| Is your dataset big enough? Sample size requirements when using artificial neural networks for discrete choice analysis A Alwosheel, S van Cranenburgh, CG Chorus Journal of choice modelling 28, 167-182, 2018 | 292 | 2018 |
| On the impact of vehicle automation on the value of travel time while performing work and leisure activities in a car: Theoretical insights and results from a stated preference … GH de Almeida Correia, E Looff, S van Cranenburgh, M Snelder, ... Transportation Research Part A: Policy and Practice 119, 359-382, 2019 | 168 | 2019 |
| New insights on random regret minimization models S van Cranenburgh, CA Guevara, CG Chorus Transportation Research Part A: Policy and Practice 74, 91-109, 2015 | 127 | 2015 |
| Random regret minimization for consumer choice modeling: Assessment of empirical evidence C Chorus, S van Cranenburgh, T Dekker Journal of Business Research 67 (11), 2428-2436, 2014 | 101 | 2014 |
| How will automated vehicles shape users’ daily activities? Insights from focus groups with commuters in the Netherlands B Pudāne, M Rataj, EJE Molin, N Mouter, S van Cranenburgh, CG Chorus Transportation Research Part D: Transport and Environment 71, 222-235, 2019 | 100 | 2019 |
| Choice modelling in the age of machine learning-discussion paper S van Cranenburgh, S Wang, A Vij, F Pereira, J Walker Journal of Choice Modelling 42, 100340, 2022 | 70* | 2022 |
| An artificial neural network based approach to investigate travellers’ decision rules S van Cranenburgh, A Alwosheel Transportation Research Part C: Emerging Technologies 98, 152-166, 2019 | 69 | 2019 |
| Vacation behaviour under high travel cost conditions–A stated preference of revealed preference approach S Van Cranenburgh, CG Chorus, B van Wee Tourism Management 43, 105-118, 2014 | 56 | 2014 |
| Do individuals have different preferences as consumer and citizen? The trade-off between travel time and safety N Mouter, S Van Cranenburgh, B Van Wee Transportation research part A: policy and practice 106, 333-349, 2017 | 52 | 2017 |
| An empirical assessment of Dutch citizens' preferences for spatial equality in the context of a national transport investment plan N Mouter, S van Cranenburgh, B van Wee Journal of Transport Geography 60, 217-230, 2017 | 43 | 2017 |
| Traveller behaviour in public transport in the early stages of the COVID-19 pandemic in the Netherlands S Shelat, O Cats, S van Cranenburgh Transportation Research Part A: Policy and Practice 159, 357-371, 2022 | 36 | 2022 |
| The consumer-citizen duality: Ten reasons why citizens prefer safety and drivers desire speed N Mouter, S Van Cranenburgh, B Van Wee Accident Analysis & Prevention 121, 53-63, 2018 | 32 | 2018 |
| Potential changes in value of travel time as a result of vehicle automation: a case study in the Netherlands E De Looff, GHA Correia, S van Cranenburgh, M Snelder, B van Arem 97th Annual Meeting of the Transportation Research Board, 7-11, 2018 | 25 | 2018 |
| Why did you predict that? Towards explainable artificial neural networks for travel demand analysis A Alwosheel, S van Cranenburgh, CG Chorus Transportation Research Part C: Emerging Technologies 128, 103143, 2021 | 23 | 2021 |
| Revealing transition patterns between mono-and multimodal travel patterns over time: A mover-stayer model M Kroesen, S van Cranenburgh European Journal of Transport and Infrastructure Research 16 (4), 2016 | 20 | 2016 |
| On the robustness of random regret minimization modelling outcomes towards omitted attributes S Van Cranenburgh, CG Prato Journal of choice modelling 18, 51-70, 2016 | 20 | 2016 |
| Substantial changes and their impact on mobility: a typology and an overview of the literature S Van Cranenburgh, C Chorus, B Van Wee Transport Reviews 32 (5), 569-597, 2012 | 20 | 2012 |
| On the robustness of efficient experimental designs towards the underlying decision rule S van Cranenburgh, JM Rose, CG Chorus Transportation Research Part A: Policy and Practice 109, 50-64, 2018 | 17 | 2018 |
| ‘Computer says no’is not enough: Using prototypical examples to diagnose artificial neural networks for discrete choice analysis A Alwosheel, S Van Cranenburgh, CG Chorus Journal of choice modelling 33, 100186, 2019 | 15 | 2019 |
| An artificial neural network based method to uncover the value-of-travel-time distribution S van Cranenburgh, M Kouwenhoven Transportation 48, 2545-2583, 2021 | 14 | 2021 |
Niek MouterAssociate professor Delft University of TechnologyVerified email at tudelft.nl
