Abstract
Customer movements in large tourism industries (such as public transport systems, attraction parks or ski resorts) can be understood as business processes. Their processes describe the flow of persons through the networked systems, while Information Systems log the different steps. The prediction of how large numbers of customers will behave in the near future is a complex and yet unsolved challenge. However, the possible business benefits of predictive analytics in the tourism industry are manifold. We propose to approach this task with the yet unexploited appli-cation of predictive process mining. In a prototypical use case, we work together with two major European ski resorts. We implement a predictive process mining algorithm towards the goal of predicting near future lift arrivals of skiers within the ski resort in real-time. Furthermore, we present the results of our prototypical implementation and draw conclusions for future research in the area.
Recommended Citation
Brunk, Jens; Riehle, Dennis M.; and Delfmann, Patrick, "Prediction of Customer Movements in Large Tourism Industries by the Means of Process Mining" (2018). Research Papers. 40.
https://aisel.aisnet.org/ecis2018_rp/40