The location of logistics hubs is one of the most crucial success factors for potential economic

growth in logistics sector. Since the logistics hub has direct and indirect impacts on different

stakeholders including investors, policy makers, infrastructure providers, hub operators, hub

users and the community itself, it needs to be considered carefully. Therefore, logistics hubs

should be located in such a way that it can provide a better accessibility to three different modes

of transportation- road, rail and waterways. The aim of this study is to evaluate the potential

locations for logistics hubs and to find out the criteria that affect for the selection of location for

logistics hubs. A comprehensive literature study reveals the factors that are affecting the

selection of location for logistics hubs and the methods to evaluate those locations considering

the criteria. Location selection or evaluation is a typical multi-criteria decision making (MCDM)

problem in which performance criteria plays a vital role for the final decision making. Both

qualitative and quantitative MCDM methods are applied in this study, where the Analytic

Hierarchy Process (AHP) is qualitative and the gravity method is quantitative method. Analytic

Hierarchy Process (AHP) is a structured approach to reach the final decision which is one of the

best methods of all MCDM problems, used in recent literature to evaluate the location selection

problems. A case study is done for the logistics company, Brinova Fastigheter AB in Sweden.

This study is followed by AHP method which is considered with selected factors, i.e. highway

accessibility, intermodal capacity, port capacity and land availability. Moreover, this study is

conducted by evaluating the four major potential locations in Sweden i.e. Stockholm, Göteborg,

Helsingborg and Karlshamn for selecting as a logistics hub. Besides, the location for selecting

logistics hubs is evaluated by the gravity method, which is a quantitative method to determine

the level of accessibility for the selected locations, considering the flow of goods both inbound

and outbound and the transport cost between the locations. The result from the AHP method

recommend that Göteborg is the best potential location to establish logistic hub whereas the

Gravity model represents that Stockholm has the highest level of accessibility for logistics

activity. Therefore the study suggested that both Göteborg and Stockholm are considered to be

the best potential locations considering in present situation

One of the targets of the European project "CityHush Acoustically Green Road Vehicles and City Areas" under the 7th Framework Program is to support city administrations to eliminate harmful effects of noise exposure and decrease levels of transport noise, especially in urban areas. A particular attention has been paid to investigating boundary conditions and maximum noise gains especially for parks embedded in Q-zones where only quiet low emission vehicles are tolerated. Other vehicles are banned or subject to a noise fee for entering the quiet zone. Within the CityHush project existing noise levels in different parks of European cities were determined and the influence of local parameters on the noise situation, such as size of a Qzone, was investigated. Moreover a variation of noise fees and traffic restrictions as well as different percentages of low noise vehicle ownerships inside the Q-zone and outside (countrywide) was evaluated. Based on different noise and annoyance criteria possibilities and limits to reduce noise in the city environment will be shown, based on studies carried out for 5 European cities.

Background: Inflammation may contribute to the high cardiovascular risk in diabetes mellitus (DM) and chronic kidney disease (CKD). Monocyte chemoattractant protein-1 (MCP-1) facilitates the recruitment of monocytes into atherosclerotic lesions and is involved in diabetic nephropathy. Interferon gamma (IFNγ) is important in atherosclerosis and increases the synthesis of chemokines including MCP-1. Lipid-lowering treatment (LLT) with statins may have anti-inflammatory effects, and ezetimibe cotreatment provides additional cholesterol lowering. Methods: After a placebo run-in period, the effects of simvastatin alone (S) or simvastatin + ezetimibe (S+E) were compared in a randomized, double-blind, cross-over study on inflammatory parameters. Eighteen DM patients with estimated glomerular filtration rate (eGFR) 15-59 mL/min × 1·73 m2 (CKD stages 3-4) (DM-CKD) and 21 DM patients with eGFR > 75 mL/min (DM only) were included. Results: At baseline, monocyte chemoattractant protein 1 (MCP-1) (P = 0·03), IFNγ (P = 0·02), tumour necrosis factor-α (TNFα) (P < 0·01) and soluble vascular adhesion molecule (sVCAM) (P = 0·001) levels were elevated in DM-CKD compared with DM-only patients. LLT with S and S+E reduced MCP-1 levels (P < 0·01 by anova) and IFNγ levels (P < 0·01) in DM-CKD patients but not in DM-only patients. Reductions were most pronounced with the combination treatment. Conclusions: DM patients with CKD stages 3-4 had increased inflammatory activity compared with DM patients with normal GFR. Lipid-lowering treatment decreased the levels of MCP-1 and IFNγ in DM patients with concomitant CKD, which may be beneficial with regard to the progression of both atherosclerosis and diabetic nephropathy.

