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An AHP‐based framework for selecting knowledge management tools to sustain innovation process
Author(s) -
Grimaldi Michele,
Rippa Pierluigi
Publication year - 2011
Publication title -
knowledge and process management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.341
H-Index - 44
eISSN - 1099-1441
pISSN - 1092-4604
DOI - 10.1002/kpm.365
Subject(s) - analytic hierarchy process , computer science , knowledge management , process (computing) , process management , hierarchy , set (abstract data type) , portfolio , decision support system , selection (genetic algorithm) , key (lock) , management science , operations research , business , engineering , data mining , artificial intelligence , operating system , market economy , computer security , finance , economics , programming language
This paper presents a framework based on the analytic hierarchy process (AHP) methodology to select the most appropriate set of Knowledge Management (KM) tools to support the innovation processes in organizations. The framework builds on the theoretical foundations underlying organizational KM to identify key KM processes enabling innovation. The AHP is a multi‐criteria decision support technique that can be used to analyse and compare those KM tools that best support innovation processes. Organizations can select the most suitable KM tool by using the proposed framework to identify gaps and overlaps in the extent to which the capabilities provided and utilized by their current KM tools portfolio meet the KM needs of the organization to sustain the innovation. The main contributions of this work are the list of KM processes to support an innovation activity and the hierarchy of importance of such processes able to support the selection process of a KM tool. The framework can be of use to managers and other practitioners because of its ease of implementation. An illustrative example of a case study for the application of the framework is provided. Copyright © 2011 John Wiley & Sons, Ltd.