Redistributive effects of bus rapid transit (BRT) on development patterns and property values in Seoul, Korea

This study investigates the redistributive effects of Seoul's bus rapid transit (BRT) system on development patterns and property values using an urban simulation model. The Seoul Metropolitan Integrated Urban Model (SMIUM) combines the Seoul metropolitan input-output model with random utility-based location choice models and endogenous real estate markets.The major findings of this study can be highlighted as follows. First, Seoul's BRT contributes to increased development density in urban centers, acting as a centripetal force to attract firms from the suburbs into urban cores and supporting arguments for Smart Growth proponents. Second, unlike its redistributive effects on nonresidential activities, the BRT has a limited effect on the redistribution of residential activities, implying that residential locations are less sensitive to accessibility improvements made by the BRT than are nonresidential locations. Third, reflecting the transferred space demands from the suburbs to the urban cores, the CBD reaps the highest property value gains, while all of the outer ring zones suffer from reduced property values.     

A maritime container repositioning yield-based optimization model with uncertain upsurge demand

The role of container repositioning has become more important under the severe cargo shipping environment, affected by world trade growth, trade imbalance, slow steaming strategy and high container manufacturing cost. Low cost, better routing, and supplying equipment to higher yield cargo become the top criteria. A yield-based container repositioning framework is developed, followed by a constrained linear programming optimizing the container repositioning from surplus to deficit locations. The model incorporated change of destinations of empty containers and adjustment factors handling upsurge demand. The model is applied to optimize daily container repositioning operations with a better route, costs and equipment supply.     

The sky is the limit: Assessing aircraft market diffusion with agent-based modeling

This paper presents an agent-based model for the diffusion of new aircraft models. Expanding on the classical economic decision framework, where investment decision-making is entirely based on profitability, our more holistic modeling approach takes into account profitability, flexibility, as well as the environmental impact of new aircraft models in the adoption decision process. Technical parameters, such as the range and passenger number per aircraft model considered, various types of pollutant emissions of the aircraft engine, as well as daily operational data, are used as covariates in the model. In validation for the most common mid-range passenger aircraft models of Airbus and Boeing, our agent-based model produces results that are comparable to observed real-world data on the market diffusion of existing mainstream aircraft models. This result shows the applicability and usefulness of our model, which can subsequently also be applied for studying the diffusion of aircraft models embodying new generations of components. Our simulation shows that a price reduction or a decrease in pollutant emissions of new aircraft models can be expected to lead to more adoption and faster diffusion. Furthermore, our modeling approach demonstrates that a holistic and systematic framework that includes not only profitability (in terms of payback time) but also flexibility (in terms of optimal range and amount of passengers) and environmental impact (in terms of deviation from regulatory standards) can be helpful for modeling the investment decision-making process of airlines.     

A strategic network choice model for global container flows: specification, estimation and application

Container flows have been booming for decades. Expectations for the 21st century are less certain due to changes in climate and energy policy, increasing congestion and increased mobility of production factors. This paper presents a strategic model for the movement of containers on a global scale in order to analyse possible shifts in future container transport demand and the impacts of transport policies thereon. The model predicts yearly container flows over the world’s shipping routes and passing through 437 container ports around the world, based on trade information to and from all countries, taking into account more than 800 maritime container liner services. The model includes import, export and transhipment flows of containers at ports, as well as hinterland flows. The model was calibrated against observed data and is able to reproduce port throughput statistics rather accurately. The paper also introduces a scenario analysis to understand the impact of future, uncertain developments in container flows on port throughput. The scenarios include the effects of slow steaming, an increase in land based shipping costs and an increased use of large scale infrastructures such as the Trans-Siberian rail line and the opening of Arctic shipping routes. These scenarios provide an indication of the uncertainty on the expected port throughputs, with a particular focus on the port of Rotterdam in the Netherlands.     

