物流与供应链管理领域的诸多问题是典型的多准则决策议题，而基于决策实验室法的网络程序分析法(DANP)在关键因素与因果关系的决定上扮演了相当重要的角色。然而，DANP在应用上通常需要发放“成对影响比较问卷”，而大量的题项很有可能降低受访者的填答意愿，也会干扰最后的研究结果分析，这一方面限制了该方法在次级数据上的使用，另一方面也让受访者承担了填写大量题项的负荷，严重限制了DANP技术的应用。因此，本书结合了灰关联分析提出称为“基于灰关联的决策实验室与网络程序分析”(GDANP)的创新决策分析方法，其具体特点即在于利用德尔菲的调查问卷或是统计数据，即可衡量准则之间的影响关系与因果关系。为彰显GDANP在供应链管理上的应用与发展潜力，本书将所提出的GDANP模型应用于两个重要的实务案例。本书理论价值和实践应用价值均较高，适合专业人员阅读。

1 Introduction
1.1 Background and Problems
1.2 Objectives
1.3 Framework and Methodologies
1.4 Structure
2 Literature Review
2.1 Supply Chain Management
2.2 Green Supply Chain Management
2.3 Green Supplier Selection for Automotive Industry
2.4 Interaction between Manufacturing and Logistics Industries
3 Research Methods
3.1 Delphi Method
3.2 DEMATEL-based ANP(DANP)
3.3 The Proposed Grey Decision-Making Method
4 Case Study for Evaluation Green Suppliers for Automotive Industry
4.1 Delphi Questionnaire Survey
4.2 Determining Key Factors Using Traditional DANP
4.3 Determining Key Factors Using the Proposed GDANP
4.4 Comparison between DANP and GDANP
4.5 Cause-Effect Analysis
4.6 Importance-Performance Analysis (IPA)
4.7 Managerial Implications
5 Case Study for Exploring Interaction between Manufacturing and Logistics Industries
5.1 Preliminary
5.2 Determining the Key Factors Using Entropy
5.3 Generating the Initial Direct Influence Matrix Using GRA
5.4 Determining the Total Influence Matrix 8
5.5 Deriving the Limiting Supermatrix
5.6 Comparison between Entropy and GDANP
5.7 Depicting the Causal Diagram
5.8 Managerial Implications
6 Discussion and Conclusions
6.1 Practical Contribution
6.2 Computational Complexity
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