A dynamic analysis of motorcycle ownership and usage: A panel data modeling approach

2012 ◽  
Vol 49 ◽  
pp. 193-202 ◽  
Author(s):  
Chieh-Hua Wen ◽  
Yu-Chiun Chiou ◽  
Wan-Ling Huang
Keyword(s):  
Panel Data ◽  
Dynamic Analysis ◽  
Data Modeling ◽  
Modeling Approach

scholarly journals Application of “panel-data” modeling to predict groundwater levels in the Neishaboor Plain, Iran

2011 ◽  
Vol 20 (3) ◽  
pp. 435-447 ◽  
Author(s):  
A. Izady ◽  
K. Davary ◽  
A. Alizadeh ◽  
B. Ghahraman ◽  
M. Sadeghi ◽  
...  
Keyword(s):  
Panel Data ◽  
Data Modeling ◽  
Groundwater Levels

Dynamic Analysis of Traveler Attitudes and Perceptions Using Panel Data

2000 ◽  
Vol 1718 (1) ◽  
pp. 52-60 ◽  
Author(s):  
Sridhar Sunkanapalli ◽  
Ram M. Pendyala ◽  
Arun R. Kuppam
Keyword(s):  
Panel Data ◽  
Policy Analysis ◽  
Dynamic Analysis ◽  
Descriptive Analysis ◽  
Puget Sound ◽  
Panel Survey ◽  
Market Segments ◽  
Attitudes And Perceptions ◽  
Similarities And Differences ◽  
Over Time

A dynamic analysis of travelers’ attitudes, preferences, and values was carried out using three waves of the Puget Sound Transportation Panel survey to investigate dynamics in traveler attitudes and perceptions. An in-depth descriptive analysis was performed to examine the variations in attitudinal ratings over time. A traditional one-way analysis of variance (ANOVA) method was used to explore for similarities and differences in traveler attitudinal ratings across different waves of the panel survey. A similar analysis was performed on the stayer sample (i.e., the respondents who participated in all three waves of the panel used in this study). The ANOVA results show significant differences in mean attitudinal ratings across the three waves of the panel survey. The differences in traveler attitudes and perceptions among stayers, dropouts (respondents who leave the panel survey), and refreshments (respondents who are newly recruited as the panel survey proceeds) were also captured. Finally, differences in traveler attitudes and preferences across different modal market segments were examined. The results indicate the need for greater consideration of attitudinal dynamics in transportation planning and policy analysis.

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