A behavioral model of accessibility based on the number of available opportunities

The paper proposes a new behavioral definition of accessibility as the expected number of opportunities “available” for a subject to perform an activity, where “available” means that the opportunity i) is perceived as a potential alternative to satisfy one's needs, and ii) it can be reached given the spatiotemporal constraints of the individual's schedule. A new class of accessibility models is derived in accordance with the above definition, exploiting the strengths of both utility-based and opportunity-based models, and explicitly incorporating spatiotemporal constraints which may limit the availability of perceived opportunities. The proposed model is formulated for both active and passive accessibility, does not suffer from reflexivity issues, supports both trip-based and activity-based formulations, and scales up from individual to spatially aggregated opportunities, taking into account effectively the different ways of perceiving opportunities. Moreover, the resulting accessibility measure has a straightforward interpretation, being expressed in physical units, and is comparable across different locations. Performances of the proposed model in reproducing the active accessibility to cinemas in the Naples metropolitan area (Italy) are compared to those of a traditional isochrone-based measure and a distance–decay model. For this aim, measurements of individuals' perceived cinemas were gathered through a survey, and adopted for the calibration of both the accessibility models. Calibration results show that the proposed model outperforms both the traditional isochrone-based measure and a distance–decay model calibrated against the same dataset, better reproducing both the quantity and spatial distribution of perceived opportunities.     

Experience conditioning in commuter modal choice modelling – Does it make a difference?

This paper investigates the impact of decision maker’s experience on model elasticities and predicted market share, using data collected in Sydney on commuter mode choice. Usage frequency is used as a proxy for experience and two separate mode choice models are estimated – one with experience conditioning choice and one without. Key model outputs are compared and we find that differences in the value of travel time savings and model elasticities are very marked. This suggests that ignoring experience that one has with each alternative in their choice set may be a candidate source of error in travel demand forecasts. We develop a method to obtain the level of experience for use in application of choice models to increase their prediction power.     

Robust schedule design for liner shipping services

This paper examines the design of liner ship route schedules that can hedge against the uncertainties in port operations, which include the uncertain wait time due to port congestion and uncertain container handling time. The designed schedule is robust in that uncertainties in port operations and schedule recovery by fast steaming are captured endogenously. This problem is formulated as a mixed-integer nonlinear stochastic programming model. A solution algorithm which incorporates a sample average approximation method, linearization techniques, and a decomposition scheme, is proposed. Extensive numerical experiments demonstrate that the algorithm obtains near-optimal solutions with the stochastic optimality gap less 1.5% within reasonable time.     

Robust schedule design for liner shipping services

This paper examines the design of liner ship route schedules that can hedge against the uncertainties in port operations, which include the uncertain wait time due to port congestion and uncertain container handling time. The designed schedule is robust in that uncertainties in port operations and schedule recovery by fast steaming are captured endogenously. This problem is formulated as a mixed-integer nonlinear stochastic programming model. A solution algorithm which incorporates a sample average approximation method, linearization techniques, and a decomposition scheme, is proposed. Extensive numerical experiments demonstrate that the algorithm obtains near-optimal solutions with the stochastic optimality gap less 1.5% within reasonable time.     

Multi-objective optimization for planning liner shipping service with uncertain port times

This paper considers a joint tactical planning problem for the number of ships, the planned maximum sailing speed, and the liner service schedule in order to simultaneously optimize the expected cost, the service reliability and the shipping emission in the presence of port time uncertainty. The problem is formulated into a stochastic multi-objective optimization problem at the operational level. The relationships between the objectives and the decision variables are established. A simulation-based non-dominated sorting genetic algorithm is then presented to solve this problem. A case study is provided to illustrate the results and the application of the model.     

Optimal vendor selection in a multiproduct supply chain with truckload discounts

When products are sold by multiple vendors in various locations, the purchaser must decide what to order from each vendor and where to send it. To solve this decision problem, a novel optimization model is developed and applied to a situation involving the nationwide wholesale distribution of grocery products. Comparing the model’s solution with the actual record of shipments reveals instances in which the model selected higher-priced vendors in order to capitalize on truckload cost savings, which are seen to be an important factor in vendor selection. Additional models are developed to reduce computation time and assign shipments to vehicles.     

