Investigating the Impacts of Urban–Rural Bus Service Quality on Rural Residents’ Travel Choices Using an SEM–MNL Integration Model
Abstract
:1. Introduction
2. Literature Review
2.1. The Quality of Public Transportation Services
2.2. Travel-Mode-Choice Behavior
3. Methodology
3.1. Questionnaire Design
- The socio-demographic characteristics of rural residents include gender, age, occupation, education level, monthly income, and private car ownership.
- The urban–rural travel characteristics survey mainly includes rural residents’ urban–rural travel mode, urban–rural travel distance, and urban–rural travel frequency.
- To evaluate rural residents’ satisfaction, the survey covered six latent variables reflecting the comfort, convenience, safety, reliability, economy, and facility completeness of urban–rural bus service quality. Twenty-two corresponding observed variables were selected to quantify the latent variables. The specific measurement scale is shown in Table 2. All the indicators were measured with a 5-point Likert scale (1 = very dissatisfied, 2 = dissatisfied, 3 = neutral, 4 = satisfied, and 5 = very satisfied).
- The actual service level of urban–rural buses and the expectations of rural residents were investigated, including the ticket price, waiting time, and walking time from home to the stop. In addition, rural residents’ current monthly urban and rural bus trips and future travel intentions were also investigated. It should be noted that these surveys were designed to better understand the subjective intentions of rural residents and were not considered in the model.
3.2. Study Area and Data Collection
3.3. Framework of the SEM–MNL Integration Model
3.4. Solution Method of the SEM–MNL Model
4. Results
4.1. Descriptive Statistical Analysis
4.2. Analysis of Reliability and Validity
4.3. SEM Estimation Results and Analysis
4.4. Estimation Results of the SEM–MNL Model
4.5. Policy Implications
5. Discussion and Conclusions
Author Contributions
Funding
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Authors | Study Area | Observable Variables | Latent Variables (Users’ Perceptions) | Analysis Method |
---|---|---|---|---|
Han et al. [50] | Urban | Personal attributes (Gender, Age, Occupation, Education level, Income, Car ownership); Travel attributes (Travel time, Trip distance, Waiting time, Travel frequency) | Public transport service attributes (Convenience, Safety, Flexibility, Comfort, and Economy) | SEM–NL |
Si et al. [51] | Urban | Personal attributes (Gender, Age, Occupation, Education level, Income); Travel attributes (Trip purpose, Travel time, Trip distance, Waiting time, Place of departure) | Taxi service attributes (Convenience, Reliability, Safety, Comfort, and Economy) | SEM–Logit |
Shah et al. [62] | Urban | Personal attributes (Gender, Age, Income, Vehicle ownership); Travel attributes (Distance to the mode, Trip purpose, Trip time, Trip cost) | Public transport and private vehicles service attributes (Comfort and Convenience, Safety and Security, Service and Facilities, Attraction and quality of riding) | Integrated Choice and Latent Variable (ICLV) model |
Chen and Li [63] | Urban | Personal attributes (Gender, Occupation, Vehicle ownership); Mode attributes (Travel cost) | Public transport service attributes (Convenience, Personal safety, Modal comfort, Service environment, and Waiting feelings) | Integrated SEM and Discrete Choice Model (SEM–DCM) |
Akpan et al. [57] | Rural | Personal attributes (Gender, Age, Income, Household size); Ownership and use of means of transportation; Travel days and cost of trips | — | MNL |
