Modeling the Evolutionary Mechanism of China’s Domestic Air Transport Network
Abstract
:1. Introduction
2. Literature Review
2.1. Airport Hierarchy in the CATN
2.2. The Impact of Low-Cost Carriers on CATN
2.3. The Impact of High-Speed Rail on CATN
2.4. Methodology Modeling Network Dynamics
3. Data Considerations and Exploratory Analysis
3.1. Data
3.2. Exploratory Analysis
3.2.1. The Changes in the CATN Based on Airport Hierarchy
3.2.2. The Changes of CATN Based on Distance
3.2.3. The Impact of LCCs and HSR
4. Model Specification and SABMs
4.1. Structural Covariates
- Density effect
- Transitivity closure effect
- Betweenness effect
- Number of distances-two effect
4.2. Dyadic Covariates
- Distance effect
- LCC effect
- HSR effect
4.3. Actor Covariates
- Airport hierarchy effect
- Growing airports effect
- Emerging integrated traffic center effect
5. Results
5.1. Model Tests
5.2. Parameter Interpretation
6. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Author Name | Indicators | # Clusters | # Airports | Airport IATA Code | ||||
---|---|---|---|---|---|---|---|---|
First Tier | Second Tier | Third Tier | Fourth Tier | Fifth Tier | ||||
Mo et al. [10] | Network centrality | 3 | 146 | 4 *: PEK, PVG, SHA, CAN | 5: SZX, KMG, CTU, XIY, CKG | 137: Others | ||
Ding et al. [13] | Integrated transport hubbing | 4 | 42 | 4: PEK, PVG, SHA, CAN | 7: KMG, CTU, XIY, WUH, CKG, SHE, URC | 15: TSN, CGO, NKG, HGH, HRB, and another 10 airports | 17: SJW, TYN, FOC, HFE, HAK, and another 12 airports | |
Zhang et al. [12] | Connectivity | 3 | 69 | 3: PEK, PVG, CAN | 5: SZX, KMG, CTU, XIY, SHA | 40: CGO, HGH, URC, XMN, HRB, and another 35 airports | 21: JJN, NAY, BAV, XUZ, and another 17 airports | |
O’Connor et al. [11] | Airline supply and competition | 3 | 37 | 3: PEK, PVG, SHA, CAN | 5: SZX, KMG, CTU, XIY, CKG | 18: HGH, WUH, CSX, TAO, and another 14 airports | 15: CGQ, KHN, LHW, HET, HFE, and another 10 airports | |
This paper | Changes in population and enplanements | 5 | 127 | 3: PEK, PVG, CAN | 7: SZX, KMG, CTU, XIY, CKG, HGH, SHA | 13: NKG, WUH, TSN, XMN, CGO, and another 8 airports | 16: KWE, TNA, NNG, LHW, FOC, and another 11 airports | 88: WUX, YNT, XNN, JJN, SWA, and another 83 airports |
Statistic | 2011 | 2017 |
---|---|---|
Number of airports | 127 | 127 |
Density | 0.048 | 0.069 |
Average degree | 6.079 | 8.701 |
Existing ties | 772 | 1105 |
Changes | ||
Jaccard index | 0.439 | |
No tie: 0 → 0 | 14698 | |
New tie: 0 → 1 | 532 | |
Broken tie: 1 → 0 | 199 | |
Maintained tie: 1 → 1 | 573 |
Airport Hierarchy | Airport Number | Number of Routes Per Airport | Share of Number of Routes Per Airport | ||||
---|---|---|---|---|---|---|---|
2011 | 2017 | Change (%) | 2011 | 2017 | Change (%) | ||
First Tier | 3 | 63 | 66 | 4.8 | 40.2 | 34.1 | −15.2 |
Second Tier | 7 | 42 | 54 | 28.6 | 27.0 | 28.1 | 4.1 |
Third Tier | 13 | 27 | 38 | 40.7 | 17.5 | 20.0 | 14.3 |
Fourth Tier | 16 | 21 | 29 | 38.1 | 13.6 | 15.0 | 10.3 |
Fifth Tier | 88 | 3 | 5 | 66.7 | 1.7 | 2.8 | 64.7 |
Total | 127 | 156 | 193 | 23.7 | 100.0 | 100.0 | 0.0 |
Distance Type (km) | Number of Routes | Share of Number of Routes | ||||
---|---|---|---|---|---|---|
2011 | 2017 | Change (%) | 2011 | 2017 | Change (%) | |
<=1000 | 330 | 408 | 23.6 | 42.7 | 36.9 | −13.6 |
1001–2000 | 363 | 551 | 51.8 | 47.0 | 49.9 | 6.0 |
>2000 | 79 | 146 | 84.8 | 10.2 | 13.2 | 29.1 |
Total | 772 | 1105 | 43.1 | 100.0 | 100.0 | 0.0 |
Route Type | Number of Routes | Share of Number of Routes | ||||
---|---|---|---|---|---|---|
2011 | 2017 | Change (%) | 2011 | 2017 | Change (%) | |
