A Bayesian network model of consumers’ Kaiyu behaviors. (English) Zbl 1533.91292
Saito, Saburo (ed.) et al., Recent advances in modeling and forecasting Kaiyu. Tools for predicting and verifying the effects of urban revitalization policy. Singapore: Springer. New Front. Reg. Sci., Asian Perspect. 36, 571-599 (2023).
Summary: A consumer walking around a downtown shopping area usually visits several places and shops. From the point of view of city management, it is crucial to know and predict people’s movements in the area, for example, to plan to make better pathways to enhance mobility. From a shop manager’s point of view, it is also vital to grasp the tendency of people visiting other shops to identify whether those shops are competing or cooperating with his/her shop. In order to offer helpful information for these tasks, we used graphical models called Bayesian networks in this research. By applying the models to actual data obtained from questionnaire surveys of consumers who visited a downtown shopping area, we analyzed consumers’ shop-around or Kaiyu behaviors.
For the entire collection see [Zbl 1531.91008].
For the entire collection see [Zbl 1531.91008].
MSC:
| 91B42 | Consumer behavior, demand theory |
| 91B70 | Stochastic models in economics |
| 91B72 | Spatial models in economics |
Software:
BNTReferences:
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