ABSTRACT Prevailing Knowledge Management (KM) models offer limited support for detecting Critical Knowledge erosion before it compromises strategic resilience. This study proposes the Hydrological Model of Knowledge Dynamics for Science, Technology, and Innovation (ST&I) , a systemic artifact that represents knowledge flows, stocks, losses, and governance controls in ST&I environments. Based on literature review, bibliometric analysis, and field observation in the Brazilian Aerospace and Defense sector, the model formalizes a functional isomorphism between hydrological and Dynamic Knowledge Management (DKM) processes. The propositions, framed as hypotheses for future empirical validation, explain how organizational amnesia may emerge from attrition‐driven drainage, obsolescence‐related evaporation, crisis‐driven outflow, and monitoring failures. The article also distinguishes Essential Knowledge from Critical Knowledge as knowledge‐stock categories requiring different governance logics. Rather than claiming empirically validated effects, the study provides a structured conceptual lens for examining knowledge vulnerability and supporting diagnostic routines in volatile, high‐complexity sectors.
ABSTRACT As artificial intelligence (AI) increasingly transforms organizational and creative workflows, sustaining human expertise has become a critical challenge for organizations seeking to balance automation with long‐term capability development. To prevent cognitive deskilling and support knowledge retention, organizations must understand how professionals develop, transfer, and maintain AI‐related competencies over time. Drawing on Social Cognitive Theory (SCT), this study examines the relationship between AI literacy and sustainable skill transferability, with technical self‐efficacy mediating and AI autonomy moderating. Data were collected from 260 professional designers using a three‐wave, time‐lagged research design and analyzed through SmartPLS‐SEM (version 4). The findings indicate that AI literacy positively influences technical self‐efficacy, which in turn enhances the sustainable transferability of skills across evolving technological contexts. However, the results also reveal that higher levels of AI autonomy weaken the positive relationship between AI literacy and technical self‐efficacy. This suggests that while autonomous AI systems may improve operational efficiency, they may simultaneously reduce opportunities for mastery experiences that support the development of confidence and long‐term capability retention. By extending SCT to AI‐enabled design environments, this study contributes to emerging debates on human–AI collaboration and offers practical guidance for designing co‐creative workflows that promote sustainable capability development rather than mere task automation.
ABSTRACT Organisations are ceding visibility over how their employees develop knowledge. As generative AI tools become widely accessible, workers are steadily building capabilities and co‐producing knowledge through informal AI engagements that operate entirely outside sanctioned training systems. This paper theorises shadow learning, the informal and autonomous appropriation of AI by workers for knowledge expansion beyond managerial design, as a process that fundamentally reconfigures how knowledge authority is distributed in organisations. Integrating critical management learning with sociomaterial and post‐human perspectives, and drawing on current debates in AI ethics and human–AI interaction, the paper conceptualises shadow learning through a recursive model of constraint, appropriation and reconfiguration. This framework shows how AI functions as a sociomaterial catalyst that alters who holds knowledge authority and how learning unfolds in practice. The paper makes three contributions. It introduces shadow learning as a concept that extends beyond informal learning by foregrounding its subversive and sociomaterial dimensions; it bridges critical and sociomaterial perspectives to show how AI‐mediated learning works at once as political resistance and distributed practice and it draws both traditions into contact with current debates in AI ethics. The contribution lies in that integration and its application to a phenomenon neither tradition has theorised alone, not in restating a post‐human case sociomaterial scholarship has already made. The model offers knowledge management scholars and practitioners a conceptual tool for understanding why informal AI‐mediated knowledge practices are not deviations from organisational learning systems but constitutive features of them.
This study aims to identify which cluster formation factors influence the diffusion and adoption of eco-innovations and how these processes have been addressed in literature. Through a literature review and bibliometric analysis of 128 studies, we identify key factors associated with clusters that affect the uptake of eco-innovations in production processes. Recurring elements include cluster capacity, governance and coordination structures, regional and organizational culture, level of cooperation, competitive pressure, policies and regulation, demand dynamics, economic and environmental outcomes, access to new markets, and cluster development. The results indicate that literature remains theoretically fragmented, although several conceptual perspectives emphasize the role of relational, institutional, and territorial factors in shaping eco-innovation processes. The study proposes an integrative conceptual framework that synthesizes the main cluster-related factors identified in literature. Our findings contribute to the systematization of theoretical perspectives and cluster formation factors, offering insights for scholars and policymakers aiming to foster sustainable innovation in clusters.
