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The purpose of this paper is to advance knowledge of the transformative potential of big data on city-based transport models. The central question guiding this paper is: how could big data transform smart city transport operations? In answering this question the authors present initial results from a Markov study. However the authors also suggest caution in the transformation potential of big data and highlight the risks of city and organizational adoption. A theoretical framework is presented together with an associated scenario which guides the development of a Markov model.

A model with several scenarios is developed to explore a theoretical framework focussed on matching the transport demands (of people and freight mobility) with city transport service provision using big data. This model was designed to illustrate how sharing transport load (and capacity) in a smart city can improve efficiencies in meeting demand for city services.

This modelling study is an initial preliminary stage of the investigation in how big data could be used to redefine and enable new operational models. The study provides new understanding about load sharing and optimization in a smart city context. Basically the authors demonstrate how big data could be used to improve transport efficiency and lower externalities in a smart city. Further how improvement could take place by having a car free city environment, autonomous vehicles and shared resource capacity among providers.

The research relied on a Markov model and the numerical solution of its steady state probabilities vector to illustrate the transformation of transport operations management (OM) in the future city context. More in depth analysis and more discrete modelling are clearly needed to assist in the implementation of big data initiatives and facilitate new innovations in OM. The work complements and extends that of Setia and Patel (2013), who theoretically link together information system design to operation absorptive capacity capabilities.

The study implies that transport operations would actually need to be re-organized so as to deal with lowering CO₂ footprint. The logistic aspects could be seen as a move from individual firms optimizing their own transportation supply to a shared collaborative load and resourced system. Such ideas are radical changes driven by, or leading to more decentralized rather than having centralized transport solutions (Caplice, 2013).

The growth of cities and urban areas in the twenty-first century has put more pressure on resources and conditions of urban life. This paper is an initial first step in building theory, knowledge and critical understanding of the social implications being posed by the growth in cities and the role that big data and smart cities could play in developing a resilient and sustainable transport city system.

Despite the importance of OM to big data implementation, for both practitioners and researchers, we have yet to see a systematic analysis of its implementation and its absorptive capacity contribution to building capabilities, at either city system or organizational levels. As such the Markov model makes a preliminary contribution to the literature integrating big data capabilities with OM capabilities and the resulting improvements in system absorptive capacity.

This study aims to explore the challenges of truck-sharing and effective ways of dealing with those in achieving supply chain collaboration and collaboration in transportation management (e.g. transport collaboration) for transport capacity expansion, and reducing carbon emission and traffic congestion for integrating environmental and social sustainability issues. This paper also reveals insights into successful shared-transportation and a reduction in empty trips.

This exploratory qualitative study was conducted by means of interviewing road carriers from the container transportation industry.

In a truck-sharing initiative, technical issues (e.g. carrying capacity) arise, some of which involve the container truck and some involving constraints that cannot be controlled, such as driving restrictions, seaport operating hours, and the presence of the large number of container categories pertaining to the industry. Therefore, a significant amount of “structural empty running” may always prevail. It should also be noted that some, seemingly vital, constraints can actually be changed, treated, or modified for better truck-sharing outcomes, such as building a foundation of trust and establishing coordination among road carriers.

A probable solution to the problem of increasing hinterland transport capacity is to make appropriate use of the huge number of idle truck slots that exist; this could be achieved by encouraging the acceptance of the challenges of truck-sharing realistically and suggesting an approach to handling them.

To broaden its appeal, truck-sharing initiatives must be able to overcome challenges by combining theoretical insight with an understanding of the practical aspects of such an endeavor. This original research fosters knowledge that is unique and which also has real-life applications in maritime logistics studies and supply chain literature for both port authorities and container road carriers.

Empty container trucks may cause a deficit in transport capacity and contribute to congestion and emissions in the port territory. Reengineering of the container truck hauling process to introduce truck-sharing arrangements using the truck appointment system has the potential of reducing the number of empty-truck trips. The paper aims to discuss these issues.

This research evaluates the results from an investigation of the truck appointment system using a case study approach. The data collection phase involved primary and secondary sources along with using publicly available data on port operations.

The study explores a dynamic truck-sharing facility for a computer-based matching system to assign probable export containers to available empty slots of a container truck. The proposed model reengineers the truck appointment system with a potential to reduce the number of empty-truck trips to increase container transport capacity around seaport gates.

Due to continuous increases in container-freight traffic, leading seaports of the world are experiencing a capacity shortage resulting in traffic congestion. The research findings are useful in practice as the proposed truck-sharing model can be introduced to enhance capacity in the container transport chain of the port territory.

The empty-trucks problem has not been addressed much in studies from a decentralized perspective where all truck operators have an equal chance to contribute to optimize the supply chain in contrast with the typical one-company-based optimization. The solution addressed here uses the shared-transportation concept to cover the research gap.

This study aims to analyze the development direction of train speed, density and weight in China.

The development of China's railway in the past 40 years can be divided into 3 stages. At the stage of potential tapping and capacity expansion, it is important to improve the train weight and density by upgrading the existing lines, and improving transportation capacity rapidly. At the stage of railway speed increase, the first priority is to increase train speed, reduce the travel time of passenger train, and synchronously take into account the increase of train density and weight. At the stage of developing high-speed railway, train speed, density and weight are co-developing on demand.

