European Conference on Knowledge Management

Developing Entrepreneurial Mindset Among Non-Business Majors Through Experiential Learning and AI Tools

Fawad Ahmed — 2025-08-29

Despite the proliferation of entrepreneurship education (EE) programs, conventional pedagogies often fall short in cultivating the critical cognitive and affective dimensions of the entrepreneurial mindset, particularly in areas such as opportunity recognition, creative problem-solving, and resilience. This study addresses this enduring pedagogical challenge by embedding experiential learning and generative artificial intelligence (AI) tools into an entrepreneurship education. Drawing upon Kolb’s Experiential Learning Theory and Biggs’ Constructive Alignment frameworks, the instructional design integrated immersive fieldwork, problem-based tasks, and iterative AI-supported learning experiences. Generative AI tools were strategically deployed to scaffold ideation, support inquiry, and enhance formative feedback throughout the entrepreneurial process. Using a mixed-methods approach, the study assessed the entrepreneurial mindset (EM) of 92 postgraduate students before and after the intervention. Partial Least Squares Structural Equation Modeling (PLS-SEM) confirmed EE explains 47.8% of the variance in EM. Quantitative findings reveal a statistically significant 35.48% increase in EM scores. Qualitative data, drawn from student reflections and thematic analyses, further underscored the perceived value of AI integration and real-world engagement in fostering entrepreneurial thinking, industry relevance, and innovation capacity. The findings contribute to the evolving discourse on entrepreneurship education by demonstrating the pedagogical value of integrating immersive, AI-augmented experiential learning in developing future-ready entrepreneurial competencies. By incorporating AI into the experiential learning framework, students were not only trained in research methods and entrepreneurial problem-solving but also in AI literacy, which is increasingly seen as an essential futuristic skill. This study makes a theoretical contribution by empirically validating how Kolb’s Experiential Learning Theory and Biggs’ Constructive Alignment Model can be enhanced through AI integration in entrepreneurship education. It offers actionable insights for educators and institutions seeking to modernize entrepreneurship programs. Our problem-based approach, incorporating immersive field trips, AI-assisted research tools (ChatGPT, DeepSeek), and authentic assessments, proved particularly effective in developing students’ critical thinking, opportunity recognition, and adaptive problem-solving skills.

Factors Shaping Knowledge Sharing Behaviour in Remote Work

Anna Albrychiewicz-Słocińska — 2025-08-29

The discussions that take place in the literature on the subject in relation to the advantages or disadvantages of remote work take on additional significance if employees representing the youngest generation of employees are taken as a reference point. For representatives of this generation, the communication tools used in remote work dominate over the form of direct communication. Through them, young employees build relationships, learn, acquire knowledge and share it. However, the results of the research draw attention to the fact that in relation to Generation Z, there may be problems related to the exchange of knowledge understood as learning and teaching others, which may result from different generational characteristics, including professed values, attitude to work and expectations towards it. The research results presented in the study are part of a quantitative survey on "Managerial aspects of remote work management", carried out among young people working remotely. The survey was carried out in December 2022 and analysed areas of remote work such as knowledge exchange/learning, communication, work organization, WLB, motivation and employee relations. The study diagnoses measurement models using structural modeling (SEM) in the field of latent factors. The analyses were carried out using IBM SPSS and IBM SPSS AMOS software.

Fostering Knowledge Management Practices Through Artificial Intelligence: Vision 2030 as a Catalyst

Abobakr Aljuwaiber — 2025-08-29

The rapid integration of artificial intelligence (AI) into organisational operations has transformed knowledge management (KM) practices, providing opportunities to enhance decision-making, innovation and efficiency. This study explores the adoption and impact of AI on KM practices in Saudi Arabia, focusing on the alignment of these advancements with the Kingdom’s Vision 2030 objectives for economic diversification and innovation-driven growth. Using a quantitative methodology, data were collected from management in private and public organisations to analyse the perceptions, challenges and opportunities of adopting AI for KM. While AI tools significantly enhance knowledge sharing, collaboration and the accuracy of knowledge repositories, the findings reveal that AI adoption is hindered by challenges such as limited technical expertise, high costs and resistance to change. The data underscore a strong expectation that AI-driven KM will become essential for maintaining competitiveness in the next decade. Additionally, organisational managers highlight the role of AI in fostering a culture of innovation and entrepreneurship, crucial for achieving the strategic goals of Vision 2030. This research provides actionable insights for policymakers and business leaders, identifying critical enablers of AI adoption, including investments in digital infrastructure, skill development and change management strategies. By addressing these barriers, organisations can optimise the integration of AI to support sustainable development and innovation. The study contributes to the growing body of literature on AI and KM in emerging economies, offering practical recommendations that bridge the gap between technology-driven initiatives and strategic objectives.

Generative AI Applied to the Design Thinking Process in Knowledge Engineering Projects

Ranieri Alves dos Santos — 2025-08-29

The need for user-centered and agile solutions has driven the adoption of methodologies such as Design Thinking in knowledge engineering projects. While the Design Thinking emphasizes empathy, iteration, and innovation focused on user experience, the knowledge engineering aims to build intelligent systems based on formalized expert knowledge. Despite the conceptual alignment between these approaches, the integration of Generative Artificial into this context remains underexplored. This study proposes a model that incorporates generative AI tools into the design thinking process to accelerate and enhance the development of knowledge-based systems. Based on the Design Science Research (DSR) methodology, a narrative literature review and exploratory research were conducted to identify generative AI techniques applicable to each design thinking phase: Empathize, Define, Ideate, Prototype, and Test. A total of 17 generative AI approaches were mapped and organized into a model that supports small and agile teams in knowledge engineering projects. The model was instantiated through the development of GPT-based agents customized for specific tasks, such as persona generation, empathy mapping, requirements analysis, and prototype creation. These agents leverage prompts containing transcripts, observations, or interview data to generate detailed and realistic outputs, streamlining processes that are traditionally manual and time-consuming. One example presented is the Persona Generation Agent, which creates structured user profiles and illustrative images from simple textual input. This integration contributes both theoretically and practically by demonstrating how generative AI can be used to enhance user experience (UX) focused design processes in knowledge engineering. The proposed model promotes more efficient workflows, while keeping the user at the center of development. It also supports interdisciplinary collaboration, faster iteration cycles, and the creation of intelligent systems that are more aligned with user needs. Future work includes empirical validation of the model in diverse application contexts, aiming to refine its use and encourage widespread adoption in knowledge engineering and related fields.

Valorising Academic Knowledge: A Framework for Research-to-Market Pathways

Fabrizio Amarilli — 2025-08-29

The present study investigates how entrepreneurial universities can systematically exploit diverse knowledge assets for societal and economic impact. Despite growing emphasis on research valorisation, literature lacks clarity on managing varied research types, such as fundamental or domain-specific, and aligning them with exploitation goals. Universities often struggle to deliver their wealth of research assets to the market. Through an ethnographic case study of a technical university, this research examines three exploitation pathways. By analysing research assets through a framework that classifies knowledge based on its Research Focus and Exploitation Scope, the study unveils the internal and external conditions that enable research exploitation. These results advance knowledge management theory by integrating creation-to-application dynamics and refine the well-known Triple Helix model with operational insights. From a practice perspective, the framework provides a strategic tool for university researchers and administrators to map assets, assess exploitation states, and guide transitions, enhancing governance and partnerships.

Bibliometric Analysis Method of Examining the Concept of Green Knowledge Management and Sustainability: A Test for Web of Science Application

Muhammet Ünal Arvas — 2025-08-29

The concept of sustainability and organizational green policies is very important from environmental studies perspectives nowadays. Green practices are evaluated in many different aspects, such as environmental, technological, and economic, in organizations. The green and environmental adaptation of all aspects of knowledge management is defined as “green knowledge management,” as well as is being examined by scientists in various aspects, following the organizational structure in the study. The development of green knowledge management, its applications, analyzing it geographically, evaluating its academic performance, and evaluating the existing intellectual accumulation on the subject is possible with bibliometric analysis. Bibliometric analysis methods are used in both academic and administrative studies, as well as to quantitatively analyze scientific publications produced by scientists and academic institutions. It plays an active role in the decision-making process, especially in the measurement of academic performance, in the evaluation of a particular subject, publication, institution, and in the collection development policy practices of libraries. In this study, in addition to the distribution of articles on green knowledge management indexed in the Web of Science (WoS) database according to years, countries, and institutions, keywords and institutions are also used to explain the relationship between the concepts related to green knowledge management and sustainability concepts.

Application of Knowledge Management and Decision Support Systems in Lafarge Africa Plc

Adedola Atolagbe — 2025-08-29

The twenty-first-century economy has been termed as the Knowledge economy that is driven by people, information, and technology. Knowledge management has also been proven to enhance strategic advantage and improve organizational performance. Decision making and Decision support systems are enhanced with knowledge management. It is, therefore, critical for organizations to focus on knowledge management that derives effective and well- informed decision making with decision making as a tool. The purpose of this research was to examine and establish a knowledge management strategy and decision support systems in Lafarge Africa Plc. The study focused on the following research questions: What is the current level of knowledge management in Lafarge Africa Plc? What are the gaps in knowledge management in Lafarge Africa Plc? What are the impacts of Knowledge management on decision making in Lafarge Africa Plc? How can knowledge management strategy enable decision support systems in Lafarge Africa Plc? A mixed research method was adopted using a survey design by administering a questionnaire and conducting an interview for data collection. The population universe 1532 was used to calculate the sample size of 307 comprises 7 Top Management staff and 300 employees, using sample size calculator. Stratified Random sampling was utilized to arrive at the final respondents. The researcher used a questionnaire administered through email and semi-structured interview as the primary source of data collection instruments. Data was analysed using quantitative measures and was presented using percentages and tables. The study revealed that the level of knowledge Management practices in the organisation is low as several employees (Operational Staff) are not even aware of it. Even though, the Results confirmed that knowledge management enhances effective decision making, however, there was no significant impacts of knowledge management (KM) on decision-making at Lafarge Africa Plc It was recommended for a systemic shift encompassing technology upgrades, cultural transformation, and governance frameworks that make knowledge visible, accessible, and actionable across all levels of the enterprise, It also recommended that the management should Select and appoint experts internally to analyse, design and implement integrated KM framework.

Back to the Office, or not? Learning Lessons from Amazon vs. Spotify

Stefan Güldenberg — 2025-08-29

As we are slowly recovering from the COVID-19 crisis and the impact it has had on work and society, organizations are more and more questioning their remote and hybrid work models and are tempted to go back to a more “traditional” approach of working from the office. These initiatives are often referred to as the “return to office” (RTO) movement and have gained popularity and traction among many organizations. At the same time, many organizations have developed hybrid knowledge work models or even “work from anywhere” (WFA) approaches that emphasize location flexibility to their knowledge workers. Both discourses currently co-exist and compete in a discursive arena, that of the discourses that surround the future of work. The process of discursive institutionalization has received a broad interest since the seminal work of Phillips et al. (2004). Research has also emphasized the relationship between this legitimacy and discursive institutionalization (Golant & Sillince, 2007), suggesting that discursive legitimation (Vaara et al., 2024) can be key in a process of institutionalization. In this work, we focus on remote knowledge work and on how two major actors (Amazon and Spotify) have adopted very different practices on the topic of workplace location, with Amazon urging its employees to be back in the office full time and Spotify promoting a full remote or hybrid model of knowledge work. More specifically, we analyze how competing discourses about workplace location co-exist in a discursive arena and how both discourses are competing in a discursive legitimation process. To do so, we rely on official communication from both organizations focusing on official blog posts, reports, as well as media interventions from executives. We then conduct a critical discursive analysis focusing on storytelling that is used to support both RTO and WFA discourses. Findings highlight that Amazon and Spotify’s stories about workplace location share some similarities and differences in how they are built and the opposing ideologies that support these discourses. This work contributes to research on discursive legitimation and knowledge management theory by highlighting that Amazon and Spotify’s discourses about knowledge work and workplace location share some insightful similarities and differences as well as how competing discourses evolve within a discursive arena and how these institutionally innovating (or de-institutionalizing) discourses are competing in the same field.

Rethinking Strategic Thinking Through the Lens of Strategic Coherence

Konstantin Bagrationi — 2025-08-29

In light of the rapidly evolving complexities in strategic management and organizational behaviour, the aim of this research is to explore the conceptualization of strategic thinking in the context of innovative developments that have occurred in the research field over the past decades. This study is a follow-up upon the findings of a bibliometric analysis of publications between 1962 and 2024 obtained from the Scopus database and conducted to investigate shifts and trends in the research landscape of strategic thinking. Key conceptual shifts were identified through a co-occurrence analysis with a minimum threshold of 3. The study was also complemented with a qualitative analysis that offered a richer exploration of strategic thinking as a multidimensional construct. The research indicates that strategic thinking is no longer the sole purview of the C-suite but rather is being pushed down throughout the organization. Within this paper, four key dimensions of strategic thinking were identified: (1) analytical reasoning, (2) systems thinking, (3) strategic intuition, and (4) creativity – each critical to decision-making under uncertainty. Beyond mapping these dimensions, we demonstrate how they interact to produce strategic coherence – defined as the mutually compatible configuration of meanings, choices, and resource deployments that shape long‑term advantage. The research also explains how digital transformation and AI-based decision augmentation transformed strategic thinking from a rigid, top-down function to a dynamic, distributed, and ecosystem-centric model. An outcome of this is that strategic decision-making has become more dynamic, with employees at all tiers now expected to engage in strategic thinking. Drawing on these insights, along with an analysis of the strategic choices laying ahead, the paper outlines an alternative understanding of strategic thinking that takes into consideration both real-world and technological dimensions of it. This refinement in conceptualization enhances literature in strategic management and organizational psychology by showing that leaders must strengthen their muscle of strategic agility, digital literacy, and navigating uncertainty in pluralistic business ecosystems. The paper closes by outlining leadership‑development, strategic‑learning, and policy implications that flow from a strategically coherent mindset.

A Conceptual Framework for City Learning to Drive City Transformations Utilising Contextual Knowledge Management: Insights from Theory and Practice

Pradipta Banerjee — 2025-08-29

Cities of the future have been described as smart, socially innovative, people and community-driven, shaping collaborative ecosystems for learning and innovation. Cities are complex socio-technical ecosystems described as large-scale organisations. A city’s or an organisation’s knowledge can be transferred through collaborative processes involving relevant actors. City transformations through sustainable, citizen-centric development and innovation of cities require understanding cities as collaborative learning and innovation ecosystems aligned with societal needs that are often supported by technology. It calls for new and innovative ideas in knowledge management to address both organisations and cities. Building on theoretical work that conceptualises cities as learning and innovation ecosystems, this study proposes a conceptual framework for city learning. The framework includes a high-level ecosystem model and maps key elements/processes, illustrating interactions that can drive city learning. Through case studies of two European neighbourhood development projects complemented by an expert interview, we gain insights into utilising contextual knowledge management in city learning through multi-stakeholder interactions. The elements of a city include actors such as government and administrative bodies, citizens, private business institutions, funding bodies, and community groups, alongside the natural, built and technical environments. Elements assuming the role of facilitators emerged as catalysts in fostering collaboration and contextual innovation through knowledge exchange, while limited citizen participation and funding constraints remain challenges. The study reveals that trust among stakeholders and political vision can decisively influence learning outcomes in cities, highlighting the context-dependent nature of learning in cities. This study's main contribution is a framework for city learning to drive sustainable city transformations utilising contextual knowledge management.

Challenges and Practices for Knowledge Transfer in Global Software Development: An Updated Literature Review

Marcos Vinícius Benigno — 2025-08-29

In recent years, the evolution of technology and the increasing globalization of work have significantly transformed the software development industry. Global Software Development (GSD) has become a prevalent practice, enabling companies to reduce costs, leverage time zone differences for continuous development, and access diverse talent pools worldwide. However, knowledge transfer among distributed teams remains a significant challenge, often resulting in inefficiencies, project delays, and decreased software quality. As organizations increasingly rely on geographically dispersed teams, understanding the barriers to effective knowledge transfer in GSD is essential. This study is motivated by the need to reassess knowledge transfer in GSD, especially considering recent advancements in communication tools, collaboration platforms, and the widespread shift to remote work. While previous studies, such as those conducted by Zahedi et al. (2016), have examined knowledge transfer challenges and practices in GSD, the rapid technological and organizational shifts over the past decade necessitate an updated literature review. This work aims to provide a comprehensive overview of distributed teams’ challenges in knowledge transfer and the emerging practices to address these issues. A systematic literature review was conducted, building on the work of Zahedi et al. (2016) by analyzing research published between 2014 and 2024. The study followed a rigorous research protocol, utilizing the Scopus database to identify relevant papers and extract key insights. The findings highlight persistent challenges, including communication barriers, cultural differences, time zone constraints, and difficulties managing knowledge within distributed teams. Social and organizational factors hinder effective knowledge transfer, such as a lack of trust and inadequate coordination. The literature points to several best practices for facilitating knowledge transfer, including on-site visits for remote employees, synchronous and asynchronous communication tools, structured documentation, training programs, and establishing communities of practice. This study contributes to the field by offering an updated perspective on knowledge transfer in GSD, providing valuable insights for organizations aiming to optimize their global collaboration strategies. Future work should compare these findings with previous studies to track the evolution of knowledge transfer practices over time and explore new organizational approaches that have emerged in response to the changing dynamics of distributed software development.

