Pitfalls in Effective Knowledge Management: Insights from an International Information Technology Organization

• URL: http://arxiv.org/abs/2304.07737v2
• Date: Tue, 19 Sep 2023 06:48:12 GMT
• Title: Pitfalls in Effective Knowledge Management: Insights from an International Information Technology Organization
• Authors: Kalle Koivisto, Toni Taipalus
• Abstract summary: This study aims to identify hindering factors that prevent individuals from effectively sharing and managing knowledge. Several hindering factors were identified, grouped into personal social topics, organizational social topics, technical topics, environmental topics, and interrelated social and technical topics. The presented recommendations for mitigating these hindering factors are focused on improving employees' actions, such as offering training and guidelines to follow.
• Score: 8.847473225998908
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Knowledge is considered an essential resource for organizations. For organizations to benefit from their possessed knowledge, knowledge needs to be managed effectively. Despite knowledge sharing and management being viewed as important by practitioners, organizations fail to benefit from their knowledge, leading to issues in cooperation and the loss of valuable knowledge with departing employees. This study aims to identify hindering factors that prevent individuals from effectively sharing and managing knowledge and understand how to eliminate these factors. Empirical data were collected through semi-structured group interviews from 50 individuals working in an international large IT organization. This study confirms the existence of a gap between the perceived importance of knowledge management and how little this importance is reflected in practice. Several hindering factors were identified, grouped into personal social topics, organizational social topics, technical topics, environmental topics, and interrelated social and technical topics. The presented recommendations for mitigating these hindering factors are focused on improving employees' actions, such as offering training and guidelines to follow. The findings of this study have implications for organizations in knowledge-intensive fields, as they can use this knowledge to create knowledge sharing and management strategies to improve their overall performance.

Related papers

• Factory Operators' Perspectives on Cognitive Assistants for Knowledge Sharing: Challenges, Risks, and Impact on Work [51.78233291198334]
  This study investigates the real-world impact of deploying Cognitive Assistants (CAs) in factories. Our results indicate that while CAs have the potential to significantly improve efficiency through knowledge sharing, they also introduce concerns around workplace surveillance. Our findings stress the importance of addressing privacy, knowledge contribution burdens, and tensions between factory operators and their managers.
  arXiv  Detail & Related papers  (2024-09-30T11:08:27Z)
• Navigating Knowledge Management Implementation Success in Government Organizations: A type-2 fuzzy approach [0.0]
  The study aims to identify critical success and failure factors for implementing knowledge management systems in government organizations. The study highlights the critical success factors for knowledge management systems in government organizations, including cooperation, an open atmosphere, staff training, creativity and innovation, removal of organizational constraints, reward policies, role modeling, and focus.
  arXiv  Detail & Related papers  (2024-06-18T07:22:32Z)
• Large Language Models are Limited in Out-of-Context Knowledge Reasoning [65.72847298578071]
  Large Language Models (LLMs) possess extensive knowledge and strong capabilities in performing in-context reasoning. This paper focuses on a significant aspect of out-of-context reasoning: Out-of-Context Knowledge Reasoning (OCKR), which is to combine multiple knowledge to infer new knowledge.
  arXiv  Detail & Related papers  (2024-06-11T15:58:59Z)
• Private Knowledge Sharing in Distributed Learning: A Survey [50.51431815732716]
  The rise of Artificial Intelligence has revolutionized numerous industries and transformed the way society operates. It is crucial to utilize information in learning processes that are either distributed or owned by different entities. Modern data-driven services have been developed to integrate distributed knowledge entities into their outcomes.
  arXiv  Detail & Related papers  (2024-02-08T07:18:23Z)
• Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators [78.63553017938911]
  Large language models (LLMs) outperform information retrieval techniques for downstream knowledge-intensive tasks. However, community concerns abound regarding the factuality and potential implications of using this uncensored knowledge. We introduce CONNER, designed to evaluate generated knowledge from six important perspectives.
  arXiv  Detail & Related papers  (2023-10-11T08:22:37Z)
• Mitigating the Risk of Knowledge Leakage in Knowledge Intensive Organizations: a Mobile Device Perspective [0.0]
  Modern organizations struggle with the protection of sensitive data and organizational knowledge. Not much is known about strategies to mitigate the risk of knowledge leakage using mobile devices.
  arXiv  Detail & Related papers  (2023-08-18T01:22:31Z)
• Influence of External Information on Large Language Models Mirrors Social Cognitive Patterns [51.622612759892775]
  Social cognitive theory explains how people learn and acquire knowledge through observing others. Recent years have witnessed the rapid development of large language models (LLMs) LLMs, as AI agents, can observe external information, which shapes their cognition and behaviors.
  arXiv  Detail & Related papers  (2023-05-08T16:10:18Z)
• We Are Not There Yet: The Implications of Insufficient Knowledge Management for Organisational Compliance [25.30364629335751]
  This paper presents the findings of an exploratory qualitative study with data protection officers and other privacy professionals. We found issues with knowledge management to be the underlying challenge of our participants' feedback. This paper questions what knowledge management or automation solutions may prove to be effective in establishing better computer-supported work environments.
  arXiv  Detail & Related papers  (2023-05-06T14:19:54Z)
• Ethical and Social Considerations in Automatic Expert Identification and People Recommendation in Organizational Knowledge Management Systems [10.252604597192153]
  Organizational knowledge bases are moving from passive archives to active entities in the flow of people's work. We pose a number of open questions that warrant attention and engagement across industry and academia. We wish to enter into the cross-disciplinary discussion we believe is required to tackle the challenge of developing recommender systems that respect social values.
  arXiv  Detail & Related papers  (2022-09-08T13:49:03Z)
• Knowledge Management Strategies and Emerging Technologies -- An Overview Of the Underpinning Concepts [0.0]
  Knowledge management plays an increasingly important role in global economic development. Numerous leading social scientists in this field have asserted that organisational knowledge should be regarded as a strategic asset. In order to remain relevant in the modern world, organisations should not ignore knowledge management and emerging technologies.
  arXiv  Detail & Related papers  (2022-05-03T14:33:31Z)
• Adaptive cognitive fit: Artificial intelligence augmented management of information facets and representations [62.997667081978825]
  Explosive growth in big data technologies and artificial intelligence [AI] applications have led to increasing pervasiveness of information facets. Information facets, such as equivocality and veracity, can dominate and significantly influence human perceptions of information. We suggest that artificially intelligent technologies that can adapt information representations to overcome cognitive limitations are necessary.
  arXiv  Detail & Related papers  (2022-04-25T02:47:25Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.