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Digital transformation of organizations managing freight transportation corridors is today, under the so-called "Nearshoring" trend, a key challenge for the logistics sector operating in regions such as the USMCA (United States-Mexico-Canada Agreement). Since Mexico has a significant role in North American industrial supply chains' regionalization, this paper proposes a graph theory-based logistics approach to model and measure the operational robustness of Mexican freight transportation corridors. The proposed method consisted of four steps: (a) construct a dual network for evaluating road section indexes by transforming road links into nodes; (b) assign weights to the edges based on each route distance; (c) simulating potential disruptions in road sections based on topological indices and variations in distance; and (d) developing a web-based digital tool to manage and evaluate the impact of freight transportation corridor management's impact on supply chains' efficiency, sustainability, and resilience. This paper makes two contributions to the current body of knowledge and practical applications. Firstly, it identifies the limitations of some topological indices when assessing the dual graph. Secondly, it discusses the challenges and opportunities for implementing the digital transformation of freight transportation corridor management in Mexico. In conclusion, this paper presents insights for policymakers and researchers and outlines future research directions. [ABSTRACT FROM AUTHOR]

Technology provides the capability to automate the collection of commercial vehicle drivers' hours of service (HOS), and this can potentially lead to fewer errors. This study compares the use of paper-based and automated (or electronically recorded) hours of service for three motor carriers using process analysis. Potential errors are categorized by operations within an information-based process, and results demonstrate that a reduction of errors can be achieved with an electronic system. The analysis shows that some of the errors that occur with paper-based systems (e.g., verification of accurate records) still exist with electronic recordings, and there are some additional minor errors. However, data collection, entry, and storage are improved, as the system requires fewer steps and less manual requirements within the process. The study provides a systematic and structured comparison of the two methods, highlighting the error types that occur in both. Policymakers can consider this comparison when making recommended revisions to HOS documentation procedures. [ABSTRACT FROM AUTHOR]

Urban transportation is a major element of sustainable urban development and a key factor affecting the health of urban residents. It influences public health through noise, air pollution, social isolation, inactive modes of transportation, and sedentary behaviors. This paper reviews literature related to urban transportation and health from two perspectives: travel behavior and environmental impact. It focuses on passenger transportation and freight transportation to analyze their respective negative environmental externalities, such as noise, environmental pollution, and accidents. After the literature review, the paper identifies the main deficiencies in urban transportation research aiming to build healthy cities, and proposes measures and suggestions for future research. [ABSTRACT FROM AUTHOR]

This paper proposes a multi-layer integrated IoT-blockchain conceptual architecture to solve the issues of the traditional bill of ladings, namely double-spending, duplicated documents, masqueraded information, and fraud and hacking threads related to the complexity of traditional format and fragmented supply chain activities. We formulate the tasks and functions of each IoT-blockchain layer and illustrates how the proposed conceptual architecture can overcome several inefficiency and security issues in the status quo. The proposed conceptual architecture can link IoT and blockchain technologies with port community systems' practices to reduce potential risks behind issuing the bill of lading. [ABSTRACT FROM AUTHOR]

Classification of vehicles into distinct groups is critical for a number of applications including freight and commodity flow modeling, pavement management and design, tolling, air quality monitoring, and intelligent transportation systems. The main goal of this paper is to demonstrate how data from Light Detection and Ranging (LiDAR) sensors could be leveraged to distinguish between specific types of truck trailers beyond what is generally possible by the traditional vehicle classification sensors (e.g., piezoelectric sensors and inductive loop detectors). A multi-array LiDAR sensor enables the construction of 3D-profiles of vehicles since it measures the distance to the object reflecting its emitted light. This paper shows how point-cloud data from a 16-beam LiDAR sensor are processed to extract useful information and features to classify semi-trailer trucks hauling ten different types of trailers: a reefer and non-reefer dry van, 20 ft and 40 ft intermodal containers, 40 ft reefer intermodal container, platforms, tanks, car transporter, open-top van/dump and aggregated other types (i.e., livestock, logging). K-Nearest Neighbors (KNN), Multilayer Perceptron (MLP), Adaptive Boosting (AdaBoost.M2), and Support Vector Machines (SVM) supervised machine learning algorithms are implemented on the field data collected on a freeway segment that includes over seven-thousand trucks. The results show that with the SVM model, different trailer body types can be distinguished with a very high level of accuracy ranging from 85% to 98%. [ABSTRACT FROM AUTHOR]

The use of information technologies such as Transportation Management System (TMS) is crucial to improve the transportation process in a company, offering potential results that include optimization of shipments, an increase in cost savings and customer satisfaction. The TMS, along with data analysis techniques such as Machine Learning (ML) and/or Data Mining (DM) are useful tools for demand forecasting, facilitating strategic, tactical and operational decision making, which ultimately improves the logistics distribution performance. For this, this work proposes a methodology that will compare three prediction methods (traditional statistical method, hybrid method and artificial neural network), which will be tested through the Mean Squared Error (MSE) indicator to determine which one has more accurate results in the forecast of demand for freight transport. The experimental results obtained in this research show that the historical data saved in a TMS can be used for reliably freight transportation demand forecasting. Each of the three methods proposed in this paper has been an effective tool in resolving time series forecasting problems, and when Artificial Neuronal Network (ANN) was used, better results are yielded. [ABSTRACT FROM AUTHOR]

The integration of Ukraine's economy into the European space requires the dynamic and balanced development of all its sectors, especially the transport sector. The purpose of the research is to identify the factors related to transport entrepreneurship that affect the economic development of Ukraine, in particular regarding the formation of added value (gross regional product). The paper presents the author's definition of transport entrepreneurship as an independent, systematic, and risky entrepreneurial activity in providing transport services. The results revealed a negative trend in the formation of the added value of the transport enterprises of Ukraine, both in terms of value and as a percentage of GDP. This prompted the authors to determine the factors affecting the formation of gross added value (gross regional product) by transport enterprises of Ukraine to further develop proposals aimed at their activation. Four models were created in the first stage of the research to achieve the goal. These models are based on gross regional product in transport, warehousing, postal and courier activities; gross regional product in transport, warehousing, and postal and courier activities per capita; gross value added in transport, warehousing, and postal and courier activities; and gross value added in transport, warehousing, and postal and courier activities per capita. In the second stage of the research, the fifth model with the highest correlation coefficients was built, which made it possible to identify the factors of negative and positive influence on the formation of gross added value (gross regional product) by transport enterprises in Ukraine. Based on the results, a number of measures are proposed to stimulate factors of positive influence and neutralize negative influence. The proposed tools for identifying the factors related to transport entrepreneurship that affect the economic development of Ukraine can serve as markers for the formation of the country's post-war strategy in the field of transport entrepreneurship. [ABSTRACT FROM AUTHOR]

