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• 1. Ben-Akiva, M.
KTH, Superseded Departments, Infrastructure.
Hybrid choice models: Progress and challenges2002In: Marketing letters, ISSN 0923-0645, E-ISSN 1573-059X, Vol. 13, no 3, p. 163-175Article in journal (Refereed)
• 2.
KTH, Superseded Departments, Infrastructure.
KTH, Superseded Departments, Infrastructure and Planning.
Identifying local spatial association in flow data1999In: Journal of Geographical Systems, ISSN 1435-5930, E-ISSN 1435-5949, Vol. 1, no 3, p. 219-236Article in journal (Refereed)

In this paper we develop a spatial association statistic for flow data by generalizing the statistic of Getis-Ord, Gi (and Gi*). This local measure of spatial association, Gij, is associated with each origin-destination pair. We define spatial weight matrices with different metrics in flow space. These spatial weight matrices focus on different aspects of local spatial association. We also define measures which control for generation or attraction nonstationarity. The measures are implemented to examine the spatial association of residuals from two different models. Using the permutation approach, significance bounds are computed for each statistic. In contrast to the Gi statistic, the normal approximation is often appropriate, but the statistics are still correlated. Small sample properties are also briefly discussed.

• 3.
KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis.
KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis.
Kan vi lita på trafikprognoser? – En kritisk granskning av några trafikmodeller1996Report (Other academic)
• 4.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics. Royal Institute of Technology.
KTH, Superseded Departments (pre-2005), Infrastructure and Planning.
A joint between-day and within-day activity based travel demand with forward looking individualsManuscript (preprint) (Other academic)

Including day-to-day planning to account for systematic variability in activity participation has the potential to further improve travel demand models. This paper introduce a dynamic discrete choice model of day-to-day and within-day planning in a joint framework. No model up to date jointly treats within-day and day-to-day planning with individuals that take future days into account. The model is estimated using a combination of a small survey with week long data and a larger single day travel survey. A static, myopic and forward looking version of the model is estimated. There is a big improvement in model fit when moving from a static to a dynamic model, but allowing forward-looking behaviour gives a relatively small additional improvement. As a policy test, grocery stores are closed on Sundays. The myopic model predicts that people as a consequence will shop more on Mondays-Thursdays and therefore unintuitively also less on Saturdays. The forward looking model also predicts increased shopping on weekdays but mainly that people will shop more on Saturdays anticipating that stores are closed on Sundays.

• 5.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics. Royal Institute of Technology.
KTH, Superseded Departments (pre-2005), Infrastructure and Planning. KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics.
Discount factors greater than or equal to one in infinite horizon dynamic discrete choice modelsManuscript (preprint) (Other academic)

In this paper, the theory on infinite horizon DDCM's is extended to allow for discount factors greater than or equal to one. The proposed methods are applied to Rust's (1987) bus engine replacement model, where a discount factor of 1.075 is identified using grid search. The infinite horizon problem with and without a terminal state are treated separately. Sufficient conditions are given for the existence of solutions to Bellman's equation in the terminal state problem and to a normalized version of Bellman's equation in the non-terminal state setting. If a terminal state exists, acting according to Bellman's equation still yields the maximum expected total utility under derived conditions on the one-stage utility functions and reachability of the terminal state. In the non-terminal state problem, $\beta=1$ implies that individuals maximize the average cost per stage, but for $\beta>1$ no rationale for acting according to Bellman's equation, even when it has a solution, has been found.

• 6.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics. Royal Institute of Technology.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science. KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics.
A dynamic discrete choice activitybased travel demand modelManuscript (preprint) (Other academic)

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.

• 7.
KTH, Superseded Departments, Infrastructure and Planning.
KTH, Superseded Departments, Infrastructure and Planning.
A new information theoretical measure of global and local spatial association, S2002In: The Review of Regional Research, Vol. 22, p. 13-40Article in journal (Refereed)

In this paper a new measure of spatial association, the S statistics, is developed.The proposed measure is based on information theory by defininga spatially weighted information measure (entropy measure) that takes thespatial configuration into account. The proposed S-statistics has an intuitiveinterpretation, and furthermore fulfils properties that are expected from anentropy measure. Moreover, the S statistics is a global measure of spatialassociation that can be decomposed into Local Indicators of Spatial Association(LISA). This new measure is tested using a dataset of employmentin the culture sector that was attached to the wards over Stockholm Countyand later compared with the results from current global and local measuresof spatial association. It is shown that the proposed S statistics share manyproperties with Moran’s I and Getis-Ord Gi statistics. The local Si statisticsshowed significant spatial association similar to the Gi statistic, but has the advantage of being possible to aggregate to a global measure of spatialassociation. The statistics can also be extended to bivariate distributions.It is shown that the commonly used Bayesian empirical approach can beinterpreted as a Kullback-Leibler divergence measure. An advantage of Sstatisticsis that this measure select only the most robust clusters, eliminatingthe contribution of smaller ones composed by few observations and that mayinflate the global measure.

