Pub Date : 2024-10-09DOI: 10.1109/TEM.2024.3477493
Xide Zhu;Tao Wang;Gui-Hua Lin;Haiyang Cui
Numerous Internet platforms have amassed considerable profits through market dominance, thereby exhibiting monopolistic behaviors in specific instances. In response to ensuing protests and legal actions, these platforms have been compelled to restructure their prevailing single-rate revenue sharing schemes, adopting differential designs aimed at redistributing more revenue to suppliers. In this article, we construct a two-tier supply chain model encompassing a platform with a large supplier and numerous smaller suppliers under price competition. Our investigation establishes that, in contrast with the single-rate scheme, the implementation of a differential revenue sharing scheme can significantly alleviate the financial pressures faced by small suppliers and provides substantial profit increase. Under specific conditions, this scheme also demonstrates a propensity to enhance the overall welfare of the platform and large supplier. Moreover, we illustrate that the adoption of differential scheme incentivizes both large and small suppliers to formulate distinct pricing strategies in most cases, avoiding traditional price wars, thereby mitigating the direct and potential competitive pressures among suppliers. Notably, the differential scheme appears to impose constraints on the platform's ability to extract substantial profits, yet paradoxically facilitates increased revenue generation and sustains a balance between large and small suppliers, fostering the platform's long-term dominance.
{"title":"Differential Revenue Sharing in Platform Selling: A Framework Incorporating Pricing Decisions","authors":"Xide Zhu;Tao Wang;Gui-Hua Lin;Haiyang Cui","doi":"10.1109/TEM.2024.3477493","DOIUrl":"https://doi.org/10.1109/TEM.2024.3477493","url":null,"abstract":"Numerous Internet platforms have amassed considerable profits through market dominance, thereby exhibiting monopolistic behaviors in specific instances. In response to ensuing protests and legal actions, these platforms have been compelled to restructure their prevailing single-rate revenue sharing schemes, adopting differential designs aimed at redistributing more revenue to suppliers. In this article, we construct a two-tier supply chain model encompassing a platform with a large supplier and numerous smaller suppliers under price competition. Our investigation establishes that, in contrast with the single-rate scheme, the implementation of a differential revenue sharing scheme can significantly alleviate the financial pressures faced by small suppliers and provides substantial profit increase. Under specific conditions, this scheme also demonstrates a propensity to enhance the overall welfare of the platform and large supplier. Moreover, we illustrate that the adoption of differential scheme incentivizes both large and small suppliers to formulate distinct pricing strategies in most cases, avoiding traditional price wars, thereby mitigating the direct and potential competitive pressures among suppliers. Notably, the differential scheme appears to impose constraints on the platform's ability to extract substantial profits, yet paradoxically facilitates increased revenue generation and sustains a balance between large and small suppliers, fostering the platform's long-term dominance.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15057-15069"},"PeriodicalIF":4.6,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524181","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 : 2024-10-09DOI: 10.1109/TEM.2024.3476917
Ana Asensio-Ciria;Carmen De-Pablos-Heredero;Francisco José Blanco Jiménez;José Luis Montes Botella;Antón García Martínez
This article quantifies the relationships among the different phases of the business incubation process. A total of 89 surveys coming from business incubators in Spain in the period 2022–2023 have been collected. A structural equation model (SEM) is applied to determine the association among incubation phases 1, 2, 3, and 4. The results show that the “spreading entrepreneurship” phase has a strongly positive significative influence on preincubation, phases 1 and 2 (hypothesis 1) basic incubation, phase 3 (hypothesis 4), and advanced incubation phase 4 (hypothesis 5). Besides, a moderate positive influence was found between preincubation and basic incubation (hypothesis 2) and between preincubation and advanced incubation (hypothesis 6). In this context, spreading entrepreneurship will be a useful tool to determine the success of entrepreneurship during the incubation process. Improving variables, such as counseling, channels, and training, will positively impact incubation. Therefore, taking action at the spreading entrepreneurship stage to improve the business incubator results and evaluate the structural deficiencies of entrepreneurs to improve their training level and technicians’ specialization is recommended. Applying SEM models in business incubators to evaluate their influence on graduation rates will also be of great interest.
