Abstract
Purpose: This paper aims to investigate the potential of knowledge management (KM) as a discipline in helping understand and manage social and economic complexity. The paper highlights some of the potential relationships between KM in organisations and their economic performance. Finally, the authors assess the role of human resources and technological infrastructures in the relationship between organisation’s approach to KM and their performance. Design/methodology/approach: The hypotheses are tested via a survey on a sample of managerial-level employees of information technology organisations located in the city of Brno in Czech Republic. The data collected are analysed using structural equation modelling (SEM) to study the relationship between KM; the workforce’s willingness and ability to collaborate and co-create value; and the organisations’ economic performance. Findings: The research found that there is a direct and positive relationship between an organisation’s approach to KM and its economic performance. This study also shows that the workforce’s behaviour and the technological infrastructure of the organisation have a direct effect on business performance. Finally, the authors proposed that a link between human resource management and technology orientation must be established and supported by a KM strategy. Originality/value: This paper offers a new perspective to the approach to KM in organisations. Reflections and empirical results underline the need for organisations to invest in the implementation of KM strategies that involve both the human resources and technological infrastructure as a way to improve the impact of knowledge on the companies’ economic performances.
Original language | English |
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Pages (from-to) | 1314-1334 |
Number of pages | 21 |
Journal | Journal of Knowledge Management |
Volume | 23 |
Issue number | 7 |
Early online date | 11 Jul 2019 |
DOIs | |
Publication status | Published - 30 Sept 2019 |
Keywords
- Human resources
- Information technology
- Knowledge management phases
- Learning organization
- Structural equation modelling
- Surveys
- Technology