Multimodal transport efficiency in agricultural supply chains: a case study of rail-road integration in Thailand’s sugar logistics

A multi-modal transportation system is a transportation system with multiple travel modes, which usually includes solo-driving, car-pooling, public transit, freight transportation, ride-sourcing, park-and-ride, etc. With emerging technologies, multimodal transportation becomes highly ubiquitous and diversified nowadays. From the system perspective, the co-existence of all these travel modes lead to diversified and complex systems that enables more instruments to alleviate traffic congestion and improve users’ quality of life, provided that the comprehensive systems are managed and operated in a proper way. To properly manage a multi-modal transportation system, we need a holisticmodeling framework of multi-modal transportation networks to support the decision making, including tasks like transportation demand management, what-if analysis,congestion alleviation, estimation of system costs, etc. However, due to the complexity of the multi-modal transportation system, there are several challenges forbuilding such a model. First, traffic in such systems usually contains different types of vehicles. How to model the behavior and estimate the travel cost of these vehiclesin the heterogeneous traffic flow remains unsolved. Secondly, it is also challenging to integrate different travel modes in a single multi-modal transportation system.Their linkage and interdependency is complicated and stochastic due to the nature of human’s behaviors.In this dissertation, we focus on the problem of multi-modal transportation system modeling and management leveraging mobility data. The final goal is to comprehensivelymodel the entire multi-modal transportation system, to better understand the interaction and linkage among each component of transportation systems, and to ultimately facilitate optimal decision making on urban transportation system planning and operation. Specifically, we propose a simulation-based dynamic traffic assignment modelfor cars and trucks to simulate the traffic flow in the system. We build a public transit operation performance analytics framework using multiple types of mobilitydata. We also propose a model to optimize the curbside parking of ridesourcing vehicles. Finally, a holistic multi-modal dynamic user equilibrium model is proposedto integrate all travel modes and model the travelers’ behaviors in a general multimodal transportation system. Numerical experiments based on different multi-modaltransportation networks are conducted for each of the work and show our models and methods have excellent performance and applicability. In this dissertation work, we mainly focus on the day-to-day equilibrium state ofthe multi-modal transportation systems. Other scenarios including abnormal, hazardous and disaster situations are not considered. Moreover, the calibration of themulti-modal dynamic traffic assignment model is also not the main focus of this dissertation, which is studied and introduced in other papers of the author and collaborators.

A production department and two distribution departments form a multimodal logistics supply network. The production department provides two ordering opportunities within one production cycle, and the real-time updates of demand information are required in the interval between two orders. Based on this, the paper studies the security inventory optimization problem of multimodal transport networks. On the basis of portraying the real-time information update process, the multimodal network optimization model without considering safety stock and the multimodal network optimization model considering safety stock are constructed, respectively, and the transshipment price and demand information of the intermodal network are updated. The parameters are analyzed for sensitivity. The analysis of examples shows that, on the one hand, with the update of demand information, the distribution department adopts the multimodal transport model with safety stock to improve the profit of the distribution department and the supply network. On the other hand, the production sector can meet market demand with a lower production scale, while the distribution department can effectively respond to stochastic demand through a multimodal model with safety stock.

Impacts of truck platooning on the multimodal freight transport market: An exploratory assessment on a case study in Italy

The major component of logistic system is multimodal transportation. This paper presents the various alternative methodologies available to multimodal transportation planning. There is an application need for network modeling approach the optimization of people and freight transportation with different techniques. In the process of selecting the most efficient transportation modes, a multimodal transport costD model is used to demonstrate and clarify multimodal transport routing alternatives. Risk factors are also considered for each route, transport modes and nodal links. The goal of this paper is to review literature concerning a generic multi transportation network model based on implementation of computational techniques to increase efficiency.

