1,721,032 research outputs found
Challenges in Knowledge Sharing with Artificial Intelligence: A Research Exploration
No full textThe integration of Artificial Intelligence (AI) into knowledge management has transformed how organisations create, store, and share knowledge. However, alongside its innovative potential, AI presents significant challenges that can impede effective knowledge sharing. This study explores the complex challenges organisations face when incorporating AI into knowledge-sharing practices. Using a systematic review of current literature and interviews with practitioners, the research identifies major barriers such as algorithmic opacity, data privacy issues, bias in AI-produced knowledge, erosion of human trust, and ethical questions around decision-making autonomy. The study also emphasises how organisational culture, digital preparedness, and governance structures influence the relationship between AI adoption and knowledge-sharing success. By presenting a conceptual framework of these interconnected challenges, this paper adds to the ongoing discourse on responsible and human-centred AI in knowledge management, offering practical insights for managers and researchers striving to balance technological efficiency with ethical and collaborative concerns
Artificial intelligence in knowledge management: Identifying and addressing the key implementation challenges
Full text linkIn today's digital landscape, Knowledge Management (KM) is crucial for organisational competitiveness. Artificial Intelligence (AI) offers transformative potential for KM practices, yet its integration presents multifaceted challenges. This study addresses significant gaps in the literature by identifying and prioritising critical challenges associated with AI integration in KM.
Employing a tripartite methodological approach, this research combines a literature review on KM and AI’s challenges, a Delphi study with domain experts, and confirmatory factor analysis (CFA) across four KM processes. Data from retail sector professionals validate the challenges identified by experts.
Findings reveal a comprehensive landscape of challenges, categorised into technological, organisational, and ethical domains, with variations across different KM processes. The study contributes to the field by comprehensively exploring AI-related challenges in KM, offering a quantitative ranking, and enhancing understanding of the AI-KM interplay.
This research provides valuable insights for business leaders, facilitating the development of strategies to foster robust knowledge ecosystems. By addressing these challenges proactively, organisations can enhance their KM practices, leveraging AI to maintain competitiveness in an increasingly digital business environment. The study contributes to theoretical discourse and offers practical implications for organisations navigating AI integration in their KM practices
Unlocking knowledge transfer dynamics across borders: key drivers in international strategic alliances
Full text linkAbstract
Purpose
In today’s swiftly evolving and intensely competitive business landscape, organisations increasingly recognise the significance of cross-border collaborative partnerships. International Strategic Alliances (ISAs) have emerged as effective platforms to foster innovation and gain a competitive advantage. Within the context of the hotel industry, which epitomises international operations, this study aims to investigate the pivotal role of knowledge transfer (KT) in the performance of ISAs.
Design/methodology/approach
The research framework draws on the influence of technological drivers (TD), organisational drivers (OD) and individual drivers (ID) on successful KT within ISAs. By analysing data from managers and owners of international hotel businesses using Confirmatory Factor Analysis (CFA), this study empirically examines the relationships between these drivers and KT dynamics.
Findings
Findings highlight the direct impact of these drivers on KT and subsequent alliance performance. However, among these drivers, factors related to TDs, such as Web 2.0, knowledge management systems and IT infrastructure, generally received the highest values.
Originality/value
This study contributes to international business and knowledge management and sheds light on the intricate interactions between the drivers of KT and ISAs. The insights derived from this study provide a foundation for enhancing strategic alliance practices in a global context. By embracing KT mechanisms, organisations can harness collaborative potential, drive innovation and achieve sustainable growth
Knowledge Management in the AI Era: Evolution, Challenges and Strategic Adaptation
No full textWhy Knowledge Management Matters in the Artificial Intelligence Era:
In an age where Artificial Intelligence (AI) is revolutionising industries, knowledge is no longer static; it is dynamic, evolving, and increasingly intertwined with intelligent systems. Knowledge management (KM), once centred on human expertise and structured repositories, has reached a pivotal moment where AI is not just a tool for efficiency but a force reshaping how knowledge is created, shared, and applied. This book explores the transformative impact of AI on KM, uncovering both the opportunities and challenges that arise as organisations adapt to an era of intelligent knowledge ecosystems.
For decades, KM relied on paper-based records, institutional memory, and traditional databases. With the rise of digital transformation (DT), information became more accessible, structured, and retrievable. However, the emergence of AI has fundamentally altered this landscape, shifting from static information management to dynamic, self-improving systems that can learn, predict, and generate insights autonomously. Machine learning (ML) algorithms now extract hidden patterns from vast datasets, while natural language processing (NLP) enables seamless human-machine interaction. AI-driven expert systems also contribute to decision-making processes. These advancements challenge conventional understandings of knowledge, raising critical questions: What constitutes knowledge in the era of AI? How does AI reshape the way knowledge is created and shared? What are the risks and ethical implications of relying on machine-generated knowledge?
