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Metadata analysis of knowledge management in supply chain: Investigating the past and predicting the future

Vishal Ashok Bhosale (Department of Mechanical Engineering, S.V. National Institute of Technology, Surat, India)
Ravi Kant (Department of Mechanical Engineering, S. V. National Institute of Technology, Surat, India)

Business Process Management Journal

ISSN: 1463-7154

Article publication date: 5 February 2016

1497

Abstract

Purpose

The purpose of this paper is to present a comprehensive and useful insight into the knowledge management (KM) in the supply chain (SC) research and provide gaps and future research implications. The literature review includes a metadata analysis of KM in SC research along a number of dimensions, the existing dimensions as well as dimensions which are previously not been presented within the current area to predict the future role of KM in SC.

Design/methodology/approach

The study is to examine the status of KM in SC within academic and industrial research in the last 14 years. The systematic literature review of KM in SC is based on 176 peer reviewed articles selected through a multi-stage process, from 1,063 studies during January 2001-June 2014.

Findings

An increase in the interest level of incorporating KM in SC is clearly visible while studying available literature. The statistics prove that research in the field of KM in SC is overwhelmingly empirically oriented. Another major finding shows that the survey model score highest among all the research method used in the discipline. In general, the research is more interpretive in nature and provides a frame for theoretical critique. The result indicates that there is a need to use of advanced data analysis techniques with traditional data analysis technique.

Originality/value

The review simply provides statistical summary which is easy to understand for practitioner and provide increased insights on the current state of research for the KM in SC.

Keywords

Citation

Bhosale, V.A. and Kant, R. (2016), "Metadata analysis of knowledge management in supply chain: Investigating the past and predicting the future", Business Process Management Journal, Vol. 22 No. 1, pp. 140-172. https://doi.org/10.1108/BPMJ-02-2015-0014

Publisher

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Emerald Group Publishing Limited

Copyright © 2016, Emerald Group Publishing Limited

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