Big data and computational technologies are increasingly important worldwide in asset and investment management. Many investment management firms are adopting these data science (DS) methods and technologies to improve performance across all investment processes. A good question is whether we can make better decisions in developing quantitative strategies. Therefore, the main objective of this research was to develop a multicriteria assessment framework and scoring decision support system to evaluate quantitative investment strategies that apply machine learning (ML) and DS techniques in their research and development. Subject matter experts will assess all framework perspectives from a systematic literature review to approve their reliability. The perspectives consist of economic and financial foundations, data perspective, features perspective, modeling perspective, and performance perspective. The research methodology applied was the hierarchical decision model (HDM) to provide a 360° view of the quantitative investment strategy and improve and generalize the concept to other asset classes and regions. This study accomplished a rigorous integration of an extensive literature review connecting DS, ML, and investment decision-making in developing quantitative investment strategies. As a result, the major contribution of this study is the comprehensive examination, which included identifying and quantifying perspectives and criteria. The results, while limited indicated significant gaps in strategies examined and therefore generated critical knowledge to improve ML/DS-driven investment strategies, which are valuable for financial companies and policymakers.
{"title":"An Evaluation Framework for Machine Learning and Data Science-Based Financial Strategies: A Case Study-Driven Decision Model","authors":"Mohammadsaleh Saadatmand;Tugrul Daim;Carlos Mena;Haydar Yalcin;Gulin Bolatan;Manali Chatterjee","doi":"10.1109/TEM.2024.3522313","DOIUrl":"https://doi.org/10.1109/TEM.2024.3522313","url":null,"abstract":"Big data and computational technologies are increasingly important worldwide in asset and investment management. Many investment management firms are adopting these data science (DS) methods and technologies to improve performance across all investment processes. A good question is whether we can make better decisions in developing quantitative strategies. Therefore, the main objective of this research was to develop a multicriteria assessment framework and scoring decision support system to evaluate quantitative investment strategies that apply machine learning (ML) and DS techniques in their research and development. Subject matter experts will assess all framework perspectives from a systematic literature review to approve their reliability. The perspectives consist of <italic>economic and financial foundations</i>, <italic>data perspective</i>, <italic>features perspective</i>, <italic>modeling perspective</i>, and <italic>performance perspective</i>. The research methodology applied was the hierarchical decision model (HDM) to provide a 360° view of the quantitative investment strategy and improve and generalize the concept to other asset classes and regions. This study accomplished a rigorous integration of an extensive literature review connecting DS, ML, and investment decision-making in developing quantitative investment strategies. As a result, the major contribution of this study is the comprehensive examination, which included identifying and quantifying perspectives and criteria. The results, while limited indicated significant gaps in strategies examined and therefore generated critical knowledge to improve ML/DS-driven investment strategies, which are valuable for financial companies and policymakers.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"349-362"},"PeriodicalIF":4.6,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993283","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 : 2024-12-23DOI: 10.1109/TEM.2024.3521542
Lei Shen;Xiaodi Zhao;Debadrita Panda;Vinit Parida
This study explores how governmental and regional investments in the digital economy foster the emergence of new industries and the region's sustainable competitiveness. In particular, we focus on the creation of the big data comprehensive pilot zone (BDCPZ) in China that serves as a proxy for digital economy advancement initiatives. Employing a quasi-experimental design and a panel dataset from 31 Chinese provinces (2009–2020), this study uses the difference-in-differences approach to evaluate the impact of BDCPZ on the region's competitiveness. Our findings show that enhanced digital economy advancement significantly boosts the creation of new industries, such as the creative industry. This study advances understanding by linking economic development and the business environment and conducting a heterogeneity analysis to identify the most influential characteristics for new industry creation. These characteristics are categories that fall under regional ecosystems—including talent mobility, innovation culture, and financial institutions—and act as mediators of this relationship, offering valuable insights for stakeholders to enhance regional sustainable competitiveness and innovation.
Managerial relevance statement: This study offers valuable managerial insights for managers, policymakers, and industrial networks to apply in practice. By understanding the importance of regional talent mobility and strong innovation culture, managers in traditional engineering firms can experiment with novel strategies like rotational mobilizing programs to increase agility and diversify into creative sectors. Policymakers can support these efforts in three ways: by incentivizing digital economy advancements like automation, application of emerging technologies through tax breaks and grants; by establishing cross-sector innovation hubs where traditional industries collaborate with tech startups and creative enterprises; and by focusing on training and reskilling programs. Finally, industrial networks, i.e. consultancy networks drive strategy and collaboration, are encouraged to educate financial institutions on how to assess creative industry projects and facilitate talent mobility by linking traditional engineering firms with SMEs and startups to acquire valuable cross-sector experience, foster innovation, and contribute to the development of new industries.