The train speed of high-speed railway will be 400 km h⁻¹, the interval time of train tracking will be 3 min, and the traffic density will be more than 190 pairs per day. The running speed of high-speed freight EMU will reach 200 km h⁻¹ and above. The maximum speed of passenger train on mixed passenger and freight railway can reach 200 km h⁻¹. The minimum interval time of train tracking can be compressed to 5 min. The freight train weight of 850 m series arrival-departure track railway can be increased to 4,500–5,000 t and that of 1,050 m series to 5,500–6,400 t. EMU trains should gradually replace ordinary passenger trains to improve the quality of railway passenger service. Small formation trains will operate more in intercity railway, suburban railway and short-distance passenger transportation.

The research can provide new connotations and requirements of railway train speed, density and weight in the new railway stage.

In difficult geographical zones (mountain, intra-cities areas, etc.), many shippers, from small and medium enterprises to individuals, may demand delivery of different food products (fresh, refrigerated, frozen, etc.) in small quantities. On the other side, carrier companies wish to use their vehicles optimally. Taking into account the perishability constraints (short-shelflife, temperature limits, etc.) of the transported food products and environmental constraints (pollution, carbon impact) while consolidating multiple kinds of food products to use vehicles optimally is not achieved by current transportation planning solutions. The purpose of this paper is to present an interoperable solution of a marketplace, formed by shippers and carriers, dedicated to the schedule of food transport orders.

This transportation planning system named Interoperable-Pathfinder, Order, Vehicle, Environment and Supervisor (I-POVES) is an interoperable multi-agent system, based on the SCEP (supervisor, customer, environment and producer) model (Archimede and Coudert, 2001). Ontologies are developed to create the planning marketplace comprising demands and offers from different sources (multiple shippers and carriers).

A hierarchy ontology for food products. A transporter system ontology. A global ontology that contains all shared concepts used by local ontologies of both shippers and carriers. I-POVES an interoperable model, which facilitates collaboration between carriers and their shippers through its active agents.

I-POVES is tested on a case study from the TECCAS Poctefa project, comprising transport and food companies from both sides of the Pyrenees (France and Spain).

There has been much work in the literature on the delivery of products, but very few on the delivery of food products. Work related to delivery of food products focuses mostly on timely delivery for avoiding its wastage. In this paper, constraints related to food products and to environment (pollution and carbon impact) of transport resources are taken into account while planning the delivery.

This paper aims to analyse available multimodal transport route variations for iron ore shipments from northwest Australia to northeast China, focusing on a major iron and steel manufacturer.

The research is focused on a case study and uses an established cost model as a framework, for the first time, in the context of heavy bulk cargo shipments. Field interviews and a questionnaire form the principal methods of primary data collection. The characteristics of bulk iron ore transport flow are analysed against traditional criteria and an appraisal of the transport infrastructure in north east China is made, considering both road and rail options, and various possible combinations for transport being evaluated. All factors affecting modal choice in the region are examined, including cargo volume, weight, and value, transport distance, transit time, transport costs and schedule reliability.

The volumes of iron ore moved are large, with a high weight‐to‐volume ratio, and shipments are regular. The research initially confirms that sea and rail transport combinations are the most appropriate for the movement of iron ore. However, where rail transport corridors are congested, provided that the transport distances are not too great, road haulage appears to be an effective substitute and the most competitive multimodal transport route, at least in the short to medium term, is found to be a rail‐sea‐road combination via Port Bayuquan in China.

The research focuses on the delivery of iron ore to one major steel manufacturer in northeast China; so findings may not be transferable to other companies or circumstances.

The paper first demonstrates that, for heavy, high volume cargoes concentration of flows on to one corridor, perhaps under the control of one service provider, maximises scale economies, but works against competition and route/mode choice. Second, it demonstrates that, for long haul shipments of iron ore, port variations and modal differences for inland transport yield only marginal differences in overall logistics costs.

An assessment of high volume/heavy/low value cargoes such as iron ore has not previously been undertaken using this cost model. This paper therefore provides an original analysis of such supply chains.

COVID-19 has changed the landscape within which we travel. Working from Home (WFH) in many countries has increased significantly, and while it was often forced on a society it has delivered some unintended positive consequences associated in particular with the levels of congestion on the roads and crowding on public transport. With a likelihood of some amount of WFH continuing as we move out of the active COVID-19 period, the question being asked is whether the post-COVID-19 period will return the pre-COVID-19 levels of traffic congestion and crowding. In many jurisdictions, there is a desire to avoid this circumstance and to use WFH as a policy lever that has appeal to employees, employers and government planning agencies in order to find ways of better managing future levels of congestion and crowding. This chapter uses the ongoing research and surveys we have been undertaking in Australia since March 2020 to track behavioural responses that impact on commuting and non-commuting travel, and to examine what the evidence tells us about opportunities into the future in many geographical settings to better manage congestion and crowding. This is linked to a desire by employers to maintain WFH where it makes sense as a way of not only supporting sustainability charters but also the growing interest in a commitment to a broader social licence. We discuss ways in which WFH can contribute to flattening peaks in travel; but also the plans that some public transport authorities are putting in place to ensure that crowding on public transport is mitigated as people increasingly return to using public transport. Whereas we might have thought that we now have plenty of public transport capacity, this may not be the case if we want to control crowding, and more capacity may be needed which could be a challenge for trains more than buses given track capacity limits. We conclude the chapter by summarising some of the positive benefits associated with WFH, and the implications not just for transport but for society more widely.