摘要：
In the current business environment, both managers and researchers have realized that assessing and managing risk in a supply chain operation is crucial to business success. Furthermore, the traditional assessment methodologies are unable to deal with intangible criteria which are crucial factor in the analysis. Thus, we develop an orders-of-magnitude AHP (OM-AHP) based ex-ante supply chain risk assessment model, to enable the comparison of the tangible and intangible elements that influence supply chain risks. In the application of OM-AHP method to risk assessment it also became apparent a formal guiding structure of how to pivot using OM-AHP did not exist. A formal method is proposed that can significantly reduce the number of needed comparisons and improve the consistency with pairwise comparisons matrices under any AHP decision. The process of the proposed supply chain risk assessment framework consists of three phases: risk identification, risk assessment, and risk ranking and analysis. An illustrative example is provided to demonstrate the efficacy of the proposed risk assessment framework. The results are organized in a 2-way risk matrix based on their probability and consequence severity and tested for robustness via sensitivity analysis.(C) 2016 Elsevier B.V. All rights reserved.
期刊：
European Journal of Operational Research,2016年250(2):521-530 ISSN：0377-2217
通讯作者：
Dong, Qingxing
作者机构：
[Dong, Qingxing] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.;[Cooper, Orrin] Univ Memphis, Fogelman Coll Business & Econ, Memphis, TN 38152 USA.
通讯机构：
[Dong, Qingxing] C;Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.
关键词：
Consensus reaching;Group decision making;The Analytic Hierarchy Process (AHP);Weight determination
摘要：
Consensus reaching models are widely applied in group decision making problems to improve the group's consensus level before making a common decision. Within the context of the group Analytic Hierarchy Process (AHP), a novel consensus reaching model in a dynamic decision environment is proposed. A Markov chain method can be used to determine the decision makers' weights of importance for the aggregation process with respect to the group members' opinion transition probabilities. The proposed group consensus reaching model facilitates a peer to peer opinion exchange process which relieves the group of the need for a moderator by using an automatic feedback mechanism. Moreover, as the elements in the group decision framework change in a dynamic decision making problem, this model provides feedback suggestions that adaptively adjust for each of the decision makers depending on his credibility in each round. The full process of the dynamic adaptive consensus reaching model is presented and its properties are discussed. Finally, a numerical example is given to demonstrate the effectiveness of our model.
