Publications
60 Years Of Conjoint: Where We Come From And Where We Are
Kurz P., 2024 – Analytics & Insights Summit – USA 2024
Conjoint analysis: From classic designs to modern simulations. A 60-year retrospective and call for pragmatic, decision-driven applications.
Renewable gases in the heating market: Identifying consumer preferences through a Discrete Choice Experiment
Rilling B., Kurz P., Herbes C., 2023 – in Energy Policy Volume 184, 2024
What drives acceptance of renewable gases? A discrete choice study reveals what consumers value most in sustainable heating.
Omitted Budget Constraint Bias and Implications for Competitive Pricing
Pachali M., Kurz P., Otter T., 2023 – in Journal of Marketing Research, 2023
How ignoring budget constraints distorts results – and how explicit modeling enables better price strategies and market forecasts.
Archetypal Analysis And Product Line Design
Liu, Y., Kurz P., Allenby, G., 2022 – Sawtooth Software Conference – USA 2022
How archetypal analysis helps design targeted product lines – using consumer profiles, preferences, and usage contexts.
Behavioral Conjoint Model With Simultaneous Attribute And Parameter Weighting
Kurz P., Rausch, M., Binner S., 2022 – Sawtooth Software Conference – USA 2022
Behavioral Calibration Questions (BCQs) enhance predictive accuracy in conjoint by anchoring decisions in actual shopper behavior.
Volumetric Conjoint And The Role Of Assortment Size
Hardt, N., Kurz, P., 2022 – Sawtooth Software Conference – USA 2022
How the shown assortment size distorts volumetric predictions – and how a new model improves accuracy for multi-purchase categories.
Enhance Conjoint With A Behavioral Framework
Kurz P., Binner S., 2021 – Sawtooth Software Conference – USA 2021
How nine simple questions can enhance conjoint studies by aligning them with actual consumer behavior.
Hierarchical Bayes Conjoint Choice Models – Model Framework, Bayesian Inference, Model Selection, and Interpretation of Estimation Results
Goeken, N., Kurz, P., Steiner, W., 2021 – in Marketing ZFP Volume 43, 2021, 49-64.
Understanding HB choice models: Bayesian estimation of utilities, model selection, and result interpretation.
Using Hierarchical Bayes draws for improving shares of choice predictions in conjoint simulations: A study based on conjoint choice data
Hein, M., Goeken, N., Kurz, P., Steiner, W., 2021 – European Journal of Operational Research, 2021
A study on how Hierarchical Bayes draws improve the accuracy of share-of-choice predictions in conjoint simulations.
How to Generalize from a Hierarchical Model?
Pachali M., Kurz P., Otter T., 2020 – in Quantitative Marketing and Economics Volume 18 Number 4, 2020, 343-380.
Strategies to generalize individual-level results from HB models without introducing aggregation bias.
Consumer Willingness To Pay for Proenvironmental Attributes of Biogas Digestate-Based Potting Soil
Herbes, C., Dahlin, J., Kurz, P., 2020 – in Sustainability Vol. 12, Iss. 16, 2020
Conjoint study on consumer preferences for environmentally friendly attributes in peat-free potting soil.
Conjoint Meets AI
Kurz P., Binner S., 2020 – Sawtooth Software Conference – USA 2020
How neural networks can enhance choice-based conjoint studies: AI-driven designs lead to better data quality and more realistic respondent choices.
Latent Class Conjoint Choice Models: A Guide for Model Selection, Estimation, Validation, and Interpretation of Results
Paetz, F., Hein, M., Kurz P., Steiner, W., 2019 – in Marketing ZFP Volume 41, 2019, 3-20
How to select, estimate, validate, and interpret latent class conjoint models for segmentation and insight generation.
Revisiting Ensembles – A Straightforward Approach to Increase Model Accuracy?
How combining multiple conjoint models improves forecast accuracy – without increasing complexity.
Kurz P., Müller M., Geisselhardt I., 2019 – SKIM/Sawtooth Software European Conference – Paris 2019
On the effect of HB covariance matrix prior settings. A simulation study
Hein M., Kurz P., Steiner W., 2019 – in Journal of Choice Modelling 31, 2019, 51–72
How prior settings affect HB model covariance estimation. Insights from simulation.
Predictive Analystics with RPSP Models
Kurz P., Binner S., 2018 – Sawtooth Software Conference – USA 2018
RPSP models combine conjoint data with real market data to integrate trends and seasonality into simulations.
On Estimating Pricing Models from End-Consumer Internet Car-Configuration Data
Fuhrmann T., Kurz P., Schweizer M., Geyer-Schulz A., 2017 – in Mucha, H.-J. (ed.): Big Data Clustering: Data preprocessing, variable selection, and dimension reduction.
