Hankammer, Stephan; Jiang, Ruth; Kleer, Robin (2016)
Mass Customization (MC) has become a major trend in the consumer goods market in recent years. However, it is still unclear if MC goods have a positive impact on the environment due to the many influencing factors in comparison to mass produced goods. With Google’s “Project Ara”, a modular and customizable smartphone approach is very likely to reach market maturity and its economic, social and ecologic impacts are still unclear. Using a qualitative case study approach, we shed light on its potential economic success. Furthermore, we use the two theoretical concepts of Eco Innovation (EI) and Systemic Innovation (SI) to assess Google Ara’s potential to lead to changes in terms of ecologic and social concerns.
In our analysis, we show that Project Ara has the potential to outperform its competitors of modular smartphones. We work out that Google’s modular approach could lead to a longer useful life of smartphones – or at least for some components. Finally, we affirm Project Ara’s general potential for being an SI. Even though Project Ara will very likely not change the complete smartphone market and the behavior of the involved actors, there is a potential for influencing sociocultural behavior in the long tail of the smartphone market.
This article discusses the financial perspective in a case study at ICTRA that deals with improving ICT service delivery. It outlines the three-step approach taken in the Finance Transformation Project and explains how this approach helped ICTRA in becoming a more business-oriented ICT shared service centre.
Poelmans, Jonas; Elzinga, Paul; Viaene, Stijn; Dedene, Guido (+); Kuznetsov, Sergei O. (2011)
Formal Concept Analysis (FCA) is an unsupervised clustering technique and many scientific papers are devoted to applying FCA in Information Retrieval (IR) research. We collected 103 papers published between 2003-2009 which mention FCA and information retrieval in the abstract, title or keywords. Using a prototype of our FCA-based toolset CORDIET, we converted the pdf-files containing the papers to plain text, indexed them with Lucene using a thesaurus containing terms related to FCA research and then created the concept lattice shown in this paper. We visualized, analyzed and explored the literature with concept lattices and discovered multiple interesting research streams in IR of which we give an extensive overview. The core contributions of this paper are the innovative application of FCA to the text mining of scientific papers and the survey of the FCA-based IR research.
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