• This paper addresses a novel practical problem faced by a major North American railway. • The problem involves decisions such as how inbound trains are split, on which tracks the railcars are parked for loading and off-loading operations, and how the railcars are assigned to outbound blocks. • We propose a 2-step approach that considers all the decisions that must be made by terminal operators. • Tests based on realistic benchmark instances indicate that our approach is able to generate good quality solutions for all instances. In the last decades the intermodal transportation of containers has become a key component of the entire international trade system, as it allows safe and efficient intercontinental door-to-door movement of freight by combining land and sea transportation services. Intermodal railway terminals are special components of these systems that allow container traffic to be consolidated from different sources and to be transported by train over long distances. This paper addresses a practical problem faced by a major North American railway. On a daily basis, terminal operators must make several decisions such as how inbound trains are split into sequences of railcars, on which tracks these railcars are parked for loading and off-loading operations, and how the railcars are assigned to outbound blocks so as to fulfill the demand of each block. We introduce an approach that incorporates all these decisions to obtain improved solutions. In a first step, a mixed integer linear programming (MILP) model is used to create a set of patterns that specify how each inbound train is split and how the railcars are assigned to the blocks. Then, in a second step, another MILP formulation decides which patterns to use and where to park the railcars. Tests on generated benchmark instances based on realistic data from the railway indicate that our approach is able to generate good quality solutions for all instances and can be used by the company to assist decision makers in generating less costly and more efficient plans. [ABSTRACT FROM AUTHOR]

Currently in Europe, road freight transport is characterized by the most dynamic advancement. Year after year, we may observe an increase in the amount of transported goods. The paper presents the emissions of gaseous exhaust components such as CO, THC, and NOx as well as fuel consumption in freight transport. The emission analysis was performed for the entire transport cycle covering the handling of the goods with forklifts and carriage with a heavy-duty truck. The investigations were performed under actual conditions of operation using a Portable Emission Measurement System (PEMS). The fuel mileage was determined using the carbon balance method. The test routes were designed so as to reproduce the transport-logistic system typical of small towns. The setting for the tests was a town located in central Poland near the A2 motorway constituting part of the trans-European logistic network with multiple locations of logistic centers. In order to present the real emissions during handling, two test variants were considered: an outdoor variant (on a nearby lot) and inside a warehouse. The test run of the heavy-duty truck involved transporting 24,000 kg of load on urban and extra-urban (local and intercity) roads. The exhaust emissions and fuel mileage were determined for each of the stages as well as for the entire research cycle. [ABSTRACT FROM AUTHOR]

Understanding factors that drive the parking choice of commercial vehicles at delivery stops in cities can enhance logistics operations and the management of freight parking infrastructure, mitigate illegal parking, and ultimately reduce traffic congestion. In this paper, we focus on this decision-making process at large urban freight traffic generators, such as retail malls and transit terminals, that attract a large share of urban commercial vehicle traffic. Existing literature on parking behavior modeling has focused on passenger vehicles. This paper presents a discrete choice model for commercial vehicle parking choice in urban areas. The model parameters were estimated by using detailed, real-world data on commercial vehicle parking choices collected in two commercial urban areas in Singapore. The model analyzes the effect of several variables on the parking behavior of commercial vehicle drivers, including the presence of congestion and queueing, attitudes toward illegal parking, and pricing (parking fees). The model was validated against real data and applied within a discrete-event simulation to test the economic and environmental impacts of several parking measures, including pricing strategies and parking enforcement. [ABSTRACT FROM AUTHOR]

This paper examines a new hybrid intercontinental freight transport alternative (IFTA) that combines a logistics island (i.e. an offshore container port), vertical take-off and landing (VTOL) aircraft, and ocean vessel transport. The hybrid IFTA offers a 'midway' alternative for intercontinental shippers that is cheaper (and slower) than conventional air freight, but slightly faster and significantly more reliable (albeit, more expensive) than conventional ocean vessel transport calling at busy ports that may be subject to disruptive delays. To compare the proposed hybrid IFTA with the conventional air- and ocean-based IFTAs, this paper employs a utility maximization framework. A mathematical model determines the shipper value of time (VOT) range, normalized by payload, for which the proposed hybrid IFTA would be preferable to the conventional air- and ocean-based IFTAs. Preliminary results suggest that this range of shipper VOT, normalized by payload, is between $0.6/ton-hour and $22.9/ton-hour, indicating a potential market for the proposed hybrid IFTA might exist. Additionally, sensitivity analyses reveal several interesting insights; most notably, the attractiveness of the proposed hybrid IFTA hinges on decreasing the distance VTOL aircraft transport freight between the logistics island and an onshore warehouse or transloading facility. • Defines hybrid intercontinental freight transport alternative (IFTA). • Combines logistics island (offshore port), VTOL aircraft, ocean vessel transport. • Circumvents disruptive delays at major urban ports, enhances reliability. • Market potential assessment based on mathematical max utility framework. • Potential market for goods with moderate (high) value of time (reliability). [ABSTRACT FROM AUTHOR]

Understanding the mobility of surface freight transportation is relevant in urban planning and for developing public policies. Literature shows that most previous efforts on this topic rely on surveys and limited data. In contrast to other works, in this paper, we present an innovative methodology for characterizing last-mile freight transportation that uses a novel and copious data source: mobile phone data, which provides a broader scope. Our methodology involves calibrating supervised machine-learning models that allow us to link cell phones with truck drivers. In this endeavor, we construct several input variables that track mobile phone's daily movement patterns, including traveled distances, interactions with highway networks, and land use variables. We test our approach by conducting a case study in Santiago, Chile, for which we analyze mobility patterns and logistics indicators disaggregated by day, hour, and zoning. For this case, we show that all supervised models performed well regarding AUC, which can be attributed to the high granularity and handling of the data. However, we chose to use NGBoost in all subsequent experiments, as it provided slightly better results on our validation data. Our work has several implications for practice. For instance, our results can support decision-makers and policymakers in identifying critical areas where urban logistics centers and transportation interventions are needed. Finally, several research lines stem from our work, which include assessing the impact of incorporating geospatial information and the measurement of logistics sprawl over time. [ABSTRACT FROM AUTHOR]

