Journal of Engineering and Technology Management最新文献

{"title":"External collaboration network knowledge relatedness and firm innovation capability: The moderating effect of the internal inventor collaboration network","authors":"Yan Zhao ,&nbsp;Qiuying Li ,&nbsp;Jianlin Lyu ,&nbsp;Hong Du ,&nbsp;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":"2025-10-01","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}

{"title":"Configuring AI-guided sustainable competitive advantage for SMEs through business model innovation: A systematic literature review approach","authors":"Ariful Islam ,&nbsp;Md Asadul Islam ,&nbsp;Francesca Dal Mas ,&nbsp;Justyna Fijałkowska ,&nbsp;Mahfuzur Rahman ,&nbsp;Maurizio Massaro","doi":"10.1016/j.jengtecman.2025.101921","DOIUrl":"10.1016/j.jengtecman.2025.101921","url":null,"abstract":"<div><div>Researchers have been exploring an effective framework for achieving competitive advantage for many years, specifically tailored to small and medium-sized enterprises (SMEs) to ensure their long-term survival. The recent surge in advanced technologies, particularly artificial intelligence (AI), has made their debates more challenging. Thus, the study proposes a conceptual framework specifically designed to leverage AI for long-term competitive advantage in SMEs, examining their business models through this lens. This study conducts a systematic literature review (SLR) to cover a broad range of relevant literature within a final sample of 69 articles. The SLR method was chosen to integrate research in a systematic, transparent, and reproducible way. For qualitative analysis and framework derivation, the study draws on a thematic ontological analysis. The study identifies multiple research streams at the intersection of advanced technology and entrepreneurship aimed at enhancing the competitiveness of SMEs. The primary outcome of this study is the development of a comprehensive business model framework, encompassing both external antecedents (namely, market and industry dynamics, technological infrastructure, government policies and support, strategic alliances, socio-cultural factors) and internal antecedents (digital leadership, dynamic capabilities/adaptability, entrepreneurial mindset, data strategy, growth/resilience), ultimately contributing to sustainable performance. Practically, the study provides a comprehensive avenue for SME owners and managers to adopt and use AI in business strategies and operations. Based on the results, SMEs can implement automation and machine learning to streamline business processes, minimize manual labor, and boost overall operational efficiency. More theoretical and practical implications, along with limitations and future directions, are also discussed, revealing multiple theoretical gateways and an agenda for subsequent empirical work.</div></div>","PeriodicalId":50209,"journal":{"name":"Journal of Engineering and Technology Management","volume":"78 ","pages":"Article 101921"},"PeriodicalIF":3.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269147","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}

{"title":"Mapping innovation ecosystem research published from 2006 to 2023: A scientometric review","authors":"Neng Shen,&nbsp;Lianjun Wu,&nbsp;Jingwen Zhou,&nbsp;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":"2025-10-01","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}

{"title":"Igniting twin transition through artificial intelligence and stakeholder value: The case of platform-based agri-food companies","authors":"Maria Chiara De Lorenzi,&nbsp;Marta Menegoli,&nbsp;Maria Laura Giangrande","doi":"10.1016/j.jengtecman.2025.101920","DOIUrl":"10.1016/j.jengtecman.2025.101920","url":null,"abstract":"<div><div>This study presents an original and relevant exploration of how platform-based companies can leverage Artificial Intelligence to address sustainability challenges, particularly in compliance with European Sustainable Development Goals. Starting by the observation of platformization as a process bringing to Business Model Innovation and focusing on the intersection of Artificial Intelligence and sustainability, the study fills a critical gap in existing literature, which often overlooks the specific implications of Artificial Intelligence integration in various business scenarios. A comprehensive conceptual framework that guides the study’s investigation into Artificial Intelligence as a boost for the twin transition with a focus on advancing stakeholder legitimacy within agri-food platform-based companies was designed. The study was based on a qualitative research approach through a three-phases methodology. The results of study derived from a Systematic Literature Review within content analysis and multiple case study that using desktop analysis on a 52 platform-based agri-food companies sample. Follow a discussion through inside-out and outside-in perspective underline results evidence in order to build academic evidence for practice and empirical evidence for academia. The use of Artificial Intelligence in sustainable practices provides concrete evidence that enhances the understanding of how value is created, captured, and delivered within platform-based business models for sustainability. Moreover, the impact of these AI-driven practices on stakeholder perceptions offers updated empirical insights into Stakeholder Theory, particularly regarding the practical mechanisms through which normative legitimacy is built or undermined in the context of advanced technologies. The research agenda outlines critical avenues for future investigation. These directions aim to deepen our understanding of the complex interplay between advanced technologies, sustainable transformation, and societal acceptance.</div></div>","PeriodicalId":50209,"journal":{"name":"Journal of Engineering and Technology Management","volume":"78 ","pages":"Article 101920"},"PeriodicalIF":3.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145333743","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}

{"title":"Transforming mindsets toward open industry platforms: The role of AI in business model innovation","authors":"Pia Hautamäki ,&nbsp;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":"2025-10-01","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}

{"title":"Beyond replacement: How project managers perceive the transformative role of AI in project work","authors":"Costanza Mariani,&nbsp;Mauro Mancini","doi":"10.1016/j.jengtecman.2025.101927","DOIUrl":"10.1016/j.jengtecman.2025.101927","url":null,"abstract":"<div><div>Recent advancements in Artificial Intelligence (AI) have intensified discussions about job transformation, with growing evidence that many professional roles will be significantly affected. This paper examines the impact of analytical AI systems on project management, focusing on how data-driven, algorithmic tools influence both the quantitative and qualitative dimensions of project management activities. While existing studies often highlight the potential of AI in this domain, they frequently concentrate on generative AI or overlook project managers’ own expectations regarding whether analytical AI will replace or augment their work. Using the Nominal Group Technique, this study investigates which project management activities practitioners expect to be replaced, supported, or remain unaffected by analytical AI. The findings reveal that although analytical AI is not anticipated to replace project managers, it is likely to reshape how tasks are executed. As a result, project managers will increasingly need to develop new skills and competencies to remain competitive in an AI-enhanced project environment.</div></div>","PeriodicalId":50209,"journal":{"name":"Journal of Engineering and Technology Management","volume":"78 ","pages":"Article 101927"},"PeriodicalIF":3.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145618099","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}

