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}
Pub Date : 2025-07-01DOI: 10.1016/j.jengtecman.2025.101895
Xiaobin Feng, Bowen Xiao, Hanzhong Zheng
Although the importance of digital technology in fostering cross-boundary innovation (CBI) has attracted increasing attention from scholars and practitioners, research gaps persist concerning how firms’ capabilities in leveraging digital technologies influence CBI and the boundary conditions that either facilitate or impede its effectiveness. Based on firm capability theory, this study distinguishes firms’ digital ambidextrous capabilities to achieve different digital goals from an organisational ambidexterity perspective. Using fixed effects and interaction effects models to analyse data from 730 publicly listed Chinese firms, this investigation explores the roles of digital exploratory capability (DERC) and digital exploitative capability (DEIC) in enhancing CBI. The results indicate that DERC and DEIC substantially foster CBI. Technological diversification acts as a positive moderator in the relationship between DERC and CBI, whilst exhibiting an inverted U-shaped moderation between DEIC and CBI. Furthermore, environmental turbulence moderates the relationship between DERC and CBI in an inverted U-shape and positively moderates the relationship between DEIC and CBI. Additionally, SOEs are more reliant on DEIC for CBI and less susceptible to environmental turbulence. This study provides new managerial insights for firms to establish and leverage digital ambidextrous capabilities to achieve CBI.
{"title":"The key role of digital ambidextrous capabilities in cross-boundary innovation: Moderating effects of technological diversification and environmental turbulence","authors":"Xiaobin Feng, Bowen Xiao, Hanzhong Zheng","doi":"10.1016/j.jengtecman.2025.101895","DOIUrl":"10.1016/j.jengtecman.2025.101895","url":null,"abstract":"<div><div>Although the importance of digital technology in fostering cross-boundary innovation (CBI) has attracted increasing attention from scholars and practitioners, research gaps persist concerning how firms’ capabilities in leveraging digital technologies influence CBI and the boundary conditions that either facilitate or impede its effectiveness. Based on firm capability theory, this study distinguishes firms’ digital ambidextrous capabilities to achieve different digital goals from an organisational ambidexterity perspective. Using fixed effects and interaction effects models to analyse data from 730 publicly listed Chinese firms, this investigation explores the roles of digital exploratory capability (DERC) and digital exploitative capability (DEIC) in enhancing CBI. The results indicate that DERC and DEIC substantially foster CBI. Technological diversification acts as a positive moderator in the relationship between DERC and CBI, whilst exhibiting an inverted U-shaped moderation between DEIC and CBI. Furthermore, environmental turbulence moderates the relationship between DERC and CBI in an inverted U-shape and positively moderates the relationship between DEIC and CBI. Additionally, SOEs are more reliant on DEIC for CBI and less susceptible to environmental turbulence. This study provides new managerial insights for firms to establish and leverage digital ambidextrous capabilities to achieve CBI.</div></div>","PeriodicalId":50209,"journal":{"name":"Journal of Engineering and Technology Management","volume":"77 ","pages":"Article 101895"},"PeriodicalIF":3.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144514145","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.2025.101898
Lea Daniel , Lars Groeger , Katharina Hölzle
<div><div>Technological change presents significant challenges for organizations and society and needs to be understood from a socio-technical perspective. Technology and Innovation Management (TIM) can play a crucial role in understanding disruptive change. Smart farming technologies (SFTs) are used as prime examples for disruption in a traditional industry. This paper shows how scholars can use TIM theories to contribute to a better understanding and subsequent recommendations for action. We review 973 articles using bibliographic coupling to synthesize existing literature. We identify the most prominent research themes and problematize the existing narratives in light of three theoretical approaches to technological change: evolutionary economics, social construction of technology, and actor-network theory. Finally, we present theory-driven questions for future research that indicate new directions for TIM. We comprehensively review and synthesize existing research at the intersection of smart farming technologies and the TIM domain, using bibliographic coupling to identify prominent research themes, highlight blind spots, and generate questions for future research. To counter the common shortcomings of systematic literature reviews in general (Alvesson and Sandberg, 2020) and trending automated literature reviews, we supplement our analysis with an extensive explorative-qualitative discussion of the results, linking our findings back to theory and deriving a comprehensive set of research questions for future research. We build upon Bruun and Hukkinens’ (2003) Integrative Framework for Studying Technological Change to guide our discussion and expand our critical review. Thus, we make three main contributions. First, we give a curated and comprehensive overview of articles on SFT and technological change to identify the theoretical deficiencies that lead to oversimplified assumptions regarding the dissemination of smart farming technologies. Second, we enrich the TIM literature by applying three established theories of technological change in a particular sector, making the connection between a specific domain of technological application (SFT) and established theories in the technology and innovation management field. Third, by detailing the extent to which the three theories help us understand the existing literature and discussing it in its entire complexity, we identify several blind spots of current research and derive research questions for future research in both, the SFT and the TIM field. This approach opposes a technology-deterministic and simplistic view of technological developments. By doing so, we aim to inspire TIM scholars to use theories that sharpen their understanding of the socio-technical system and the complexity of technological change. The article is structured as follows: we present the current state of smart farming adoption and diffusion, introduce the theoretical framework, describe the methodology employed for our b