• Formulated the autonomous truck platooning problem with platoon size limit and size-dependent fuel consumption. • Jointly optimized platoon formation, scheduling, and routing. • Proposed a computationally efficient exact algorithm. • Performed sensitivity analyses on platoon size limit and the diffusion and tightness of AT time windows. Autonomous trucks offer a promising avenue for enhancing the efficiency and reducing the environmental impact of road freight transportation. This paper examines a transitional phase towards a fully unmanned truck fleet, focusing on a platooning approach with a lead driver. We develop a novel optimization model for autonomous truck platooning that simultaneously considers platoon formation, scheduling, and routing to minimize costs related to labor and fuel. The model incorporates the possibility of detours, nonlinear fuel savings due to air-drag reduction, and the practical platoon size limit. We present an enhanced column generation method, termed the platoon-generation-and-updating approach, which demonstrates high effectiveness in reducing computational time and complexity. Our numerical analysis, based on the Hong Kong highway network, demonstrates the substantial cost advantages of autonomous truck platooning. It also investigates how platooning efficiency is influenced by various operating factors, including truck fleet size, platoon size restrictions, labor-to-fuel cost ratio, and the strictness of delivery time windows, with practical implications interwoven into the discussion. [ABSTRACT FROM AUTHOR]

Since early 2010s, the Green Routing Problem (GRP) has dominated the literature of logistics and transportation. The problem itself consists of finding a set of vehicle routes for a set of customers while minimizing the detrimental effects of transportation activities. These negative externalities have been intensively tackled in the last decade. Operations research studies have particularly focused on minimizing the energy consumption and emissions. As a result, the rich literature on GRPs has already reached its peak, and several early literature reviews have been conducted on various aspects of related vehicle routing and scheduling problem variants. The major contribution of this paper is that it represents a comprehensive review of the current reviews on GRP studies. In addition to that, it is an up-to-date review based on a new chronological taxonomy of the literature. The detailed analysis provides a useful framework for understanding the research gaps for the future studies and the potential impacts for the academic community. [ABSTRACT FROM AUTHOR]

Freight transportation network is an essential backbone for supporting the industrial activities and economic developments of the nation and global trade. In this paper, we extend the network-based measures recently developed by Xu et al. (2018) for assessing freight transportation network redundancy – an important component in making freight transportation networks more robust and resilient against disruptions. Redundancy of freight transportation networks is characterized by two network-based measures. The route diversity measure evaluates the existence of multiple efficient routes available for freight users or the degree of connections between a specific origin-destination (O-D) pair, while the network spare capacity measure quantifies the network-wide spare capacity with an explicit consideration of congestion effect and modal split. These two measures can complement each other by providing a two-dimensional characterization of freight transportation network redundancy that can be used to provide information to freight users as well as to assist network planners in making future infrastructure investment decisions to enhance the redundancy of freight transportation networks. A case study of the Utah freight network for transporting coal is provided to demonstrate the features of the two network-based redundancy measures as well as the applicability of assessing the redundancy of freight transportation networks. The analyses reveal that the two measures provide useful results from two perspectives that may be of benefit to freight carriers and transportation system planners. [ABSTRACT FROM AUTHOR]

The attraction area division is the foundation of distribution and organization of freight flow among railway stations. The development of railway container terminal, large railway freight distribution center, is closely related to logistics planning and economy development of local city. In this study, we divide freight flow attraction area of inland railway container terminal by using gravity model, break-point model and weighted-Voronoi-diagram with SPSS and ArcGIS. And then under the target of minimal cost and time window limitations, we develop 0-1 integer programming model for freight flow organization optimization between inland terminal and its attraction area. Finally, this paper takes railway container terminal in Harbin as an example to test model feasibility under different speeds from different transportation modes. The results show that it is necessary to divide attraction area when choosing reasonable transportation mode from feeder nodes to railway container terminal. The improvement of feeder transportation speed is an effective method to improve freight volume, increase railway revenue and realize sustainable development of China Railway (CR) Express. [ABSTRACT FROM AUTHOR]

Introduction: This paper presents an analytical model to contrast the carbon emissions from a number of goods delivery methods. This includes individuals travelling to the store by car, and delivery trucks delivering to homes. While the impact of growing home delivery services has been studied with combinatorial approaches, those approaches do not allow for systematic conclusions regarding when the service provides net benefit. The use of the analytical approach presented here, allows for more systematic relationships to be established between problem parameters, and therefore broader conclusions regarding when delivery services may provide a CO benefit over personal travel. Methods: Analytical mathematical models are developed to approximate total vehicle miles traveled (VMT) and carbon emissions for a personal vehicle travel scenario, a local depot vehicle travel scenario, and a regional warehouse travel scenario. A graphical heuristic is developed to compare the carbon emissions of a personal vehicle travel scenario and local depot delivery scenario. Results: The analytical approach developed and presented in the paper demonstrates that two key variables drive whether a delivery service or personal travel will provide a lower CO solution. These are the emissions ratio, and customer density. The emissions ratio represents the relative emissions impact of the delivery vehicle when compared to the personal vehicle. The results show that with a small number of customers, and low emissions ratio, personal travel is preferred. In contrast, with a high number of customers and low emissions ratio, delivery service is preferred. Conclusions: While other research into the impact of delivery services on CO emissions has generally used a combinatorial approach, this paper considers the problem using an analytical model. A detailed simulation can provide locational specificity, but provides less insight into the fundamental drivers of system behavior. The analytical approach exposes the problem's basic relationships that are independent of local geography and infrastructure. The result is a simple method for identifying context when personal travel, or delivery service, is more CO2 efficient. [ABSTRACT FROM AUTHOR]

