Showing papers in "Networks and Spatial Economics in 2016"

Influence of social networks on latent choice of electric cars : a mixed logit specification using experimental design data

Abstract: Electric cars can potentially make a substantial contribution to the reduction of pollution and noise. The size of this contribution depends on the acceptance of this new technology in the market. This paper reports on the design and results of an elaborate stated choice experiment to investigate the effects of vehicle attributes, contextual and social network attributes on the latent demand for electric cars. The study contributes to the existing literature primarily by explicitly modelling the effects of different elements of social networks on the latent demand for electric cars. Moreover, the number of attributes included in the study design exceeds the typical number of attributes used in previous research, making the model more sensitive to a larger spectrum of variables. Two different mixed logit models are estimated: one with random parameters for vehicle attributes and contextual attributes and fixed effects for the social network attributes; one with random effects for social network attributes and fixed effects for the remaining attributes. Results indicate substantive differences between these two models in terms of the shape of utility curves. Overall, vehicle attributes are most important in the choice of electric cars, followed by social influence attributes. The effects of social network are relatively small.

Sustainability SI: Optimal Prices of Electricity at Public Charging Stations for Plug-in Electric Vehicles

Abstract: With an increasing deployment of plug-in electric vehicles, evaluating and mitigating the impacts of additional electrical loads created by these vehicles on power distribution grids become more important. This paper explores the use of prices of electricity at public charging stations as an instrument, in couple of road pricing, to better manage both power distribution and urban transportation networks. More specifically, a multi-class combined distribution and assignment model is formulated to capture the spatial distribution of plug-in electric vehicles across the transportation network and estimate the electrical loads they impose on the power distribution network. Power flow equations are subsequently solved to estimate real power losses. Prices of electricity at public charging stations and road tolls are then optimized to minimize both real power losses in the distribution grid and total travel time in the urban transportation network. The pricing model is formulated as a mathematical program with complementarity constraints and solved by a manifold suboptimization algorithm and a pattern search method. Numerical examples are presented to demonstrate the proposed model and solution algorithms.

The Electric Vehicle Shortest-Walk Problem With Battery Exchanges

Abstract: Electric vehicles (EV) have received much attention in the last few years. Still, they have neither been widely accepted by commuters nor by organizations with service fleets. It is predominately the lack of recharging infrastructure that is inhibiting a wide-scale adoption of EVs. The problem of using EVs is especially apparent in long trips, or inter-city trips. Range anxiety, when the driver is concerned that the vehicle will run out of charge before reaching the destination, is a major hindrance for the market penetration of EVs. To develop a recharging infrastructure it is important to route vehicles from origins to destinations with minimum detouring when battery recharging/exchange facilities are few and far between. This paper defines the EV shortest-walk problem to determine the route from a starting point to a destination with minimum detouring; this route may include cycles for detouring to recharge batteries. Two problem scenarios are studied: one is the problem of traveling from an origin to a destination to minimize the travel distance when any number of battery recharge/exchange stops may be made. The other is to travel from origin to destination when a maximum number of stops is specified. It is shown that both of these problems are polynomially solvable and solution algorithms are provided. This paper also presents another new problem of finding the route that minimizes the maximum anxiety induced by the route.

Sustainability SI: Multimode Multicommodity Network Design Model for Intermodal Freight Transportation with Transfer and Emission Costs

Abstract: Intermodal freight transportation is concerned with the shipment of commodities from their origin to destination using combinations of transport modes. Traditional logistics models have concentrated on minimizing transportation costs by appropriately determining the service network and the transportation routing. This paper considers an intermodal transportation problem with an explicit consideration of greenhouse gas emissions and intermodal transfers. A model is described which is in the form of a non-linear integer programming formulation, which is then linearized. A hypothetical but realistic case study of the UK including eleven locations forms the test instances for our investigation, where uni-modal with multi-modal transportation options are compared using a range of fixed costs.

