There has been a growing interest in understanding how firms allocate their trucks across hauls, and how this allocation changes under various economic environments. This study investigates how variations in route/haul, carrier and vehicle characteristics affect the optimal vehicle size choice and the associated choice of shipment size. We show that the two choices are derived from the same optimization problem. There can be a continuum of shipment sizes, but decision-makers in freight transport have to choose from a limited number of vehicle alternatives. Therefore, we use a discrete-continuous econometric model where shipment size is modeled as a continuous variable, and vehicle size/type choice as a discrete variable. The results indicate that when faced with higher demand, and during longer trips firms are more likely to use heavier vehicles and ship in larger quantities which suggest that firms are realizing economies of scale and economies of distance. The study also discusses the effect of vehicle operating cost on the vehicle selection process and its policy implications.

Currently, there is a great need for new methods to collect travel data. Traditional methods have considerable drawbacks and, at the same time, the models used to analyse the transport system require more and more detailed and high-quality data. An alternative method that stands out as very promising is to capture raw data from devices that can use any positioning technology (e.g., GPS, WiFi positioning, GSM, etc.), followed by transforming the raw data into meaningful travel data. Since most smartphones are equipped with various sensors that can be used to determine the location of the smartphone, and since smartphones are integrated in the daily life of most people, they provide an unprecedented opportunity for large-scale travel data collection. This method has a great potential to solve the problems related to the estimation of distance/travel time, geographic coding of departure/destination locations and forgotten trips and it will also provide a more detailed and extensive data set. In a recently completed research project the feasibility of replacing or complementing the traditional travel diary, with a suite of tools that make use of smartphone collected travel data has been evaluated. The advantages and disadvantages of the traditional method and the proposed method were studied. For a fair comparison, both methods have been tested in the same city, at the same time, and with the same respondents. To achieve the objectives of the project, MEILI, a system that consists of a smartphone application for capturing the movement of users and a web application for allowing the users to annotate their movement, has been deployed. The recruitment of respondents is a critical phase for traditional travel diaries and, as expected, this was the case also for the smartphone based method. A lesson learnt was that it is important to simplify the registration process as much as possible. In total 2142 trips were collected and annotated by 171 users. 51 of the users annotated trips covering more than a week. The experiences from the field trial shows that a smartphone based travel diary collection is a very useful complement to traditional travel diary collection methods since it appeals to a different age group and collects more detailed travel data for a longer period. The main findings of the paper are that smartphone based data collection is feasible, that the algorithms to save battery work well and that trips of the same respondent vary considerably depending on day of the week.

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.

Cost Benefit Analysis (CBA) has for a long time been used in transport planning, but it is often questioned. One main argument against CBA is that the results depend largely on assumptions regarding one or a few input factors, as for example the future fuel price or valuation of CO2 emissions.

The three papers included in this thesis investigate some aspects of uncertainty in transport CBA calculations. The two first papers explore how changes in input data assumptions affect the CBA ranking of six rail and road investments in Stockholm. The first paper deals with the effect of different land-use assumptions while the second deals with the influence of economic growth, driving cost and public transport fare. The third paper investigates how alternative formulations of the public transport mode choice and route choice affect travel flows, ticket revenues and consumer surplus. These are important factors previously known to affect CBA results.

The findings of the first two papers suggest that CBA results are robust concerning different land-use scenarios and single input factors. No change in rank between a road and a rail object is observed in the performed model calculations, and only one change between two road objects. The fact that CBA results seem robust regarding input assumptions supports the use CBA as a tool for selecting transport investments. The results in the third paper indicate that if there is detailed interest in, for example, number of boardings and ticket income from a certain transit line, or the total benefit of a price change, a more detailed formulation of the public transport mode choice and route choice will provide more reliable results. On the other hand, this formulation requires substantially more data on the transit line and price structure than the conventional formulation used in Swedish transport planning, especially in areas with many different pricing systems.

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.

The research on regulatory reform has identified and measured three types of costs associated with the shift from monopoly to competition: transaction costs, misalignment costs and transition costs. In this article we use a case study approach to measure and compare these costs during the deregulation of the Swedish railway system from 2000-2015. Our case studies confirm earlier research that vertical separation and the introduction of competition in the railway markets result in comparatively small direct transaction costs. Extraordinary transaction costs in the form of interrupted contracts are also a minor problem for the railway system as a whole but might create major problems for the affected region. Our research concurs with earlier research on the British railway system and a CER study that misalignment costs seem to be significantly bigger and more troublesome to handle than direct transaction costs. Railway maintenance costs in Sweden using competitive tenders are increasing four to five times faster than railway operations with no measurable improvement in performance. Transition costs have been and continue to be important in the deregulated Swedish railway system. First, procrastination in the form of delayed changes in the allocation of train paths results in misalignment costs that seem to be growing. Second, adjustment costs in the form of handouts to the former monopolist have been ten times higher than the costs for interrupted contracts.