Mattson et al. [58] | Rural | Personal attributes (Gender, Age, Income); Travel attributes (Disability, Trip purpose, Party size); Mode attributes (Travel time, Travel price, Access distance, Service frequency) | — | Mixed Logit Model |
Ao et al. [59] | Rural | Personal attributes (Gender, Age, Hukou type, Education level); Family attributes (Number of people working, Total household income, Number of vehicles); Travel attributes (Travel distance, Travel time, Departure time, Daily activity); Built environment (Building density, Road density, Distance to transit, Destination accessibility) | Built environment perception and preference | MNL |
Latent Variables | Measurement Variables | |
---|---|---|
Comfort (BC) | BC1 | Stable running status of bus |
BC2 | Comfortable interior environment of bus | |
BC3 | Friendly service attitude of driver | |
BC4 | Follows the prescribed route | |
BC5 | Crowdedness of the carriage | |
Convenience (TC) | TC1 | Convenience from home to bus stop |
TC2 | Convenience from bus stop to destination | |
TC3 | Ease of transfer to other transportation in the city | |
TC4 | Accessibility to other villages | |
TC5 | Convenient to carry large items | |
TC6 | Time of service provision | |
Economy (TE) | TE1 | Bus fares |
TE2 | Bus fare discounts | |
Safety (TS) | TS1 | Safety of vehicle operation |
TS2 | Safety of the interior facilities | |
TS3 | Safety of bus stop | |
Reliability (TR) | TR1 | Waiting time |
TR2 | Punctuality rate | |
TR3 | Travel time on bus | |
Facility Completeness (CF) | CF1 | Adequacy of bus stop facilities |
CF2 | Adequacy of bus interior facilities | |
CF3 | Release and inquiry of bus operation information |
Attribute Category | Variable | Category | Percentage | Variable | Category | Percentage |
---|---|---|---|---|---|---|
Socio-demographic characteristics | Gender | Male | 33.2% | Occupation | Student | 14.5% |
Female | 66.8% | Peasant | 47.8% | |||
Age | <18 | 11.1% | Migrant worker | 12.1% | ||
18–30 | 7.6% | Commuter | 9.5% | |||
30–50 | 74.2% | Others | 16.1% | |||
≥50 | 7.1% | Education level | Junior high school and below | 59.7% | ||
Average monthly income (CNY) | <2000 | 53.3% | Senior high school | 26.1% | ||
2000–4000 | 31.7% | Junior College or above | 14.2% | |||
4000–6000 | 11.4% | Private car ownership | No | 41.5% | ||
≥6000 | 3.6% | Yes | 58.5% | |||
Urban–rural travel characteristics | Monthly travel frequency | 0 | 38.6% | Travel distance | <20 km | 34.3% |
1–2 | 41% | 20–30 km | 40.5% | |||
3–4 | 12.8% | ≥30 km | 25.3% | |||
>5 | 7.6% |
Variables | Items | Cronbach α | CR | AVE | Variables | Items | Cronbach α | CR | AVE |
---|---|---|---|---|---|---|---|---|---|
BC | BC1 | 0.787 | 0.798 | 0.523 | TE | TE1 | 0.728 | 0.729 | 0.573 |
BC2 | TE2 | ||||||||
BC3 | TS | TS1 | 0.835 | 0.837 | 0.631 | ||||
BC4 | TS2 | ||||||||
BC5 | TS3 | ||||||||
TC | TC1 | 0.828 | 0.832 | 0.534 | TR | TR1 | 0.779 | 0.783 | 0.547 |
TC2 | TR2 | ||||||||
TC3 | TR3 | ||||||||
TC4 | CF | CF1 | 0.818 | 0.821 | 0.605 | ||||
TC5 | CF2 | ||||||||
TC6 | CF3 |
Path | Standardized Path Coefficient | Path | Standardized Path Coefficient |
---|---|---|---|
BC ⟷ TS | 0.588 | TS ⟷ TE | 0.652 |
BC ⟷ TE | 0.617 | TS ⟷ TR | 0.734 |
BC ⟷ CF | 0.545 | TS ⟷ CF | 0.784 |
BC ⟷ TC | 0.669 | TS ⟷ TC | 0.609 |
BC ⟷ TR | 0.638 | TE ⟷ TR | 0.791 |
TR ⟷ CF | 0.819 | TE ⟷ CF | 0.734 |
TR ⟷ TC | 0.828 | TE ⟷ TC | 0.797 |
CF⟷ TC | 0.718 |
Evaluation Index | RMSEA | CFI | TLI | SRMR | |
---|---|---|---|---|---|
Fit Criteria | <3 | <0.08 | >0.9 | >0.9 | <0.08 |
Test Results | 2.675 | 0.054 | 0.944 | 0.936 | 0.046 |
Path | Standardized Coefficients | Standard Error (S.E.) | Critical Ratio (C.R.) | p-Value |
---|---|---|---|---|
OS ← Gender | 0.532 | - | - | - |
OS ← Age | −0.149 | 0.042 | −4.394 | *** |
