Journal of Knowledge Management最新文献

{"title":"From GenAI-enabled knowledge creation to SME digital transformation: the mediating role of entrepreneurial innovativeness","authors":"Haoyu Cao,Hyoungsuk Lee,Vikram Kumar Sharma,Jehan Saleh Lardhi,Omar Abdeljaber","doi":"10.1108/jkm-06-2026-1177","DOIUrl":"https://doi.org/10.1108/jkm-06-2026-1177","url":null,"abstract":"Purpose This study aims to examine how generative artificial intelligence (GenAI)-enabled knowledge creation processes influence entrepreneurial knowledge co-creation and small and medium-sized enterprise (SME) digital transformation through entrepreneurial general innovativeness and entrepreneurial specific innovativeness. Design/methodology/approach Drawing on the socialization, externalization, combination and internalization (SECI) knowledge creation framework, the study develops and tests a mediation model linking GenAI internalization (GAI), GenAI externalization (GAE), GenAI socialization (GAS) and GenAI combination (GAC) with SME outcomes. Data was collected from 391 SME respondents and analysed using covariance-based structural equation modelling in analysis of moment structures. Findings The findings show that GAI, GAE and GAC significantly enhance both entrepreneurial general innovativeness and entrepreneurial specific innovativeness. GAS significantly influences entrepreneurial specific innovativeness but does not significantly affect entrepreneurial general innovativeness. Both forms of entrepreneurial innovativeness positively influence entrepreneurial knowledge co-creation and SME digital transformation. Mediation results further show that entrepreneurial general innovativeness mediates the effects of GAI, GAE and GAC, while entrepreneurial specific innovativeness provides a more consistent mediating pathway across GenAI-enabled knowledge processes. Practical implications SME managers should use GenAI not merely for automation or content generation, but for learning, knowledge articulation, knowledge integration, innovation adoption and digital transformation. Originality/value The study advances GenAI entrepreneurship research by showing how GenAI-enabled SECI processes create SME value through entrepreneurial innovativeness.","PeriodicalId":48368,"journal":{"name":"Journal of Knowledge Management","volume":"64 1","pages":"1-21"},"PeriodicalIF":7.0,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149092741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Green knowledge transaction networks, knowledge absorptive capacity and breakthrough green innovation","authors":"Hao Li,Yi Yu,Shoujian Jiang,Yiming Cao","doi":"10.1108/jkm-05-2026-0891","DOIUrl":"https://doi.org/10.1108/jkm-05-2026-0891","url":null,"abstract":"Purpose Drawing on the knowledge-based view, structural holes theory and absorptive capacity theory, this study aims to examine how firms’ structural advantages in green knowledge transaction networks affect breakthrough green innovation. It further investigates the mechanisms through which knowledge retrieval ability, knowledge integration ability, and knowledge absorptive capacity shape this relationship. Design/methodology/approach This study measures the structural advantage of the green knowledge transaction network by the structural hole index and measures breakthrough green innovation by highly cited green invention patents within the same technology field. Findings The results show that structural advantages in green knowledge transaction networks are positively associated with breakthrough green innovation. This effect persists over time but gradually weakens. Mechanism tests indicate that knowledge retrieval ability and knowledge integration ability are important channels through which network structural advantages are transformed into breakthrough green innovation. The moderation results show that knowledge absorptive capacity strengthens the positive effect of green knowledge transaction network structural advantages on breakthrough green innovation. Further analysis shows that this effect is more pronounced in state-owned enterprises and firms in low-technology industries, while there is little difference in the effect between polluting and clean industries. Originality/value This study introduces green knowledge transaction networks into knowledge management research and incorporates knowledge retrieval ability, knowledge integration ability, and knowledge absorptive capacity into a unified analytical framework. It reveals the conversion logic through which green knowledge transaction networks affect breakthrough green innovation.","PeriodicalId":48368,"journal":{"name":"Journal of Knowledge Management","volume":"62 1","pages":"1-20"},"PeriodicalIF":7.0,"publicationDate":"2026-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149123777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI knowledge capability and innovation: the power of cognitive processing and empowerment","authors":"Dengkai Wu,Canghong Wang,Abdul Hameed Pitafi,Jehan Saleh Lardhi,Oumaima Haj Ammar","doi":"10.1108/jkm-04-2026-0780","DOIUrl":"https://doi.org/10.1108/jkm-04-2026-0780","url":null,"abstract":"Purpose This study aims to integrate ideas from organizational learning theory with new AI capabilities to