Application of Structure Equation Models in Trip Behavior Analysis of Tehran Bazar Trip Makers

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Research/Original Article (دارای رتبه معتبر)
Abstract:
This paper examines the structure of traveler behavior and how it can be measured using a set of survey questions. In this context, senses of place factors were extracted using a three- tiered, structural equation model, which simultaneously estimated three factors:Attitude, Lifestyle and shopping orientation. Through this research we have been able to both transfer successful questions measuring well accepted behavior constructs and examine further place attributes contribution. However, it is necessary to further this research and the preliminary findings of this exploratory analysis. All three factors need to be verified in future studies for their ability to explain behavior, and should be examined in different everyday activity settings to compare the strength of the manifested factors across types of activities and settings. In parallel, qualitative analysis can be used to enhance the understanding of these concepts. Although several socio- demographic characteristics were shown to be attitudes, these indicators are only able to explain a small subset of the variation, and the rich nature of behavior may require more in-depth scrutiny of their formation as well as other determinants. This study is limited to behavior about one specific location studied (Bazar), and within a short period of a day’s activities. Future research should be conducted to determine if there are aspects of behavior and their development that might be predicted more completely using socio- demographic indicators. The idea of applying these variables in modeling the individual clothes shopping destination choice by using structure equation models was sourced from ethology studies on customers of shopping centers (novelty of paper). In this paper 213 samples are collected by internet- based questionnaire and individuals socio- economic, attitude, lifestyle and shopping orientation were asked. This integrated model is able to correctly predict the 68.1 percent of observation has the highest percent correct.
Language:
Persian
Published:
Journal of Transportation Research, Volume:15 Issue: 3, 2018
Pages:
1 to 13
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