{"title":"Relationship Among the Startup Incubation Process Phases: A Structural Equation Model","authors":"Ana Asensio-Ciria;Carmen De-Pablos-Heredero;Francisco José Blanco Jiménez;José Luis Montes Botella;Antón García Martínez","doi":"10.1109/TEM.2024.3476917","DOIUrl":"https://doi.org/10.1109/TEM.2024.3476917","url":null,"abstract":"This article quantifies the relationships among the different phases of the business incubation process. A total of 89 surveys coming from business incubators in Spain in the period 2022–2023 have been collected. A structural equation model (SEM) is applied to determine the association among incubation phases 1, 2, 3, and 4. The results show that the “spreading entrepreneurship” phase has a strongly positive significative influence on preincubation, phases 1 and 2 (hypothesis 1) basic incubation, phase 3 (hypothesis 4), and advanced incubation phase 4 (hypothesis 5). Besides, a moderate positive influence was found between preincubation and basic incubation (hypothesis 2) and between preincubation and advanced incubation (hypothesis 6). In this context, spreading entrepreneurship will be a useful tool to determine the success of entrepreneurship during the incubation process. Improving variables, such as counseling, channels, and training, will positively impact incubation. Therefore, taking action at the spreading entrepreneurship stage to improve the business incubator results and evaluate the structural deficiencies of entrepreneurs to improve their training level and technicians’ specialization is recommended. Applying SEM models in business incubators to evaluate their influence on graduation rates will also be of great interest.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15141-15155"},"PeriodicalIF":4.6,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10710139","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142565633","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 : 2024-10-03DOI: 10.1109/TEM.2024.3472292
Fan Yang;Mohammad Zoynul Abedin;Yanan Qiao;Lvyang Ye
Digital platforms are experiencing a growing presence of generative artificial intelligence (AI) content, raising concerns due to the prevalence of misinformation that disrupts market integrity. Consequently, the development of effective regulatory measures for overseeing generative AI content becomes imperative. This necessitates the establishment of mechanisms to detect and filter out inaccuracies, ensuring compliance with regulatory requirements. In addition, collaboration among experts, regulators, and AI developers is essential to encourage responsible AI deployment on digital platforms. Successful governance hinges on principles of transparency, accountability, and proactive risk management to navigate the evolving generative AI on digital platforms. Therefore, in order to address the security issues currently faced by artificial intelligence generated content (AIGC), this article first proposes a method of efficient cache mechanism for AIGC content. The secure method of determining the identity of AIGC content owners is proposed based on blockchain technology. Subsequently, it suggests mechanisms for access control and data encryption for generated content within a blockchain environment. Finally, it presents an efficient data supervision mechanism tailored to the AIGC environment. The methods outlined in this article aim to enhance security from three perspectives: protection of content creators' identities, safeguarding data security, and ensuring effective data supervision within the AIGC framework. The experimental results further confirm that our proposed method not only ensures the security of the AIGC framework but also provides an efficient data analysis and supervision solution for digital platforms.
