In this paper, we analyze the performance of weather-conditional rebates by explicitly considering the impact of different risk behaviors.
First, we study the case in which the retailer and customers are risk-neutral and show that the weather-conditional rebates are effective in increasing the retailer's profits.
Furthermore, by combining the rebate program with a financial instrument such as binary weather options, the retailer can obtain greater benefits from weather-conditional rebates.
Specifically, weather-conditional rebates are incentives offered in an advance promotional period to be paid to the early buyers if the weather state in the regular season is unfavorable.
The time n represents a step of the process, and the conditional probability distribution for the process at the next step depends only on the current state.An example is given by Fig. 2, where the probabilities of weather conditions (modeled as either sunny (state 1) or rainy (state 2)) on next day is given by the weather on the current day.
Starting from reliable and high quality registered meteorological data of daily temperatures, rain and snow precipitations at nine Italian weather stations, conditional probability functions of occurrence of snow precipitation, accumulation and melting have been preliminarily determined as functions of daily maximum and minimum air temperatures.
The weather generator is also adapted to conditional simulation based on seasonal forecasts involving modification of the third component.
(The conditional is a condition.
In the final conditional logistic regression models, the weather variables were treated as confounders.
Sprinkler BN is a binary network that shows the conditional probability distributions for the events of the weather being cloudy, raining, grass being wet and the sprinkler being on.
The analysis was conducted for the hospitalization data and for the mortality data for each community separately, and we applied a conditional logistic regression controlling for day of the week and weather.