A Model of Green Acceptance and Intentions to Use Bike-Sharing: YouBike Users in Taiwan

Abstract: With the emphasis on sustainability in transportation, bike-sharing systems are gaining popularity. This paper investigates the attitudes of users of a bike-sharing system with the aim of identifying their priorities, thus allowing local governments to focus their efforts most effectively on enhancing users’ intentions to use such systems. The relationships among green perceived usefulness (the extent to which individuals believe that a bike-sharing system will improve the environmental performance of some part of their life within a specific context), user attitude and perceived ease of use with green intentions, and the mediation effect of user attitude towards bike-sharing are explored. The focus of the study is on how to enhance green intentions via perceived usefulness, perceived ease of use and user attitude of the green technology acceptance model (green TAM) (Davis 1989). The two-step approach of structural equation modeling was applied to analyze the empirical results, which indicated that green perceived usefulness and user attitude have positive influences on the green intentions of 262 users and 262 non-users from ten sampled bike-sharing sites around the central administrative districts of Taipei. However, user attitude has the highest mediation effect on green intentions, and perceived ease of use does not have a significant effect on intentions for either users or non-users. Therefore, governmental institutions can strive to improve the attitudes of bike-sharing users and non-users, their green perceived usefulness, and perceived ease of use to strengthen their intentions to use this mode of sustainable transportation.

Sustainability SI: Logistics Cost and Environmental Impact Analyses of Urban Delivery Consolidation Strategies

Abstract: Among new, innovative city logistics strategies, urban delivery consolidation has received increasing academic and practical attention mostly in Europe and Japan. It is believed to bring cost savings and environmental benefits with the right setting. This paper demonstrates an alternative modeling framework to examine, from the strategic planning perspective, the effectiveness of urban delivery consolidation in terms of monetary logistics cost, energy consumption and PM2.5 emissions with respect to a number of operational (e.g., rent cost, customer demand) and policy factors (e.g., commercial vehicle size restriction in city centers). The framework consists of two key modeling components: the Continuous Approximation (CA) method to model urban delivery (the so-called last-mile delivery) and the Motor Vehicle Emission Simulator (MOVES by the U.S. Environmental Protection Agency) to estimate the energy consumption and PM2.5 emissions associated with the logistics activities. It is found that the potential logistics and environmental benefits of UCC could come from either improving the utilization of the vehicle capacity through consolidation, or shifting the more expensive storage cost from customers in the city center to the less expensive UCC rent cost—due to a less centralized location and/or government subsidy or other cost sharing mechanisms—outside of the city center. However, UCC could achieve those benefits compared to non- consolidation strategies only under certain conditions, for example when there is an economy of scale or high customer density (i.e., high shipping volume) in the service area. The paper discusses in detailed under what assumptions and conditions UCC could work. Study limitations and future work are also presented.

Robust Multi-period Fleet Allocation Models for Bike-Sharing Systems

Abstract: This paper presents mathematical programming models that generate optimal daily allocation of bicycles to the stations of a bike-sharing system. First, a time-space network is constructed to describe time-dependent bike flows in the system. Next, a bike fleet allocation model that considers average historical demand and fixed fleet size is established based on the time-space network. In addition to fleet allocation in multiple periods, this model generates least cost empty bicycle redistribution plans to meet demand in subsequent time periods. The model aims to correct demand asymmetry in bike-sharing systems, where flow from one station to another is seldom equal to the flow in the opposing direction. An extension of the model that relaxes the fleet size constraint to determine optimal fleet size in supporting planning stage decisions is also presented in the paper. Moreover, we describe uncertain bike demands using some prescribed uncertainty sets and develop robust bike fleet allocation models that minimize total system cost in the worst-case or maximum demand scenarios derived from the uncertainty sets. Numerical experiments were conducted based on the New Taipei City’s public bike system to demonstrate the applicability and performance of the proposed models. In addition, this research considers two performance measures, robust price and hedge value, in order to investigate the tradeoff between robustness and optimality, as well as the benefit of applying robust solutions relative to nominal optimal solutions in uncertain demand situations.

