Pub Date : 2025-10-01DOI: 10.1016/j.jengtecman.2025.101919
Francesco Schiavone , Francesco Paolo Appio , Daniel Palacios , Sai Lan
The advancement of digital technologies such as AI, blockchain, and IoT is reshaping business models and driving societal change. This issue examines how organizations innovate to meet evolving social demands, strategic uncertainties, and ethical challenges. Drawing from diverse sectors, the contributions highlight mechanisms for responsible and sustainable innovation, including leadership, dynamic capabilities, and inclusive collaboration. The studies emphasize the need to manage innovation with foresight and resilience. Building on these insights, future research should explore ethical governance, digital equity, and human capital dynamics to better understand how digital business models can foster inclusive and impactful societal outcomes.
{"title":"Managing the innovation of business models for social change and digital transformation: Future challenges and scenarios","authors":"Francesco Schiavone , Francesco Paolo Appio , Daniel Palacios , Sai Lan","doi":"10.1016/j.jengtecman.2025.101919","DOIUrl":"10.1016/j.jengtecman.2025.101919","url":null,"abstract":"<div><div>The advancement of digital technologies such as AI, blockchain, and IoT is reshaping business models and driving societal change. This issue examines how organizations innovate to meet evolving social demands, strategic uncertainties, and ethical challenges. Drawing from diverse sectors, the contributions highlight mechanisms for responsible and sustainable innovation, including leadership, dynamic capabilities, and inclusive collaboration. The studies emphasize the need to manage innovation with foresight and resilience. Building on these insights, future research should explore ethical governance, digital equity, and human capital dynamics to better understand how digital business models can foster inclusive and impactful societal outcomes.</div></div>","PeriodicalId":50209,"journal":{"name":"Journal of Engineering and Technology Management","volume":"78 ","pages":"Article 101919"},"PeriodicalIF":3.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145693362","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 : 2025-10-01DOI: 10.1016/j.jengtecman.2025.101922
Dongping Yu , Yalin Zheng , Ying Sun , Minchao Liao , Tiantian Kong , Lazarus Masule Jamu
In the context of the knowledge economy, the complexity of technological innovation networks is increasing, leading to the formation of relationship divisive faultlines among innovation stakeholders based on varying levels of proximity. While this phenomenon gives rise to both intra-subgroup and inter-subgroup reciprocity within the network, there has been limited exploration of the relationship between relationship divisive faultlines and subgroup reciprocity. Drawing on faultlines theory, cohesive subgroup theory, and organizational learning theory, this study analyses global patent data in the unmanned aerial vehicle field from 2002 to 2021 to construct a technological innovation network. Empirical findings reveal an inverted U-shaped relationship between relationship divisive faultlines and subgroup reciprocity. Specifically, knowledge search and knowledge absorption partially mediate this relationship. These results highlight the sequential mediating role of knowledge search and absorption in influencing subgroup reciprocity within technological innovation networks, contributing valuable insights to subgroup theory.
{"title":"Relationship divisive faultlines and subgroup reciprocity in technological innovation networks: Analysing the sequential mediating role","authors":"Dongping Yu , Yalin Zheng , Ying Sun , Minchao Liao , Tiantian Kong , Lazarus Masule Jamu","doi":"10.1016/j.jengtecman.2025.101922","DOIUrl":"10.1016/j.jengtecman.2025.101922","url":null,"abstract":"<div><div>In the context of the knowledge economy, the complexity of technological innovation networks is increasing, leading to the formation of relationship divisive faultlines among innovation stakeholders based on varying levels of proximity. While this phenomenon gives rise to both intra-subgroup and inter-subgroup reciprocity within the network, there has been limited exploration of the relationship between relationship divisive faultlines and subgroup reciprocity. Drawing on faultlines theory, cohesive subgroup theory, and organizational learning theory, this study analyses global patent data in the unmanned aerial vehicle field from 2002 to 2021 to construct a technological innovation network. Empirical findings reveal an inverted U-shaped relationship between relationship divisive faultlines and subgroup reciprocity. Specifically, knowledge search and knowledge absorption partially mediate this relationship. These results highlight the sequential mediating role of knowledge search and absorption in influencing subgroup reciprocity within technological innovation networks, contributing valuable insights to subgroup theory.</div></div>","PeriodicalId":50209,"journal":{"name":"Journal of Engineering and Technology Management","volume":"78 ","pages":"Article 101922"},"PeriodicalIF":3.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145333289","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 : 2025-10-01DOI: 10.1016/j.jengtecman.2025.101924
Tanya Munir
Purpose
The study examines how leadership competency fosters the integration of Generative AI within two-sided platform environments, specifically focusing on its impact on improving teamwork productivity. The study delves into the dynamic of integrating Gen AI within entertainment industry, focusing on the influence of socially responsible innovation and behavioral change required for successful adoption.