{"title":"Toward Trustworthy Governance of AI-Generated Content (AIGC): A Blockchain-Driven Regulatory Framework for Secure Digital Ecosystems","authors":"Fan Yang;Mohammad Zoynul Abedin;Yanan Qiao;Lvyang Ye","doi":"10.1109/TEM.2024.3472292","DOIUrl":"https://doi.org/10.1109/TEM.2024.3472292","url":null,"abstract":"Digital platforms are experiencing a growing presence of generative artificial intelligence (AI) content, raising concerns due to the prevalence of misinformation that disrupts market integrity. Consequently, the development of effective regulatory measures for overseeing generative AI content becomes imperative. This necessitates the establishment of mechanisms to detect and filter out inaccuracies, ensuring compliance with regulatory requirements. In addition, collaboration among experts, regulators, and AI developers is essential to encourage responsible AI deployment on digital platforms. Successful governance hinges on principles of transparency, accountability, and proactive risk management to navigate the evolving generative AI on digital platforms. Therefore, in order to address the security issues currently faced by artificial intelligence generated content (AIGC), this article first proposes a method of efficient cache mechanism for AIGC content. The secure method of determining the identity of AIGC content owners is proposed based on blockchain technology. Subsequently, it suggests mechanisms for access control and data encryption for generated content within a blockchain environment. Finally, it presents an efficient data supervision mechanism tailored to the AIGC environment. The methods outlined in this article aim to enhance security from three perspectives: protection of content creators' identities, safeguarding data security, and ensuring effective data supervision within the AIGC framework. The experimental results further confirm that our proposed method not only ensures the security of the AIGC framework but also provides an efficient data analysis and supervision solution for digital platforms.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"14945-14962"},"PeriodicalIF":4.6,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142450826","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 : 2024-10-03DOI: 10.1109/TEM.2024.3473288
Anas Iftikhar;Imran Ali;Ismail Golgeci;Mark Stevenson
The literature on supply chain complexity (SCC) has traditionally focused on its negative aspects, such as increased vulnerability to disruption. However, in this article, we take a different perspective, exploring the potential for SCC to trigger positive outcomes, such as enhanced supply chain viability (SCV). Informed by the dynamic capabilities view, we delve into the relationship between SCC and SCV, and how this is influenced by strategic information flow (SIF) and network capability (NC). Survey data from 242 firms are collected to examine hypothesized relationships. The data are analyzed using the partial least squares structural equation modeling technique. The findings reveal that exposure to SCC significantly indirectly influences SCV via both SIF and NC. Investigation of the serial mediation pathway (SCC → SIF → NC → SCV) indicates a partial mediation effect. This suggests that, while both mediators (SIF and NC) can independently enhance SCV, their combined sequential influence can synergistically offer additional advantages to achieving SCV. These findings provide a new perspective on SCC and guide managers and policymakers in establishing SCV in the face of SCC. For example, our findings suggest that investing in both NC and SIF enhances SCV more effectively than investing in either one alone.
{"title":"Embracing Supply Chain Complexity for Enhanced Viability: The Influence of Strategic Information Flow and Network Capability","authors":"Anas Iftikhar;Imran Ali;Ismail Golgeci;Mark Stevenson","doi":"10.1109/TEM.2024.3473288","DOIUrl":"https://doi.org/10.1109/TEM.2024.3473288","url":null,"abstract":"The literature on supply chain complexity (SCC) has traditionally focused on its negative aspects, such as increased vulnerability to disruption. However, in this article, we take a different perspective, exploring the potential for SCC to trigger positive outcomes, such as enhanced supply chain viability (SCV). Informed by the dynamic capabilities view, we delve into the relationship between SCC and SCV, and how this is influenced by strategic information flow (SIF) and network capability (NC). Survey data from 242 firms are collected to examine hypothesized relationships. The data are analyzed using the partial least squares structural equation modeling technique. The findings reveal that exposure to SCC significantly indirectly influences SCV via both SIF and NC. Investigation of the serial mediation pathway (SCC → SIF → NC → SCV) indicates a partial mediation effect. This suggests that, while both mediators (SIF and NC) can independently enhance SCV, their combined sequential influence can synergistically offer additional advantages to achieving SCV. These findings provide a new perspective on SCC and guide managers and policymakers in establishing SCV in the face of SCC. For example, our findings suggest that investing in both NC and SIF enhances SCV more effectively than investing in either one alone.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"14963-14973"},"PeriodicalIF":4.6,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524096","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 : 2024-10-02DOI: 10.1109/TEM.2024.3472841
Mingyue Wang;Yingming Li
