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