Searched for: author%3A%22van+Cranenburgh%2C+S.%22
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van Cranenburgh, S. (author), Meyerhoff, Jürgen (author), Rehdanz, Katrin (author), Wunsch, Andrea (author)
Efficient experimental designs aim to maximise the information obtained from stated choice data to estimate discrete choice models' parameters statistically efficiently. Almost without exception efficient experimental designs assume that decision-makers use a Random Utility Maximisation (RUM) decision rule. When using such designs,...
journal article 2024
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Garrido Valenzuela, F.O. (author), Cats, O. (author), van Cranenburgh, S. (author)
A thorough understanding of how urban space characteristics, such as urban equipment or network topology, affect people's density in urban spaces is essential to well-informed urban policy making. Hitherto, studies have primarily examined how the characteristics of the urban space impacts the number of people visiting different parts of the...
journal article 2023
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Hernández, J.I. (author), van Cranenburgh, S. (author), Chorus, C.G. (author), Mouter, N. (author)
We propose three procedures based on association rules (AR) learning and random forests (RF) to support the specification of a portfolio choice model applied in data from complex choice experiment data, specifically a Participatory Value Evaluation (PVE) choice experiment. In a PVE choice experiment, respondents choose a combination of...
journal article 2023
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Spierenburg, L.J. (author), van Cranenburgh, S. (author), Cats, O. (author)
This paper proposes a method to characterize residential segregation patterns along three dimensions: intensity, separation, and scale. These dimensions designate respectively the over-representation of a group in segregated regions, the proportion of people from that group living in these regions, and the spatial extent of these regions. We...
journal article 2023
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Szép, T. (author), van Cranenburgh, S. (author), Chorus, C.G. (author)
This paper proposes a new method to combine choice- and text data to infer moral motivations from people’s actions. To do this, we rely on moral rhetoric, in other words, extracting moral values from verbal expressions with Natural Language Processing techniques. We use moral rhetoric based on a well-established moral, psychological theory...
journal article 2023
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Hernández, J.I. (author), van Cranenburgh, S. (author)
Two-attribute-two-alternative stated choice experiments are widely used to infer the Value-of-Travel-Time (VTT) distribution. Two-attribute-two-alternative stated choice experiments have the advantage that their data can be analysed using nonparametric models, which allow for the inference of the VTT distribution without having to impose...
journal article 2023
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Liebe, Ulf (author), van Cranenburgh, S. (author), Chorus, C.G. (author)
Empirical studies on individual behaviour often, implicitly or explicitly, assume a single type of decision rule. Other studies do not specify behavioural assumptions at all. We advance sociological research by introducing (random) regret minimization, which is related to loss aversion, into the sociological literature and by testing it against ...
journal article 2023
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Jiao, Y. (author), Calvert, S.C. (author), van Cranenburgh, S. (author), van Lint, J.W.C. (author)
This study presents a new method to infer the average two-dimensional (2D) spacing between interacting vehicles in urban traffic from trajectory data. In this context, 2D spacing reflects the amount of road space consumed by pairs of interacting vehicles, and is related to 2D density at the macroscopic level. Due to complex interaction and...
journal article 2023
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van Cranenburgh, S. (author), Wang, Shenhao (author), Vij, Akshay (author), Pereira, Francisco (author), Walker, Joan (author)
Since its inception, the choice modelling field has been dominated by theory-driven modelling approaches. Machine learning offers an alternative data-driven approach for modelling choice behaviour and is increasingly drawing interest in our field. Cross-pollination of machine learning models, techniques and practices could help overcome problems...
journal article 2022
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Shelat, S. (author), Cats, O. (author), van Cranenburgh, S. (author)
With a few exceptions, public transport ridership around the world has been hit hard by the COVID-19 pandemic. Travellers are now likely to adapt their behaviour with a focus on factors that contribute to the risk of COVID-19 transmission. Given the unprecedented spatial and temporal scale of this crisis, these changes in behaviour may even...
