Journal of Jilin University(Engineering and Technology Edition) ›› 2023, Vol. 53 ›› Issue (10): 2839-2846.doi: 10.13229/j.cnki.jdxbgxb.20220134

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Travel satisfaction model for air-rail integration passengers based on Bayesian network

Min YANG1,2(),Cong-wei ZHANG1,2,Da-wei LI1,2(),Chen-xiang MA1,2   

  1. 1.Jiangsu Key Laboratory of Urban ITS，Southeast University，Nanjing 211189，China
    2.School of Transportation，Southeast University，Nanjing 211189，China
  • Received:2022-02-14 Online:2023-10-01 Published:2023-12-13
  • Contact: Da-wei LI E-mail:yangmin@seu.edu.cn;lidawei@seu.edu.cn

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Abstract:

To reveal the impact of air-rail passenger perception on overall passenger satisfaction， a three-layer satisfaction index system （the target， intermediate， and indicator layers） was established. The Bayesian network model was constructed by combining GTT and EM algorithms to analyze the influence of nine categories of satisfaction. The results show that the impact of categories of satisfaction on overall satisfaction are personalization， connectivity， operation， reliability， ticketing， comfort， and information service in order of strength to weakness， while accessibility and safety have little effect on overall satisfaction. The result of cross-tabulation analysis quantitatively reflects the complex interrelationship between various indicators， and the subsequent improvement strategies is quantitatively analyzed by the IPA analysis for different indicators， concluding that the current operation frequency， baggage check-in， opening routes， and operation hours need to be improved， while the problems of transfer instructions， seat comfort， convenient ticket collection， fares， transfer quality， and information planning are over-improved.

Key words: transportation planning and management, satisfaction analysis, Bayesian network, air-rail integration, combination analysis

CLC Number: 

  • U15

Fig.1

Full-text research framework"

Table 1

Personal information board frequency statistics"

变量频率统计
性别1?男性（57.8%）；2?女性（42.2%）
年龄1?18岁及以下（5.6%）；2?19~29岁（46.5%）；3?30~39岁（25.7%）；4?40~49岁（16.4%）；5?50岁以上（5.9%）
教育 水平1?高中、中专及以下（14.9%）；2?大专及本科（57.6%）； 3?硕士及以上（27.5%）
出行 距离

1?小于500 km（13.1%）；2?500~1000 km（27.7%）；

3?1000~1500 km（29.4%）；4?大于1500 km（29.9%）

出行 成本

1?小于500元（19.6%）；2?500~800元（21.6%）；

3?800~1100元（22.5%）；4?大于1100元（36.4%）

Table 2

Descriptive statistics of ARIS perception data"

变量（代号）均值排序
到达便利性（A3）1.801
到达时间成本（A1）1.922
*可达性满意度（A）2.323
*个性化满意度（P）2.884
到达经济成本（A2）3.405
航空餐食等（P3）3.406
*运营满意度（O）3.417
出发准点率（R2）3.568
行李托运（P1）3.609
托运安全性（F2）3.6710
补救服务（R1）3.7011
安检便利性（C1）3.7012
*信息服务满意度（I）3.7213
设施舒适性（S1）3.7614
运营时段（O2）3.7815
运营班次（O3）3.7816
枢纽安全性（F1）3.7917
开通线路数（O1）3.7918
*安全性满意度（F）3.8219
*衔接性满意度（C）3.8620
换乘效率（C2）3.8921
空调温度（S3）3.8922
人工服务（P2）3.9123
*舒适性满意度（S）3.9224
联程信息规划（I2）3.9225
票价（T3）3.9326
*可靠性满意度（R）3.9327
行程安全性（F3）3.9428
换乘质量（C3）3.9629
实时信息服务（I3）3.9830
*票务服务满意度（T）4.0031
取票便捷性（T2）4.0432
换乘指示（I1）4.0433
座椅舒适性（S2）4.0934
购票效率（T1）4.1035
到达准点率（R3）4.1536
**总体满意度（ALL）1.90-

Fig.2

Bayesian network for passenger perceived satisfaction of air-rail integration"

Table 3

Weighted AUC table"

代号加权AUC值代号加权AUC值
C0.969I1.000
R0.996S0.851
T0.914P0.990
F1.000O1.000
A1.000ALL0.745

Fig.3

Sensitivity analysis of overall satisfaction"

Fig.4

Results of cross-tabulation analysis"

Fig.5

IPA of positive influence and negative influence"

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