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Preface: Intelligent & Autonomous Enterprise

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References

  1. Meinzer, S., et al., Translating satisfaction determination from health care to the automotive industry. Service Business, 2016. 10(4): p. 1-35.

    Google Scholar 

  2. Gehrke, L., D. Hajizadeh, C. Kreibich, S. Meinzer, S. Augustine, and J. S. Geffers, Innovation Labs und Aktivitäten der Volkswagen Konzern IT im Zuge der Digitalisierung und Industrie 4.0, in Einführung und Umsetzung von Industrie 4.0: Grundlagen, Vorgehensmodell und Use Cases aus der Praxis, A. Roth, Editor. 2016, Springer: Berlin, Germany. p. 231-246.

    Google Scholar 

  3. Hünecke, P. and M. Gunkel, The influence of After-Sales service determinants on brand loyalty within the premium automotive industry: an empirical comparison of three countries. Service Science, 2012. 4(4): p. 365-381.

    Article  Google Scholar 

  4. Singularity. Exponential Growth of Computing. 2016; Available from: http://www.singularity.com/charts/page70.html.

  5. Kurzweil, R., How to Create a Mind: The Secret of Human Thought Revealed. 2012, London, England: Viking Adult.

    Google Scholar 

  6. IBM. IBM big data for the automotive industry: Take advantage of new sources of data to reduce costs and increase competitive advantage. 2013 09/10/2016]; Available from: http://www.oesa.org/Doc-Vault/Knowledge-Center/Operational-Performance-Content/IBM-Big-Data-for-Auto-Industry.pdf.

  7. Mearian, L., Self-driving cars could create 1GB of data a second, in Computerworld. 2013, Computerworld.

    Google Scholar 

  8. Rodgers, L., S. Zoepf, and J. Prenninger. Analysing the energy consumption of the BMW ActiveE field trial vehicles with application to distance to empty algorithms. in Transportation Research Procedia. 2014.

    Google Scholar 

  9. Seiberth, G., Wie verändern digitale Plattformen die Automobilwirtschaft?, in Praxis – Industrie 4.0: Wie digitale Plattformen unsere Wirtschaft verändert - und wie die Politik gestalten kann, Ansgar Baums | Martin Schössler | Ben Scott (Hg.): Editor. 2015, Kompendium Digitale Standortpolitik: Berlin, Germany. p. 28-41.

    Google Scholar 

  10. Wedeniwski, S., The Mobility Revolution in the Automotive Industry: How not to miss the digital turnpike. 2015, Berlin, Germany: Springer.

    Book  Google Scholar 

  11. Tummala, R., et al. New era in automotive electronics, a co-development by Georgia tech and its automotive partners. in 2016 Pan Pacific Microelectronics Symposium (Pan Pacific). 2016. IEEE.

    Google Scholar 

  12. Niculescu, A.I., et al., Designing IDA - An Intelligent Driver Assistant for Smart City Parking in Singapore, in Human-Computer Interaction – INTERACT 2015: 15th IFIP TC 13 International Conference, Bamberg, Germany, September 14-18, 2015, Proceedings, Part IV, J. Abascal, et al., Editors. 2015, Springer International Publishing: Cham. p. 510-513.

    Chapter  Google Scholar 

  13. Sinaeepourfard, A., et al. Estimating Smart City sensors data generation: Current and Future Data in the City of Barcelona. in 2016 Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net). 2016.

    Google Scholar 

  14. Geng, Y. and C.G. Cassandras, A new “Smart Parking” System Infrastructure and Implementation. Procedia - Social and Behavioral Sciences, 2012. 54: p. 1278-1287.

    Article  Google Scholar 

  15. ADL, Automotive After Sales 2015: Are you ready for the battle?, in Arthur D. Little - Automotive INSIGHT. 2015, Arthur D. Little, Germany. p. 1-6.

    Google Scholar 

  16. Gaiardelli, P., N. Saccani, and L. Songini, Performance measurement of the after-sales service network - evidence from the automotive industry. Computers in Industry, 2007. 58(7): p. 698-708.

    Article  Google Scholar 

  17. Philipp Grosse Kleimann, Dorit Posdorf, Alexander Brenner, Swen Beyer, Dr. Ralf Kiene, Torsten Hunstock. Customizing aftersales: Delivering the service that customers really want. 2013 08/28/2016]; Available from: https://de.scribd.com/document/254676885/Roland-Berger-Customizing-Aftersales-20131120.