The cost of parking is in many cities subsidized and instead channelled through higher housing prices, wages, taxes, etc. The effects on other markets are principally well known, but the work on the area is limited. In this paper, we study how parking norms affect the size of the housing stock. Our analysis is based on a model of the rental, asset- and construction markets, the results are quality-assured by interviews with market actors. Prices and profits are affected when constructors are forced, through parking norms, to build more parking spaces than the customers demand. Parking norms reduce the housing stock by 1.2% and increase rents by 2.4% (SEK 300) in our example suburb. (C) 2016 Elsevier Ltd. All rights reserved.

Standard cost-benefit analyses of transport policy measures will not capture all benefits and losses if there are labour market imperfections. In the case of congestion charges, theoretical analyses have raised concerns that these effects may constitute considerable losses, possibly to the extent that aggregate welfare is reduced, contrary to conventional wisdom. We investigate this by estimating the effects on labour income of the Stockholm congestion charges, using an estimated relationship between accessibility and income. Results show that effects on labour income are, in fact, positive. It turns out to be crucial that the model accounts for value-of-time heterogeneity.

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.

We analyse changes in individual travel behaviour in Stockholm County over 30 years, using three large cross-sectional travel survey data sets. We show how travel patterns evolve over time by gender, income and age-group, in different areas of the region (centre vs. periphery).  We relate the observed trends in travel behaviour to societal trends (gender equality, ICT adoption, knowledge-based economy) and policy changes (congestion charges), and we compare them to trends in other European capital cities.

Many western countries have seen a plateau and subsequent decrease of car travel during the 21st century. What has generated particular interest and debate is the statement that the development cannot be explained by changes in traditional explanatory factors such as GDP and fuel prices. Instead, it has been argued, the observed trends are indications of substantial changes in lifestyles, preferences and attitudes to car travel; what we are experiencing is not just a temporary plateau, but a true “peak car”. However, this study shows that the traditional variables GDP and fuel price are in fact sufficient to explain the observed trends in car traffic in all the countries included in our study: the United States, France, the United Kingdom, Sweden and (to a large extent) Australia and Germany. We argue that the importance of the fuel price increases in the early 2000s has been underappreciated in the studies that shaped the later debate. Results also indicate that GDP elasticities tend to decrease with rising GDP, and that fuel price elasticities tend to increase at high price levels and during periods of rapid price increases.

Vulnerability, exposure and criticality in various infrastructures are issues that have been more explicitly looked into in recent years. However, road vulnerability as such has not been in focus for very long, despite the fundamental importance of our road networks in everyday life, as well as in crisis evacuation situations. Consequently, network reliability in transport modelling is an important and growing field of research (Lam 1999). The connection between reliability, vulnerability and other related concepts are discussed in Berdica (2002), with the main proposition that vulnerability analysis of road networks should be regarded as an overall framework, within which different transport studies can be performed to describe how well our transport systems function when exposed to different kinds of disturbances. Following that approach, this paper presents the results from a model-based case study, performed with the overall objective to study how vulnerable the Stockholm road network is in different respects. More specifically it is built up around three main questions:

1.      How do interruptions of different critical links affect the system and how important are these links in relation to one another?

2.      How is the network performance affected by general capacity reductions and possible prioritisation of a sub-network?

3.      How is the system affected by traffic demand variations, i.e. how close to its capacity limit does the system operate?

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.

During the last decades, many activity-based models have been developed in the literature. However, especially in random utility based models timing decisions are often treated poorly or inconsistently with other choice dimensions. In this paper we show how dynamic discrete choice can be used to overcome this problem. In the proposed model, trip decisions are made sequentially in time, starting at home in the morning and ending at home in the evening. At each decision stage, the utility of an alternative is the sum of the one-stage utility of the action and the expected future utility in the reached state.

The model generates full daily activity schedules with any number of trips that each is a combination of one of 6 activities, 1240 locations and 4 modes. The ability to go from all to all locations makes evaluating the model very time consuming and sampling of alternatives were therefore used for estimation. The model is estimated on travel diaries and simulation results indicates that it is able to reproduce timing decisions, trip lengths and distribution of the number trips within sample.

To explain when people perform different activities, two sets of parameters are used: firstly, the utility of being at home varies depending on the time of day; and secondly, constants determine the utility of arriving to work at specific times. This was enough to also obtain a good distribution of the starting times for free-time activities.

