An intelligent model of green urban distribution in the blockchain environment

2022 ◽  
Vol 176 ◽  
pp. 105925
Author(s):  
Yan Li ◽  
Ming K. Lim ◽  
Chao Wang
Author(s):  
Mauricio Drelichman ◽  
Hans-Joachim Voth

Why do lenders time and again loan money to sovereign borrowers who promptly go bankrupt? When can this type of lending work? As the United States and many European nations struggle with mountains of debt, historical precedents can offer valuable insights. This book looks at one famous case—the debts and defaults of Philip II of Spain. Ruling over one of the largest and most powerful empires in history, King Philip defaulted four times. Yet he never lost access to capital markets and could borrow again within a year or two of each default. Exploring the shrewd reasoning of the lenders who continued to offer money, the book analyzes the lessons from this historical example. Using detailed new evidence collected from sixteenth-century archives, the book examines the incentives and returns of lenders. It provides powerful evidence that in the right situations, lenders not only survive despite defaults—they thrive. It also demonstrates that debt markets cope well, despite massive fluctuations in expenditure and revenue, when lending functions like insurance. The book unearths unique sixteenth-century loan contracts that offered highly effective risk sharing between the king and his lenders, with payment obligations reduced in bad times. A fascinating story of finance and empire, this book offers an intelligent model for keeping economies safe in times of sovereign debt crises and defaults.


2018 ◽  
Vol 150 ◽  
pp. 21-27 ◽  
Author(s):  
Jian Wei Ho ◽  
Johnson Wong ◽  
Percis Teena Christopher Subhodayam ◽  
Kwan Bum Choi ◽  
Divya Ananthanarayanan ◽  
...  

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4748
Author(s):  
Adrian Serrano-Hernandez ◽  
Aitor Ballano ◽  
Javier Faulin

Urban distribution in medium-sized cities faces a major challenge, mainly when deliveries are difficult in the city center due to: an increase of e-commerce, weak public transportation system, and the promotion of urban sustainability plans. As a result, private cars, public transportation, and freight transportation compete for the same space. This paper analyses the current state for freight logistics in the city center of Pamplona (Spain) and proposes alternative transportation routes and transportation modes in the last-mile city center distribution according to different criteria evaluated by residents. An analytic hierarchy process (AHP) was developed. A number of alternatives have been assessed considering routes and transportation modes: the shortest route criterion and avoiding some city center area policies are combined with traditional van-based, bike, and aerial (drone) distribution protocols for delivering parcels and bar/restaurant supplies. These alternatives have been evaluated within a multicriteria framework in which economic, environmental, and social objectives are considered at the same time. The point in this multicriteria framework is that the criteria/alternative AHP weights and priorities have been set according to a survey deployed in the city of Pamplona (Navarre, Spain). The survey and AHP results show the preference for the use of drone or bike distribution in city center in order to reduce social and environmental issues.


2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Hao Zhang ◽  
Liyu Zhu ◽  
Shensi Xu

Under the increasingly uncertain economic environment, the research on the reliability of urban distribution system has great practical significance for the integration of logistics and supply chain resources. This paper summarizes the factors that affect the city logistics distribution system. Starting from the research of factors that influence the reliability of city distribution system, further construction of city distribution system reliability influence model is built based on Bayesian networks. The complex problem is simplified by using the sub-Bayesian network, and an example is analyzed. In the calculation process, we combined the traditional Bayesian algorithm and the Expectation Maximization (EM) algorithm, which made the Bayesian model able to lay a more accurate foundation. The results show that the Bayesian network can accurately reflect the dynamic relationship among the factors affecting the reliability of urban distribution system. Moreover, by changing the prior probability of the node of the cause, the correlation degree between the variables that affect the successful distribution can be calculated. The results have significant practical significance on improving the quality of distribution, the level of distribution, and the efficiency of enterprises.


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