Modeling Mode and Route Similarities in Network Equilibrium Problem with Go-Green Modes

Abstract: Environmental sustainability is a common requirement on the development of various real-world systems, especially on road transportation systems. Motorized vehicles generate a large amount of harmful emissions, which have adverse effects to the environment and human health. Environmental sustainability requires more promotions of ‘go-green’ transportation modes such as public transit and bicycle to realize the increasing travel demands while keeping the environmental expenses low. In this paper, we make use of recent advances in discrete choice modeling to develop equivalent mathematical programming formulations for the combined modal split and traffic assignment (CMSTA) problem that explicitly considers mode and route similarities under congested networks. Specifically, a nested logit model is adopted to model the modal split problem by accounting for mode similarity among the available modes, and a cross-nested logit model is used to account for route overlapping in the traffic assignment problem. This new CMSTA model has the potential to enhance the behavioral modeling of travelers’ mode shift between private motorized mode and ‘go-green’ modes as well as their mode-specific route choices, and to assist in quantitatively evaluating the effectiveness of different ‘go-green’ promotion policies.

Organization Mining Using Online Social Networks

Abstract: Complementing the formal organizational structure of a business are the informal connections among employees. These relationships help identify knowledge hubs, working groups, and shortcuts through the organizational structure. They carry valuable information on how a company functions de facto. In the past, eliciting the informal social networks within an organization was challenging; today they are reflected by friendship relationships in online social networks. In this paper we analyze several commercial organizations by mining data which their employees have exposed on Facebook, LinkedIn, and other publicly available sources. Using a web crawler designed for this purpose, we extract a network of informal social relationships among employees of targeted organizations. Our results show that it is possible to identify leadership roles within the organization solely by using centrality analysis and machine learning techniques applied to the informal relationship network structure. Valuable non-trivial insights can also be gained by clustering an organization’s social network and gathering publicly available information on the employees within each cluster. Knowledge of the network of informal relationships may be a major asset or might be a significant threat to the underlying organization.

Towards High-Resolution First-Best Air Pollution Tolls

Abstract: In this paper, an approach is presented to calculate high-resolution first-best air pollution tolls with respect to emission cost factors provided by Maibach et al. (2008). Dynamic traffic flows of a multi-agent transport simulation are linked to detailed air pollution emission factors. The monetary equivalent of emissions is internalized in a policy which is then used as a benchmark for evaluating the effects of a regulatory measure—a speed limitation to 30 km / h in the inner city of Munich. The calculated toll, which is equal to simulated marginal costs in terms of individual vehicle attributes and time-dependent traffic states, results in average air pollution costs that are very close to values in the literature. It is found that the regulatory measure is considerably less successful in terms of total emission reduction. It reduces emissions of urban travelers too strongly while even increasing the emissions of commuters and freight, both leading to a increase in deadweight loss. That is, the regulatory measure leads to higher market inefficiencies than a “do-nothing” strategy: too high generalized prices for urban travelers, too low generalized prices for commuters and freight. Finally, long-term changes in the vehicle fleet fuel efficiency are assumed as a reaction to the Internalization policy. The results indicate, however, that the long-term effect of emission reduction is dominated by the short-term reactions and by the assumed improvement in fleet fuel efficiency; the influence of the resulting route and mode choice decisions turns out to be relatively small.

Dynamic Modeling of Performance Indices for Planning of Sustainable Transportation Systems

Abstract: Recently, sustainability has become a very important research area in transportation because of the dependencies between transportation, economic, and environmental systems. A great deal of research is being conducted regarding various aspects in order to try to understand these interdependencies. However, still there is a need to capture the behavior of such systems over time. This study attempts to build dynamic models to capture the interdependent behavior of transportation, economic, and environmental systems. The research is motivated by the well-known predator–prey models developed by renowned researchers Lotka and Volterra. Non-linear modeling techniques were utilized to capture the nominal behavior of all the three systems. The results indicated periodic behavior with a phase lag for the performance of transportation and the activity system; the performance of environment system decayed with time. The proposed modeling approach is expected to be helpful to other researchers in enhancing non-linear models for better analysis of sustainable systems.

Transportation and Regional Economic Development: Analysis of Spatial Spillovers in China Provincial Regions

Abstract: The role of spillover effect of transportation endowment on regional economic development is analyzed in this paper. We adopt the reduced form from the Solow growth model to estimate spillover effect from transportation. The panel database in use incorporates provincial gross regional product (GRP), labor and capital supply, and transportation investment information from 1985 to 2012 in China. The results confirm positive and significant spillover effect in Chinese provinces. In this paper, non-homogeneous spillover effects are captured in the empirical regression by the use of spatial weighing methods based on provincial economics and similarity as well as geographic connection. Highly positive spillovers are observed between economically similar provinces. However, for those under-developed provinces, high network connectivity often results in low or negative spillovers. The mobility and migration of production factors are believed to be the sources of the negative spillovers, while the industrial reallocation and market expansion contribute to the positive spillovers.

