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Smart mobility – an analysis of potential customers’ preference structures

Author

Listed:
  • Thomas Schulz

    (Neu-Ulm University of Applied Sciences
    Technical University of Munich)

  • Markus Böhm

    (Technical University of Munich)

  • Heiko Gewald

    (Neu-Ulm University of Applied Sciences)

  • Helmut Krcmar

    (Technical University of Munich)

Abstract

Cities around the world face major challenges caused by the extensive use of private cars. To counteract these problems, a new paradigm is necessary which promotes alternative mobility services. ‘Smart mobility’ refers to a new mobility behaviour that makes use of innovative technical solutions, such as the IT-supported combination of different alternative mobility services during a trip from an origin to a destination. Unfortunately, relatively few customers use apps that provide recommendations for smart mobility and there is limited knowledge about the desires, priorities and needs of potential customers. To fill this gap, we use conjoint analysis to explore differences in smart mobility app preferences across groups of people with varying mobility behaviour. Our study also considers the effect of age and place of residence on preference structures. Our results show, for example, that only car drivers do not consider the price of the smart mobility app to be particularly important for their selection decision.

Suggested Citation

  • Thomas Schulz & Markus Böhm & Heiko Gewald & Helmut Krcmar, 2021. "Smart mobility – an analysis of potential customers’ preference structures," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(1), pages 105-124, March.
    • Handle: RePEc:spr:elmark:v:31:y:2021:i:1:d:10.1007_s12525-020-00446-z
    DOI: 10.1007/s12525-020-00446-z
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    More about this item

    Keywords

    Conjoint analysis; Mobility as a service (MaaS); Monetization; Preference structure; Smart mobility;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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