In increasingly competitive and knowledge-intensive supply chains (SCs), effective knowledge management (KM) practices are essential for enhancing organizational learning, collaboration, innovation, and operational performance across both intra-firm and inter-firm contexts. Although prior studies have acknowledged the strategic importance of KM in SCs, the literature remains fragmented, with limited empirical evidence regarding the specific KM practices adopted by firms, their degree of diffusion, and the intensity with which they are used across organizational boundaries. This study addresses these gaps by investigating the adoption and intensity of use of 38 KM practices among European manufacturing firms operating in complex industrial environments. Drawing on survey data collected through a structured questionnaire, the study examines KM practices across three categories: KM methods, KM applications of IT, and KM-enabling management actions, comparing their use within firms and in relationships with suppliers and customers. The findings reveal substantial heterogeneity in both the degree of spread and intensity of use of KM practices. Firms rely more intensively on operationally familiar practices, such as lessons learned, brainstorming, and database systems, while more specialized KM-oriented practices, including AI systems, demonstrate comparatively lower adoption and usage levels. The results further indicate that the intensity of use of KM practices is consistently lower in inter-firm relationships than within firms. However, strong positive correlations between intra-firm and inter-firm KM usage suggest that internal KM capability development supports the extension of KM practices toward collaborative SC relationships. These findings contribute to the KM and process management literature by providing a comprehensive empirical assessment of KM practices across intra- and inter-firm contexts and by offering practical insights for managers seeking to strengthen collaborative KM initiatives and supply chain learning capabilities.
This article examines how organisational attributes shape two complementary organisational capabilities-process risk management and employee knowledge sharing-and how these capabilities contribute to organisational resilience. Drawing on organisational capability and human capital perspectives, the study adopts an integrated multi-method research design comprising two empirical components conducted in the Czech Republic. The first component investigates the organisational determinants of process risk management capability using interview and survey data collected from manufacturing firms. The second component examines the drivers of employee knowledge sharing based on a dataset of 480 employee questionnaires across organisations. The findings indicate that organisational attributes influence the development of both capabilities through distinct but interrelated mechanisms. While process risk management capability is associated with formal management systems, process orientation and specialised organisational roles, knowledge sharing is primarily driven by employee characteristics, motivation, leadership and the use of knowledge-sharing tools. Firm size emerges as a common determinant across both domains, whereas ownership structure demonstrates only limited influence. The results further suggest that organisational resilience is strengthened through the combined development of mature risk management processes and effective knowledge-sharing practices. By integrating structural and human capital perspectives within a single framework, this study contributes to the literature on organisational resilience by providing a more comprehensive understanding of resilience as an outcome of interacting organisational capabilities.
The study explores how the Human-AI Symbiotic Culture (HASC) affects the organizational performance (OP) in family businesses in the new era of the Family Business 4.0. Against the backdrop of the rapid digital transformation and growing dependence on artificial intelligence, Human-AI symbiosis, which is the collaborative combination of human intelligence and AI functionality, has become the key driver of innovation, flexibility, and competitive advantage. Based on the Socioemotional Wealth (SEW) theory and Dynamic Capability Theory (DCT), this paper places AI not as a technological instrument but as a cultural aspect that is integrated into the family firms, reconstructing the value creation process. The study hypothesizes a conceptual model with the help of information about 628 employees and managers who work in small and medium-sized family firms in Pakistan. One of the hypotheses is the positive impact of HASC on OP and AI Co-Creation Capability (AICC). Moreover, the paper explores the mediating impact of AICC and the moderating impact of the Family-Centric Value Imprinting (FCVI) that indicates the impact of family values, traditions and legacy orientations, which are deeply embedded in the organizational practices. Findings affirm that HASC has a positive influence on OP and AICC, and AICC partially mediates this association. Besides, FCVI enhances the power of AICC on performance outcomes. The results highlight the significance of human-AI collaboration and the development of a symbiotic organizational culture in order to promote OP in the family businesses setting. The practical implications of the study to the management of family firms are focusing on AI-enhanced collaborative functions and aligning technological efforts with family values. Future studies can be based on longitudinal designs and apply the model to other institutional and cultural contexts.