The use of Cost-benefit analysis (CBA) as a tool for selecting transport investments is often questioned. It is not unusual that politicians or others in the public debate argue that the outcome of a CBA completely rely on assumptions concerning a particular input factor, such as valuation of CO2 emissions or future fuel price. This paper explores whether the relative ranking of CBA outcomes are robust with respect to some key inputs in transport demand analysis driving cost, public transport fare and economic growth. We study six different infrastructure objects (three road and three rail objects) and four alternative assumptions on input factors compared to a reference scenario.

The findings suggest that single input factors in a CBA, individually have a small impact on the ranking of the studied investments. In our model calculations we observe no change in rank between a road and a rail object.

This paper develops a new mode choice and transit route choice model for work trips by either car or transit. In contrast to the conventional regional traffic models used for transportation planning in Sweden, the model accounts for the fact that the value of time varies within a population of travellers making a trip with the same purpose and the fact that the price can differ between different transit lines (bus, regional trains, etc.). A mixed binomial logit (MXL) model with a lognormally distributed cost parameter has been estimated for the mode choice. The MXL specification makes it possible to capture some of the variation in the value of time. The transit route choice model rests on the assumption that transit commuters purchase travel passes that are valid for a certain time period, e.g. a month. The travel pass then allows the traveller to use a certain set of transit lines, while others are not available. For the mode choice, the traveller compares travel cost and time with the chosen pass with the travel cost and time by car. The results from performed analyses indicate that if the interest is in overall mode share and overall travel flows, the conventional method in Swedish transport modelling will suffice. However, if the interest is more detailed, for example concerning boardings and ticket income from a certain transit line, or the total benefit of a price change, the model developed in this paper will give more reliable results.

Economic activities can be modeled at different levels of aggregation. Different levels of detail regarding spatial or temporal resolution, or levels of sectoral aggregation are appropriate depending on the question at hand. In cases where changes on the micro scale affects what happens at the macro level, and vice versa, an integrated approach is required. In this paper a modeling framework is presented, where focus is placed on the interactions between production and employment. The aggregate spatial computable general equilibrium model STRAGO is interacted with the highly detailed input-output model system rAps. Interregional and intersectoral relations of production, including agglomeration, are represented in the aggregate model, providing a coarse description of production by which the rAps model system is constrained. Such constraints will affect where individuals may find a suitable job. At the same time the aggregate model is dependent on the labour supply, provided by rAps, in determining production. An application of the proposed modeling framework is presented where future projections are compared to historical data.

Since 2008 most older people in England have benefited from unlimited area-wide free travel by bus after the morning peak period. The official policy rhetoric supporting implementation of the measure drew significantly on the need to reduce social exclusion amongst older people. However, despite a substantial increase in the number of concessionary journeys in England and the associated cost liabilities for local authorities and possibly also operators, there is currently only limited understanding of the wide ranging effects on bus use of providing a free pass, and in particular to whom benefits from the policy accrue. In part, this circumstance results from a methodological focus by evaluation studies hitherto that has emphasised aggregate-level data, often at the expense of the very rich contextual information about how the individual benefits from using a pass. This article presents insights into the perceptions, motivations and decisions relating to use of free bus passes, highlighting the existence of both tangible and intangible benefits which arise. It offers a fresh insight into previously undefined uses and benefits derived from possessing and using a concessionary bus pass. This article concludes by noting possible policy implications of the research in the context of the UK's ageing population and for other international contexts where the transport intervention of free bus travel is being considered.

