Kostas Metaxiotis, John Psarras and Stefanos Papastefanatos
Knowledge management has recently received considerable attention in the computer information systems community and is continuously gaining interest from industry, enterprises and…
Abstract
Knowledge management has recently received considerable attention in the computer information systems community and is continuously gaining interest from industry, enterprises and government. As we move towards building knowledge organizations, knowledge management in combination with information management will play a fundamental role towards the success of transforming individual knowledge into organizational knowledge. In this framework, this paper discusses the key concepts of human‐computer interaction in knowledge management, identifies new challenges of knowledge management for Web‐based business and proposes a “user agent architecture” for knowledge management in e‐learning environments. User agents use artificial neural network technology and can be used in various e‐learning or e‐training environments, in order to provide them with means of managing information stored, filtering content and enabling better knowledge adoption on behalf of their users.
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S.M. Riad Shams and Ludovico Solima
Big data management research and practice, however, have received enormous interest from academia and industry; the extant literature demonstrates that the authors have limited…
Abstract
Purpose
Big data management research and practice, however, have received enormous interest from academia and industry; the extant literature demonstrates that the authors have limited understanding and challenges in this knowledge-stream to fully capitalize with its potentials. One of the contemporary challenges is to accurately verify data veracity, and developing value from the verified data for an organization and its stakeholders. Consequently, the purpose of this paper is to develop insights on how the authors could strategically deal with the contemporary challenges in strategic management of big data, related to data veracity and data value.
Design/methodology/approach
The inductive–constructivist approach is followed to develop insights at the intersection of dynamic capabilities theory and stakeholder relationship management concept, in order to strategically deal with the contemporary challenges in big data management, related to data veracity and data value.
Findings
At the intersection of dynamic capabilities theory and stakeholder relationship management concept, an implication is acknowledged, which has research and practical significance to strategically verify data source, its veracity and value. Following this implication, a framework of a data incubator is proposed to proactively develop insights on veracity and value of data. Empirical insights are also presented in this study to support this initial framework.
Practical implications
For future research in strategic management of big data, academics will have contextual understanding on the particular interconnected and interdependent attributes from dynamic capabilities and stakeholder relationship management research streams to further enhance the understanding on big data management. For practice, these insights will be useful for executives to focus on specific attributes of the proposed data incubator to confirm data veracity and develop insights on how to design, deliver and evaluate stakeholder value based on the verified data.
Originality/value
Following a synthesis at the intersection of dynamic capabilities theory and stakeholder relationship management concept, this study introduces a data incubator to meaningfully deal with the big data management challenges, related to veracity and value of data.