MATEC Web Conf.
Volume 343, 202110th International Conference on Manufacturing Science and Education – MSE 2021
|Number of page(s)||11|
|Section||Management and Economic Engineering|
|Published online||04 August 2021|
Proactive risk assessment via fuzzy approach in a decisional process of consignment stock program adoption
University of Oradea, Engineering and Management Department, 1 Universitătii str., Oradea, Romania
* Corresponding author: email@example.com
The idea of adopting the consignment stock concept has enriched the landscape of efficient supply chains and their organizations, due to its major benefits in reducing inventory, compressing delivery time and increasing flexibility towards achieving agility and enhanced market responsiveness. The decision making process is a complex one, as besides the benefits and the economical and administrative aspects, there are also risks that must be identified, measured, assessed and managed. There is little research in the literature concerning the risks and constraints of consignment inventory implementation, while consignment contracts are widely applied in both physical and virtual supply chains. This paper introduces a model of proactive risk assessment via a fuzzy approach, allowing a sensitivity analysis of the identified risks in the matrix, in terms of probability to happen, degree of severity, impact and potential consequences, as well as mitigation. A fuzzy inference system is used to serve as assessment instrument, to fairly and more rigorously evaluate the risks, in order to avoid critical situations during or after program adoption, or even implementation failure. Fuzzy logic theory has been chosen to capture the uncertainty that usually occurs when dealing with risks and decision making. We believe that having these risk assessment insights at hand, managers and practitioners can achieve a better understanding of the challenges that come along with a new consignment program adoption, while allowing them to make the right and justified decision, in accordance with both benefit and risk considerations.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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