Smart and sustainable logistics of Port cities: A framework for comprehending enabling factors, domains and goals

Mapping the global liquefied natural gas trade network: A perspective of maritime transportation

Transportation improvements affect technological and socio-economic development, and several scholars have researched various transportation problems. The current study aims to illustrate a thorough review of those transport problems, where the Analytic Hierarchic Process (AHP) is used for enumerating the related criteria and alternatives. A systematic review methodology, the PRISMA protocol, is applied in the review process. The contribution of this work is highlighted along with the extensions of the AHP improving decision-making support. To this end, current research demonstrates the relevant results of 58 papers published from 2003 to 2019. The results indicated that most researchers applied the conventional AHP method to deal with transportation issues, while the most critical issue was public transport, followed by logistics problems. On top of that, TOPSIS was integrated with AHP more than other MCDM methods when dealing with multi-criteria transportation problems. Moreover, the “Transportation Research Part A: Policy and Practice” journal achieved first place by publishing ten papers on the topic, and the highest number of articles was published in 2018. The results are discussed adequately, and in the conclusion, policy implications are presented. 

/pdf/a-systematic-review-of-analytic-hierarchy-process-3g079djq.pdf

A Systematic Review of Analytic Hierarchy Process Applications to Solve Transportation Problems: From 2003 to 2022

https://doi.org/10.1016/j.tranpol.2022.04.006

Impact of COVID-19 on China's international liner shipping network based on AIS data

The location of logistics nodes that facilitate the China Railway Express (CRexpress) and rail-sea intermodal transportation has received increasing attention in China under the Belt and Road initiative. This paper selects 38 cities as candidate Chinese international container intermodal hubs (CICIHs) through qualitative screening by considering the current operations of the CRexpress/rail-sea intermodal transportation and government planning strategies. Subsequently, five connectivity indexes are proposed to reflect the node performance considering the multiple modes and stages of transportation in a logistics chain. In view of the shortcomings of the grey relational analysis-technique for order preference by similarity to ideal solution (GRA-TOPSIS) method, a hybrid multi-criteria decision making (MCDM) model is proposed to comprehensively evaluate the hub location. The model is based on the grey area relational analysis-technique for order preference by similarity to ideal solution (GARA-TOPSIS) in combination with analytic hierarchy process, entropy method and game theory. Tianjin, Harbin, Zhengzhou, Wuhan, Chongqing, Xi’an, Urumqi, Guangzhou, Shanghai and Nanning are selected as the final CICIHs, considering the geographical location, economic development and national policy pertaining to the Belt and Road initiative. A sensitivity analysis of the index weight and preference coefficient and a comparative analysis of different MCDM methods are performed. The robustness and stability of the proposed model are verified. This study can support the location selection of CICIHs and expand the methods and applications in the decision-making field.

Hybrid MCDM Model for Location of Logistics Hub: A Case in China Under the Belt and Road Initiative

China’s 21st Century Maritime Silk Road trade initiative includes investment in international port infrastructure. Comprehensive analysis of port competitiveness is of great significance for effectively guiding the flow of such resources. Conventional models mainly consider statistical indices for port operation, while neglecting the real operational status of these ports and their position in the changing global maritime transport network. To fill this gap in existing research, we designed a comprehensive evaluation CCPE model measuring port competitiveness by 18 factors related to conditions, capacity, potential, and efficiency using big data related to the geographical environment, cargo vessels trajectories, port infrastructure, and regional socioeconomics. This model was then used to evaluate the competitiveness of 99 ports in 51 countries along the Maritime Silk Road, with several important results. First, a port’s status in the global maritime transport network was the most influential of all competitiveness indices. Second, competitive ports were mainly concentrated in the Mediterranean, the Suez Canal, and the Hormuz Strait, with Singapore, Marsaxlokk, and Algeciras ranking as the top three. The least competitive ports were mainly concentrated in East Africa, with Rangoon, Berbera, Lamu, Songkhla, Mtwara, and Sittwe ranking lowest. Third, port competitiveness was clearly polarized in that the most competitive ports stood far above all others due to significant gaps in their network status index.

Modelling the competitiveness of the ports along the Maritime Silk Road with big data

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Modelling the competitiveness of the ports along the Maritime Silk Road with big data