The Contribution of Knowledge Management to the Co-creation of Sustainable Public Value

Marco Berardi — 2025-08-29

In recent years, public sector performance assessment has shifted beyond financial metrics to include Environmental, Social, and Governance (ESG) considerations, aligning with the sector's focus on creating public value (PV) rather than maximizing profit and guided by a Knowledge Management approach (KMA). Increasing stakeholder demands for transparency and sustainability have rendered traditional financial indicators inadequate for evaluating public resource use. In this context, Sustainability Accounting and Reporting (SAR) has emerged as a key framework, combining social and environmental accounting with formal reporting to enhance accountability and stakeholder engagement. SAR functions as an integrated mechanism for measuring and communicating progress toward sustainability goals, reinforcing transparency in public organizations through the leverage of KMA. Despite growing interest in both SAR and public value co-creation, which involves active stakeholder participation in shaping public services, their academic development has remained largely separate. This study seeks to bridge that gap by applying Mark Moore’s strategic triangle (1995) to SAR in the public sector, aiming to synthesize existing literature, identify research gaps, and examine how SAR supports the co-creation of public value.

Collaborative GenAI – Humanized Interaction Fields for Knowledge Creation

Karsten Böhm — 2025-08-29

Generative AI (GenAI) is increasingly becoming part of our habits, both in our professional and private lives. The
use of this is a way to shape, change and influence knowledge creation and utilisation, and thus a very interesting
phenomenon for the field of Knowledge Management (KM). In a previous work, the authors of this paper focused on the
bidirectional effects of KM processes due to the interaction between humans and machines using natural language as a
medium. The result of this work was the generative and responsive artificial intelligence (GRAI) model, which not only
generates content on demand, but also adapts and modifies knowledge-related interactions. This research focusses on the
concept of interaction fields and investigates the collaborative nature of those interaction fields to develop the conceptual
model even further. This is achieved by relating to the characteristics of collaborative robotics (COBOTs) as an established
form of human-machine interaction and the main differences of human-machine interactions to derive the concept of
Humanized Interaction Fields (HIF) that describe relevant aspects of interaction in the field of Human-centered AI (HCAI).
The research contributes to the understanding for the co-creation of knowledge between human and machine.

Types of Knowledge Shared Among Rural Women in the Northern Region of Ghana for Poverty Eradication

Baaba Bonuedie — 2025-08-29

This paper explores the types of knowledge shared among rural women in the northern region of Ghana for poverty eradication and make recommendations to enhance knowledge sharing among rural women in the northern region of Ghana. It uses qualitative research approach within an interpretive paradigm, primary data were collected from 111 rural women across the Tintang, Tongnoli, and Nagbali communities through face-to-face interviews, focus-group discussions, and direct observations. The findings reveal that rural women predominantly share indigenous knowledge related to agriculture, traditional crafts, maternal health, societal norms, and various local expertise. However, their access to external formal/technical knowledge is limited, which hinders their ability to enrich their existing knowledge for poverty alleviation. The study recommends expanding access to new types of knowledge through mobile network infrastructure, community radios, and other knowledge-sharing tools. Additionally, providing education and skill development opportunities is essential for fostering innovation and enhancing agricultural productivity. The paper further emphasizes the need to refine and repackage indigenous knowledge in a way that integrates external knowledge while preserving its core value, ensuring that it remains relevant for sustainable development. These findings align with the Sustainable Development Goals (SDGs), specifically Goal 1 (No Poverty) and Goal 5 (Gender Equality). The study was limited to rural women in Tintang, Tongnoli and Nagbali communities in the northern region of Ghana. A further study covering rural communities in other regions in Ghana is recommended.

AI-Supported Learning for Relational Capital Development: A Case Study in Higher Education

Manfred Bornemann — 2025-08-29

The systematic development of Relational Capital as part of Intellectual Capital is a critical element for career success. In two Austrian Master’s programs in digital technology and innovation at FHWien der WKW, an innovative teaching approach integrated AI-assisted learning with individual coaching. A customized GPT model was deployed as a structured reflection tool, assisting students in assessing and strategically developing their professional networks over the course duration. While traditional lecture time was reduced to two hours, instructional resources were redirected to AI-assisted learning and to group-coaching to enhance learning outcomes. This case study examines the use of generative AI as a dialogic tutor in a master's program on digital economy. Drawing on anonymized AI-student transcripts, coaching reflections, and structured prompts, the paper explores how AI supports strategic development of Relational Capital. Findings indicate high learner acceptance, evolving trust strategies, and improved metacognitive learning outcomes. AI shows strengths in guiding students through structured career planning exercises. However, concerns over trust and confidentiality emerged and lead students to adopt anonymization techniques to protect sensitive professional relationships. Beyond Relational Capital development, this study also highlights key pedagogical implications. AI’s effectiveness depends on high-quality learning materials, and students required training in prompt engineering to navigate information overload. The role of educators shifted towards facilitating learning processes, mentorship and strategic guidance, focusing on critical engagement with AI-generated content. This case study contributes to the discourse on AI integration in higher education. It demonstrates its role not only in developing Relational Capital but also in shaping self-directed learning behaviors and pedagogical innovation.

Artificial Knowledge and its Challenges for Knowledge Management Systems

Constantin Bratianu — 2025-08-29

It is a paradox that literature exploded in the last years with papers on “artificial intelligence”, but only a few of them dealt with “artificial knowledge”. The purpose of this paper is to analyze the concept of “artificial knowledge” and to compare it with human knowledge. That helps us to bridge the gap between artificial knowledge and knowledge management. More specifically, we focus on Generative Artificial Intelligence (GenAI), which has the capacity to simulate a human-like dialogue using natural language. The relevance of the present research comes from the need to understand the similarities and dissimilarities between artificial knowledge and human knowledge, and how both of them can be integrated into knowledge management systems. It is a conceptual paper based on a systematic literature review and a critical thinking approach. We used the theory of knowledge fields and knowledge dynamics for human knowledge and a GenAI analysis for artificial knowledge. Findings show that ChatGPT can answer a human interrogator by formulating texts comparable to those written by people. However, the imitation of human knowledge is not in its nature but in its functionality. The generation of artificial knowledge is completely different than that of human knowledge. Human knowledge is created by our sensory system and the brain through several processes, like perception and reflection. Artificial knowledge is generated by GenAI based on syntactic rules without any correlation with semantics. Computers cannot think and have no cognitive processes. Knowledge managers should be able to integrate both artificial and human knowledge into knowledge management systems. The main contribution of this paper is that it analyzes artificial knowledge and its generation from a knowledge management perspective. The main limitation of the present research comes from the scarcity of papers on the subject of artificial knowledge.

Measuring Knowledge Vulnerabilities in Knowledge Processes: A Scale Development

Constantin Bratianu — 2025-08-29

The aim of this paper is to propose and test a new measuring scale for the concept of “knowledge vulnerabilities”. With this research, we are continuing our work on a research project concerning knowledge risks and knowledge vulnerabilities that can manifest in organizations, alongside knowledge processes. In the context of a scarce literature concerning knowledge vulnerabilities, this research adds value by understanding and measuring knowledge vulnerabilities, as weak points of the knowledge system and of the knowledge management routines that could trigger or facilitate the appearance of risks, exposing the organization to threats. In this paper, we present an instrument for measuring knowledge vulnerabilities related to the knowledge processes within an organization, in the form of a questionnaire. This instrument is developed starting from a previously tested instrument, with 21 items, proposed by Neștian and Guță (2023). The new instrument contains 42 items, with newly developed items reflecting a deeper understanding of knowledge vulnerabilities. The taxonomy for knowledge vulnerabilities is based on a recent perspective of organizational knowledge dynamics (Bratianu, Neștian and Guță, 2022). In this research, seven knowledge processes are considered and vulnerabilities related to them are proposed: vulnerabilities related to knowledge creation, vulnerabilities related to knowledge acquisition, vulnerabilities related to knowledge loss, vulnerabilities related to knowledge sharing, vulnerabilities related to knowledge use, vulnerabilities related to emotional knowledge dynamics and vulnerabilities related to spiritual knowledge dynamics. The questionnaire has been applied in private companies, on both managers and non-managers. Principal components analysis was undertaken to highlight the components forming the construct of vulnerabilities related to knowledge processes. The factors resulting from applying the statistical method of principal components analysis on the data collected with this improved questionnaire are composed starting from a larger number of items and are better aligned with the theoretical perspective used, compared with the questionnaire developed in 2023 by Neștian and Guță. The items of the questionnaire loaded in the principal components can be used for relevant future studies on knowledge vulnerabilities. The resulting components offer a better picture regarding the conceptualization of the notion of vulnerabilities associated with knowledge processes.

Knowledge Sharing and Creation Through Seed Funding

Kristiina Brusila-Meltovaara — 2025-08-29

Even though international network building is increasingly recognized to be important for research, the use of seed funding as a means of building researchers’ collaboration networks prior to actual grand writing network building and knowledge sharing has not been addressed. Research is a knowledge creation and knowledge sharing activity. Networking can increase social capital and thus enhance research productivity of HEI’s. International research collaboration networks are important for knowledge production, research productivity, and enhancing innovation capabilities. The enhancement of innovation capabilities is also linked to the mission HEI’s have of collaborating and enhancing the local business community in Finland. Innovation capabilities can be seen as innovation drivers, which improve the competitive advantages of a company or specific region. A number of instruments are in place for pure academic networking; however, these differ from seed funding as seed funding in most cases also includes networking outside of academia, e.g., local SME’s. This research depicts different seed funding sources used to construct international funding application research networks and also highlights the challenges, which should be addressed when considering this approach. The research question the paper addresses is, how do we best utilize seed funding to enhance knowledge sharing. The paper uses a case study approach presenting a number of successful seed funding research collaboration cases led by LAB University of Applied Science, which have also led to successful research funding applications with international partners. The study highlights possible pitfalls and also challenges encountered during the seed funding research collaboration period. Conclusions as to best practices with regards to utilization of seed funding to enhance knowledge sharing and creation are also presented. The findings emphasize the importance of strategic planning and proactive engagement in building effective research networks.

The Impact of Vertical Trust on Knowledge Sharing Practices in Innovation Sector Companies

Felicjan Bylok — 2025-08-29

Modern enterprises functioning in conditions of international competition seek factors that support the increase in their market value. One of these is knowledge, which may be shared or exchanged in various forms by employees, managers or employee teams in an organization. Sharing necessary information and professional experience in an organization is essential in order to resolve problems with the aim of achieving innovative solutions. A factor which supports this process of sharing knowledge is that of trust, which has an influence on tightening interpersonal cooperation within employee groups and organizations with the aim of realizing common interests. The most significant entity creating trust in an organization is that of a manager who undertakes actions on behalf of building trust between employees and their superior. The acceptance of the assumption that a manager has an impact on the level of organizational trust facilitated the formulation of the aim of this paper, which is the identification of trust between employees and their head, while also its impact on the practice of sharing knowledge in enterprises of the innovative sector. The assumed aim was executed thanks to the application of the phone survey method with the CATI technique (Computer Assisted Telephone Interview). On the basis of the method of random sampling, a sample was created consisting of 575 employees in enterprises of the innovative sector. As a result of the research conducted, a statistically significant dependency was discovered between the indicators of vertical trust and sharing knowledge, while also experience on the part of employees in the analysed enterprises. The positive impact of trust on the process of accumulating knowledge and the frequency of sharing it have been indicated.

Rethinking the Future of Intellectual Capital: Emerging Perspectives in IC Theory and Practice

Slađana Čabrilo — 2025-08-29

Intellectual capital (IC) theory, emphasizing that the primary source of organizational value is derived from intangible, knowledge-based resources, has long been recognized as a critical driver of sustainable competitive advantage. However, as the business landscape continues to evolve in the face of technological, institutional and socio-political disruptions, and natural disturbances, it seems viable that the theories for understanding IC and practices for managing it should also be updated. This paper seeks to challenge and advance existing IC theory by presenting a forward-looking exploration of the evolving landscape of IC. We propose some critical theoretical and practical updates that can bridge the gap between conceptual advancements and real-world applications. By adopting an ecosystem-oriented approach, we highlight how IC operates across different levels of analysis- from individual to societal - and how multilevel, dynamic, and complex interactions within the IC ecosystem contribute to innovation, value creation, and sustainable development. The paper challenges traditional IC frameworks by emphasizing the fluid, interconnected nature of IC, arguing that a more holistic, dynamic model is essential for understanding and leveraging IC in today’s rapidly changing environment. Furthermore, we argue that future IC agendas must address broader concerns, including sustainability, IC ethics, IC diplomacy, fair and socially equitable distribution of value, and societal justice. Recognizing this progress in IC research and practice as essential for sustainable growth and social well-being in the coming era, we aim to contribute to a deeper understanding of emerging paradigms and to align IC theory and practice with future economic, technological and social transformations.

How Does AI-Driven Knowledge Management Enhance Sustainability of Startups? A Conceptual Framework

Furong Cai — 2025-08-29

In response to growing sustainability imperatives and environmental uncertainties, startups are increasingly expected to embed green values into their strategic and operational processes. However, their limited resources, organisational learning base, and process maturity often hinder their capacity to achieve sustainable competitive advantage. Drawing on an integrative review of the literature, the study conceptually examines how AI-driven knowledge management (KM) contributes to the sustainability of startups. Based on the Resource-Based View and Dynamic Capability Theory, this paper identifies and integrates six core constructs: Green Entrepreneurial Orientation (GEO), Green Knowledge Management (GKM), Dynamic Capabilities (DCs), Big Data Analytics and Artificial Intelligence (BDA-AI), and Sustainable Competitive Advantage (SCA). These constructs are synthesised into a conceptual model that explains the mechanisms through which green strategic intent and knowledge practices interact with digital enablers to foster sustainable advantage. The proposed model highlights three key pathways. First, GEO is positioned as a strategic antecedent that directly enhances GKM and SCA, indicating that a green entrepreneurial mindset can drive sustainability-oriented knowledge processes and competitive outcomes. Second, GKM enhances DCs, which in turn contributes to SCA, with DCs mediating the GKM-SCA relationship, reinforcing the role of dynamic adaptability in transforming knowledge into sustainable advantage. Third, BDA-AI is proposed as a moderator that strengthens the effects of GKM on DCs and DCs on SCA by accelerating sensing, learning, and reconfiguration processes, particularly in uncertain and resource-constrained environments. Building upon these interrelationships, eight hypotheses are developed to construct the conceptual framework and provide a basis for future empirical validation. This study advances the theoretical discourse on sustainable entrepreneurship by integrating sustainability, KM, and AI perspectives. It offers practical insights for startups and policymakers seeking to leverage digital technologies for long-term viability. While conceptual, the proposed model provides a foundation for empirical validation and future refinements to account for contextual dynamics such as industry-specific challenges and policy influences.

A Systematic Literature Review on GenAI Through the Lens of Corporate Sustainability

Giuseppe Liccardo — 2025-08-29

Generative artificial intelligence (GenAI) is a subset of AI capable of autonomously producing new content in the form of text, audio, video and code based on previously learned data patterns. As modern organizations face increasing pressure to align with environmental, social, and governance (ESG) objectives, GenAI, due to its enormous potential is reshaping organizational processes, presents an unprecedented opportunity for fostering sustainable practices related knowledge. In this context, this study aims to critically review the existing literature on the topic with the aim of analysing its potential to support social responsibility. Specifically, this Systematic Literature Review (SLR) examines the intersection of GenAI, Knowledge management (KM), and sustainability, emphasizing the role of Green Knowledge Management (GKM), a framework that integrates environmentally conscious knowledge practices into corporate strategy. Through an extensive review of peer-reviewed articles, four key thematic areas emerge: (1) sector-specific application of GenAI for sustainability, (2) Ethical and regulatory concerns on GenAI implementation, (3) GenAI in promoting organizational knowledge and innovation and (4) The role GenAI in corporate social responsibility (CSR). The result of the review indicate that GenAI is increasingly emerging as a catalyst for sustainability. Its role in promoting green innovation and its capacity to facilitate the exchange of knowledge regarding sustainable practices provide crucial support for firms pursuing ESG compliance. Despite these benefits, considerable concerns remain, especially regarding the ethical use of GenAI. This study contributes to the ongoing discussion on the role of GenAI as key enablers of sustainability. By providing a systematization of the research domain, it not only provides a comprehensive understanding of its current applications but also indicates present gaps and opportunities. In addition, it outlines future directions and serves as foundation for further empirical research on the use of GenAI to promote responsible corporate practices.

