Knowledge Management (KM) research outputs have been expanding exponentially in the past years, generating diversified topics, which lack integration and classification. It has been challenging for experts to classify KM because of its versatile open fields, and in our view, it contributes to the technocratic approach remaining behind the organizational approach. This paper highlights a way to classify KM publications through a pattern that will support technocratic developments representing knowledge in a more explicit form. This study uses a classification method thatuses a template in a taxonomy shape, executing some procedures and allowingan accurate identification and organizationof KM research outputs. The proposed taxonomy method is proven on a set of 150 different KM publications from the last 15 years. This scheme is grouped into two main categories: Conceptual and Empirical which could enable academics and practitioners alike to better understand the current gaps that are prevalent in KM.
Authors
- Rodrigo Oliveira de Castro,
- Cesar Sanin,
- prof. dr hab. inż. Edward Szczerbicki link open in new tab ,
- Andrew Levula
Additional information
- DOI
- Digital Object Identifier link open in new tab 10.1080/01969722.2020.1871223
- Category
- Publikacja w czasopiśmie
- Type
- artykuły w czasopismach
- Language
- angielski
- Publication year
- 2021
