTO-1 and WIPO-alpha. Experimental results show that our model outperforms other state-of-the-art classification models. Furthermore, we perform a series of ablation studies and analyses to demonstrate the necessity of each component of our model. This paper provides important theoretical contributions and practical implications for innovation and technology management. \u0000<p><i>Managerial Relevance Statement</i>—This study helps advance the field of R&D, innovation and technology management by introducing a novel supervised learning-based classification model for professional technical documents (PTDs). Our proposed approach, termed Making Full Use of Label Information (MFULI), is specifically designed for hierarchical multi-label PTD classification, addressing the challenges posed by the growing diversity and volume of PTDs. By integrating innovative components such as the Label-aware Supervised Contrastive Learning Module (LSCLM) and the Hierarchy-aware Label Embedding Attentive Module (HLEAM), MFULI significantly enhances document representation and classification accuracy. The experimental validation of the model on public patent datasets underscores its practical utility and superiority over other existing state-of-the-art models. For managers and practitioners in R&D, innovation and technology management, the implications of this research are profound. Our study provides significant contributions to the fields of technology and innovation management, engineering management, and automated document classification, yielding both theoretical insights and practical implications. The model's ability to effectively categorize large-scale PTDs aids in streamlining knowledge management processes, enhancing decision-making, and fostering more efficient innovation strategies. In summary, this research offers a robust and innovati","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15188-15208"},"PeriodicalIF":4.6,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595099","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}
Pub Date : 2024-10-16DOI: 10.1109/TEM.2024.3481670
Robin Weidlich;Tobias Albrecht;Patrick Derr;Maximilian Röglinger
Digital twins have gained significant attention in recent years as a means to represent physical objects digitally. It is now applied for planning, monitoring, and decision-making across various domains. While extensively leveraged in manufacturing, digital twins also present promising opportunities in other process-intensive sectors, such as the testing, inspection, and calibration industries. Industrial testing laboratories face challenges such as cost pressures and efficiency demands, operating within a complex socio-technical and highly regulated environment. Current digital solutions, such as laboratory information management systems, fall short of providing a comprehensive data and process management perspective and do not fully comply with the ISO/IEC 17025 standard, which ensures trust in laboratory operations and results. This article aims to address these gaps by proposing a set of design principles and a software architecture for a process-oriented digital lab twin developed through a design science research approach. The artifact is evaluated through expert interviews, a prototypical implementation, and a field study in an industrial laboratory setting. The findings offer valuable insights for designing digital twins in laboratory process management, guiding future research and practical applications.
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