• 8.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering. KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics.
Estimating changes in transport CO2 emissions due to changes in weather and climate in SwedenManuscript (preprint) (Other academic)

There is a considerable body of studies on the relationship between daily transport activities and CO2 emissions. However, how these emissions vary in different weather conditions within and between the seasons of the year is largely unknown. Because individual activity–travel patterns are not static but vary in different weather conditions, it is immensely important to understand how CO2 emissions vary due to the change of weather. Using Swedish National Travel Survey data, with emission factors calculated through the European emission factor model ARTEMIS, this study is a first attempt to derive the amount of CO2 emission changes subject to the change of weather conditions. A series of econometric models was used to model travel behaviour variables that are crucial for influencing individual CO2 emissions. The marginal effects of weather variables on travel behaviour variables were derived. The results show an increase of individual CO2 emissions in a warmer climate and in more extreme temperature conditions, whereas increasing precipitation amounts and snow depths show limited effects on individual CO2 emissions. It is worth noting that the change in CO2 emissions in the scenario of a warmer climate and a more extreme temperature tends to be greater than the sum of changes in CO2 emissions in each individual scenario. Given that a warmer climate and more extreme weather could co-occur more frequently in the future, this result suggests even greater individual CO2 emissions than expected in such a future climate.

• 9.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering. KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics.
Weather Variability and Travel Behaviour - What Do We Know and What Do We Not KnowManuscript (preprint) (Other academic)

Given that severe weather conditions is becoming more and more frequent, understanding the roles of weathers in influencing individual’s daily activity-travel pattern is important. Whilst some of previously rare events, such as heavy rain, unpredictable snow, higher temperature, less clear differences between seasons etc., would become more common, it is still largely unknown how individual would change and adapt their travel pattern in future climate conditions. Because of this concern, the number of researches on weather and travel behaviour has been increased dramatically in the recent decades. Most of those empirical evidences, however, have not been adopted in cost-benefit analysis (CBA), which serves as the main tool for policy evaluation and project selection by stakeholders. This study summarizes the existing findings in relations between weather variability and travel behaviour, and critically assesses the methodological issues in those studies. Several further research directions are identified and suggested for bridging the gap between empirical evidence and current practice in CBA.

• 10.
KTH, School of Architecture and the Built Environment (ABE), Transport Science.
KTH, School of Architecture and the Built Environment (ABE), Transport Science. KTH, School of Architecture and the Built Environment (ABE), Transport Science.
Estimating changes in transport CO2 emissions due to changes in weather and climate in Sweden2016In: Transportation Research Part D: Transport and Environment, ISSN 1361-9209, E-ISSN 1879-2340, Vol. 49, p. 172-187Article in journal (Refereed)

There is a considerable body of studies on the relationship between daily transport activities and CO2 emissions. However, how these emissions vary in different weather conditions within and between the seasons of the year is largely unknown. Because individual activity–travel patterns are not static but vary in different weather conditions, it is immensely important to understand how CO2 emissions vary due to the change of weather. Using Swedish National Travel Survey data, with emission factors calculated through the European emission factor model ARTEMIS, this study is a first attempt to derive the amount of CO2 emission changes subject to the change of weather conditions. A series of econometric models was used to model travel behaviour variables that are crucial for influencing individual CO2 emissions. The marginal effects of weather variables on travel behaviour variables were derived. The results show an increase of individual CO2 emissions in a warmer climate and in more extreme temperature conditions, whereas increasing precipitation amounts and snow depths show limited effects on individual CO2 emissions. It is worth noting that the change in CO2 emissions in the scenario of a warmer climate and a more extreme temperature tends to be greater than the sum of changes in CO2 emissions in each individual scenario. Given that a warmer climate and more extreme weather could co-occur more frequently in the future, this result suggests even greater individual CO2 emissions than expected in such a future climate.

• 11.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering. KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics.
Jointly modelling individual’s daily activity-travel time use andmode share by a nested multivariate Tobit model system2015In: Transportation Research Procedia: 21st International Symposium on Transportation and Traffic Theory, Elsevier, 2015, Vol. 9, p. 71-89Conference paper (Refereed)

Understanding mechanisms underlie the individual’s daily time allocations is very important to understand the variability ofindividual’s time-space constraints and to forecast his/her daily activity participation. At most of previous studies, activity timeallocation was viewed as allocating a continuous quantity (daily time budget) into multiple discrete alternatives (i.e. variousactivities and trips to engage with). However, few researches considered the influence of travel time that needs to be spent onreaching the activity location. Moreover, travel time itself is influenced by individuals’ mode choice. This can lead to an over- orunder-estimation of particular activity time location. In order to explicitly include the individual’s travel time and mode choiceconsiderations in activity time allocation modelling, in this study, a nested multivariate Tobit model is proposed. This proposedmodel can handle: 1. Corner solution problem (i.e. the present of substantial amount of zero observations); 2. Time allocationtrade-offs among different types of activities (which tends to be ignored in previous studies); 3. Travel is treated as a deriveddemand of activity participation (i.e. travel time and mode share are automatically censored, and are not estimated, ifcorresponding activity duration is censored). The model is applied on a combined dataset of Swedish national travel survey(NTS) and SMHI (Swedish Meteorological and Hydrological Institute) weather record. Individuals’ work and non-work activitydurations, travel time and mode shares are jointly modelled as dependent variables. The influences of time-locationcharacteristics, individual and household socio demographics and weather characteristics on each dependent variable areexamined. The estimation results show a strong work and non-work activity time trade-offs due to the individual’s time-spaceconstraints. Evidences on a potential positive utility of travel time added on non-work activity time allocation in the Swedish case,are also found. Meanwhile, the results also show a consistent mode choice preference for a given individual. The estimatednested multivariate Tobit model provides a superior prediction, in terms of the deviation of the predicted value against the actualvalue conditional on the correct prediction regarding censored and non-censored, compared to mutually independent Tobitmodels. However, the nested multivariate Tobit model does not necessarily have a better prediction for model componentsregarding non-work related activities.

