This study discusses how knowledge management (KM) practices at the community level can help regenerate youth in farming communities as part of the farmers. The study is based on the KM model proposed by Probst (1998), which comprises the identification, acquisition, development, distribution, use and preservation of knowledge as interrelated processes that maintain intergenerational sustainability of the agricultural sector. By filling a major research gap, the study relates to the paucity of empirical research specifically examining farmer regeneration through a KM lens, the dearth of understanding how KM practices are lived differently by generations and the dearth of research on how Indonesian farming communities experience indigenous, formal and digital knowledge systems in sustaining agriculture across generations. These observations indicate that KM activities in the community, such as knowledge sharing through participation, intergenerational learning, mentoring, and leadership opportunities, are at the centre stage in influencing youth engagement and their motivation to join the agricultural sector. As much as structural barriers remain, such as a lack of access to land, failure to change perceptions about agricultural work, and dissimilar exposure to modern agricultural knowledge, farmer groups can entice and keep young farmers by promoting collaborative learning settings and utilising both traditional and new sources of knowledge. On the whole, this paper contributes to a clear understanding of the importance of a community-based approach to knowledge management around the area of youth unemployment in agriculture and provides conceptual and practical recommendations to policymakers, non-governmental organisations, and agricultural institutions to enhance farmer regeneration and intergenerational agricultural knowledge.
This study sought to advance our understanding of what affects knowledge adoption (a key process of knowledge sharing) in China by exploring the impact of two main affective determinants (ganqing and renqing) of Chinese interpersonal relationships on Chinese employees’ adoption of explicit and tacit knowledge contributed by their peers. Compared with two other main processes (contribution and seeking) of knowledge sharing and their determinants, knowledge adoption and its contributing factors have received much less attention in the extant literature on knowledge sharing in China. The effects of ganqing and renqing on explicit and tacit knowledge adoption were examined and tested with the data from a survey of 243 MBA students in China. The results from the hierarchical regression analyses showed that ganqing was positively related to explicit knowledge adoption and tacit knowledge adoption. Renqing was also found to be positively related to the adoption of both types of knowledge. While effective knowledge sharing relies on both the ‘supply of knowledge’ through knowledge contribution and the ‘demand of knowledge’ via knowledge adoption, prior research on knowledge sharing in China has placed more emphasis on the supply side of knowledge sharing and its determinants. By linking knowledge adoption to two affective factors, the findings from this study help address this imbalance in the knowledge sharing research related to China and increase our knowledge of what might have hindered the diffusion of knowledge management in China and how to better promote it. Other research and practical implications from the study are discussed.
Generative Artificial Intelligence (GenAI) is rapidly reshaping knowledge processes in higher education, yet its contribution to Sustainable Performance (SP) remains unclear. This study investigates how GenAI use affects the sustainable performance of higher education institutions (HEIs), where SP is conceptualised as a multidimensional outcome encompassing financial, environmental and social performance. Drawing on the Resource-Based View, the Knowledge-Based View and Stakeholder Theory, the study proposes that GenAI creates value indirectly through two organisational capabilities: Knowledge Management Capability (KMC) and Institutional Social Responsibility (ISR). Survey data were collected from 387 instructors in Kazakhstani colleges who actively use GenAI tools in their work, and analysed using partial least squares structural equation modelling with higher-order constructs. The results show that GenAI does not directly enhance SP, but is positively associated with KMC, which in turn has a strong positive effect on SP. ISR is also positively related to SP, yet GenAI has no significant direct effect on ISR. Mediation analysis reveals that KMC mediates the GenAI–SP relationship, and that GenAI contributes to SP through a significant serial pathway GenAI → KMC → ISR → SP, while ISR alone does not mediate the GenAI–SP link. The findings extend existing theory by demonstrating that GenAI acquires strategic value only when embedded in robust knowledge-management and responsibility structures. Practically, the study highlights the need for HEIs in transition economies such as Kazakhstan to move from tool-centred GenAI adoption towards capability-driven strategies that strengthen KMC and formalise ISR in order to achieve financial, environmental and social gains
