On Developing a More Comprehensive Decision-Making Architecture for Empirical Social Research: Agent-Based Simulation of Mobility Demands in Switzerland

Nguyen, Khoa; Schumann, René

doi:10.1007/978-3-030-60843-9_4

Cited by 8 publications

(19 citation statements)

References 20 publications

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“…In the first, we describe an AB simulation platform called Behavior Driven Demand Model (BedDeM) that we configured to build a specific model. The platform building process is discussed in Nguyen and Schumann (2019). 6 and a use case is addressed in Bektas et al (2018) and Bektas and Schumann (2019b).…”

Section: Case Studymentioning

confidence: 99%

“…These theories state that individual's intention to act is the key determinant of behavior (Bektas et al 2018). There are several AB models and platforms they attempted to incorporate these theories (Nguyen and Schumann 2019).…”

Section: Agent's Decision-making Mechanismmentioning

confidence: 99%

“…As Nguyen and Schumann (2019) state, TIB includes all aspects of TRA and TPB, as well as additional components such as habits that potentially improve its predictive power and descriptive accuracy. Although there is no proof which theory is more suited to build an AB platform, TIB was chosen for the BedDeM platform, since it provides a more comprehensive understanding of the origins of individual behavior.…”

Section: Agent's Decision-making Mechanismmentioning

confidence: 99%

“…According to the configuration, he can choose the first best option deterministically in the list, or certain probabilities can be created over the scores; thus, he can choose an option stochastically. More detailed information regarding the platform and its decision-making mechanism can be found in Nguyen and Schumann (2019).…”

Section: Agent's Decision-making Mechanismmentioning

confidence: 99%

“…The method is discussed in the next section in detail. To apply the method as a case study, we build an AB model through configuring an AB simulation platform called Behavior Driven Demand Model (BedDeM) (Nguyen and Schumann 2019). The model and its features are explained in "Case study" thoroughly.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A meso-level empirical validation approach for agent-based computational economic models drawing on micro-data: a use case with a mobility mode-choice model

2021

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The complex nature of agent-based modeling may reveal more descriptive accuracy than analytical tractability. That leads to an additional layer of methodological issues regarding empirical validation, which is an ongoing challenge. This paper offers a replicable method to empirically validate agent-based models, a specific indicator of “goodness-of-validation” and its statistical distribution, leading to a statistical test in some way comparable to the p value. The method involves an unsupervised machine learning algorithm hinging on cluster analysis. It clusters the ex-post behavior of real and artificial individuals to create meso-level behavioral patterns. By comparing the balanced composition of real and artificial agents among clusters, it produces a validation score in [0, 1] which can be judged thanks to its statistical distribution. In synthesis, it is argued that an agent-based model can be initialized at the micro-level, calibrated at the macro-level, and validated at the meso-level with the same data set. As a case study, we build and use a mobility mode-choice model by configuring an agent-based simulation platform called BedDeM. We cluster the choice behavior of real and artificial individuals with the same ex-ante given characteristics. We analyze these clusters’ similarity to understand whether the model-generated data contain observationally equivalent behavioral patterns as the real data. The model is validated with a specific score of 0.27, which is better than about 95% of all possible scores that the indicator can produce. By drawing lessons from this example, we provide advice for researchers to validate their models if they have access to micro-data.

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Section: Case Studymentioning

confidence: 99%

Section: Agent's Decision-making Mechanismmentioning

confidence: 99%

Section: Agent's Decision-making Mechanismmentioning

confidence: 99%

Section: Agent's Decision-making Mechanismmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A meso-level empirical validation approach for agent-based computational economic models drawing on micro-data: a use case with a mobility mode-choice model

2021

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Using Mobility Profiles for Synthetic Population Generation

Bektas

Schumann

2021

Springer Proceedings in Complexity

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An Exploratory Comparison of Behavioural Determinants in Mobility Modal Choices

Nguyen

Schumann

2021

Springer Proceedings in Complexity

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The rising demand for mobility in the 21st century creates a challenge for interdisciplinary researchers. As a result, the number of papers devoted to the application of agent-based technologies in the transportation engineering domain has grown enormously. However, there is still a need for modelling platforms that are capable of exploring the influence of different psychological factors on individual decision-making. By utilising our current mobility simulator -BedDeM, we propose an experimental method to test and investigate the impact of core determinants in Triandis' Theory of Interpersonal Behaviour on the usage of different transportation modes. Comparing the results with a calibrated population of Swiss household data, we conclude that Intention and Affect have a positive effect on the usage of private vehicles, while Habit and Social factors can encourage people to travel with public or soft transportation modes.

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On Developing a More Comprehensive Decision-Making Architecture for Empirical Social Research: Agent-Based Simulation of Mobility Demands in Switzerland

Cited by 8 publications

References 20 publications

A meso-level empirical validation approach for agent-based computational economic models drawing on micro-data: a use case with a mobility mode-choice model

A meso-level empirical validation approach for agent-based computational economic models drawing on micro-data: a use case with a mobility mode-choice model

Using Mobility Profiles for Synthetic Population Generation

An Exploratory Comparison of Behavioural Determinants in Mobility Modal Choices

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