• 12. Dagsvik, John K.
KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Transport and Location Analysis (closed 20110301).
Compensating variation and Hicksian choice probabilities in random utility models that are nonlinear in income2005In: The Review of Economic Studies, ISSN 0034-6527, E-ISSN 1467-937X, Vol. 72, no 1, p. 57-76Article in journal (Refereed)

In this paper we discuss Hicksian demand and compensating variation in the context of discrete choice. We first derive Hicksian choice probabilities and the distribution of the (random) expenditure function in the general case when the utilities are nonlinear in income. We subsequently derive exact and simple formulae for the expenditure and choice probabilities under price (policy) changes conditional on the initial utility level. This is of particular interest for welfare measurement because it enables the researcher to compute the distribution of compensating variation in a simple way. We also derive formulae for the joint distribution of expenditure, the choice before and after a policy change has been introduced.

• 13.
KTH, School of Architecture and the Built Environment (ABE), Transport Science.
KTH, School of Architecture and the Built Environment (ABE), Transport Science. KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics.
Collecting a multi-dimensional three-weeks household time-use and activity diary in the Bandung Metropolitan Area, Indonesia2015In: Transportation Research Part A: Policy and Practice, ISSN 0965-8564, E-ISSN 1879-2375, Vol. 80, p. 231-246, article id 1641Article in journal (Refereed)

This paper describes a comprehensive panel data collection and analysis at household level, including detailed travel behaviour variables and comprehensive in-home and out-of-home activities, individual cognitive habits and affective behaviours, the rate of physical activity, as well as health related quality of life (QoL) information in the Bandung Metropolitan Area (BMA) of Indonesia. To our knowledge, this is the first attempt to collect an individual's activity diary over an extended period as it captures the multi-tasking activities and multidisciplinary factors that underlie individual activity-travel patterns in a developing country. Preliminary analyses of the collected data indicate that different beliefs, anticipated emotions, support and attachment to motorised modes significantly correlate with different groups of occupation, gender, age, activity participation, multi-tasking activities, and physical health, but not with different social and mental health. This finding highlights the reason why implementing car reduction policies in Indonesia, without breaking or changing the individual's habits and influencing his/her attitudes have not been fruitful. The results also show that endorsing more physical activities may result in a significant reduction in the individual's motorised mode use, whilst individuals who demonstrate a tendency to use their spare time on social activities tend to have better social health conditions. Furthermore, undertaking multi-tasking out-of-home discretionary activities positively correlates with better physical health. All these highlight the importance of properly understanding and analysing the complex mechanisms that underlie these fundamental factors that shape individual daily activity-travel patterns in developing countries. This type of multidisciplinary approach is needed to design better transport policies that will not only promote better transport conditions, but also a healthier society with a better quality of life.

• 14. Dharmowijoyo, Dimas B. E.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics. KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics.
Relationships among discretionary activity duration, its travel time spent and activity space indices in the Jakarta Metropolitan Area, Indonesia2016In: Journal of Transport Geography, ISSN 0966-6923, E-ISSN 1873-1236, Vol. 54, p. 148-160Article in journal (Refereed)

This study examines the interdependencies among an individual's time allocation for different activities and the travel time spent on a given day, socio-demographic and built environment variables on these in-home and out of-home discretionary activities time duration, and how interaction of those variables on discretionary activities time duration influences an individual's activity space indices in the Jakarta Metropolitan Area (JMA), Indonesia. The 3SLS model and the 2004 SITRAMP household travel survey were used to achieve this objective. The results show that the time allocation for certain discretionary activities significantly influences the time allocation for other discretionary activities. Workers, students and non-workers have different complex mechanisms pertaining to how they allocate time across different activities and journeys. This unique trade-off mechanism gives an individual a unique distribution of activity locations and spatial movement patterns. This is observed via his/her activity space indices throughout time and space. For example, the estimation result shows that workers' and students' time-use allocation, activities participation and activity space indices are highly influenced by their engagement in mandatory activities. However, this is not the case for non-workers. Furthermore, the mandatory travel time variable has a stronger impact on an individual's discretionary activities time-use pattern than the duration of mandatory activities. This may lead to the argument that, in order to provide more opportunities and flexibilities among the JMA's workers and students for undertaking discretionary activities, travel time reduction policies can play more significant role in shaping the discretionary activity-travel patterns than reduction in working/school hour policies. Additionally, in-line with previous findings in developed countries, locating grocery shops closer to residential areas in the CBD and in suburban areas creates more opportunities for workers and students to spend more time on out-of-home maintenance activities; with a shorter travel time, especially on. Fridays.