Integrated Co-evolution Model of Land Use and Traffic Network Design

Abstract: An integrated co-evolution model with the consideration of land use and traffic network design is proposed in this paper. In the suggested model, two kinds of economic agents are considered. On the one hand, the government makes the investment decision for the traffic network improvement based on the current traffic condition under the limited budget. On the other hand, households and companies will choose their locations according to the attraction of each traffic zone related to the road network accessibility and the housing price. Therefore, the land use is indicated by the population and employment distributions through the evolution process. Besides, the improvement of road capacity is modeled by a general bi-level programming of traffic network design. Simulation experiments show that the city will be more efficient and will have higher average accessibility for employment and population in the evolution process.

Incorporating Ridesharing in the Static Traffic Assignment Model

Abstract: This paper develops a combined mode choice and traffic assignment model that incorporates ridesharing as an option in a mode choice model, attempting to quantify the ridesharing market share in an equilibrium context. The mode choice model takes into account that the waiting time for a ride is dependent on the available drivers. The traffic assignment model is a static user equilibrium that interacts with the discrete choice model through level of service variables. An iterative algorithm was implemented and applied in a simple network and a more realistic network. The results indicate that the quantity of ride sharing drivers is a key parameter to the service success, and below a critical mass of drivers, it is unlikely that passengers will find the service valuable. It is also shown that ride sharing has the ability to reduce in-vehicle times for all the users, although passenger may suffer from longer door-to-door times, having to wait for their ride.

The multiregional core-periphery model: the role of the spatial topology

Abstract: We use the multiregional core-periphery model of the new economic geography to analyze and compare the agglomeration and dispersion forces shaping the location of economic activity for a continuum of network topologies — spatial or geographic configuration — characterized by their degree of centrality, and comprised between two extremes represented by the homogenous (ring) and the heterogeneous (star) configurations. Resorting to graph theory, we systematically extend the analytical tools and graphical representations of the core-periphery model for alternative spatial configuration, and study the sustain and break points. We study new phenomena such as the infeasibility of the dispersed equilibrium in the heterogeneous space, resulting in the introduction of the concept pseudo flat-earth as a long-run equilibrium corresponding to an uneven distribution of economic activity between regions.

Sustainability SI: Bundling of Outbound Freight Flows: Analyzing the Potential of Internal Horizontal Collaboration to Improve Sustainability

Abstract: van Lier, T (reprint author), Vrije Univ Brussel, MOBI, Pl Laan 2, B-1050 Brussels, Belgium. tom.van.lier@vub.ac.be; an.caris@uhasselt.be

Optimal 4-D Aircraft Trajectories in a Contrail-sensitive Environment

Abstract: Aircraft induced contrails present an important source and a growing concern for climate change in aviation. This paper develops a methodology to determine optimal flight trajectories that minimize the total flying cost in a dynamic, contrail-sensitive environment. The total flying costs consist of costs due to fuel burn, crew, passenger travel time, CO2 emission, and contrail formation. By constructing a multi-layer hexagonal grid structure to represent the airspace, we formulate the single aircraft trajectory optimization problem as a binary integer program that allows for flight altitude and heading adjustment, and contrail information update. Various cost factors are quantified, in particular the one corresponding to aviation-generated contrails, using the Global Warming Potential concept. Computational analyses show that optimal trajectories depend critically upon the time horizon choice for calculating the CO2 climate impact. Shifting flights to periods with low contrail effect is not justified, given the limited benefit but potentially large passenger schedule delay cost increase. The analyses are further extended to determining the optimal trajectories for multiple flights using a successive optimization procedure.