{"title":"Exploring the impact of AI on Web3 decentralized platform business model innovation","authors":"Francesco Fasano ,&nbsp;Chiara Bartoli ,&nbsp;Francesco Cappa ,&nbsp;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":"2025-10-01","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}

{"title":"Integrating AI and ESG in digital platforms: New profiles of platform-based business models","authors":"Giulia Nevi ,&nbsp;Raffaella Montera ,&nbsp;Nicola Cucari ,&nbsp;Francesco Laviola","doi":"10.1016/j.jengtecman.2025.101913","DOIUrl":"10.1016/j.jengtecman.2025.101913","url":null,"abstract":"<div><div>The integration of artificial intelligence (AI) into digital platforms is transforming the way businesses tackle environmental, social and governance (ESG) issues. This study investigates how AI can enable platform business models (Platform BMs) to create, deliver and capture ESG-related value, with a particular focus on the ESG rating industry. Using the Platform Business Model Canvas as a conceptual framework, and conducting a comparative analysis of six case studies, the research identifies three distinct configurations of AI-enabled Platform BMs: (1) ESG data wrangling and integration; (2) financial analysis and provision of ESG data to investors and companies; and (3) compliance and management of ESG issues in supply chains. Each configuration embeds specific mechanisms, such as predictive analytics, compliance automation and stakeholder coordination, through which AI can support ESG-oriented business innovation. Based on these findings, the study proposes four theoretical propositions that clarify the relationships between AI capabilities, data governance, and ESG value creation within platform ecosystems. The paper advances the academic understanding of the relationship between AI and sustainability and provides a typology to inform the strategic development of ESG-focused digital platforms.</div></div>","PeriodicalId":50209,"journal":{"name":"Journal of Engineering and Technology Management","volume":"78 ","pages":"Article 101913"},"PeriodicalIF":3.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221733","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}

{"title":"Craftsmen and digital transformation: Business strategies and contracts in a post-Covid world","authors":"Maria Alice Moreira Trindade ,&nbsp;Pietro De Giovanni","doi":"10.1016/j.jengtecman.2025.101917","DOIUrl":"10.1016/j.jengtecman.2025.101917","url":null,"abstract":"<div><div>Craftsmen traditionally relied on proximity markets and localized territories to conduct their business without heavy investments in digital solutions. However, the Covid-19 pandemic necessitated the adoption of digital solutions to access markets also giving unexpected opportunities like, for example, international exposure. Such investments required a complete change in the craftsmen's business strategies and persisted in the post-pandemic period requesting continuous and new investments. In this study, we employ Structural Equation Modeling on a sample of 762 Italian craftsmen to investigate how the post-Covid business strategies influence the investments in both digital marketing and digital technologies and their subsequent impact on performance. Furthermore, this study seeks to explore the advantages that craftsmen derive from subscribing to post-Covid commercial and digital-based contracts with strategic partners that joined the business model due to the pandemic. By doing so, we demonstrate the profound influence of these contract types on firms' business strategies and digital-related adoption paths and contribute to a better understanding of the factors driving technology adoption in craftsmen industry.</div></div>","PeriodicalId":50209,"journal":{"name":"Journal of Engineering and Technology Management","volume":"78 ","pages":"Article 101917"},"PeriodicalIF":3.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221732","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}

{"title":"External corporate venturing for strategic renewal: A comparative study of corporate venture capital and corporate venture clienting","authors":"Louisa Heiduk ,&nbsp;Philipp Frey ,&nbsp;Lysander Weiss ,&nbsp;Dominik K. Kanbach","doi":"10.1016/j.jengtecman.2025.101915","DOIUrl":"10.1016/j.jengtecman.2025.101915","url":null,"abstract":"<div><div>Within the domain of corporate entrepreneurship, external corporate venturing (CV) offers firms different avenues for strategic renewal, yet research comparing its different modes remains limited. This study examines two external CV approaches—Corporate Venture Capital (CVC) and Venture Clienting (VCL)—to investigate how they differentially and complementarily facilitate strategic renewal. The study applies a flexible pattern-matching approach to abductively compare empirical insights from 99 semi-structured interviews with CV managers to existing theory on strategic corporate venturing. The findings show that CVC often primarily functions as an exploratory external CV mode oriented toward future growth, characterized by strong strategic and external linkages, proactive sensing, and investment-led innovation processes. In contrast, VCL tends to serve as an exploitative external CV mode focused on near-term operational enhancement through tight business-unit integration, structured piloting, and implementation activities. While both modes support certain aspects of strategic renewal, the findings suggest that orchestrated jointly, CVC and VCL have the potential to facilitate distributed ambidexterity, enabling companies to balance exploration and exploitation across time horizons to renew current and future competitive advantages. The study contributes to the literature by empirically conceptualizing complementary configurations of CVC and VCL for a distributed architecture for strategic renewal and by advancing the configurational view of external CV through a formalized configuration space that links structural features to heterogeneous ambidextrous behaviours.</div></div>","PeriodicalId":50209,"journal":{"name":"Journal of Engineering and Technology Management","volume":"78 ","pages":"Article 101915"},"PeriodicalIF":3.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145333290","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}