Methodology
The study employed a quantitative survey-based approach using random sampling of employees from Pakistani entertainment agencies. Data were collected via online platforms over four months, securing 530 valid responses.
Findings
All four hypothesis are supported, underscoring the study pivotal role of leadership competency in driving Gen AI adoption and enhancing teamwork productivity. The study findings highlight that platform-based interactions benefit from AI enabled leadership strategies and that socially responsible innovative practices, coupled with behavioral change act as critical enablers in two sided AI-enhanced ecosystems.
Practical implications
Managers can use these results to design training programs, foster AI-driven collaboration, and implement socially responsible innovation practices, ensuring efficiency, reduced bias, and sustained competitiveness across diverse organizational settings.
Social implications
By promoting ethical, transparent, and inclusive AI practices, organizations can enhance employee trust, encourage behavioral change, and create equitable opportunities for collaboration. These insights support broader societal goals of fairness, accountability, and sustainability in technology-enabled workplaces.
{"title":"Leadership competency and Gen AI in two-sided platforms: Driving innovation, productivity, and responsible change in the entertainment industry","authors":"Tanya Munir","doi":"10.1016/j.jengtecman.2025.101924","DOIUrl":"10.1016/j.jengtecman.2025.101924","url":null,"abstract":"<div><h3>Purpose</h3><div>The study examines how leadership competency fosters the integration of Generative AI within two-sided platform environments, specifically focusing on its impact on improving teamwork productivity. The study delves into the dynamic of integrating Gen AI within entertainment industry, focusing on the influence of socially responsible innovation and behavioral change required for successful adoption.</div></div><div><h3>Methodology</h3><div>The study employed a quantitative survey-based approach using random sampling of employees from Pakistani entertainment agencies. Data were collected via online platforms over four months, securing 530 valid responses.</div></div><div><h3>Findings</h3><div>All four hypothesis are supported, underscoring the study pivotal role of leadership competency in driving Gen AI adoption and enhancing teamwork productivity. The study findings highlight that platform-based interactions benefit from AI enabled leadership strategies and that socially responsible innovative practices, coupled with behavioral change act as critical enablers in two sided AI-enhanced ecosystems.</div></div><div><h3>Practical implications</h3><div>Managers can use these results to design training programs, foster AI-driven collaboration, and implement socially responsible innovation practices, ensuring efficiency, reduced bias, and sustained competitiveness across diverse organizational settings.</div></div><div><h3>Social implications</h3><div>By promoting ethical, transparent, and inclusive AI practices, organizations can enhance employee trust, encourage behavioral change, and create equitable opportunities for collaboration. These insights support broader societal goals of fairness, accountability, and sustainability in technology-enabled workplaces.</div></div>","PeriodicalId":50209,"journal":{"name":"Journal of Engineering and Technology Management","volume":"78 ","pages":"Article 101924"},"PeriodicalIF":3.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145528444","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 : 2025-10-01DOI: 10.1016/j.jengtecman.2025.101926
Antonio Lerro , Giovanni Schiuma , Ciro Troise , Daniela Carlucci , Francesco Santarsiero
This paper proposes the Technology-Enhanced Learning Spaces (TELS) as physical and virtual structures that support and enhance acceleration programs, particularly by fostering continuous learning, collaborative dynamics, knowledge acquisition, and developing organizational capabilities and soft skills. Specifically, the analysis focuses on how the TELS can help the accelerators to manage knowledge flows more effectively and contribute to the growth and innovation of startups. A series of case studies is presented to show the applicability of the TELS’ activities to current acceleration programming. Five different TELS were identified and thoroughly investigated. A comparative analysis was, then, conducted to extract actionable managerial insights. The study identifies the characteristics and the activities of TELS that may enhance acceleration programs. The findings also emphasize the importance of managing both “inside-out” and “outside-in” knowledge flows under open innovation principles. The research contributes to the existing literature by providing a comprehensive framework and effective empirical evidences for better designing and managing successful acceleration programs.
