Integrated decision-making framework for urban freight logistics policy-making

2019 ◽  
Vol 72 ◽  
pp. 333-357 ◽  
Author(s):  
Milena Janjevic ◽  
Desirée Knoppen ◽  
Matthias Winkenbach
1981 ◽  
Vol 33 (2) ◽  
pp. 234-252 ◽  
Author(s):  
Jerel A. Rosati

The bureaucratic politics model has achieved great popularity in the study of decision making. Yet too often the term “bureaucratic politics” is used by scholars and practitioners without clearly stating its policy application. The decision-making behavior that occurred during the Johnson and Nixon administrations for SALT I serves to illustrate many of the limits of the model. First, the decision-making structure posited by the bureaucratic politics model is not nearly as prevalent within the executive branch as is commonly assumed. Second, even where the bureaucratic politics structure is present, the decision-making process is not always one of bargaining, compromise, and consensus. Finally, the decision context and the decision participants are ignored in the model. To provide a clearer understanding of policy-making behavior, a more systematic decision-making framework is offered, which should contribute to the development of better model- and theory-building.


2021 ◽  
Vol 2042 (1) ◽  
pp. 012091
Author(s):  
Nuoa Lei ◽  
Zhu Cheng ◽  
Zhi Cao ◽  
Eric Masanet

Abstract Intelligent load scheduling is an emerging approach that has the potential to facilitate extreme sustainable data center (DC) operation. However, scarcity of straightforward tools in the public domain challenges decision makers performing quantitative analysis of the DC load planning and its potential benefits. In this work, a novel integrated decision-making framework was developed to address this issue, which provides the basis for the multi-objective optimization of carbon-, water-, and economic-intelligent load scheduling. The proposed framework was demonstrated with a case study DC in California, which showed the usefulness of the proposed framework in informing sustainable DC operations.


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