Evaluating Agility in Extended Enterprise Systems: A Transportation Network case
Mo Mansouri, Anirban Ganguly and Ali Mostashari
DOI : 10.3844/ajeassp.2011.142.152
American Journal of Engineering and Applied Sciences
Volume 4, Issue 1
Problem statement: Agility of an enterprise system is considered as its ability to adapt successfully and efficiently to unexpected changes of the environment. Agility is key in effectiveness of enterprise systems and also it is crucial in gaining competitive advantage in global market. Approach: This is particularly true in the case of an Extended Enterprise System (EES), which represents a network of interconnected enterprises. Infrastructure systems such as transportation systems are generally considered examples of an EES. Results: The efficiency of an EES generally lies in its responsiveness to the change and the ability of all its constituents in working effectively in order to achieve a common objective. As a result, agility might prove to be a very important ingredient for an EES to thrive and sustain in today’s highly complex and interrelated environment. The purpose of this study is to introduce an assessment method and a subsequent agility index to evaluate agility in a generic EES and utilize it to a selected part of the New York City transportation network. The proposed method in this research is essential for understanding the nature and quality of interaction among constituent systems and provides stakeholders with the knowledge that is necessary for agility management in an EES. The contribution of this study to the domain of management and systems science are twofold. Firstly, the proposed method is expected to be a prominent part of the available literatures on evaluating the agility of an EES. Secondly, it is applied to a transportation network case, which as an infrastructure system is considered to be a classic example of an EES. Conclusion: Findings of such research will be useful in developing network agility strategies from the governance perspective.
© 2011 Mo Mansouri, Anirban Ganguly and Ali Mostashari. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.