A multivariate analysis for the creation of Port Community System approaches

Moros-Daza, Adriana; Solano, Nestor Caicedo; Amaya, Rene; Paternina, Carlos D.

doi:10.1016/j.trpro.2018.09.015

Cited by 10 publications

(7 citation statements)

References 10 publications

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“…The authors also provided a classification scheme for PCSs based on their functionalities and examine the role of PCSs in enhancing port efficiency, sustainability, and resilience. Also, in [38], the authors explore the development of effective approaches for the implementation of PCSs and conduct a multivariate analysis of factors that affect the success of PCS implementation, such as the level of collaboration between stakeholders, the extent of data sharing, and the availability of technical infrastructure.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…In previous articles [37,38], the authors have widely explained the use of information systems and optimization for increasing the efficiency and productivity in port operations. Information systems equipped with sensors and Internet-of-Things (IoT) devices enable real-time monitoring of various environmental parameters in and around the port [25,50].…”

Section: Managerial Insightsmentioning

confidence: 99%

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Towards Cleaner Ports: Predictive Modeling of Sulfur Dioxide Shipping Emissions in Maritime Facilities Using Machine Learning

et al. 2023

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Maritime ports play a pivotal role in fostering the growth of domestic and international trade and economies. As ports continue to expand in size and capacity, the impact of their operations on air quality and climate change becomes increasingly significant. While nearby regions may experience economic benefits, there are significant concerns regarding the emission of atmospheric pollutants, which have adverse effects on both human health and climate change. Predictive modeling of port emissions can serve as a valuable tool in identifying areas of concern, evaluating the effectiveness of emission reduction strategies, and promoting sustainable development within ports. The primary objective of this research is to utilize machine learning frameworks to estimate the emissions of SO2 from ships during various port activities, including hoteling, maneuvering, and cruising. By employing these models, we aim to gain insights into the emission patterns and explore strategies to mitigate their impact. Through our analysis, we have identified the most effective models for estimating SO2 emissions. The AutoML TPOT framework emerges as the top-performing model, followed by Non-Linear Regression with interaction effects. On the other hand, Linear Regression exhibited the lowest performance among the models evaluated. By employing these advanced machine learning techniques, we aim to contribute to the body of knowledge surrounding port emissions and foster sustainable practices within the maritime industry.

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Section: Literature Review and Problem Statementmentioning

confidence: 99%

Section: Managerial Insightsmentioning

confidence: 99%

Towards Cleaner Ports: Predictive Modeling of Sulfur Dioxide Shipping Emissions in Maritime Facilities Using Machine Learning

et al. 2023

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“…Integration means developing cooperative relationships with the various stakeholders in supply chains, based on trust, technical capacity, and information exchange [9]. Usually, companies do both import and export activities; therefore, a PCS must customize both perspectives, offering a wide range of services [10]. Supply chains with fully integrated seaports have uninterrupted communications, through the just-intime concept with operations cost reductions.…”

Section: Literature Reviewmentioning

confidence: 99%

Port Community Systems: Accelerating the Transition of Seaports toward the Physical Internet—The Portuguese Case

Caldeirinha

Nabais

Pinto

2022

JMSE

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Supply chains are complex systems that have grown in dimension and spread worldwide. In supply chains, physical and information flows have strict service quality requirements, namely transparency conditions and traceability. Seaports, connecting land and maritime transport, are special components of supply chains where multiple players interact with different perspectives, and conflicting goals may arise. Port community authorities invest in electronic platforms to foster communication and integration with the companies that interact with the seaport, guiding the digitization of the seaport business. In main European and world ports, the Port Community System (PCS) is the platform that supports the creation of a network composed of shipping agents, shippers, freight forwarders, transporters, terminals, logistics platforms, and public entities. PCS focuses on service level, partner networks, maritime services, freight services, logistical services, and advanced port services. These features have an impact on seaport operations, which affects supply chain performance. Digitization within the scope of the PCSs has fostered the development of horizontal collaboration between seaport community partners. The Physical Internet (PI) is an innovative concept that seeks new logistics solutions requiring integration and interoperability between partners in the supply chain, including maritime and land transport. This paper focuses on (i) the evolution guidelines of PCSs and (ii) on the PCS Business Factors that can drive the supply chain into a significant improvement in performance. A survey was sent to a sample of Portuguese supply chain experts regarding the causal relationship between PCS Business Factors and supply chain performance in the next 10 to 20 years. From the data collected, recent services evolving at PCS are promoting a mindset change aligned to the implementation of a Physical Internet. Establishing a Physical Internal in Portuguese seaports could take decades, but it will support the transition to a new phase of PCS, accelerating the transition from Isolated Supply Chains (I-SCs) to Open Supply Chains (O-SCs), thus improving supply chain performance.

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“…Another aspect of port community system development was considered by Moros-Daza A. et al [12]. Authors conducted multivariate analysis for the purpose of developing specific IT tool that will help to reduce seaport costs and increase its competitiveness.…”

Section: Sergii Patkovskyi Sergiy Lytvynenko "The Ways Of Supply Chain Responsiveness Increase At Time Of Port Infrastructure and Transpomentioning

confidence: 99%

The Ways of Supply Chain Responsiveness Increase at Time of Port Infrastructure and Transportation Assets Productivity Disruption

Patkovskyi¹,

Lytvynenko²

2020

Intellectualization of Logistics and SCM

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The electronic scientific and practical journal is registered in international scientometric data bases, repositories and search engines. The main characteristic of the edition is the index of scientometric data bases, which reflects the importance and effectiveness of scientific publications using indicators such as quotation index, h-index and factor impact (the number of quotations within two years after publishing).In 2020,

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A multivariate analysis for the creation of Port Community System approaches

Cited by 10 publications

References 10 publications

Towards Cleaner Ports: Predictive Modeling of Sulfur Dioxide Shipping Emissions in Maritime Facilities Using Machine Learning

Towards Cleaner Ports: Predictive Modeling of Sulfur Dioxide Shipping Emissions in Maritime Facilities Using Machine Learning

Port Community Systems: Accelerating the Transition of Seaports toward the Physical Internet—The Portuguese Case

The Ways of Supply Chain Responsiveness Increase at Time of Port Infrastructure and Transportation Assets Productivity Disruption

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