The rising adoption of distributed agile teams has reshaped the global software industry. However, sustaining their effectiveness remains a significant challenge, particularly in the rapidly evolving Information Technology (IT) industry. While trust dynamics, knowledge sharing process, and Information and Communication Technology (ICT) are extensively recognized as essential facilitators of collaboration, their interconnections in distributed agile teams remain underexplored. The present study examined the relationship between Cognitive-based Trust (CBT) and Affect-based Trust (ABT) and key knowledge-sharing processes, including Socialization (SOC) and Externalization (EXT), and assessed their mediation role in relation to Agile Distributed Team Performance (ADTP). The study also investigated the moderating role of ICT in these relationships. To address the objectives, a quantitative, cross-sectional research design was adopted. Data were collected through a survey using structured questionnaires from ADTP associated with the IT industry of Pakistan. Using purposive sampling, three major cities, namely Lahore, Karachi, and Islamabad, were selected. As a result, 193 responses were deemed usable for data analysis. The study utilized Structural Equation Modelling (SEM) to investigate the hypothesized relationships. SPSS 25 and SmartPLS 4 were applied to test hypothesized relationships. The most important findings demonstrate that CBT is significantly associated with both knowledge-sharing processes and team performance, whereas ABT shows weaker or non-significant effects. SOC and EXT are confirmed as key mediators linking trust to ADTP. ICT strengthens EXT but provides limited support for SOC-related processes. By integrating trust theory, selected SECI knowledge conversion processes, and socio-technical perspectives, this study advances understanding of trust and ICT operating through process-specific boundary conditions in distributed agile collaboration. It also provides practical guidance for emerging IT contexts. The findings also have implications for e-learning practices through an emphasis on CBT, knowledge articulation, and the efficient development of ICT in collaborative learning and knowledge-sharing within technology-oriented learning environments. On the other hand, the empirical demonstration of the role of socio-technical enablers in the knowledge-sharing process and its impact on performance in a collaborative learning environment enhances the existing e-learning literature. It also highlights the importance of fostering CBT, improving documentation practices, and aligning ICT use with relational engagement to enhance ADTP.
This study examines how generative artificial intelligence use and knowledge-oriented leadership influence entrepreneurial orientation through the mediating role of knowledge management capability in postsecondary education institutions . Despite the growing interest in artificial intelligence and entrepreneurship, prior research has predominantly focused on individual-level outcomes, while the organizational mechanisms that translate technological and leadership inputs into entrepreneurial behavior remain insufficiently understood. Addressing this gap, the present study adopts a capability-based perspective grounded in the knowledge-based view. A quantitative research design was employed. Data were collected from 387 academic staff members across 25 colleges in Kazakhstan using a structured questionnaire. The proposed model was tested using partial least squares structural equation modeling (PLS-SEM), enabling the assessment of both direct and indirect relationships among the constructs. The results indicate that knowledge-oriented leadership exerts a strong positive effect on knowledge management capability, which in turn significantly enhances entrepreneurial orientation. Generative AI use demonstrates both a direct effect on entrepreneurial orientation and an indirect effect through knowledge management capability, suggesting a complementary mediation mechanism. The findings further reveal that the impact of GenAI is contingent upon its integration into organizational knowledge processes rather than its isolated or ad-hoc use. The study contributes to the literature by providing a capability-based explanation of how technological and leadership factors jointly shape entrepreneurial orientation at the organizational level. It extends prior research by moving beyond individual-level perspectives and highlighting the central role of knowledge management capability as a transformation mechanism. From a practical standpoint, the findings suggest that educational institutions should prioritize the development of structured knowledge processes and leadership practices that support knowledge sharing and application when implementing GenAI initiatives. Such an approach enhances the sustainability and consistency of entrepreneurial behavior within knowledge-intensive environments.