Shadow Prices in Territory Division

Abstract: We consider a geographic optimization problem in which we are given a region R, a probability density function f(⋅) defined on R, and a collection of n utility density functions u i (⋅) defined on R. Our objective is to divide R into n sub-regions R i so as to “balance” the overall utilities on the regions, which are given by the integrals $\iint _{R_{i}}f(x)u_{i}(x)\, dA$ . Using a simple complementary slackness argument, we show that (depending on what we mean precisely by “balancing” the utility functions) the boundary curves between optimal sub-regions are level curves of either the difference function u i (x) − u j (x) or the ratio u i (x)/u j (x). This allows us to solve the problem of optimally partitioning the region efficiently by reducing it to a low-dimensional convex optimization problem. This result generalizes, and gives very short and constructive proofs of, several existing results in the literature on equitable partitioning for particular forms of f(⋅) and u i (⋅). We next give two economic applications of our results in which we show how to compute a market-clearing price vector in an aggregate demand system or a variation of the classical Fisher exchange market. Finally, we consider a dynamic problem in which the density function f(⋅) varies over time (simulating population migration or transport of a resource, for example) and derive a set of partial differential equations that describe the evolution of the optimal sub-regions over time. Numerical simulations for both static and dynamic problems confirm that such partitioning problems become tractable when using our methods.

Efficient Data Reporting in Intelligent Transportation Systems

Abstract: Recently, intelligent transportation systems (ITSs) have emerged. These systems can improve traditional transportation systems and provide traffic information to travelers. In the area of transportation, wireless sensor networks (WSNs) can replace the existing wired sensors and expensive traffic monitoring systems to mitigate the time and costs of installing such systems. However, accurate and on-time traffic information delivery is a major challenge, considering the energy constraints of sensor nodes. In this paper, we propose a two-tier architecture that includes a network of mobile objects (vehicles) in the upper layer and a hierarchical WSN in the bottom layer. Using this approach, a portion of loads on the low-power static sensor nodes can be transferred to mobile objects, such as powerful mobile devices. Moreover, to provide accurate and timely traffic information, a QoS-aware link cost function has been proposed and used for data transmission between the static sensor nodes. In addition, due to the mobility of the objects and the probability of losing packets in the mobile object tier, a reliable data forwarding mechanism has been proposed for this tier. In this mechanism, data packets are forwarded to the neighbors, which enhance the probability of the packets’ being received. The performance evaluation results indicate the effectiveness of the proposed architecture and data reporting mechanism for use in ITS applications.

Reduced Carbon and Energy Footprint in Highway Operations: The Highway Energy Assessment (HERA) Methodology

Abstract: Global demand for mobility is increasing and the environmental impact of transport has become an important issue in transportation network planning and decision-making, as well as in the operational management phase. Suitable methods are required to assess emissions and fuel consumption reduction strategies that seek to improve energy efficiency and furthering decarbonization. This study describes the development and application of an improved modeling framework – the HERA (Highway EneRgy Assessment) methodology – that enables to assess the energy and carbon footprint of different highways and traffic flow scenarios and their comparison. HERA incorporates an average speed consumption model adjusted with a correction factor which takes into account the road gradient. It provides a more comprehensive method for estimating the footprint of particular highway segments under specific traffic conditions. It includes the application of the methodology to the Spanish highway network to validate it. Finally, a case study shows the benefits from using this methodology and how to integrate the objective of carbon footprint reductions into highway design, operation and scenario comparison.

Competitive Location and Pricing on Networks with Random Utilities

Abstract: In this paper we analyze the effect of including price competition into a classical (market entrant’s) competitive location problem. The multinomial logit approach is applied to model the decision process of utility maximizing customers. We provide complexity results and show that, given the locations of all facilities, a fixed-point iteration approach that has previously been introduced in the literature can be adapted to reliably and quickly determine local price equilibria. We present examples of problem instances that demonstrate the potential non-existence of price equilibria and the case of multiple local equilibria in prices. Furthermore, we show that different price sensitivity levels of customers may actually affect optimal locations of facilities, and we provide first insights into the performance of heuristic algorithms for the location problem.

