A Framework for Knowledge Based Software Service Supply Chain (SSSC): A Comparative Analysis with Existing Frameworks

0Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.

Abstract

Knowledge management adoption in the supply chain (SC) is at its infancy and related scholarly research is relatively scarce. The main difficulties are in figuring out how to combine knowledge management concepts with the SC development process, to improve the overall steps, performance and productivity of the SC. The purpose of this paper is to test and analyse the existing knowledge based SCs frameworks in the literature (including manufacturing, service and software SCs), and verify how they integrate with the knowledge management concepts, taking into consideration some parameters including lessons learned, etc. which we believe, hinder such knowledge process in the existing frameworks. To come up with the proposed framework, we conducted an extensive research on the existing frameworks to identify how they handle and transfer knowledge during the development process of the SC and how they integrate the knowledge management concepts with their frameworks. Few SC frameworks were tested to figure out their efficiency and effectiveness. Finally, after detailed comparative analysis and testing, the research suggests that the proposed framework adds value to existing research and could be adopted by SC participants as a useful knowledge based framework which could increase the SC overall speed, performance and productivity. The proposed framework consists of parameters which should be introduced for more effective SSSC operations, while the absence of major parameters (identified in this paper) makes a framework less efficient.

Cite

CITATION STYLE

APA

Baydoun, A., & El-Den, J. (2017). A Framework for Knowledge Based Software Service Supply Chain (SSSC): A Comparative Analysis with Existing Frameworks. In Procedia Computer Science (Vol. 124, pp. 205–215). Elsevier B.V. https://doi.org/10.1016/j.procs.2017.12.148

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free