Objective. The purpose of the study is to identify the specifics of the development of the regional freight transportation market in the Kherson region, taking into account advanced transportation technologies and assessing the concentration of the freight transportation market. Design/methodology/approach. The following research methods were used: problem-oriented (in terms of identifying the problems of the freight transportation market and factors influencing it); logical generalization, analysis and synthesis (to formulate conclusions about the prospects for the development of the multimodal freight transportation market in the region); structural and factual analysis (to analyze the structure and dynamics of freight transportation parameters); index method (to determine the concentration of the regional multimodal freight transportation market using indices). Conclusions. The analysis of the elemental structure of the logistics system of the Kherson region with the participation of water transport showed a developed infrastructure of cargo transportation and ample opportunities for focusing participants around the centers of the transportation process. The asymmetry of price competition for access to port berths and roadside transshipment was revealed, which distorts equal working conditions for cargo transportation market participants and modifies the structure of cargo transshipment and, accordingly, the centers of dominance in the target markets of multimodal transportation. Prioritizing the export of bulk cargo and import of containerized cargo in the Kherson region requires the development of a transport policy that would ensure the freight independence of cargo flows, and the identified unstable dynamics of the geography of transportation routes in the region requires the expansion of alternatives for choosing parameters and directions for the development of transportation technologies for servicing local cargo flows. It is also necessary to balance the existing advanced development of the grain cargo delivery infrastructure against the capacity of their one-time storage in grain terminals in ports. It has been established that the multimodal transportation market of the Kherson region (as of 2021) is characterized by an uneven distribution of market shares between transport enterprises, is highly concentrated, with a low level of competition and the threat of monopolization. Market power in the “market core” is evenly distributed among PJSC “Ukrzaliznytsia”, SE “Kherson Commercial Sea Port”, and LLC JV “Nibulon”. The Herfindahl – Hirschman index confirmed the concentration of power among these three enterprises, identified by the concentration index, which amounted to 80.87 %. The lower share of the transport sector of the Kherson region in the total economic activity of cranes in the period 2015–2020 in favor of other industries was identified, and therefore the insufficient level of meeting the production and non-production needs of consumers in the region in all types of cargo transportation. Practical implications. The results of this study are of interest to multimodal transportation market operators and cargo owners who are interested in actively implementing the logistics concept in regional development and building multimodal regional clusters. In this way, it is expected to increase the attraction of cargo flows to the regions, the development of competition; employment growth in the freight transportation sector and other related industries. The results of the assessment of the development of multimodal freight transportation can be taken into account by the Logistics Coordination Council under the Ministry of Infrastructure of Ukraine when forming the strategic framework for the development of the country‟s logistics system. Originality/value. Assessment of the concentration of regional markets will provide an analytical basis in the process of forming a mechanism for ensuring the integrated efficiency of multimodal transportation of goods and minimizing interregional asymmetries: in terms of levels of cargo flows in accordance with the stated needs of consumers; the state of transport and logistics infrastructure; availability of all types of vehicles, service levels, etc.

Multimodal transport security: Frameworks and policy applications in freight and passenger transport

In recent years, China keeps working on restructuring the country’s multimodal transport and highly develops the high-speed rail (HSR) infrastructure to improve transport efficiency. As the economic engine of China, the Yangtze River Delta region keeps leading the HSR development and the transporting modal transformation within the whole country. The fast development of HSR on the one hand highly improves passengers’ travel efficiency and, on the other hand, releases the capacity of conventional rail infrastructures to support regional multimodal freight transport. This study applies a three-level AHP structure and constructs a comprehensive index to evaluate the development of a rail-based multimodal freight transport network including railway, rail-water, and rail-road. The comprehensive index contains 14 quantitative and 8 qualitative indexes, covering the rail-based infrastructures, multimodal transport capability, freight transport performance, and transport sustainability. The comprehensive index is then applied to analyze the rail-based multimodal freight transport for the Yangtze River Delta region. The operational data of 59 freight stations and more than 200 railway links of the Yangtze River Delta were recorded. About 172 valid questionnaires were collected to score the qualitative indexes, and all the quantitative indexes are scored based on the real-life freight data. The results reveal the impacts of HSR development on rail freight transportation and show that Zhejiang has led rail freight transportation while Shanghai mainly leads the waterway freight transportation. Meanwhile, Anhui performs very well on road-rail transportation and Jiangsu has made a great improvement on water-rail transportation.

A large part of freight transport movements are part of a multimodal transport chain, in particular for port-related containerized transport flows. Because data of multimodal transports are unavailable it is challenging to develop a multimodal transport chain models. This paper describes the development of a new module for multimodal transport chains for modelling container transport within the Dutch strategic freight transport model “BasGoed”. The choice model distinguishes unimodal, bi-modal or tri-modal transport chains, depending on whether the transport chain is port-related. A direct road chain is available between each production and consumption combination; direct barge or rail transport is only available between seaports. A route enumeration module generates a choice set for each observed uni- or multimodal container transport. Since no directly observed PC data are available, a synthetic dataset was constructed with container flows between locations of production and consumption, using uni-modal observed transport data. Main assumption is that each container transported by rail or barge requires a road leg at the side of destination and/or origin, to complete the multimodal transport chain. Discrete choice models were estimated with different model structures. The best choice model that was found was a multinomial logit model, segmented by port dependency. The results show that a choice model can be estimated with significant parameters, and with plausible model sensitivities.

Multi-Mode and Single Goods Transportation Network Equilibrium Model Based on Super Network

Diversity is one of the main characteristics of transportation data collected from multiple sources or formats, which can be extremely complex and disparate. Moreover, these multimodal transportation data are usually characterised by spatial and temporal properties. Multimodal transportation network data modelling involves both an engineering and research domain that has attracted the design of a number of spatio-temporal data models in the geographic information system (GIS). However, the application of these specific models to multimodal transportation network is still a challenging task. This research addresses this challenge from both integrated multimodal data organization and object-oriented modelling perspectives, that is, how a complex urban transportation network should be organized, represented and modeled appropriately when considering a multimodal point of view, and using object-oriented modelling method. We proposed an integrated GIS-based data model for multimodal urban transportation network that lays a foundation to enhance the multimodal transportation network analysis and management. This modelling method organizes and integrates multimodal transit network data, and supports multiple representations for spatio-temporal objects and relationship as both visual and graphic views. The data model is expressed by using a spatio-temporal object-oriented modelling method, i.e., the unified modelling language (UML) extended to spatial and temporal plug-in for visual languages (PVLs), which provides an essential support to the spatio-temporal data modelling for transportation GIS.