Population-driven Urban Road Evolution Dynamic Model

Abstract: In this paper, we propose a road evolution model by considering the interaction between population distribution and urban road network. In the model, new roads need to be constructed when new zones are built, and existing zones with higher population density have higher probability to connect with new roads. The relative neighborhood graph and a Fermat-Weber location problem are introduced as the connection mechanism to capture the characteristics of road evolution. The simulation experiment is conducted to demonstrate the effects of population on road evolution. Moreover, the topological attributes for the urban road network are evaluated using degree distribution, betweenness centrality, coverage, circuitness and treeness in the experiment. Simulation results show that the distribution of population in the city has a significant influence on the shape of road network, leading to a growing heterogeneous topology.

Sustainability SI: Bikeway Network Design Model for Recreational Bicycling in Scenic Areas

Abstract: A bikeway network design model was developed for recreational bicycling in scenic areas. The multi-objective 0–1 programming problem is to determine spatial layouts for networks of bikeways and service stations. The model objectives are maximizing bikeway service coverage, maximizing service station service coverage, minimizing cyclist risk and maximizing bikeway suitability. The model constraints are network connectivity, bikeway type, monetary budget, location relationships between bikeways and service stations, and value ranges of decision variables. The programming problem was solved by e-constraint method in a case study of a bikeway network in North Coast & Guanyinshan National Scenic Area in northern Taiwan. Four of the six non-dominated alternatives generated in the case study were substantially superior to existing bikeways, and budget limits sensitively affected cyclist risk and bikeway suitability. The proposed network design model for recreational bikeways can assist planners in efficiently and systematically developing alternatives for further evaluation.

Reference Policies for Non-myopic Sequential Network Design and Timing Problems

Abstract: Despite a growing number of studies in stochastic dynamic network optimization, the field remains less well defined and unified than other areas of network optimization. Due to the need for approximation methods like approximate dynamic programming, one of the most significant problems yet to be solved is the lack of adequate benchmarks. The values of the perfect information policy and static policy are not sensitive to information propagation while the myopic policy does not distinguish network effects in the value of flexibility. We propose a scalable reference policy value defined from theoretically consistent real option values based on sampled sequences, and estimate it using extreme value distributions. The reference policy is evaluated on an existing network instance with known sequences (Sioux Falls network from Chow and Regan 2011a): the Weibull distribution demonstrates good fit and sampling consistency with more than 200 samples. The reference policy is further applied in computational experiments with two other types of adaptive network design: a facility location and timing problem on the Simchi-Levi and Berman (1988) network, and Hyytia et al.’s (2012) dynamic dial-a-ride problem. The former experiment represents an application of a new problem class and use of the reference policy as an upper bound for evaluating sampled policies, which can reach 3 % gap with 350 samples. The latter experiment demonstrates that sensitivity to parameters may be greater than expected, particularly when benchmarked against the proposed reference policy.

Finding Efficient and Environmentally Friendly Paths for Risk-Averse Freight Carriers

Abstract: This paper aims to incorporate two important measures into a freight shortest path problem, namely reliability and sustainability. Reliability measure deals with the uncertainty of link travel time while sustainability measure tends to reduce the fuel consumption and emission along the path. Greenhouse gas (GHG) emission rates are generated from Motor Vehicle Emission Simulator (MOVES) model and approximated as a function of the average link travel speed. To model uncertainty, the link travel speed is treated as a discrete random variable with a given distribution. Freight carriers are assumed to be risk-averse; for example, given two paths with the same average cost, carriers prefer the one with less variability. The risk-averse behavior is captured by the second order stochastic dominance (SSD) relationship. Specifically, SSD constraints are introduced in our model to narrow down the feasible paths which dominate a chosen benchmark path. The reliable and sustainable routing model is formulated as an integer program that can be easily tailored to a variety of modeling preferences. The study experiments with eight variants of the base model, each corresponding to a different trade-off strategy between three objectives, namely, efficiency, reliability and sustainability. The numerical experiments illustrate the benefits of the models discussed in the paper.

