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A novel credibility-based group decision making method for Enterprise Architecture scenario analysis using Data Envelopment Analysis

机译:基于数据包络分析的企业架构场景分析的基于信誉的群体决策新方法

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摘要

Analysis and selection of Enterprise Architecture (EA) scenarios is a difficult and complex decision making process directly effecting the long-term business strategies realization. This complexity is associated with contradictory objectives and significant uncertainties involved in analysis process. Although a large body of intuitive and analytical models for EA analysis has evolved over the last few years, none of them leads to an efficient and optimized ranking in fuzzy environments. Moreover, it is necessary to simultaneously employ some complementary methods to reflect the ambiguity and vagueness as the main sources of uncertainty. This paper incorporates the concept of Data Envelopment Analysis (DEA) model into EA scenario analysis through a group analysis under uncertain conditions. To resolve the vagueness and ambiguity of the EA analysis, fuzzy credibility constrained programming and p-robustness technique are applied, respectively. Not only is the proposed DEA model linear, robust, and flexible in aggregating experts' opinion in a group decision making process, but it also is successful in discrimination power improvement - a major shortcoming associated with classic DEA model. The proposed model provides useful solutions to support decision making process for large-scale Information Technology (IT) development planning. (C) 2015 Elsevier B.V. All rights reserved.
机译:企业架构(EA)场景的分析和选择是一个困难而复杂的决策过程,直接影响着长期业务战略的实现。这种复杂性与分析过程中相互矛盾的目标和重大不确定性相关。尽管在过去几年中发展了用于EA分析的大量直观和分析模型,但没有一个模型可以在模糊环境中提供有效且优化的排名。此外,有必要同时采用一些补充方法来反映模糊性和模糊性,这是不确定性的主要来源。本文通过不确定条件下的分组分析将数据包络分析(DEA)模型的概念纳入EA情景分析。为了解决EA分析的模糊性和歧义性,分别应用了模糊可信度约束编程和p-鲁棒性技术。提出的DEA模型不仅线性,鲁棒,灵活,可以在团队决策过程中聚集专家的意见,而且在歧视能力改善方面也很成功,这是经典DEA模型的主要缺点。提出的模型提供了有用的解决方案,以支持大型信息技术(IT)开发计划的决策过程。 (C)2015 Elsevier B.V.保留所有权利。

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