A random utility maximization (RUM) based measure of accessibility to transit: Accurate capturing of the first-mile issue in urban transit

The paper presents a random utility-based measure of accessibility to explain the first-mile issue in urban transit. A discrete access stop/station location choice model is used to calculate the expected maximum utility of transit access choices as the measure of the proposed access to transit measurement approach. It captures the effects of changes in various personal, sociodemographic, transportation and land-use variables on access to urban transit that are overlooked by conventional approaches of accessibility measurements (count-based cumulative opportunities measures and gravity-based measures). The proposed accessibility to transit measurement approach is empirically measured for the Greater Toronto Area and is integrated into an operational tool programmed in a GIS-based traffic assignment software, TransCAD 7.0. This allows comparing it to the conventional measures, and the results reveal that the conventional measures tend to over-estimate access to transit.     

Transportation mode selection with positive manufacturing lead time

In this paper we present a dual supply model taking into account that in many industries the replenishment cycle does not only involve the physical distribution of goods, but also the manufacturing of products. Further, we suggest postponing the transportation mode decision until the products are available for shipping. We investigate a class of order-up-to policies and show how to compute the optimal policy parameters. Our model enables us to quantify the value of the postponement of the transportation decision and the value of using an additional slow mode instead of only using the existing fast mode. In a numerical study the influence of various model parameters is investigated and it is shown that the use of a slow mode can be economically beneficial, especially for low value items.     

Dynamic DEA models with network structure: An application for Iranian airlines

Efficiency estimation of interdependent divisions within a company or assessing the interrelated processes in a production system provides insights for improving the operational performance. Recent developments in network data envelopment analysis (NDEA) models enable decision making units (DMUs) to be informed of inefficient processes within the system. The NDEA model assesses the processes of the system in a specific moment and ignores the dynamic effects within the production processes. Thus, without considering the temporal dimension of production processes, biased efficiency measurement will be obtained that provides misleading information to DMUs. For evaluating the performance of a DMU with interrelated processes during specified multiple periods, this paper proposes a relational dynamic NDEA (DNDEA) model which measures the efficiencies of the system and its internal processes over the time, simultaneously. To illustrate the capability of the proposed model, this study for the first time measures the efficiency of eight Iranian airlines in several periods connected to each other by carry over flows. The actual data is gathered in three periods from 2010 to 2012 and the results are compared with the dynamic DEA and network DEA models in the same time span.     

Space-time dynamics: A modeling approach for commuting departure time on linked datasets

Commuters' departure time related decisions are important in time geography. Analytic tools have been proposed to capture the inherent choice determinants both in time and space. Although the dynamic aspects of the problem have been identified, most of the existing studies are based on static models. In this paper, a dynamic modeling framework is proposed to explore the relationship between commuters' departure time choices and the evolution of en route traffic. A data linkage method is developed to create an integrated dataset that enables the observation of commuters' reaction to changes in travel time and traffic conditions over time. A regional household travel survey is linked to travel information obtained from the Google Maps application program interface (API), creating a synthetic longitudinal dataset. Two decision rules are applied to model commuters' response to the evolution of traffic. The results indicate that travel time, distance to work location, flexibility in working schedule, expected arrival time, and commuters' sociodemographic influence departure time choices. It is also found that accounting for dynamics improves model fit and out-of-sample predictions. Both the dynamic model and the proposed data linkage method contribute to the understanding of human activities in space and time and can be used to enhance transportation demand analysis and urban policy studies.     

Global supply chain design: A literature review and critique

In this paper, we review decision support models for the design of global supply chains, and assess the fit between the research literature in this area and the practical issues of global supply chain design. The classification scheme for this review is based on ongoing and emerging issues in global supply chain management and includes review dimensions for (1) decisions addressed in the model, (2) performance metrics, (3) the degree to which the model supports integrated decision processes, and (4) globalization considerations. We conclude that although most models resolve a difficult feature associated with globalization, few models address the practical global supply chain design problem in its entirety. We close the paper with recommendations for future research in global supply chain modeling that is both forward-looking and practically oriented.     

