Marketing

Prof. Dr. Stefan Mayer (Interim Professor)

Chair of Marketing

Office
Faculty of Economics and Social Sciences
Chair of Marketing
Nauklerstr. 47, 1st floor, room 105
 +49 7071 29-76979
stefan.mayerspam prevention@uni-tuebingen.de
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Office Hours
Upon appointment via email.

 

 

 

Research Interests

  • Product Design, Aesthetics and Visual Presentation
  • Machine Learning, Deep Learning and Image Analytics
  • Processing Fluency, Consumer Judgments and Decision-Making
  • Open Science

Selected Awards & Honors

  • AMA-Sheth Doctoral Consortium Fellow 2017
  • Best Paper of the EMAC Research Camp 2016

Short Biography

2024

Since October 2024, Interim Professor of Marketing, School of Business and Economics, University of Tübingen

2019

Since March 2019, Assistant Professor of Marketing Analytics (tenure track), School of Business and Economics, University of Tübingen

2018

Visiting Scholar, Department of Psychology, University of California, San Diego (Prof. Dr. Piotr Winkielman)

2017

Doctoral Dissertation on product design and visual aesthetics (summa cum laude)

2012

Doctoral Student and Research Associate, Goethe University, Frankfurt, Department of Marketing (Prof. Dr. Jan Landwehr)

2012

Diploma in Psychology (M.Sc. equivalent), Johannes Gutenberg University, Mainz

2006

Studies of Psychology and Computer Science, Johannes Gutenberg University, Mainz

Selected Publications

Peer-reviewed journals

  • Mayer, S. & Landwehr, J. R. (2018). Quantifying Visual Aesthetics Based on Processing Fluency Theory: Four Algorithmic Measures for Antecedents of Aesthetic Preferences. Psychology of Aesthetics, Creativity, and the Arts, 12(4), 399–431. doi: 10.1037/aca0000187 [open access]
  • Graf, L. K. M., Mayer, S., & Landwehr, J. R. (2018). Measuring Processing Fluency: One versus Five Items. Journal of Consumer Psychology, 28(3), 393–411. doi: 10.1002/jcpy.1021 [open access]
  • Otter, T., Pachali, M. J., Mayer, S., & Landwehr, J. R. (2018). Causal Inference Using Mediation Analysis or Instrumental Variables – Full Mediation in the Absence of Conditional Independence. Marketing ZFP – Journal of Research and Management, 40, 41–57. doi: 10.15358/0344-1369-2018-2-41 [open access]
  • Mayer, S. & Landwehr, J. R. (2018). Objective measures of design typicality. Design Studies, 54, 146–161. doi: 10.1016/j.destud.2017.09.004 

Conference presentations (peer-reviewed)