• 15. Dharmowijoyo, Dimas B. E.
KTH, School of Architecture and the Built Environment (ABE), Transport Science.
Analysing the complexity of day-to-day individual activity-travel patterns using a multidimensional sequence alignment model: A case study in the Bandung Metropolitan Area, Indonesia2017In: Journal of Transport Geography, ISSN 0966-6923, E-ISSN 1873-1236, Vol. 64, p. 1-12Article in journal (Refereed)

Using a panel regression model and a multidimensional three-week household time-use and activity diary, this study analyses the complexity of the day-to-day variability in individuals' activity-travel patterns by applying a multidimensional sequence alignment model. It is found that the variability between weekend and weekday pairs is much greater than between weekday-weekday pairs or weekend-weekend pairs. The variability of other household members' activity-travel patterns is found to significantly influence an individual's activity-travel patterns. The results also show that the variability in the activity-travel patterns of workers and students is greater when conducting a particular discretionary activity on weekdays. Due to performing discretionary activities more often and for longer, non-workers tend to have more predictable activity-travel patterns. Undertaking multitasking activities within different activities on weekdays significantly impacted the different degrees of variability in an individual's activity-travel patterns. Having different health and built environment characteristics also corresponds with different degrees of predictability of the activity-travel patterns, particularly in the worker/student case.

• 16.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering. KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics.
Analysing the complexity of day-to-day individuals’ activity-travel pattern using Multi-dimensional Sequence Alignment Method: A case study in Bandung Metropolitan Area, IndonesiaManuscript (preprint) (Other academic)
• 17.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis.
Day-to-day interpersonal and intrapersonal variability of individuals' activity spaces in a developing country2014In: Environment and Planning, B: Planning and Design, ISSN 0265-8135, E-ISSN 1472-3417, Vol. 41, no 6, p. 1063-1076Article in journal (Refereed)

Using the SITRAMP dataset, which was collected in the Jakarta metropolitan area, Indonesia, over four consecutive days, this study examines day-to-day variability of individuals' activity spaces. The impact of individual heterogeneity and variability of transport network conditions on day-to-day variability of activity spaces is also investigated. Results show that individuals' activity spaces vary from day to day and between different individuals. The activity space of other household members was found to be the most significant factor influencing an individual's activity space. Against the common belief in developing countries that better traffic conditions make individuals travel farther, results show that higher road-network travel speed and better road surface conditions within the home zones actually encourage individuals to visit a more compact set of activity locations and/or visit fewer activity locations. Smoother road surface conditions and higher travel speeds within home zones also bring the centroid of activity locations closer to individuals' home locations. Furthermore, day-to-day variability analysis of individual activity spaces showed that weekday activity spaces are more compact than those at weekends. Moreover, it was found that students' activity spaces show most variability, while those of nonworkers have the lowest variability.

• 18.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
Day-to-day variability in travellers' activity-travel patterns in the Jakarta metropolitan area2016In: Transportation, ISSN 0049-4488, E-ISSN 1572-9435, Vol. 43, no 4, p. 601-621Article in journal (Refereed)

Using four consecutive days of SITRAMP 2004 data from the Jakarta metropolitan area (JMA), Indonesia, this study examines the interactions between individuals’ activity-travel parameters, given the variability in their daily constraints, resources, land use and road network conditions. While there have been a significant number of studies into day-to-day variability in travel behaviour in developed countries, this issue is rarely examined in developing countries. The results show that some activity-travel parameter interactions are similar to those produced by travellers from developed countries, while others differ. Household and individual characteristics are the most significant variables influencing the interactions between activity-travel parameters. Different groups of travellers exhibit different trade-off mechanisms. Further analyses of the stability of activity-travel patterns across different days are also provided. Daily commuting time and regular work and study commitments heavily shape workers’ and students’ flexibility in arranging their travel time and out-of-home time budget, leading to more stable daily activity-travel patterns than non-workers.

• 19.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering. KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics.
On complexity and variability of individuals’ day-to-day discretionary activitiesManuscript (preprint) (Other academic)
• 20. Dharmowijoyo, Dimas B. E.
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, System Analysis and Economics. KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, System Analysis and Economics.
On complexity and variability of individuals' discretionary activities2018In: Transportation, ISSN 0049-4488, E-ISSN 1572-9435, Vol. 45, no 1, p. 177-204Article in journal (Refereed)

Using a hierarchical structured equation model and a multi-dimensional 3-week household time-use and activity diary conducted in Bandung Metropolitan Area, Indonesia, this study investigated the interaction among individuals' non-instrumental variables, time space (such as their day-to-day time duration of activity participation, socio-demographics and built environment), and health factors on individuals' day-to-day discretionary activities. The results show that individuals' subjective characteristics and day-to-day time-space components significantly influence decision making processes to participate in certain activities, particularly grocery shopping. Integration between subjective factors and day-to-day time duration of activity participation also reveals how an individual categorises a particular behaviour as routine, planned or impulsive. For example, grocery shopping is a planned behaviour with real consequences (e.g. starving). Appearing as a strong commitment and intention enables individuals to allocate time to engage in this activity. Thus, given the individual's time-space constraints, there may be a regular trade-off between frequency and duration. On the other hand, out-of-home social-recreational activity is a less urgent/impulsive activity and depends far more on an individual's day-to-day time-space constraints than his/her subjective characteristics. If the situation on the given day is not feasible for him/her to undertake the out-of-home social recreational activity, he/she is more likely to re-schedule the activity. The study results also show that land use configuration and perceived accessibilities influence individuals' discretionary activity participation.