This study examines the critical success factors (CSFs) that facilitate Knowledge Management Implementation (KMI) and their influence on Knowledge Worker Productivity (KWP) within regulatory bodies in Pakistan. Drawing on the knowledge-based theory of the firm, the study investigates three most CSF, the Knowledge-Centered Culture (KCC), Information Technology Capability (ITC) and Environmental Dynamics (ED), to check that how these CSF support the KMI and enhance KWP. Primary data were collected from employees working in regulatory authorities in Pakistan. A total of 307 responses were analyzed using Structural Equation Modeling through SmartPLS. The findings indicate that KCC, ITC, and ED significantly and positively influence KMI, while KMI significantly improves KWP. Mediation analysis further confirms that KMI partially mediates the relationships between these CSF and KWP. The study provides guidance for policymakers and managers seeking to strengthen knowledge management systems and enhance workers' productivity in regulatory organizations.
Drawing on the Diffusion of Innovations Theory, the study explored the knowledge flows, the interorganizational network created by those flows, and the factors impacting the diffusion and adoption of the HACCP system as a novel organizational practice among food processing organizations in Armenia. A multi-site, cross-sectional qualitative study was conducted with the food safety professionals from food processing organizations, governmental authorities, and consulting non-governmental companies. The study utilized a qualitative directed content analysis along with network analysis approaches. Three main types of clusters formed the core of the interorganizational network, which had more relations with other actors and greater access to diversified sources of knowledge on the HACCP system. In contrast to entities appearing in the periphery of the network, these clusters had external knowledge connections facilitating the transfer of more novel and diversified knowledge on the HACCP system adoption and keeping the interorganizational network open to more specialized and complex knowledge. Factors impacting effective knowledge sharing in the network and subsequently the diffusion and adoption process were identified and summarized in the conclusion. Interpersonal knowledge transfer appeared considerably predominant among most adopters for raising their awareness of and building knowledge on the HACCP system adoption. The study provides important insights into how policymakers can better engage with the needs of food processing organizations and support the development of a more favorable environment with the consideration of the catalogue of barriers and facilitators for the diffusion and adoption of the HACCP system at the level of the interorganizational network.
ABSTRACT The enormous scientific and technological progress of the early 21st century has a strong impact on all fields of activity. And as everyone knows, knowledge is the engine of progress, especially in the realities of a knowledge‐based economy. The expansion of cooperation between enterprises during the product lifecycle is an urgent trend in the global market. As a result, various forms of inter‐company cooperation of business entities are becoming important. Collaborative network is one of the most effective. This network is being created as a temporary alliance to meet the rapidly changing market window of opportunity. Therefore, the goal of this paper is to present a collaborative network as a driver for knowledge creation. In consequence, first we define the importance of the problem, then provide a literature review and finally show the results of the implementation of an industrial knowledge creation network between two industrial companies, namely PJSC Severstal and KAMAZ Group, Nissan and JAXA, Fiat and Google, First Moscow State Medical University and Beeline Big Data and AI. The results show that confirming theory confirms the intuition that collaborative networks are important for knowledge creation and our case study illustrates that reality very strongly—more specifically, the continuous growth of the knowledge base is the most important result of the collaborative network's action. This study is of value for researchers in the field of industrial economics and industrial practitioners.
Knowledge hiding has become a growing concern in academic settings, where knowledge exchange is central to learning, research, and scholarly development. Drawing on Conservation of Resources (COR) Theory and Social Cognitive Theory (SCT), this study examines the effect of perceived competition, knowledge complexity, and knowledge territoriality on knowledge hiding, as well as the moderating role of self-efficacy. This study employed a quantitative method using a self-administered survey, collecting 673 valid responses from graduate students in Indonesia. PLS-SEM was utilized for data analysis. The results revealed that competition, knowledge complexity, and knowledge territoriality positively affect knowledge hiding, while self-efficacy weakens these effects. Additional analyses further show that the moderating role of self-efficacy varies across demographic groups. Specifically, self-efficacy weakens the positive effect of knowledge complexity on knowledge hiding among female and older students, weakens the effects of competition and knowledge territoriality among younger students, and weakens the effect of competition among doctoral students. By integrating COR theory and SCT, this study extends knowledge hiding research by explaining both why graduate students may hide knowledge under conditions of perceived resource threat and when this tendency is less likely to occur. The findings also offer practical insights for higher education institutions seeking to reduce knowledge hiding by strengthening students' self-efficacy and creating more supportive academic environments.
