Challenges from Choice Modeling Practice

Challenges from Choice Modeling PracticeTBA

Abstract: (AI-Generated, from my side)
This talk highlights practical challenges that arise when applying choice modeling methods in real world settings. Building on earlier work in traditional demand modeling, the presentation focuses first on co ideation and evaluation workflows that combine conversational AI surveys, large scale MaxDiff exercises, and machine learning–based prediction. The second part turns to “SKU–price” conjoint studies—CBC designs with minimal attribute structure—which represent a major share of commercial applications despite receiving limited academic attention. Together, these examples illustrate methodological blind spots, implementation hurdles, and opportunities for advancing practice oriented choice modeling.

More information on Dr. Nino Hardt can be found here.

Please use the following link for Zoom: https://uni-frankfurt.zoom.us/j/62958556058?pwd=b01qWXlrbVMzc1JFVEhjSWNvdGZPQT09