• 21.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering. KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics.
Relationships among discretionary activity duration, travel time spent and activity space indices in the Jakarta Metropolitan Area, IndonesiaManuscript (preprint) (Other academic)
• 22.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis.
The Day to Day Inter and Intra Personal Variability of Individual's Action Space in Developing CountryIn: Environment and Planning, B: Planning and Design, ISSN 0265-8135, E-ISSN 1472-3417Article in journal (Other academic)
• 23.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
The Day to Day Variability of Traveller's Activity Travel Pattern in The Jakarta Metropolitan Area2012In: TRB 93rd Annual Meeting Compendium of Papers, TRB , 2012, , p. 24Conference paper (Refereed)

Using four consecutive days of SITRAMP Data (2004) from the Jakarta Metropolitan Area (JMA), this study examines the interactions between individuals’ activity-travel pattern variables in the context of their daily constraints, resources and external opportunities. The results from our simultaneous equation modeling show that the observed individual’s activity-travel patterns are the result of the complex interactions between each individual’s activity-travel parameters, which vary from day to day. Some of the interactions are similar with the patterns produced by travelers from developed countries, while others are different. Household and individual characteristics are the most significant variables influencing the interactions among individual activity-travel patterns. Different groups of travelers have different trade-off mechanisms. Further analyses on the stability of the activity-travel patterns across different days are provided. Daily commuting time and regular work commitments heavily shape workers’ and students’ flexibility in arranging their travel time and out-of-home time budget, leading them to more stable daily activity-travel patterns than non-workers. The model also shows that highly unpredictable traffic significantly influences workers’ and students’ intra-personal variability in travel time, more so than any other variable.

• 24.
KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Land and Water Resources Engineering. KTH, School of Architecture and the Built Environment (ABE), Transport Science.
KTH, School of Architecture and the Built Environment (ABE), Transport Science. KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Land and Water Resources Engineering.
Applying spatial regression to evaluate risk factors for microbiological contamination of urban groundwater sources in Juba, South Sudan2017In: Hydrogeology Journal, ISSN 1431-2174, E-ISSN 1435-0157, Vol. 25, p. 1077-1091Article in journal (Refereed)

This study developed methodology for statistically assessing groundwater contamination mechanisms. It focused on microbial water pollution in low-income regions. Risk factors for faecal contamination of groundwater-fed drinking-water sources were evaluated in a case study in Juba, South Sudan. The study was based on counts of thermotolerant coliforms in water samples from 129 sources, collected by the humanitarian aid organisation M,decins Sans FrontiSres in 2010. The factors included hydrogeological settings, land use and socio-economic characteristics. The results showed that the residuals of a conventional probit regression model had a significant positive spatial autocorrelation (Moran's I = 3.05, I-stat = 9.28); therefore, a spatial model was developed that had better goodness-of-fit to the observations. The most significant factor in this model (p-value 0.005) was the distance from a water source to the nearest Tukul area, an area with informal settlements that lack sanitation services. It is thus recommended that future remediation and monitoring efforts in the city be concentrated in such low-income regions. The spatial model differed from the conventional approach: in contrast with the latter case, lowland topography was not significant at the 5% level, as the p-value was 0.074 in the spatial model and 0.040 in the traditional model. This study showed that statistical risk-factor assessments of groundwater contamination need to consider spatial interactions when the water sources are located close to each other. Future studies might further investigate the cut-off distance that reflects spatial autocorrelation. Particularly, these results advise research on urban groundwater quality.

• 25.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
Using Sparse GPS Data to Estimate Route Choice Models with Correlated Path Costs2012Conference paper (Refereed)
• 26.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis.
Consistently estimating link speed using sparse GPS data with measured errors2014In: Transportation: Can we do more with less resources? – 16th Meeting of the Euro Working Group on Transportation – Porto 2013, Elsevier, 2014, p. 829-838Conference paper (Refereed)

Data sources using new technology such as the Geographical Positioning System are increasingly available. In many different applications, it is important to predict the average speed on all the links in a network. The purpose of this study is to estimate the link speed in a network using sparse GPS data set. Average speed is consistently estimated using Indirect Inference approach. in the end, the Monte Carlo evidence is provided to show that the results are consistent with parameter estimates.

• 27.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
Estimating flexible route choice models using sparse data2012In: Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference on, IEEE conference proceedings, 2012, p. 1215-1220Conference paper (Refereed)

GPS and nomad devices are increasingly used to provide data from individuals in urban traffic networks. In many different applications, it is important to predict the continuation of an observed path, and also, given sparse data, predict where the individual (or vehicle) has been. Estimating the perceived cost functions is a difficult statistical estimation problem, for different reasons. First, the choice set is typically very large. Second, it may be important to take into account the correlation between the (generalized) costs of different routes, and thus allow for realistic substitution patterns. Third, due to technical or privacy considerations, the data may be temporally and spatially sparse, with only partially observed paths. Finally, the position of vehicles may have measurement errors. We address all these problems using a indirect inference approach. We demonstrate the feasibility of the proposed estimator in a model with random link costs, allowing for a natural correlation structure across paths, where the full choice set is considered.