Heavy Commercial Vehicle (HCV) parking is an important issue for commercial drivers due to concerns regarding parking supply, hours-of-service (HOS) laws, and electronic logging device (ELD) mandates. HOS laws are intended to reduce driver fatigue while ELD mandates ensure strict HOS compliance. Unfortunately, inadequate HCV parking availability may force drivers to make an undesirable choice: park illegally in a potentially unsafe location or drive longer than the law permits and face fines for HOS violations. These outcomes occur frequently throughout Canada and the United States, leading to safety and financial concerns for government jurisdictions and the broader public. Despite the importance of this topic, we lacked an exhaustive classification scheme for the systematic analysis of truck parking in a given area. Many studies have considered only public rest areas and likely underestimated the actual amount of viable HCV parking supply. Without accurate data on HCV parking locations and deficiencies, jurisdictions are unable to make optimal decisions. This paper developed a set of categories that can be used to classify locations used by HCV drivers for rest breaks on long journeys. The categories are based on a thorough literature review and detailed GPS data obtained for our study area in Peel Region, Ontario, Canada. The categories are exhaustive in that they include all HCV parking locations, both legal and unauthorized. The data-driven systematic approach contributes towards a better understanding of HCV parking supply for long-haul truck trips. • Heavy commercial vehicles (HCV) face potential parking shortages to accommodate hours of service (HOS) rest requirements. • A new classification scheme is developed to categorize various types of authorized and unauthorized parking. • Most authorized parking locations in the Region of Peel study area locate near large freight hubs such as Pearson Airport. • Unauthorized parking locations are spatially sprawled when compared to authorized parking locations. • Reduce unauthorized events by adding new HCV parking, expanding existing parking, or utilizing new technology. [ABSTRACT FROM AUTHOR]

Because of China's rapid economic development, its freight transportation system has grown to become one of China's high‐pollution‐emission sectors. However, there are few studies that pay close attention to measuring and improving the environmental performance of China's freight transportation system, especially in regard to seaports. In this paper, data envelopment analysis (DEA) is applied to measure the environmental performance of freight transportation seaports. In addition, we also provide benchmarking information to point the way to improving environmental performance effectively. Our proposed DEA model is based on the closest targets, which satisfies the strong monotonicity and can yield the most relevant solution for the inefficient seaports. An empirical study of 21 of China's primary freight transportation seaports shows that most of them have relatively good environmental performance. Among the five coastal port groups, the Bohai‐rim port group had the best environmental performance, whereas the Pearl River port group had the worst. Our data show significant differences between the best and worst performances, indicating that more measures should be taken to balance and coordinate the development between the five coastal port groups. [ABSTRACT FROM AUTHOR]

Robust road transportation networks are essential to facilitate truck movements between regions. Disruptions along certain road links could degrade the network's robustness and curtail regional commerce. A network is considered robust if the network-wide travel cost does not change significantly before and after disruptions. The network robustness index (NRI) is a well-known measure for examining the effect of reduced capacity on one or more links. It has been mainly applied to urban networks and passenger trips. In this paper, the NRI is applied to assess the robustness of the Ontario-wide truck network. Truck flows between the 49 census divisions within Ontario and 25 external zones for the year 2012 are modeled on the network of 35,254 road links and 14,444 associated nodes. Several scenarios of incrementally reduced capacity on specific critical links are devised and simulated. The NRI is calculated for each scenario to identify the level of network robustness. The locational effects of the capacity reductions were explored with the help of maps to assess the change in traffic volumes of the simulated scenarios relative to the base case. As expected, traffic diffuses or shifts to neighboring links when capacities are reduced. These results can be useful in infrastructure planning and the design of alternative routes to minimize the negative impact on traffic flows when disruptions occur. [ABSTRACT FROM AUTHOR]

In the United States, freight transportation consumes 9% of all energy consumed and emits 12% of all CO2 emissions in the entire economy. Freight energy consumption and CO2 emissions have also been growing faster than those of other economic sectors since 1980. In response, this paper surveys freight energy consumption trends from both a modal-disaggregate (e.g. truck, rail, ship, etc.) and commodity-disaggregate (e.g. food products, wood products, consumer electronics, etc.) perspective. A systems approach is used to delineate the boundary between the freight systems and other economic systems with which it interacts, and to provide a framework for understanding the structure of freight. From a modal perspective, it is found that the amount of freight energy consumed by trucks has remained at about two-thirds of the total for the past two decades. However, there are also some recent examples of growing use of rail, which can be expanded to make U.S. freight less energy intensive. On the commodity side, freight energy use is found to be concentrated in a limited number of products, such as food products, farm products, and nonmetallic minerals, so that collaboration with these industries can provide a focal point for reducing freight energy. The subsequent discussion considers other factors such as changes to supply chains, impact of geographic patterns of freight, dematerialization of products, and transitioning to low-carbon fuels. [ABSTRACT FROM AUTHOR]

Globally, even as environmental protection and sustainability are becoming increasingly important, freight transportation firms are faced with the enormous need to reduce the significant environmental burdens that accrue from transport vehicles. Eco-innovation can aid freight transport firms through fostering sustainable transportation alternatives at best possible costs to ensure effective decision- making for freight logistics sustainability. Yet, freight logistics companies are faced with numerous difficulties when attempting to implement eco-innovation practices along their supply chains. This paper therefore identifies the challenges to implementing eco-innovation practices for freight logistics sustainability to aid management to take informed decisions to overcome these challenges before the environmental burdens become critical. The Best- Worst method is adopted to evaluate and rank these challenges in terms of their relative importance in Nigeria, an emerging economy, which is characterized by increased consumption due to huge population size coupled with government green requirements. The results depict that unavailable funds, lack of clarity on the financial benefits of eco-innovation practices, poor technology infrastructure and reluctant attitude towards eco-innovation practices are the most pressing challenges amongst the challenges faced by Nigeria freight logistics companies. These results will provide insight and guidelines for decision-makers and policymakers in the freight logistics sector who seeks to integrate eco-innovation initiatives to achieve sustainability. [ABSTRACT FROM AUTHOR]

The paper suggests a method for determining the optimal location of service points (warehouses) based on the method for optimal planning of radiation therapy of malignant tumors. This method enabled us to identify the location of the most optimal number of warehouses taking into account their capacity for the required volume of freight transportation and distance from warehouses to consumers. The results of the study coincide with the results obtained by using the method of ant algorithm. The proposed method of finding the optimal location of warehouses enables to significantly minimize the cost of delivering goods from a producer to a consumer. [ABSTRACT FROM AUTHOR]

Abstract The rapid development of China's economy has led to a rapid increase in port throughput and made the issue of hinterland transport emissions more prominent. In this paper, a system dynamics model was established to project the long-term emissions of hinterland transportation. The model functions in a modular manner, consisting of core subsystems developed based on the classic four-step model of transportation, and several additional subsystems that are used to address the characteristics of the hinterland transport processes. The developed model was applied to a specific case in China to assess the long-term effects of alternative environmental policies on hinterland transport emissions. Through a comprehensive comparison of different policy scenarios, the model demonstrates explicitly how alternative environmental policies affect long-term emissions through a systematic intervention on a series of hinterland transport processes. The model also identifies the effective policies by which a lower emissions stock could be achieved. In addition, some suggestions for the policy making in hinterland transportation are provided. Graphical abstract Image 1009 Highlights • Some unique characteristics of hinterland transport processes are considered. • System dynamics modeling for long-term hinterland transport emissions projection. • Alternative modal shift policies are considered and compared by the model. • Policies' effects on both hinterland transport processes and emissions are shown. • The policies that effectively reduce hinterland transport emissions are identified. [ABSTRACT FROM AUTHOR]