Knowledge-sharing practices is crucial for communities striving to combat poverty. The paper explores knowledge-sharing practices for poverty eradication among rural women in Ghana and makes recommendations to improve knowledge sharing. It adopted the interpretive paradigm and a qualitative research approach. The primary data were obtained from 111 rural women in the Northern region, Ghana. Face-to-face interviews, focus-group discussions and observations were used to collect data. The study was guided by the following question: “What are the knowledge-sharing practices for poverty eradication among rural women in the northern region of Ghana?” Thematic analysis was conducted based on Braun and Clarke’s (2006) framework. The findings revealed that rural women engage in a variety of knowledge-sharing practices such as social interactions with extension officers, interactions between family and friends, interactions with social cliques and self-proclaimed experts, village meetings, religious leaders and institutions meetings, Communities of Practice and knowledge sharing programmes. The study recommends the need for rural women to seek professional knowledge from established knowledge centers. A dedicated mobile phone helpline project is also recommended, as well as the training and motivation of extension officers to improve the quality of extension services provided to rural women. Additionally, elements such as literacy programs, appropriate leadership, stakeholder participation, trust and respect for culture, ICT technology, gender-equity campaigns, behavioral change, social amenities and resource availability and ongoing knowledge-sharing programmes were also considered crucial for enhancing knowledge sharing practices. The study contributes to knowledge management by demonstrating how tacit knowledge flows are sustained through informal networks, trust, and reciprocity in rural contexts. By foregrounding these socially embedded and community-driven practices, it broadens knowledge management theory beyond corporate settings and highlights their relevance for poverty eradication and women’s empowerment. The study is timely as it seeks to leverage knowledge management practices to eradicate poverty, empower women, and address gender inequality in line with Goals 1 and 5 of the Sustainable Development Goals.
The growing conceptual complexity and persistent ambiguity surrounding the definition and measurement of the Knowledge Society/Knowledge Economy (KS/KE) and its associated competencies point to an unresolved research gap, which may contribute to fragmented and insufficiently coordinated policy responses. While numerous frameworks describing 21st-century skills and competencies exist, their linkage to macro-level indicators capturing the performance of knowledge-based economies remains limited and methodologically underexplored. This paper addresses this gap by examining the methodological viability of systematically deriving key competencies for the KS/KE from Knowledge Economy Index (KEI) indicators and by assessing whether the resulting competency model demonstrates conceptual congruence with established 21st-century competency frameworks. The primary objective of the study is to develop and apply a novel and robust methodological framework for constructing a key competency model tailored to the contemporary socio-economic context of the KS/KE. The proposed approach is grounded in a systematic content analysis of existing KEIs and their constituent indicators. Specifically, the methodology is applied to a dataset comprising 301 indicators derived from four internationally recognised KEIs: the Global Knowledge Index (GKI), the Global Innovation Index (GII), the European Innovation Scoreboard – Summary Innovation Index (EIS- SII), and the Digital Economy and Society Index (DESI). A central methodological contribution of the study lies in the uniform semantic categorisation of all indicators and their systematic division into input indicators, capturing structural prerequisites and investments, and output indicators, reflecting achieved results and performance. This analytical structure enables the identification of key competencies that mediate the transformation of invested resources into measurable and socially desirable outcomes within KE. To assess the conceptual robustness of the proposed model, the resulting key competency model for KS/KE is validated against a reference database of competencies synthesised from authoritative policy and strategic documents issued by organisations such as the OECD, UNESCO, the European Commission, the Council of the European Union, the World Economic Forum, and the Partnership for 21st Century Learning. The validation confirms a high degree of conceptual alignment between the empirically derived competencies and established 21st-century competency frameworks. In addition, the study exploits an extensive longitudinal dataset of KEI indicators available since 2017 as the empirical basis for a model-based analysis of anticipated trends in key competency development over a forthcoming three-year horizon. Compared to traditional competency modelling approaches based on expert studies, job analyses, behavioural observations, Delphi methods, or surveys, the proposed model leverages dynamically updated KEI indicators, offering greater flexibility and responsiveness to rapid socio-economic change. At the societal level, the resulting KS/KE key competency model provides a foundation for preparing future knowledge workers, while at the organisational level it supports talent management practices and the development of organisation-specific competency models aimed at sustaining competitive advantage.
