Classification of supply chain knowledge: A morphological approach
Purpose – The purpose of the article is to create a knowledge classification model that can be used by knowledge management (KM) practitioners for establishing a knowledge management framework (KMF) in a supply chain (SC) network. Epistemological and ontological aspects of knowledge have been examin...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
Emerald
2014
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| Online Access: | http://hdl.handle.net/20.500.11937/33112 |
| _version_ | 1848753854880940032 |
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| author | Sudhindra, S. Ganesh, L. Kaur, Arshinder |
| author_facet | Sudhindra, S. Ganesh, L. Kaur, Arshinder |
| author_sort | Sudhindra, S. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Purpose – The purpose of the article is to create a knowledge classification model that can be used by knowledge management (KM) practitioners for establishing a knowledge management framework (KMF) in a supply chain (SC) network. Epistemological and ontological aspects of knowledge have been examined. SC networks provide a more generic setting for managing knowledge due to the additional issues concerning flow of knowledge across the boundaries of organizations. Design/methodology/approach – Morphological analysis has been used to build the knowledge classification model. Morphological approach is particularly useful in exploratory research on concepts/ entities having multiple dimensions. Knowledge itself has been shown in literature to have many characteristics, and the methodology used has enabled a comprehensive classification scheme based on such characteristics. Findings – A single comprehensive classification model for knowledge that exists in SC networks has been proposed. Nine characteristics, each possessing two or more value options, have been finally included in the model. Research limitations/implications – Knowledge characteristics have been mostly derived from past research with the exception of three which have been introduced without empirical evidence. Although the article is primarily about SC knowledge, the results are fairly generic. Practical implications – The proposed model would be of use in developing KM policies, procedures and establishing knowledge management systems in SC networks. The model will cater to both system and people aspects of a KMF. Originality/value – The proposed knowledge classification model based on morphological analysis fills a gap in a vital area of research in KM as well as SC management. No similar classification model of knowledge with all its dimensions has been found in literature. |
| first_indexed | 2025-11-14T08:31:08Z |
| format | Journal Article |
| id | curtin-20.500.11937-33112 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:31:08Z |
| publishDate | 2014 |
| publisher | Emerald |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-331122018-06-12T03:32:09Z Classification of supply chain knowledge: A morphological approach Sudhindra, S. Ganesh, L. Kaur, Arshinder Knowledge management Supply chain knowledge Knowledge classification Epistemological classification Ontological classification Morphological analysis Purpose – The purpose of the article is to create a knowledge classification model that can be used by knowledge management (KM) practitioners for establishing a knowledge management framework (KMF) in a supply chain (SC) network. Epistemological and ontological aspects of knowledge have been examined. SC networks provide a more generic setting for managing knowledge due to the additional issues concerning flow of knowledge across the boundaries of organizations. Design/methodology/approach – Morphological analysis has been used to build the knowledge classification model. Morphological approach is particularly useful in exploratory research on concepts/ entities having multiple dimensions. Knowledge itself has been shown in literature to have many characteristics, and the methodology used has enabled a comprehensive classification scheme based on such characteristics. Findings – A single comprehensive classification model for knowledge that exists in SC networks has been proposed. Nine characteristics, each possessing two or more value options, have been finally included in the model. Research limitations/implications – Knowledge characteristics have been mostly derived from past research with the exception of three which have been introduced without empirical evidence. Although the article is primarily about SC knowledge, the results are fairly generic. Practical implications – The proposed model would be of use in developing KM policies, procedures and establishing knowledge management systems in SC networks. The model will cater to both system and people aspects of a KMF. Originality/value – The proposed knowledge classification model based on morphological analysis fills a gap in a vital area of research in KM as well as SC management. No similar classification model of knowledge with all its dimensions has been found in literature. 2014 Journal Article http://hdl.handle.net/20.500.11937/33112 10.1108/JKM-12-2013-0490 Emerald restricted |
| spellingShingle | Knowledge management Supply chain knowledge Knowledge classification Epistemological classification Ontological classification Morphological analysis Sudhindra, S. Ganesh, L. Kaur, Arshinder Classification of supply chain knowledge: A morphological approach |
| title | Classification of supply chain knowledge: A morphological approach |
| title_full | Classification of supply chain knowledge: A morphological approach |
| title_fullStr | Classification of supply chain knowledge: A morphological approach |
| title_full_unstemmed | Classification of supply chain knowledge: A morphological approach |
| title_short | Classification of supply chain knowledge: A morphological approach |
| title_sort | classification of supply chain knowledge: a morphological approach |
| topic | Knowledge management Supply chain knowledge Knowledge classification Epistemological classification Ontological classification Morphological analysis |
| url | http://hdl.handle.net/20.500.11937/33112 |