Since 2008, older people in England have been provided with nationwide zero-fare travel by bus as part of the Government’s wider social inclusion agenda. In common with other international zero-fare transportation measures, the scheme has stimulated a substantial increase in demand for bus travel, yet relatively little is known about how pass holders are using their passes. This is characterised by a lack of in-depth statistical analyses of pass holders’ usage trends. Through analysis of an on-board bus survey of 487 pass holders conducted in Southwest England, this paper explores the relationship between pass holders’ characteristics and their propensity to increase their travel by bus, and ultimately report an improvement in their quality of life as a result of the policy. The results confirm that the pass is mainly being used for shopping and social reasons, with evidence that the zero-fare pass has led to some modal substitution from the car, but also has facilitated trips that would not have taken place in the absence of the scheme. Multivariate analysis reveals that those pass holders who are older (75+), would have travelled as a car passenger, or used the bus anyway in the absence of a pass, are the ones least likely to report increased bus use since obtaining a pass. Interestingly, two of these variables (being older, and being a car passenger in the absence of a pass) simultaneously increase pass holders’ propensity to report an improvement in their quality of life, leading to the conclusion that zero-fare policy has the potential to improve quality of later life above and beyond changes in pass holder bus trip frequency. In other words, the traditionally assumed link between increase in bus trips and derived benefit is not supported in all cases by this research.

Uncertainties related to demand model system outputs is an important issue in travel demand models. This paper focuses on uncertainties arisen from the fact that models are estimated on a sample of the population (and not the whole population). Forecasting systems can be quite complex, and may contain procedures that not easily permit analytically derived statistical measures of uncertainty. In this paper, the possibilities to use computer-intensive numerical methods to compute statistical measures for very complex systems, without being bound to an analytical approach, are explored. Here, the bootstrap method is used to obtain statistical measures of outputs produced by the forecasting system SAMPERS. The SAMPERS system is used by Swedish transport authorities. The bootstrap method is briefly described as well as the procedure of applying bootstrap on the SAMPERS system. Numerical results are presented for selected forecast results at different levels such as total traffic demand, origin-destination demand, train line demand and the demand on specific links. Also, the uncertainty related to the value of time estimate is analysed. 

The increased focus in Sweden on greenhouse gas emissions, oil dependency and energy efficiency has lead to the implementation of different policy measures in the transport sector. In Sweden there has been a long tradition of buying large, powerful and heavy cars with high fuel consumption and CO<inf>2</inf> emissions. The Swedish car fleet is the heaviest car fleet in all Europe. We describe and discuss effects of major measures that have been implemented to accelerate the introduction of clean cars in the Swedish car fleet. We also briefly describe a decision support tool to evaluate policies affecting the composition of the car fleet. We find that the result of the implemented measures is a high share of clean cars in new car sales and that these policies have lead to a dominance of low emission diesel cars and E85 cars in this share. We also find that the share of biogas cars is still very small and that the use of E85 fuel for E85 cars is quite price sensitive.

In this study we have used a neural network model in order to investigate the impact of emotional processes on economic phenomena. We have built a replica of a model presented by Frank and Claus (2006, Anatomy of a Decision: Striato-Orbitofrontal Interactions in Reinforcement Learning, Decision Making, and Reversal, Psychological Review), although using other software. The model displays, similar to the one referred to above, the characteristics that constitute prospect theory. Additionally, we take a first step toward investigating what explanatory power this model might have in studying the influence of emotions on economic decision-making. We note that by externally altering the activity level in the amygdala, a brain region that has been proven essential for emotional reactions, the risk attitudes of the model can be manipulated. We find that a decrease in activity in the amygdala implies a lower degree of risk-averse, as well as a higher degree or risk-seeking, behavior. Finally, we conclude that response times are longer and choice uncertainty higher for tasks that involve only negative outcomes as compared to tasks that involve partially or exclusively positive outcomes, a result that can be linked to e.g. decision field theory.

Congestion charges were introduced in Stockholm in 2006, first as a trial followed by a referendum, then permanently from 2007. This paper discusses what conclusions can be drawn from the first five years of operation, until mid-2011. We show that the traffic reduction caused by the charges has increased slightly over time, once external factors are controlled for. Alternative fuel vehicles were exempt from the charges through 2008, and we show that this substantially increased the sales of such vehicles. We discuss public and political acceptability, synthesising recent research and Swedish experience. We conclude that objective and subjective effects on the traffic system, as well as general environmental and political attitudes, formed the basis of the strong public support, while institutional reforms and resolution of power issues were necessary to gain political support. Finally, we briefly discuss implications for the transport planning process in general.