This research undertakes a systematic literature review to explore the integration and application of ontologies within Business Intelligence (BI) components across a variety of domains. Ontologies, as formal representations of knowledge, have emerged as a key enabler in enhancing the functionality and intelligence of BI systems, particularly in the era of big data and digital transformation. The objective of this study is to analyze how ontologies are designed, implemented, and utilized to improve data integration, semantic interoperability, and system adaptability. The review draws upon data sources from Scopus, IEEE Explore, Science Direct, and Google Scholar, ensuring a rigorous and comprehensive coverage of relevant literature. Following a structured selection process based on inclusion and exclusion criteria, 27 peer-reviewed articles published between 2011 and 2024 were identified as meeting the quality and relevance standards for this study. The selected studies reveal that ontology-driven BI components offer several advantages, including the unification of heterogeneous data sources, improved semantic clarity, and enhanced reasoning capabilities for decision support. Moreover, ontologies contribute significantly to the flexibility and scalability of BI systems, facilitating the development of context-aware and domain-specific analytical tools. Despite these advantages, the review also highlights persistent challenges, such as difficulties in managing large-scale ontologies, real-time processing limitations, and organizational resistance to adoption due to complexity and integration costs. By synthesizing the existing body of knowledge, this review not only consolidates the current understanding of ontology-driven BI but also provides a conceptual framework for future research. It emphasizes the need for innovative approaches that address identified limitations and align ontology development with dynamic organizational requirements. The findings serve as a valuable resource for both researchers and practitioners, offering strategic insights into the design and deployment of advanced BI solutions. Ultimately, this study contributes to the evolving discourse on intelligent decision-making systems by bridging theoretical perspectives with real-world applications.
Escalating global environmental challenges have intensified pressure on businesses to adopt sustainable practices, particularly within Small and Medium-sized Enterprises (SMEs). While leadership is recognized as a pivotal driver of this transition, the specific internal organizational mechanisms through which leadership influences green outcomes remain underexplored. This study examined the impact of transformational leadership on green business performance in SMEs, focusing specifically on the mediating roles of knowledge management practices and cultural infrastructure. A quantitative research design was employed, utilizing survey data collected from 135 SMEs across diverse manufacturing and service sectors in Southeast Asia. Structural equation modeling was used to test the hypothesized relationships in the study. The findings indicate a significant positive relationship between transformational leadership and green business performance. Crucially, both knowledge management practices and cultural infrastructure were found to mediate this relationship significantly, both individually and in concert. This study underscores the strategic importance of nurturing robust knowledge management systems and a supportive cultural environment to translate transformational leadership initiatives into tangible green outcomes within SME. This study contributes to a more nuanced understanding of the pathways through which leadership fosters sustainability, offering interdisciplinary insights relevant to management, economics, and environmental studies.
This study examines the cultural dynamics that influence knowledge-sharing in Philippine higher education institutions (HEIs). It addresses the gap in understanding the impact of national, organizational, and local (institutional) cultural factors on educators' intentions to share knowledge. The research employs a mixed-methods approach, integrating quantitative analysis via multiple regression and ANOVA with qualitative insights from follow-up interviews. This comprehensive methodology suggests that cultural dimensions, such as power distance and collectivism, have a significant influence on knowledge-sharing intentions. The findings indicate that diminishing power distance and formalizing knowledge-sharing processes enhance the knowledge ecosystem within HEIs. These insights are valuable for educational practitioners, administrators, and policymakers who aspire to cultivate a collaborative and knowledge-rich environment. By customizing strategies to align with local cultural contexts, institutions can enhance teaching, research, and application, thereby advancing the domains of learning and organizational competitiveness.