• 28.
Technical University of Denmark, 2800 Kgs Lyngby, Denmark .
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
A link based network route choice model with unrestricted choice set2013In: Transportation Research Part B: Methodological, ISSN 0191-2615, E-ISSN 1879-2367, Vol. 56, p. 70-80Article in journal (Refereed)

This paper considers the path choice problem, formulating and discussing an econometric random utility model for the choice of path in a network with no restriction on the choice set. Starting from a dynamic specification of link choices we show that it is equivalent to a static model of the multinomial logit form but with infinitely many alternatives. The model can be consistently estimated and used for prediction in a computationally efficient way. Similarly to the path size logit model, we propose an attribute called link size that corrects utilities of overlapping paths but that is link additive. The model is applied to data recording path choices in a network with more than 3000 nodes and 7000 links.

• 29.
KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis.
KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis.
A dynamic discrete choice approach for consistent route choice model estimation2011In: Proceedings of the Swiss Transport Research Conference, 2011Conference paper (Refereed)

We propose a dynamic discrete choice approach for consistently estimating route choice model parameters based on path observations using maximum likelihood. The approach is computationally efficient and does not require choice set sampling.

• 30. Fosgerau, Mogens
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis.
Consistent route choice model estimation without choice set sampling: a dynamic discrete choice approach2011In: Proceedings of the European Transport Conference, 2011Conference paper (Refereed)
• 31.
KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Transport and Location Analysis (closed 20110301). KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Transport and Location Analysis (closed 20110301). KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Transport and Location Analysis (closed 20110301). KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
Dynamically choosing routes: A dynamic discrete choice model using Krylov subspace methods and LU decomposition2010Conference paper (Other academic)
• 32.
KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Transport and Location Analysis (closed 20110301). KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Transport and Location Analysis (closed 20110301).
Route choice modeling without route choice2009In: Proceedings of the European Transport Conference, 2009Conference paper (Refereed)

Route choice modeling is complex. The number of alternative paths is often very large, while the paths are likely to share unobserved attributes which induces correlation. When modelling this, we face a trade-off between using models that are simple enough to handle many alternative paths while at the same time being able to handle correlation. There is a substantial ongoing research effort seeking to resolve this dilemma, so far with limited success. For these reasons the multinomial logit model (path size logit and c-logit proposed by Ben-Akiva and Bierliare, 1999, and Cascetta et. al., 1996, respectively) is widely used in spite of its known limitations.

The main purpose of this paper is to present and test a dynamic discrete choice approach for the estimation of the parameters of a route choice model. In the dynamic modeling approach, the individual is seen as taking sequential decisions on which link to choose, and the choices are made at the nodes in the network. The obvious advantage with this approach is that the choice set at every stage is quite small and well defined, while a correlation structure is naturally imposed among different paths, even if each sequential decision follows a multinomial logit model. From an econometric point of view, the link choice model can be a lot simper to deal with.

The utility maximising choice of path may be broken down into a sequence of link choices, where at each stage the individual considers the utility associated with downstream link choices accumulated into a value function. However, if we were to compute the value function associated with the available link choices at every stage, the complexity of the problem would be at least the same as the original path choice problem. An exact solution method to calculate the value function runs into the curse of dimensionality when solving a dynamic programming problem. Therefore, the computational burden may be prohibitive for large networks if one tries to solve the dynamic programming problem by brute force. This is probably why the sequential approach is not used for estimating route choice models in spite of having been around for many years (e.g., Dial, 1971).

However, it is not strictly necessary to solve the dynamic programming problem in order to estimate the parameters of the route choice model consistently. It is sufficient to find a suitable approximation to the value function. So the objective of this paper is to test whether it is possible to generate good predictors for the value function such that the parameters of the route choice model may be estimated on link choices rather than path choices. If this turns out to be possible, then both the econometric and computational complexity of route choice modelling may be dramatically reduced.

The paper therefore discusses the conditions under which the route choice model can be consistently estimated. We then test the approach using simulated data for a real network (Borlänge, Sweden), where route choice observations are generated using the exact model, i.e. solving the dynamic programming problem. This allows us to compare the exact value functions with the approximations. We show how the approximation can be defined using proxy variables such as direction and distance to destination. The paper concludes with a discussion on the use of the model for prediction (policy analysis) and related issues.

• 33.
KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Transport and Location Analysis (closed 20110301).
The value of reliability2010In: Transportation Research Part B: Methodological, ISSN 0191-2615, E-ISSN 1879-2367, Vol. 44, no 1, p. 38-49Article in journal (Refereed)

We derive the value of reliability in the scheduling of an activity of random duration, such as travel under congested conditions. Using a simple formulation of scheduling utility, we show that the maximal expected utility is linear in the mean and standard deviation of trip duration, regardless of the form of the standardised distribution of trip durations. This insight provides a unification of the scheduling model and models that include the standard deviation of trip duration directly as an argument in the cost or utility function. The results generalise approximately to the case where the mean and standard deviation of trip duration depend on the starting time. An empirical illustration is provided.

