A Push for Obscurity: The Role of Social Influence on Mobile Location Data Disclosure

Abstract

Within the context of green shipping, the concept of Just-In-Time (JIT) arrival has attracted much attention. Research achieves the JIT arrival for container ships by combining the berth allocation and quay crane assignment problem (BACAP) and the vessel speed optimization (VSO), both subject to the data exchange. Many prediction models of the research to date generally aim to reduce the uncertainty of the communicated estimated time of arrivals. There is a lack of research that simultaneously assesses the application effect of prediction models on both plans of the BACAP and the VSO. Therefore, this paper proposes a twostage model that integrates the prediction of the vessel arrival time with the optimization of the BACAP-VSO.The application in our specific case study shows that the random forest performs best in the first stage. The results are forwarded to the second stage and lead to a reduction of the service delay, fuel consumption cost, and vessel emissions.

The implementation of berth allocation policies that enable Just-in-Time arrival in port calls

“…For example, Merkel et al (2022) and Jia et al (2017) estimated savings between 2% and 20% in fuel and emissions by the implementation of JIT in the Swedish and global context of port calls for the tramp shipping segment, respectively. In the Chinese container port context, the implementation of JIT would reduce service delay, fuel consumption and emission by 6.87%, 8.11% and 4.98% for calling vessels (Yu and Voß, 2023). Transitioning from FCFS to PBP positively affects berth utilization in the Port of Amsterdam (Eisen et al, 2021).…”