Research exploring the integration of knowledge management and artificial intelligence has grown significantly over the past two decades, driven by the transformative potential of intelligent technologies in reshaping how organizations create, share, and apply knowledge. Despite this expansion, the field remains conceptually fragmented, with limited synthesis across theoretical and practical contributions. This study offers a comprehensive bibliometric analysis of 1,650 peer-reviewed publications indexed in the Web of Science from 1975 to 2024. By employing performance metrics, co-citation and keyword co-occurrence analyses, timeline visualizations, and citation burst detection; the study maps the intellectual landscape and thematic evolution of this interdisciplinary domain. The results reveal four core thematic areas: the strategic application of artificial intelligence in human resource management, hybrid decision-making frameworks, innovation-driven supply chain transformation, and the use of intelligent systems in hospitality and service delivery. These clusters illustrate the field's conceptual diversity and the convergence of technological and managerial perspectives. Burst-detection analysis pinpoints 2020–2023 as a tipping period, when landmark publications sharply accelerated theoretical diversification and research momentum across the KM–AI domain. Theoretically, the study refines the Knowledge-Based View by introducing the contingencies of algorithmic transparency and inter‑organizational power asymmetry, advancing a paradox-aware lens that reconciles augmentation vs. transformation and optimization vs. resilience tensions. Practically, cluster-specific evidence is translated into adaptable principles for HR leaders, supply-chain managers, and service innovators, emphasizing phased AI deployment, transparency-driven trust, and balanced efficiency–resilience strategies, while informing sector-specific governance standards and paradox-aware curricula for policymakers and educators. By identifying key research trajectories, influential contributions, and emerging areas of inquiry, this work provides a structured overview of the field's development and lays the foundation for future investigations into the evolving relationship between knowledge management and artificial intelligence. The results reveal four core thematic areas: the strategic application of artificial intelligence in human resource management, hybrid decision-making frameworks, innovation-driven supply chain transformation, and the use of intelligent systems in hospitality and service delivery. These clusters illustrate the field's conceptual diversity and the convergence of technological and managerial perspectives. Burst-detection analysis pinpoints 2020–2023 as a tipping period, when landmark publications sharply accelerated theoretical diversification and research momentum across the KM–AI domain. Theoretically, the study refines the Knowledge-Based View by introducing the contingencies of algorithmic transparency and inter‑organizational power asymmetry, advancing a paradox-aware lens that reconciles augmentation vs. transformation and optimization vs. resilience tensions. Practically, cluster-specific evidence is translated into adaptable principles for HR leaders, supply-chain managers, and service innovators, emphasizing phased AI deployment, transparency-driven trust, and balanced efficiency–resilience strategies, while informing sector-specific governance standards and paradox-aware curricula for policymakers and educators. By identifying key research trajectories, influential contributions, and emerging areas of inquiry, this work provides a structured overview of the field's development and lays the foundation for future investigations into the evolving relationship between knowledge management and artificial intelligence.
Understanding the role of moderating variables is important. Researchers, academicians, and practitioners can see what is happening between two variables and find ways of addressing the changes. Promoters of the resource-based view theory assert that organizations possess heterogeneous resources with unique strategic characteristics that make them competitive. A shared understanding is required for organizations to control the resources. This paper seeks to establish the moderating role of information systems resources on the relationship between shared information systems knowledge and information system function performance. The study used interdisciplinary theories and adopted descriptive, exploratory, and cross-sectional research designs. We used data from 42 public and private universities in Kenya. Members of each university's Top management team and the IT head took part in the study. The data was modeled and analyzed using the partial least squares structural equation modeling technique. The findings of the study revealed that information system resources have a direct and significant effect on information system function performance (β= 0.820), (t=13.904), and p-value (0.000). However, shared IS knowledge has an insignificant effect on information system function performance (β= 0.025), (t = 0.336), and p-value (0.369). The findings suggest that there may be other factors influencing the relationship between shared IS knowledge and IS function performance, as IS resources do not show a moderating effect. The study had limitations. First, the study sample included only a few university strategic leaders. A higher number of strategic leaders in the sample may provide a better representative sample of university leaders. Second, other factors, like culture, can influence the level of information sharing. Finally, the study suggests future longitudinal research to test if there are other factors and mechanisms that combine with shared IS knowledge to affect IS function performance in organizations. The findings of the study provide useful information about shared IS knowledge, IS resources and how they interact to impact IS function performance. Understanding the moderating effect of IS resources towards IS function performance and how it can help university IS strategic leaders improve the overall performance of information systems is important. Also, these findings may be useful for information technology or systems service managers and industry practitioners in appreciating practices that bring positive contributions to their information systems. The research findings are useful to policymakers and practitioners in helping them to gain better insights and understanding of the factors and changes to better exploit organizational IS resources. The findings will also help them understand what structures and mechanisms to use for a better understanding of shared IS knowledge to fully exploit resources for Optimal IS function performance. The study's findings will provide organizational leaders with the opportunity to share knowledge and understanding, as well as to develop cultural change structures for better utilization of IS resources to enhance performance.