• 34.
KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Transport and Location Analysis (closed 20110301).
KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301). KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Transport and Location Analysis (closed 20110301).
Traveller Responses to the Stockholm Congestion Pricing Trial: Who Changed, Where Did They Go, and What Did It Cost Them?2009In: Travel Demand Management and Road User Pricing: Success, Failure and Feasibility, Ashgate, 2009Chapter in book (Other academic)
• 35.
KTH, School of Architecture and the Built Environment (ABE), Transport and Economics, Transport and Location Analysis.
KTH, School of Architecture and the Built Environment (ABE), Transport and Economics, Transport and Location Analysis.
Travel Time Reliability for Stockholm Roadways Modeling Mean Lateness Factor2009In: Transportation Research Record, ISSN 0361-1981, E-ISSN 2169-4052, no 2134, p. 106-113Article in journal (Refereed)

In recent years, there has been an increasing awareness that travel time reliability, apart from expected travel time, is an important component of cost-benefit analysis, especially during congested traffic conditions. A common measure of travel time reliability is standard deviation, and it has been shown that this is a theoretically sound measure under scheduling constraints, provided that the mean lateness factor is known. Hence, in applied cost-benefit analyses, one will need both the standard deviation and the mean lateness factor. These analyses would be particularly simple if the mean lateness were constant across time of day and for different routes chosen. A study was done to explore how the mean lateness varies and how its variations can be approximated. With the use of travel time measurements on individual links, it is shown how mean lateness varies considerably across time and space. It is shown that mean lateness exhibits a time-varying pattern depending on the characteristics of congestion on the link. It is also shown that the location of the link in the network is a significant determinant. The resulting model for mean lateness represents a considerable improvement over existing practice, where the mean lateness is implicitly assumed constant, yet a large portion of its variation remains unexplained. The model is useful for informing future research but is of less value for predicting the mean lateness in broad applied settings.

• 36. Glerum, Aurélie
KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics. Royal Institute of Technology.
A dynamic discrete-continuous choice model of car ownership, usage and fuel typeManuscript (preprint) (Other academic)

This paper presents a dynamic discrete-continuous choice model of car ownership, usage, and fuel type that embeds a discrete-continuous choice model into a dynamic programming framework to account for the forward-looking behavior of households in the context of car acquisition. More specifically, we model the transaction type, the choice of fuel type, and the annual driving distance for up to two cars in the household. We present estimation and cross-validation results based on a subsample of the Swedish population that is obtained from combining the population and car registers. Finally we apply the model to analyze a hypothetical policy that consists of a subsidy that reduces the annual cost of diesel cars.

• 37. Glerum, Aurélie
Faculté des arts et des sciences, Department of Computer Science and Operations Research Université de Montréal Montréal, Canada. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
A dynamic discrete-continuous choice model of car ownership and usage2013In: Proceedings of the 13th Swiss Transport Research Conference, 2013, p. 1-13Conference paper (Refereed)

In this paper we present the methodologicalframework of adynamic discrete-continuouschoicemodel (DDCCM)of car ownership, usage and fuel type. The approach consistsof embeddinga discrete-continuous choice model into adynamic programming (DP)framework. This workproposes the following novel features. First, decisions are modeled at a household level. Sec-ond, we consider an extensive choice variable which involves the car replacement decision,the annual driving distance, the fuel type, the decision to take a company car, or a new versussecond-hand car.

• 38. Gospic, Katarina
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
Altruism costs-the cheap signal from amygdala2014In: Social Cognitive & Affective Neuroscience, ISSN 1749-5016, E-ISSN 1749-5024, Vol. 9, no 9, p. 1325-1332Article in journal (Refereed)

When people state their willingness to pay for something, the amount usually differs from the behavior in a real purchase situation. The discrepancy between a hypothetical answer and the real act is called hypothetical bias. We investigated neural processes of hypothetical bias regarding monetary donations to public goods using fMRI with the hypothesis that amygdala codes for real costs. Real decisions activated amygdala more than hypothetical decisions. This was observed for both accepted and rejected proposals. The more the subjects accepted real donation proposals the greater was the activity in rostral anterior cingulate cortex-a region known to control amygdala but also neural processing of the cost-benefit difference. The presentation of a charitable donation goal evoked an insula activity that predicted the later decision to donate. In conclusion, we have identified the neural mechanisms underlying real donation behavior, compatible with theories on hypothetical bias. Our findings imply that the emotional system has an important role in real decision making as it signals what kind of immediate cost and reward an outcome is associated with.