Knowledge management (KM) is increasingly recognised as a strategic asset that enhances learning, performance and resilience. Yet assessing its value beyond immediate outcomes is challenging, especially in humanitarian operations where knowledge is often tacit, relational and embedded in ad hoc practices and inter-agency networks. This paper applies the General KM Maturity Model (G-KMMM) to a humanitarian organisation to explore how formative assessment can identify implementation gaps and evaluate KM maturity. Findings reveal challenges including fragmented structures, limited process standardisation, insufficient integration of internal and external knowledge, and reliance on personal networks. While these results align with KM literature emphasising trust, incentives and system integration, they also highlight the limitations of conventional maturity models in capturing informal learning and relational knowledge flows. The study proposes context-sensitive adaptations of KM assessment frameworks to improve learning, coordination and knowledge use under operational constraints in humanitarian settings.
This paper advances the circular economy (CE) strategy by conceptualising epistemic misalignment as a structural constraint on circular performance in emerging economies. Although CE governance increasingly relies on globally codified metrics and ESG reporting tools, such instruments often fail to capture locally embedded recovery infrastructures in contexts characterised by institutional heterogeneity. Using Nigeria's plastics recovery landscape as an analytical lens, the study introduces the construct of knowledge asymmetry to explain how distorted knowledge integration generates strategic blind spots, operational inefficiencies and legitimacy risks. Integrating decolonial political economy with the Knowledge-Based View and dynamic capabilities theory, the paper reconceptualises informal sector integration (ISI) as a dynamic capability that enhances circular performance and mitigates the adverse effects of knowledge asymmetry. The framework further specifies ethical governance and institutional integrity as boundary conditions shaping integration outcomes. By reframing CE transitions as knowledge governance challenges, the study contributes a decolonised strategic perspective on sustainability transitions in Global South supply chains.
This systematic literature review examines the evolution and contemporary relevance of the SECI model in knowledge management. A hybrid methodology, combining bibliometric analysis with the TCCM (Theories, Contexts, Characteristics, Methods) framework, was used to provide a comprehensive overview of the research domain. The study addresses four key questions: the evolution of research in terms of publication structure and key contributors, theoretical extensions and integration with complementary frameworks, contextual applications and influencing factors, and emerging methodological trends. Findings reveal that while the SECI model has adapted to digitalization and globalization, research remains fragmented with limited integration into strategic theories. The review identifies significant gaps in contexts, such as the public sector, and a reliance on qualitative methods. An integrative agenda is proposed to guide future research, focusing on cross-disciplinary studies, advanced methodologies, and new contexts like AI-enabled environments, offering an intellectual roadmap for scholars and practitioners.
This research investigates how knowledge sharing and digital innovation affect the value creation of Science and Technology-based Small and Medium Enterprises (ST-SMEs) in China. Using text mining and panel data from the ChiNext board (2011-2019), we construct a provincial-level Knowledge Sharing Development Index and employ mediation models to analyze its mechanisms. The results demonstrate that knowledge sharing enhances value creation not only directly but also indirectly through digital innovation, with significantly stronger effects observed in eastern regions. This study bridges the gap in understanding how digital innovation mediates the relationship between knowledge sharing and value creation in ST-SMEs, offering region-specific policy implications. We propose targeted strategies to address knowledge leakage risks, optimize digital infrastructure, and foster cross-regional knowledge ecosystems, thereby advancing both theoretical frameworks and practical governance for ST-SMEs in emerging economies.JEL Classification: O33, L25, M15, R11
This research fills a gap in previous studies by exploring how job satisfaction mediates the connection between the efficacy of empowerment practices and employee agility. A comprehensive dataset was amassed through the distribution of 460 questionnaires to employees within commercial banks. Utilizing structural equation modeling, the data underwent rigorous statistical analysis to scrutinize the proposed hypotheses. This research significantly contributes to the existing literature by elucidating the pivotal role played by job satisfaction in shaping the intricate dynamics between empowerment practices and employee agility. The findings underscore the substantial mediating effect of job satisfaction in this relationship. Consequently, the study imparts practical policy recommendations for commercial banks, emphasizing enhancements in decision-making processes, communication strategies, delegation of authority, team dynamics, and job satisfaction to foster employee agility and attain a competitive edge. In conclusion, addressing this research gap enhances comprehension of these interconnections, ultimately leading to heightened organizational efficacy.