A scoping review was conducted in order to systematically map the research featuring Project Based Organizations (PBOs) in relation to knowledge transfer. This scoping review considered over 50 years of research to ascertain how PBOs transfer knowledge by using an interpretative structural model (ISM) to illustrate the outcomes of the investigation via the Systemic Lessons Learned Knowledge (Syllk) Model, created by Duffield and Whitty (2015). We wanted to illustrate what knowledge transfer elements from the authors’ original model outlining six key themes were sustained and prevalent in literature as representative of this knowledge transfer process. The six elements are: learning, culture, social, technology, process and infrastructure. Employing an ISM also helped identify gaps in existing knowledge. The following research questions formed the basis of our study: Research Question 1: How does the Syllk model help interpret and categorize knowledge transfer dynamics in PBO contexts? Research Question 2: What adaptations are required, if any, to the Syllk Model (Duffield & Whitty, 2015) to better facilitate knowledge transfer within PBOs? Research Question 3: What are the key barriers to knowledge transfer in PBOs? Findings: Extant literature indicated that knowledge sharing depends on the willingness of individuals to participate, without which lessons cannot be learned. The results of this scoping review illustrated how some of the elements within the original Syllk Model by Duffield and Whitty (2015) are not fully exploited by organizations. Moreover, several terms possess hazy definitions which further disadvantaged outcomes as it makes some reserch outputs open to question because concensus on the ideology for each element considered as a key theme is subject to interpretation. We propose the Aspirational Syllk (ASyllk) Model as a reconceptualized ISM that enables PBOs to systematically capture and assess experiential learning outcomes. Methodology: A scoping review was undertaken looking at 202 peer reviewed journal papers: Scoping reviews differ from a systematic review in that the former maps a broad body of literature on relevant topic areas and provides tabular outputs, as well as identifying gaps. Whereas the latter considers a far narrower range of research material as it possesses a dedicated synthesis. We subscribed to the scoping review protocol advocated by Bragge et al. (2011) in that we delineated our area of exploration, thereafter we conducted an extensive literature review and then we reported upon these sources to accurately assess the barriers to organizational learning and, thus, identify the gaps in literature. We also considered the antecedents that go into knowledge transfer in PBOs. Significance: Despite a half century of research on knowledge transfer, our findings indicated that knowledge transfer is not intrinsic to PBOs, thus illustrating the need for robust project termination processes to garner key lessons learned for subsequent organizational learning capacity. Through our extensive examination of existing literature, covering over 200 sources, we illustrated a detailed understanding of the barriers to knowledge transfer within PBOs. This scoping review serves as a powerful resource for researchers and practitioners by offering insights into an ammended model to test in future research.
Knowledge management (KM) is recognized as being vital for organizational competitiveness and sustainability for both private and public organizations. A great myriad of theories, frameworks, and tools have been developed, many of which have been developed with private organizations in mind, given their dependence on maintaining competitiveness in the market for their survival. However, the stakes for public organizations could be considered greater, as their decisions and actions affect a wide range of stakeholders, and their management, in general, faces important challenges, such as the high turnover of their employees. For this reason, numerous efforts have been made to improve the way knowledge is managed in public institutions, yet its effective implementation in public entities remains a challenge. In Latin America, one of the countries where explicit efforts have been made to foster KM in public institutions is Colombia. The country has developed an Integrated Planning and Management Model (IPMM), which includes a specific mandate for KM implementation in all the public institutions of the country. Although the IPMM includes this KM mandate, Colombian public entities have been facing several difficulties in achieving the KM implementation. In fact, KM adoption has been slow and its impact limited, signalling the need for systemic solutions. This research employs a systemic approach, grounded in the ISO 30401 standard and a comprehensive literature analysis, to develop a KM implementation strategy tailored to the IPMM. The proposed strategy, emphasizing strategic, human, and operational factors, positions KM as the central organizing principle of the IPMM and, at the same time, is aligned with ISO 30401 guidelines. This integration aims to ease the implementation of KM within a KM system that leads to enhancing the performance of public entities in Colombia. Although being developed for Colombian public entities, the proposed strategy offers valuable insights for public administrations globally seeking to leverage KM for strategic advantage to better fulfil their mandates for the benefit of society as a whole.
