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A novel use of big data analytics for service innovation harvesting

Conference Paper


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 {\em 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.

UOW Authors


  •   Gou, Yingzhi (external author)
  •   Ghose, Aditya
  •   Morrison, Evan (external author)

Publication Date


  • 2013

Citation


  • Ghose, A. K., Morrison, E. & Gou, Y. (2013). A novel use of big data analytics for service innovation harvesting. Proceedings - 2013 5th International Conference on Service Science and Innovation, ICSSI 2013 (pp. 208-214). United States: IEEE Computer Society.

Scopus Eid


  • 2-s2.0-84890720858

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1935

Start Page


  • 208

End Page


  • 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 {\em 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.

UOW Authors


  •   Gou, Yingzhi (external author)
  •   Ghose, Aditya
  •   Morrison, Evan (external author)

Publication Date


  • 2013

Citation


  • Ghose, A. K., Morrison, E. & Gou, Y. (2013). A novel use of big data analytics for service innovation harvesting. Proceedings - 2013 5th International Conference on Service Science and Innovation, ICSSI 2013 (pp. 208-214). United States: IEEE Computer Society.

Scopus Eid


  • 2-s2.0-84890720858

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/1935

Start Page


  • 208

End Page


  • 214