A Train Dispatching Model Under a Stochastic Environment: Stable Train Routing Constraints and Reformulation

Abstract: After major capacity breakdown(s) on a railway network, train dispatchers need to generate appropriate dispatching plans to recover the impacted train schedule from perturbations and minimize the expected total train delay time under stochastic scenarios. In this paper, we propose a cumulative flow variables-based integer programming model for dispatching trains under a stochastic environment on a general railway network. Stable Train Routing (STR) constraints are introduced to ensure that trains traverse on the same route across different capacity breakdown scenarios, which are further reformulated to equivalent linear inequality constraints. Track occupancy and safety headways are modelled as side constraints which are dualized through a proposed Lagrangian relaxation solution framework. The original complex train dispatching problem is then decomposed to a set of single-train and single-scenario optimization subproblems. For each subproblem, a standard label correcting algorithm is embedded for finding the time dependent least cost path on a space-time network. The resulting dual solutions can be transformed to feasible solutions through priority rules. Numerical experiments are conducted to demonstrate the efficiency and effectiveness of the proposed solution approach.

Impact of Logistics on Technical Efficiency of World Production (2007–2012)

Abstract: This research uses a production function of the type proposed by Mankiw et al. (1992) to study the effect of logistics and information and communication technologies (ITC) on domestic technical efficiency using stochastic frontier analysis for thirty-four countries over the period 2007–2012. We find that logistics and ICT are important channels for improving efficiency. This paper contributes to the literature by estimating the contribution of logistics and ICT to domestic technical efficiency. The economic impact of logistics measured using the LPI (Logistics Performance Index) on technical efficiency is estimated at 0.59 % for every 1 % increase in LPI, ceteris paribus.

Dynamics in the European Air Transport Network, 2003–9: An Explanatory Framework Drawing on Stochastic Actor-Based Modeling

Abstract: In this paper, we outline and test an explanatory framework drawing on stochastic actor-based modeling to understand changes in the outline of European air transport networks between 2003 and 2009. Stochastic actor-based models show their capabilities to estimate and test the effect of exogenous and endogenous drivers on network changes in this application to the air transport network. Our results reveal that endogenous structural effects, such as transitivity triads, indirect relations and betweenness effects impact the development of the European air transport network in the period under investigation. In addition, exogenous nodal and dyadic covariates also play a role, with above all the enlargement of the European Common Aviation Area having benefitted its new members to open more air routes between them. The emergence of major low-cost airline-focused airports also significantly contributed to these changes. We conclude by outlining some avenues for further research.

Exploring Vulnerability and Interdependency of UK Infrastructure Using Key-Linkages Analysis

Abstract: It has been argued the UK has experienced significant underinvestment in critical infrastructure over the last two decades. This in turn has resulted in infrastructure that is less capable of assisting the UK economy to grow. This article seeks to undertake an in-depth analysis of the inter-linkages and economic contributions from infrastructure within the UK. It explores the relationship between nine infrastructure sectors and how these sectors contribute to the rest of the UK economy using key-linkage analysis. Each infrastructure sector is shown to be unique in the way it interacts with other economic sectors and in the form of contribution it makes to the economy overall. Infrastructure is found to be a necessary and important part of economic development. The analysis finds that over the last 23 years there has been a decline in the relative economic contribution from infrastructure to UK GVA. Only two infrastructure sectors increased their relative contribution to GVA since 1992. These were the water transport sector and sewerage and sanitary services sector. Railway transport and gas distribution have had the largest relative decline in contribution towards UK GVA with relative contributions decreasing by over 50 % since 1992. The three most important infrastructure sectors contributing to UK GDP are land transport, electricity production and distribution and telecommunications respectively.

Spatial Analysis of Single Allocation Hub Location Problems

Abstract: Hubs are special facilities that serve as switching, transshipment and sorting nodes in many-to-many distribution systems. Flow is consolidated at hubs to exploit economies of scale and to reduce transportation costs between hubs. In this article, we first identify general features of optimal hub locations for single allocation hub location problems based on only the fundamental problem data (demand for travel and spatial locations). We then exploit this knowledge to develop a straightforward heuristic methodology based on spatial proximity of nodes, dispersion and measures of node importance to delineate subsets of nodes likely to contain optimal hubs. We then develop constraints for these subsets for use in mathematical programming formulations to solve hub location problems. Our methodology can also help narrow an organization’s focus to concentrate on more detailed and qualitative analyses of promising potential hub locations. Results document the value of including both demand magnitude and centrality in measuring node importance and the relevant tradeoffs in solution quality and time.