Enterprise Ontology model for tacit knowledge externalization in socio-technical enterprises

Shreyas Suresh Rao, Ashalatha Nayak

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Aim/Purpose: A vital business activity within socio-technical enterprises is tacit knowledge externalization, which elicits and explicates tacit knowledge of enterprise employees as external knowledge. The aim of this paper is to integrate diverse aspects of externalization through the Enterprise Ontology model. Background: Across two decades, researchers have explored various aspects of tacit knowledge externalization. However, from the existing works, it is revealed that there is no uniform representation of the externalization process, which has resulted in divergent and contradictory interpretations across the literature. Methodology: The Enterprise Ontology model is constructed step-wise through the conceptual and measurement views. While the conceptual view encompasses three patterns that model the externalization process, the measurement view employs certainty-factor model to empirically measure the outcome of the externalization process. Contribution: The paper contributes towards knowledge management literature in two ways. The first contribution is the Enterprise Ontology model that integrates diverse aspects of externalization. The second contribution is a Web application that validates the model through a case study in banking. Findings: The findings show that the Enterprise Ontology model and the patterns are pragmatic in externalizing the tacit knowledge of experts in a problem-solving scenario within a banking enterprise. Recommendations for Practitioners: Consider the diverse aspects (what, where, when, why, and how) during the tacit knowledge externalization process. Future Research To extend the Enterprise Ontology model to include externalization from partially automated enterprise systems.

Original languageEnglish
Pages (from-to)99-124
Number of pages26
JournalInterdisciplinary Journal of Information, Knowledge, and Management
Volume12
Publication statusPublished - 01-01-2017

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All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Information Systems and Management

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