Digital transformation has emerged as a crucial lever for promoting sustainable development worldwide. The question of whether and how digital transformation can empower green technological innovation (GTI) represents an urgent topic that necessitates exploration. Given the advantages of digital technology in optimizing factor allocation, this study examines whether the digital transformation of enterprises can enhance their capability and motivation for GTI by facilitating innovation elements searching (IES), using data from 253 manufacturing companies in China. Based on this, we categorize the impact pathway of digital transformation on GTI into two stages, using IES as a dividing point, and empirically test the influence of external environmental dynamism in the first stage and the impact of corporate environmental commitment in the second stage. The research findings indicate that 1) digital transformation exerts a positive influence on GTI within enterprises, characterized by diverse transformation pathways. Notably, the depth and breadth of IES serve as significant mediators, with the direct pathway contributing more than the two indirect pathways. 2) As the dynamism of the external environment increases, the positive effect of digital transformation on the breadth and depth of IES diminishes, revealing a moderating effect that has certain limits. Specifically, when external environmental dynamics exceed critical threshold, the moderating effect becomes insignificant. 3) Within a specified boundary range, corporate environmental commitment positively influences the relationship between IES and GTI, with variations observed in the breadth and depth of IES. This study offers valuable insights into the pathways and mechanisms of the integrated development of digitalization and green growth, thereby contributing to the achievement of sustainable development goals.
{"title":"Exploring the Relationship Between Enterprise Digital Transformation and Green Technological Innovation: From the Perspective of Innovation Elements Searching","authors":"Mingyue Wang;Yingming Li","doi":"10.1109/TEM.2024.3472841","DOIUrl":"https://doi.org/10.1109/TEM.2024.3472841","url":null,"abstract":"Digital transformation has emerged as a crucial lever for promoting sustainable development worldwide. The question of whether and how digital transformation can empower green technological innovation (GTI) represents an urgent topic that necessitates exploration. Given the advantages of digital technology in optimizing factor allocation, this study examines whether the digital transformation of enterprises can enhance their capability and motivation for GTI by facilitating innovation elements searching (IES), using data from 253 manufacturing companies in China. Based on this, we categorize the impact pathway of digital transformation on GTI into two stages, using IES as a dividing point, and empirically test the influence of external environmental dynamism in the first stage and the impact of corporate environmental commitment in the second stage. The research findings indicate that 1) digital transformation exerts a positive influence on GTI within enterprises, characterized by diverse transformation pathways. Notably, the depth and breadth of IES serve as significant mediators, with the direct pathway contributing more than the two indirect pathways. 2) As the dynamism of the external environment increases, the positive effect of digital transformation on the breadth and depth of IES diminishes, revealing a moderating effect that has certain limits. Specifically, when external environmental dynamics exceed critical threshold, the moderating effect becomes insignificant. 3) Within a specified boundary range, corporate environmental commitment positively influences the relationship between IES and GTI, with variations observed in the breadth and depth of IES. This study offers valuable insights into the pathways and mechanisms of the integrated development of digitalization and green growth, thereby contributing to the achievement of sustainable development goals.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15125-15140"},"PeriodicalIF":4.6,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524192","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}
This study analyzes the current state of artificial intelligence (AI) technologies for addressing and mitigating climate change in the manufacturing sector and provides an outlook on future developments. The research is grounded in the concept of general-purpose technologies, motivated by a still limited understanding of innovation patterns for this application context. To this end, we focus on global patenting activity between 2011 and 2023 (5919 granted patents classified for “mitigation or adaptation against climate change” in the “production or processing of goods”). We examined time trends, applicant characteristics, and underlying technologies. A topic modeling analysis was performed to identify emerging themes from the unstructured textual data of the patent abstracts. This allowed the identification of six AI application domains. For each of them, we built a network analysis and ran growth trends and forecasting models. Our results show that patenting activities are mostly oriented toward improving the efficiency and reliability of manufacturing processes in five out of six identified domains (“predictive analytics,” “material sorting,” “defect detection,” “advanced robotics,” and “scheduling”). Instead, AI within the “resource optimization” domain relates to energy management, showing an interplay with other climate-related technologies. Our results also highlight interdependent innovations peculiar to each domain around core AI technologies. Forecasts show that the more specific technologies are within domains, the longer it will take for them to mature. From a practical standpoint, the study sheds light on the role of AI within the broader cleantech innovation landscape and urges policymakers to consider synergies. Managers can find information to define technology portfolios and alliances considering technological coevolution.