The parameters for travel time and travel cost are central in travel demand forecasting models. Since valuation of infrastructure investments requires prediction of travel demand for future evaluation years, inter-temporal variation of the travel time and travel cost parameters is a key issue in forecasting. Using two identical stated choice experiments conducted among Swedish drivers with an interval of 13 years, 1994 and 2007, this paper estimates the inter-temporal variation in travel time and cost parameters (under the assumption that the variance of the error components of the indirect utility function is equal across the two datasets). It is found that the travel time parameter has remained constant over time but that the travel cost parameter has declined in real terms. The trend decline in the cost parameter can be entirely explained by higher average income level in the 2007 sample compared to the 1994 sample. The results support the recommendation to keep the travel time parameter constant over time in forecast models, but to deflate the travel cost parameter with the forecasted income increase among travellers and the relevant income elasticity of the cost parameter. Evidence from this study further suggests that the inter-temporal and the cross-sectional income elasticities of the cost parameter are equal. The average elasticity is found to be -0.8 to -0.9 in the present sample of drivers, and the elasticity is found to increase with the real income level, both in the cross-section and over time.

This paper describes a study undertaken to estimate a departure-time and mode-choice model for Stockholm. The model is segmented according to trip purpose, and a mixed - or error component - logit model is estimated. Estimation draws on stated preference data collected from drivers travelling toward the city centre during morning peak hours. The study uncovers drivers' preferences for scheduled delay, unexpected delay, travel time and cost as well the patterns of substitution between mode and time of day alternatives. The result indicates that disutility of unexpected delay depends on the scheduled deviation from preferred arrival time. The preference for scheduled delay is roughly proportional to the time shift and varies in the population, but is much more consistent within an individual. Another finding is that constraints at the destination mainly restrict late arrival, whereas constraints at the origin mainly restrict early departure.

This study uses a stated choice experiment and drawings of four different type-environments to assess how various security-promoting factors in the built physical environment influence valuation of walking time when accessing public transport. Valuations that can be applied for evaluating policies to improve perceived security are obtained. Consistent results are achieved, indicating that the method is promising for incorporating aspects in the physical environment in the welfare analysis. The results indicate a systematic variation in value of walk time in different physical environments and it is more dependent of the physical environment for women than for men. This paper thereby contributes to the literature by showing that results by social sciences can be verified using methods and theories traditionally used in transport and welfare analysis and may therefore be incorporated in standard CBA. A contribution of this study is the insight that the perception of insecurity involved in accessing the public transport system is a welfare loss that can be quantified.

This study uses a stated choice experiment and drawings of four different type-environments to assess how various security-promoting factors in the built physical environment influence valuation of walking time when accessing public transport. Valuations that can be applied for evaluating policies to improve perceived security are obtained. Consistent results are achieved, indicating that the method is promising for incorporating aspects in the physical environment in the welfare analysis. The results indicate a systematic variation in value of walk time in different physical environments and it is more dependent of the physical environment for women than for men. This paper thereby contributes to the literature by showing that results by social sciences can be verified using methods and theories traditionally used in transport and welfare analysis and may therefore be incorporated in standard CBA. A contribution of this study is the insight that the perception of insecurity involved in accessing the public transport system is a welfare loss that can be quantified.

We analyze Internet and telephone Stated Choice (SC) survey methods in the context of the Swedish value of time study 2008. In this study, extensive piloting and follow up surveys was undertaken to assure high quality data. We use these data and data from the main survey to analyse properties of the different data collection methods. One conclusion is that Internet gives less random error in the SC data. On the other hand, the response rate drops when Internet is the only response and recruiting mode. A mixed mode survey, where Internet is the primary method but where respondents are knowingly subject to a telephone follow up survey, is found to give substantially higher Internet response rates. If the telephone follow up does not include SC questions, the value of time result will still be biased. A large part of this bias seems to be explained by socio-economic data, such as income and age, which are cheaper to collect.

The purpose of this paper is to explore to what extent the effects of congestion charges rely on specific features of a city and its transport system. We use Stockholm, and its current congestion charging scheme, as a case study by making various modifications in the transport system influencing the availability and attractiveness of public transport, bypasses and bottleneck capacities. We use a transport model to forecast the effects of the Stockholm charges given each transport system modification. Our main conclusion is that although the social benefit of a given charging system is considerably and non-linearly dependent on initial congestion levels, traffic effects and adaptations costs are surprisingly stable across transport system modifications. Specifically, the level of public transport provision has only small effects on baseline congestion, and therefore on the total benefit of the charges. Contrary to expectation, the charges' effect on traffic volumes remains virtually unchanged regardless of the changes in public transport supply. All results are compared to and consistent with the one-market standard model. We interpret our results with respect to common arguments against the transferability of experiences from cities having introduced congestion charges.