AI-Driven Generation of Key Intelligence Topics and Questions: Enhancing the Work of CI Professionals

Jan Černý — 2025-08-29

Competitive Intelligence (CI) is a critically important instrument for monitoring an organization's external
environment, providing management with unique insights into markets, competitors, trends, and other entities influencing
the organization's strategic position. Simultaneously, it serves as an effective tool for mitigating risks by identifying and
interpreting early signals from the competitive landscape, while also uncovering opportunities for capturing competitive
advantages. Recent developments in artificial intelligence (AI), particularly the emergence of Large Language Models (LLMs),
have opened new possibilities for enhancing Competitive Intelligence (CI) processes. This paper explores the potential of
LLMs in addressing specific CI tasks through CI-oriented prompt design. The study specifically focuses on the planning phase,
demonstrating how LLMs can support the identification and formulation of Key Intelligence Topics (KITs) and Key Intelligence
Questions (KIQs). In addition, the paper discusses the application of LLMs in the data collection phase, emphasizing their role
in identifying relevant sources aligned with the direction of the KIQs. The implications of integrating LLMs into CI are
substantial; however, this implementation must be approached cautiously to ensure accuracy, reliability, and ethical
compliance emphasizing the need for thorough validation and human oversight.

Unlocking the Business Value of Dark Data: The Importance of Data Governance

Graham Chant — 2025-08-29

Hidden amongst data is dark data; unstructured, unanalysed and typically unused data. Dark data is a complex phenomenon as it is typically difficult to access, lacks meaning without human interpretation, yet could add value and benefit to an organisation. Alternatively, a risk of not activating dark data for an organisation could be inaccurate data used for decision making. Dark data provides the opportunity for building knowledge and in turn, can provide a competitive advantage. Whilst awareness of the value of dark data is increasing, accessing and effectively using this data is not straightforward. Dark data engagement brings with it challenges of how to access this data, how to convert this data for it to be usable and who will be accountable to ensure appropriate use of such data. This paper argues that data governance will be necessary to unlock dark data, control the conversion of dark data to usable data and manage appropriate use of such data. This paper also argues that not unlocking dark data may mean business decision-making may be at risk of not having an accurate base to inform decisions. Appropriate use of dark data aims to maximize benefits for a competitive company, but these organizations will need data governance to control and manage how this data is used. This paper will examine data governance to reduce risks associated with dark data, ensure security and integrity of all data, protect data from misuse, and improve dark data processing.

The Role of Doctors During Apprenticeships and Medical Residents in Knowledge Transfer in Teaching Hospitals

Jolanta Chluska — 2025-08-29

In the era of the knowledge economy, knowledge is the most important asset of an organization. Teaching hospitals are medical entities that provide healthcare services to patients. The specialized medical staff not only provides medical care, but also educates future healthcare professionals, while also conducts clinical research and supports the advancement of medical technologies. Knowledge transfer in teaching hospitals is essential to their growth and serves as a key operational goal. Future healthcare professionals undertaking apprenticeships and placements in teaching hospitals not only contribute to knowledge transfer, but also play a strategic role in addressing current and future challenges facing the healthcare system. The aim of this paper is to identify knowledge-sharing processes within teaching hospitals as part of the medical staff education system. The following research question was posed: Is the education of doctors during apprenticeships and residents an element of the knowledge transfer strategies of teaching hospitals? The analyses indicate that the training of doctors during apprenticeships and residency is central to the mission and strategy of teaching hospitals, particularly in terms of knowledge transfer and the development of intellectual capital. The analyses are professional by nature, conducted from the perspective of a certified auditor and long-term researcher of the operational challenges of hospitals as healthcare institutions.The reflections presented in this paper offer an important perspective on the conditions required for the development of teaching hospitals as institutions with intellectual capital capable of addressing global health challenges. The paper continues the author's previous research on the development of intellectual capital among staff in Polish teaching hospitals.

Sharing is Where the Heart is: A Mediation-Moderation Model of Trust and Generosity Influence on Knowledge Sharing in NPOs

Carla Curado — 2025-08-29

Knowledge sharing plays a crucial role in the success of organizations, including those relying on the goodwill of their social actors, such as nonprofit organizations (NPOs). While knowledge-based management practices have been adopted in various types of NPOs, research still lacks a comprehensive understanding of the factors driving knowledge sharing, particularly the role of prosocial motivations. Trust, generosity, and team cohesion are recognized as key determinants of knowledge-sharing behavior, yet their interactions and combined effects in NPOs remain insufficiently explored. Following a research design grounded in Social Exchange Theory, this work examines how trust, generosity, and team cohesion contribute to knowledge sharing within Portuguese NPOs using a mediation-moderation model approach. Using survey data and structural equation modelling, we investigate how generosity and team cohesion mediate and moderate the relationship between trust and knowledge sharing. Our findings indicate that trust has a strong, positive impact on generosity and team cohesion, reinforcing its foundational role in knowledge-sharing dynamics. Furthermore, both generosity and team cohesion are positively associated with knowledge sharing. Notably, team cohesion plays a dual role by mediating and moderating the relationship between trust and knowledge sharing, amplifying its effects. Generosity, however, exhibits a more complex influence, serving as a positive mediator while also acting as a negative moderator in this relationship. These results highlight the nuanced interplay between trust, generosity, and team cohesion in shaping knowledge-sharing behaviors within NPOs. By uncovering such dynamics, this study contributes with valuable insights for both scholars and nonprofit managers, offering a deeper understanding of the mechanisms that foster effective knowledge-sharing environments in NPOs. The findings emphasize the importance of cultivating trust and team cohesion while managing the dual effects of generosity to optimize knowledge-sharing practices in nonprofit organizations. Our results show trust, team cohesion and generosity influencing KS in NPOs as not seen before, however, the present study is not free from limitations, such as the sample size, and the elimination of some variable items throughout the statistical analysis phase. We are aware that results apply to the specific context of Portuguese NPOs, therefore we invite colleagues to replicate the model in other geographies and, thus, test for national culture effects.

Enhancing Knowledge Management and Strategic Foresight through Information and Communication Technologies

Gustavo de Oliveira — 2025-08-29

Knowledge Management (KM) and Strategic Foresight (SF) are essential for organizational growth, particularly in today’s environment shaped by Information and Communication Technologies (ICT). This study conducts a literature review to investigate the effective integration of KM and SF practices with ICT. It addresses two key research questions: How can KM practices be incorporated into SF processes? How can ICT enhance the management of future-oriented knowledge through SF? The increasing complexity of organizational environments and the challenges posed by information overload and future scenario forecasting highlight the importance of this research. ICT serves as a crucial enabler, utilizing tools such as Big Data analytics, Artificial Intelligence (AI), and the Internet of Things (IoT) to optimize KM and SF practices. However, the integration of these technologies encounters significant barriers that require further exploration. The primary objective of this study is to map the current integration of ICT within KM and SF, emphasizing opportunities, limitations, and the potential contributions of AI to these processes. Utilizing a Rapid Review methodology, which streamlines the systematic review process to provide timely insights, the research involved searches in the Scopus database and a snowballing technique, resulting in an analysis of 12 selected articles. Findings indicate that ICT can significantly improve the efficiency and effectiveness of KM and SF processes, particularly in scenario-building and strategic decision-making. The study identifies specific tools and methods, such as collective knowledge systems and IoT frameworks, that organizations can adopt to enhance these practices. Future research should expand on this groundwork by including larger samples and practical studies to validate the proposed hypotheses. This study aims to encourage organizations to adopt ICT-based solutions, fostering sustainable competitive advantages in dynamic business environments.

AI for Knowledge-Driven Business Decisions: Capabilities and Constraints

Ettore Bolisani — 2025-08-29

This paper presents experimental research evaluating the capability of generative artificial intelligence (GenAI) chatbots to assist business executives in their decision-making processes. With the growing prominence of large language models such as ChatGPT and Perplexity, there is significant interest in their potential for knowledge management (KM) and decision support, but empirical evidence is still lacking. This study conducted over 210 experiments using approximately 900 prompts to assess the performance of ChatGPT and Perplexity across various business decision tasks, including marketing analysis, work shift optimization, sentiment analysis, review of company financial and strategic documentation, and product marketing evaluation. The outputs generated by the chatbots were compared with traditional decision support methods, human expert analysis, and benchmarking data. The results indicate that GenAI chatbots can streamline processes by collecting, interpreting, and synthesizing data into actionable insights. Nevertheless, limitations were identified in handling complex file formats, response variability based on context framing, and the necessity for human validation of outputs. A comparative analysis of ChatGPT and Perplexity revealed distinct differences: ChatGPT demonstrated overall reliability but struggled with tabular data, whereas Perplexity provided more substantive yet occasionally less accurate responses. The findings suggest that GenAI chatbots could enhance decision efficiency through rapid analysis, but a collaborative human-AI model remains advisable to validate outputs and iteratively refine queries. Our study underscores the potential of GenAI for KM in guiding decisions while highlighting the need for further research on evaluation methods, integration with business intelligence tools, and the development of user guidelines for the responsible adoption of this technology.

Knowledge Audit in HEIs: A Framework for its Strategic Management

Ana Diez-Gaviria — 2025-08-29

In the Knowledge Era, Higher Education Institutions (HEIs) are recognized as knowledge-intensive organizations whose sustainability and capacity for transformation depend largely on how they manage not only academic and scientific knowledge but also the organizational knowledge that emerges from their internal practices. However, most HEIs focus their efforts on knowledge derived from teaching and research functions, leaving aside the strategic management of the knowledge produced, stored, and applied in administrative, operational, and relational domains. This disconnection limits the potential of organizational knowledge as a source of differentiation, innovation, and dynamic capabilities. This article proposes a systemic approach to knowledge audits in HEIs, aimed at closing the gap between academic and organizational knowledge. The study follows a qualitative and propositional methodology structured in three phases: a critical literature review, an empirical analysis of eight cases from knowledge-intensive organizations, and the design of a strategic management framework for systemic knowledge audits. The framework includes seven interconnected components: (1) characterization of knowledge in relation to institutional strategy; (2) multi-level inventory of core, tactical, operational, and relational knowledge; (3) diagnosis of risks such as leakage, obsolescence, and knowledge gaps; (4) development of knowledge and risk maps; (5) governance structures for knowledge management; (6) design of intervention routes; and (7) monitoring, evaluation, and continuous improvement. From a systemic and sociomaterial perspective, organizational knowledge is understood as an emergent, distributed, and dynamic configuration shaped by practices, technologies, and structures (Schatzki, 2016; Tsoukas, 2000). Accordingly, knowledge audits are conceived not only as diagnostic tools but also as organizational interventions (Czarniawska, 2003) that enable institutions to make sense of their own knowledge, identify critical areas, and design transformation strategies. The findings contribute to the construction of an integrated model that positions organizational knowledge as a key driver of sustainability, innovation, and strategic alignment in HEIs (Nonaka, Toyama and Hirata, 2018) (Probst, Raub and Romhardt, 2001) (Teece, 2007).

Knowledge Management and COVID-19: A Review of the Literature and Implications for Practice

Nasser Fathi Easa — 2025-08-29

Knowledge Management (KM) was an essential strategic resource during the Covid-19 crisis. KM has been crucial in guiding organizations to make strategic decisions on behalf of individuals. This paper aims to review the research on KM and COVID-19. Based on an empirical systematic review of research conducted, content analysis has been conducted for several peer-reviewed articles in the English language. Research findings, implications, and future research agenda are presented. The results indicate that deploying appropriate KM models and managing knowledge relevant to the COVID-19 epidemic enhances effective decision-making and enables crisis management. The findings stress the importance of using enterprise social networking (ESN) systems in times of crisis, especially during face-to-face restrictions

How Do Consumers Perceive the Benefits for Businesses Arising from Their Active Involvement in Business Activities and Projects?

Monika Eisenbardt — 2025-08-29

Consumer collaboration with businesses has become increasingly prevalent, with consumers being actively involved in various projects aimed at providing their ideas, opinions, and knowledge. These collaborations often leverage digital technologies and occur without formal contractual agreements. While the benefits for consumers are well-documented, the advantages for businesses remain underexplored. This paper presents a study on the benefits businesses gain from the active involvement of consumers in business activities and projects, focusing on consumer perceptions. Using a model of business benefits derived from a systematic literature review, the study categorizes these benefits into four main groups: product-related, reputational, economic and social, and technological and informational benefits. The research, based on 375 consumer surveys, reveals that consumers most strongly associate their involvement with reputational benefits, such as a better understanding of customer needs, more effective promotional activities, and improved customer relationships. Product-related benefits, such as product personalization and tailoring offerings to consumer needs, were also identified as highly valuable. Additionally, technological and informational benefits, including access to emerging market trends and enhanced digital engagement, were seen as critical for driving innovation within companies. However, economic and social benefits, such as risk minimization and the establishment of new distribution channels, were perceived as less impactful by consumers. These findings offer valuable insights for businesses looking to harness consumer knowledge effectively, emphasizing the importance of leveraging consumer input to enhance brand reputation, product offerings, and technological advancements, while also considering potential risks and limitations.

Exploring Alternative Approaches to Contemporary AI Testing

Tomasz Eisenbardt — 2025-08-29

While the first artificial intelligence test proposed by A. Turing has a long-standing tradition, it is no longer sufficient to meet today's challenges. There is now a strong need for more multi-contextual testing and comparison of AI solutions. Among other things, the emergence of the new Chinese language model, DeepSeek—designed to compete with Western solutions such as ChatGPT, Copilot, and Gemini—has caused quite a stir. It has not only influenced financial markets but also ignited a broader discussion about the quality of contemporary AI systems. As a result, there is a growing need to systematically test and compare these tools. The aim of this paper is to present an original attempt to identify and systematize contemporary approaches to AI testing. The discussion is framed by a reference to the Turing Test and its relevance in the modern context. The author seeks to identify common features between software testing, human intelligence testing, and AI testing. Subsequently, based on a critical analysis of relevant literature and other available sources, the paper outlines and organizes the types of tests currently in use. The conducted considerations allowed for the identification of three trends in contemporary AI testing: tests imitating or referring to human intelligence testing, tests analogous to approaches used in software engineering, and tests based on parameters.

Project Execution Models and Knowledge Management

Anandasivakumar Ekambaram — 2025-08-29

Projects are one-time activities that are aimed at achieving a particular objective within limited time and limited resources. Though projects are per definition unique, they also have known elements, such as known methods, approaches and solutions. Hence, projects are considered as learning arenas where new knowledge is developed (knowledge exploration), and existing knowledge is shared with other members of the projects (knowledge exploitation). Several measures are taken to ensure effective and efficient execution of projects. One such measure is to use project execution models. These models provide guidelines for project managers to conduct their projects effectively. They are developed based on the best practices and lessons learned over a period of time. They give a standard way of conducting projects in organizations. In this regard, it is interesting to look at project execution models with respect to knowledge management. This paper describes the connection between the application of project execution models and knowledge management by looking at concepts / theories that are related to knowledge sharing and learning. It also takes into consideration the topics of organizational structure and organizational culture to discuss the use of project execution models. Information about project execution models that are used in two municipalities in Norway serves as a background for this paper. Qualitative research method was applied in this study. Interviews were conducted to collect data. In addition to the interviews, document study was carried out to obtain more detail about the project execution models that are used in the municipalities. The study on which this paper is based, is connected to a pre-project that is financed by Project Norway. Project Norway is a national competence center for the development of future project processes through research and knowledge sharing.

Application of Knowledge Discovery in Databases to Determine Car Sales Trends in Türkiye

Orkun Eker — 2025-08-29

In today's world, organizations of all sizes, including companies, institutions, and governments, manage vast amounts of data. Organizations that effectively harness data and extract valuable insights can achieve their strategic objectives. This study exemplifies the application of data mining techniques by analyzing the trend of vehicle sales. It highlights the significance of data mining in the automotive sector and demonstrates how accurate and meaningful results can be produced.

Categorisation of Tacit and Explicit Knowledge and Its Implications for Organisational Growth in Higher Education Institutions

Rexwhite Tega Enakrire — 2025-08-29

In this paper, we report on the categorisation of tacit and explicit knowledge and its implications for organisational growth in higher education institutions (HEIs), which are known as universities. We note that the two types of knowledge- tacit, which resides in a person's mind is acquired through personal experience over time, and explicit, found in manuals and documents- have become increasingly vital for organisational growth, particularly in universities, from the perspectives of operational effectiveness and the sustainability of lecturers' roles. Unfortunately, not all lecturers, students, and staff members in universities are familiar with categorising these two types of knowledge and the implications this knowledge portrays for organisational growth. Two research objectives guided this study: first, to examine how the two types of knowledge can be categorised for better application in universities, and second, to determine which of the two categorised types plays a key role in universities. A quantitative research method of PRISMA and interpretive content analysis was used in this study, wherein the authors examined and synthesised literature on tacit and explicit knowledge sourced from Scopus and Google Scholar databases. The findings revealed that the two types of knowledge were categorised based on their distinct functionalities in universities. The study indicates that lecturers now mix tacit and explicit knowledge for creating lecture notes and modules from diverse reading materials, assessing student submissions, delivering lectures in class, and conceptualising and drafting research papers. Tacit knowledge is more advantageous since much of what occurs in universities relates to lecturers' intuitive knowledge application in teaching, learning, and research, as well as in supporting students. Nevertheless, integrating both enables lecturers to develop, reflect, and gain a comprehensive understanding of their teaching and research practices. To foster engaging dialogue and continued participation in universities, the study suggests enhancing awareness of the various types of knowledge among lecturers and scholars, considering their diverse backgrounds.

