考虑个人偏好的观赛人群组合决策选择行为

doi:10.13229/j.cnki.jdxbgxb.20220675

Abstract

Abstract:

Understanding the travel behavior characteristics of spectators is the key to solve the problem of the surge in traffic during the event and ensure the normal operation of urban traffic. Combining the 954 survey samples of the individual attributes， travel characteristics， spectators behavior characteristics and travel intention of the spectators， a structural equation model （SEM） can describe the causal relationship between four latent variables and eleven obvious variables from the perspectives of safety， convenience， economy and travel intention. Considering the potential impact of personal preference in the combined departure time decision and travel mode chosen behavior， a SEM Nested Logit（SEM-NLogit）model is developed to investigate the combined decision-choice behavior of spectators. The results show that the developed SEM-NLogit model has the best fit and accuracy， and the prediction accuracy is 87.06%， which is 6.99% and 18.18% improvement compared to the NLogit and multivariate logit models respectively. Moreover， the findings show that the elders prefer to departure early， more companions， higher income， more likely to choose a car to travel， and the spectators more emphasis on safety and economy when traveling， which is the findings that NLogit model cannot obtain， but it is more in line with the actual travel law.

Key words: urban traffic, large-scale events, combined decision-choice behavior, nested Logit model, structural equation model

CLC Number:

U491.1

Zhi-hua XIONG,Dai-yue DONG,Chun-jiao DONG,Yan ZHENG,Chao XIE. Combined decision-choice behavior of spectators considering personal preferences[J].Journal of Jilin University(Engineering and Technology Edition), 2024, 54(4): 979-986.

Figures/Tables 9

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潜变量	观测变量	公共交通		小汽车
潜变量	观测变量	均值	标准差	均值	标准差
安全性	对出行安全性的满意程度（A1）	4.70	0.59	4.35	0.77
安全性	对运行平稳的满意程度（A2）	4.41	0.84	4.45	0.71
便捷性	对出行换乘便捷的满意程度（B1）	4.65	0.63	4.42	0.77
	对出行准时性的满意程度（B2）	4.64	0.63	4.25	0.84
	是否受气候影响小（B3）	4.68	0.61	4.27	0.85
经济性	对出行行程时间的满意程度（J1）	4.52	0.75	4.45	0.71
经济性	对出行费用/票价的满意程度（J2）	4.67	0.60	3.88	1.09
出行意向	是否低碳环保（C1）	4.71	0.60	3.87	1.11
出行意向	是否经常使用该种出行方式（C2）	4.63	0.67	4.23	0.92

模型	Log likelihood	LL（β）	LL（0）	K	LR test for IIA Prob > chi2
SEM?NLogit	-1 007.944 5	-1 571	-2 006	30	0.000 5
NLogit	-1 263.215 3	-1 941	-2 327	30	0.000 0
多元Logit	-1 263.215 3	-2 031	-2 369	55	/

显变量	影响变量	安全性A		便捷性B		经济性J		出行意向C
显变量	影响变量	路径系数	P>\|z\|	路径系数	P>\|z\|	路径系数	P>\|z\|	路径系数	P>\|z\|
观赛特征	观赛项目	0.088	0.011	0.088	0.006	0.060	0.005	0.081	0.015
观赛特征	观赛次数	/	/	/	/	0.076	0.000	/	/
出行特征	同伴数量	0.081	0.020	0.108	0.001	0.084	0.000	0.063	0.063
	出行时间	/	/	/	/	0.164	0.000	/	/
	出行费用	0.107	0.000	0.204	0.000	0.784	0.000	0.264	0.000
个人属性	性别	0.166	0.000	0.120	0.000	0.116	0.000	0.102	0.001
	受教育程度	0.330	0.000	0.231	0.000	0.217	0.000	0.234	0.000
	年龄	/	/	/	/	0.109	0.000	/	/
	小汽车拥有量	/	/	/	/	0.066	0.003	/	/
	乘坐公共交通频率	0.124	0.004	0.098	0.003	0.098	0.000	0.124	0.000

影响因素	SEM?NLogit		NLogit
影响因素	系数	p>\|z\|	系数	p>\|z\|
出行时间	0.07	0.000	0.04	0.000
出行费用	-0.11	0.000	-0.15	0.000
安全性	-0.23	0.002	/	/
便捷性	-0.29	0.003	/	/
经济性	-0.07	0.000	/	/
出行意向	-0.02	0.000	/	/

影响因素	SEM-NLogit				NLogit
	赛前1 h		赛前1~2 h		赛前1 h		赛前1~2 h
	系数	p>\|z\|	系数	p>\|z\|	系数	p>\|z\|	系数	p>\|z\|
观赛次数	-0.01	0.003	-0.03	0.006	-0.04	0.007	-0.03	0.049
年龄	-0.30	0.024	/	/	/	/	/	/
性别	0.28	0.004	0.36	0.030	0.22	0.005	0.36	0.043

Combined decision-choice behavior of spectators considering personal preferences

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