# Vulnerability Analysis of a Multilayer Logistics Network against Cascading Failure
## 2 Methodology and Data
### Data  
To compare and analyze the topological properties and vulnerability of the global logistics network, the following four kinds of data are collected (from January to August 2018). (1) Container shipping data. Shipping companies with a business share of more than 1% are collected from Alphhainer (site: [[https://alphaliner.axsmarine.com/PublicTop1](https://alphaliner.axsmarine.com/PublicTop1)]([https://alphaliner.axsmarine.com/PublicTop1](https://alphaliner.axsmarine.com/PublicTop1)) 00/ (accessed on 1 January 2018)). The companies above have a containerized volume accounting for 86% of the total global container volume, which is representative. In addition, the maritime data are derived from the cities in the shipping schedule of the company's website mentioned above. In order to standardize the scope of cities, cities with 2 or more ports are combined and extracted (e.g., there are 4 container ports in Shenzhen, namely, Shekou Port, Yantian Port, Chiwan Port, and Dachan Bay, which are simplified and combined into a unified calculation for Shenzhen). (2) Air cargo data. Only the freight routes and airport cargo data are collected to measure the important relationship of freight airports in the global logistics network. The air cargo company is derived from Air Cargo World (site: [[https://aircargoworld.com/allposts/freight-50-top-50-carriers-chart/](https://aircargoworld.com/allposts/freight-50-top-50-carriers-chart/)]([https://aircargoworld.com/allposts/freight-50-top-50-carriers-chart/](https://aircargoworld.com/allposts/freight-50-top-50-carriers-chart/)) (accessed on 1 March 2018)), and the data process is the same as the shipping network. (3) Organizational structure of logistics companies data. The companies are selected according to the authoritative magazine of the North American Logistics Association, namely, Transport Topics (site: [[https://www.ttnews.com/top50/logistics/2017](https://www.ttnews.com/top50/logistics/2017)]([https://www.ttnews.com/top50/logistics/2017](https://www.ttnews.com/top50/logistics/2017)) (accessed on 1 March 2018)). The headquarters and branches of the top 50 global logistics enterprises are collected. In addition, a Taylor series chain model algorithm is introduced to research the production service industry. According to its standard of service value [54], the value matrix is constructed. (4) International trade data. Compared to the previous research estimating trade flow [55], an airport cargo and mail throughput number is introduced. This part of the data is calculated by the proportion of total merchandise trade between countries, the proportion of each city's port container throughput in the country's total number, and the proportion of each city's airport cargo and mail throughput in the country's total number. Assuming that countries have the same foreign trade goods generation coefficients, simplify the formula to:  
\[T_{ij}=TC_{uv}\cdot\frac{P_{i}}{PC_{u}}\cdot\frac{P_{j}}{PC_{p}}\cdot\frac{A_{ i}}{AC_{u}}\cdot\frac{A_{j}}{AC_{p}} \tag{17}\]where \(T_{ij}\) is the estimated value of merchandise trade (weights) from city \(i\) to country \(j\), \(TC_{uv}\) is the merchandise trade from country \(u\) to country \(v\), \(P_{i}\) is the container throughput at ports of city \(i\), \(PC_{u}\) is the total port container throughput of country \(u\), \(A_{i}\) is the cargo and mail throughput at airports of city \(i\), \(AC_{u}\) is the total airport cargo and mail throughput of country \(u\), \(U\) is the city aggregation of country \(u\), \(Z\) is the city aggregation of country \(z\).