{"title":"Does Digital Economy Investment Promote Sustainable Competitiveness by Creating New Industry?","authors":"Lei Shen;Xiaodi Zhao;Debadrita Panda;Vinit Parida","doi":"10.1109/TEM.2024.3521542","DOIUrl":"https://doi.org/10.1109/TEM.2024.3521542","url":null,"abstract":"This study explores how governmental and regional investments in the digital economy foster the emergence of new industries and the region's sustainable competitiveness. In particular, we focus on the creation of the big data comprehensive pilot zone (BDCPZ) in China that serves as a proxy for digital economy advancement initiatives. Employing a quasi-experimental design and a panel dataset from 31 Chinese provinces (2009–2020), this study uses the difference-in-differences approach to evaluate the impact of BDCPZ on the region's competitiveness. Our findings show that enhanced digital economy advancement significantly boosts the creation of new industries, such as the creative industry. This study advances understanding by linking economic development and the business environment and conducting a heterogeneity analysis to identify the most influential characteristics for new industry creation. These characteristics are categories that fall under regional ecosystems—including talent mobility, innovation culture, and financial institutions—and act as mediators of this relationship, offering valuable insights for stakeholders to enhance regional sustainable competitiveness and innovation. \u0000<p><i>Managerial relevance statement:</i> This study offers valuable managerial insights for managers, policymakers, and industrial networks to apply in practice. By understanding the importance of regional talent mobility and strong innovation culture, managers in traditional engineering firms can experiment with novel strategies like rotational mobilizing programs to increase agility and diversify into creative sectors. Policymakers can support these efforts in three ways: by incentivizing digital economy advancements like automation, application of emerging technologies through tax breaks and grants; by establishing cross-sector innovation hubs where traditional industries collaborate with tech startups and creative enterprises; and by focusing on training and reskilling programs. Finally, industrial networks, i.e. consultancy networks drive strategy and collaboration, are encouraged to educate financial institutions on how to assess creative industry projects and facilitate talent mobility by linking traditional engineering firms with SMEs and startups to acquire valuable cross-sector experience, foster innovation, and contribute to the development of new industries.</p>","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"295-307"},"PeriodicalIF":4.6,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938540","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 : 2024-12-19DOI: 10.1109/TEM.2024.3515471
Fu Jia;Jiguang Guo;Lujie Chen;Nazrul Islam
Financial technology, or Fintech, is used to describe disruptive new technologies that help firms manage their financial operations and improve the cost effectiveness of customer services. However, the role of Fintech adoption in sustainable supply chain management performance is unclear. Using the panel data from Chinese A-share listed companies from 2018 to 2022, in this article, we empirically demonstrate that Fintech adoption can significantly improve sustainable supply chain management performance. This improvement is primarily attributed to Fintech's ability to enhance information transparency and refine decision-making capabilities, thereby fostering sustainability. Furthermore, green innovation, digital innovation policies, top management team forward-looking innovation orientation, and persistent innovation orientation strengthen the relationship between Fintech adoption and sustainable supply chain management performance. Green innovation enables firms to comply with environmental regulations and gain a competitive advantage, thereby facilitating the integration of Fintech into sustainable supply chain management. Digital innovation policies provide regulatory support and establish norms, creating a conducive environment for technology applications. The innovation orientation of the top management team drives the continuous optimization of supply chain processes and services through Fintech. This research contributes to the current industrial sustainability debate by integrating Fintech adoption and sustainable supply chain management from an innovation-intensive environment perspective.
