Application and Comparison of LISREL and Neural Networks in Analyzing Passengers' Behavioral Intentions

Causal model is one of the most powerful instruments in consumer behavioral intention research. LISREL and neural networks have recently become the popular method to perform the causal model. In order to recognize the differences between LISREL and neural networks methods in passengers' behavioral intentions research, this paper applied and discussed these two methods in theory and practice. The paper took passengers of intercity buses on national freeways as samples. First, this study applied LISREL to test the goodness of fit of research model. Then two kinds of NN model which one is the full connected network and the other is non-full connection network were tested. The results indicated that LISREL can be a convenience and effective analysis tool while the causal relationships were known. On the other hand, no matter the causality was derived out in advance, NN still has suitable prediction after the proper training procedure. At last, we proposed our conclusions and suggestions based on our study results.

• Corporate Authors:

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Hu, Kai-Chieh
• Conference:
  • Transportation Research Board 85th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2006-1-22 to 2006-1-26
• Date: 2006

Language

• English

Media Info

• Media Type: CD-ROM
• Features: Figures; References; Tables;
• Pagination: 14p
• Monograph Title: TRB 85th Annual Meeting Compendium of Papers CD-ROM

Subject/Index Terms

• TRT Terms: Applications; Behavior; Bus transit; Consumer behavior; Neural networks; Passenger service; Passengers; Samples; Systems engineering; Transportation planning
• Subject Areas: Administration and Management; Highways; Passenger Transportation; Planning and Forecasting; Public Transportation; Research; I10: Economics and Administration;

Filing Info

• Accession Number: 01023150
• Record Type: Publication
• Report/Paper Numbers: 06-1354
• Files: TRIS, TRB
• Created Date: Mar 3 2006 10:39AM