Accessibility evaluation of land-use and transport strategies: review and research directions

A review of accessibility measures is presented for assessing the usability of these measures in evaluations of land-use and transport strategies and developments. Accessibility measures are reviewed using a broad range of relevant criteria, including theoretical basis, interpretability and communicability, and data requirements of the measures. Accessibility impacts of land-use and transport strategies are often evaluated using accessibility measures, which researchers and policy makers can easily operationalise and interpret, such as travelling speed, but which generally do not satisfy theoretical criteria. More complex and disaggregated accessibility measures, however, increase complexity and the effort for calculations and the difficulty of interpretation. The current practice can be much improved by operationalising more advanced location-based and utility-based accessibility measures that are still relatively easy to interpret for researchers and policy makers, and can be computed with state-of-the-practice data and/or land-use and transport models. Research directions towards theoretically more advanced accessibility measures point towards the inclusion of individual's spatial–temporal constraints and feedback mechanisms between accessibility, land-use and travel behaviour. Furthermore, there is a need for theoretical and empirical research on relationships between accessibility, option values and non-user benefits, and the measurement of different components of accessibility.     

Replenishment and lead time decisions in manufacturer–retailer chains

This study investigates the decisions of replenishment and lead-time reduction for a single-manufacturer multiple-retailer integrated inventory system in which the probability distribution of demand for each retailer is unknown but its mean and variance are given. A decision model is presented and a minimax distribution free procedure is applied to determine the lead time, the common shipment cycle time, the target levels of replenishments and the number of shipments per production cycle so that the expected total system cost can be minimized. A decision support system has been implemented on a personal computer to illustrate the application of the model.     

What comes next after recession? – Airline industry scenarios and potential end games

While airline managers learned lessons from the 2001/2003 “double dip” economic crisis, the post 2008 downturn has been more extreme. Airlines reacted quickly in 2008 and adjusted capacities and cost levels but recovery in profits has been slow for many airlines. The dynamics of the downturn has enlarged the gap between successful and less successful business models, and fostered shakeouts of the latter. Furthermore, the occurrence of new business models has accelerated. In 2001, it was the European continental low cost model; this time, we may see new attempts to change the rules of the game in international long-haul traffic. Long-term non-cyclical trends such as deregulation or consolidation will also shape potential end game scenarios, We briefly examine the differences between the last (2001/03) and the recent (2008/09) aviation crises, and evaluate the impact on different types of carriers.     

School travel mode choice in Beijing,China

This study explores school travel mode choice behavior of 7–18 year-old students in Beijing, China, based on the data collected in Fifth Travel Survey of Beijing Inhabitants. The integration of tree-based and logit-based models is employed to examine the influence of key variables on school travel mode choice. In particular, the tree-based model is used to preliminarily select the traits which have a statistical effect on mode choice, and the logit-based model is used to provide deeper understanding of the underlying decision processes and the correlation effects of the variables. Results show that car ownership, poor walking/cycling environment, and adults' convenience for escorting students significantly stimulate the use of cars in school commuting. Students are more inclined to choose cars when their departure time is at rush hour compared to the other time. Moreover, the longer distance encourages the use of motorized transport, where the households with local hukou (usually related to the car ownership and other welfares) are more willing to drive their children to school. A number of recommendations on car restraint, sustainable travel environment improvement, different working hour implementing, and educational resources layout for the encouragement and promotion of sustainable travel practices are lastly proposed.     

Berth allocation considering fuel consumption and vessel emissions

We propose a more elaborate model on berth allocation considering fuel consumption than before, and overcome the nonlinear complexity by casting it as a mixed integer second order cone programming model. Furthermore, we conduct the vessel emission (in sailing periods) calculation with the widely-used emission factors. Besides, vessel emissions in mooring periods are also analyzed through a post-optimization phase on waiting time. Experimental results demonstrate that the new berth allocation strategy, reflected by the proposed model, is competent to significantly reduce fuel consumption and vessel emissions, while simultaneously retaining the service level of the terminal.