Predictive Analytics: Digital Metrics for Estimating Knowledge Assets

Scott Erickson — 2025-08-29

Digitization, big data, and follow-on metrics have burgeoned over the last couple of decades. While the knowledge management (KM) community has embraced some of the advances in data-driven decision-making in business, there remain new applications that are relatively unexplored. One of these applications is the use of digital metrics to estimate knowledge holdings or intellectual capital (IC). In a discipline still at the mercy of troublesome metrics, new opportunities to better measure IC would fill a large gap in the existing body of knowledge. Previous work, across several industries and well-known brands, established digital media variables of interest such as volume of mentions, variability of mentions, influencer quality, brand sentiment, and some more platform-specific (X, Facebook, etc.) measures (Erickson, 2023; Erickson & Rothberg, 2023; Erickson, Schmidt & Rothberg, 2020). These indicators were compared with brand equity from a separate source and methodology, establishing apparent links. In short, certain digital media variables seemed related to higher brand equity, a proxy for the intellectual capital component of relational capital. More recent research explored the statistical link between digital metrics and brand equity (relational capital) (Erickson & Rothberg, 2024). On a very small sample, key indicators were shown to predict brand equity values at a very high correlation using different approaches (regression, neural network). This study continues that work, with a larger set of firms. The firms are drawn from two industries, autos and information technology, both of which have a number of companies with available brand equity estimates. Moreover, the study adds price/book value ratios, calculated on an annual basis (like brand equity) but which can also be easily estimated for shorter time periods by altering share price. As a result, in estimating correlation, periodic digital media independent variables can be compared not only with annual brand equity metrics but with matching periodic price/book ratios. Price/book is an effective proxy for not just relational capital but all intellectual capital of the firm, providing a different approach from a new perspective.

Perceived Factors of Trustworthiness in Generative Artificial Intelligence (GenAI): Towards an Understanding of how to Assess and Build Trustworthiness

Max Evans — 2025-08-29

Given the benefits and risks associated with GenAI adoption in organizations, many academics and practitioners have stressed the importance of understanding how humans come to trust these technologies and the information and knowledge (e.g., solutions/decisions) they produce. The objective of this paper is to further examine human trust in AI technologies through the lens of a widely accepted organizational trust theory and model developed by Mayer, Davis, and Schoorman. More specifically, this paper focuses on developing a better understanding of perceived factors of GenAI trustworthiness since assessing trustworthiness is a critical determinant of trust. Building on the existing theory and model, it is proposed that an individual's perception of one or more of the following dimensions of trustworthiness - ability, integrity, and benevolence - will determine how trustworthy they find GenAI to be. Ability (or competence) refers to the trustee’s specific skills, knowledge, and expertise required in a specific domain. Integrity reflects the trustee’s sound values or principles (e.g., fairness, consistency, justice). Benevolence is an altruistic loyalty that reflects the trustee’s concern for the welfare, needs, desires, and interests of the individual over organizational or profit motives. Many researchers have proposed assessments related to GenAI ability, but integrity and benevolence are more difficult to assess, as technologies do not intrinsically embody human values or altruistic behaviors. Consequently, other parties within the organizations, such as AI designers and developers, strategic decision-makers, or the organization may be conflated into perceptions of these dimensions. The paper continues by briefly discussing how emotions and organizational culture may influence individuals' perceptions of trustworthiness and concludes by suggesting potential directions and strategies for building and representing each dimension of perceived trustworthiness in the context of GenAI.

A Systematic Literature Review on Intergenerational Tacit Knowledge Transfer: A KPI Perspective

Bettina Falckenthal — 2025-08-29

Organizations often have several generations working with them at the same time. Without an effective strategy experienced workers of older generations will leave the organizations taking with them a precious amount of relevant knowledge and skills. What do organizations currently do to support tacit knowledge transfer from Seniors to Juniors? Which formats have been proven to be especially successful? What Key Performance Indicators (KPI) could be used to evaluate cost and benefit of Tacit Knowledge Transfer across generations? Decision-makers faced with a potentially critical amount of tacit knowledge loss due to retiring senior experts are applying different solutions and strategies to overcome this problem, while encountering the challenge to measure and quantify the outcomes. Our research revealed that a gap exists regarding the balancing of the investment and compelling business cases for transferring tacit knowledge from senior to junior employees. We offer Key Performance Indicators (KPIs) with financial and social perspectives that may be applied to guide the enterprise. To achieve this, we conducted a thorough analysis and literature review to evaluate the business cases behind different formats of intergenerational knowledge transfer. Various studies have looked at the methodology behind intergenerational knowledge transfer: we analyzed publications that approach this matter from an organizational perspective including the start-up and Business Angel environment and a further stream of publications that look at the perspective of the individuals involved. Even though organizations are increasingly creative and willing to keep senior experts on board beyond legal retirement age the cost/benefit question is difficult to answer. The analyzed literature regarding Serious Games as one format for intergenerational tacit knowledge transfer was often based on small sample groups or specific needs of an organization or industry. The authors writing about Serious Games agreed that transferability was limited. Their contributions are nonetheless significant as the data collected in pilot projects is invaluable in any decision-taking process for potentially larger scale operations. Based on the current need to balance spending and ensure knowledge continuity our study contributes with novel KPIs and success factors for intergenerational knowledge transfer that can help decision makers in building a business case and steering their investments. The KPIs depend on desired outcomes such as Interpersonal Trust and Increased Efficiency – and therefore we see KPIs such as Quality of Relationships and Skill Improvement Score. KPIs also depend on Expected Investments such as Buying Lost Knowledge (e.g., involving rehiring retirees, or external consultants).

The Impact Of An Inclusive Leadership Style On Generation Z's Willingness To Share Knowledge

Joanna Gajda — 2025-08-29

In the knowledge-based economy, inclusive leadership strengthens employees' sense of belonging and psychological safety. Generation Z brings new values and expectations regarding managerial leadership styles, influencing their willingness to share knowledge. This article aims to examine the impact of inclusive leadership on Generation Z’s propensity to share knowledge, considering demographic and organizational variables as well as the level of organizational identification, which plays a key role as a factor enhancing employee engagement and willingness to share knowledge in the workplace. Spearman’s rank correlation test was applied to data from 318 anonymous online surveys conducted within Polish organizations. Statistical analyses were performed using Statistica 13.3 (StatSoft). The results revealed a positive impact of inclusive leadership on knowledge sharing, with stronger effects observed among women than men. Tenure and company size influenced perceptions of leadership. Organizational identification, particularly pride and sense of influence, enhanced the propensity to exchange knowledge. The findings confirm that inclusive leadership and strong organizational identification promote knowledge sharing among Generation Z employees in Polish organizations. They also highlight the importance of considering demographic and organizational variables such as gender, tenure, and company size, which moderate these relationships. This knowledge can assist leaders in creating environments conducive to open communication and knowledge exchange, crucial for the development of knowledge-based organizations.

Exploring Knowledge Management Approaches to Enhance Documentation Management within the AI realms

Dilyan Georgiev — 2025-08-29

Artificial intelligence (AI) technologies have an increasing impact on companies' digital transformation. On the one hand, it is expected that AI tools can support process automation and quality improvement, on the other hand, many professionals fear that AI systems will displace their roles. It is assumed that paperwork processes and workflow documentation are among the most tedious tasks for employees. However, proper workflow documentation is the backbone of effective company knowledge management (KM) and decision-making. In contrast with traditional documentation management systems (DMS) that struggle with retrieval, accessibility, and workflow automation, KM challenges hinder documenting and sharing insights gained during projects, with knowledge often hidden or lost post-project. Overcoming these barriers requires AI-driven systems to contextualize and structure unstructured knowledge for better inter-project collaboration and retention. By investigating KM approaches, the present research aims to identify and model the key features that will support job augmentation with intelligent document management processing. The study steps on the Automated Documentation Management System (ADMS) with an integrated ChatGPT-based assistant, which enables users to interact with documents through conversational queries, analysis, retrieval, and summarization requests. The first part of the paper explores KM approaches related to workflow documentation and project management. Next, a short overview presents the ADMS system functionalities for improving contextual understanding of the complex processes, data integration, and knowledge sharing. Based on this, a new application model is identified, supporting KM job augmentation. At the end, the discussion explores how advanced DMSs can support KM processes in companies to enhance quality, efficiency, and job augmentation, improving decision-making, collaboration in project management. By enabling seamless knowledge sharing, it preserves insights beyond project lifecycles, supporting future initiatives. As projects grow more complex and data-driven, AI integration in PM can transform how teams capture, share, and apply knowledge for sustained success.

Technologies as KM Tool for Sustainability in Hospitality: Practitioners Perspective

Jagoda Goll-Stefańska — 2025-08-29

This study explores how hospitality businesses leverage technologies as Knowledge Management (KM) tools to enhance sustainable performance in this sector. By integrating artificial intelligence (AI) and other emerging technological solutions, businesses can mitigate negative environmental impacts, improve employee working conditions, and reduce operational costs. The study highlights the strategic role of technology in facilitating knowledge creation, sharing, and application to drive sustainability in the hospitality sector. The research is based on a narrative analysis of qualitative secondary data obtained from the Hospitality Technology Network and expert panel discussions at a leading industry conference in Poland, focusing on automation and technological advancements in the hospitality sector. The results indicate that AI and other technological innovations serve as effective KM tools, enabling hospitality businesses to achieve economic, social, and environmental benefits. Practitioners view these technologies as critical enablers of sustainable development, process optimization, and long-term competitive advantage. The study underscores the role of technology in transforming knowledge into actionable insights and facilitating sustainable business practices. This paper provides insights into the adoption and effective use of sustainable technologies, particularly for small and medium-sized hospitality enterprises (SMEs). By examining practitioners' experiences with KM-driven technological solutions, the study offers practical recommendations for hospitality managers seeking to enhance sustainability. The findings can serve as a knowledge base for SMEs aiming to integrate technology into their sustainability strategies. This research contributes to the discourse on KM and sustainability in the hospitality industry by identifying specific technologies and systems used by practitioners. By emphasizing the intersection of technology, KM, and sustainable business practices, the study offers a novel perspective on the digital transformation of hospitality businesses. The insights presented provide a foundation for further research and practical applications in the field of sustainable knowledge management.

Leveraging Experience-Based Knowledge for Social Impact Analysis of Research and Development Projects in Banking

Tadeusz A. Grzeszczyk — 2025-08-29

Banking projects are diverse and go beyond classic financial products and include advanced customer service tools, analytics, and AI. Large financial institutions are leaders of technological change, increasingly creating internal innovation labs that independently conduct research and development work using specialized teams, which helps them achieve a positive social impact and build a sustainable and stable competitive advantage in the long term, thanks to the rapid adaptation of solutions to changing market requirements. The issues relating to social impact analysis and assessment of R&D projects in banking are new, and a research gap can be noticed in this field. Publications on implementing such projects are mainly focused on their products and the time of delivering innovations to the market, not on the methods of managing project knowledge necessary for social impact analysis processes. There is, therefore, a need to build theoretical and methodological foundations for improving management processes and using experience-based knowledge in this area. This paper aims to propose a model inspired by case-based reasoning (CBR) and generative AI. The model can be helpful in supporting the solution of decision-making problems using historical knowledge, as well as considering the current specificity of projects and their environment. The presentation of the model is supplemented with examples concerning the social impact analysis of R&D projects in the banking sector, which prove that its use can improve the use of experience from such projects.

Artificial Intelligence for Adaptive Planning of Healthcare Projects

Tadeusz A. Grzeszczyk — 2025-08-29

Planning and managing healthcare projects involves making decisions in conditions of high uncertainty due to a complex and turbulent environment, technological transformation, and the use of largely subjective resources of tacit knowledge possessed by project managers as a result of accumulated years of experience. It is desirable to look for solutions that allow for the creation of flexible and agile systems supporting the management of updated knowledge resources, enabling dynamic adaptation to current problems and changing environmental conditions. One possible solution is using intelligent systems that would support adaptive planning. The paper aims to present an AI model for knowledge management in adaptive planning of healthcare projects, which are usually complex, expensive, and require efficiently updated interdisciplinary scientific knowledge. Additionally, such projects often only have generally formulated goals and planned results, which makes their definition, planning, and initial evaluation much more difficult. Thanks to the conclusions drawn from this research, it is possible to reduce the number of errors made during project planning, which usually significantly affect the implementation and success of projects. It is justified to develop interdisciplinary research conducted on the border of healthcare project planning and AI computing systems because expert planning methods dominate, and there is a lack of adequate support. Implementing this type of research and its further continuation allows for the creation of knowledge and methodological solutions related to introducing AI computation to healthcare projects to assist agile decision-making.

Analyzing the Societal Impact of Academic Research Using Fuzzy Inference Models

Tadeusz A. Grzeszczyk — 2025-08-29

Improving universities’ social impact is a significant problem in the higher education sector, which can be solved by appropriately shaping public policies, strategies of individual scientific organizations, and academic practices. Effectively conducting social impact analyses can support improving organizations’ functioning mechanisms and individual academics’ impact practices. These analyses can use data analysis methods and systems that are helpful for better understanding the positive or negative effects of decisions regarding selecting organizational impact strategies. The study of social impact and interactions between scientific organizations and their stakeholders is multifaceted and complex. Therefore, it requires the use of interdisciplinary approaches and sophisticated knowledge-based models. It is worth paying attention to fuzzy logic, which is useful in building such models and developing research on their application to support knowledge management necessary for conducting comprehensive analyses of the social impact of various scientific organizations. This is justified by the need to learn about the mechanisms of functioning systems of relations between scientific organizations and their stakeholders, as well as the types of influence occurring and knowledge exchange during the implemented interaction processes. The pace of changes in the scientific community environment forces an increase in openness for introducing analysis models adequate for the dynamic progress in developing new computational technologies. The main goal of this paper is to create a fuzzy inference model that helps support knowledge management for ongoing analysis and assessment of the social impact of research. The presented theoretical considerations, relating to the construction of the proposed model, are supplemented with a proposal for its implementation, which may later facilitate extensive verification studies based on empirical data. The obtained preliminary research results allow for the formulation of fundamental limitations, the overcoming of which creates a reasonable basis for further development of research on subsequent models of the analysis of social impact.

Effective Knowledge Creation and Transfer in e-Learning Using SECI Model

Alina Guzik — 2025-08-29

With the growing use of e-learning in corporate environments, it is increasingly important to evaluate its role in supporting effective knowledge management. E-learning has become an increasingly influential tool for organizational development and knowledge management (KM). While traditionally used for employee training, its role has expanded to include supporting the creation, sharing, and internalization of knowledge. This paper explores the potential and limitations of e-learning in facilitating knowledge creation and transfer using the SECI model, a foundational framework in KM theory. Although widely applied in traditional environments, the adaptation of the SECI model to e-learning contexts remains underexplored. To address this gap, we conducted a qualitative, exploratory study involving experienced e-course designers from the Gdańsk University of Technology, aiming to identify how each phase of the model can be effectively implemented in digital learning environments. Our findings indicate that each phase demands distinct strategies, tools, and pedagogical approaches. In the Socialization phase, “learning by interacting” is crucial, yet the lack of spontaneous dialogue in online environments poses a significant barrier. Effective strategies include designing informal communication spaces, implementing structured peer interactions, and building psychological safety. The Externalization phase, or “learning by exchanging,” requires structured environments where learners can articulate tacit knowledge. Challenges such as low motivation and trust issues can be mitigated through incentives, peer-to-peer learning, and content validation functionalities. The Combination phase, characterized by “learning by creating,” focuses on synthesizing explicit knowledge through collaborative tasks. However, evaluating creativity and ensuring equal participation remain problematic in large-scale e-learning. Solutions include AI-assisted assessment, collaborative platforms with contribution tracking, and milestone-based project work. In the Internalization phase, “learning by doing” is essential for converting explicit knowledge into tacit. This requires practice-oriented activities such as simulations, case studies, and prototype development. Barriers like limited personalized feedback and high implementation costs can be addressed through peer review, AI-based feedback systems, and ready-made simulations. A key insight from this research is that the primary barrier to applying the SECI model in e-learning is not technological, but rather a lack of instructional design expertise. While technology plays a supportive role, the success of knowledge processes depends largely on thoughtful, pedagogically informed course design. The study emphasizes that e-learning should be seen not merely as a content delivery tool but as a dynamic environment for organizational learning and innovation. This paper offers both theoretical and practical contributions. It extends the application of the SECI model to online learning environments and provides a structured framework for instructional designers, HR professionals, and corporate trainers aiming to enhance KM through e-learning. It also outlines practical tools, challenges, and design strategies for each SECI phase. While the study is exploratory in nature and based on a limited sample, it lays the foundation for future research into integrating KM theory with digital education, particularly in the context of emerging technologies such as artificial intelligence.

The Magic of One-Day Music Camps: How Reproduce the Magic in Academia?

Tone Vold — 2025-08-29

Music camps are intensive one-day seminars where students are tasked with creating lyrics, composing melodies, and producing a song within 11 hours. This experience is demanding for both the students and the faculty. Faculty members must be experienced and adept at monitoring the progress of the various groups, providing different inputs based on each group's advancement. The music camps follow a sequence of activities designed to facilitate song development and production within the given time frame. Over three years of longitudinal study on the music camp practice during the first year of the Bachelor program in Music Business and Production at the Business School of the University of Inland Norway, students have unanimously agreed that it is a highly effective learning experience. Is this possible to utilize in other parts of academia? What needs to be considered if this approach is to be successfully implemented? Hence, how can this approach be applied to other courses and curricula? In this paper we explore the possibilities and seek to suggest some possible solutions for successful integration it into different curricula.

