語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
The geography of airfares: Modeling ...
~
Cordoba, Hilton A.
FindBook
Google Book
Amazon
博客來
The geography of airfares: Modeling market and spatial forces in the U.S. airline industry.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
The geography of airfares: Modeling market and spatial forces in the U.S. airline industry./
作者:
Cordoba, Hilton A.
面頁冊數:
129 p.
附註:
Source: Dissertation Abstracts International, Volume: 76-04(E), Section: A.
Contained By:
Dissertation Abstracts International76-04A(E).
標題:
Geography. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3647553
ISBN:
9781321403893
The geography of airfares: Modeling market and spatial forces in the U.S. airline industry.
Cordoba, Hilton A.
The geography of airfares: Modeling market and spatial forces in the U.S. airline industry.
- 129 p.
Source: Dissertation Abstracts International, Volume: 76-04(E), Section: A.
Thesis (Ph.D.)--Florida Atlantic University, 2014.
This item must not be sold to any third party vendors.
The deregulation of the airline industry created a myriad of changes in the U.S. air transport system that has both defended and sparked debate on the wisdom of such policy change for over three decades. One of the promises of deregulation from its proponents in the 1970s was increased competition that would lead to a reduction in fares for consumers. Historic data and literature has indeed shown this to be to the case as average airfares have trended downward especially over the last twenty years. Nonetheless, the industry has become much more complex since deregulation in terms of pricing to the point that very sophisticated yield management computer models are used to achieve an optimum balance between load factors and price. Consequently, this has in turn translated into a haphazard experience for most air travelers in the United States; for instance, the cost of a ticket is sometimes lower traveling from coast to coast than within a particular region of the U.S. and paid fares for the exact same trip can deviate dramatically, often based on variation in the date of purchase. Additionally, this has also resulted in a spatial pattern where certain regions throughout the country have enjoyed lower airfares more so than others. This research seeks to identify this regional disparity using a geographically weighted regression and spatial autoregressive models in a sample of 6,200 routes between 80 primary U.S. airports. The results from the global model showed that variables which measure competition (airlines), operating cost (flights, distance) and elasticity (layover time) proved to be statistically significant and had a positive relationship with airfare The GWR results indicated that while some factors like distance, and hub size, were statistically significant almost nationwide, other factors such as frequency, presence of low cost carriers, and numbers of airlines were only statistically significant at certain airports. Finally, the spatial regressions models indicate that the spatial autocorrelation found in U.S. airfares resemble the first order properties of spatial autocorrelation (i.e. spatial heterogeneity) and not the second order properties (i.e. spatial dependence).
ISBN: 9781321403893Subjects--Topical Terms:
524010
Geography.
The geography of airfares: Modeling market and spatial forces in the U.S. airline industry.
LDR
:03224nmm a2200313 4500
001
1988057
005
20150716112203.5
008
150803s2014 ||||||||||||||||| ||eng d
020
$a
9781321403893
035
$a
(MiAaPQ)AAI3647553
035
$a
AAI3647553
040
$a
MiAaPQ
$c
MiAaPQ
100
1
$a
Cordoba, Hilton A.
$3
2122916
245
1 4
$a
The geography of airfares: Modeling market and spatial forces in the U.S. airline industry.
300
$a
129 p.
500
$a
Source: Dissertation Abstracts International, Volume: 76-04(E), Section: A.
500
$a
Adviser: Russell L. Ivy.
502
$a
Thesis (Ph.D.)--Florida Atlantic University, 2014.
506
$a
This item must not be sold to any third party vendors.
520
$a
The deregulation of the airline industry created a myriad of changes in the U.S. air transport system that has both defended and sparked debate on the wisdom of such policy change for over three decades. One of the promises of deregulation from its proponents in the 1970s was increased competition that would lead to a reduction in fares for consumers. Historic data and literature has indeed shown this to be to the case as average airfares have trended downward especially over the last twenty years. Nonetheless, the industry has become much more complex since deregulation in terms of pricing to the point that very sophisticated yield management computer models are used to achieve an optimum balance between load factors and price. Consequently, this has in turn translated into a haphazard experience for most air travelers in the United States; for instance, the cost of a ticket is sometimes lower traveling from coast to coast than within a particular region of the U.S. and paid fares for the exact same trip can deviate dramatically, often based on variation in the date of purchase. Additionally, this has also resulted in a spatial pattern where certain regions throughout the country have enjoyed lower airfares more so than others. This research seeks to identify this regional disparity using a geographically weighted regression and spatial autoregressive models in a sample of 6,200 routes between 80 primary U.S. airports. The results from the global model showed that variables which measure competition (airlines), operating cost (flights, distance) and elasticity (layover time) proved to be statistically significant and had a positive relationship with airfare The GWR results indicated that while some factors like distance, and hub size, were statistically significant almost nationwide, other factors such as frequency, presence of low cost carriers, and numbers of airlines were only statistically significant at certain airports. Finally, the spatial regressions models indicate that the spatial autocorrelation found in U.S. airfares resemble the first order properties of spatial autocorrelation (i.e. spatial heterogeneity) and not the second order properties (i.e. spatial dependence).
590
$a
School code: 0119.
650
4
$a
Geography.
$3
524010
650
4
$a
Economics.
$3
517137
650
4
$a
Geographic information science and geodesy.
$3
2122917
650
4
$a
Transportation.
$3
555912
690
$a
0366
690
$a
0501
690
$a
0370
690
$a
0709
710
2
$a
Florida Atlantic University.
$b
Geosciences.
$3
2096498
773
0
$t
Dissertation Abstracts International
$g
76-04A(E).
790
$a
0119
791
$a
Ph.D.
792
$a
2014
793
$a
English
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3647553
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9265624
電子資源
11.線上閱覽_V
電子書
EB
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入