Search results for "time series."
showing 3 items of 243 documents
Qualitative analysis of housing demand using Google trends data
2019
Big data analytics often refer to the breakdown of huge amounts of data into a more readable and useful format. This study utilises Google Trends big data as a proxy for an analysis of housing demand. We employ a qualitative method (fuzzy set/Qualitative Comparative Analysis, fsQCA), instead of a quantitative method, for our estimate and forecast. The empirical results show that fsQCA successfully forecasts seasonal time series, even though the dataset is small in size. Our findings fill the gap in the qualitative and time series forecasting literature, and the forecasting procedure herein also offers a good standard for industry.
Identifying the Sales Patterns of Online Stores with Time Series Clustering
2018
Electronic commerce, especially in the business-to-consumer (B2C) context, has for years been a popular research topic in information systems (IS). However, the prior research on the topic has traditionally been dominated by the consumer focus instead of the business focus of online stores. For example, whereas various segmentations exist for online consumers based on their purchase behaviour, no such segmentations have been developed for online stores based on their sales patterns. In this study, our objective is to address this gap in prior research by identifying the most typical sales patterns of online stores operating in the B2C context. By using self-organising maps (SOM) to analyse …
Univariate and multivariate properties of wind velocity time series
2009
We analyze the time series of hourly average wind speeds measured at 29 different stations located in Sicily, a region with a complex morphology. The investigation, performed from the univariate as well as the multivariate point of view, evidences that the statistical properties of wind at the single sites have features that are not reproduced by standard models and, thus, require specific modeling. Moreover, the synchronous evolution of wind velocity presents a cluster structure, obtained with different algorithms, that persists in the standard deviation too.