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Knowledge management reliability assessment: an empirical investigation

Knowledge management reliability assessment: an empirical investigation Purpose– A perfect knowledge management (KM) initiative is one that achieves its objectives without any failure during a pre-defined period. However, KM implementation is not perfect in every organization as it requires substantial changes in organizational infrastructures, including culture, structure, and technology. Therefore, the purpose of this paper is to propose a model for assessing the reliability of KM to help organizations evaluate their ability to implement KM successfully by identifying key reliability variables, modeling the complex interaction structure among variables, and determining the probability of failure for each KM capability. Design/methodology/approach– In this study, relevant variables are identified by a thorough analysis of related references in literature. In order to determine the compound structure of complicated interactions among variables, a group-based approach is utilized. Based on the combined cognitive maps, a cognitive network is constructed as a framework for graphically representing the logical relationships between variables and capturing the uncertainty in the dependency among these variables using conditional probabilities. The applicability of the proposed approach and the efficacy of the model was verified and validated with data from a banking institution. Findings– Results show that KM reliability can be defined by the degree to which required KM capabilities, including infrastructure and process capabilities, have the ability to perform as intended in a certain organizational environment. Furthermore, it is demonstrated that reliability assessment of KM through a hybrid approach of fuzzy cognitive map and Bayesian network is possible and useful. Practical implications– The proposed reliability assessment model facilitates the process of understanding why and how failures occur in KM. Moreover, the proposed approach evaluates the probability of success for each variable as well as for the entire KM initiative. Therefore, it can provide insight for managers and executives into the degree of reliability for their existing KM and prevention of failures in vital factors through necessary actions. Originality/value– The suggested approach to KM reliability assessment is a novel method that provides powerful arguments for a more holistic view of KM reliability factors, which is crucial for the successful implementation of KM. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Aslib Journal of Information Management Emerald Publishing

Knowledge management reliability assessment: an empirical investigation

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
2050-3806
DOI
10.1108/AJIM-08-2014-0109
Publisher site
See Article on Publisher Site

Abstract

Purpose– A perfect knowledge management (KM) initiative is one that achieves its objectives without any failure during a pre-defined period. However, KM implementation is not perfect in every organization as it requires substantial changes in organizational infrastructures, including culture, structure, and technology. Therefore, the purpose of this paper is to propose a model for assessing the reliability of KM to help organizations evaluate their ability to implement KM successfully by identifying key reliability variables, modeling the complex interaction structure among variables, and determining the probability of failure for each KM capability. Design/methodology/approach– In this study, relevant variables are identified by a thorough analysis of related references in literature. In order to determine the compound structure of complicated interactions among variables, a group-based approach is utilized. Based on the combined cognitive maps, a cognitive network is constructed as a framework for graphically representing the logical relationships between variables and capturing the uncertainty in the dependency among these variables using conditional probabilities. The applicability of the proposed approach and the efficacy of the model was verified and validated with data from a banking institution. Findings– Results show that KM reliability can be defined by the degree to which required KM capabilities, including infrastructure and process capabilities, have the ability to perform as intended in a certain organizational environment. Furthermore, it is demonstrated that reliability assessment of KM through a hybrid approach of fuzzy cognitive map and Bayesian network is possible and useful. Practical implications– The proposed reliability assessment model facilitates the process of understanding why and how failures occur in KM. Moreover, the proposed approach evaluates the probability of success for each variable as well as for the entire KM initiative. Therefore, it can provide insight for managers and executives into the degree of reliability for their existing KM and prevention of failures in vital factors through necessary actions. Originality/value– The suggested approach to KM reliability assessment is a novel method that provides powerful arguments for a more holistic view of KM reliability factors, which is crucial for the successful implementation of KM.

Journal

Aslib Journal of Information ManagementEmerald Publishing

Published: Jul 20, 2015

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