{"title":"Driving innovation through knowledge: Integrating Technology-Enhanced Learning Spaces (TELS) for successful acceleration programs","authors":"Antonio Lerro , Giovanni Schiuma , Ciro Troise , Daniela Carlucci , Francesco Santarsiero","doi":"10.1016/j.jengtecman.2025.101926","DOIUrl":"10.1016/j.jengtecman.2025.101926","url":null,"abstract":"<div><div>This paper proposes the Technology-Enhanced Learning Spaces (TELS) as physical and virtual structures that support and enhance acceleration programs, particularly by fostering continuous learning, collaborative dynamics, knowledge acquisition, and developing organizational capabilities and soft skills. Specifically, the analysis focuses on how the TELS can help the accelerators to manage knowledge flows more effectively and contribute to the growth and innovation of startups. A series of case studies is presented to show the applicability of the TELS’ activities to current acceleration programming. Five different TELS were identified and thoroughly investigated. A comparative analysis was, then, conducted to extract actionable managerial insights. The study identifies the characteristics and the activities of TELS that may enhance acceleration programs. The findings also emphasize the importance of managing both <em>“inside-out”</em> and <em>“outside-in”</em> knowledge flows under open innovation principles. The research contributes to the existing literature by providing a comprehensive framework and effective empirical evidences for better designing and managing successful acceleration programs.</div></div>","PeriodicalId":50209,"journal":{"name":"Journal of Engineering and Technology Management","volume":"78 ","pages":"Article 101926"},"PeriodicalIF":3.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145618098","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 : 2025-09-27DOI: 10.1016/j.jengtecman.2025.101918
Yan Zhao , Qiuying Li , Jianlin Lyu , Hong Du , Alexander Brem
In the context of open innovation, effectively integrating internal and external collaborative networks to leverage relevant knowledge is crucial for enhancing innovation capabilities. Current research has largely overlooked the potential non-linear effects of knowledge relatedness (similarity and complementarity) in external collaboration networks on firm innovation capability, particularly the risk of innovation suppression caused by excessive relatedness. Moreover, systematic investigation is still lacking regarding how internal inventor collaboration networks moderate this relationship. Using a sample of 189 publicly listed firms and employing social network analysis along with negative binomial regression modeling, this study addresses two key questions: (1) Does knowledge relatedness in external collaboration networks nonlinearly affect firm innovation capability? (2) How does the structure of internal collaboration networks influence this relationship? The findings reveal an inverted U-shaped relationship between both knowledge similarity (the alignment of a firm's internal knowledge) and knowledge complementarity (differences between shared resources) and firm innovation capability. Moderate levels of knowledge similarity and complementarity are most conducive to enhancing innovation capability. Furthermore, transitivity within internal inventor collaboration networks strengthens the effect of knowledge relatedness on innovation, whereas network stability weakens it. These results extend the application of absorptive capacity theory in network innovation contexts and offer a theoretical basis for firms to optimize partner selection and improve internal collaboration mechanisms.