{"title":"Artificial Intelligence for Climate Change: A Patent Analysis in the Manufacturing Sector","authors":"Matteo Podrecca;Giovanna Culot;Sam Tavassoli;Guido Orzes","doi":"10.1109/TEM.2024.3469370","DOIUrl":"https://doi.org/10.1109/TEM.2024.3469370","url":null,"abstract":"This study analyzes the current state of artificial intelligence (AI) technologies for addressing and mitigating climate change in the manufacturing sector and provides an outlook on future developments. The research is grounded in the concept of general-purpose technologies, motivated by a still limited understanding of innovation patterns for this application context. To this end, we focus on global patenting activity between 2011 and 2023 (5919 granted patents classified for “mitigation or adaptation against climate change” in the “production or processing of goods”). We examined time trends, applicant characteristics, and underlying technologies. A topic modeling analysis was performed to identify emerging themes from the unstructured textual data of the patent abstracts. This allowed the identification of six AI application domains. For each of them, we built a network analysis and ran growth trends and forecasting models. Our results show that patenting activities are mostly oriented toward improving the efficiency and reliability of manufacturing processes in five out of six identified domains (“predictive analytics,” “material sorting,” “defect detection,” “advanced robotics,” and “scheduling”). Instead, AI within the “resource optimization” domain relates to energy management, showing an interplay with other climate-related technologies. Our results also highlight interdependent innovations peculiar to each domain around core AI technologies. Forecasts show that the more specific technologies are within domains, the longer it will take for them to mature. From a practical standpoint, the study sheds light on the role of AI within the broader cleantech innovation landscape and urges policymakers to consider synergies. Managers can find information to define technology portfolios and alliances considering technological coevolution.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15005-15024"},"PeriodicalIF":4.6,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10703137","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524095","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 : 2024-10-01DOI: 10.1109/TEM.2024.3471876
Mehdi Soltanifar;Madjid Tavana;Francisco J. Santos-Arteaga;Vincent Charles
This study introduces a novel approach named the fuzzy Kemeny median indicator ranks accordance (KEMIRA) method tailored for multiattribute decision making (MADM) while capturing and processing the uncertainties inherent in complex problems. We explore preferential voting to enhance MADM models, rewriting it as a linear programming (LP) problem with weight restrictions. Our fuzzy KEMIRA model leverages LP to ascertain optimal priorities and weights for each feature, guided by discrimination intensity functions. To illustrate the effectiveness of our approach, we utilize a well-known numerical example from the literature. We also present a case study describing the location selection of an innovation park constrained by experts’ subjective judgments across various attributes. Through comparative analyses with hesitant fuzzy KEMIRA and stochastic KEMIRA, we demonstrate our proposed fuzzy KEMIRA method's higher flexibility and reduced computational burden. By emphasizing these attributes, we underscore the versatility of our method, which applies to a broad spectrum of MADM problems that go well beyond specific instances.
