The use of CGE models in the evaluation of air transport policy and large-scale investment

2020 ◽  
pp. 108-128
Author(s):  
Eric Tchouamou Njoya ◽  
Peter Forsyth
Keyword(s):  
Large Scale ◽  
Transport Policy ◽  
Air Transport ◽  
Cge Models

scholarly journals Uzbekistan’s Development under the Leadership of Various Political Reforms: The Case of Air Transport Industry

2021 ◽  
Vol 15 (1) ◽  
pp. 160-169
Author(s):  
Sarvar Khalikov ◽  
Wei Liu ◽  
Madina Turaeva ◽  
Liliya Achilova
Keyword(s):  
Soviet Union ◽  
Large Scale ◽  
Russian Language ◽  
Air Transport ◽  
Transport Sector ◽  
Aviation Industry ◽  
Policy Reforms ◽  
Political Reforms ◽  
Air Transport Industry ◽  
New Perspective

The First President of Uzbekistan, Islam Karimov, continued to isolate the country for many years even after the collapse of the Soviet Union in 1991, which in turn worsened all the strategic sectors in the country, especially the aviation market and tourism industries. However, in the period 2017-2018, the skyrocket in the number of tourists, from 2.69 million to 5.34 million, became possible due to the coming of Shavkat Mirziyoyev to power as the new President. But the lack of air connectivity kept reducing aspiration of traveling from non-CIS countries. To solve the issue, the new President Mirziyoyev’s large-scale policy reforms concerned the air transport sector, too. The main objective of the study is to compare the development of the country under the leadership of various political reforms using the aviation industry of Uzbekistan as an example. To achieve the purposes, the authors examine reciprocal action/influence between airlines, airports and government. In addition, a significant amount of data was collected from Russian-language sources to enrich the content. Even though the paper was written before the COVID-19 pandemic, the authors' research is still important to nudge readers into a new perspective.

Domestic Air Transport Policy. Part I

Economica ◽  
1961 ◽  
Vol 28 (110) ◽  
pp. 156
Author(s):  
Lucien Foldes
Keyword(s):  
Transport Policy ◽  
Air Transport

scholarly journals Planning the use of helicopters in the last mile distribution process in catastrophes

2021 ◽  
Vol 28 (4) ◽  
Author(s):  
Iran Rosa Xavier ◽  
Renata Albergaria de Mello Bandeira ◽  
Leandro de Oliveira Silva ◽  
Adriano de Paula Fontainhas Bandeira ◽  
Vânia Barcellos Gouvêa Campos ◽  
...  
Keyword(s):  
Disaster Response ◽  
Large Scale ◽  
Transportation Systems ◽  
Air Transport ◽  
Earthquake Response ◽  
Multiple Products ◽  
Last Mile ◽  
Hypothetical Scenario ◽  
Distribution Process ◽  
Key Steps

Abstract: The shortage of funding, the challenging assessment of aid needs, and the lack of transportation systems for the rescue and care of victims represent major constraints to disaster response operations. In order to improve logistical performance in these conditions, including remote and large areas, this paper proposes a formal mathematical model to assist air transport planning, using helicopters, for large-scale disasters, considering multiple deposit systems, multiples vehicles and multiple products, implemented in AIMMS to evaluate its performance. To achieve the objectives, a literature review is conducted to understand the ways in which helicopters are used in aid operations and to identify key steps in decision making and modeling processes. In the end, a hypothetical scenario is created with similar characteristics from the records of earthquake response operations that hit Haiti in 2010 for consolidation and validation of the procedure.

scholarly journals Application of Nonnegative Tensor Factorization for Intercity Rail–Air Transport Supply Configuration Pattern Recognition

2019 ◽  
Vol 11 (6) ◽  
pp. 1803
Author(s):  
Han Zhong ◽  
Geqi Qi ◽  
Wei Guan ◽  
Xiaochen Hua
Keyword(s):  
Pattern Recognition ◽  
High Speed ◽  
Large Scale ◽  
Rapid Expansion ◽  
Air Transport ◽  
Tensor Factorization ◽  
Nonnegative Tensor ◽  
Data Set ◽  
Nonnegative Tensor Factorization ◽  
Supply Level

With the rapid expansion of the railway represented by high-speed rail (HSR) in China, competition between railway and aviation will become increasingly common on a large scale. Beijing, Shanghai, and Guangzhou are the busiest cities and the hubs of railway and aviation transportation in China. Obtaining their supply configuration patterns can help identify defects in planning. To achieve that, supply level is proposed, which is a weighted supply traffic volume that takes population and distance factors into account. Then supply configuration can be expressed as the distribution of supply level over time periods with different railway stations, airports, and city categories. Furthermore, nonnegative tensor factorization (NTF) is applied to pattern recognition by introducing CP (CANDECOMP/PARAFAC) decomposition and the block coordinate descent (BCD) algorithm for the selected data set. Numerical experiments show that the designed method has good performance in terms of computation speed and solution quality. Recognition results indicate the significant pattern characteristics of rail–air transport for Beijing, Shanghai, and Guangzhou are extracted, which can provide some theoretical references for practical policymakers.

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