{"title":"External collaboration network knowledge relatedness and firm innovation capability: The moderating effect of the internal inventor collaboration network","authors":"Yan Zhao , Qiuying Li , Jianlin Lyu , Hong Du , Alexander Brem","doi":"10.1016/j.jengtecman.2025.101918","DOIUrl":"10.1016/j.jengtecman.2025.101918","url":null,"abstract":"<div><div>In the context of open innovation, effectively integrating internal and external collaborative networks to leverage relevant knowledge is crucial for enhancing innovation capabilities. Current research has largely overlooked the potential non-linear effects of knowledge relatedness (similarity and complementarity) in external collaboration networks on firm innovation capability, particularly the risk of innovation suppression caused by excessive relatedness. Moreover, systematic investigation is still lacking regarding how internal inventor collaboration networks moderate this relationship. Using a sample of 189 publicly listed firms and employing social network analysis along with negative binomial regression modeling, this study addresses two key questions: (1) Does knowledge relatedness in external collaboration networks nonlinearly affect firm innovation capability? (2) How does the structure of internal collaboration networks influence this relationship? The findings reveal an inverted U-shaped relationship between both knowledge similarity (the alignment of a firm's internal knowledge) and knowledge complementarity (differences between shared resources) and firm innovation capability. Moderate levels of knowledge similarity and complementarity are most conducive to enhancing innovation capability. Furthermore, transitivity within internal inventor collaboration networks strengthens the effect of knowledge relatedness on innovation, whereas network stability weakens it. These results extend the application of absorptive capacity theory in network innovation contexts and offer a theoretical basis for firms to optimize partner selection and improve internal collaboration mechanisms.</div></div>","PeriodicalId":50209,"journal":{"name":"Journal of Engineering and Technology Management","volume":"78 ","pages":"Article 101918"},"PeriodicalIF":3.9,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145159471","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 : 2025-09-26DOI: 10.1016/j.jengtecman.2025.101914
Pia Hautamäki , Minna Heikinheimo
Many traditional business-to-business (B2B) firms across industries have introduced digital platforms to enhance joint value creation and productivity, using artificial intelligence (AI) for platform development. Platform owners play a critical role in such platforms’ governance and in designing platform-based business models (BMs) to foster value creation within platform ecosystems. Given the complex architecture of B2B platforms, platform owners must continuously renew their capabilities and shift their mindset throughout the platform lifecycle to innovate new platform-based BMs, and they increasingly use AI tools for this purpose. However, little research on business model innovation (BMI) has focused on how managers can shift their mindsets to support the evolution of digital platforms or how AI can support these shifts. Therefore, this study investigates how AI is advancing BMI in the platform context and what mindset shifts must occur in managers. We focused on nine traditional firms that are B2B platform owners and interviewed 15 managers. Our findings show that AI plays three distinct roles in the evolution of a digital platform’s BMI: AI as Optimizer, as Expander, and as Creator. Our findings emphasize that AI-powered BMI in platform ecosystems is not solely technology driven but also requires significant shifts in managers’ mindsets. We also provide practical insights, demonstrating how AI’s capacity to process vast amounts of data can empower platform owners to develop more sophisticated BMI. Furthermore, we encourage managers in traditional firms to reflect on their own mindsets during digital platform evolution.