• Technologies enable certain capabilities to road freight transportation systems. • 58 papers comprising Technologies-enabled capabilities are systematically reviewed. • An analysis of secondary data to verify the Readiness Level of the capabilities. • 32 technologies-enabled capabilities are highlighted. • 28 Technologies-enabled capabilities are at a commercial level. Several studies in the literature have already analyzed the role of adopting technologies in road freight transportation, encompassing mainly information and communication technologies (ICTs) and intelligent transportation systems (ITSs). However, to the best of the authors' knowledge, no studies have sought to identify technology-enabled capabilities in road freight transportation systems, nor is there any research in this specific field that considers different groups of technologies, including technologies related to the advent of Industry 4.0 (e.g., IoT, blockchain, augmented reality). Our paper identifies technology-enabled capabilities in road freight transportation and evaluates the readiness level (RL) for these capabilities to fill this gap. We use a multi-method approach that includes a systematic literature review (SLR) to identify the technology-enabled capabilities, an analysis of secondary data to verify the RL of each of the capabilities identified in the SLR, and finally, the validation of the data by experts. The findings reveal 32 technology-enabled capabilities in road freight transportation systems, grouped into six categories. Furthermore, we were able to find examples of commercial applicability for 28 of these capabilities. This study contributes to the road freight transportation literature by providing academics and professionals with an overview of the capabilities enabled by technology. Further, based on the discussion of the RL of these capabilities, stakeholders at different levels of road freight transportation (e.g., shippers, carriers, regulators) can understand which capabilities can be adopted in the operational context, as well as which capabilities still require investment in research to reach a commercial level. [ABSTRACT FROM AUTHOR]

Purpose: Targeting the problem of overloaded trucking regarding the Highway Transportation of iron ore from Caofeidian to Tangshan (HTCT), this paper aims to assess the long-term effects of alternative Truck Weight Regulation (TWR) policies on the sustainability of the HTCT. Design/methodology/approach: This paper develops a model for policy evaluation using System Dynamics (SD). The model, comprising six interrelated modules, is capable of simulating the effects of TWR policies on trucking issues, such as freight flow, truck traffic flow, pavement performance, highway transport capacity and trucking time. The model further sheds light on the Cumulative Economic Cost (CEC), including the transport cost and time cost of freight owners, and the Cumulative Social Cost (CSC), including the pavement maintenance cost, greenhouse gas emission cost, atmospheric pollutants emission cost and traffic accidents cost, so the effects of TWR policies on the sustainability of the HTCT could be evaluated. Findings: According to the different values of the overload ratio that are allowed by policy, alternative TWR policies are classified into three types, which are The Rigid Policy (TRP), The Moderate Policy (TMP) and The Tolerant Policy (TTP). The results show that the best policy for the sustainability of the HTCT depends on the relative importance of CSC, which is expected by the local government. To be specific, (1) if CSC is considered to be much less important than CEC, the local government should continue implementing TTP with the maximum overload ratio; (2) if CSC is considered to be much more important than CEC, then TRP is recommended; and (3) if CSC is considered to be slightly more important than CEC, TMP with an overload ratio of 80% is best. Practical implications: The conclusions of this paper may help the local government design appropriate TWR policies to achieve the sustainability of the HTCT. Originality/value: To the best of our knowledge, this is the first effort to evaluate TWR policies on the sustainability of the highway freight system based on SD. [ABSTRACT FROM AUTHOR]

This paper provides fuel price elasticity estimates for single-unit truck activity, where single-unit trucks are defined as vehicles on a single frame with either (1) at least two axles and six tires; or (2) a gross vehicle weight greater than 10,000 lb. Using data from 1980 to 2012, this paper applies first-difference and error correction models and finds that single-unit truck activity is sensitive to certain macroeconomic and infrastructure factors (gross domestic product, lane miles expansion, and housing construction), but is not sensitive to diesel fuel prices. These results suggest that fuel price elasticities of single unit truck activity are inelastic. These results may be used by policymakers in considering policies that have a direct impact on fuel prices, or policies whose effects may be equivalent to fuel price adjustments. [ABSTRACT FROM AUTHOR]

Freight transportation by railroads is an integral part of the U.S. economy. Identifying critical rail infrastructures can help stakeholders prioritize protection initiatives or add necessary redundancy to maximize rail network resiliency. The criticality of an infrastructure element, link or yard, is based on the increased cost (delay) incurred when that element is disrupted. An event of disruption can cause heavy congestion so that the capacity at links and yards should be considered when freight is re-routed. This paper proposes an optimization model for making-up and routing of trains in a disruptive situation to minimize the system-wide total cost, including classification time at yards and travel time along links. Train design optimization seeks to determine the optimal number of trains, their routes, and associated blocks, subject to various capacity and operational constraints at rail links and yards. An iterative heuristic algorithm is proposed to attack the computational burden for real-world networks. The solution algorithm considers the impact of volume on travel time in a congested or near-congested network. The proposed heuristics provide quality solutions with high speed, demonstrated by numerical experiments for small instances. A case study is conducted for the network of a major U.S. Class-I railroad based on publicly available data. The paper provides maps showing the criticality of infrastructure in the study area from the viewpoint of strategic planning. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we study an emission-based heterogeneous fixed fleet vehicle routing problem (E-HFFVRP) with considerations of fuel and carbon emissions. This problem involves routing a fleet of a fixed number of vehicles with various capacities to serve a set of customers. It seeks to minimize the objective function, which incorporates the fixed expenses and variable costs consisting of fuel consumptions and carbon emissions. It is a new variant of the heterogeneous fixed fleet vehicle routing problem (HFFVRP), in which a fleet consists of a fixed number of vehicles with different capacities, fixed costs and variable costs. We formulate this problem with a mixed integer programming model by introducing an approach to calculate fuel and carbon emissions. Moreover, a split-based adaptive tabu search (SATS) algorithm using an optimal split scheme and an adaptive tabu search algorithm is proposed. Its key features and components are designed accordingly. Results of numerical experimentations on two sets of generated instances confirm the efficiency and effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

