Prof. Dr. Daniel Klapper

Die Forschung von Prof. Dr. Daniel Klapper konzentriert sich auf die Schnittstelle von Marketing, Verhaltensökonomie und Datenwissenschaft. Er untersucht empirisch, wie Transparenz, Preisstrategien und digitale Umgebungen das Verbraucherverhalten beeinflussen, insbesondere bei langlebigen Gütern und im Kontext von CO2-Emissionen. Methodisch setzt er fortgeschrittene Techniken wie Machine Learning, Deep Learning und Eye-Tracking ein, um komplexe Marktstrukturen zu modellieren und kognitive Verzerrungen zu analysieren. Seine Arbeit verbindet theoretische Modelle mit Feldexperimenten und der Analyse großer Datensätze, um regulatorische Fragen wie den AI Act oder Preisstrategien zu beleuchten.

🔒 Das System hat 1.090 mögliche Industrie-Partner gefunden — Firmen, Scores und Begründungen sind nur für eingeloggte Nutzer:innen sichtbar. Anmelden

• Jahrestagung 2013 der Forschungsgruppe Konsum & Verhalten

  Quelle ↗

  Zeitraum: 02/2013 - 03/2014 Projektleitung: Prof. Dr. Daniel Klapper

• 5. Workshop zum Thema "Marketing Metrics, Risk and Performance Modeling" 2013

  Quelle ↗

  Zeitraum: 03/2013 - 12/2013 Projektleitung: Prof. Dr. Daniel Klapper

• Ökonomische Risiken, Konsumentenheterogenität und die Bewertung von Preis- und Produktstrategien"

  Quelle ↗

  Förderer: DFG Sachbeihilfe Zeitraum: 09/2013 - 08/2016 Projektleitung: Prof. Dr. Daniel Klapper

• Empirical Evidence on the Role of Nonlinear Wholesale Pricing and Vertical Restraints on Cost Pass-Through

  2012

  The Review of Economics and Statistics · DOI

  How a cost shock is passed through to final consumer prices may relate to nominal price stickiness and rigidities, the existence of nonadjustable cost components, strategic markup adjustments, or other contract terms along the supply distribution chain. This paper presents a simple framework to assess the potential role of nonlinear pricing contracts and vertical restraints, such as resale price maintenance or wholesale price discrimination in the supply chain, in explaining the degree of pass-through from upstream cost shocks in the ground coffee category to downstream retail prices. We find that resale price maintenance increases pass-through rate.

• Behavioral biases in marketing

  2019

  Journal of the Academy of Marketing Science · DOI

• Choice Set Heterogeneity and the Role of Advertising: An Analysis with Micro and Macro Data

  2011

  Journal of Marketing Research · DOI

  The authors show how to use microlevel survey data from a tracking study on brand awareness in conjunction with data on sales and advertising expenditures to improve the specification, estimation, and interpretation of aggregate discrete choice models of demand. In a departure from the commonly made full information assumption, they incorporate limited information in the form of choice sets to reflect that consumers may not be aware of all available brands at purchase time. They find that both the estimated brand constants and the price coefficient are biased downward when consumer heterogeneity in choice sets is ignored. These biased estimates can lead firms to make costly price-setting mistakes. In addition, the tracking data enable the authors to identify separately two processes by which advertising influences market shares. They find that advertising has a direct effect on brand awareness (inclusion in choice set) in addition to its effect on consumer preferences (increase in utility). This improved understanding of how advertising works enhances researchers’ ability to make policy recommendations.