An Extension of the Theory of Planned Behavior to Model Pedestrians’ Violating Crossing Behavior

摘要

　　This study aims to examine pedestrians' self-reported violating crossing BehaviorIntentions by applying the theory of planned behavior (TPB).The Behavior Intentions werestudied in relation to Instrumental Attitude, Subjective Norm and Perceived Behavioral Control,which were the basic components of TPB.Other factors were also added, includingDescriptive Norm, Perceived Risk and Conformity Tendency to investigate specifically theirimpact on pedestrians' Behavior Intentions as an extension of the TPB.Two questionnaireswere developed with different scenarios: the first scenario where pedestrians jaywalk in themiddle of the block and the second scenario where pedestrians cross the road violating thepedestrian lights at an intersection.Each item in the questionnaire was measured on a 7-pointLikert scale.The survey was conducted in the city of Dalian in China, and a total of 499 validsamples were collected, 239 for the first scenario and 260 for the second scenario.Reliabilityand validity of the data set for each scenario were evaluated.The data was analyzed using thestructural equation modeling (SEM), in which four models were built for each scenario andestimated using the maximum likelihood method.For both scenarios, the results show thatpeople has a negative attitude towards pedestrians' crossing behavior in a risky way, They alsoperceived social influences from family and friends, and they have the belief that this kind ofrisky behavior would lead them to an accident and probably they would get injured or theirlives would be endangered.For Scenario 1, results reveal that Instrumental Attitude is thestrongest predictor followed by Subjective Norm.Conformity Tendency has shown to be asignificant predictor of pedestrians' behavior after its addition in the model.Perceived Risk wasnot found to be a significant predictor indicating that Chinese pedestrians don't perceive therisk in this type of crossing behavior.For Scenario 2 the results also show that InstrumentalAttitude is the strongest predictor followed by Descriptive Norms.Once Conformity Tendencyis added to the model this construct becomes the strongest predictor showing that the presenceof other pedestrians influence behavioral intention.Perceived risk was not significant until theaddition of Conformity Tendency.In both scenarios, Perceived Behavioral Control was notsignificant in any of the models under consideration of the study.In addition to the results, theanalysis with regards to the similarities and differences found in two scenarios would help todesign a better intervention, such as changing people's attitude toward this behavior in order toreduce pedestrians' causalities or fatalities.Given the welfare implication of planned behaviorto predict pedestrian's causalities, the Government should vigorously pursue prudent policiesconducive to minimize causalities, commit to a developed strategic plan to secure the safety ofpedestrians and increase their welfare output.
　　Key Words:pedestrian;violating road-crossing behavior;theory of planned behavior;traffic safety;structural equation modeling (SEM)

目录

声明

Abstract

1 Introduction

1．1 Background

1．2 Objectives of the Study

1．3 Research Models and Hypotheses

1．4 Scope and Limitations of the Study

1．5 Organization of the Study

2 Literature Review

2．1 Theory of Planned Behavior

2．1．1 Attitude

2．1．2 Social Norms-Subjective Norm and Descriptive Norm

2．1．3 Perceived Behavioral Control

2．1．4 Conformity Tendency

2．2 Health Belief Model

3 Introduction to Behavioral Theories

3．1 Expectancy-Value Theory

3．2 Theory of Planned Behavior

3．2．1 Components of Theory of Planned Behavior

3．2．2 Descriptive Norm and Conformity Tendency

3．2．3 Model

3．3 Health Belief Model

3．3．1 Components of the Health Belief Model

4 Methodologies

4．1 Questionnaire Design

4．1．1 Preliminary Survey and Analysis Technique

4．1．2 Questionnaire Content

4．2 Data Collection

4．2．1 Sample Size

4．2．3 Sampling Approach

4．3 Data Analysis

4．3．1 Data Screening

4．3．2 Validity and Reliability

4．4 Structural Equation Modeling

4．4．1 Latent and Observed Variables

4．4．2 Indexes to assess the goodness-of-fit

4．4．3 Models

5 Results

5．1 Descriptive Statistics

5．1．1 Scenario 1-Non-intersection

5．1．2 Scenario 2-Intersection

5．2 Data Reliability

5．2．1 Cronbach’s alpha (α) for Scenario 1 Non-intersection

5．2．2 Cronbach’s alpha (α) for Scenario 2 Intersection

5．3 Data validity

5．3．1 Correlation for Scenario 1-Non-intersection

5．3．2 Correlation for Scenario 2-Intersection

5．4 Analysis of the model

5．4．1 Scenario 1-Non-intersection

5．4．2 Scenario 2-Intersection

6 Discussions

6．1 Predictors of behavioral intention

6．2 Implications of developing road safety interventions

6．3 Direction for future study

Conclusions

References

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Acknowledgement