In the fast-moving industrial environment of the world today, the importance of promoting innovation has clearly increased as a key driver of business performance. Nowhere is this more obvious than in the pharmaceutical industry, where the quest for advances in Research and development is viewed as crucial. Developing an awareness of the drivers of innovative working behavior among workforce members is of the highest priority, and this study investigates the link between knowledge sharing and innovative work behavior among pharmaceutical engineers in Morocco. Despite the increasing relevance of innovation in the pharmaceutical sector, studies on the effects of knowledge sharing in non-Western contexts are limited. This gap demonstrates the necessity for further research aimed at the Moroccan environment, where hierarchical structures and limited R&D capabilities influence knowledge-sharing practices. A sample of 286 pharmaceutical engineers contributed to a quantitative research study. The findings indicate that knowledge donating and knowledge collecting positively impact innovative work behavior, with knowledge donating exerts a greater influence. The paper highlights the value of promoting a culture of knowledge sharing to stimulate innovation. Limitations identified relate to the choice of convenience sampling and the restriction to a single sector. Additional investigation could be conducted in other sectors to better understand the links between knowledge sharing and innovative work behavior.
Small and medium-sized businesses (SMEs), especially those in the e-commerce industry, are finding it more challenging to use intangible assets to support innovation and commercial performance in the knowledge-based digital economy. Few studies have thoroughly investigated how various aspects of knowledge capability collectively impact business performance through innovation capability, particularly in the context of emerging economies like Vietnam, despite the substantial body of literature on knowledge management (KM) and innovation. By integrating five essential knowledge factors—knowledge management, knowledge absorptive capability, knowledge application, knowledge transformation, and knowledge sharing—and evaluating their effects on innovation capability and business performance, this study seeks to close this gap. A quantitative research strategy was used to accomplish this goal. Using a standardized questionnaire with validated scales, 567 SMEs in the Vietnamese e-commerce industry were surveyed to collect primary data. To test the hypotheses and assess the structural links between the constructs, the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that all five knowledge-related elements have a beneficial impact on corporate performance and innovation capability. Interestingly, knowledge transformation had the most significant influence on innovation potential, while knowledge management had the most significant direct impact on company performance. The association between knowledge components and business results was also found to be somewhat mediated by innovation capability, underscoring its function as a dynamic capability that transforms knowledge into concrete value. The theoretical presumptions of the Knowledge-Based View (KBV), the Resource-Based View (RBV), and the Dynamic Capabilities theory are all supported by these findings. The results show how knowledge management and knowledge capabilities can be used to boost innovation and enhance business performance in the digital economy, with practical implications for SME managers, legislators, and other stakeholders.
In the contemporary knowledge-driven economy, organisations are increasingly dependent on knowledge management and intellectual capital as key drivers for enhancing organisational performance. Despite the growing academic interest in these domains, research examining their combined impact remains limited, particularly within the context of the telecommunications sector in developing economies. This study aims to address this gap by identifying the impact of knowledge management on organisational performance through intellectual capital in the Yemeni telecommunications sector. To achieve this objective, the present study employed the quantitative research methodology, incorporating descriptive and analytical approaches. SPSS was utilised for descriptive and preliminary statistical analysis, while PLS-SEM was employed to examine the effects among the variables. The questionnaire was the principal instrument used to collect the necessary data for this study. A structural model has been proposed for the study variables, illustrating the relationship between knowledge management, intellectual capital, and their subsequent impact on organisational performance. The non-proportional stratified random sampling method was employed to select the study sample individuals. The model was evaluated using data obtained from 289 individuals employed in the Yemeni telecommunications sector. The study's findings indicated that knowledge management positively impacts organisational performance (B=0.776; p < 0.05), suggesting that knowledge management plays a significant role in enhancing organisational performance. In addition, intellectual capital was found to have a statistically significant direct impact on organisational performance (B=0.557; p < 0.05), highlighting its contribution to enhancing organisational performance. Furthermore, the results revealed a significant effect of knowledge management on IC (B=0.852; p < 0.05), suggesting that knowledge management enhances intellectual capital, which in turn strengthens its impact on organisational performance. Moreover, the mediation analysis confirmed that intellectual capital mediated the relationship between knowledge management and organisational performance, demonstrating that knowledge management influences organisational performance both directly and indirectly through intellectual capital. The findings contribute to the development of the resource-based view (RBV) and the knowledge-based view (KBV) by demonstrating how knowledge management and intellectual capital interact and jointly influence organisational performance. Furthermore, this study contributes to the extant literature by presenting a model that connects these variables in the telecommunications sector, a field that has not been sufficiently studied in previous research. In light of the aforementioned findings, the study recommended an increased focus on organisational performance and the establishment of organisational units within the organisational structures of the Yemeni telecommunications sector concerned with knowledge management, due to its significant impact on enhancing organisational performance in the Yemeni telecommunications sector.
