This paper deals with inferring key parameters on marketing response at a true high frequency while data are partly or fully available only at a lower frequency aggregate levels. The familiar Koyck model turns out to be very useful for this purpose. Assuming this model for the high-frequency data makes it possible to infer the high-frequency parameters from modified Koyck type models when lower frequency data are available. This means that inference using the Koyck model is robust to temporal aggregation
Consumer preferences are changing over time. In this dissertation, we provide three studies regardin...
Good marketing decisions require managers ' understanding of the nature of the market-response ...
Earlier research on the effects of nonoverlapping temporal aggregation on demand forecasting showed ...
The geometric distributed lag model, after application of the so-called Koyck transformation, is oft...
textabstractThe geometric distributed lag model, after application of the so-called Koyck transforma...
Abstract: Differences in estimated parameters depending on the frequency of aggregate data have bee...
Demand forecasting is central to decision making and operations in organisations. As the volume of f...
Recent advances have demonstrated the benefits of temporal aggregation for demand forecasting, inclu...
Demand forecasting is central to decision making and operations in organisations. As the volume of f...
Good marketing decisions require managers' understanding of the nature of the market-response functi...
Temporal demand aggregation has been shown in the academic literature to be an intuitively appealing...
Demand forecasting performance is subject to the uncertainty underlying the time series an organizat...
textabstractIn this paper we put forward a duration model to analyze the dynamic effects of marketin...
In this paper we present a mechanism to elicit and aggregate dispersed information. Our mechanism re...
This paper examines the quantitative importance of temporal aggregation bias in distorting parameter...
Consumer preferences are changing over time. In this dissertation, we provide three studies regardin...
Good marketing decisions require managers ' understanding of the nature of the market-response ...
Earlier research on the effects of nonoverlapping temporal aggregation on demand forecasting showed ...
The geometric distributed lag model, after application of the so-called Koyck transformation, is oft...
textabstractThe geometric distributed lag model, after application of the so-called Koyck transforma...
Abstract: Differences in estimated parameters depending on the frequency of aggregate data have bee...
Demand forecasting is central to decision making and operations in organisations. As the volume of f...
Recent advances have demonstrated the benefits of temporal aggregation for demand forecasting, inclu...
Demand forecasting is central to decision making and operations in organisations. As the volume of f...
Good marketing decisions require managers' understanding of the nature of the market-response functi...
Temporal demand aggregation has been shown in the academic literature to be an intuitively appealing...
Demand forecasting performance is subject to the uncertainty underlying the time series an organizat...
textabstractIn this paper we put forward a duration model to analyze the dynamic effects of marketin...
In this paper we present a mechanism to elicit and aggregate dispersed information. Our mechanism re...
This paper examines the quantitative importance of temporal aggregation bias in distorting parameter...
Consumer preferences are changing over time. In this dissertation, we provide three studies regardin...
Good marketing decisions require managers ' understanding of the nature of the market-response ...
Earlier research on the effects of nonoverlapping temporal aggregation on demand forecasting showed ...