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Frontiers of Engineering Management

ISSN 2095-7513

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Front. Eng    2019, Vol. 6 Issue (3) : 327-335    https://doi.org/10.1007/s42524-019-0051-2
RESEARCH ARTICLE
Interactive effects of high-speed rail on nodal zones in a city: Exploratory study on China
Guo LIU1, Kunhui YE2()
1. School of Civil Engineering and Architecture, Anhui University of Technology, Ma’anshan 243032, China; School of Management Science and Real Estate, Chongqing University, Chongqing 400044, China
2. School of Management Science and Real Estate, Chongqing University, Chongqing 400044, China
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Abstract

The arrival of the high-speed rail (HSR) era has accelerated the pace of urban development, but its broad socioeconomic impact remains subject to intense debates. This research aims to propose a model for measuring the impact of HSR operation on HSR stations and the surrounding areas, which this research call the HSR-based nodal zone (HNZ). The proposed model is composed of two variables (i.e., transportation situation and vitality) and three subsystems (i.e., economic, societal, and environmental). Data were collected in China through questionnaire survey. Results indicate that the effects of HSR operation on HNZ are multidimensional, transportation vitality has an intermediary role in the effects, and the effects on the physical environment are negative. This study presents an early examination of the impact of HSR operation on the HSR stations and relevant areas and contributes new evidence to academic debates on the contribution of HSR to urban development. Accordingly, urban development policies should be built on the mechanism of HSR in driving the growth of HNZ.
Keywords high-speed rail      nodal zone      interactive effects      sustainable urbanization      China     
Corresponding Author(s): Kunhui YE   
Just Accepted Date: 04 July 2019   Online First Date: 05 August 2019    Issue Date: 04 September 2019
 Cite this article:   
Guo LIU,Kunhui YE. Interactive effects of high-speed rail on nodal zones in a city: Exploratory study on China[J]. Front. Eng, 2019, 6(3): 327-335.
 URL:  
https://academic.hep.com.cn/fem/EN/10.1007/s42524-019-0051-2
https://academic.hep.com.cn/fem/EN/Y2019/V6/I3/327
Fig.1  Conceptual model.
No. Effects Abbr. References
1 Condition of outward connectivity among cities OC (Willigers, 2008)
2 Condition of inward connectivity in urban IC (Hou et al., 2012)
3 Service level of public facilities (transportation) SPF (Nuworsoo and Deakin, 2009; Kager et al., 2016)
4 Travel time to other places TT (Willigers, 2008; Vickerman, 2015)
5 Transportation cost to other places TC (Gargiulo and Ciutiis, 2010)
6 Passenger volume PV (Cascetta et al., 2011; Zhao et al., 2015)
7 Passenger structure PS ( Hong and Yao, 2016; Lu et al., 2016)
8 Degree of traffic congestion DTC (Loukaitou-Sideris et al., 2012)
9 Cultural diversity of inhabitants CD (Hiroshi, 1994; Yang and Sun, 2014)
10 Population of permanent residents PPR (Zhuang and Zhao, 2014)
11 Crime rate CR (Geng et al., 2015)
12 Structure of employment SE (Bollinger and Ihlanfeldt, 1997)
13 Rate of employment RE ( Hiroshi, 1994; Loukaitou-Sideris et al., 2012; Schuetz, 2015)
14 Household income FI (Loukaitou-Sideris et al., 2012)
15 Government revenue GR (Zhuang and Zhao, 2014)
16 Intensity of land development ILD (Loukaitou-Sideris et al., 2012)
17 Structure and layout of industries SLI (Nuworsoo and Deakin, 2009; Wang, 2015; Lu et al., 2016)
18 Values of real estate (e.g., house and land) VRE (Gargiulo and Ciutiis, 2010; Diao et al., 2017)
19 Electromagnetic radiation ER (Geng et al., 2015)
20 Noise pollution NP (Bertolini et al., 2005)
Tab.1  Preliminary variables on the effects of HSR on HNZ
Latent variables Observed variables
TS OC, IC, SPF
TV TT, TC, PV, PS, DTC
SS CD, PPR, SE, RE, FI, CR
EcS GR, ILD, SLI, VRE
EnS ER, LP, NP, LCB
Tab.2  Categorization of the variables
Respondents’ information Groups Number Percent
Profession Staff and related personnel 24 17%
Government officials 18 13%
Business or service persons 16 11%
Professionals and technicians 60 42%
Others 25 17%
General purpose for using HSR Travel 22 13%
Business trip 14 10%
Visiting relatives or friends 40 28%
Consumption and visiting families or friends 1 1%
Consumption and travel 1 1%
Travel and visiting families or friends 23 16%
Business trip and consumption 1 1%
Business trip and traveling 9 6%
Business trip, travel, consumption, and visiting families or friends 2 1%
Business trip, travel, and visiting families or friends 21 15%
Business trip and visiting families or friends 9 6%
Average trip by HSR per year Less than 2 times 44 31%
3–6 times 56 39%
7–10 times 19 13%
11–14 times 7 5%
More than 15 times 17 12%
Main function of HNZ Traffic distribution 109 76%
Economic development 21 15%
Image promotion of the city 13 9%
Time taking from dwelling place to HSR station by public bus Less than 15 min 7 5%
16–30 min 34 24%
31–45 min 20 14%
46–60 min 34 24%
61–75 min 2 1%
76–90 min 7 5%
More than 90 min 5 3%
None HSR station 34 24%
Tab.3  Details of the respondents
Variables All TS TA EnS SS EcS
Cronbach’s alpha values 0.926 0.777 0.826 0.902 0.875 0.848
Tab.4  Reliability test of the questionnaire responses
Goodness of fit measure Index Criteria
CMIN/DF 1.393 <5.00
Absolute fit
RMSEA 0.053 <0.08
SRMR 0.049 <0.05
Incremental fit
CFI 0.964 >0.90
TLI 0.957 >0.90
Parsimonious fit
PNFI 0.735 >0.50
PGFI 0.654 >0.50
Tab.5  Results of goodness of fit
Direct effect path Coefficient Indirect effect path Coefficient
TS→TV 0.93 TS→EnS→TV 0.05
TS→EnS 0.21 TS→EnS→SS 0.06
TV→SS 0.40 TS→TV→SS 0.37
TV→EcS 0.41 TS→EnS→TV→SS 0.02
EnS→TV 0.22 TS→TV→EcS 0.38
EnS→SS 0.28 TS→TV→SS→EcS 0.21
SS→EcS 0.56 TS→EnS→SS→EcS 0.03
TS→EnS→TV→EcS 0.02
TS→EnS→TV→SS→EcS 0.01
TV→SS→EcS 0.22
EnS→TV→SS 0.09
EnS→TV→EcS 0.09
EnS→SS→EcS 0.16
EnS→TV→SS→EcS 0.05
Tab.6  Paths and coefficients of the model
Fig.2  Results of the model exploration.
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