The role of information and communication technologies (ICTs) in freight transport as key enabler is well recognised. However the uptake of recent ICT advances for multimodal freight transport provisions in the UK and Europe has been slow. The aim of our paper is to explore the potential reasons for such a slow adoption and assess how recent technological advances such as cloud computing and Internet of Things might have changed the landscape and thus help to overcome these barriers. Via an extensive review of 33 EU framework programme projects, we are able to consolidate and present current major efforts in ICT developments in the freight multimodal transport setting at European level. We further discuss barriers inhibiting quick take-up of ICT applications in multimodal transport. Resolutions were then explored by reviewing four key ICT development trends recently emerging and evaluating their potential impact in reducing such barriers for deployment. Our contribution is two-fold: it advances current knowledge by presenting an up-to-date overview of existing and emerging ICT applications in the field of multimodal transport and barriers to e-enabled multimodal transport. It also captures some of the best practices in industry and aims to provoke a debate among practitioners and academics via the analysis of how innovative use of recent technological developments could potentially lower the barriers to multimodal ICT adoption and lead to a more integrated freight transport network. Therefore it lays the foundation for further research.

Currently, long‐distance freight transport is shifting towards multimodal transport, the combination of multiple freight transport modes. Multimodal transport enables enterprises with the same logistics function to operate on the same level of the supply chain. Through horizontal cooperation, these enterprises can give play to their advantages, make up their deficiencies, improve service levels, reduce cost input, and thereby enhance market status. Therefore, multimodal transport is an intensive development model that promotes the alliance between giants. The reasonable path design and planning (PDP) and investment and construction mode (ICM) of the multimodal transport network help freight demanders, as well as multimodal freight transport platforms, obtain the maximum profit. Therefore, this paper explores the PDP and ICM of the multimodal transport network based on big data analysis. Firstly, the influencing factors and behavioral features of multimodal transport were deeply examined, drawing on the logit model and the big data on multiple freight services, namely, railway transport, highway transport, waterway transport, and airway transport. After classifying the freights, the authors analyzed the modeling and decision‐making of path design and optimization (PDO) for multimodal transport network. The proposed model was proved effective through experiments. This paper theoretically explores the goals, principles, and needs of path selection in the modern transportation industry. In a realistic sense, the research findings help decision‐makers optimize their decisions on the multimodal transport network and operate the network at the minimum transport cost.

The research on the multimodal transport development within the cross-border area is a result of identified gaps in the system solutions and cooperation between stakeholders of three countries: Poland, the Czech Republic and Slovakia. Freight transport is an especially complex problem. It is an area that is not comprehensively recognized in the context of cross-border cooperation. The results of the research presented in this paper are the continuation of analyses performed within the scope of the international project framework TRANS TRITIA. At the moment, transport policy assumes the struggle for the utilization of multimodality within freight transport. This is justified by the need to reduce external transport costs. At the same time, this necessitates actions of a technical, organizational, and legislation nature as well as cooperation between stakeholders. The multimodal transport ecosystem is a vision of the transport within cross-border areas that assumes the increase in the flow dynamics within the multimodal transport. The main goal of this paper was the stakeholders’ analysis and identification of their roles in the ecosystem of multimodal freight transport within the Polish–Czech–Slovak cross-border area. The conceptualization of the multimodal freight transport ecosystem was essential to achieving the objective. To achieve the objective, a stakeholder analysis has been performed based on expert research. As a result of the research, organizational projects have been proposed to strengthen the idea of the coevolution of the multimodal transport ecosystem. The key conclusion from the performed research is the declaration that a holistic view of the multimodal transport ecosystem necessitates the appointment of a coordinator who will synchronize knowledge, business, and innovation ecosystems.

Hub seaport multimodal freight transport network design: Perspective of regional integration development

The European Commission has dedicated itself steadily to multimodal freight transport to reduce problems such as air pollution or congestion and to reach the goals set by the Paris Agreement. Despite the political efforts to promote multimodality, the majority of freight transport is still carried out by truck. The aim of this paper is to capture the reasons for the small share of multimodal transport and suggest measures to promote multimodal transport. To collect data, a multiple-case study was conducted involving ten logistics service providers. The barriers to multimodal freight transport are analyzed in a holistic manner using interpretive structural modeling. Overall, fifteen barriers are presented which are classified as demand-related barriers, shipment characteristics, infrastructural/supply-related barriers, organizational barriers and legal / political barriers. Based on that, a bottom-up approach involving the ten logistics service providers (LSPs) is used to develop user-centered policy measures for multimodal transport. The direct involvement of LSPs facilitates acceptance of the proposed measures. The internalization of external costs, efficient information provision and education/training/awareness raising are rated as high impact measures to promote multimodal transport.