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In recent years, many regions including China have witnessed fast growth of dry ports. Unlike in the other regions of the world, the amount of cargos handled by most dry ports in China is not in compliance with the significant amount of resources invested, but the reasons behind have not been discussed before. After a brief review on the development pattern of Chinese dry ports, certain dry port functions like customs clearance and rail connection, dry port ownership structure, and inter-competition among dry ports are identified as the unique factors which distinguish Chinese dry ports from others and affect their performance. We investigate the relationship between these factors and the efficiency of Chinese dry ports with a two-stage approach based on a panel data collected from eight dry ports affiliated to the port of Ningbo, China, covering the 2011–2016 period. In the first stage, Data Envelopment Analysis (DEA) is used to measure these dry ports' technical efficiency. In the second stage, Tobit regression analysis is applied to explore the relationship between efficiency and the above mentioned factors. Several insightful findings are observed, further leading to useful managerial insights. • The unique features in development of Chinese dry ports are discussed. • Impacts of these features on dry ports' efficiency are empirically examined. • Provision of customs service implies low efficiency at dry ports. • Seaport's ownership may not be beneficial to dry ports and local economy. [ABSTRACT FROM AUTHOR]

This study proposes high-frequency container port congestion measures based on Automatic Identification System (AIS) data. Vessel movement information of 3,957 container ships from March 2017 to April 2017 is included. The world top 20 container ports' berth and anchorage areas are identified through Density Based Spatial Clustering of Applications with Noise (DBSCAN) and convex hull methods, and their hourly port congestion statuses are depicted in terms of the traffic volume and turnaround time. The constructed congestion measures overcome the disadvantages of the traditionally used port or industry data, which is heterogenous, behind the time and not easy to obtain publicly. The higher frequency (hourly) of the proposed measures can effectively monitor any slight change in port performance. A Long Short-Term Memory (LSTM) neural network model is then proposed for congestion prediction using constructed congestion measures. Point prediction and sequence prediction are both performed. We innovatively introduce congestion propagation effects into the prediction model as input features. Using Shanghai, Singapore and Ningbo ports as case studies, results show that the inclusion of congestion propagation effect can improve the prediction performance especially for sequence prediction. This study provides significant implications and decision support for container shipping market participants. [ABSTRACT FROM AUTHOR]

• We exam the social psychology of technology adoption in container trucking industry. • Our research includes contextualized behavior analysis and discrete choice model. • Risk tolerance positively moderates influence of the status quo on adoption. • Service-orientation negatively moderates influence of the status quo on adoption. Most extant literature in the transportation industry views innovation adoption as a rational choice process conducted on a cost-benefit calculation basis. This restricts our understanding of innovation decisions made by individuals embedded in a social-economic context. By investigating the underlying social psychology of the innovation adoption in the Chinese container trucking industry, this paper aims to answer the question as to 'why trucking operators postpone adopting the cargo-truck matching system during its early stage'. In order to achieve the research objective, a mixed methods research framework is proposed. First, we conduct four in-depth interviews using semi-structured questionnaires to investigate the contextualized behavior of individuals, based on which three hypotheses are developed. Second, based on the data collected from an online questionnaire survey covering 282 trucking operators in Ningbo, the proposed empirical hypotheses are tested using a discrete choice model. We find that risk tolerance positively moderates influence of the status quo on the innovation adoption decision, whilst the effect on it of service-orientation is negative. [ABSTRACT FROM AUTHOR]