Research on the Effective Reduction of Accidents on Operating Vehicles with fsQCA Method—Case Studies
Abstract
1. Introduction
2. Materials and Methods
2.1. Selection of Research Method
2.2. Case Selection for Research
- (1)
- Integrity. All selected cases have complete accident analysis reports with transparent accident processes, reasons, and complete information;
- (2)
- Representativeness. The accident case has attracted wide attention from society and has been published on the Ministry of Emergency Management website or other media, with significant influence;
- (3)
- Comparability. To ensure the external validity of conclusions, we should select cases that could be comparable; that is, there is heterogeneity among cases [31].
2.3. Variable Selection and Assignment
3. Results
3.1. Necessary Conditions Analysis
3.2. Portfolio Analysis of Influencing Factors
3.3. Robustness Test
4. Discussion
- Strengthen supervision over the self-employed.
- 2.
- Attaching importance to passenger transport safety.
- 3.
- Be aware of negligence and carelessness.
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Topic | Word |
---|---|
0 | prediction, model, neural network, network, method, layer, BP, value, error, degree… |
1 | road traffic, traffic, impact, death, number of people, vehicle, driver, accident, environment, lighting, … |
2 | prediction, model, road traffic, accident, impact, death, number of people, traffic, time, highway, … |
3 | accident, vehicle, traffic, driver, damage, system, car, operation, passenger vehicle, speed, … |
4 | accident, driving, death, traffic, driver, number of people, vehicle, road traffic, violation, driving experience, … |
5 | prediction, model, accident, road, desert, number of people, systems, traffic, a section of road, pavement, … |
6 | accident, death, vehicle, emergency response, driving, traffic, data, personnel, background, management, … |
7 | accident, driver, motorcycle, death, system, number of people, prediction, fuzzy, method, loss, … |
Level of Accident | Explanation | Value |
---|---|---|
Extraordinarily serious accident | Death toll ≥ 30, number of seriously injured ≥ 100, or direct economic loss ≥ CNY 100 million; | 1 |
Serious accident | 10 ≤ death toll < 30, 50 ≤ number of seriously injured < 100, or CNY 50 m ≤ direct economic loss < CNY 100 million | 0.67 |
Larger accident | 3 ≤ death toll < 10, 10 ≤ number of seriously injured < 50, or CNY 10 m ≤ direct economic loss < CNY 50 m; | 0.33 |
Ordinary accident | Death toll < 3, number of seriously injured < 10, or direct economic loss < CNY 10 m. | 0 |
Number | DE | AG | MM | BS | RG | WE | LI | AS |
---|---|---|---|---|---|---|---|---|
1 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 1 |
2 | 0 | 0 | 1 | 1 | 1 | 0 | 1 | 1 |
3 | 1 | 0 | 1 | 0 | 1 | 1 | 1 | 1 |
4 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 |
5 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 |
6 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 |
7 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 1 |
8 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
9 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 1 |
10 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 |
…… |
Antecedent Condition | Outcome Variable | |
---|---|---|
Consistency | Coverage | |
DE | 0.689594 | 0.579259 |
~DE | 0.543210 | 0.724706 |
AG | 0.635802 | 0.658748 |
~AG | 0.690917 | 0.708729 |
MM | 0.778660 | 0.744519 |
~MM | 0.585097 | 0.654339 |
BS | 0.589065 | 0.607273 |
~BS | 0.410935 | 0.423636 |
RG | 0.896825 | 0.580645 |
~RG | 0.292328 | 0.739130 |
WE | 0.470899 | 0.508571 |
~WE | 0.529101 | 0.521739 |
LI | 0.411199 | 0.564836 |
~LI | 0.719753 | 0.593837 |
Variables | T1 | T2 | T3 | T4 | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|
S1 | S2 | S3 | S4 | S5 | S6 | S7 | S8 | S9 | S10 | S11 | |
DE | * | × | * | ● | * | * | × | × | × | * | |
AG | ● | ● | ● | ⊗ | * | * | ⊗ | ⊗ | ⊗ | × | |
MM | * | ● | ● | ● | ● | * | * | × | * | * | |
BS | ⊗ | ● | ● | ⊗ | × | ● | ● | ● | ● | ● | |
RG | * | ⊗ | ⊗ | ● | * | * | * | * | * | * | * |
WE | ⊗ | × | * | ● | ● | ⊗ | ⊗ | * | × | × | * |
LI | ⊗ | ⊗ | ⊗ | ● | ⊗ | ● | ● | * | × | * | |
consistency | 1 | 1 | 1 | 1 | 0.992496 | 1 | 1 | 1 | 0.914141 | 0.859155 | 1 |
Raw coverage | 0.0458554 | 0.0440917 | 0.0348324 | 0.0662698 | 0.174956 | 0.0507055 | 0.058642 | 0.0586861 | 0.159612 | 0.13179 | 0.0821429 |
Unique coverage | 0.0458553 | 0.0185185 | 0.0282187 | 0.00886244 | 0.117725 | 0.0149912 | 0.0295414 | 0.0441358 | 0.0282628 | 0.0180776 | 0.0101852 |
Solution consistency | 0.96141 | ||||||||||
Solution coverage | 0.571208 |
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Zhang, X.; Lu, Y.; Huang, X.; Zhou, A. Research on the Effective Reduction of Accidents on Operating Vehicles with fsQCA Method—Case Studies. Appl. Sci. 2022, 12, 12737. https://doi.org/10.3390/app122412737
Zhang X, Lu Y, Huang X, Zhou A. Research on the Effective Reduction of Accidents on Operating Vehicles with fsQCA Method—Case Studies. Applied Sciences. 2022; 12(24):12737. https://doi.org/10.3390/app122412737
Chicago/Turabian StyleZhang, Xue, Yi Lu, Xianwen Huang, and Aizhao Zhou. 2022. "Research on the Effective Reduction of Accidents on Operating Vehicles with fsQCA Method—Case Studies" Applied Sciences 12, no. 24: 12737. https://doi.org/10.3390/app122412737
APA StyleZhang, X., Lu, Y., Huang, X., & Zhou, A. (2022). Research on the Effective Reduction of Accidents on Operating Vehicles with fsQCA Method—Case Studies. Applied Sciences, 12(24), 12737. https://doi.org/10.3390/app122412737