• 39.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
An empirical study of predicting car type choice in Sweden using cross-validation and feature-selectionManuscript (preprint) (Other academic)
• 40.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics.
KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science.
Model combination for capturing the inconsistency in the aggregate predictionManuscript (preprint) (Other academic)

What is the appropriate aggregation level for modeling when the purpose of modelingis aggregate prediction: is it to estimate a disaggregate model and aggregateindividual predictions or estimate an aggregate model for the aggregate prediction?There is no unique answer to this old question in the literature as well as no generalmethodology to address the problem. In this paper, we propose to tackle theaggregation problem by employing and developing model combination methods tocombine aggregate and disaggregate models. Dierent aspects of aggregation arecovered in this paper: aggregation over time, individuals and alternatives. We examinethe eect of aggregation on the prediction accuracy of a nested multinomiallogit (NMNL). The application of interest is to predict the monthly share of cleancars in the Swedish car eet. We investigate a situation wherein the large scalemodels are already estimated, and we are interested in improving their predictionperformance in a post-processing manner. We combine NMNL with a regressiontree to capture individual heterogeneity as well as a time-series model to capturedynamics of the market share of clean cars at the aggregate level. Models are combinedthrough a latent variable model and a Bayesian model averaging approach.We propose aggregate likelihood as the likelihood to be maximized for the modelselection and combination when the purpose of modeling is aggregate prediction.The results show the increase in the predictive power of combined models.

• 41.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
Prediction-driven approach to model selection using feature selection and nonrandom hold-out validationManuscript (preprint) (Other academic)

In this paper, we address the forecast problem and propose a prediction drivenapproach to model selection. Furthermore, we investigate to what extent dierentprediction questions lead to dierent \best" models. Most of the studies in theeld, take an inference-driven approach to select the best model and project theresults to the future population. In contrast, we take a prediction-driven approachfor both selection criteria and validation sample. We use feature (variable) selectionand nonrandom hold-out validation to select the model with the highest predictiveperformance in an out-of-sample prediction manner. The application of interest iscar type choice modeling using the Swedish car eet data. We introduce two dier-ent types of model selection criteria: maximum likelihood which is the conventionalmethod of model selection, and root mean squared error of the prediction quantityof interest. We compare the best models obtained by dierent criterion functions.The results show that the \best" model for the purpose of prediction depends con-siderably on the prediction question of interest. Moreover, when the objective isto predict a sub-section of a population such as the total share of ethanol cars,maximizing log-likelihood is not the most accurate model selection criterion.

• 42.
Transport Economics Unit, National Road and Transportations Research Institute, Borlänge, Sweden.
KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. Transport Economics Unit, National Road and Transportations Research Institute, Stockholm, Sweden.
The value of commuting time in an empirical on-the-job search model: An application based on moments from two samples2013In: Applied Economics, ISSN 0003-6846, E-ISSN 1466-4283, Vol. 45, no 19, p. 2827-2837Article in journal (Refereed)

This article estimates the Value of Commuting Time (VOCT) among Swedish males in an empirical on-the-job search model. It uses a large sample of employee-establishment linked data obtained from administrative registers. The sample lacks information on mode choice for the journey to work. We therefore estimate a mode choice model on another sample and use this model to link the administrative data to the relevant set of travel times, costs and distances. The VOCT is found to be 1.8 times the net hourly wage rate in the sample. The relatively high estimate results from a high VOCT among cohabiting men.

• 43.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
User benefits & time-geography2012Conference paper (Refereed)
• 44.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis.
Reconciling user benefit and time-geography-based individual accessibility measures2014In: Environment and Planning, B: Planning and Design, ISSN 0265-8135, E-ISSN 1472-3417, Vol. 41, no 6, p. 1031-1043Article in journal (Refereed)

This paper presents a dynamic discrete choice model of activity scheduling that features classic time-geography properties within a microeconomic framework. We present results that show how the model can produce accessibilities that form space-time prisms, while retaining the properties of traditional measures based on consumer surplus in the form of logsums. The main features of the model are that it handles time-space constraints, travel time uncertainty, and endogenous trip chaining in one consistent framework. The resulting accessibility respects the individual's time budget and fixed activities. The dynamic discrete choice framework makes possible estimation of behavioural parameters using well-known methods. Some of the remaining computational challenges are discussed. The final section provides some examples of the policy analysis possibilities provided by a model of this kind.

• 45.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
Tillgänglighet, tidsgeografi och aktiviteter2012Conference paper (Refereed)
• 46.
KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Transport and Location Analysis (closed 20110301).
KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Transport and Location Analysis (closed 20110301).
SCAPES: A dynamic microeconomic model of activity schedulingArticle in journal (Other academic)
• 47.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport and Location Analysis. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
Anxiety and rank dependent scheduling models: probability weighting and an experiment2011Conference paper (Other academic)
• 48.
KTH, School of Architecture and the Built Environment (ABE), Transport Science, System Analysis and Economics.
Appraisal2014In: Handbook of Choice Modelling / [ed] Stephane Hess and Andrew Daly, Edward Elgar Publishing, 2014, p. 601-626Chapter in book (Other academic)
• 49.
KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Transport and Location Analysis (closed 20110301). KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS.
Computational approaches to deal with the curse - applications from transport economics2010Conference paper (Other academic)
• 50.
KTH, School of Architecture and the Built Environment (ABE), Transport and Economics (closed 20110301), Transport and Location Analysis (closed 20110301).
Developing new multivariate generalized extreme value models: Theory and some applications2008In: Transportation Research Part B: Methodological, ISSN 0191-2615, E-ISSN 1879-2367Article in journal (Other academic)
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