Seaport throughput forecasting and post COVID-19 recovery policy by using effective decision‐making strategy: A case study of Vietnam ports

Cuong, Truong Ngoc; Kim, Hwan–Seong; You, Sam–Sang; Nguyễn, Duy Anh

doi:10.1016/j.cie.2022.108102

Cited by 20 publications

(5 citation statements)

References 47 publications

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“…In terms of traditional econometric models, Sanguri et al (2022) proposed an intertemporal forecasting model based on exponential smoothing to forecast container throughput at the Port of Los Angeles. In terms of the artificial intelligence model, Cuong et al (2022) utilized a neural network predictive controller and adaptive fractional-order supervision sliding mode control to handle throughput under external disturbances. In the meantime, some scholars have also used the decomposition integration method (Du et al, 2019;Jin et al, 2023), SARIMA and machine learning hybrid method (Huang et al, 2022;Mo et al, 2018) for forecasting container throughput prediction.…”

Section: Maem 71mentioning

confidence: 99%

“…(2022) proposed an intertemporal forecasting model based on exponential smoothing to forecast container throughput at the Port of Los Angeles. In terms of the artificial intelligence model, Cuong et al . (2022) utilized a neural network predictive controller and adaptive fractional-order supervision sliding mode control to handle throughput under external disturbances.…”

Section: Literature Reviewmentioning

confidence: 99%

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Research and application of a novel grey multivariable model in port scale prediction under the impact of Free Trade Zone

Sun,

Zhang,

Zhao

2024

MAEM

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Purpose Considering the impact of the Free Trade Zone (FTZ) policy on forecasting the port cargo throughput, this paper constructs a fractional grey multivariate forecasting model to improve the prediction accuracy of port cargo throughput and realize the coordinated development of FTZ policymaking and port construction.Design/methodology/approach Considering the effects of data randomization, this paper proposes a novel self-adaptive grey multivariate prediction model, namely FDCGM(1,N). First, fractional-order accumulative generation operation (AGO) is introduced, which integrates the policy impact effect. Second, the heuristic grey wolf optimization (GWO) algorithm is used to determine the optimal nonlinear parameters. Finally, the novel model is then applied to port scale simulation and forecasting in Tianjin and Fujian where FTZs are situated and compared with three other grey models and two machine learning models.Findings In the Tianjin and Fujian cases, the new model outperforms the other comparison models, with the least mean absolute percentage error (MAPE) values of 6.07% and 4.16% in the simulation phase, and 6.70% and 1.63% in the forecasting phase, respectively. The results of the comparative analysis find that after the constitution of the FTZs, Tianjin’s port cargo throughput has shown a slow growth trend, and Fujian’s port cargo throughput has exhibited rapid growth. Further, the port cargo throughput of Tianjin and Fujian will maintain a growing trend in the next four years.Practical implications The new multivariable grey model can effectively reduce the impact of data randomness on forecasting. Meanwhile, FTZ policy has regional heterogeneity in port development, and the government can take different measures to improve the development of ports.Originality/value Under the background of FTZ policy, the new multivariable model can be used to achieve accurate prediction, which is conducive to determining the direction of port development and planning the port layout.

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Section: Maem 71mentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Research and application of a novel grey multivariable model in port scale prediction under the impact of Free Trade Zone

Sun,

Zhang,

Zhao

2024

MAEM

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“…Gui et al [29] incorporated the synergistic use of fuzzy Bayesian inference, the analytical hierarchy process, and the coefficient of variation method to facilitate handling uncertainties and quantitative analysis of congestion under different impacts of port risk factors. Cuong et al [30] examined effective decision-making strategies for indicating dynamic interactions between seaports and regulating port productivity through the case of ports where productivity was impacted by the COVID-19 pandemic. Furthermore, they investigated the profits of the supply chain under environmental disruptions, incorporating risk assessment methodologies to analyse the costs associated with hinterland shipments and transshipment, as well as port profits under stochastic disruptions [31].…”

Section: Literature Reviewmentioning

confidence: 99%

Research on Port Risk Assessment Based on Various Meteorological Disasters

Wang,

Ding,

Poo

et al. 2024

Urban Science

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Within the framework of economic globalisation, ports serve as critical junctures in international trade and play a vital role. However, as infrastructure is closely linked to the natural environment, ports are highly susceptible to the impacts of meteorological disasters. Therefore, a comprehensive assessment of the risks posed by meteorological hazards to ports, establishing corresponding early warning mechanisms, and adopting reasonable response and recovery strategies, is paramount in ensuring the safe operation of ports and maintaining the stability of international trade. This study has comprehensively analysed historical data and identified the pre-established loss stratification system, improving the theoretical construct of “expected loss”. Additionally, this research has innovatively integrated the idea of preventative factors aligned with risk indicators. A quantitative algorithm was used to factor in the preventative factors within the computational procedure, deriving the weights pertinent to each risk indicator. This research aimed to reduce the subjectivity inherent in the weighting assignment process through such an approach, thereby enhancing disaster risk assessment’s scientific rigour and reliability. Moreover, it underscores the critical role of adaptive urban planning in enhancing the resilience of crucial economic nodes like ports, thereby contributing to the broader objectives of sustainable urban development.

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“…SC optimization means improved decision-making schemes under constraints or limited resources. Research studies have revealed that simulation [82], system dynamics [83], and decision support systems are required for decision making [84]. In addition, the objectives of SC optimization can be discussed from two perspectives: enterprises and public organizations.…”

Section: Cluster 5: (Purple) Supply Chain Optimization During Pheicsmentioning

confidence: 99%

Supply Chain Management during a Public Health Emergency of International Concern: A Bibliometric and Content Analysis

et al. 2023

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A public health emergency of international concern, such as a pandemic, disrupts the normal operation of the global supply chain, which necessitates in-depth research on supply chain management. In this paper, we used bibliometric and content analysis to provide a systematic analysis of the supply chain industry from this background. The descriptive analysis provides insights into the publication growth trajectory, in terms of the contributing authors, countries, and subject categories, which presents an intuitive display of previous research. In addition, the existing research mainly covers three dimensions of supply chain disruption, strategies, and sustainability, which can be clustered into supply chain disruption, disruption recovery, reconfiguration, digital intelligence, optimization, and sustainability. By revisiting the supply chain industry, we explored the transformation of its characteristics in the pandemic, covering themes ranging from expansion to contraction, from traditional to digital intelligence, and from fragile to sustainability, which suggests potential research directions for future studies. This contributes to the further research of supply chain management during the pandemic and provides supply chain managers with a practical approach for dealing with supply chain disruption risks and improving supply chain sustainability in this context.

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Seaport throughput forecasting and post COVID-19 recovery policy by using effective decision‐making strategy: A case study of Vietnam ports

Cited by 20 publications

References 47 publications

Research and application of a novel grey multivariable model in port scale prediction under the impact of Free Trade Zone

Research and application of a novel grey multivariable model in port scale prediction under the impact of Free Trade Zone

Research on Port Risk Assessment Based on Various Meteorological Disasters

Supply Chain Management during a Public Health Emergency of International Concern: A Bibliometric and Content Analysis

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