{"title":"A New Fuzzy KEMIRA Method With an Application to Innovation Park Location Analysis and Selection","authors":"Mehdi Soltanifar;Madjid Tavana;Francisco J. Santos-Arteaga;Vincent Charles","doi":"10.1109/TEM.2024.3471876","DOIUrl":"https://doi.org/10.1109/TEM.2024.3471876","url":null,"abstract":"This study introduces a novel approach named the fuzzy Kemeny median indicator ranks accordance (KEMIRA) method tailored for multiattribute decision making (MADM) while capturing and processing the uncertainties inherent in complex problems. We explore preferential voting to enhance MADM models, rewriting it as a linear programming (LP) problem with weight restrictions. Our fuzzy KEMIRA model leverages LP to ascertain optimal priorities and weights for each feature, guided by discrimination intensity functions. To illustrate the effectiveness of our approach, we utilize a well-known numerical example from the literature. We also present a case study describing the location selection of an innovation park constrained by experts’ subjective judgments across various attributes. Through comparative analyses with hesitant fuzzy KEMIRA and stochastic KEMIRA, we demonstrate our proposed fuzzy KEMIRA method's higher flexibility and reduced computational burden. By emphasizing these attributes, we underscore the versatility of our method, which applies to a broad spectrum of MADM problems that go well beyond specific instances.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"14933-14944"},"PeriodicalIF":4.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142565632","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 : 2024-09-30DOI: 10.1109/TEM.2024.3470776
Madhur Srivastava;Karuna Jain
Effective management of technology has become the engine for development. However, the fuzzy nature of technology development and management renders decision-makers dependent on credible information for technology-related decisions. A patent, a techno-legal document granted by the government to inventors to protect their inventions from imitation, proves to be a rich source of information. Various analytical tools can be employed on patent data to gain insights about managing technology strategically. The article conducts a scoping review to assess the application of patent analysis in technology management. This article replenishes the absence of a comprehensive review, revealing the application of patent analysis in technology management. Also, this review provides a panoramic view of how the researchers have employed various tools and techniques on patent data to harness its immense potential to aid in technology-related decision-making.
{"title":"Application of Patent Analysis in Technology Management: A Scoping Review","authors":"Madhur Srivastava;Karuna Jain","doi":"10.1109/TEM.2024.3470776","DOIUrl":"https://doi.org/10.1109/TEM.2024.3470776","url":null,"abstract":"Effective management of technology has become the engine for development. However, the fuzzy nature of technology development and management renders decision-makers dependent on credible information for technology-related decisions. A patent, a techno-legal document granted by the government to inventors to protect their inventions from imitation, proves to be a rich source of information. Various analytical tools can be employed on patent data to gain insights about managing technology strategically. The article conducts a scoping review to assess the application of patent analysis in technology management. This article replenishes the absence of a comprehensive review, revealing the application of patent analysis in technology management. Also, this review provides a panoramic view of how the researchers have employed various tools and techniques on patent data to harness its immense potential to aid in technology-related decision-making.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"14897-14914"},"PeriodicalIF":4.6,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442983","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 : 2024-09-27DOI: 10.1109/TEM.2024.3470309
Jing Wang
The fanfare surrounding artificial intelligence (AI) transformation often hails the sophisticated technology used to develop Big Data, yet better technology does not equal better transformation. In this article, we draw on an in-depth case study of iFLYTEK, a pioneer in the AI industry of Hefei, Anhui province in China, investigating how the platform-based firm fosters AI innovations by aligning the quadruple helix model. The article finds that the university helix has changed from technology support to ecosystem participation. The role of the government helix has shifted from being the resources supplier and solutions buyer to resources coordinator and solutions coregulator. The industry helix has been upgraded from the mode of benefiting individual entrepreneurs to the mode of empowering the whole industry. The user helix transitioned from the innovation feedback to the innovation input by focusing on interdependence among tiers of user in AI solutions. This article unravels the importance of the quadruple helix model in the context of AI innovations, where the sociotechnical meaning of AI converges as different helices closely collaborate as a whole through emerging roles. It also contributes to the existing helix model by introducing the platform-based firm as the driver that blends elements of AI innovations and the roles of different helices.