{"title":"Does Fintech Adoption Improve Sustainable Supply Chain Management? An Innovation-Intensive Environment Perspective","authors":"Fu Jia;Jiguang Guo;Lujie Chen;Nazrul Islam","doi":"10.1109/TEM.2024.3515471","DOIUrl":"https://doi.org/10.1109/TEM.2024.3515471","url":null,"abstract":"Financial technology, or Fintech, is used to describe disruptive new technologies that help firms manage their financial operations and improve the cost effectiveness of customer services. However, the role of Fintech adoption in sustainable supply chain management performance is unclear. Using the panel data from Chinese A-share listed companies from 2018 to 2022, in this article, we empirically demonstrate that Fintech adoption can significantly improve sustainable supply chain management performance. This improvement is primarily attributed to Fintech's ability to enhance information transparency and refine decision-making capabilities, thereby fostering sustainability. Furthermore, green innovation, digital innovation policies, top management team forward-looking innovation orientation, and persistent innovation orientation strengthen the relationship between Fintech adoption and sustainable supply chain management performance. Green innovation enables firms to comply with environmental regulations and gain a competitive advantage, thereby facilitating the integration of Fintech into sustainable supply chain management. Digital innovation policies provide regulatory support and establish norms, creating a conducive environment for technology applications. The innovation orientation of the top management team drives the continuous optimization of supply chain processes and services through Fintech. This research contributes to the current industrial sustainability debate by integrating Fintech adoption and sustainable supply chain management from an innovation-intensive environment perspective.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"210-226"},"PeriodicalIF":4.6,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938291","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}
Marketing mix modeling (MMM) optimizes budget allocation and determines the return on advertising investment through market response analysis. MMM are vital tools to help marketers define their marketing strategies according to the firm's business and marketing objectives while reducing uncertainty in the decision-making process. As AI and automated MMM out-of-the-box packages gain popularity among marketers, it has become evident there is a theoretical and empirical gap in the understanding of the benefits and inconveniences of these new methods over traditional econometric models. To shed light on these questions, two different models using the same database from a telecommunications firm have been developed and tested using a traditional econometric model and Robyn, an AI-powered open-sourced MMM package from meta marketing science. The research compares both methods’ development processes and subsequent outputs from different perspectives: technical, business, and practical. It shows the advantages and shortcomings of each, providing insightful recommendations for academics and practitioners to navigate through the process of adoption of econometric and AI models for budget allocation decision-making. Econometric models are easy to explain and replicate, while AI complexity from the combination of several methods, their parametrization, and the random initialization of iterations during training, hinders its explainability.
{"title":"A Primer on Out-of-the-Box AI Marketing Mix Models","authors":"Macarena Estevez;María Teresa Ballestar;Jorge Sainz","doi":"10.1109/TEM.2024.3519172","DOIUrl":"https://doi.org/10.1109/TEM.2024.3519172","url":null,"abstract":"Marketing mix modeling (MMM) optimizes budget allocation and determines the return on advertising investment through market response analysis. MMM are vital tools to help marketers define their marketing strategies according to the firm's business and marketing objectives while reducing uncertainty in the decision-making process. As AI and automated MMM out-of-the-box packages gain popularity among marketers, it has become evident there is a theoretical and empirical gap in the understanding of the benefits and inconveniences of these new methods over traditional econometric models. To shed light on these questions, two different models using the same database from a telecommunications firm have been developed and tested using a traditional econometric model and Robyn, an AI-powered open-sourced MMM package from meta marketing science. The research compares both methods’ development processes and subsequent outputs from different perspectives: technical, business, and practical. It shows the advantages and shortcomings of each, providing insightful recommendations for academics and practitioners to navigate through the process of adoption of econometric and AI models for budget allocation decision-making. Econometric models are easy to explain and replicate, while AI complexity from the combination of several methods, their parametrization, and the random initialization of iterations during training, hinders its explainability.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"282-294"},"PeriodicalIF":4.6,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10804651","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938542","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 : 2024-12-16DOI: 10.1109/TEM.2024.3518585
Haiwen Li;Junying Liu;Bo Xia;Yanyan Hong
Organizational resilience (ORE) is crucial for businesses to cope with disruptions and achieve long-term survival in volatile environments. Strategic orientation (SO), which serves as a beacon for the long-term development of firms, has a significant influence on ORE. However, existing research remains inconclusive regarding the relationship between SO and ORE. This article seeks to investigate the mechanisms through which the emerging dimensions of SO—digital orientation (DO) and environmental orientation (EO)—impact ORE, drawing on resource orchestration (ROR) theory and organizational learning theory. In particular, we explore the mediating role of ROR in explaining the diverse pathways from DO and EO to ORE under the boundary conditions of organizational memory (OM) and environmental hostility (EH). This research tests the proposed hypotheses using a mixed-methods approach with a sample of 304 Chinese firms. The hierarchical multiple regression results indicate that both DO and EO positively affect ORE, with ROR serving as a full mediator. More interestingly, OM positively moderates the indirect effects of DO and EO on ORE via ROR, whereas EH only strengthens the indirect relationship between DO and ORE via ROR. Furthermore, the fuzzy set qualitative comparative analysis results reinforce these findings by revealing that four configurations of these variables can achieve high ORE. This study helps enrich the literature on SO and ORE and provides practical insights to guide firms in enhancing ORE.