Report no. 29, WIAS, Berlin 2017.
By analyzing rational configurations, price structures can be estimated using linear regression models.
Simulating From HB Upper Level Model
Kurz P., Binner S., 2016 – Sawtooth Software Conference – USA 2016
Using the upper level of the HB model to improve preference simulations and prediction accuracy.
Capturing Individual Level Behavior In DCM
Kurz P., Binner S., 2015 – Sawtooth Software Conference – USA 2015
How well do choice models capture individual preferences? This paper explores limitations caused by shrinkage in HB estimation.
The Validity of Conjoint Analysis: An Investigation of Commercial Studies Over Time
Selka S., Baier D., Kurz P., 2014 – in Spiliopoulou, M. (Hrsg.): Data Analysis, Machine Learning and Knowledge Discovery, Springer 2014, 227-234.
An empirical analysis of over 2,000 commercial studies shows: The validity of conjoint analysis has not improved in recent years.
Research Space and Realistic Pricing in Shelf Layout Conjoint
Kurz P., Binner S., Kehl L., 2013 – Sawtooth Software Conference – USA 2013
How to run realistic shelf tests with Shelf Layout Conjoint. Practical insights on pricing, SKU selection, and modeling.
The Individual Choice Task Threshold
Kurz P., Binner S., 2012 – Sawtooth Software Conference – USA 2012
The Choice Task Threshold describes the point at which respondents disengage during CBC surveys.
Application Specific Communication Stack for Computationally Intensive Market Research Internet Information System
Kurz P., Sikorski A., 2011 – BIS Conference – Posen 2011
A specific communication stack ensures reliable transactions in computational intensiv market research applications.
Which are the Right Covariates in HB Estimation?
Kurz P., Binner S., 2011 – SKIM Conference – Wien 2011
This analysis shows when covariates in HB models are useful, based on real and simulated data.
Added Value through Covariates in HB Modeling
Kurz P., Binner S., 2010 – Sawtooth Software Conference – USA 2010
Examines the impact of covariates on estimation accuracy in hierarchical Bayes models based on ten conjoint analysis case studies.
Conjoint Analysis: Respondents and Clients Experience
Binner S., 2010 – SKIM Conference – Köln 2010
Success factors of conjoint projects: client involvement, realistic tasks, actionable insights and business integration.
Psychological Price Barriers in Conjoint Analysis
Binner S., Kehl L., 2008 – SKIM Conference – Barcelona 2008
Price thresholds can distort conjoint results. This paper shows how FTDA can deliver more realistic price elasticity insights.
Hierarchical Approach for Optimized Concept Estimation
Binner S., 2007 – Cutting the Edges of Market Research Conference – Düsseldorf 2007
Dual conjoint model combining price and attribute analysis to enhance simulation realism and concept optimization.
Do Individual Hit-Rates Matter at All?
Binner S., 2006 – Design & Innovations Conference – München 2006
Individual hit rates in conjoint studies are often low—but this doesn’t mean the results are invalid. Learn why.
Deriving the Real Market Potential of New-to-the-World Products
Binner S., 2005 – Design & Innovations Conference – Berlin 2005
How to realistically simulate market potential for new-to-the-world products using an extended Purchase Likelihood model.
Linking Hierarchical Conjoints with Hierarchical Bayes Regression
Kurz P., 2005 – SKIM Conference – Amsterdam 2005
Hierarchical Conjoint combines micro and macro models to validly capture complex preference decisions with many attributes.
Driving Brand Management through Effective Brand Equity Measurement
Binner S., Hoffmann-Wiebe W., 2002 – Esomar Annual Congress – Barcelona 2002
Brand equity measurement using conjoint and C.D.I.: How businesses can make informed brand strategy decisions.
Conjoint Analysis in International Industrial Markets
Binner S., 2000 – Sawtooth Software Conference – USA 2000
How does conjoint work in international industrial markets? Opportunities and barriers at a glance.
www and International Industrial Marketing Research
Binner S., 2000 – Esomar Annual Congress – Wien 2000
How the internet transforms international B2B market research – insights and implications.
Effective Competitive Intelligence Techniques for Industrial Markets
Binner S., Beswick R., 1999 – Esomar CI Conference – Genf 1999
How companies gather strategic competitive insights in industrial B2B markets – structured and ethical.
Using Conjoint Methodologies for New Pricing Strategies
Binner S., Kramer M., 1997 – Esomar B2B Conference – Wien 1997
How simulation-based pricing strategies succeed in technical B2B markets using conjoint analysis.