investigate how AI-driven knowledge processes may improve innovation performance. Specifically, this study explores the process in which AI-based (AI Ba) knowledge production and integration support advancement of AI knowledge capability and AI psychological empowerment. In addition, this study also investigates the moderating role of Gen-AI cognitive. Design/methodology/approach Data were collected from 301 professionals in the USA working in AI-enabled organizational settings, and structural equation modeling was used for data analysis. Findings The results of this study show that both AI knowledge production Ba and AI knowledge integration Ba is positively associated with AI knowledge capability and AI psychological empowerment. AI knowledge capability is also positively related to AI innovation performance. Similarly, AI psychological empowerment is also significantly related to AI innovation performance. Furthermore, the findings of this study show that Gen-AI cognitive processing positively moderates the association between AI knowledge capability and AI innovation performance, while Gen-AI cognitive processing did not moderate the relationship between AI psychological empowerment and AI innovation performance. Originality/value Overall, this study contributes to the literature by providing an extensive framework for linking AI-enabled knowledge processes to psychological and performance consequences. This study also has practical implications for organizations attempting to use AI capabilities to drive creativity, highlighting the relevance of cognitive and psychological factors in AI adoption.","PeriodicalId":48368,"journal":{"name":"Journal of Knowledge Management","volume":"7 1","pages":"1-22"},"PeriodicalIF":7.0,"publicationDate":"2026-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149123778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unlocking the value of generative AI for supply chain resilience and crisis readiness: a complex adaptive systems perspective","authors":"Lojain Alkhuzaim,Siraj Hussain,Rsha Alghafes,Tahmid Nayeem","doi":"10.1108/jkm-04-2026-0814","DOIUrl":"https://doi.org/10.1108/jkm-04-2026-0814","url":null,"abstract":"Purpose The existing literature conceptualizes generative artificial intelligence (GenAI) as a knowledge infrastructure that facilitates organizational abilities to use changes. However, there is a dearth of studies to illustrate the core reasons why GenAI-enabled knowledge mechanisms thrive with unequal variations across various spheres of organizations. The purpose of the current research is to draw on complex adaptive systems (CAS) theory and investigate how GenAI-enabled information quality and GenAI governance maturity are associated with supply chain resilience and crisis readiness through two distinct knowledge-sharing mechanisms: GenAI-enabled tacit and explicit knowledge sharing. Design/methodology/approach The authors develop a CAS-informed model that distinguishes between GenAI-enabled tacit and explicit knowledge sharing as complementary pathways linking GenAI-derived value to adaptive outcomes. The model is tested using survey data from 192 full-time employees in organizations adopting GenAI. Confirmatory factor analysis and structural equation modelling are conducted in SPSS AMOS. Findings GenAI-enabled information quality positively influences both GenAI-enabled tacit and explicit knowledge sharing. GenAI governance maturity also positively influences both forms of knowledge sharing. GenAI-enabled explicit knowledge sharing yields considerable advancement in supply chain resilience and crisis readiness. GenAI-enabled tacit knowledge sharing enhances supply chain resilience smoothly, but its association with crisis readiness does not appear significant. Research limitations/implications The limitation lies in the cross-sectional, perceptual design, as it limits causal inference and fails to capture the temporal evaluation highlighted by the CAS framework. It implies that future studies use longitudinal or event-based research designs and objective indicators (e.g. documentation traces, usage logs) to examine how GenAI-enabled knowledge dissemination advances across disruption layers. Practical implications It is imperative to support supply chain resilience and preparedness. Institutions should invest in GenAI governance maturity and information quality (timeliness, accuracy and interpretability); propel GenAI governance maturity by structured policies, regulation and incremental optimization; and intentionally frame processes that strengthen both tacit sensemaking and explicit artefacts. Originality/value This study reframes GenAI as an adaptive infrastructure within CAS and demonstrates that GenAI value materializes through distinct tacit vs explicit knowledge-sharing pathways, clarifying why GenAI investments yield uneven outcomes, especially for supply chain resilience under disruption.","PeriodicalId":48368,"journal":{"name":"Journal of Knowledge Management","volume":"35 1","pages":"1-21"},"PeriodicalIF":7.0,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149123779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From personalized gamification to knowledge outcomes: the role of digital literacy, information quality