Routes served only by LCC | 2 | 0 | −100.0 | 0.3 | 0.0 | −100.0 |
Routes served only by HSR | 310 | 764 | 146.5 | 40.2 | 69.1 | 72.2 |
Routes served by both LCC and HSR | 36 | 107 | 197.2 | 4.7 | 9.7 | 107.7 |
Others | 426 | 234 | −45.1 | 55.2 | 21.2 | −61.6 |
Total | 772 | 1105 | 43.1 | 100.0 | 100.0 | 0.0 |
Parameters | Mode1 | Mode2 | Mode3 | Mode4 | Mode5 | Model6 | Mode7 |
---|---|---|---|---|---|---|---|
Rate parameter | 10.374 *** (0.547) | 10.095 *** (0.532) | 10.039 *** (0.511) | 9.242 *** (0.470) | 9.257 *** (0.474) | 11.589 *** (0.595) | 11.684 *** (0.604) |
Outdegree (density) | −0.967 *** (0.233) | −0.961 *** (0.156) | −0.955 *** (0.216) | −0.885 *** (0.255) | −0.890 *** (0.258) | 0.407 (0.332) | 0.358 (0.349) |
Transitive triplets | 0.204 *** (0.065) | 0.209 *** (0.039) | 0.212 *** (0.068) | 0.255 *** (0.081) | 0.255 *** (0.062) | 0.054 *** (0.019) | 0.054 *** (0.020) |
Betweenness | −0.102 (0.11) | −0.092 (0.056) | −0.086 (0.097) | −0.096 (0.122) | −0.096 (0.154) | −0.272 *** (0.049) | −0.269 *** (0.053) |
NbrDist2 | −0.129 * (0.075) | −0.139 *** (0.036) | −0.151 ** (0.074) | −0.160 ** (0.080) | −0.159 (0.108) | −0.091 *** (0.022) | −0.092 *** (0.021) |
DistanceMedium | −0.554 * (0.332) | −0.443 (0.305) | −0.502 (0.349) | −0.391 (0.371) | −0.765 * (0.450) | −0.754 * (0.419) | |
DistanceLong | −0.142 (0.497) | −0.167 (0.635) | −0.606 (0.696) | −0.552 (0.587) | −1.604 ** (0.740) | −1.605 ** (0.695) | |
LCC | −1.550 *** (0.438) | −1.522 *** (0.568) | −2.395 *** (0.857) | −3.523 *** (0.818) | −3.388 *** (0.947) | ||
HSRBothEnds | −1.362 *** (0.349) | −1.512 ** (0.641) | −3.457 *** (1.032) | −3.165 *** (0.739) | |||
LCC*HSRBothEnds | 1.388 (0.855) | 2.169 * (1.117) | 2.139 ** (0.975) | ||||
FirstTier ego | 5.226 *** (1.297) | 5.190 *** (1.226) | |||||
SecondTier ego | 6.968 *** (1.505) | 6.797 *** (1.616) | |||||
ThirdTier ego | 5.154 *** (0.984) | 5.050 *** (1.061) | |||||
FourthTier ego | 3.871 *** (0.769) | 3.720 *** (0.708) | |||||
GrowingAirports ego | 0.508 * (0.269) | ||||||
EmergingIntegratedNodes ego | 0.158 (0.167) | ||||||
Score-type tests | 4.600 * df = 2 | 15.797 *** df = 1 | 12.490 *** df = 1 | 1.303 df = 1 | 4076.540 *** df = 4 | 5.059 * df = 2 | |
Wald-type tests | 4.011 df = 2 | 8.055 *** df = 1 | 13.413 *** df = 1 | 1.726 df = 1 | 31.737 *** df = 4 | 5.000 * df = 2 | |
Overall maximum convergence ratio | 0.126 | 0.105 | 0.071 | 0.115 | 0.150 | 0.170 |
Airport Code | 2011 | 2017 | Difference |
---|---|---|---|
SJW | 7 | 25 | 18 |
PVG | 7 | 19 | 12 |
LHW | 0 | 9 | 9 |
CGQ | 0 | 9 | 9 |
SHE | 6 | 14 | 8 |
NGB | 0 | 6 | 6 |
SHA | 16 | 21 | 5 |
BHY | 0 | 4 | 4 |
Total | 38 | 107 | 69 |
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Zhang, S.; Hu, Y.; Tang, X.; Fuellhart, K.; Dai, L.; Witlox, F. Modeling the Evolutionary Mechanism of China’s Domestic Air Transport Network. Sustainability 2020, 12, 6295. https://doi.org/10.3390/su12166295
Zhang S, Hu Y, Tang X, Fuellhart K, Dai L, Witlox F. Modeling the Evolutionary Mechanism of China’s Domestic Air Transport Network. Sustainability. 2020; 12(16):6295. https://doi.org/10.3390/su12166295
Chicago/Turabian StyleZhang, Shengrun, Yue Hu, Xiaowei Tang, Kurt Fuellhart, Liang Dai, and Frank Witlox. 2020. "Modeling the Evolutionary Mechanism of China’s Domestic Air Transport Network" Sustainability 12, no. 16: 6295. https://doi.org/10.3390/su12166295
APA StyleZhang, S., Hu, Y., Tang, X., Fuellhart, K., Dai, L., & Witlox, F. (2020). Modeling the Evolutionary Mechanism of China’s Domestic Air Transport Network. Sustainability, 12(16), 6295. https://doi.org/10.3390/su12166295