journal article 2022
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Delfos, J. (author), Zuiderwijk-van Eijk, A.M.G. (author), van Cranenburgh, S. (author), Chorus, C.G. (author)
As the application of machine learning (ML) algorithms becomes more widespread, governmental organisations try to benefit from this technology. While ML has the potential to support public services, its application also introduces challenges. Several scholars have described the possible opportunities and challenges of ML applications in the...
conference paper 2022
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Szép, T. (author), van Cranenburgh, S. (author), Chorus, C.G. (author)
We examine identifiability and distinguishability in Decision Field Theory (DFT) models and highlight pitfalls and how to avoid them. In the past literature, the models’ parameters have been put forward as being able to capture the psychological processes in a decision maker's mind during deliberation. DFT models have been widely used to analyse...
journal article 2022
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Itten, A.V. (author), van Cranenburgh, S. (author)
Conspiracy theories on climate change and the energy transition have found a stronghold on the Internet. Many online discussions are dominated by a few users with extreme beliefs, such as attributing secret agendas to powerful elites, governments not telling the truth, or sinister intentions of activists and lobbyists. As such beliefs largely...
report 2021
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Geržinič, N. (author), van Cranenburgh, S. (author), Cats, O. (author), Lancsar, Emily (author), Chorus, C.G. (author)
Since the introduction of Discrete Choice Analysis, countless efforts have been made to enhance the efficiency of data collection through choice experiments and to improve the behavioural realism of choice models. One example development in data collection are best-worst discrete choice experiments (BWDCE), which have the benefit of obtaining...
journal article 2021
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Chorus, C.G. (author), van Cranenburgh, S. (author), Daniel, A.M. (author), Sandorf, Erlend Dancke (author), Sobhani, Anae (author), Szép, T. (author)
Theories of decision-making are routinely based on the notion that decision-makers choose alternatives which align with their underlying preferences—and hence that their preferences can be inferred from their choices. In some situations, however, a decision-maker may wish to hide his or her preferences from an onlooker. This paper argues that...
journal article 2021
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Alwosheel, A.S.A. (author), van Cranenburgh, S. (author), Chorus, C.G. (author)
Artificial Neural Networks (ANNs) are rapidly gaining popularity in transportation research in general and travel demand analysis in particular. While ANNs typically outperform conventional methods in terms of predictive performance, they suffer from limited explainability. That is, it is very difficult to assess whether or not particular...
journal article 2021
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Pudane, B. (author), van Cranenburgh, S. (author), Chorus, C.G. (author)
Fully Automated Vehicles (AVs) have been widely expected to revolutionise the future travel experience. Recent studies have shown that their impact may also reach beyond the travel episode, and lead their users to alter other activities performed during the day – their daily lifestyles. This study is among the first to empirically investigate...
journal article 2021
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Huang, B. (author), van Cranenburgh, S. (author), Chorus, C.G. (author)
Although Automated vehicles (AVs) are expected to have a major and positive effect on road safety, recent accidents caused by AVs tend to generate a powerful negative impact on the public opinion regarding safety aspects of AVs. Triggered by such incidents, many experts and policy makers now believe that paradoxically, safety perceptions may...
journal article 2020
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van Cranenburgh, S. (author), Kouwenhoven, M.L.A. (author)
This study proposes a novel Artificial Neural Network (ANN) based method to derive the Value-of-Travel-Time (VTT) distribution. The strength of this method is that it is possible to uncover the VTT distribution (and its moments) without making assumptions about the shape of the distribution or the error terms, while being able to incorporate...
journal article 2020
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Alwosheel, A.S.A. (author), van Cranenburgh, S. (author), Chorus, C.G. (author)
Artificial Neural Networks (ANNs) are increasingly used for discrete choice analysis, being appreciated in particular for their strong predictive power. However, many choice modellers are critical – and rightfully so – about using ANNs, for the reason that they are hard to diagnose. That is, for analysts it is hard to see whether a trained ...
journal article 2019
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