{"title":"Surfing With the Tides: How Does Dual Strategic Orientation Enhance Organizational Resilience Through Resource Orchestration? A Moderated Mediation Model","authors":"Haiwen Li;Junying Liu;Bo Xia;Yanyan Hong","doi":"10.1109/TEM.2024.3518585","DOIUrl":"https://doi.org/10.1109/TEM.2024.3518585","url":null,"abstract":"Organizational resilience (ORE) is crucial for businesses to cope with disruptions and achieve long-term survival in volatile environments. Strategic orientation (SO), which serves as a beacon for the long-term development of firms, has a significant influence on ORE. However, existing research remains inconclusive regarding the relationship between SO and ORE. This article seeks to investigate the mechanisms through which the emerging dimensions of SO—digital orientation (DO) and environmental orientation (EO)—impact ORE, drawing on resource orchestration (ROR) theory and organizational learning theory. In particular, we explore the mediating role of ROR in explaining the diverse pathways from DO and EO to ORE under the boundary conditions of organizational memory (OM) and environmental hostility (EH). This research tests the proposed hypotheses using a mixed-methods approach with a sample of 304 Chinese firms. The hierarchical multiple regression results indicate that both DO and EO positively affect ORE, with ROR serving as a full mediator. More interestingly, OM positively moderates the indirect effects of DO and EO on ORE via ROR, whereas EH only strengthens the indirect relationship between DO and ORE via ROR. Furthermore, the fuzzy set qualitative comparative analysis results reinforce these findings by revealing that four configurations of these variables can achieve high ORE. This study helps enrich the literature on SO and ORE and provides practical insights to guide firms in enhancing ORE.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"252-266"},"PeriodicalIF":4.6,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938541","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 : 2024-12-09DOI: 10.1109/TEM.2024.3513773
Lin Zhang;Zhen Shao;Bin Chen;Jose Benitez
Despite the transformative potential of generative artificial intelligence (AI) systems within enterprise digital platforms, there still exist gaps in understanding the challenges and strategies associated with their adoption. Addressing this pressing issue, this article draws upon institutional theory to delve into the drivers influencing firms’ adoption of generative AI within their enterprise digital platforms. Leveraging survey data collected from 328 firms that have implemented digital platforms to support their business operations, we find that institutional pressures positively influence generative AI adoption within their enterprise digital platforms. Furthermore, we identify salient moderating effects of policy uncertainty and innovative culture in shaping the relationships. Our research findings make a substantial contribution to AI literature by illuminating the potential challenges and strategies toward generative AI adoption as well as reassessing the application of institutional theory within the digital landscape.
{"title":"Unraveling Generative AI Adoption in Enterprise Digital Platforms: The Effect of Institutional Pressures and the Moderating Role of Internal and External Environments","authors":"Lin Zhang;Zhen Shao;Bin Chen;Jose Benitez","doi":"10.1109/TEM.2024.3513773","DOIUrl":"https://doi.org/10.1109/TEM.2024.3513773","url":null,"abstract":"Despite the transformative potential of generative artificial intelligence (AI) systems within enterprise digital platforms, there still exist gaps in understanding the challenges and strategies associated with their adoption. Addressing this pressing issue, this article draws upon institutional theory to delve into the drivers influencing firms’ adoption of generative AI within their enterprise digital platforms. Leveraging survey data collected from 328 firms that have implemented digital platforms to support their business operations, we find that institutional pressures positively influence generative AI adoption within their enterprise digital platforms. Furthermore, we identify salient moderating effects of policy uncertainty and innovative culture in shaping the relationships. Our research findings make a substantial contribution to AI literature by illuminating the potential challenges and strategies toward generative AI adoption as well as reassessing the application of institutional theory within the digital landscape.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"335-348"},"PeriodicalIF":4.6,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142976131","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 : 2024-12-09DOI: 10.1109/TEM.2024.3514653
Yalan Zhu;Yufei Huang
How to launch multiple versions of a product sequentially into the market is always an important but challenging question. In this article, we consider the price–quality heuristic, namely consumers' strategic deliberation when they use prices to infer product quality over different versions, and employ an analytical model focusing on how the presence of the price–quality heuristic affects the firm's decision on product introduction strategies. Our analysis yields three main insights. First, in the presence of the price–quality heuristic, even though the sales of the earlier version are low, it can serve as a reference for consumers to better understand the quality improvement in the later version, therefore, can bring more profits to the firm. Second, when consumers use prices to infer product quality, the firm can benefit from consumers' strategic deliberation over different versions. Third, as the intensity of the price–quality heuristic becomes stronger, the firm's optimal pricing strategy switches from mark-down to mark-up. In an extension, we find that the trade-in program is optimal when quality improvement is big, but the price–quality heuristic undermines the advantage of the trade-in program. Our analysis indicates that the firm should carefully evaluate how consumers interpret product quality via prices when devising its product introduction strategy.