This study aims to investigate the effects of human-AI collaboration signalling (HACS) in the organisational communication in the motivation of knowledge workers (KWM). In particular, the research question is whether the perceived augmentation benefits (PAB) and technological self-efficacy (TSE) mediate this relationship and whether the relationship strengths differ according to the task complexity (TC) (routine vs. complex tasks). The research uses the signalling theory (ST) and social cognitive theory (SCT) to form the research model. An experimental design based on controlled scenarios was used, where the participants rated the communication within an organization when describing the work environments that are aided by AI. The participants were asked to rate the impact of AI collaboration signals on their perceptions and motivation to be employed by AI systems. The findings suggest that the HACS is positively related to KWM indirectly through PAB and TSE. In addition, the results indicate that the moderator of these relationships is TC. The indirect effects are substantially more pronounced in the complex, cognitively demanding tasks, in which AI is viewed as a power tool that promotes productivity and ability to solve problems. Conversely, the impacts are less in daily work, in which AI could be seen as a potential competitor, not a work partner.
This study sought to explore the possible reasons why salespeople hide knowledge from customers in a business-to-consumer context (B2C). Based on the existing literature on knowledge hiding at the individual, organizational, and sales levels, an exploratory methodology with a qualitative approach was adopted. Interviews were conducted with 16 customers and 24 salespeople from different sectors. Based on the content analysis, a theoretical model was developed consisting of three categories that together explain the reasons for knowledge hiding by salespeople. Individual factors indicate that salespeople show intentional behavior, on a personal level, to hide knowledge requested by customers. At the organizational level, culture, leadership, and organizational climate can lead to knowledge hiding. Finally, in relational terms, knowledge hiding can occur in the interaction between salespeople and customers, a phenomenon that has not yet been identified in literature. The results provide input for improving sales practices and strategies, as well as enhancing value propositions for customers. Understanding the reasons behind knowledge hiding can contribute to better management and training of sales staff.
Drawing on the resource-based view, the current study examines the association between knowledge management practices and competitive advantage in Pakistan's PHEIs, with multiple mediators of innovation capabilities such as product development capability, innovativeness, strategic capability, and technological capability. A hypothetico-deductive research design with a time-lag approach was employed to collect data from 266 respondents at PHEIs in Pakistan, conducted in three phases with a one-month time interval. The development of underlying mechanisms comprising crucial multiple mediators in PHEIs in Pakistan leads to the attainment of CA. The study demonstrated that RBV can also be used in higher education settings to achieve competitive advantage (CA). The study further validates several underlying processes that contribute to the competitive advantage of Public Higher Education Institutions (PHEIs) in Pakistan.
This study aims to examine how collaboration between humans and intelligent systems facilitates the evolution of digital nudging from a short-term behavioral intervention into a catalyst for strategic foresight and knowledge strategy, specifically within the context of employees' decision-making in service organizations. Additionally, it seeks to identify the antecedents, outcomes, and conditions that influence this transformation. The research employs an integrated mixed methodological design, combining the fuzzy Delphi technique with structural modeling to validate construct dimensions, test causal relationships, and identify the mediating role of human and intelligent system collaboration, as well as the moderating role of organizational readiness for innovation. This is conducted across a sample of 3176 respondents from knowledge-intensive service sectors. The results indicate that digital nudging impacts strategic foresight only when mediated through effective collaboration between humans and intelligent systems. This collaboration significantly enhances knowledge creation, sharing, integration, and strategic application. Furthermore, the findings suggest that digital literacy, trust in intelligent systems, data quality, and innovation readiness are critical antecedents of collaboration, while anticipatory decision-making and collective sensemaking improve with the presence of trust, transparency, and psychological comfort. The study fully supports all proposed hypotheses and demonstrates that collaborative foresight nudges form an integrated pathway connecting behavioral influence with future-oriented knowledge strategy. The study offers managers a comprehensive model for embedding anticipatory intelligence into daily work processes, enabling organizations to reduce cognitive overload, enhance decision accuracy, stimulate proactive innovation, and strengthen long-term resilience. The results illustrate how organizations can design transparent, ethically governed, and psychologically supportive intelligent systems that enhance employee engagement and accelerate knowledge-driven transformation. This study presents a novel theoretical integration linking nudging theory, strategic foresight theory, and the knowledge-based view through the mechanism of human and intelligent system collaboration. It introduces the concept of collaborative foresight nudges as a new explanatory construct, advancing the understanding of how micro-level digital cues translate into macro-level strategic knowledge outcomes. The study provides a validated socio-technical framework that redefines the role of intelligent systems in shaping the future of organizational decision-making.