The standard method of estimating the value of travel time variability for use in policy appraisal is to estimate the parameters of a reduced-form utility function, where some measure of travel time variability (such as the standard deviation) is included. A problem with this approach is that the obtained valuation will in general depend on the standardized travel time distribution, and hence cannot be transferred from one context to another. A recently suggested remedy for this problem has been to estimate a scheduling model, which in theory is transferrable, and use the implied reduced-form to derive valuations for use in appraisal. In this paper we estimate both a scheduling model and the implied reduced-form model, using stated choice data. The valuation of travel time variability implied by the scheduling model turns out to be substantially smaller than what is obtained from a reduced-form model estimated on the same sample. The results suggest that the scheduling model does not capture all of the disutility arising from travel time variability. Hence, although it can be shown that scheduling and reduced-form models are theoretically equivalent, that hypothesized equivalence is not reflected in the empirical evidence. We speculate that the derivation of reduced-form models from an underlying scheduling model omits two essential features: first, the notion of an exogenously fixed "preferred arrival time" neglects the fact that most activities can be rescheduled given full information about the travel times in advance, and second, disutility may be derived from uncertainty as such, in the form of anxiety, decisions costs or costs for having contingency plans. We also report our estimates of the valuation of travel time variability for public transit trips, for use in applied appraisal.

Transport infrastructure is long-term and in appraisal it is necessary to value travel timesavings for future years. This requires knowing how the value of time (VTT) will develop over time as incomes grow. This paper investigates if the cross-sectional incomeelasticity of the VTT is equal to inter-temporal income elasticity. The study is based ontwo identical stated choice experiments conducted with a 13. year interval. Results indicate that the relationship between income and the VTT in the cross-section has remained unchanged over time. As a consequence, the inter-temporal income elasticityof the VTT can be predicted based on cross-sectional income elasticity. However, theincome elasticity of the VTT is not a constant but increases with income. For this reason, the average income elasticity of the VTT in the cross-sections has increased between the two survey years and can be expected to increase further over time. 

Standard CBA is often criticised for not taking land use effects induced by transport investments and wider economic benefits into account. The purpose of this paper is to estimate the size of these effects using the Stockholm Metro built in the 1950’s, the largest urban rail investment in Sweden, as a case study. We find that benefits of the Metro increase 60 percent due to long term land use adjustments. Wider economic benefits increase the benefit by 17 percent.We show that the Stockholm Metro was socially beneficial to build according to present standard methods, even without taking land use effects and wider economic benefits into account. Hence, the anecdote that the Metro of Stockholm had not been built if CBA had been a part of the appraisal seems to be false.

Cost Benefit Analysis (CBA) has been a fundament of appraisal in Northern European Countries for decades and is becoming increasingly important in Sweden (Eliasson and Lundberg, 2011). Still, the CBA methodology is a relatively young tool and has been developed for evaluation of smaller infrastructure objects. Also proponents of the CBA method recognise some methodological problems (see for instance Mackie and Preston (1998)), in particular of large infrastructure investments. Uncertainty in CBA outcome was recently discussed by the OECD Forum for infrastructure issues, International Transport Forum. To undermine the trust in CBA as an accurate decision support, it is often stated in the Swedish debate that the Stockholm Metro, build in the 1950’s and now central for the functioning of the traffic system and commuting, would not have shown a positive CBA outcome if the present methods and tools had been available at the time. The purpose of this paper is to perform an ex-post cost benefit analysis of the Metro system, the largest urban rail investment in Sweden. The Stockholm Metro has a track length of 105 kilometres, of which 62 kilometres are in tunnels, with a total of 100 stations spread over three lines. The application of CBA to an investment of the size of the Stockholm Metro illustrates clearly that there are certain benefits that may not be sufficiently well captured in standard CBA: land-use benefits, labour market benefits and benefits arising from increased capacity in the road and public transit network. In this paper we try to assess the size of the external labour market effects and land-use effects in the Stockholm Metro case.

Transit systems exercise complex dynamics and evolve through the interaction of various agents. The analysis of transit performance requires emulating the dynamic loading of travellers and their interaction with the underlying transit system. Multi-agent simulations aim to mimic the emergence of global spontaneous order from numerous inter-dependent local decisions. This paper presents a framework for a multi-agent transit operations and assignment model which captures supply uncertainties and adaptive user decisions. An iterative day-to-day learning process consisting of a within-day dynamic network loading loop simulates the interaction between transit supply and demand. The model requires the development and integration of several modules including traffic simulation, transit operations and control, dynamic path choice model and real-time information generator. BusMezzo, a transit simulation model, is used as the platform for implementation.