This qualitative study investigates the impact of implementing a Wiki-based knowledge management system on job satisfaction and performance in a medium-sized enterprise (SME) operating in the pool construction industry in Western Europe. This study aims to address the conflicting findings in the literature regarding the relationship between knowledge management, job satisfaction, and employee performance as well as the lack of research in the context of Western European SMEs. Using a qualitative methodology, the study provides nuanced insights into the effects of specific knowledge management processes, such as knowledge acquisition, sharing, generation, codification, and preservation, at different organisational levels. The results showed that the implementation of the Wiki-based knowledge database led to significant improvements in job satisfaction, mainly because of the ease of finding information and streamlining work processes. However, the system’s ability to fully meet employees' specific knowledge needs influences their satisfaction levels. This study also highlights the differential impact of knowledge management processes at different organisational levels, with middle management and professionals benefiting more than top management and administrative staff. The findings are consistent with previous research indicating a positive relationship between knowledge management practices and job satisfaction and support the notion that well-structured and accessible knowledge resources can lead to better job performance. This study contributes to the field by offering a rich, qualitative perspective on the implementation of Wiki-based knowledge systems in the specific context of the pool construction industry in Western Europe, providing valuable insights for both researchers and practitioners in the fields of knowledge management and organisational behaviour.
Software Development Projects (SDPs) in developing economies often experience high failure rates, with the knowledge transfer (KT) behavior of SDP managers being a key challenge. While research on KT behavior is extensive in developed nations, limited studies focus on emerging economies, particularly Nigeria. This study aims to examine the factors influencing KT behavior among SDP managers in Nigeria based of insights from Social Cognitive Theory (SCT) and the SECI model. This study employs a quantitative research approach with multiple regression analysis in SPSS to test the research hypothesis and analyze the relationships among the variables in the proposed model. Data was collected from 160 SDP managers in Nigeria using a structured survey questionnaire. The results indicate that Work Motivation, Trust to Share, Social Interaction, IT Infrastructure, and Security and Privacy significantly influence KT behavior among SDP managers. However, Reciprocity, Social Identity, and Shared Language were found to have no significant impact. These findings suggest that both psychological and technological factors play a vital role in fostering KT behavior, however SDP managers in Nigeria do not regard reciprocal benefit social identity and shared languages as critical factors that influences their KT behaviors. This study provides insights for SDP managers, policymakers, and knowledge management practitioners on the factors that can improve KT behaviors of SDP managers. It emphasizes the need for targeted interventions, such as fostering trust-based collaboration, strengthening IT infrastructure, and ensuring secure knowledge-sharing platforms to enhance KT practices.
Technological developments have seen a rapid evolution in the last decade. The complexity and cyber-attacks increase within the advancement of technology and artificial intelligence, this creates pressures for corporations to adopt the necessary methods to ensure they function in a safe environment. This study attempts to assess the role of managers’ informational security intelligence (MISI) along with procedural information security countermeasure awareness (PCM) and cybersecurity protection motivation in promoting cybersecurity protective behaviour among employees in the public sector within the context of UAE. The study employs quantitative cross-sectional design with primary data collected from 520 employees in nine listed organisations in the public sector of Abu Dhabi, UAE. The data is analysed using Partial Least Square Structural Equation Modelling (PLS-SEM). The findings indicated that perceived threat susceptibility, self-efficacy, information security problem-solving, and social competence significantly affect cybersecurity protective behaviour. Additionally, MISI positively influences PCM, which in turn affects cybersecurity protection motivation. Finally, attitude moderates the relationship between self-efficacy and cybersecurity protective behaviour. The study extended the protection motivation theory by investigating the capabilities and competences of managers related to information security in addition to adding the attitude as a moderating variable. The findings offer valuable insights for policy makers in the aspect of ensuring the implementation of cyber security national strategies; for managers in organisations in the aspect of promoting awareness and capabilities among themselves and among their employees through educational and training programs to enhance their cybersecurity practices and mitigate risks.