{"title":"Transforming mindsets toward open industry platforms: The role of AI in business model innovation","authors":"Pia Hautamäki , Minna Heikinheimo","doi":"10.1016/j.jengtecman.2025.101914","DOIUrl":"10.1016/j.jengtecman.2025.101914","url":null,"abstract":"<div><div>Many traditional business-to-business (B2B) firms across industries have introduced digital platforms to enhance joint value creation and productivity, using artificial intelligence (AI) for platform development. Platform owners play a critical role in such platforms’ governance and in designing platform-based business models (BMs) to foster value creation within platform ecosystems. Given the complex architecture of B2B platforms, platform owners must continuously renew their capabilities and shift their mindset throughout the platform lifecycle to innovate new platform-based BMs, and they increasingly use AI tools for this purpose. However, little research on business model innovation (BMI) has focused on how managers can shift their mindsets to support the evolution of digital platforms or how AI can support these shifts. Therefore, this study investigates how AI is advancing BMI in the platform context and what mindset shifts must occur in managers. We focused on nine traditional firms that are B2B platform owners and interviewed 15 managers. Our findings show that AI plays three distinct roles in the evolution of a digital platform’s BMI: <em>AI as Optimizer, as Expander,</em> and <em>as Creator.</em> Our findings emphasize that AI-powered BMI in platform ecosystems is not solely technology driven but also requires significant shifts in managers’ mindsets. We also provide practical insights, demonstrating how AI’s capacity to process vast amounts of data can empower platform owners to develop more sophisticated BMI. Furthermore, we encourage managers in traditional firms to reflect on their own mindsets during digital platform evolution.</div></div>","PeriodicalId":50209,"journal":{"name":"Journal of Engineering and Technology Management","volume":"78 ","pages":"Article 101914"},"PeriodicalIF":3.9,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145159472","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 : 2025-09-25DOI: 10.1016/j.jengtecman.2025.101916
Neng Shen, Lianjun Wu, Jingwen Zhou, Jing Zhang
With the acceleration of a new round of technological revolution and industrial transformation, the innovation ecosystem has emerged as a central focus in both academic research and managerial practice. Based on a combination of bibliometric co-citation network analysis, citation relationship path analysis, and bibliographic coupling analysis, this study systematically reviews the literature on innovation ecosystem indexed in the Web of Science (WOS) database from 2006 to 2023. First, we categorize the evolution of innovation ecosystem research into distinct stages based on the screened literature and present the distribution of relevant publications across academic journals. Second, following a “point-line-surface” analytical framework, we identify ten key publications (research nodes), two historical developmental paths (evolutionary trajectories), and three major knowledge clusters (thematic areas) within the field. Finally, adhering to a logical structure of definition–structure–evaluation–optimization, we propose five potential or underexplored directions for future research on innovation ecosystem. This study offers valuable insights and guidance for policymakers, industry leaders, and business decision-makers seeking a deeper understanding of innovation ecosystem.
随着新一轮技术革命和产业变革的加速推进，创新生态系统已成为学术界和管理实践关注的焦点。本文采用文献计量共被引网络分析、引文关系路径分析和书目耦合分析相结合的方法，对Web of Science （WOS）数据库2006 - 2023年收录的创新生态系统文献进行了系统回顾。首先，在文献筛选的基础上，将创新生态系统研究的演进划分为不同的阶段，并给出了相关文献在学术期刊上的分布情况。其次，根据“点-线-面”分析框架，我们确定了该领域内的十个关键出版物（研究节点），两条历史发展路径（进化轨迹）和三个主要知识集群（专题领域）。最后，按照“定义-结构-评价-优化”的逻辑结构，提出了创新生态系统未来研究的五个潜在或未开发的方向。本研究为寻求对创新生态系统更深入理解的政策制定者、行业领导者和商业决策者提供了有价值的见解和指导。
{"title":"Mapping innovation ecosystem research published from 2006 to 2023: A scientometric review","authors":"Neng Shen, Lianjun Wu, Jingwen Zhou, Jing Zhang","doi":"10.1016/j.jengtecman.2025.101916","DOIUrl":"10.1016/j.jengtecman.2025.101916","url":null,"abstract":"<div><div>With the acceleration of a new round of technological revolution and industrial transformation, the innovation ecosystem has emerged as a central focus in both academic research and managerial practice. Based on a combination of bibliometric co-citation network analysis, citation relationship path analysis, and bibliographic coupling analysis, this study systematically reviews the literature on innovation ecosystem indexed in the Web of