Knowledge Sharing in an Academic Institution: A Case Study on Joint Course Evaluation

Tone Vold — 2025-08-29

There is an increasing demand in academia for working more effectively. As budgets are tighter and lecturers struggle to find time for all administration tied to each course, we need to work differently, but without losing opportunities of sharing knowledge amongst the lecturers that make up the community of practice that represents a study program. One way of sharing knowledge and to help strengthen the community feeling amongst the lecturers on a study program, is to join forces regarding course evaluations. Often courses can be viewed as connected, particularly within the same study program. Hence, to save time for the students and for faculty staff, it is thus possible to organize for a joint evaluation form. In this paper we will present the students’ and the lecturers’ feedback on using a joint evaluation form that comprises evaluation for two courses within the same study program for two different study programs; “Organization, leadership and digitalization” and “Knowledge Management”, both part time study programs, but with a rather high number of students (approximately 250 and 90). We will investigate how this affects the knowledge sharing amongst colleagues lecturing at the same study program. Our qualitative research approach has consisted of observations and group interviews. One of the most interesting findings was that the students got an improved understanding of the connection between the courses and allowed utilizing their own work background in both courses, the latter enabling them to understand better what happens in their workplace. For the faculty staff it facilitated for more collaboration and a stronger sense of being in a community of practice.

Navigating Between Order and Chaos: Temporal Organizing and Event Time in Hackathons

Christina Haefliger — 2025-08-29

Hackathons are temporary collaborative events that have the potential to accelerate innovation. While temporal pressure – which boosts creativity – has been studied from the hackathon participants’ perspective, it is less clear how hackathon organizers orchestrate the temporal aspects of hackathons. Therefore, this research investigates the temporal organizing dynamics in hackathons, using a qualitative case study approach. We identify temporal organizing in hackathons as consisting of three main structuring processes: temporal preparation, temporal sequencing, and temporal condensation. We analyze how time pressure is used for creativity and the temporal structuration mechanisms that facilitate collaboration and innovation. Further, we examine how subjective and objective notions of time are intertwined in these accelerated innovation events and how the temporal design benefits the actors. Our research contributes to the literature on hackathon organizing and temporal organizing, and it contributes to practitioner insights on innovation contest management in time-restricted settings.

The Impact of Customer Knowledge and Market Orientation on Developing Services and Product Diversification

Nabard Hama — 2025-08-29

The study's major objective is to investigate the impact of customer knowledge and marketing orientation on product and service improvement. Furthermore, emphasizing the ability of customers to think creatively is the most significant aspect in creating organizational creativity. It also aimed to demonstrate the importance of knowledge in institutions' survival and growth, as well as to improve their effectiveness and performance in light of the enormous challenges that organizations face, by establishing a competitive advantage, using forms of coordination, design, and structure to make the organization more flexible. The descriptive-analytical approach was used to respond to the research questions and to demonstrate the validity of the hypotheses. This study's methodology is based on positivism philosophy, and it also used the quantitative research approach, which attempts to collect data about a specific occurrence or condition to examine these data in order to make recommendations and suggestions. By collecting works and theoretical books on knowledge, marketing orientation, and the development of new products and services, this study tried to assess data, and then construct a questionnaire to evaluate reality based on the previous analysis and apply it to the study sample. The study using proper statistical techniques analyze the data to make a conclusion and interpret them to reach the most important ideas that will help and enrich the research area. The hypothesis has been confirmed, with the study's findings indicating that the independent variables (customer knowledge and marketing orientation) have a statistically significant positive impact on the dependent variable (product diversification and new service improvement).

Trust And Knowledge Sharing In Temporary Project Teams: A Literature Review

Geraldine Hamill — 2025-08-29

Knowledge has become a pivotal organisational asset, with its value realised primarily through effective sharing. This is especially critical in project-based organisations (PBOs), where temporary teams operate in dynamic environments. Trust is a key enabler influencing knowledge sharing within these teams. This paper reviews literature on the relationship between trust and knowledge sharing in project teams, focusing on how trust facilitates or impedes knowledge flow. It examines mechanisms for trust development in temporary, team-based organisational structures and explores the concept of swift trust as a model for rapid trust formation. The review identifies gaps in understanding how traditional trust models apply to temporary teams and highlights unique challenges in PBOs, where trust must often be established quickly among members without prior relationships. Findings suggest that while trust remains essential for effective knowledge sharing, its development in temporary teams relies on different mechanisms than in long-term teams. The paper concludes by emphasizing the need for early trust-building strategies in temporary teams and calls for further research on trust dynamics in these contexts.

Navigating the Unknown: Knowledge Management in Machine Learning-Driven Product Development

Irina-Emily Hansen — 2025-08-29

The Digital Fish Simulation Project is a machine learning-driven innovation initiative aimed at optimizing fish production processes by developing simulation-based tools for digital modeling of fish behavior. Set within the context of the seafood industry's increasing demand for sustainability, precision, and efficiency, the project operates in a domain characterized by limited prior expertise and significant biological variability. As such, knowledge creation must be dynamic, interdisciplinary, and continuously evolving. This article explores the project from a knowledge management perspective, applying Nonaka and Takeuchi’s SECI model of organizational knowledge creation and the Manulab–Industry Competence Building Process as theoretical frameworks. The study focuses on how structured knowledge management practices, embedded from the earliest stages, enable successful navigation of uncertainty and foster innovation in machine learning-based product development. Workshops were employed as the primary research method, functioning not only as operational project checkpoints but also as structured environments for facilitating interdisciplinary collaboration, surfacing tacit knowledge, externalizing insights, and iteratively refining concepts and prototypes. Through this action research methodology, the study captures the dynamic interplay between knowledge creation activities and project advancement. Preliminary findings indicate that, unlike traditional automation projects where knowledge transfer follows linear trajectories, machine learning-driven innovation demands multiple, parallel SECI cycles running simultaneously across different knowledge domains. Sustained involvement of industry partners from the earliest stages, coupled with interdisciplinary teamwork among engineers, biologists, simulation specialists, and students, has proven critical for effective knowledge creation. Trial-and-error learning, real-time adaptation, and continuous feedback loops emerged as key mechanisms for accelerating organizational learning. The article concludes with recommendations for future research, emphasizing the need to explore structured models for parallel SECI cycle management, interdisciplinary knowledge transfer optimization, and the institutionalization of trial-and-error learning processes. The findings contribute to a deeper understanding of how knowledge management practices must evolve to support sustainable, human-centric innovation in emerging machine learning-driven industrial environments.

Knowledge-Based HRM: A Systematic Literature Review and Research Agenda

Agi Syarif Hidayat — 2025-08-29

This study aims to conduct a systematic literature review on Knowledge-Based HRM (KBHRM) by exploring the development of research, implementation, key variables related to antecedents, mediation, moderation, and outcomes, as well as providing directions for future research. The review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The data analyzed are sourced from Scopus and Google Scholar databases. The findings indicate that empirical research on KBHRM began to develop in 2009, focusing on strategic human resource management. However, subsequent developments have been more influenced by studies in knowledge management. The most common KBHRM implementations include knowledge-based recruitment and selection, training and development, knowledge-based compensation, and performance appraisal. Further analysis reveals that none of the articles reviewed specifically addressed the determinants of KBHRM. However, there is evidence that KBHRM implementation positively impacts both individual and organizational levels. Regarding methodology, most existing studies use surveys as the primary approach, with a scarcity of alternative methods. Additionally, we identify that most KBHRM-related research adopts a single-level approach at the organizational level, while research at the individual level or using perceived approaches is still rare. There is also debate regarding conceptualizing KBHRM as a unidimensional or multidimensional construct. In the final section, this study provides directions for future research, including recommendations related to antecedents, research methods, levels of analysis, and new approaches to develop the KBHRM concept further.

How Can Interorganizational Dialogue Generate New Knowledge for Problem Solving?

Yayoi Hirose — 2025-08-29

The study aims to clarify how interorganisational dialogue can promote the generation of new knowledge. Additionally, it aims to propose the role of an organisational manager who need to generate new business knowledge through the dialogue. Nowadays, it is important for people, organisations, and countries in different positions to understand each other and collaboratively create new solutions. However, the success rate of such multidisciplinary collaborations is not necessarily high. One of the primary reasons for this is that differences in disciplinary backgrounds and professional positions often lead to misunderstandings or a lack of mutual comprehension regarding perspectives and ideas. Analysing these challenges and identifying the key factors that facilitate productive dialogue -- thereby increasing the likelihood of generating new knowledge -- has become essential in contemporary business environments. While much of the literature on knowledge creation focuses on the mechanisms by which knowledge is generated, relatively little attention has been paid to the diverse backgrounds of individuals involved in such creation processes and how these individuals engage with differences in perspectives and assumptions to co-create new knowledge. Similarly, although existing studies on knowledge creation and dialogue frequently highlight the potential of interdisciplinary dialogue to generate novel insights, they tend to lack detailed discussions on the specific steps, conditions, and considerations required to facilitate such processes effectively. This study seeks to shed light on the process of knowledge creation through interorganisational, interdisciplinary dialogue at the individual level, with an emphasis on cognitive aspects. Specifically, it explores what kind of preparatory understanding or mindset participants should cultivate prior to engaging in dialogue, how they should perceive and work with different perspectives and thought frameworks of other disciplinary experts, and how these interactions can lead to the generation of new knowledge. Furthermore, this study discusses the role of organisational managers in enabling and supporting productive interorganisational dialogue among specialists from different fields.

Business Analytics Governance, External Uncertainty, and Firm Performance

Henri Hussinki — 2025-08-29

Constantly evolving business environment and technological innovations, such as business analytics and artificial intelligence, press firms to rethink their information technology governance approaches in order to secure business value extracted from these technologies. Business analytics governance comprises several key mechanisms, among which is business analytics organizing, which guides the firm’s business analytics activities, related decision-making authority, and location of business analytics function within the organization. The pros and cons of different approaches to business analytics organizing have been discussed in the existing business analytics literature, but there is only scant empirical evidence on how they help firms extract business value of their business analytics capability investments. Further, current literature posits that the level of uncertainty of the external business environment has a strong influence over which information technology governance approach a firm adopts, but the links between the external uncertainty, business analytics organizing, and firm performance are unestablished. Our study seeks to contribute to the contemporary business analytics literature by developing and testing a research model that comprises a firm’s business analytics capability, firm’s operational performance, and the moderating impact of business analytics organizing and uncertainty of the firm’s external environment. In more detail, we propose that business analytics capability is positively associated with the firm’s operational performance, and that business analytics organizing, ranging from centralized to decentralized, moderates this relationship. That is, centralized business analytics organizing characterized by concentrated expertise and standardization of analytics services helps firms achieve operational efficiency gains, while more de-centralized organizing approach burdened with a lack of control and possible agency issues weakens the association. Further, we also propose that the uncertainty of the external environment further moderates the other moderation effect, i.e., the centralized business analytics organizing approach works better in low uncertainty environments, while a decentralized organizing approach characterized by wider spread business analytics expertise and agile decision-making outperforms the centralized organizing approach in more uncertain circumstances. Our paired-response survey data collected from Finnish firms provide support for our hypotheses.

Modern Technologies in Knowledge Management in HR Processes in Organizations

Waldemar Jędrzejczyk — 2025-08-29

The paper examines the role of modern technologies in knowledge management within HR processes, emphasizing their importance for building a competitive advantage in the era of digital transformation. It has been demonstrated that organizations are increasingly utilizing advanced IT tools to support key HR functions, such as recruitment, onboarding, competency development, performance evaluation, and talent management. Based on qualitative research involving HR department employees, the most commonly used technologies were identified, including Artificial Intelligence, Applicant Tracking Systems (ATS), Human Resource Management Systems (HRM), HR process automation (workflow automation), Learning Management Systems (LMS), and Robotic Process Automation (RPA). These technologies enable the automation of repetitive tasks, the analysis of HR data, and the personalization of training programs while also supporting the development of an organizational culture based on knowledge sharing. Although the study was of a pilot nature, the obtained results provide a basis for further quantitative analysis. The next stage will involve a survey aimed at assessing the extent to which modern IT technologies are used in knowledge management within HR, as well as identifying their strengths and weaknesses and the benefits and barriers associated with their implementation.

Knowledge Sharing in Communities of Interest for Better Self-Confidence

Saulė Jokūbauskienė — 2025-08-29

Sharing knowledge in a community of interest creates additional value to the members of the community. The way to avoid hardly bearable problems and live a better life is to search for and belong to communities of interest. The previous research analyzes the environmental factors for playing a crucial role in shaping knowledge sharing behaviors within virtual communities (Cai and Shi, 2020). The success of open knowledge sharing community requires individuals to involve in and make continuous commitment to a community the one must be accepted by all the members of the community as equally and involved (Wu et al., 2019). Multiple studies highlight the importance of trust in fostering knowledge sharing. For instance, (Lin and Huang, 2013) (Cien et al., 2005) identified affective-based trust as a positive influence on knowledge sharing behavior, while (Lin, Hung and Chen, 2009) found that trust significantly influences knowledge sharing self-efficacy. The norm of reciprocity is frequently examined as an environmental factor for knowledge sharing (Cheung, Lee and Lee, 2013). Reciprocity is mentioned in the selected motherhood community members’ answers. Communities share common goals and create a safe climate where individuals exchange ideas, experiences, and expertise. Such interactions contribute to both individual and group development by accelerating learning, refining skills, and fostering creative solutions to everyday challenges and are the subject to explore. The aim of the research is to identify the factors that contributes to knowledge sharing in communities of Interest for better self-confidence. The research method is case study of community of interest of mothers by conducting qualitative survey. The qualitative methodology was selected on purpose to gain personal reflections on knowledge sharing in communities of interest.

Environmental Knowledge Management in Food Service Industry. A Preliminary Empirical Research from Companies in Poland

Bartłomiej Kabaja — 2025-08-29

The last phase of the food chain, the food service industry, stands out because of its significant waste emissions, energy and natural resource consumption. This occurs in the situation of disposing of uneaten, cleaning consumption areas, disinfecting vegetables and fruits, among others. It should be borne in mind that also a very large amount of consumer products constitute waste that is difficult to manage in the system. Therefore, environmental protection in the food service industry requires the implementation of good practices both at the corporate management level, but also these procedures must be put into practice at the lowest operational levels. Therefore, the aim of the study was to assess the functioning of environmental knowledge management in the food service industry. The method of individual interviews was used, which makes it possible to collect a wide range of information regarding the opinions, perceptions and comments of the subject. The interview was based on a semi structured interview form, which consisted of several survey steps. The research was conducted in Poland. Due to the scarcity of publications in this field, it was considered that the individual interview would be a suitable tool for obtaining detailed and in-depth information on environmental knowledge management in the food service industry. The results of the collected data gave a broad picture of the situation of the food service industry in Poland and potential opportunities to increase environmental protection. Undoubtedly, the survey confirmed that better knowledge management in this specific industry is required. Employees' responses indicated a lack of training in this area. Which made it much more difficult for them to make pro-environmental decisions on the job. Posters and other materials in graphic form, which on the one hand would remind of the necessity of pro-environmental behavior but on the other hand would indicate the right course of action, turned out to be good solutions. The research made it possible to draw attention to a very important aspect of knowledge management relating to environmental procedures and principles. Despite the existence of a large number of environmental regulations, it appears that front-line employees are not convinced about the maximum involvement of their companies in pro-environmental activities and there is an area where more could be done.

Managing Environmental Knowledge in Enterprises. The Perspective of Young Employees

Bartłomiej Kabaja — 2025-08-29

Ever-increasing industrial production and consumption are putting an increasing strain on the environment. Currently, the most unfavourable rates of greenhouse gas emissions and waste generation are recorded. Analysing these data, it is apparent that the political and regulatory measures taken are having insufficient effect. In building public awareness of this issue, it is important to create responsibility among the employees of enterprises, who have a direct impact on environmental protection with their everyday decisions. Very important in this process are the internal systems of companies, which should allow the creation of good environmental practices and solutions. But also the sharing of this knowledge and its implementation in the daily activities of employees. Based on the above premises, the aim of this study was to assess the status of environmental knowledge management processes in enterprises. A questionnaire survey was used to achieve the objective. The questionnaire contained open and closed questions and was distributed via the Internet. The target group of the survey was young employees of enterprises. The results obtained determined that those surveyed are characterised by a high awareness of environmental protection. However, most of them believe that they are not well informed about environmental protection principles when doing their job. Respondents also gave a low rating to the availability of knowledge in this area and the possibility of acquiring and improving it. In only about 2% of cases did the respondents receive training dedicated to environmental protection at their workplace. In contrast, as many as ca. 84% declared that there was no environmental training at their workplace. Respondents indicated knowledge gained individually on the Internet, TV, books and other resources as the main source of their knowledge. The identified state prompts actions to raise the profile and role of employee education and the implementation of knowledge management systems, which will be able to contribute to improving environmental performance on the part of enterprises. It is important to keep in mind that very often line operational staff have a very strong influence on environmental issues. They are the ones who separate waste, package products, use consumables, operate equipment, etc.