This book aims to provide a comprehensive exploration of KM in the AI era by addressing these critical questions. It examines how KM has evolved in response to AI and DT, redefines knowledge in the context of intelligent systems, and analyses how AI enhances or disrupts traditional knowledge-sharing practices. It also critically evaluates the risks, biases, and ethical concerns associated with AI-driven KM, while offering strategic insights on how organisations can adapt to this rapidly evolving landscape. By engaging with these themes, this book serves as a guide for scholars, business leaders, and knowledge professionals seeking to navigate and leverage AI in their KM strategies. Importantly, this book bridges theory and practice, offering empirical insights that matter deeply to real-world decision-makers. For small and medium-sized enterprises (SMEs), the findings reveal how AI can democratise access to strategic knowledge, helping them compete more effectively against larger firms by leveraging data-driven insights, automating knowledge workflows, and enhancing innovation capabilities. For managers and leaders, this work highlights the skills and cultural shifts necessary to successfully embed AI into KM practices, including fostering trust in AI-generated knowledge, mitigating biases, and ensuring ethical stewardship of knowledge assets. Moreover, for practitioners and consultants, it outlines actionable frameworks and decision-making tools to design adaptive knowledge ecosystems that are resilient, inclusive, and future-ready. Through real-world case examples, conceptual models, and strategic recommendations, the book offers a roadmap for organisations of all sizes to not merely survive but thrive in the AI-driven knowledge economy.
AI is not merely a technological advancement; it is a paradigm shift that will define the future of knowledge work. Organisations that fail to integrate AI into their KM strategies risk inefficiency, knowledge fragmentation, and missed opportunities. Conversely, those that embrace AI-driven KM will unlock new capabilities, from predictive analytics to real-time knowledge generation, fostering enhanced collaboration, innovation, and decision-making.
This book is not just about technology; it is about the very nature of knowledge in the AI age and its profound implications for organisations, researchers, and policymakers. As AI becomes an integral part of how knowledge is created, stored, and utilised, understanding its role in KM is no longer optional; it is essential. This book provides the insights and frameworks necessary to navigate this transformation, offering a forward-looking perspective on how AI is shaping the knowledge landscape and what it means for the future of KM
Islamic Accounting laws or Islamic laws in Accounting
Full text linkIn the academic and professional circles in accounting, The issue of Islamic accounting has always been challenging and controversial.. A group of accountants believes that traditional accounting, based on Western philosophy, cannot meet the financial reporting needs in Islamic countries. Therefore, Muslim scholars should provide a definition for accounting in Islamic countries and clarify the reporting requirements by simplifying the goals and characteristics of Islamic accounting. This group believes by defining an Islamic framework, a new branch in accounting, that is called Islamic Accounting, is created .Another group of Muslim accountants insists that there is no Islamic accounting or Western accounting, and any change in accounting in order to standardize it should be in line with the needs and demands of users in the country or region and even specific religious groups. Proponents of this theory say that if there is an independent Islamic accounting, then there may also be Christian accounting or Jewish accounting. The final opinion of Islamic accounting opponents is that accounting is accounting
AI in knowledge sharing, which ethical challenges are raised in decision-making processes for organisations?
No full textThis study aims to identify and assess the key ethical challenges associated with integrating Artificial Intelligence (AI) in knowledge-sharing (KS) practices and their implications for decision-making processes within organisations. The research explores the ethical dimensions of AI-driven KS, such as privacy and data protection, bias and fairness, and transparency and explainability.
The study employs a mixed-methods approach, beginning with a comprehensive literature review to extract background information on AI and KS and to identify potential ethical challenges. Subsequently, a confirmatory factor analysis (CFA) is conducted using data collected from individuals employed in business settings to validate the challenges identified in the literature and to assess their impact on decision-making processes.
The findings reveal that challenges related to privacy and data protection, bias and fairness, and transparency and explainability are particularly significant in AI-driven decision-making. Moreover, challenges related to accountability and responsibility and the impact of AI on employment also show relatively high coefficients, highlighting their importance in the decision-making process. In contrast, challenges such as intellectual property and ownership, algorithmic manipulation, and global governance and regulation are found to be less central to the decision-making process.
