Recent researches have seen an upsurge in the analysis of consumer reviews. Although, several dimensions have been explored, less is known on the temporal dynamics of events that happen over the lifecycle of online products. What are the dominant sales patterns? How are they affected by review count, rating, helpfulness and sentiment? How is trust characterized and what are its effects on sales...

Although syndromic surveillance systems using nonclinical data have been implemented in the United States, the approach has yet to be tested in France. We present the results of the first model based on drug sales that detects the onset of influenza season and forecasts its trend. Using weekly lagged sales of a selected set of medications, we forecast influenzalike illness (ILI) incidence at th...

A method is proposed for obtaining a final list of raw material requirements, which must be available in the warehouse of automotive companies that produce rubber and rubber-metal parts for manufacturing engines, gearboxes, shock absorbers, etc. This method determines the critical materials considering the historical sales records. For each critical item, a distribution model of sales is determ...

We evaluate the performance of an information aggregation mechanism (IAM) implemented inside Intel to forecast unit sales for the company. Developed, refined and tested in the laboratory using experimental methods, the IAM is constructed from institutional features that improve performance and overcome barriers to successful applications of other information aggregation methods. Its implementat...

BACKGROUND The growth in expenditure on orphan medicinal products (OMP) across Europe has been identified as a concern. Estimates of future expenditure in Europe have suggested that OMPs could account for a significant proportion of total pharmaceutical expenditure in some countries, but few of these forecasts have been well validated. This analysis aims to establish a robust forecast of the fu...

This paper studies the relation between activity on Twitter and sales. While research exists into the relation between Tweets and movie and book sales, this paper shows that the same relations do not hold for products that receive less attention on social media. For such products, classification of Tweets is far more important to determine a relation. Also, for such products advanced statistica...

Traditionally, statistical time series methods like moving average (MA), autoregression (AR), or combinations of them are used for forecasting sales. Since these models predict future sales only on the basis of previous sales, they fail in an environment where the sales are more influenced by exogenous variables such as size, price, color, climatic data, effect of media, price changes or campai...

W e present a method for forecasting sales using financial market information and test this method on annual data for US public retailers. Our method is motivated by the permanent income hypothesis in economics, which states that the amount of consumer spending and the mix of spending between discretionary and necessity items depend on the returns achieved on equity portfolios held by consumers...

Forecasting future retail sales is one of the most important activities that form the basis for all strategic and planning decisions in effective operations of retail businesses as well as retail supply chains. This chapter illustrates how to best model and forecast retail sales time series that contain both trend and seasonal variations. The effectiveness of data preprocessing such as detrendi...