{"title":"Analysis of Product Introduction Strategies in the Presence of Price–Quality Heuristic","authors":"Yalan Zhu;Yufei Huang","doi":"10.1109/TEM.2024.3514653","DOIUrl":"https://doi.org/10.1109/TEM.2024.3514653","url":null,"abstract":"How to launch multiple versions of a product sequentially into the market is always an important but challenging question. In this article, we consider the price–quality heuristic, namely consumers' strategic deliberation when they use prices to infer product quality over different versions, and employ an analytical model focusing on how the presence of the price–quality heuristic affects the firm's decision on product introduction strategies. Our analysis yields three main insights. First, in the presence of the price–quality heuristic, even though the sales of the earlier version are low, it can serve as a reference for consumers to better understand the quality improvement in the later version, therefore, can bring more profits to the firm. Second, when consumers use prices to infer product quality, the firm can benefit from consumers' strategic deliberation over different versions. Third, as the intensity of the price–quality heuristic becomes stronger, the firm's optimal pricing strategy switches from mark-down to mark-up. In an extension, we find that the trade-in program is optimal when quality improvement is big, but the price–quality heuristic undermines the advantage of the trade-in program. Our analysis indicates that the firm should carefully evaluate how consumers interpret product quality via prices when devising its product introduction strategy.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"267-281"},"PeriodicalIF":4.6,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10787210","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938543","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 : 2024-12-09DOI: 10.1109/TEM.2024.3512780
Eva Panetti;Michele Simoni
This article explores the critical role of visual inquiry tools (VITs) in overcoming cognitive barriers to business model innovation (BMI), especially within the context of digital innovation. While existing tools have shown promise, they often fall short in addressing the specific cognitive barriers tied to business model transformation and lack a theoretical foundation. To bridge this gap, we followed the principles of design science research and design theory and designed the “transformative strategic thinking” (TST) tool. The TST tool is a VIT designed to facilitate BMI by stimulating the creative thinking abilities needed to challenge the dominant business model logic and experiment with alternative scenarios. In this article, we present the main phases of our design journey.
{"title":"Designing a Visual Inquiry Tool for Business Model Innovation","authors":"Eva Panetti;Michele Simoni","doi":"10.1109/TEM.2024.3512780","DOIUrl":"https://doi.org/10.1109/TEM.2024.3512780","url":null,"abstract":"This article explores the critical role of visual inquiry tools (VITs) in overcoming cognitive barriers to business model innovation (BMI), especially within the context of digital innovation. While existing tools have shown promise, they often fall short in addressing the specific cognitive barriers tied to business model transformation and lack a theoretical foundation. To bridge this gap, we followed the principles of design science research and design theory and designed the “transformative strategic thinking” (TST) tool. The TST tool is a VIT designed to facilitate BMI by stimulating the creative thinking abilities needed to challenge the dominant business model logic and experiment with alternative scenarios. In this article, we present the main phases of our design journey.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"134-145"},"PeriodicalIF":4.6,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142937850","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}
Crises caused by a broad spectrum of emergency triggers are creating unprecedented challenges for local and global institutions and business entities. The capacity of a system to respond and recover from a crisis is strongly influenced by the ability to manage coordination among “coalitions” of involved agents and to support dialogue and collaborative leadership. However, coordination science and engineering approaches have not been extensively investigated in crisis management studies and practitioner applications. This article is positioned in such a research gap and it adopts a cross-disciplinary view to design a novel crisis management paradigm, which defines coordination as a keystone of effective and efficient responses. In this article, we present a coordination core, with three key dependencies (i.e., fit, flow, and share) concerned with resource and activity management during a crisis, and four pillars of crisis prevention, crisis awareness, crisis response, and crisis recovery, with 64 associated attributes, including constructs, processes, tools, and analytics. We present two illustrative scenarios and we discuss that findings are made along a societal and organizational crisis management viewpoint. The article further develops crisis management theory by bringing a coordination engineering perspective, and it offers business leaders and policymakers a practical model for embedding crisis management capabilities in their organizations.