The resilience of the transport system is acknowledged as an important policy objective. Resilience refers to the extent to which a system is affected by various disturbances, and its capability to recover from such disturbances and restore its level of performance. Public transport networks (PTN) are subject to recurring service disruptions. However, most studies on transport network resilience have focused on the physical degradation of the road network. Hence, their findings have limited transferability to the PTN context. Previous studies on PTN resilience have considered vulnerability in terms of connectivity reliability. Graph theory principles were used to analyze the impact of network structure on robustness with respect to random and intentional attacks. Such analysis allows the comparison of alternative network design properties. However, it does not capture many of the PTN features that we believe are essential for analyzing its resilience.The underlying principles of PTN design and operations make it fundamentally different from road networks and potentially more vulnerable. PTN are usually less dense than the underlying road network, resulting in fewer alternative paths. Moreover, PTN operate close to capacity due to the increasing marginal operation cost during the peak period. In addition, PTN exercise discontinuity in time and space, inducing varying and stochastic waiting, walking and transfer times. Stochastictravel times arise from the inherent and interdependent underlying sources of uncertainty. Another matter thatneeds to be taken into account is that PTN are often multimodal, consisting of several independent infrastructures. As a result of these characteristics, service disruptions in the PTN have wider direct implications compared to the road network due to theescalating impacts on service availability and capacity further downstream. We develop an analysis framework for PTN resilience. The framework integrates stochastic supply and demand models, dynamic route choice and limited operational capacity. Moreover,the plausible correlation between degraded capacities among network elements is captured through the dynamic modellingof network performance. The criticality of a link is evaluated as the increase in system travel time due to a capacity reduction of the link. In general, criticality depends on the flow on the link and the availability of alternative paths in the PTN. We analyze the influence of the capacity of alternative paths on the criticality of a link. High volume to capacity ratios on neighboring links suggest that the effects of the initial disruption can cascade to the surrounding network and lead to severe impacts for many travellers. Further, we analyze the potential of increasing network resilience by increasing capacity on alternative links in response to disruptions. This implies operational strategies such as increasing the frequency on existing lines, or running replacement lines for the disrupted line. This analysis thus enables the evaluation of alternative mitigation measures designed to improve network resilience.

The introduction of new links to network topology could potentially contrib-ute to greater capability to withstand system breakdowns. This paper analyses the value of adding new cross-radial links for public transport network resilience. The value is evaluated in terms of passenger welfare under disruptions. Using a model that considers passengers’ dynamic travel choices, stochastic traffic conditions, timetables and capacity constraints, a new light rail transit line in Stockholm, Sweden is evaluated. The results show that the cross-radial link reduces the impacts of disrup-tions of critical links; the total value of resilience is positive and significantly offsets the loss in welfare caused by disruption of the cross-radial link itself.

Waiting time uncertainty is one of the main determinants of public transport reliability and overall level-of-service. The dissemination of real-time information concerning vehicle arrivals is often considered an important measure to reduce unreliability. Moreover, the prediction of downstream vehicle trajectories could also benefit real-time control strategies. In order to adequately analyze the performance of real-time bus arrival information system, the generated predictions have to be compared against empirical bus arrival data. A conventional real-world bus arrival prediction scheme is formulated and applied on the trunk lines network in Stockholm. This scheme was found to systematically underestimate the remaining waiting time by 6.2% on average. Prediction error accuracy and reliability varies considerably over time periods, along the route and as a function of the prognosis horizon. The difference between passengers' waiting time expectations derived from the timetable and real-time information is equivalent to 30% of the average waiting time.

Cities worldwide are looking for new policies to attract travelers to shift from cars to public transport. Policies focused on reducing public transport fares are aimed at improving social inclusion and leading to a modal shift. The City of Tallinn, the capital of Estonia, has recently introduced a fare-free public transport (FFPT) service in an effort to improve accessibility and mobility for its residents. The case of Tallinn is a full-scale, real-world experiment that provides a unique opportunity for investigating the impacts of FFPT policy. A macrolevel empirical evaluation of FFPT impacts on service performance, passenger demand, and accessibility for various groups of travelers is presented. In contrast to previous studies, the influence of FFPT on passenger demand was estimated while changes in supply were controlled. The results indicate that the FFPT measure accounts for an increase of 1.2% in passenger demand, with the remaining increase attributed to an extended network of public transport priority lanes and increased service frequency. The relatively small effect could be attributed to the previous price level and public transport share as well as analysis of the short-term impact. The evidence-based policy evaluation in this paper is instrumental in supporting policy making and facilitating the design of public transport pricing strategies.