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Full-Text Articles in Physical Sciences and Mathematics
Consumer Driven Innovation Management, Arcot Desai Narasimhalu, Shekhar Mitra
Consumer Driven Innovation Management, Arcot Desai Narasimhalu, Shekhar Mitra
Arcot Desai NARASIMHALU
The evolution of human society leads to increased affluence and prosperity of certain populations, sometimes at the expense of well-established markets. Market leaders in products and services tend to be so focused on their current customer base that they are caught off guard with the changes in markets created by the evolution. These changes often go unnoticed until it is too late. The change in customer base often requires the repositioning of products and services through innovations, which address new and emerging markets. Some of these changes could potentially result in tectonic market shifts that force innovation managers to involve …
Wie Featured Person Of The Month Highlights (Katina Michael), Keyana Tenant, Katina Michael
Wie Featured Person Of The Month Highlights (Katina Michael), Keyana Tenant, Katina Michael
Professor Katina Michael
The WIE Featured Person of the Month is Katina Michael, editor-in-chief of IEEE Technology and Society Magazine. After working at OTIS Elevator Company and Andersen Consulting, Katina was offered and exciting graduate engineering position at Nortel in 1996; and her career has been fast track from there. Read Katina’s story on Page 7.
A Comparison Of Periodic Autoregressive And Dynamic Factor Models In Intraday Energy Demand Forecasting, Thomas Mestekemper, Goeran Kauermann, Michael Smith
A Comparison Of Periodic Autoregressive And Dynamic Factor Models In Intraday Energy Demand Forecasting, Thomas Mestekemper, Goeran Kauermann, Michael Smith
Michael Stanley Smith
We suggest a new approach for forecasting energy demand at an intraday resolution. Demand in each intraday period is modeled using semiparametric regression smoothing to account for calendar and weather components. Residual serial dependence is captured by one of two multivariate stationary time series models, with dimension equal to the number of intraday periods. These are a periodic autoregression and a dynamic factor model. We show the benefits of our approach in the forecasting of district heating demand in a steam network in Germany and aggregate electricity demand in the state of Victoria, Australia. In both studies, accounting for weather …
Constructing And Evaluating An Autoregressive House Price Index, Chaitra Nagaraja, Lawrence Brown
Constructing And Evaluating An Autoregressive House Price Index, Chaitra Nagaraja, Lawrence Brown
Chaitra H Nagaraja
No abstract provided.