{"title":"Collaborative Crisis Management: A Coordination Science Framework to Enhance Stakeholder Responses to Emergencies","authors":"Alessandro Margherita;Gianluca Elia;Gianluca Solazzo;Luca Gatti;Annemarie Poorterman","doi":"10.1109/TEM.2024.3508037","DOIUrl":"https://doi.org/10.1109/TEM.2024.3508037","url":null,"abstract":"Crises caused by a broad spectrum of emergency triggers are creating unprecedented challenges for local and global institutions and business entities. The capacity of a system to respond and recover from a crisis is strongly influenced by the ability to manage coordination among “coalitions” of involved agents and to support dialogue and collaborative leadership. However, coordination science and engineering approaches have not been extensively investigated in crisis management studies and practitioner applications. This article is positioned in such a research gap and it adopts a cross-disciplinary view to design a novel crisis management paradigm, which defines coordination as a keystone of effective and efficient responses. In this article, we present a coordination core, with three key dependencies (i.e., fit, flow, and share) concerned with resource and activity management during a crisis, and four pillars of crisis prevention, crisis awareness, crisis response, and crisis recovery, with 64 associated attributes, including constructs, processes, tools, and analytics. We present two illustrative scenarios and we discuss that findings are made along a societal and organizational crisis management viewpoint. The article further develops crisis management theory by bringing a coordination engineering perspective, and it offers business leaders and policymakers a practical model for embedding crisis management capabilities in their organizations.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"191-201"},"PeriodicalIF":4.6,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142937853","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 : 2024-12-02DOI: 10.1109/TEM.2024.3510401
Xiuqi Jiang;Ying Jiang
The advent of digital transformation (DT) within Chinese listed companies has ushered in significant changes in the workplace, reshaping the dynamics of employee protection (EP). However, existing research focuses on the impact of DT on EP from the employee perspective and we want to explore the influence of DT on EP under the background of private listed companies in China. We adopt a two-way fixed-effect model and use the data of Chinese A-share-listed companies from 2010 to 2020 to analyze the impact of DT on the well-being of employees and its associated mechanism. This article analyzes the impact of DT on EP from both internal and external perspectives. By increasing external information disclosure and internal communication channels, enterprise DT enhances the pressure and ability of enterprises to fulfill employee responsibilities, thus strengthening EP. A series of robustness tests, such as instrumental variables, propensity score matching, increasing fixed effects and substituting variables, further verified our conclusion. The study further shows that these effects are more pronounced in firms with more external attention, high employee density, and visionary management. Our findings contribute significantly to the literature on DT and employee welfare by shedding light on the positive impacts of DT on EP and providing decision support for managers and policymakers.
{"title":"The Impact of Digital Transformation on Employee Protection","authors":"Xiuqi Jiang;Ying Jiang","doi":"10.1109/TEM.2024.3510401","DOIUrl":"https://doi.org/10.1109/TEM.2024.3510401","url":null,"abstract":"The advent of digital transformation (DT) within Chinese listed companies has ushered in significant changes in the workplace, reshaping the dynamics of employee protection (EP). However, existing research focuses on the impact of DT on EP from the employee perspective and we want to explore the influence of DT on EP under the background of private listed companies in China. We adopt a two-way fixed-effect model and use the data of Chinese A-share-listed companies from 2010 to 2020 to analyze the impact of DT on the well-being of employees and its associated mechanism. This article analyzes the impact of DT on EP from both internal and external perspectives. By increasing external information disclosure and internal communication channels, enterprise DT enhances the pressure and ability of enterprises to fulfill employee responsibilities, thus strengthening EP. A series of robustness tests, such as instrumental variables, propensity score matching, increasing fixed effects and substituting variables, further verified our conclusion. The study further shows that these effects are more pronounced in firms with more external attention, high employee density, and visionary management. Our findings contribute significantly to the literature on DT and employee welfare by shedding light on the positive impacts of DT on EP and providing decision support for managers and policymakers.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"72 ","pages":"202-209"},"PeriodicalIF":4.6,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142937854","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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