and online flow experience","authors":"Weilan Xu,Vaishali Agarwal,Hanoof Bandar Alkasham,Irma Potháczky Rácz,Marwan Al-Smeiat","doi":"10.1108/jkm-05-2026-0903","DOIUrl":"https://doi.org/10.1108/jkm-05-2026-0903","url":null,"abstract":"Purpose This study aims to examine how personalized gamification (PG) and digital literacy (DL) shape perceived information quality (PIQ), online flow experience (OFE) and knowledge management outcomes in social media environments. Design/methodology/approach Drawing on knowledge management theory, the study proposes a model linking PG and DL with PIQ, OFE, knowledge creation (KC) and knowledge storage (KS). Explicit knowledge application (EKA) is examined as a moderator of the OFE–KS relationship. Data were collected from 293 demographically balanced social media users in the United States through Prolific and analyzed using partial least squares structural equation modeling. Findings PG and DL positively influence PIQ, which subsequently strengthens OFE. OFE is positively associated with both KC and KS. The serial indirect effects of PG and DL on KC and KS through PIQ and OFE are also supported. However, EKA does not significantly moderate the relationship between OFE and KS. Research limitations/implications The findings show how platform personalization and users’ digital capabilities jointly shape information evaluation, immersive engagement and knowledge outcomes. They also place PIQ and OFE at the center of the process through which social media interactions contribute to knowledge creation and storage. Originality/value The study brings PG, DL, information quality and OFE into a single knowledge management model. It clarifies how platform-related and user-related factors work together in digital knowledge processes and shows that EKA does not alter the effect of OFE on knowledge storage.","PeriodicalId":48368,"journal":{"name":"Journal of Knowledge Management","volume":"42 1","pages":"1-23"},"PeriodicalIF":7.0,"publicationDate":"2026-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149123840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-driven organisational cognitive transformation: knowledge management strategies for hybrid cognition","authors":"Giovanni Schiuma","doi":"10.1108/jkm-02-2026-0425","DOIUrl":"https://doi.org/10.1108/jkm-02-2026-0425","url":null,"abstract":"Purpose This paper aims to position artificial intelligence (AI) as a knowledge-based cognitive technology that drives organisational cognitive transformation (OCT). This paper addresses three gaps in knowledge management (KM) theory. First, there is a need to further clarify the conceptualisation of AI’s cognitive role within a tradition that has attributed cognitive agency essentially to people, even as AI’s growing role requires such clarity. Second, treating AI as a generic technological capability is limiting; it requires distinguishing among different forms of human–AI cognitive integration and their differential effects on organisational hybrid cognition. Third, AI governance in relation to organisational decision-making and value creation is underdeveloped. Design/methodology/approach This paper adopts an integrative conceptual approach to theory building. The OCT construct is elucidated through a systematic literature review of 101 papers, spanning from Cyert and March (1963) to recent AI–cognition scholarship. This is complemented by a purposive, theory-driven review of the AI–KM literature, which identifies the mechanisms linking AI capabilities to organisational cognitive functions. Findings Organisational cognition is disaggregated into six interdependent dimensions that constitute an organisation’s cognitive architecture: interpretative framing, attentional allocation, distributed coordination of socio-material cognition, knowledge creation and learning, organisational memory and unlearning and epistemic authority and validation. A working definition of OCT is provided as the consequential reconfiguration of an organisational cognitive architecture, distinguished from digital transformation, organisational learning and socio-technical change. A functional, rather than ontological, conception of AI agency is discussed, acknowledging that AI produces artificial knowledge and accelerates the combination phase of knowledge conversion, while socialisation, internalisation and externalisation, together with epistemic authority over meaning and ethical accountability, remain human. Five AI-based KM strategies, for example, knowledge discovery and sensemaking, generative knowledge creation and co-production, reflexive learning, autonomous knowledge orchestration and co-evolutionary ecosystem intelligence, are proposed, and their impact on core KM processes and OCT dimensions is examined, recognising their complementary, contingent and cumulative nature within a path-dependent model of architectural reconfiguration. Research limitations/implications As a conceptual contribution, the framework requires empirical validation. Four propositions address adaptive sensemaking capacity, the moderating role of governance quality, the conditions under which generative knowledge artefacts strengthen dynamic capabilities and the risk of epistemic authority displacement. The six