Title :
Big data technologies in support of real time capturing and understanding of electric vehicle customers dynamics
Author :
Qiu, Robin G. ; Wang, Kangping ; Shan Li ; Jin Dong ; Ming Xie
Author_Institution :
Div. of Eng., Pennsylvania State Univ., University Park, PA, USA
Abstract :
Energy overconsumption and greenhouse gas emission have been contributing to air pollutions and the global warming for years. The unceasingly increasing number of fossil fuels based vehicles around the world is considered as one of main factors making to the situation worse year by year. Electric vehicles (EV) are promoted as a viable and promising alternative transportation means for customers. However, there is an array of issues hindering EVs from the fast adoption in the global auto market. As these issues bear different priorities that surely vary with marketplaces, it becomes essential for EV makers and governments to capture and understand the dynamics of EV consumers in real time. This paper explores how the emerging big data technologies can be applied to facilitate the process of deciphering the acceptance and behavior of EV customers from marketplace to marketplace. A data-collecting web system is discussed. IBM BigInsights platform technologies, including Hadoop, Streams, SPSS modeler and text analytics, are utilized for looking into the insights of collected data. Examples are provided to show the promising future of big data technologies in the field of customer analytics in today´s globalized economy.
Keywords :
Big Data; consumer behaviour; data acquisition; electric vehicles; real-time systems; Big Data technologies; EV consumers dynamics; EV customers acceptance; EV customers behavior; EV makers; Hadoop; IBM BigInsights platform technologies; SPSS modeler; Streams; air pollutions; alternative transportation means; customer analytics; data-collecting Web system; electric vehicle customers dynamics; energy overconsumption; fossil fuels based vehicles; global auto market; global warming; globalized economy; governments; greenhouse gas emission; marketplaces; real time capturing; text analytic; Analytical models; Batteries; Big data; Cities and towns; Government; Real-time systems; Vehicles; Electric vehicles; InfoSphere BigInsights; big data technologies; customer behavior; customer dyanmics; incentives; policies;
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-3278-8
DOI :
10.1109/ICSESS.2014.6933559