DocumentCode :
633972
Title :
A Novel Use of Big Data Analytics for Service Innovation Harvesting
Author :
Ghose, Aditya K. ; Morrison, Evan ; Yingzhi Gou
Author_Institution :
Decision Syst. Lab., Univ. of Wollongong, Wollongong, NSW, Australia
fYear :
2013
fDate :
29-31 May 2013
Firstpage :
208
Lastpage :
214
Abstract :
Service innovation has assumed considerable significance with the growth of the services sectors of economies globally, yet progress has been slow in devising carefully formulated, systematic techniques to under pin service innovation. This paper argues that a novel approach to big data analytics offers interesting solutions in this space. The paper argues that the use of big data analytics for generating enterprise service insights is often ignored (while the extraction of insights about customers, the market and the enterprise context has received considerable attention). The paper offers a set of techniques (collectively referred to as innovation harvesting) which leverage big data in various forms, including object state sensor data, behaviour logs as well large-scale sources of open data such as the web to mine service innovation insights. The paper also outlines how systematic search might help overcome the limitations of big data analytics in this space.
Keywords :
customer services; data analysis; data mining; innovation management; behaviour logs; big data analytics; enterprise service insights generation; innovation harvesting technique; object state sensor data; service innovation harvesting; service innovation insights mining; services sector; systematic search; Analytical models; Data handling; Information management; Semantics; Technological innovation; Unified modeling language;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Service Science and Innovation (ICSSI), 2013 Fifth International Conference on
Conference_Location :
Kaohsiung
Type :
conf
DOI :
10.1109/ICSSI.2013.45
Filename :
6599387
Link To Document :
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