  • Blaseg, D., & Mayer, S.(2023, October). Judging a Pitch by its Cover? Experimental Evidence on the Role of Visual Aesthetics and Quality in Startup Pitch Decks. AMJ Paper Development Workshop, Barcelona, ES.
  • Blaseg, D., & Mayer, S.(2023, August). Judging a Pitch by its Cover? Experimental Evidence on the Role of Visual Aesthetics and Quality in Startup Pitch Decks. Young European Scholars (YES) Marketing Conference, Maastricht, NL.
  • Blaseg, D., & Mayer, S.(2023, May). Judging a Pitch by its Cover? Experimental Evidence on the Role of Visual Aesthetics and Quality in Startup Pitch Decks. Workshop on Behavioral Perspectives in VC, Copenhagen, DK.
  • Landwehr, J. R., Mayer, S., Bäker, A., & Nattter, M. (2023, February). The Face of Trustworthiness: Can a Machine Detect Valid Cues of Trustworthy Behavior in Human Faces? Machine Learning meets Quantitative Social Sciences Conference, Tübingen, DE.
  • Mast, D., Mayer, S., Behl, A., & Papies, D. (2023, February). Understanding Fashion Product Sales Using Product Images and Convolutional Neural Networks. Marketing Analytics Symposium Sydney (MASS), Sydney, AU.
  • Blaseg, D., & Mayer, S.(2022, September). Judging a Pitch by its Cover? Experimental Evidence on the Role of Visual Aesthetics and Quality in Startup Pitch Decks. Conference on Field Experiments in Strategy, London, UK.
  • Mast, D., Mayer, S., Behl, A., & Papies, D. (2022, May). Understanding Fashion Product Sales Using Product Images and Convolutional Neural Networks. European Marketing Academy (EMAC) Conference, Budapest, HU.
  • Felder, C., & Mayer, S. (2022, May). Customized Stock Return Prediction with Deep Learning. IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr), Helsinki, FI.
  • Behl, A., Mayer, S., Bevot, A., Pauser, D., Papies, D., & Hansmann, S. (2021, September). Video-Based, Marker-Less Gait-Analysis in Children and Adolescents Based on Transfer Learning with Deep Neural Networks. European Paediatric Rheumatology (PReS) Conference, Satigny, CH.
  • Mayer, S. (2020, March). How to Share Your Research by Developing R Packages. Annual Business Researcher Conference (VHB), Frankfurt, DE.
  • Mayer, S. & Landwehr, J. R. (2020, February). Visual Similarity Based on Deep Neural Networks. American Marketing Association (AMA) Winter Conference, San Diego (CA), USA.
  • Mayer, S. (2019, May). What is deep learning, and why should I care? European Marketing Academy (EMAC) Conference, Hamburg, DE.
  • Mayer, S. (2019, May). imagefluency: Image Fluency Scores in R. European Marketing Academy (EMAC) Conference, Hamburg, DE.
  • Mayer, S., Landwehr, J. R., Beck, O. (2019, May). The Power of Deep Neural Networks: How Machine Learning can Advance the Forecasting of Product Success Based on Aesthetic Appearance. Theory + Practice in Marketing (TPM) Conference, New York (NY), USA.
  • Mayer, S., Landwehr, J. R., Beck, O. (2018, June). The Power of Deep Neural Networks: How Machine Learning can Advance the Forecasting of Product Success Based on Aesthetic Appearance. INFORMS Marketing Science Conference, Philadelphia (PA), USA.
  • Otter, T., Pachali, M. J., Mayer, S., Landwehr, J. R. (2018, May). Causal Inference Using Mediation Analysis or Instrumental Variables – Full Mediation in the Absence of Conditional Independence. European Marketing Academy (EMAC) Conference, Glasgow, UK.
  • Graf, L. K. M., Mayer, S., & Landwehr, J. R. (2017, May). Multiple Sources and Consequences, Yet Only One Experience? A Systematic Analysis of Processing Fluency Effects. European Marketing Academy (EMAC) Conference, Groningen, NL.
  • Mayer, S. & Landwehr, J. R. (2016, October). Objective measures of design typicality that predict aesthetic liking, fluency, and car sales. Association for Consumer Research (ACR) North America Conference, Berlin, DE.
  • Mayer, S. & Landwehr, J. R. (2016, September). Objective measures of design typicality that predict aesthetic liking, fluency, and car sales. EMAC Junior Faculty & Doctoral Student Research Camp, Vienna, AT.
  • Mayer, S. & Landwehr, J. R. (2016, August). The Toolbox for Quantified Aesthetics: Objective measures of visual antecedents of aesthetics preferences. Conference of the International Association of Empirical Aesthetics (IAEA), Vienna, AT.
  • Mayer, S. & Landwehr, J. R. (2016, June). Measuring design typicality – A comparison of subjective and objective approaches. Design Research Society (DRS) Conference, Brighton, UK.
  • Mayer, S. & Landwehr, J. R. (2016, May). Measuring design typicality – A comparison of subjective and objective approaches. European Marketing Academy (EMAC) Conference, Oslo, NO. [Nominated for the Best Paper Award based on a Doctoral Work]
  • Mayer, S. & Landwehr, J. R. (2015, August). The Measurement of Visual Antecedents of Processing Fluency and Aesthetic Liking. European Conference on Visual Perception (ECVP), Liverpool, UK.
  • Mayer, S. & Landwehr, J. R. (2014, October). When Complexity is Symmetric: The Interplay of Two Core Determinants of Visual Aesthetics. Association for Consumer Research (ACR) North America Conference, Baltimore (MD), USA.

Software