{"title":"Unpacking smart farming innovation: A systematic literature review on technological change in agriculture","authors":"Lea Daniel , Lars Groeger , Katharina Hölzle","doi":"10.1016/j.jengtecman.2025.101898","DOIUrl":"10.1016/j.jengtecman.2025.101898","url":null,"abstract":"<div><div>Technological change presents significant challenges for organizations and society and needs to be understood from a socio-technical perspective. Technology and Innovation Management (TIM) can play a crucial role in understanding disruptive change. Smart farming technologies (SFTs) are used as prime examples for disruption in a traditional industry. This paper shows how scholars can use TIM theories to contribute to a better understanding and subsequent recommendations for action. We review 973 articles using bibliographic coupling to synthesize existing literature. We identify the most prominent research themes and problematize the existing narratives in light of three theoretical approaches to technological change: evolutionary economics, social construction of technology, and actor-network theory. Finally, we present theory-driven questions for future research that indicate new directions for TIM. We comprehensively review and synthesize existing research at the intersection of smart farming technologies and the TIM domain, using bibliographic coupling to identify prominent research themes, highlight blind spots, and generate questions for future research. To counter the common shortcomings of systematic literature reviews in general (Alvesson and Sandberg, 2020) and trending automated literature reviews, we supplement our analysis with an extensive explorative-qualitative discussion of the results, linking our findings back to theory and deriving a comprehensive set of research questions for future research. We build upon Bruun and Hukkinens’ (2003) Integrative Framework for Studying Technological Change to guide our discussion and expand our critical review. Thus, we make three main contributions. First, we give a curated and comprehensive overview of articles on SFT and technological change to identify the theoretical deficiencies that lead to oversimplified assumptions regarding the dissemination of smart farming technologies. Second, we enrich the TIM literature by applying three established theories of technological change in a particular sector, making the connection between a specific domain of technological application (SFT) and established theories in the technology and innovation management field. Third, by detailing the extent to which the three theories help us understand the existing literature and discussing it in its entire complexity, we identify several blind spots of current research and derive research questions for future research in both, the SFT and the TIM field. This approach opposes a technology-deterministic and simplistic view of technological developments. By doing so, we aim to inspire TIM scholars to use theories that sharpen their understanding of the socio-technical system and the complexity of technological change. The article is structured as follows: we present the current state of smart farming adoption and diffusion, introduce the theoretical framework, describe the methodology employed for our b","PeriodicalId":50209,"journal":{"name":"Journal of Engineering and Technology Management","volume":"77 ","pages":"Article 101898"},"PeriodicalIF":3.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523521","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.2025.101896
Danilo Pesce , Claudia Franzè
The digitalization of cultural and creative industries has often followed a path of convergence between physical and digital artefacts, leading to the rise of digital platforms that reshape value chains. However, the cultural heritage sector has undergone a different form of digital transformation. Digital platforms in this field create a “phygital” experience that blends tradition with innovation. This study examines the role of digital platforms in fostering social and economic development in the cultural heritage sector, focusing on Google Arts & Culture, launched by Google in 2011. Through a longitudinal case study, we explore how digital platforms create value for multiple stakeholders—museums, users, and the platform itself—by enhancing efficiency, complementarities, novelty, and lock-in mechanisms. Our findings indicate that digital platforms introduce a more dynamic and complex ecosystem that drives growth and innovation while shifting cultural organizations from integrated supply chains to networks of strategic partnerships. The success of digital platforms in promoting social and economic development depends on museums’ ability to internalize legacy knowledge and platforms’ capacity to reinterpret this knowledge using advanced digital tools. This research contributes to the literature on innovation and strategic management by demonstrating that, rather than disrupting tradition, digital platforms enhance the cultural heritage experience. Additionally, while platforms like Google Arts & Culture operate under a non-profit model to democratize culture, they capture significant value through data aggregation, which may play a key role in training artificial intelligence systems.
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