{"title":"Platform-Based Firm-Driven Quadruple Helix Model in Artificial Intelligence Innovations: Evidence From iFLYTEK in China","authors":"Jing Wang","doi":"10.1109/TEM.2024.3470309","DOIUrl":"https://doi.org/10.1109/TEM.2024.3470309","url":null,"abstract":"The fanfare surrounding artificial intelligence (AI) transformation often hails the sophisticated technology used to develop Big Data, yet better technology does not equal better transformation. In this article, we draw on an in-depth case study of iFLYTEK, a pioneer in the AI industry of Hefei, Anhui province in China, investigating how the platform-based firm fosters AI innovations by aligning the quadruple helix model. The article finds that the university helix has changed from technology support to ecosystem participation. The role of the government helix has shifted from being the resources supplier and solutions buyer to resources coordinator and solutions coregulator. The industry helix has been upgraded from the mode of benefiting individual entrepreneurs to the mode of empowering the whole industry. The user helix transitioned from the innovation feedback to the innovation input by focusing on interdependence among tiers of user in AI solutions. This article unravels the importance of the quadruple helix model in the context of AI innovations, where the sociotechnical meaning of AI converges as different helices closely collaborate as a whole through emerging roles. It also contributes to the existing helix model by introducing the platform-based firm as the driver that blends elements of AI innovations and the roles of different helices.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"15025-15035"},"PeriodicalIF":4.6,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524180","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}
We tackle the problem of digitalization of supply chains, focusing on the collaboration and sharing of information. By generalizing the notion of digital twins, we review, develop, and conceptualize the (emerging) notion of digital twins of supply chains (DTofSC). While digital twins is an active research area with data available from numerous industry projects, its application to supply chains is just emerging as a cross discipline stemming from decades of maturing the notion of digital supply chains. While digital twins has been used in supply chains, the notion of digitalization of supply chains is only a nascent area, with imprecise definitions beyond key metaphors (e.g., visibility, traceability); as we conceptualize, the overall vision is to create technical and organizational mechanisms enabling any supply chain to be monitored and controlled from, e.g., a dashboard screen. After a literature review on the intersections between digital supply chains, digital twins, and digital technologies (e.g., blockchain), we propose a synthesis systems architecture of DTofSC, identify a key requirement gap (that we term addressability), and ground our contributions, and in the absence of real-world use-cases in practice, we apply our conceptualized systems architecture to battery recycling based on feedback from an industry-targeted workshop.
{"title":"Digital Twins of Supply Chains: A Systems Approach","authors":"Vitor Jesus;Dimitra Kalaitzi;Luciano Batista;Nestor Leal Lopez","doi":"10.1109/TEM.2024.3468177","DOIUrl":"https://doi.org/10.1109/TEM.2024.3468177","url":null,"abstract":"We tackle the problem of digitalization of supply chains, focusing on the collaboration and sharing of information. By generalizing the notion of digital twins, we review, develop, and conceptualize the (emerging) notion of digital twins of supply chains (DTofSC). While digital twins is an active research area with data available from numerous industry projects, its application to supply chains is just emerging as a cross discipline stemming from decades of maturing the notion of digital supply chains. While digital twins has been used in supply chains, the notion of digitalization of supply chains is only a nascent area, with imprecise definitions beyond key metaphors (e.g., visibility, traceability); as we conceptualize, the overall vision is to create technical and organizational mechanisms enabling any supply chain to be monitored and controlled from, e.g., a dashboard screen. After a literature review on the intersections between digital supply chains, digital twins, and digital technologies (e.g., blockchain), we propose a synthesis systems architecture of DTofSC, identify a key requirement gap (that we term addressability), and ground our contributions, and in the absence of real-world use-cases in practice, we apply our conceptualized systems architecture to battery recycling based on feedback from an industry-targeted workshop.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"14915-14932"},"PeriodicalIF":4.6,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442989","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}
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