Advanced Spiritual Knowledge Management: Main Features of the Concept and Initial Ideas for Implementation in Schools and School Pastoral Care

Alexander Kaiser — 2025-08-29

Purpose: This paper aims to conceptualize and explore Spiritual Knowledge Management (SpKM) as an advanced and transformative paradigm within the evolving field of Knowledge Management (KM). It shifts KM’s purpose from supporting predefined goals to enabling a learning journey toward the best version of the self or the organization, integrating spiritual, non-rational, and identity-forming dimensions of knowledge. Research Methodology: The study combines conceptual development grounded in interdisciplinary literature with empirical data from a large-scale quantitative survey on school pastoral care. The survey, conducted in the Archdiocese of Salzburg, included 844 valid student responses and explored the role of faith, identity, and expectations regarding school pastoral care. Findings: The empirical results confirm that spiritual aspects of knowledge are relevant and meaningful in the educational context. Students value faith and spiritual guidance particularly in times of personal challenge and see school pastoral care as a support for identity formation, hope, and holistic personal development—elements strongly aligned with the principles of Spiritual KM. Implications of the Study: These findings suggest that school pastoral care is a suitable and impactful domain for implementing Spiritual KM. Moreover, SpKM could inform broader educational strategies by integrating deeper learning processes and resonance-based reflection, thereby fostering wisdom and ethical orientation in knowledge development. Practicality of the Study: The study demonstrates how spiritual knowledge can be accessed and applied in real-world educational contexts. It proposes that SpKM principles be integrated into school systems through staff development, pedagogical methods, and strategic design of spiritual learning environments. Value/Originality of the Study: This is the first study to apply the emerging concept of Spiritual Knowledge Management to the context of school pastoral care. It contributes to the redefinition of KM by incorporating spirituality and purpose as central components and demonstrates its practical relevance through empirical validation.

What Knowledge Management is Not

Yasmina Khadir — 2025-08-29

This conceptual paper aims to initiate a discussion and raise awareness about some of the misinterpretations of Knowledge Management (KM) that we have observed in recent conferences and academic papers. We contend that continuing to ignore these misconceptions might jeopardize the future of KM within the emerging Super Smart Society. Method: The essay begins with an introduction that outlines the problem and its extent. The second section examines significant misuses and misinterpretations of KM in the literature. For each theme, the essay critiques the inappropriate application of KM and offers clarifications to distinguish its true nature. The themes discussed include: KM is not synonymous with innovation; KM is distinct from dynamic capabilities; and KM is not merely an extension of organizational learning. The third section revisits the origins of KM, exploring how seminal scholars originally conceptualized it—shifting the perspective from a Newtonian framework to one that embraces uncertainty through people and practices. The human-centred nature of KM is emphasized, particularly in relation to how individuals address knowledge uncertainties and absences. The essay concludes by reflecting on the future of KM within the paradigm of Society 5.0. Outcome and Contribution: The essay highlights numerous instances in which more established fields tend to overshadow knowledge management (KM)—a persistent trend. Old habits die hard, and KM appears increasingly isolated within the strategy literature, particularly in the post-1995 era. A pervasive industrial mindset continues to frame KM as a positivistic tool, despite warnings from seminal scholars. Considering the emerging human-centred paradigm, this essay seeks to reassert KM’s centrality as a standalone field within Strategic Management. By revisiting KM’s origins and clarifying its distinct identity in relation to adjacent disciplines, the essay contributes to a deeper understanding of the field and its evolving role within the context of Society 5.0.

Regional Technology Foresight for Material Technologies

Lilla Knop — 2025-08-29

The Silesian Voivodeship is undergoing rapid technological transformation and industrial restructuring. This necessitates a systematic, evidence-based approach to identifying priority technologies that will drive regional development by 2050. The purpose of this article is to present the key results from the initial diagnostic phase of the technology foresight project conducted in the Silesian Voivodeship, focusing on the material production and processing sector. The research employs a multi-method approach, PESTEL analysis, integrating Porter's Diamond Model, the emerald model and SWOT analysis, supported by desk research, expert consultations and focus group discussions to assess technological potential and strategic priorities. The study identifies three critical technology groups: metallic, polymeric, and ceramic materials, as key enablers of industrial innovation. These technologies are of particular importance in several strategic sectors, including but not limited to the automotive, aerospace, chemical, steel, pharmaceutical, renewable energy and advanced manufacturing industries. The detailed analyses were summarized in a synthetic technology assessment using four key criteria: effectiveness of technology, market age, scope of application, and impact on the technology landscape. The results indicate that global trends are increasingly shaping the world within the BANI (Brittle, Anxious, Nonlinear, Incomprehensible) framework. These trends highlight several critical challenges for future scenarios, including the green revolution, achieving climate neutrality, reducing energy and material consumption, advancing automation and digitization, and localizing supply chains while better understanding global markets. The Silesian Voivodeship's robust industrial foundation, cutting-edge research infrastructure, and a highly skilled workforce provide a solid foundation for technological innovation and commercialisation, thereby ensuring sustained economic growth. The analysis emphasises the importance of strategic investments in high-performance materials, additive manufacturing, smart materials, green technologies and advanced recycling solutions. Furthermore, the promotion of collaboration between industry, academia, and local authorities is imperative for the acceleration of technology transfer, R&D commercialisation, and the development of regional innovation ecosystems. Furthermore, the enhancement of interdisciplinary synergies and knowledge-sharing platforms will promote the adoption of emerging technologies. To guarantee a sustainable and competitive position in the global market, the Silesian Voivodeship must develop a long-term innovation strategy that integrates technological foresight with industrial policy frameworks.

Knowledge Sharing and Customer Knowledge Management in the Context of Sustainability and CSR: a Case Study of the Fashion Industry in Poland

Natalia Kozik — 2025-08-29

The fashion industry, long challenged by overproduction, unsustainable resource use, and labor issues, is increasingly pressured to adopt sustainable and ethical practices. Modern consumers expect brands to incorporate corporate social responsibility (CSR) into their operations and transparently communicate these efforts. Knowledge sharing (KS), understood as the internal and external exchange of information and best practices, is key in enhancing operational performance and strengthening consumer relationships. Transparent communication of CSR activities builds credibility, trust, and brand loyalty. Likewise, customer knowledge management (CKM), which refers to collecting, analyzing, and utilizing consumer data, enables companies to align marketing and CSR strategies with customer expectations. In fashion, this includes personalized messaging, eco-focused loyalty programs, and initiatives like clothing return schemes or recycling. This paper aims to examine the role of customer knowledge management and knowledge sharing in the fashion industry within the context of sustainability and corporate social responsibility. Specifically, it evaluates how fashion brands use their websites to implement these practices. A two-phase methodology was applied: (1) content analysis of selected fashion retailers’ websites to assess the presence and quality of sustainability information, and (2) evaluation of consumer interaction through CSR engagement and educational content. The study, based on a proprietary evaluation tool, included both international and Polish brands. The results indicate wide variation in the communication of CSR and highlight the need for further research, given the importance of digital channels in shaping consumer awareness and behavior.

The Role of the Transport and Logistics Observatory in Gathering Knowledge for Sustainable Urban Logistics Development

Marzena Kramarz — 2025-08-29

A well-functioning urban logistics system is one of the dimensions that can contribute to the realisation of a smart sustainable city. This is because smart logistics systems are characterised by the sustainability of flows, which requires the use of various types of modern logistics technologies, including storage, transport and information technologies. Sustainable city logistics aims to reduce the nuisance associated with the flow of people and goods in urban areas, while maintaining the social and economic development of the organisations and cities involved. Data on urban flows of people and goods are scattered, as are decisions on how to organise urban flows. This makes knowledge management in such a complex system extremely difficult, especially in the first stage of the process - identifying and collecting knowledge. The article points out that building knowledge resources for effective decision-making in the field of sustainable urban logistics requires the involvement of different stakeholders. Involving stakeholders in building knowledge resources for sustainable flows of people and goods in the city is a task that can be undertaken by public administration units or independent organisations set up for this purpose. The aim of this article is to define the role of an observatory in the process of gathering knowledge on logistics flows in cities. In order to achieve this objective, a literature review was carried out, focusing on the role of stakeholders in knowledge collection, the types of data and knowledge needed to achieve sustainable flows in the city, and the ways in which data and knowledge can be collected. Two models of knowledge gathering were identified - a decentralised model and a centralised model. The centralised model proposes the coordination of knowledge collection by a regional specialist observatory. The case study analysed the collection of data and knowledge by the Transport and Logistics Observatory in the Silesian Voivodeship. The result of the study is the development of a concept for the collection of logistical knowledge in cities in a centralised model and the identification of conditions and limitations for the implementation of such a concept.

Knowledge Management in the Context of Sustainability Reporting

Patrycja Krawczyk — 2025-08-29

The evolution of sustainability reporting as a fundamental component of contemporary corporate operations is indicative of its growing significance in the modern business landscape. From being initially used as a marketing tool to build an image of corporate social responsibility (CSR), sustainability reporting has evolved into a key element expected by investors, as well as an obligation imposed by increasingly stringent legal regulations. The aim of this article is to outline how contemporary organisations are using knowledge management in the context of the increasing requirements for sustainability reporting. The article examines how knowledge management is addressed by key standards and regulations such as the Global Reporting Initiative (GRI), the Task Force on Climate-related Financial Disclosures (TCFD), the Sustainability Accounting Standards Board (SASB) and the Corporate Sustainability Reporting Directive (CSRD). The paper also presents case studies of companies that have implemented advanced knowledge management systems, such as databases, business intelligence tools and collaboration platforms, to optimise their sustainability reporting processes. The case studies show that the integration of these solutions allows for increased efficiency, transparency and credibility of sustainability reports, which in turn translates into increased trust among stakeholders. The article concludes with recommendations.

Integrating GenAI into Corporate Knowledge Management: A Socio-Technical Approach to Overcoming Knowledge Management Challenges

Maria Kretschmer — 2025-08-29

The growing importance of Artificial Intelligence (AI), especially Generative AI (GenAI), is revolutionising the way knowledge is handled and opening up enormous potential for corporate knowledge management (KM). The rapid development of Large Language Models (LLM) and complementary technologies such as Retrieval Augmented Generation (RAG) or knowledge graphs opens up new opportunities for corporate KM, but also presents companies with complex challenges and barriers. This study examines the integration of genAI into corporate KM, taking into account a holistic socio-technical approach. A AI4KM survey was designed to capture the current state of AI use by asking companies about their use of AI technologies. The survey aims to gain insights into the practical implementation of AI solutions, particularly in relation to KM challenges. Based on the results of the AI4KM survey, a socio-technical TOP approach (Technology - Organisation - People) for the introduction of AI-based KM will be developed, which takes into account not only technical, but also organisational and people-related aspects. By addressing these three factors, the study aims to provide a comprehensive framework that ensures the successful adoption of AI technologies in diverse business environments. Specific recommendations for the development of an effective, holistic AI strategy in KM are developed for the various barriers. Among other things, the importance of human-machine interaction will be emphasised in order to create a seamless link between human expertise and machine intelligence. The results of these studies should help companies, especially small and medium-sized enterprises (SME), to effectively use genAI technologies for their KM, to counteract the loss of knowledge due to demographic change and to increase their competitiveness. The combination of theoretical findings and practical recommendations will build a bridge between research and business practice, contributing to the successful integration of AI into corporate KM and equipping companies for the challenges of the future.

Agile Mindset Leaders and Their Experience-Based Tacit Knowledge Absorption Mastery: Polish-Finnish, Technological, and Non- Technological Leaders’ View

Wioleta Kucharska — 2025-08-29

Agile mindset leaders are central to agile organizations driven by knowledge. Previous studies have enabled us to assume that constant, tacit knowledge acquisition appears to be a valuable effect of constant agile learning, contributing to the intellectual mastery of agile leaders. Therefore, the question to which this study is dedicated is: Which competencies (demonstrated skills) do agile mindset leaders perceive as critical for their tacit knowledge acquisition? As previous studies have shown, technological and non-technological mindsets can see agile leadership differently. Therefore, this study aims to investigate whether there are any differences in the informal learning habits of agile mindset leaders in the IT sector compared to other sectors, as perceived by employees in Poland and Finland. A qualitative, interpretive approach, supported by MAXQDA software, is employed to achieve this. Results showed that contextual learning, learning from experiences (both positive and negative), learning from failures and mistakes, critical thinking, constant analysis and synthesis, seeking understanding, and systematic self-development are habitual skills – key informal learning activities employed by agile mindsets. Additionally, employees from other sectors highlighted the value of agile mindset leaders' habit of supporting others; IT employees specified these habits as giving constructive feedback and serving as mentors or coaches. Other sector employees also emphasized that ‘scenario thinking’ and self-discipline are habits that support the informal learning of agile mindset leaders. Apart from minor details, no significant differences were noted between Poland and Finland.

The Relation Between Learning Climate and Mistake-Acceptance Components of Learning Culture: The Double Bias of Mistakes View

Wioleta Kucharska — 2025-08-29

The synergy of the KLC approach components (knowledge, learning, and collaboration cultures) supports a knowledge-driven organization's sustainability. However, given the profound alleged "synergy" between the KLC cultures, the question arises: How does this synergy occur? Based on the former studies, it is assumed that a collaborative culture appears to be the unifying and synergy-driving force of all cultures incorporated into the KLC approach. However, learning culture is at the center of the KLC's power to support collective intelligence development in knowledge-driven organizations. This study aims to investigate in-depth how learning culture components, learning climate, and the mistakes acceptance component as a source of learning interact, based on Kucharska's and Karwowska's (2025) 'KLC-sustainability' model. To do so, a moderation analysis is performed based on a sample of 496 Polish knowledge workers using the ordinary least squares (OLS) regression method. Results showed that a strong learning culture has a high potential to neutralize the adverse effects of the double bias of mistakes.

The Erosion of Scientific Inquiry: Economic and Ethical Aspects of Fake Knowledge and GenAI

Franciszek Kutrzeba — 2025-08-29

The article explores the increasing prevalence of fake knowledge as a substitute for scientific knowledge and examines its economic drivers. It highlights the rising retraction rates of scientific papers due to fraud and paper mills, demonstrating weaknesses in peer review. The author also argues that knowledge generated by GenAI and scientific knowledge, on the other hand, can be perceived as marketable goods, where the former serves as a lower-cost alternative, making it attractive despite its unpredictable lack of validity. A novel theoretical approach to examining recent trends in the knowledge market is presented. Economic factors are discussed, and how they affect shifting consumer preferences from scientific knowledge (SK) to fake knowledge (FK) and GenAI. While top universities remain in demand, financial constraints have pushed some students toward alternative, often less reliable, sources. Apart from income polarization, the proliferation of GenAI has accelerated the spread of fake knowledge by lowering knowledge creation costs and bypassing traditional information gatekeepers, such as peer-reviewed journals or experienced scholars. Furthermore, Generative AI tools and fake knowledge are facilitated by social and psychological tendencies, as people seek knowledge—regardless of its accuracy—to reduce uncertainty. The article concludes by considering fake knowledge in the context of business ethics. It suggests that the dissemination of fake knowledge may serve political and economic interests, particularly in influencing public opinion, destabilizing and eroding trust in public figures and institutions. Given the role of digital platforms in spreading fake knowledge, AI researchers can explore how algorithms influence the visibility of misinformation and what ethical considerations should guide content recommendation systems. Research is needed to examine the interplay between income distribution, digitalization, and the propagation of fake knowledge from sociological, psychological, and economic perspectives; and to investigate the role of cognitive biases, social trust, and political motivations in knowledge preferences.

Entrepreneurial Orientation and Knowledge Integration: The Case of Mature Companies

Anna Lemańska-Majdzik — 2025-08-29

The dynamically changing environment of companies, in addition to the continuous collection and analysis of information, forces adaptation to the internal and external conditions of the business environment. Adaptation of companies and maintaining a competitive advantage is possible thanks to appropriate actions of the organization, including knowledge management, which consists of a number of elements and actions. It can be indicated that the knowledge resources of the organization are the most important source allowing for gaining a competitive advantage, and knowledge management (KM) is an important element of the entire process of managing the organization. One of the areas in the process of managing the organization's knowledge is knowledge integration (KI). According to the literature review, KI is an important element influencing the company's results, the ability to collect and process the organization's characteristic information resources, and is of key importance, among others, for the innovativeness of companies. The literature review indicates that many organizational behaviors correlate with KM, including entrepreneurial orientation (EO). The EO concept describes strategic behaviors of enterprises expressed by the desire to implement innovations, take risks, and take proactive actions more intensively than competitors. The paper is based on a review of international literature and the results of own research on a group of mature companies. The aim of the article is to identify dimensions of EO that affect KI in organizations. The actual research was preceded by a pilot study. During the study, an original questionnaire was used. The study involved 280 randomly selected Polish enterprises. The analysis conducted using descriptive statistics and linear regression indicated the relationship between dimensions of EO and KI in the organization. In addition, it enabled the identification of EO dimensions, which dimensions influence the level of KI in the organization. The conducted study has limitations, but it also constitutes a contribution to science. The novelty of the article is the indication of dimensions of EO that correlate most strongly with the level of KI in the organization.