Science (WOS) database from 2006 to 2023. First, we categorize the evolution of innovation ecosystem research into distinct stages based on the screened literature and present the distribution of relevant publications across academic journals. Second, following a “point-line-surface” analytical framework, we identify ten key publications (research nodes), two historical developmental paths (evolutionary trajectories), and three major knowledge clusters (thematic areas) within the field. Finally, adhering to a logical structure of definition–structure–evaluation–optimization, we propose five potential or underexplored directions for future research on innovation ecosystem. This study offers valuable insights and guidance for policymakers, industry leaders, and business decision-makers seeking a deeper understanding of innovation ecosystem.</div></div>","PeriodicalId":50209,"journal":{"name":"Journal of Engineering and Technology Management","volume":"78 ","pages":"Article 101916"},"PeriodicalIF":3.9,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145160185","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 : 2025-09-17DOI: 10.1016/j.jengtecman.2025.101912
Songhee Kang , Jörn Altmann , Ahreum Hong
This study investigates the impact of knowledge absorption and transfer timing on firm performance in the software industry, utilizing 11 years of transaction-level tax invoice data from 2665 firms. Results reveal that early-stage knowledge absorption has a stronger and more sustained impact on performance than late-stage absorption, while knowledge transfer yields only short-term benefits. Firms that consistently internalize external knowledge over the product life cycle outperform those that do not. These findings underscore the significance of temporal alignment in knowledge management strategies, suggesting that software supply chains should prioritize early and continuous knowledge absorption to enhance competitiveness and innovation outcomes.
{"title":"Strategic insights into temporal knowledge management in software industry networks","authors":"Songhee Kang , Jörn Altmann , Ahreum Hong","doi":"10.1016/j.jengtecman.2025.101912","DOIUrl":"10.1016/j.jengtecman.2025.101912","url":null,"abstract":"<div><div>This study investigates the impact of knowledge absorption and transfer timing on firm performance in the software industry, utilizing 11 years of transaction-level tax invoice data from 2665 firms. Results reveal that early-stage knowledge absorption has a stronger and more sustained impact on performance than late-stage absorption, while knowledge transfer yields only short-term benefits. Firms that consistently internalize external knowledge over the product life cycle outperform those that do not. These findings underscore the significance of temporal alignment in knowledge management strategies, suggesting that software supply chains should prioritize early and continuous knowledge absorption to enhance competitiveness and innovation outcomes.</div></div>","PeriodicalId":50209,"journal":{"name":"Journal of Engineering and Technology Management","volume":"78 ","pages":"Article 101912"},"PeriodicalIF":3.9,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145107827","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 : 2025-09-14DOI: 10.1016/j.jengtecman.2025.101911
Francesco Fasano , Chiara Bartoli , Francesco Cappa , Paolo Boccardelli
Advancements in information technologies have revolutionized business models (BMs), which are now increasingly based on digital platforms. The spread of Web3 has led to further development in this direction, giving rise to platform business models enabled by blockchain technology. At the same time, the advent of artificial intelligence (AI) has further expanded opportunities to innovate BMs. In this study we examine how the integration of AI influences BMs in blockchain-based platforms. We find that the integration of AI plays a key role in the three main dimensions of platform business models: value creation, value delivery, and value capture. We demonstrate, in particular, how AI enhances operational efficiency, strategic governance, and decision-making in Web3 platforms enabled by blockchains. Moreover, AI optimizes personalization, matching processes, and interactions in decentralized platforms. AI also fosters innovation in decentralized platform BMs and requires a skilled workforce. This research underscores how AI can improve performance in blockchain-based platforms, advancing scientific knowledge of decentralized platforms and offering recommendations for managers and policymakers on how to innovate their BMs and leverage AI to maximize value across platforms.