This research contributes to the ongoing discourse on the ethical challenges of AI in knowledge management and decision-making within organisations. By providing insights and recommendations for researchers, managers, and policymakers, the study emphasises the need for a holistic and collaborative approach to harness the benefits of AI technologies while mitigating their associated risks
What drives the process of knowledge management in a cross-cultural setting; The impact of social capital
No full textPurposeThis paper aims to consider the role and influence of social capital (SC) on knowledge management (KM) and sets out to develop an understanding of the importance of the impact of the cross-cultural environment on this relationship.Design/methodology/approachAccording to the notion, in this study, the relationship between two essential aspects in management and business, SC on KM practices, has been analyzed. By applying a descriptive and correlational method, the impact of various dimensions of SC on KM in a cross-cultural setting has been investigated, and required data has been obtained through questionnaires consist of 30 items, which is prepared for a sample of 232 people.FindingsAlthough the findings are varied, the results indicated that there is an important relationship between SC dimensions and KM in the research environment, which is cross-cultural.Research limitations/implicationsFirst, as the data derived from different branches of a big company in Iran, its results cannot be easily extended to other contexts. Therefore, future streams of research can expand the scope of this paper into other contexts with different characteristics. Moreover, the sample of this paper is taken from different communities (branches) which increase the variety of personality features in distinct cultures. Thus, further research can stress a particular organization/ branch to avoid the problem of cultural variation and focus on a more homogenous sample. Finally, this study targeted a big organization in the IT sector. However, future studies can investigate another type of firm (e.g. small and medium firms) in different sectors (e.g. manufacturing, food sector, etc.).Practical implicationsIn this research, using scientific and practical methods, the impacts have been examined carefully and deliberately to assist the managers of organizations in theoretically and managerially as these outcomes contribute to the development of a new concept called cross-cultural in knowledge management and social capital, and support organizations to cope with the implications of this concept.Originality/valueThere is not much empirical research on cross-cultural settings and its effects on management, finance and business, especially on correlations between KM and SC. This investigation tries to fill this gap and explain the ways, which companies can use SC for enhancing their effectiveness of KM by considering culture diversity impacts
Digitalisation in transport and logistics: a roadmap for entrepreneurship in Russia
No full textThe transport and logistics system has always been an attractive sector for investments and entrepreneurship. Its importance becomes increasingly stressed by the advance in technology and the advent of digitalisation. Consequently, the digital economy opens new possibilities for optimising the transport and logistics section of national economies. Thus, this paper proposed and developed a conceptual model of digitalisation of transport and logistics in Russia, a developing country where this sector may represent many entrepreneurship potentialities. The suggested model is based on new technologies related to Industry 4.0 as blockchain, big data, the internet of things, virtual reality, and artificial intelligence. Accordingly, this paper pointed out the key factors of digitalisation of the industry: a) accessibility of financing; b) availability of digital technologies of Industry 4.0; c) public support for digitalisation of transport and logistics and consumer preferences. Interestingly, the paper offers an intriguing economic approach to understand players' behaviours potential strategies based on the Prisoner's dilemma. This provides some useful recommendations to public policymakers, investors, and entrepreneurs to govern the digitalisation of transport and logistics in Russia
How Do Experts Think? An Investigation of the Barriers to Internationalisation of SMEs in Iran
No full textNowadays, “internationalisation” is a topic of concern for many types of research on small and medium-sized enterprises (SMEs). SMEs pursue internationalization policy as a leading process to keep and improve their position in the competitive business markets. However, SMEs face many challenges that hinder the successful implementation of the internationalization process. This chapter aims to recognise the important barriers to internationalisation for Iranian SMEs. We conduct two studies using a combined exploratory and confirmatory approach. We apply the Delphi method for exploring and forecasting the key barriers in the first study. In the second study, we validate the key indicator employing a Structural Equation Modelling technique for the Confirmatory Factor Analysis of the survey data. In the Delphi method, a group of 24 managers and academic professors in Iran, identified the main barriers. A sample of 210 survey observations was collected from the owner and top managers, senior managers, and employees. The results suggest 8 key factors and 31 indicators of barriers to internationalisation associated with Iranian SMEs: informational, financial, marketing, functional, procedural, governmental, environmental and, tariff and non-tariff. This research contributes to the knowledge of critical obstacles concern for current and future business internationalisation, and the outcomes provide practical implications. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
Seeking traces of democracy in the workplace: effects on knowledge sharing
No full textPurpose This study aims to examine the role of organisational democracy (OD) in facilitating the knowledge sharing (KS) process within companies, thus considering the effect of different OD principles. Design/methodology/approach The authors used data collected through a questionnaire on a sample of 254 employees at private universities and colleges to test the relationship between OD and KS. Data were analysed using the structural equation modelling technique. Findings Overall, OD has a direct and significant effect on facilitating KS in organisations. Also, the results showed that there are different degrees and intensities among the individual principles (sub-concepts) of OD and KS. Practical implications The findings highlight the important role of democracy in an organisation to enhance the organisational climate and employees' behaviours, thus leading to higher KS outcomes. Also, results, provide an opportunity for managers to consider enhancing democracy in an organisation for improving internal collaboration effectiveness in KS. Originality/value This paper sheds light and adds new knowledge to embryonic studies that are directed towards the integration of democracy within the main concept of knowledge management (KM). This emphasises the need to use and stimulate OD and its principles for improving the effectiveness of KM practices with specific attention to KS
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