The Dharma of Knowledge: Bridging Ancient Indian Practices and Contemporary Thought

Udayan Mamgain — 2025-08-29

The present study aims to explore the foundations of knowledge management and sharing as seen in Ancient Indian culture. In a world that is making significant strides towards digitisation, knowledge management serves as an essential tool for efficiency, innovation and cultural continuity. Contemporary systems rely on technological infrastructure, but ancient civilisations developed sophisticated practices to ensure knowledge sharing and management. The study will delve into classical texts such as the Vedas and Brahmanas – which provide spiritual wisdom; Arthashastra – which offers administrative and economic knowledge; Manusmriti – which served as a benchmark for legal codifications, and other related texts. These works, while mainly religious and political, provide profound insights into the generation, transmission, and regulation of knowledge in Ancient Indian society. The study will involve thematic and textual analysis to understand the pedagogical frameworks, oral teachings, institutions such as Gurukulas, and the duties and information mentioned in the relevant texts; the research will uncover practices and principles of knowledge management and sharing. Drawing from these historical insights, the end goal of the study is to create and propose a model that can be incorporated into contemporary education systems to bridge ancient epistemological paradigms with contemporary organisational needs. This model can serve as a foundation for an enhanced knowledge management system, inspire the younger generations to understand the value of ancient wisdom and lead to further innovation in interdisciplinary studies by offering a culturally grounded yet universally relevant framework for knowledge management in the 21st century. Ultimately, this study aims to deepen our understanding of how oral traditions in ancient India successfully preserved and transmitted knowledge across generations long before the widespread use of script and writing.

A Resource-Based View Framework for Knowledge Risk Management in SMEs

Stevens Mamorobela — 2025-08-29

Small and Medium Enterprises (SMEs) face a significant challenge of knowledge loss due to their inability to implement Knowledge Risk Management (KRM) strategies effectively, which ultimately negatively affects their competitiveness and sustainability. The modern nature of work causes an over-reliance on technology to perform remote work, conduct organisational collaboration and exchange knowledge assets, which poses risks associated with knowledge exposure and loss for SMEs. Given that SMEs are resource constrained, they put little effort into risk management strategies that can potentially save them from losing their most critical knowledge. This study proposes a Resource-Based View framework (RBV) for SMEs to leverage internal resources and capabilities to mitigate the risks related to knowledge loss. A systematic literature review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) to analyse academic publications from the past ten years (2014–2024) in order to identify key trends, challenges and strategies related to KRM, RBV and SMEs. Thematic analysis was applied to analyse the selected articles, with three themes emerging, namely the role of intellectual capital in mitigating knowledge risks; technological interventions for knowledge protection; and organizational culture’s impact on knowledge-sharing and security. SMEs struggle with managing intellectual capital, implementing technological interventions for knowledge retention, protection and sharing due to limited resources. Their approach to knowledge-sharing is unstructured and formal processes are less frequently implemented. However, organizations that integrate KRM effectively demonstrate greater resilience, sustainability and competitive advantage. The results underscore the need for SMEs to develop structured KRM frameworks aligned with their resource capabilities. This research bridges the gap between RBV and KRM, providing insights for SME managers to manage knowledge loss risks and enhance long-term sustainability. Future research should explore empirical case studies to validate the findings and proposed framework of this paper.

Improving Project Goal Setting Through AI-Driven Knowledge Management Tools

Diana Mardarovici — 2025-08-29

This paper investigates how artificial intelligence (AI)-driven knowledge management (KM) tools might better shape project goal setting. The paper focuses on their capacity to surface relevant organisational knowledge at the earliest and most strategic phase of project planning. While knowledge management (KM) has long been considered as a lever for improving project outcomes, its integration into the goal-setting process remains underdeveloped, particularly in connection with AI-enabled technologies such as large language models (LLMs), natural language processing (NLP), and robotic process automation (RPA). We argue that project goals are not set in isolation. We consider that these are shaped by what an organisation knows, remembers, or forgets. In this context, our author’s team strongly believes that AI-enhanced KM tools might have the potential to highly influence what goals are proposed, prioritised, and formalised. The paper adopts a case study approach, analysing five organisations across manufacturing, insurance, IT, and infrastructure sectors. The selected cases vary in their use of KM systems and AI capabilities, allowing us to compare both traditional and advanced configurations. Using the SECI model (Socialisation, Externalisation, Combination, and Internalisation) just as an useful interpretive framework, we trace how knowledge is captured, transformed, and embedded into planning processes. Our comparative analysis shows that AI enhances the speed, scale, and contextual relevance of knowledge flows, particularly during the Combination and Internalisation phases. The paper also highlights that successful implementation also highly depends on cultural readiness and correspondingly on the capability to properly integrate into the existing planning routines. Findings indicate that AI-KM tools may contribute to improving the planning quality by surfacing overlooked insights, reducing scope drift, and correspondingly by aligning goals with past performance data. However, we consider that these tools cannot replace human judgement or communication and soft skills, mostly concerning negotiation. The core competences and mostly soft skills have an important impact that lies in enabling better-informed conversations between partners involved within negotiations. We conclude that AI-driven KM, when effectively embedded, might turn organisational memory into a usable asset that might be helpful within the strategic decision-making process. We consider that our research might contribute to both knowledge management and project management literature by reasserting the importance of goal setting as a knowledge-intensive process, one that AI might support, but not in an automatic way.

Knowledge-Sharing Behaviour Within a Non-Profit Organisation: A Reflexive Thematic Analysis

Paul McManus — 2025-08-29

Despite their heterogeneous compositions, non-profit organisations (NPO) are inherently knowledge-centric, necessitating continued exploration into the influential constructs that shape knowledge-sharing (KS) behaviour among employees. This study offers an in-depth examination of KS behaviour within a community-based service provider in Dublin, Ireland. Using a novel approach to Reflexive Thematic Analysis (RTA), data collection consisted of seventeen semi-structured interviews across multiple locations. Findings show that four overarching themes explain how and why knowledge is shared in this organisational context. The four themes developed through rigorous RTA offer the organisation a greater understanding of its employees’ KS behaviours. Practical recommendations are provided to inform organisational policy and improve staff performance in the service of those in its care. Additionally, the novel approach to RTA, the showcasing of axial connections, and the integration of theoretical models represent scholarly advancements in the fields of organisational psychology and motivational theory. By offering a deeper understanding of human interaction within knowledge-intensive work environments, this research informs organisational policy to foster a knowledge-sharing culture. It highlights the importance of supporting employee autonomy, enhancing competence and cultivating stronger workplace relatedness. These developments contribute to creating a psychologically safe environment capable of withstanding increasing social and structural demands.

AI Adoption in Open Innovation Partnerships: Trends, Challenges, and Strategic Implications

Marita McPhillips — 2025-08-29

Artificial intelligence (AI) is transforming innovation partnerships and clusters across diverse sectors, yet its adoption remains uneven, with numerous challenges hindering effective implementation. This study examines the adoption patterns of various AI technologies among open innovation partnerships, analyzing the motivations, challenges, and success metrics associated with AI integration. Drawing on open innovation paradigms, and emerging research on AI in collaborative contexts, we investigate how partnerships navigate the complex tensions between automation and augmentation when implementing AI across organizational boundaries. Our analysis of survey data from 45 European innovation partnerships across multiple industries reveals significant sectoral variations in AI readiness and implementation approaches. We identify four distinct adoption patterns—AI Leaders, Specialized Adopters, Early Experimenters, and Non-Adopters—each characterized by specific implementation approaches, technology preferences, barrier profiles, and ethical considerations. Knowledge gaps emerge as the most significant implementation barrier, showing a negative correlation with adoption levels, while efficiency improvement and innovation enhancement serve as primary adoption drivers. The findings highlight the transformative potential of AI in accelerating collaborative innovation processes and the role of partnership characteristics in shaping implementation strategies. By categorizing and evaluating different patterns of AI utilization, this study provides a comprehensive framework for partnerships to strategically devise and execute AI initiatives aligned with their innovation objectives. The research offers valuable insights for partnership coordinators and policymakers seeking to design effective strategies for fostering AI-driven innovation ecosystems and addressing sector-specific implementation barriers.

Battlefield or Coexistence? Customer Knowledge Creation in the Financial Management of a B2B SME

Kirsi Meriläinen — 2025-08-29

Firms often seek new knowledge from external sources like customers to enhance customer satisfaction. This requires the efficient management of customer knowledge, not only in the firm’s marketing but also in other functions to provide enablers for overall customer experience. This paper addresses the question of “how is customer knowledge created in the financial management process of B2B SME?”. The phenomenon is empirically explored using a case study research strategy that was carried out by the semi-structured interview research method and theory-guided analysis. The case SME sells and develops well-being service solutions in the B2B market in Finland. The business is characterised by credit sales and the subsequent accounts receivable, which initially puts customer understanding at the forefront to enable better decision-making in managing customer risks. The paper concludes that the creation of B2B financial knowledge in an SME seems to vary related to the characteristics of the O2C process resulting in diversified understanding of the financial position and customer behaviour of B2B customers. The SME’s process of creation of B2B customer financial data varies due to the knowledge needs emerging in different phases of O2C processes. Whereas the routine process seems to rest on the use of a customer’s explicit financial data gathered mainly from inside the company, an unexpected process, which is typically by face-to-face encounters with customers, increases a need for tacit knowledge embodied in employees. Based on the empirical findings, the study concludes that customer knowledge creation plays a critical role in the financial processes of a B2B SME. This further indicates that the management of customer knowledge and the finance of B2B firms match each other nicely, forming a coexistence rather than a battlefield.

Breaking Silos to Foster Knowledge Sharing in Universities: A Systems Thinking Perspective

Patrick Mbongwa Mhlongo — 2025-08-29

Universities operate in an environment characterized by rapid change, globalization and other unpredictable complex factors. These institutions play a critical role in the socio-economic development of society. Knowledge has been identified as a strategic resource for private and public organizations to gain competitive advantage. Furthermore, universities are under pressure to respond to the needs of their diverse stakeholders. Hence, it is critical to create a conducive environment to foster Knowledge Sharing beyond functional boundaries in these institutions. However, functional silo mentality has been identified as a major factor that encumbers Knowledge Sharing in organizations, including universities of technology. The purpose of the study was to explore the applicability of the Systems Thinking concept in the context of fostering Knowledge Sharing in Universities of Technology. Previous research investigated this phenomenon from a different perspective, whilst this study provides a University of Technology context. The study adopted a qualitative research methodology underpinned by a constructivism philosophical worldview. Qualitative data was collected from the employees of two universities of technology through semi-structured interviews. Participants in the study were purposively selected. NVivo software was used for data analysis. The study provides theoretical perspectives and practical insights for applying Systems Thinking to foster Knowledge Sharing beyond functional boundaries in organizations and Universities of Technology. Overall, the results of the study indicated that participants were positive that adopting Systems Thinking would be a strategic choice to institutionalize Knowledge Sharing in universities of technology. One of the limitations of this study was that data was collected from only two selected public universities of technology. This provides an opportunity for future research to consider collecting data from more than two universities of technology to investigate this phenomenon.

Developing Phronesis in Business Education: A Student Perspective

Ludmila Mládková — 2025-08-29

This paper aims to discuss the results of the analysis of the feedback of business university students on the phronesis-focused course. The course is part of the MA programme at the Faculty of Business Administration, Prague University of Economics and Business. Its objective is to develop three intellectual virtues (dimensions of knowledge) defined by Aristotle – the episteme (theoretical knowledge), the techne (skills, practical knowledge) and the phronesis (practical wisdom, ability to use previous two in proper way and context). The course was developed to address one of the major arguments against business-oriented education – its over-orientation to theoretical knowledge. During the course, students work in teams that fulfil three types of assignments – presentation of theory, facilitation of discussion and case study preparation and implementation in the class. The teacher is the coach, helps teams with their work, and provides feedback. Episteme is developed via new theoretical knowledge of management. Techne is developed via training in different skills, like presentation skills, discussion skills, and skills to understand the professional text. Phronesis is developed through the interaction of students when preparing and implementing tasks. It becomes active as the ability to understand the colleague's point of view, discuss and harmonise one's own opinion with the ideas of others or understand the social climate in the class and adjust one's behaviour to it. As one of the course authors said, we do not want to teach students about management; we want to teach them management. The feedback of students was captured and analysed by the research based on three research questions: Q1 What do students like about the course? Q2 What do students dislike about the course? Q3 What do students think they learned in the course? The data were collected by the open-question questionnaire with three questions reflecting the research questions. The respondents were students from two classes of the course. The answers were analysed by thematic analysis. The research results show that respondents value the episteme they learn as it allows them to see and understand management holistically. They also like the originality of the course concept based on the cooperation of students and the teacher and the environment the course provides for skills and phronesis development. On the other hand, respondents disliked that the low quality of work of less motivated students influenced the whole class and found the course too demanding for preparation and attention. Even though limited, the research points at important aspects of phronesis-focused courses – they teach students a lot but are demanding and require a change of pedagogical paradigm. Students must be willing to take responsibility for their learning and development and learn even though this may threaten their identity and self-image.

Knowledge Management in the Tech Sector: A Rapid Review of Benefits, Challenges, and Metrics

Alice Monteiro — 2025-08-29

Knowledge Management (KM) plays a fundamental role in technology-based organizations by enabling them to effectively manage and utilize their knowledge resources in dynamic and fast-evolving environments. While KM has been extensively explored across various industries, its application within technology-driven sectors requires further examination due to the unique challenges these organizations face, such as rapid technological advancements, knowledge silos, information overload, and high employee turnover. Knowledge is a key driver of innovation, decision-making, and competitive advantage, so a deeper understanding of how KM operates in these contexts is essential. This study conducts a rapid literature review to investigate the benefits, challenges, and evaluation metrics associated with Knowledge Management in technology-based organizations. The findings reveal that well-implemented KM strategies enhance innovation capacity, operational efficiency, and more effective decision-making processes. However, despite its advantages, Knowledge Management implementation is often hindered by cultural barriers, reluctance to share knowledge, and difficulties aligning KM initiatives with overarching strategic goals. Overcoming these obstacles requires targeted investments in digital infrastructure, leadership support, and promoting a strong knowledge-sharing culture. We also identify a set of potential metrics for assessing KM effectiveness, including operational efficiency indicators, employee and customer satisfaction levels, patent data, knowledge stock, and structural capital. While these metrics build upon insights from the literature, further research is necessary to validate their applicability and reliability as measures of KM success in rapidly changing technology environments. Despite these challenges, Knowledge Management presents transformative potential for organizations seeking to leverage knowledge as a strategic asset, driving continuous innovation, improving organizational performance, and sustaining a competitive edge in an increasingly knowledge-intensive economy. By providing a structured understanding of KM’s role, challenges, and possible success metrics, this study offers valuable insights for researchers and practitioners, guiding them in refining Knowledge Management strategies to enhance adaptability, collaboration, and long-term resilience in technology-driven industries.

A Ten-Step Guideline to Implementing Knowledge Management in Higher Education

Molefi Motsoenyane — 2025-08-29

The value of knowledge management (KM) in today's fast-paced world cannot be emphasised. It is a crucial factor that can determine the success or failure of any institution. To guarantee that KM practices are sustainable, institutions must identify and maximise the use of the elements that contribute to KM's success. This identification is especially vital for Higher Education Institutions (HEIs), as effective knowledge sharing is crucial to the institution's growth and development, as well as to enhancing a country's industrial sustainability. This article examines the unique environment of Higher Education Institutions (HEIs) and identifies Critical Success Factors (CSFs) for successful Knowledge Management (KM) implementation, considering external and internal forces and enablers. The research strategy involved a thorough, systematic literature review using academic databases. Key terms related to knowledge management, higher education, strategies, and critical success factors were identified. The search was limited to peer-reviewed journal articles, conference papers, and books published between 1994 and 2025. The study was limited to articles published between 1994 and 2025 to ensure relevance, with 47 of the 96 studies evaluated and deemed significant for the research. The study emphasises the importance of KM in HEIs, highlighting the need for a comprehensive institutionalisation strategy where organisations seek synergy between the management of critical political, economic, technological, legal and social forces and factors such as leadership, governance, technology, infrastructure, trust, people, structure, strategy, finance and culture. The ten-step guideline for institutionalising KM is intended for use by HEIs. While helpful, this guideline oversimplifies the complex nature of KM, particularly concerning KM CSFs in other organisations. Further research is needed to explore variances in KM success factors across industries and the practical implementation of KM in diverse sectors. The research offers a ten-step guideline for the effective institutionalisation of KM in HEI, focusing on resource allocation, collaboration, trust, alignment, and prioritising investments. The research highlights the significance of a holistic perspective to KM institutionalisation in HEIs.