dimensions provide a basis for operationalising OCT and the impact of AI as ","PeriodicalId":48368,"journal":{"name":"Journal of Knowledge Management","volume":"23 1","pages":"1-20"},"PeriodicalIF":7.0,"publicationDate":"2026-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149123781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perceived coworker AI knowledge and AI-knowledge withholding: role of job insecurity and organizational AI readiness","authors":"Donglu Shan,Kaichen Zhao,Yu Yan,Shuaiping Xiao","doi":"10.1108/jkm-12-2024-1430","DOIUrl":"https://doi.org/10.1108/jkm-12-2024-1430","url":null,"abstract":"Purpose This study aims to examine how employees’ perceptions of their coworkers’ artificial intelligence (AI) knowledge influence their own tendency to withhold AI-related knowledge and explore the mediating and moderating mechanisms that explain this process. Design/methodology/approach Data were collected from 236 employees across three time points. Hypotheses were tested using regression analysis and bootstrapping methods. Findings Drawing on interdependence theory, we reveal that employees who perceive their coworkers as more proficient in AI experience heightened job insecurity, which drives AI-knowledge withholding. Organizational AI readiness moderates the indirect effect of perceived coworker AI knowledge on AI-knowledge withholding via job insecurity. Originality/value This study enhances understanding of knowledge withholding during AI transitions and offers actionable insights for organizations to minimize counterproductive knowledge behaviors.","PeriodicalId":48368,"journal":{"name":"Journal of Knowledge Management","volume":"12 1","pages":"1-21"},"PeriodicalIF":7.0,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149124127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Orchestrating and deploying knowledge for supply chain resilience: the roles of AI-enabled augmentation, immersive integration and knowledge reconfiguration advantage","authors":"Yue Xu,Khalid Mehmood,Di Wu,Ajay Kumar Patel,Norah Albishri","doi":"10.1108/jkm-01-2026-0141","DOIUrl":"https://doi.org/10.1108/jkm-01-2026-0141","url":null,"abstract":"Purpose In increasingly data-intensive and disruption-prone supply chains, firms must move beyond traditional knowledge practices by leveraging AI-enabled augmentation and immersive integration capabilities to enhance the depth, quality, and alignment of knowledge. However, the extent to which these capabilities translate into resilience depends on how effectively knowledge is orchestrated, deployed, and dynamically reconfigured in response to environmental volatility. Drawing on the knowledge-based view (KBV), this study aims to examine how AI-enabled knowledge augmentation capability (AKAC) and immersive knowledge integration capability (IKIC) influence knowledge-based supply chain resilience (KSCR). Specifically, the study investigates the roles of knowledge orchestration capability (KOC) and knowledge deployment capability (KDC) as key knowledge processes, as well as the moderating effect of knowledge reconfiguration advantage (KRA) in strengthening the relationship between knowledge deployment and resilience. Design/methodology/approach Data were collected from textile manufacturing SMEs using a three-wave time-lagged survey design. A structured questionnaire was administered to 303 firms, and Hayes’ PROCESS macro was employed to test the hypothesized relationships. Findings The results show that AKAC and IKIC significantly enhance KOC, which in turn positively influences KDC. KDC is further found to significantly improve KBSCR. In addition, KRA positively moderates the relationship between KDC and KSCR, such that the effect of knowledge deployment on resilience is stronger under higher levels of knowledge reconfiguration advantage. Originality/value This study contributes to the knowledge management literature by linking AI-enabled and immersive knowledge capabilities to supply chain resilience through key knowledge processes. By incorporating knowledge reconfiguration advantage as a boundary condition, the study extends the knowledge-based view and highlights the role of adaptive knowledge capabilities in enhancing the effectiveness of knowledge deployment in dynamic environments.","PeriodicalId":48368,"journal":{"name":"Journal of Knowledge Management","volume":"7 1","pages":"1-20"},"PeriodicalIF":7.0,"publicationDate":"2026-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149124313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Algorithmic and user-generated content for civic engagement: a knowledge management perspective on social media","authors":"Yilinna Bao,Jehan Saleh Lardhi,Vaishali Agarwal,Norah Muflih Alruwaili","doi":"10.1108/jkm-03-2026-0638","DOIUrl":"https://doi.org/10.1108/jkm-03-2026-0638","url":null,"abstract":"Purpose This study aims to examine how algorithmic agenda-setting and user-generated content influence are associated with political cognition and civic engagement in social media environments. Grounded in second-level agenda-setting theory and a knowledge management perspective, it develops and tests a framework linking algorithmic curation and participatory content with issue salience perception, framing