The Pickup and Delivery Problem with Time Windows and Scheduled Lines (PDPTW-SL) consists of routing and scheduling a set of vehicles, by integrating them with scheduled public transportation lines, to serve a set of freight requests within their time windows. This paper presents an exact solution approach based on a branch-and-price algorithm. A path-based set partitioning formulation is used as the master problem, and a variant of the elementary shortest path problem with resource constraints is solved as the pricing problem. In addition, the proposed algorithm can also be used to solve the PDPTW with transfers (PDPTW-T) as a special case. Results of extensive computational experiments confirm the efficiency of the algorithm: it is able to solve small- and medium-size instances to optimality within reasonable execution time. More specifically, our algorithm solves the PDPTW-SL with up to 50 requests and the PDPTW-T with up to 40 requests on the considered instances. The online appendix is available at https://doi.org/10.1287/trsc.2017.0798. [ABSTRACT FROM AUTHOR]

Abstract: Environmental sustainability has recently become more and more of a concern among both academics and practitioners. In particular logistics services operations can play a significant role in reducing the environmental burden of the supply chain. Although studies on these issues have been progressively increasing in the extant literature, still little investigation has been performed among Logistics Service Providers (LSPs). The present paper aims to fill this gap and provides the results of an empirical study on the adoption of environmental initiatives in the contract logistics industry, along with the metrics used for environmental performance measurement and the barriers and drivers that may hinder or facilitate the adoption of these initiatives. After a careful literature review, a framework was developed to identify the initiatives towards environmental sustainability with a focus on companies involved in logistics and transportation processes. The framework was applied to a set of ten LSPs by examining their environmental reporting and a sub-set of three companies was finally selected for in-depth interviews. An analysis of the environmental sustainability initiatives of primary multinational LSPs and their adoption level is presented. The present paper contributes to the knowledge of environmental sustainability for logistics and transportation and offers new insights in theory, paving the way for further research on these topics. [Copyright &y& Elsevier]

The feasibility of implementing short sea shipping (SSS) between two specific ports has been typically approached on the operative level, in terms of time and cost for a specific origin–destination pair. This paper focuses on the strategic level. Particularly, its goal is to study the potential of SSS in different industrial sectors by analysing their freight-distribution strategies. To achieve the objective, some standard freight-distribution strategies are defined based on the requirements of the industry, the demand and the product being transported. The information is complemented with a survey of more than 100 Spanish companies distributing internationally. As a result it is concluded that there are economies of scale related to the size of the carrier (the ship) and its capacity to absorb the variability in demand. This potential increases with the cargo value. Additionally, a framework of supply/distribution chains is provided which can help to identify potential customers/sectors and the feasibility of new potential shipping lines. The value of this paper resides in its approach (strategic, instead of operational/tactical), and the solid groundwork point provided for future researchers. [ABSTRACT FROM AUTHOR]

People, industries, and public agencies all face the possibility of sudden events that disrupt their normal activities. Disasters on the transportation network, whether attributable to nature, human error, or human intent, raise awareness of the need for plans of action to quickly restore mobility. Resilience of the transportation network is the capacity to absorb the effects of a disruption and to quickly return to normal operating levels. Resilience measures are useful to evaluate and predict disruptions and recovery and to guide infrastructure investments that protect against those disruptions or that accelerate recovery after a disruption. This paper presents a methodology for estimating two composite resilience measures-reduction and recovery. The method is illustrated by using resilience triangles derived from sampled truck speeds and counts along the Interstate corridor from Hudson to Beloit, Wisconsin during two significant weather events in 2008. This paper presents a set of criteria, on the basis of observed effects on various sections of the highway corridor, to qualify the computed resilience measures. In this paper, the focus is on generalizing the characteristics of the resilience response rather than characteristics of the corridor sections that lead to patterns of the response for each section. The criteria and the measures together are a useful tool to evaluate resilience. [ABSTRACT FROM AUTHOR]

This paper presents a continuous approximation model for the vehicle routing problem for emissions minimization (EVRP) and demonstrates the model's applicability and usefulness with numerical studies based on implementations of the Solomon test instances. The EVRP is a variant of the time-dependent vehicle routing problem (TDVRP) in which minimizing emissions is an additional objective of the model. The continuous approximation model presented in this paper will facilitate strategic planning of one-to-many distribution systems and evaluate the effects of emissions costs. Furthermore, results from the continuous model can provide guidelines for constructing solutions for the discrete EVRP. Results from a sensitivity analysis indicated that the optimal number of dispatches during the peak period is smaller than the optimal number of dispatches during the off-peak period when considering the temporal effects of congestion. Results revealed that the potential cost savings attributable to incorporating emissions in distribution problems are considerable. Incorporating emissions costs in distribution problems will contribute toward having more environmentally sustainable distribution systems. The proposed continuous approximation model can be extended for other specific conditions (e.g., when considering pipeline inventory, storage restrictions, different customers, random demand, discriminating strategies, etc.). [ABSTRACT FROM AUTHOR]

Abstract: While it is certainly too early to make a definitive assessment of the effectiveness of Intelligent Transportation Systems (ITS), it is not to take stock of what has been achieved and to think about what could be achieved in the near future. In our opinion, ITS developments have been up to now largely hardware-driven and have led to the introduction of many sophisticated technologies in the transportation arena, while the development of the software component of ITS, models and decision-support systems in particular, is lagging behind. To reach the full potential of ITS, one must thus address the challenge of making the most intelligent usage possible of the hardware that is being deployed and the huge wealth of data it provides. We believe that transportation planning and management disciplines, operations research in particular, have a key role to play with respect to this challenge. The paper focuses on Freight ITS: Commercial Vehicle Operations and Advanced Fleet Management Systems, City Logistics, and electronic business. The paper reviews main issues, technological challenges, and achievements, and illustrates how the introduction of better operations research-based decision-support software could very significantly improve the ultimate performance of Freight ITS. [Copyright &y& Elsevier]

The principal focus of this paper is to study carrier pricing decisions for a type of vehicle routing problems defined in a competitive and dynamic environment. This paper introduces the vehicle routing problem in a competitive environment (VRPCE) as an extension of the traveling-salesman problem with profits (TSPP) to a dynamic competitive auction environment. In the VRPCE, the carrier must estimate the incremental cost of servicing new service requests as they arrive dynamically. The paper presents a rigorous and precise treatment of the sequential pricing and costing problem that a carrier faces in such an environment. The sequential pricing problem presented here is an intrinsic feature of a sequential auction problem. In addition to introducing the formulation of this class of problems and discussing the main sources of difficulty in devising a solution, a simple example is constructed to show that carriers' prices under first-price auction payment rules do not necessarily reflect the cost of servicing transportation requests. An approximate solution approach with a finite rolling horizon is presented and illustrated through numerical experiments, in competition with a static approach with no look-ahead. [ABSTRACT FROM AUTHOR]