Impact of Diverse Support on Performance of Industry–Academia Collaborative Research Teams

Yukiko Murakami — 2025-08-29

Bibliometric analyses show that industry–academia collaborative research projects tend to achieve higher performance. However, these collaborations often encounter barriers such as connection difficulties, resource constraints, differences in organizational culture, and institutional distance between industry and academia. Effective support from governments, firms, and universities is crucial to address these challenges and enhance the performance of industry–academia collaborative research teams. This study empirically examines the impact of such support on research performance using data from more than 200 collaborative research teams in Japan. This study differs from previous studies in several aspects. First, bibliographic information is matched with survey data, which enables team-level analysis instead of focusing on firms, universities, or regions. Bibliometric analysis provides an objective performance measure, i.e., the citation counts of research papers, whereas survey data offer abundant insights into team dynamics. Second, whereas most prior studies primarily examined financial support, this study considers a broader range of support measures, including the introduction of appropriate collaborators (networking), funding, provision of research equipment, management of intellectual property (IP), and assistance with administrative work. Empirical results reveal that all support measures, except for assistance with administrative work, significantly enhance research-team performance. Notably, assistance with administrative work presents a significant negative impact. Comparing the positive effects of various support measures, soft measures such as networking and IP management exert a greater impact than hard measures such as funding and equipment provision. Further analysis of the unexpected negative impact of administrative assistance indicates that administrative support occasionally results in cultural conflicts between industry and academia. These conflicts partially mediate the negative relationship between administrative support and team performance. However, administrative support from a third party in the presence of cultural conflicts within a team improves team performance. Further research is necessitated to determine the type of administrative support that can effectively bridge the organizational culture gap and enhance team performance.

Dynamic Capabilities in Social Entrepreneurship: A Case Study on Social Value Creation

Heidi Myyryläinen — 2025-08-29

Social enterprises address societal challenges in entrepreneurial ways. This duality of combining social purpose and business is said to cause tension. There is limited understanding of how this reflects dynamic capabilities in social enterprises. Another underexplored area is how individuals make sense of still-maturing organizational dynamic capabilities. This study examines how social enterprises manage tensions between social mission and financial sustainability. The study focuses on social entrepreneurs sensemaking of their organizational dynamic capabilities that enable social value creation. Using a qualitative approach and content analysis, this study contributes to the literature on dynamic capabilities in social entrepreneurship. It illustrates how sensing, seizing, and reconfiguring capabilities are described to manage tensions while developing a social business. The data consists of interviews of six social entrepreneurs. The analysis reveals how social entrepreneurs identify societal needs and develop business and mobilize resources with a value-driven approach. Furthermore, the dual mission does not cause only tensions, but also enables business, and this requires building dynamic capabilities for the organization. The findings illustrate how social entrepreneurs enhance organizational and network capabilities crucial for business development, without losing sight of their social mission.

Systematic Literature Review: The Contribution Of Creative Leadership to Sustainable Business Development

Tilda Nabbanja — 2025-08-29

The purpose of this research was to establish the relevance of Creative Leadership for Sustainable Business Development. The systematic literature review approach was used as the key method for fact finding and the indicated insights were established from an inception pool of 263 journal articles from two databases namely; Scopus (160 articles) and Web of Science (103 articles). Upon exclusion of some articles using the PRISMA 2020 guideline, 189 articles were reviewed and finally 44 articles were incorporated given their specific relevance to the topic. The intext review was carried out with a comprehensive metanalysis aimed at establishing the findings linked to the key research questions. The findings indicate that there is an adequate sign that the involvement, development and guidance of employees is possible and with creative leadership, the adoption of innovative approaches is seamless with the involvement of the employees. The results of the study provide insights that indicate a cordial relevance for creative, innovative, risk resilient and entrepreneurial oriented leadership if a business is keen about embracing change and creativity so as to attain sustainable business development. Creative leadership in organizations is found to drive intricate realities such as the adoption of ESG, ethical leadership and green practices given that management, more so if comprised of experienced members better appreciates the need for mindfulness in the adoption of innovative approaches to business. With the digital trend developments, big data analytics realities, social media marketing and emerging innovative approaches to business practices, the need for creativity as a driving factor by management is seen to be pertinent. Sustainability and therefore the posterity of the organization is assured with the design of a suitable strategy that incorporates creative management approaches and shape the organizational culture, goals and values towards longer term and therefore envisaged sustainable business development. Creative leaders that advocate for collaboration between private entity stakeholders and for government involvement are also found pertinent for sustainable business development. With these findings, organizational leadership and management teams can be inspired to confidently aspire for the adoption of creative approaches that can drive their businesses towards sustainable development.

Sharing as Power: Keys Strategies for Breaking Knowledge Silos

Maayan Nakash — 2025-08-29

This paper develops an integrative framework proposing actionable strategies for dismantling knowledge silos within corporate environments. Guided by a qualitative methodology, data was gathered from knowledge management (KM) professionals across physical and digital domains using a triangulation approach. The findings illuminate the critical importance of executive-level engagement and sustained commitment to KM initiatives, while simultaneously highlighting the fundamental role of interpersonal trust in overcoming barriers to collaboration and intellectual exchange. We identify five key strategic approaches that demonstrate symbiotic relationships across two organizational movements—Top-Down and Bottom-Up—which, when implemented cohesively, can effectively mitigate detrimental knowledge silos and enhance cross-functional knowledge flows. This work contributes original perspectives to the currently limited literature on addressing intra-organizational knowledge barriers. By situating knowledge silos and knowledge hiding within the broader context of knowledge risks, this study emphasizes the importance of comprehensive knowledge risk management in sustaining knowledge-driven innovation and organizational effectiveness. For future research, we propose investigating optimized technological systems that can effectively support and reinforce embedded knowledge-sharing routines within organizational contexts.

Implementing CTI Exchange: A Framework for the DYNAMO Project Pilot Phase

Jyri Rajamäki — 2025-08-29

Effective Cyber Threat Intelligence (CTI) exchange is essential for strengthening cybersecurity resilience across critical sectors such as healthcare, energy, and maritime. While theoretical CTI governance models exist, their real-world implementation remains challenging due to issues with trust, compliance, interoperability, and real-time collaboration. This paper aims to address these challenges by proposing a practical knowledge transfer framework for the pilot phase of CTI Exchange governance implementation. Building on two prior research studies that developed a CTI exchange governance model specifically tailored for the DYNAMO platform, this paper focuses on putting that model into practice. By utilizing the insights and methodologies from previous work, the study presents a structured approach to applying, testing, and refining governance principles in real-world settings, ensuring effective operationalization of the model through the DYNAMO platform's capabilities. The DYNAMO project, an EU initiative, offers a comprehensive approach to cyber resilience and business continuity, providing organizations with tools and strategies for threat intelligence generation, analysis, and dissemination. The proposed framework includes strategies for piloting DYNAMO tools with pilot preparation, stakeholder engagement, sector-specific governance adaptations, and evaluation metrics. It also defines clear roles and responsibilities to support consistent application of governance mechanisms, with continuous refinement based on empirical feedback. The framework also emphasizes the importance of cross-sector collaboration, ensuring that various stakeholders, including governmental bodies, private organizations, and technical experts, are actively involved throughout the process. Tailored guidelines for the healthcare, energy, and maritime sectors address sector-specific regulatory and operational challenges. Although the pilot phase has not yet been executed, the guidelines presented here provide a robust roadmap for preparing, launching, and iteratively refining CTI exchange pilots. Ultimately, this work lays the foundation for scalable, secure, and compliant CTI-sharing governance that enhances collaboration and cyber resilience across critical infrastructure environments.

From Human Experts to AI Agents: Agentic AI for Knowledge-Intense Problem-Solving in Logistics?

Gaby Neumann — 2025-08-29

Logistics planning is a complex and complicated problem solving process requiring a wide range of knowledge and competence. A planning person or team represents a particular set of knowledge, skills, experience and personal attitudes. His, her or their level of competence decides about success or failure of the planning and about the quality of its results. With this, logistics planning is knowledge-based and knowledge-creating. Because of this, Knowledge Management can provide tremendous support to the planning person. Even though, there is a wide variety of (software) tools applicable to solve specific sub-problems throughout the planning process, human expertise is the key to develop creative planning solutions so far. Latest developments with regard to Artificial Intelligence (AI) might change this picture. AI is one of the most promising technological advancements, but also one of the most ambivalently discussed topics these days. It has surpassed humans at a number of tasks already and continues in doing so at new tasks in an increasing rate. Because of this, AI is capable to assist humans in many different ways. The latest boost of development moved AI application from those sophisticated communicators or task-oriented AI to intelligent agents or agentic AI allowing for autonomous, goal-driven decision-making. Hybrid approaches combine those advanced AI capabilities with human oversight, offering context-aware adaptability without full autonomy. In this way, artificial intelligence and human intelligence join forces in teams, for example, to solve complex problems creatively. Against this background, the paper analyses agentic AI with regard to its potential to support creative problem solving in a knowledge-intense field like logistics planning. Will AI agents become co-workers in logistics planning teams or can agentic AI design logistics solutions autonomously? With this, the paper focusses on chances and challenges coming with the highly dynamic evolution of AI within a complex, knowledge-intense application area where human experience, problem-solving capability and creativity is decisive. It contributes to discussions about necessary adjustments in how organizations manage their knowledge considering artificial and human intelligence.

Green Status Threatens an Emerging Telework Regime?

Rita Nunes — 2025-08-29

The evolution of work regimes has been a central topic of discussion in organizational studies, particularly in the post-pandemic era. Telework, once considered an alternative work model, has become a strategic organizational practice, reshaping business dynamics and leadership approaches. The COVID-19 pandemic and the state of emergency in Portugal accelerated the adoption of telework, transforming it into an emerging work regime. In subsequent years, many organizations recognized its positive impact, integrating telework into their long-term operational strategies. Advancements in digital technologies have demystified telework, enabling employees to perform tasks remotely without compromising organizational efficiency. However, a paradigm shift is underway, with companies reconsidering telework policies, favoring hybrid or fully in-person models. Some researchers argue that this transition reflects organizational control mechanisms, potentially influencing voluntary turnover and employee autonomy. This study aims to examine the correlation between leadership competencies and organizational needs, assessing how telework influences business dynamics and innovation. Using a mixed-methods approach, we conducted research within a Portuguese-Angolan business group, employing critical incident techniques to analyze telework’s viability and future implementation. The findings provide valuable insights into leadership adaptation, organizational restructuring, and the sustainability of telework as a long-term strategy.

Assessing Digital Intelligence: Validation and Insights from a Law Enforcement Pilot Survey

Nóra Obermayer — 2025-08-29

Digital transformation is integral to optimising business processes, driving greater efficiency and productivity. However, the success relies on effective knowledge management, which ensures that organisational knowledge is harnessed and applied throughout the transformation journey. Digital transformation fundamentally reshapes how organisations operate, demanding not only new technological tools but also new competences, attitudes, and a flexible working environment. As organisations adopt digital technologies, they must develop and manage digital competencies across. Knowledge management systems become essential for capturing, sharing, and updating this rapidly evolving knowledge base, ensuring that workforces can access the latest digital innovations. Digital intelligence is a comprehensive concept that encompasses digital competence— confident and responsible use of digital technologies—and a positive digital attitude, which influences how individuals engage with these technologies. These elements form a holistic understanding of digital intelligence, enabling individuals to effectively navigate and contribute to the digital landscape. An eight-dimensional model served as the measurement tool in our Digital Intelligence pilot study. The initial quantitative phase of scale validation centered on one of the Hungarian Law Enforcement Organisation, facilitating subsequent measurements on the same cohort. In 2024, the online pilot survey was conducted using the LimeSurvey system. The questionnaire is completed by employees of the chosen Hungarian Law Enforcement Organisation in Hungary (n=180). The aim of the research is to evaluate the level of Digital Intelligence within the participants by establishing a comprehensive assessment framework, and analysing the differences in Digital Intelligence across various groups based upon individual characteristics. Each dimension was evaluated using nine statements (3 attitudes, 3 skills, 3 knowledge), assessed across three levels (basic, advanced, and expert). Correlation analysis indicated a strong relationship between the model components, suggesting the instrument's ability to measure digital intelligence as a cohesive and multifaceted construct. Among the target group, age showed no correlation with digital intelligence. Paired t-tests revealed the largest discrepancies in digital dialogue (interacting with others in the digital space) and digital literacy (evaluating, synthesising, and adapting information in the digital space). The scoring mechanism indicated that at least half of the respondents scored in the advanced category across all eight dimensions.

Exploring the Interplay Between Civil Liberty, Technological Innovation, and Human Capital

Samuel Amponsah Odei — 2025-08-29

While existing research has focused on analysing the relationship between democracy and innovation, they fall short on the conditions under which the effect works. We draw insights from the institutional and human capital theories to develop and test a simple theoretical model to examine the conditions under which civil liberty impacts technological innovation. Our empirical model based on a sample of 47 sub-Saharan African countries for the period 1990–2022 using the conditional fixed effect Poisson regression. The empirical results revealed that civil liberty positively influences technological innovation. We further found that human capital negatively influences technological innovation. Finally, we found that the effect of civil liberty on technological innovation conditional on human capital is higher for low values of human capital and diminishes for high values of human capital. The results are robust when we include additional control variables. The study has important implications for technological innovation in sub-Saharan African countries in the context of civil liberty and human capital development.

Leveraging Social Capital to Enhance Knowledge Sharing in Mature Enterprises

Małgorzata Okręglicka — 2025-08-29

The aim of the paper is to examine the role of social capital in the knowledge sharing (KS) process in an enterprise, with particular emphasis on its three dimensions: structural (SSC), relational (RSC) and cognitive (CSC). The paper analyses how these three dimensions of social capital contribute to the adoption of KS behaviours, which in consequence can lead to increased innovation, competitiveness and efficiency of the enterprise. Understanding the role of social capital in the knowledge sharing process provides valuable information for practitioners and decision-makers, helping them to create favorable conditions for cooperation and innovation. The contribution to science and the novelty of the current research are based on an empirical approach that focuses on mature enterprises. Analyzing social capital in the context of those organizations that have an established position on the market will allow for the discovery of unique dynamics and challenges related to KS. This research fills a research gap in the literature, focusing on mature enterprises, which are often omitted in knowledge management research. Hence, the empirical part of the article was prepared based on a questionnaire survey among 280 mature enterprises in Poland. In the study of the impact of social capital dimensions on KS, a regression model was used, which allowed us to determine the extent to which each of the dimensions of social capital affects the KS process in a mature enterprise. The regression model confirmed that among the three predictors of social capital, SSC and CSC (had significant positive effects on KS, however, RSC was not statistically significant, suggesting it does not contribute meaningfully to the prediction of KS. The assessment of the strength and direction of these relationships provides valuable information for practitioners in the field of knowledge and social capital management strategies. The current research approach also creates the possibility of continuing the research, by expanding it to include factors mediating this relationship. The research limitation is primarily the simplification in the form of defining mature enterprises only by the period of operation on the market, which should be clarified in future studies.

The Role of Regional Technology Observatories in the Creation of a Regional Knowledge Management System

Sławomir Olko — 2025-08-29

The main purpose of this article is to present the concept of a regional knowledge management system (RKMS) and the role of regional technology observatories in creating such a system. The commencement of conceptual work on an RKMS results from the need to practically embed the functioning of regional technology observatories in the Silesian Voivodeship in the broader context of managing the development of the region. The formal role of regional technology observatories in the Silesian Voivodeship in shaping the RKMS can be indicated since 2013, when the Network of Regional Specialist Observatories (NSRO) was established. The method used in the article was case study. Based on analyses of the literature, the characteristics of RKMS were identified and then, using data from 2010 to 2024, the NRSO was described and the characteristics of RKMS that NSRO met were identified. The article identifies the directions of development of RKMS and indicates the conditions favourable to endogenously rooted specialisations in the region, which have development potential in a global perspective. As an example of the scope of knowledge acquired by observatories, the results of research in the materials production and processing sector regarding innovation management and business models in this sector were presented. The example uses a quantitative analysis in which data was collected during direct surveys of companies. The research sample covered n=50 companies in the manufacturing and materials processing sector.

Developing Business Managers’ Skills for Data-Driven Decision- Making

Johanna Orjatsalo — 2025-08-29

The ongoing digitalisation of business operations continues to increase the amount of data available for organisations. As a result of this transformation, organisations are investing in business analytics tools and technologies to facilitate the use of this data in their decision-making. The existing business analytics literature suggests that the tools and technologies alone do not guarantee success in such endeavours, as organisations also need to have other types of resources, such as human skills and data-driven organisational culture, to form coherent set of business analytics resources that enable them to leverage data and business analytics technologies in their decision-making. While previous studies have recognized the importance of business analytics skills as the enablers of data-driven decision-making in organisations, they have focused mainly on the skills of analytics professionals who manage and run business analytics related operations, rather than the skills of business managers who use business analytics and its output to support their decision-making. Based on empirical data collected through 36 semi-structured interviews, the objective of this study is to identify the skills business managers need for using business analytics in their decision-making. Additionally, the study identifies several practices applied by organisations to help their business managers develop such skills. Contributing to the extant business analytics literature, this study highlights the importance of business managers’ skills in making data-driven decisions by applying analytics-based output to support their decision-making and thereby offers new insights for both scholars and organisations concerning the prerequisites for using business analytics in managerial decision-making. Besides bringing concrete and practical ideas for organisations to develop the skills of their business managers and to seize the value from their business analytics investments, our findings also help the educational professionals to design programs for the future business managers in universities and other educational institutions by increasing their understanding on the skillset required from their students.