    Google Scholar 

  18. Singh, S. Future Of Automotive Aftermarket And Car Servicing: Consumers Will Have More Channels To Shop Around. 2015 08/30/2016]; Available from: http://www.forbes.com/sites/sarwantsingh/2015/06/02/future-of-automotive-aftermarket-and-car-servicing-consumers-will-have-more-channels-to-shop-around/#35235c0a4359.

    Google Scholar 

  19. Bandaru, S., et al., Development, analysis and applications of a quantitative methodology for assessing customer satisfaction using evolutionary optimization. Applied Soft Computing, 2015. 30: p. 265-278.

    Article  Google Scholar 

  20. Chougule, R., V.R. Khare, and K. Pattada, A fuzzy logic based approach for modeling quality and reliability related customer satisfaction in the automotive domain. Expert Systems with Applications, 2013. 40(2): p. 800-810.

    Article  Google Scholar 

  21. Mavridou, E., et al., Mining affective needs of automotive industry customers for building a mass-customization recommender system. Journal of Intelligent Manufacturing, 2013. 24(2): p. 251-265.

    Article  Google Scholar 

  22. Mikusz, M., C. Jud, and T. Schäfer, Business Model Patterns for the Connected Car and the Example of Data Orchestrator, in Software Business: 6th International Conference, ICSOB 2015, Braga, Portugal, June 10-12, 2015, Proceedings, M.J. Fernandes, J.R. Machado, and K. Wnuk, Editors. 2015, Springer International Publishing: Cham. p. 167-173.

    Chapter  Google Scholar 

  23. Kohl, J., et al., Using multivariate split analysis for an improved maintenance of automotive diagnosis functions, in 15th European Conference on Software Maintenance and Reengineering (CSMR), T. Mens, Y. Kanellopoulos, and A. Winter, Editors. 2011, IEEE Computer Society: Oldenburg, Germany. p. 305–308.

    Google Scholar 

  24. Garcia, E., et al., The evolution of robotics research. IEEE Robotics & Automation Magazine, 2007. 14(1): p. 90-103.

    Article  Google Scholar 

  25. Scholer, M., M. Vette, and M. Rainer, A lightweight robot system designed for the optimisation of an automotive end-off line process station. Industrial Robot: An International Journal, 2015. 42(4): p. 296-305.

    Article  Google Scholar 

  26. DWave, Digital pioneering work: Volkswagen uses quantum computers, 2017. [Online]. Available: https://www.dwavesys.com/press-releases/digital-pioneering-work-volkswagen-uses-quantum-computers.

  27. Meinzer, Stefan; Jensen, Ulf; Thamm, Alexander; Hornegger, Joachim; Eskofier, Björn M., Can machine learning techniques predict customer dissatisfaction? A feasibility study for the automotive industry, Artificial Intelligence Research, 2017, Vol. 6 (1), pp. 80-90.

    Google Scholar 

  28. Hofmann, Martin; Neukart, Florian; Bäck, Thomas, Artificial Intelligence and Data Science in the Automotive Industry, 2017. [Online]. Available: https://data-science-blog.com/blog/2017/05/06/artificial-intelligence-and-data-science-in-the-automotive-industry/.

  29. Neukart, Florian: Reverse Engineering the Mind: Consciously Acting Machines and Accelerated Evolution, AutoUni – Schriftenreihe, 1st edition, Wolfsburg, Germany, 2017.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Volkswagen Group, Wolfsburg, Germany

    Martin Hofmann

  2. Volkswagen Data:Lab, Munich, Germany

    Stefan Meinzer

Authors
  1. Martin Hofmann
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  2. Stefan Meinzer
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Corresponding author

Correspondence to Martin Hofmann .

Editor information

Editors and Affiliations

  1. Institut für Informatik, LMU München, Munich, Bayern, Germany

    Claudia Linnhoff-Popien

  2. Allianz SE, Munich, Bayern, Germany

    Ralf Schneider

  3. Munich Airport, Munich, Bayern, Germany

    Michael Zaddach

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Hofmann, M., Meinzer, S. (2018). Preface: Intelligent & Autonomous Enterprise. In: Linnhoff-Popien, C., Schneider, R., Zaddach, M. (eds) Digital Marketplaces Unleashed. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49275-8_51

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  • DOI: https://doi.org/10.1007/978-3-662-49275-8_51

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49274-1

  • Online ISBN: 978-3-662-49275-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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