Abstract: A demand prediction device derives a first exponential function representing the time-series transition of the number of bookings until a service provision time point for a first customer group based on booking transitions up to a first time point t1. A second exponential function is similarly derived for a second customer group based on booking transitions up to a second time point t2 different from t1. The device generates information supporting a service provider based on the predicted time-series transitions for the first and second customer groups. A time constant is compared with at least one threshold value to determine a system response, which triggers an adjustment to one or more operational parameters, including modifying inventory levels, adjusting reservation or scheduling limits, reallocating staffing or system resources, or updating pricing or promotional parameters. This enables dynamic demand prediction and responsive operational optimization for service provision.

Abstract: A demand prediction device derives a first exponential function indicating the time-series transition of the number of bookings until a service provision time point for a first customer group based on the transition of the number of bookings until a time point t1 for the first group. A demand prediction device derives a second exponential function indicating the time-series transition of the number of bookings until a service provision time point for a second customer group based on the transition of the number of bookings until a time point t2 for the second customer group different from the first group. The demand prediction device generates information supporting a service providing entity based on the time-series transition of the number of bookings until an analysis target time point for the first customer group indicated by the first exponential function and that for the second customer group by the second exponential function.