Physical distribution, logistics and freight transport are currently being shaped by new technologies, corporate restructuring, and a changing market environment. Following the rapid growth of logistics, the demand for distribution facilities increases significantly. As a consequence, logistics real estate markets have emerged, shaping local development practices. By establishing distri-bution centres as single entities and integrated freight centres as agglomerations, they contribute to the formation of ‘regional distribution complexes’. The paper aims to exemplify this interrelation with two case studies in Berlin-Brandenburg, Germany: first a publicly developed integrated freight centre, offering multi-modal transport access and logistics services, and second a dispersed logistics site off the regional beltway, developed with respect to market requirements only. The paper finds that rising locational competition contributes to accelerated land consumption and further dispersal. Speculative development and outsourcing of facilities are ‘mobilising’ not only goods flows but also logistics infrastructure. Both practices, originally developed in the USA and the UK, are now changing land markets in continental Europe and affect urban and regional development. [ABSTRACT FROM AUTHOR]

In the classical vehicle-routing problem (VRP) the objective is to service some geographically scattered customers with a given number of vehicles at the minimal cost. In the present paper, we consider a variant of the VRP where the vehicles should deliver some goods between groups of customers. The customers have an associated time window, a precedence number, and a quantity. Each vehicle should visit the customers within their time windows, in nondecreasing order of precedence respecting the capacity of the vehicle. The problem will be denoted the pickup-and-delivery problem with time windows and precedence constraints (PDPTWP). The PDPTWP has applications in the transportation of live animals where veterinary rules demand that the livestocks are visited in a given sequence in order not to spread specific diseases. We propose a tighter formulation of the PDPTWP based on Dantzig-Wolfe decomposition. The formulation splits the problem into a master problem, which is a kind of set-covering problem, and a subproblem that generates legal routes for a single vehicle. The LP-relaxation of the decomposed problem is solved through delayed column generation. Computational experiments show that the obtained bounds are less than 0.24% from optimum for the considered problems. As solving the pricing problems takes up the majority of the solution time, a reformulation of the problem is proposed that makes use of the precedence constraints. By merging customers having the same precedence number into "super nodes," the pricing problem may be reformulated as a shortest-path problem defined on an acyclic layered graph. This makes it possible to solve the pricing problem in pseudopolynomial time through dynamic programming. The paper concludes with a comprehensive computational study involv ing real-life instances from the transportation of live pigs. It is demonstrated that instances with up to 580 nodes can be solved to optimality. [ABSTRACT FROM AUTHOR]

Research on short and long distance freight transport artificially separates the segments of transport chains, which are interrelated and which might be better viewed as a continuum. The eight papers of this special issue aim to bridge this gap. The major disruptions in global supply chains of the last years brought to light the vulnerability of the transport system and the need for a more integrated approach for effective transport policies. This special issue explores some of the challenges facing freight transport in three research areas: supply chain studies, transport networks and warehouse location. It also identifies avenues for further research. [ABSTRACT FROM AUTHOR]

The Pickup and Delivery Problem with Time Windows, Scheduled Lines and Stochastic Demands (PDPTW-SLSD) concerns scheduling a set of vehicles to serve a set of requests, whose expected demands are known in distribution when planning, but are only revealed with certainty upon the vehicles’ arrival. In addition, a part of the transportation plan can be carried out on limited-capacity scheduled public transportation line services. This paper proposes a scenario-based sample average approximation approach for the PDPTW-SLSD. An adaptive large neighborhood search heuristic embedded into sample average approximation method is used to generate good-quality solutions. Computational results on instances with up to 40 requests (i.e., 80 locations) reveal that the integrated transportation networks can lead to operational cost savings of up to 16% compared with classical pickup and delivery systems. [ABSTRACT FROM AUTHOR]

This paper estimates fuel price elasticities of combination trucking operations in the United States between 1970 and 2012. We evaluate trucking operations in terms of vehicle miles traveled and fuel consumption for combination trucks. Our explanatory variables include measures of economic activity, energy prices, and indicator variables that account for important regulatory shifts and changes in data collection and reporting in national transportation datasets. Our results suggest that fuel price elasticities in the United States’ trucking sector have shifted from an elastic environment in the 1970s to a relatively inelastic environment today. We discuss the importance of these results for policymakers in light of new policies that aim to limit energy consumption and reduce greenhouse gas emissions from heavy-duty vehicles. [ABSTRACT FROM AUTHOR]

While recent urban planning efforts have focused on the management of growth into developed areas, the research community has not examined the impacts of these development patterns on urban goods movement. Successful implementation of growth strategies has multiple environmental and social benefits but also raises the demand for intra-urban goods movement, potentially increasing conflicts between modes of travel and worsening air quality. Because urban goods movement is critical for economic vitality, understanding the relation between smart growth and goods movement is necessary in the development of appropriate policies. This paper reviews the academic literature and summarizes the results of six focus groups to identify gaps in the state of knowledge and suggest important future research topics in five sub-areas of smart growth related to goods movement: (1) access, parking, and loading zones; (2) road channelization and bicycle and pedestrian facilities; (3) land use; (4) logistics; and (5) network system management. [ABSTRACT FROM PUBLISHER]

The planning of freight transportation activities creates benefits as well as costs. Among those costs, some of them, namely externalities, fall on other people/society that have no direct relevance to the operations of transportation. Such externalities are accrued expenses which should be addressed by actual pricing policies to enable an efficient and sustainable freight transportation system. This paper reviews externalities in quantitative terms, and then provides pricing studies of these costs per unit of freight transported along with the most recent estimations. The associated negative externalities are structured by transportation mode (road, rail, maritime, and air). [ABSTRACT FROM AUTHOR]

The zone system used for freight data collection and the geographic resolution of published data has a significant impact on analysis and planning. The majority of existing freight model zones are created in an ad hoc way. In this paper, a new model-based design method is introduced to develop freight zones for the continental USA. It focuses on two methodology issues: (1) the criteria that represent the desired properties of a zone system and (2) the constraints that govern the shape, size, and continuity of zones. The method is applied to the continental USA by optimizing an interzonal travel distance weighted by freight flows using county-level freight data. Several optimal national-level freight zone systems with different numbers of zones are developed. The results indicate that a 300-zone system provides a balance between the number of zones and optimization measures where the currently available public freight data are provided with approximately 100 zones. [ABSTRACT FROM PUBLISHER]

