Constructing a 7-day Ahead Forecast Model for Grass Pollen at North London, United Kingdom

A number of media outlets now issue medium-range (~7 day) weather forecasts on a regular basis. It is therefore logical that aerobiologists should attempt to produce medium-range forecasts for allergenic pollen that cover the same time period as the weather forecasts. The objective of this study is to construct a medium-range (< 7 day) forecast model for grass pollen at north London. The forecast models were produced using regression analysis based on grass pollen and meteorological data from 1990-1999 and tested on data from 2000 and 2002. The modelling process was improved by dividing the grass pollen season into three periods; the pre-peak, peak and post peak periods of grass pollen release. The forecast consisted of five regression models. Two simple linear regression models predicting the start and end date of the peak period, and three multiple regression models forecasting daily average grass pollen counts in the pre-peak, peak and post-peak periods. Overall the forecast models achieved 62% accuracy in 2000 and 47% in 2002, reflecting the fact that the 2002 grass pollen season was of a higher magnitude than any of the other seasons included in the analysis. This study has the potential to make a notable contribution to the field of aerobiology. Winter averages of the North Atlantic Oscillation were used to predict certain characteristics of the grass pollen season, which presents an important advance in aerobiological work. The ability to predict allergenic pollen counts for a period between five and seven days will benefit allergy sufferers. Furthermore, medium-range forecasts for allergenic pollen will be of assistance to the medical profession, including allergists planning treatment and physicians scheduling clinical trials.

Choosing the Right Promotional Tool in the Hotel Industry: The Case of the Chinese Consumer.

The rapid growth of the Chinese tourism has stimulated competition within tourism-related industries, such as the hospitality industry. The purpose of this study is to examine the Chinese consumer reaction to different promotional tools used by hotels in China and, thus, to provide a deeper understanding for marketers of how to use sales promotion effectively to generate appropriate consumer responses. An experimental survey was administered yielding a total sample of 319 Chinese customers, who were probed using different types of sales promotion tools. Data analysis indicates that bonus packs (e.g. a 3-night stay at a hotel for the price of 2) induced the highest consumer perceived value, brand switching, and purchase acceleration intention, whereas price discounts resulted in the highest intention to spend more. Although this study has its limitations given its reliance on a convenience sample, it offers insightful practical implications for hotel business owners in Asia regarding targeting the right customers with the right promotional tools, where it is proposed that bonus packs successfully attract new Chinese customers and price discounts support in generating more sales.