OS ← Income | −0.187 | 0.038 | −5.831 | *** |
OS ← Occupation | −0.137 | 0.024 | −3.814 | *** |
OS ← Education level | −0.115 | 0.042 | −2.968 | *** |
OS ← Travel mode | 0.083 | 0.038 | 2.421 | 0.015 ** |
Path | Standardized Coefficients | Standard Error (S.E.) | Critical Ratio (C.R.) | p-Value |
---|---|---|---|---|
BC ← OS | 0.712 | - | - | - |
TS ← OS | 0.753 | 0.098 | 11.024 | *** |
TE ← OS | 0.871 | 0.109 | 11.577 | *** |
TR ← OS | 0.939 | 0.116 | 11.918 | *** |
CF ← OS | 0.835 | 0.135 | 11.683 | *** |
TC ← OS | 0.902 | 0.114 | 9.716 | *** |
BC1 ← BC | 0.702 | - | - | - |
BC2 ← BC | 0.706 | 0.068 | 14.791 | *** |
BC3 ← BC | 0.794 | 0.068 | 16.177 | *** |
BC4 ← BC | 0.545 | 0.069 | 11.698 | *** |
BC5 ← BC | 0.559 | 0.070 | 11.963 | *** |
TS1 ← TS | 0.750 | - | - | - |
TS2 ← TS | 0.815 | 0.060 | 18.655 | *** |
TS3 ← TS | 0.817 | 0.057 | 18.702 | *** |
TE1 ← TE | 0.744 | - | - | - |
TE2 ← TE | 0.771 | 0.068 | 15.974 | *** |
CF1 ← CF | 0.761 | - | - | - |
CF2 ← CF | 0.813 | 0.050 | 19.054 | *** |
CF3 ← CF | 0.760 | 0.049 | 17.831 | *** |
TC1 ← TC | 0.527 | - | - | - |
TC2 ← TC | 0.715 | 0.101 | 11.679 | *** |
TC3 ← TC | 0.713 | 0.103 | 11.598 | *** |
TC4 ← TC | 0.711 | 0.100 | 11.641 | *** |
TC5 ← TC | 0.640 | 0.098 | 11.010 | *** |
TC6 ← TC | 0.667 | 0.090 | 11.267 | *** |
TR1 ← TR | 0.720 | - | - | - |
TR2 ← TR | 0.785 | 0.060 | 17.266 | *** |
TR3 ← TR | 0.711 | 0.055 | 15.757 | *** |
Variable | MNL | SEM–MNL | ||||||
---|---|---|---|---|---|---|---|---|
Non-Motorized Vehicles | Urban–Rural Bus | Non-Motorized Vehicles | Urban–Rural Bus | |||||
Coefficient | OR | Coefficient | OR | Coefficient | OR | Coefficient | OR | |
Constant | 2.447 *** | 11.55 | 1.341 * | 3.824 | 2.284 ** | 9.815 | −1.008 | 0.365 |
Gender | 0.075 | 1.078 | −0.507 * | 0.602 | 0.074 | 1.077 | −0.520 * | 0.594 |
Age | 0.066 | 1.068 | −0.061 | 0.940 | 0.076 | 1.080 | −0.006 | 0.994 |
Occupation | −0.074 | 0.929 | 0.005 | 1.005 | −0.073 | 0.929 | 0.016 | 1.016 |
Income | −0.156 | 0.856 | −0.368 ** | 1.445 | −0.148 | 0.863 | −0.378 ** | 1.460 |
Education level | −0.494 ** | 0.610 | 0.043 | 1.044 | −0.492 ** | 0.611 | 0.137 | 1.147 |
Private car ownership | −0.269 | 0.764 | −3.384 *** | 0.034 | −0.277 | 0.758 | −3.437 *** | 0.032 |
Travel distance | −1.435 *** | 0.238 | −0.643 *** | 0.526 | −1.452 *** | 0.234 | −0.672 *** | 0.511 |
Travel frequency | 0.631 *** | 1.880 | 0.465 *** | 1.592 | 0.624 *** | 1.867 | 0.437 ** | 1.548 |
Overall satisfaction | - | - | - | - | 0.055 | 1.057 | 0.690 ** | 1.993 |
LR chi2 | 365.26 | 373.23 | ||||||
Prob > chi2 | 0.0000 | 0.0000 | ||||||
Pseudo R | 0.2890 | 0.2953 | ||||||
Log likelihood | −449.354 | −445.369 |
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Cui, H.; Li, M.; Zhu, M.; Ma, X. Investigating the Impacts of Urban–Rural Bus Service Quality on Rural Residents’ Travel Choices Using an SEM–MNL Integration Model. Sustainability 2023, 15, 11950. https://doi.org/10.3390/su151511950
Cui H, Li M, Zhu M, Ma X. Investigating the Impacts of Urban–Rural Bus Service Quality on Rural Residents’ Travel Choices Using an SEM–MNL Integration Model. Sustainability. 2023; 15(15):11950. https://doi.org/10.3390/su151511950
Chicago/Turabian StyleCui, Hongjun, Mingzhi Li, Minqing Zhu, and Xinwei Ma. 2023. "Investigating the Impacts of Urban–Rural Bus Service Quality on Rural Residents’ Travel Choices Using an SEM–MNL Integration Model" Sustainability 15, no. 15: 11950. https://doi.org/10.3390/su151511950
APA StyleCui, H., Li, M., Zhu, M., & Ma, X. (2023). Investigating the Impacts of Urban–Rural Bus Service Quality on Rural Residents’ Travel Choices Using an SEM–MNL Integration Model. Sustainability, 15(15), 11950. https://doi.org/10.3390/su151511950