• A new energy minimizing drone delivery problem with range constraint is introduced. • Explicit calculations of drone energy consumption and the drone range are included. • A nonlinear model and its second order cone program reformulation are presented. • The formulation is strengthened by perspective cuts. • An extensive computational study on a real data set is conducted. This paper introduces the Energy Minimizing and Range Constrained Drone Delivery Problem (ERDDP) in which drones are used to make deliveries to a number of customers and the drones themselves are transported by traditional vehicles that act as launch points. The ERDDP consists of (i) selecting the launch points from a potential set of sites from where drones will take off to serve a number of customers, (ii) assignments of customers to the launch points, and (iii) the speed at which drones are to travel between the customers and the launch points. The paper presents a nonlinear model for the ERDDP, which minimizes the total operational cost including an explicit calculation of the energy consumption of the drone as a function of the drone speed. The deliveries are limited by both a service time bound and the range of the drone. The model is reformulated using second order cone programming, and subsequently strengthened by the use of perspective cuts, that allows the use of off-the-shelf optimization software to solve the problem. Computational results are presented on a realistic data set that quantifies the effect of various parameters on location, assignment and speed decisions. [ABSTRACT FROM AUTHOR]

This paper contributes to the existing research on freight transportation, spatial and land use planning by investigating an improved spatial aggregation technique to delineate desirable freight traffic analysis zones. Zoning is a process of spatially aggregating several predefined basic spatial units (BSUs) into multiple zones. It plays a vital role in the transportation planning and decision-making process and is well-documented as the modifiable areal unit problem (MAUP). MAUP involves aggregating BSUs to obtain optimal zones satisfying specific criteria and constraints. This paper proposes an improved spatial aggregation methodology to develop a freight traffic analysis zone system by applying the multiobjective optimization concept using a genetic algorithm. The decision variables, namely, (i) Freight trip density; (ii) Number of establishments; (iii) Employment density; and (iv) Compactness, are chosen to represent the elements of freight, passenger traffic, and land use. The problem is formulated as a multiobjective network partitioning problem. The four objectives aim to create zones with better homogeneity and compactness. It is solved using a genetic algorithm with a weighted distance metric approach to prioritize the four objectives. Results show that zones resulting from the improved methodology are superior to the existing zones in terms of homogeneity of decision variables and compactness. The findings are expected to help the decision-making process of urban, transportation, and land-use planners in selecting appropriate freight traffic zone delineation strategies for a given region. • Multiobjective optimization concept is applied to develop freight traffic analysis zones (FTAZ) • Decision variables represent the characteristics of freight, passenger traffic, and land use. • Weighted distance metric approach using a genetic algorithm is used to prioritize zoning objectives • Findings suggest that FTAZs are superior to existing zones in homogeneity and compactness [ABSTRACT FROM AUTHOR]

Tackling poverty has been one of the greatest global challenges and a prerequisite to sustainable development of countries. Countries implement nationally appropriate social protection systems and measures to address poverty. This paper addresses an aid system adopted by the government in Turkey where significant amounts of coal is distributed to poor families each year. The objective of the coal aid system is to complete the delivery of coal to poor families by the start of winter. However, an analysis of the data from previous years indicates that the distribution to many families cannot be completed on time. This results from the fact that planning is done manually and by trial-and-error as there is no system that can be used for distribution planning. This paper describes the planning problem encountered and develops a mathematical model to solve it. The proposed model is a multimodal, multicommodity, and multiperiod linear programming (LP) model. The model can be used to develop and update a distribution plan as well as to answer several what-if questions with regard to capacities, time constraints, and so forth. The model is solved using CPLEX for several problem instances obtained under different scenarios using data for the year 2012. The results show that at least 9% cost savings and about 40% decrease in distribution completion time can be achieved when the model is used. We analyze scenario results qualitatively and quantitatively and provide several insights to the decision makers. As a part of quantitative analysis, we develop regression models to predict optimal costs based on several factors. Our main contribution is to provide an efficient and effective tool to handle a large-scale real-world problem. The model has also helped to prove that the organization responsible for distribution planning may move from the current planning practice to an all-encompassing top-down approach. • "To end poverty in all its forms everywhere" is the first of 17 UN sustainable development goals (SDGs). • Distribution of coal to poor families is a national aid system adopted to tackle poverty. • A multimodal, multicommodity, and multiperiod linear programming model is developed for planning coal distribution. • The model is utilized to solve scenarios based on different combinations of several parameters. • Scenario results are analyzed qualitatitely and using regression analysis to provide insights. [ABSTRACT FROM AUTHOR]

This paper presents a framework which includes empirical modelling methods to estimate freight transportation between defined zones. In this method, observed origin and destination matrices for each type of freight are constituted based on the link counts and the roadside truck survey data. The gravity method is selected to estimate origin and destination matrices by using observed link flows, gross domestic product by provinces and interzonal distances. Advanced statistical techniques and regression analyses are used to estimate the coefficients of the gravity method. The final freight transportation matrix is calibrated with the link flows data by using iterative techniques. The developed method was applied to find the origin and destination matrix of the total freight transportation in Turkey and successful results were obtained. [ABSTRACT FROM AUTHOR]

The concept of freight consolidation center (FCC) has emerged in recent years. Although several case studies have indicated that FCCs are beneficial to the operation of urban transportation systems, the implementation of this concept has proven difficult because the construction and operation of a FCC involves the coordination of different, and conflicting, stakeholders. Unlike other traditional approaches, this paper investigates the FCC development issue using experimental economics. First, profit functions are defined for involved stakeholders; based on those profit functions, four players-carriers, operators, government, and residents-bid on rent, financial incentives, and wages to maximize their own profits. Eight scenarios are analyzed and compared to determine potential influential factors and appropriate conditions for FCC decision making. Results show that public-private partnership lowers rent and increases wages, which leads to higher carrier, operator, and resident profits. A central location lowers rent, wages, financial incentives, and all stakeholders' profits. A larger carrier size benefits all stakeholders. In conclusion, the appropriate conditions for FCC development are public-private partnerships in noncentral locations with large carrier sizes. [ABSTRACT FROM AUTHOR]