Title :
Personalization or Codification? A Marketing Perspective to Optimize Knowledge Reuse Efficiency
Author :
Chai, Kah-Hin ; Nebus, James
Author_Institution :
Ind. & Syst. Eng., Nat. Univ. of Singapore, Singapore, Singapore
Abstract :
Organizations continue to struggle with low returns on knowledge management (KM) investments. This paper´s goal is to prescribe a KM strategy that maximizes organizational knowledge reuse efficiency (KRE). Knowledge reuse is defined as the totality of all knowledge transfers, from all producers to all consumers in the same organization, over all locations. Organizational inefficiencies result from individual knowledge producers and consumers having different priorities and agendas during the knowledge exchange. Furthermore, these producers´ and consumers´ priorities overlap with, but are not congruent with, the organization´s priorities to maximize knowledge reuse efficiency. By combining a marketing perspective with a marketing consumer stages process model of knowledge reuse, we develop a contingency model which prescribes the strategy which maximizes KRE. The organizational characteristics on which the model is contingent include organization size, the number of knowledge producers, consumers, these producer and consumer costs and utilities during the knowledge transfer, and the organization´s KM infrastructure costs. The prescribed approach specifies the degree to which a personalization and codification strategy should be combined to optimize KRE, contrary to some suggestions in the literature. A simulation supports that the model´s prescribed strategy is not overly sensitive to its contingency variables.
Keywords :
investment; knowledge management; marketing; organisational aspects; KM strategy; codification strategy; contingency model; knowledge management investment; knowledge transfers; marketing consumer stage process; marketing perspective; organizational characteristics; organizational knowledge reuse efficiency optimisation; organizational priorities; personalization strategy; Companies; Databases; Economics; Knowledge transfer; Modeling; Codification; knowledge management (KM); knowledge reuse; personalization;
Journal_Title :
Engineering Management, IEEE Transactions on
DOI :
10.1109/TEM.2010.2058855