{"title":"Exploring the impact of AI on Web3 decentralized platform business model innovation","authors":"Francesco Fasano , Chiara Bartoli , Francesco Cappa , Paolo Boccardelli","doi":"10.1016/j.jengtecman.2025.101911","DOIUrl":"10.1016/j.jengtecman.2025.101911","url":null,"abstract":"<div><div>Advancements in information technologies have revolutionized business models (BMs), which are now increasingly based on digital platforms. The spread of Web3 has led to further development in this direction, giving rise to platform business models enabled by blockchain technology. At the same time, the advent of artificial intelligence (AI) has further expanded opportunities to innovate BMs. In this study we examine how the integration of AI influences BMs in blockchain-based platforms. We find that the integration of AI plays a key role in the three main dimensions of platform business models: value creation, value delivery, and value capture. We demonstrate, in particular, how AI enhances operational efficiency, strategic governance, and decision-making in Web3 platforms enabled by blockchains. Moreover, AI optimizes personalization, matching processes, and interactions in decentralized platforms. AI also fosters innovation in decentralized platform BMs and requires a skilled workforce. This research underscores how AI can improve performance in blockchain-based platforms, advancing scientific knowledge of decentralized platforms and offering recommendations for managers and policymakers on how to innovate their BMs and leverage AI to maximize value across platforms.</div></div>","PeriodicalId":50209,"journal":{"name":"Journal of Engineering and Technology Management","volume":"78 ","pages":"Article 101911"},"PeriodicalIF":3.9,"publicationDate":"2025-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145057276","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 : 2025-07-01DOI: 10.1016/j.jengtecman.2025.101899
Jie Mi , Jiamin Dong
In the process of coupled exploration, when feedback from other teams comes in the form of disapproval, comments, and suggestions, teams may need to modify the existing technical routes or even abandon previous choices, which can perturb their ongoing exploration activities. We employ a multi-agent computational model to analyze the aforementioned processes. We have found that frequent perturbations among the R&D teams responsible for various subsystems can significantly impact the performance of coupled exploration, which is highly dependent on the speed at which teams search for better options and reach consensus. During the initial phase of coupling exploration, frequent perturbations permanently alter the trajectory of the exploration process. The reciprocal perturbation during the intermediate stage enhances the capacity for coupled exploration in subsequent stages, contingent upon the actor’s adeptness in swiftly discerning and selecting optimal strategies. When the team’s ability to identify the correct solution is weak, frequent early perturbations can result in increased divergence in feedback among teams. The presence of conflicting advice from other teams exacerbates the challenges faced by actors in making informed judgments based on feedback.
{"title":"Mutual perturbations in coupled exploration: Diverse impacts of feedback frequency and feedback timing","authors":"Jie Mi , Jiamin Dong","doi":"10.1016/j.jengtecman.2025.101899","DOIUrl":"10.1016/j.jengtecman.2025.101899","url":null,"abstract":"<div><div>In the process of coupled exploration, when feedback from other teams comes in the form of disapproval, comments, and suggestions, teams may need to modify the existing technical routes or even abandon previous choices, which can perturb their ongoing exploration activities. We employ a multi-agent computational model to analyze the aforementioned processes. We have found that frequent perturbations among the R&D teams responsible for various subsystems can significantly impact the performance of coupled exploration, which is highly dependent on the speed at which teams search for better options and reach consensus. During the initial phase of coupling exploration, frequent perturbations permanently alter the trajectory of the exploration process. The reciprocal perturbation during the intermediate stage enhances the capacity for coupled exploration in subsequent stages, contingent upon the actor’s adeptness in swiftly discerning and selecting optimal strategies. When the team’s ability to identify the correct solution is weak, frequent early perturbations can result in increased divergence in feedback among teams. The presence of conflicting advice from other teams exacerbates the challenges faced by actors in making informed judgments based on feedback.</div></div>","PeriodicalId":50209,"journal":{"name":"Journal of Engineering and Technology Management","volume":"77 ","pages":"Article 101899"},"PeriodicalIF":3.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581315","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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