Business & Information Systems Engineering

, Volume 59, Issue 2, pp 125–130 | Cite as

Quantified Vehicles

Novel Services for Vehicle Lifecycle Data
  • Alexander StockerEmail author
  • Christian Kaiser
  • Michael Fellmann

From Quantified Self to Quantified Vehicles

Three trends have shown significant impact in recent years: (1) The Internet of Things (Wortmann and Flüchter 2015) has become an enabler for a connected world full of smart objects equipped with sensors and supplies enormous and still rising amounts of (2) Big Data (Schönberger and Cukier 2013), which can be analyzed and then turned into business value in various areas, including (3) the Quantified Self movement as a popular example for everyday life big data analytics (Swan 2009). On a more abstract level, capturing real world events and digitizing them into machine-readable data to satisfy needs or assist humans and machines in decision making, evaluation and comparison of physical world events has become increasingly important. Even a new branch of business has emerged through such big data analytics for data-driven innovations, while information overload has wiped off its negative image and has become the beautiful bride everybody wants...


Quantified Vehicles Quantified-self Services Business models Vehicle lifecycle data 



This study has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 732189. The document reflects only the authors' views and the Commission is not responsible for any use that may be made of information contained herein.


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Copyright information

© Springer Fachmedien Wiesbaden 2017

Authors and Affiliations

  • Alexander Stocker
    • 1
    Email author
  • Christian Kaiser
    • 1
  • Michael Fellmann
    • 2
  1. 1.Virtual Vehicle Research CenterGrazAustria
  2. 2.Junior Professorship of Business Information SystemsUniversity of RostockRostockGermany

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