persuasion strength, agenda fragmentation awareness and civic engagement intention. The study considers social media as an algorithmically mediated digital knowledge environment and examines how civic knowledge becomes visible, shared, prioritized, interpreted and translated into intended action. Design/methodology/approach The study adopts a quantitative research design using survey data collected from 295 social media users in the USA and the UK. Measurement items were adapted from established scales and assessed using a five-point Likert scale. The proposed conceptual model, comprising six constructs, was tested using partial least squares structural equation modeling (PLS-SEM) through SmartPLS 4. Reliability, validity and common method bias were assessed before testing the direct and serial indirect relationships. The analysis included both direct and serial mediation effects to evaluate the relationships among algorithmic agenda-setting, user-generated content influence, issue salience perception, framing persuasion strength, agenda fragmentation awareness and civic engagement intention. Findings The findings show that algorithmic agenda-setting and user-generated content influence are positively associated with issue salience perception, which is subsequently associated with framing persuasion strength. Framing persuasion strength is positively related to both agenda fragmentation awareness and civic engagement intention. Significant serial indirect effects were also found, indicating that the associations of algorithmic and user-driven content with civic outcomes occur through issue salience and framing. From a KM perspective, the results show how civic knowledge progresses from visibility and participatory sharing to prioritization, interpretation, fragmentation awareness and intended action. Research limitations/implications The study is limited by its focus on respondents from the USA and UK, restricting generalizability to other cultural and technological contexts. The use of cross-sectional and self-reported data limits causal inference and may introduce response biases. Additionally, key constructs were treated as unidimensional despite their conceptual complexity. Future research should adopt longitudinal or experimental designs, incorporate behavioral data, and explore moderating variables such as political orientation and digital literacy. Despite these limitations, the study contributes a process-based KM explanation of how algorithmic curation and user participation shape the visibility, prioritization, interpretation and use ","PeriodicalId":48368,"journal":{"name":"Journal of Knowledge Management","volume":"54 1","pages":"1-22"},"PeriodicalIF":7.0,"publicationDate":"2026-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149124315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harnessing the power of Gen Al innovations for knowledge asset creation in education: a strategic response to VUCA and sustainability","authors":"Changqing Li,Kanishka Pathak,Zhi Li,Shivani Agarwal,Norah Albishri","doi":"10.1108/jkm-01-2026-0198","DOIUrl":"https://doi.org/10.1108/jkm-01-2026-0198","url":null,"abstract":"Purpose Despite the rapid proliferation of Generative Artificial Intelligence (GenAI) across multiple domains, limited research has examined its role in knowledge creation and business intelligence within startup ecosystems. This study aims to address this gap by exploring how GenAI contributes to the development of novel knowledge assets that enable startups to navigate volatile, uncertain, complex and ambiguous (VUCA) environments. Design/methodology/approach An inductive research design was adopted using the Gioia methodology to analyze qualitative insights drawn from existing literature and emergent conceptual evidence. This approach facilitated theory building on the applicability of GenAI in knowledge creation and business intelligence for startups. Findings The findings reveal that GenAI functions as a transformative technological capability that enables startups to generate novel knowledge assets and strengthen business intelligence practices. Several key GenAI features were identified as critical enablers of knowledge creation, supporting business process management and enhancing organizational adaptability. The analysis highlights GenAI’s need to foster core competencies that improve startup resilience within VUCA contexts. Practical implications The study provides actionable insights for startup leaders on integrating GenAI into strategic narratives to enhance decision-making, operational intelligence and competitive positioning in hyper-competitive environments. Originality/value This research represents one of the early conceptual efforts linking GenAI to knowledge asset creation in startup ecosystems. It contributes to knowledge management and business intelligence literature by advancing a novel perspective on GenAI as a strategic enabler for startups operating under conditions of extreme uncertainty.","PeriodicalId":48368,"journal":{"name":"Journal of Knowledge Management","volume":"73 1","pages":"1-26"},"PeriodicalIF":7.0,"publicationDate":"2026-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148933943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}