W. DeSarbo

发表

Hierarchical Bayes Conjoint Analysis: Recovery of Partworth Heterogeneity from Reduced Experimental Designs

P. Lenk, W. DeSarbo, P. Green, 1996 .

Product Positioning Under Price Competition

W. DeSarbo, P. Harker, S. C. Choi, 1990 .

Three-way metric unfolding via alternating weighted least squares

W. DeSarbo, J. Douglas Carroll, Wayne S. DeSarbo, 1985 .

Overlapping Clustering: A New Method for Product Positioning

P. Arabie, J. Carroll, W. DeSarbo, 1981 .

Gennclus: New models for general nonhierarchical clustering analysis

W. DeSarbo, 1982 .

A maximum likelihood methodology for clusterwise linear regression

W. DeSarbo, W. L. Cron, W. Cron, 1988 .

Optimal variable weighting for hierarchical clustering: An alternating least-squares algorithm

W. DeSarbo, J. Carroll, G. Soete, 1985 .

A New Measure of Predictor Variable Importance in Multiple Regression

J. Carroll, W. DeSarbo, P. Green, 1978 .

The Spatial Representation of Market Information

W. DeSarbo, Alexandru M. Degeratu, M. Wedel, 2001 .

A mixture likelihood approach for generalized linear models

W. DeSarbo, M. Wedel, 1995 .

Three-Way Scaling and Clustering.

P. Arabie, W. DeSarbo, F. Murtagh, 1991 .

Response Determinants in Satisfaction Judgments

W. DeSarbo, R. Oliver, 1988 .

Synthesized clustering: A method for amalgamating alternative clustering bases with differential weighting of variables

J. Carroll, W. DeSarbo, P. Green, 1984 .

Customer Value Analysis in a Heterogeneous Market

W. DeSarbo, Kamel Jedidi, Indrajit Sinha, 2001 .

Finite-Mixture Structural Equation Models for Response-Based Segmentation and Unobserved Heterogeneity

W. DeSarbo, Kamel Jedidi, Harsharanjeet S. Jagpal, 1997 .

Market Segment Derivation and Profiling Via a Finite Mixture Model Framework

W. DeSarbo, M. Wedel, 2002 .

Judgments of brand similarity

Tammo H. A. Bijmolt, W. DeSarbo, R. Pieters, 1998 .

Identifying consumer heterogeneity in unobserved categories

W. DeSarbo, S. Blanchard, A. S. Atalay, 2011, Marketing Letters.

A New Zero-Inflated Negative Binomial Methodology for Latent Category Identification

Simon J. Blanchard, W. DeSarbo, S. Blanchard, 2012, Psychometrika.

The Heterogeneous P-Median Problem for Categorization Based Clustering

W. DeSarbo, Daniel Aloise, S. Blanchard, 2012, Psychometrika.

Multiclus: A new method for simultaneously performing multidimensional scaling and cluster analysis

W. DeSarbo, Kamel Jedidi, D. J. Howard, 1991 .

Extracting Summary Piles from Sorting Task Data

Daniel Aloise, Wayne S. DeSarbo, Simon J. Blanchard, 2017 .

An Alternative Efficient Representation of Demand-Based Competitive Asymmetry

W. DeSarbo, Rajdeep Grewal, 2007 .

Implementing Managerial Constraints in Model-Based Segmentation: Extensions of Kim, Fong, and DeSarbo (2012) with an Application to Heterogeneous Perceptions of Service Quality

Simon J. Blanchard, W. DeSarbo, S. Blanchard, 2013 .

Modeling strategic group dynamics: A hidden Markov approach

W. DeSarbo, Rajdeep Grewal, P. Ebbes, 2010 .

Revisiting the Miles and Snow Strategic Framework: Uncovering Interrelationships between Strategic Types, Capabilities, Environmental Uncertainty, and Firm Performance

W. DeSarbo, Michael Song, Anthony Di Benedetto, 2005 .

Hybrid Strategic Groups

W. DeSarbo, Rajdeep Grewal, 2008 .

Typologies of Compulsive Buying Behavior: A Constrained Clusterwise Regression Approach

W. DeSarbo, E. A. Edwards, E. Edwards, 1996 .

Combinatorial Optimization Approaches to Constrained Market Segmentation: An Application to Industrial Market Segmentation

W. DeSarbo, Douglas B. Grisaffe, 1998 .

A Review of Recent Developments in Latent Class Regression Models

W. DeSarbo, M. Wedel, 1994 .

Representing Heterogeneity in Consumer Response Models 1996 Choice Conference Participants

Pradeep K. Chintagunta, P. Lenk, W. DeSarbo, 1997 .

Gemcat: A general multivariate methodology for estimating catastrophe models

Terence A. Oliva, Diana L. Day, W. DeSarbo, 1987 .

A Conjoint-Based Product Designing Procedure Incorporating Price Competition

W. DeSarbo, S. C. Choi, S. Choi, 1994 .

Deception by Implication: An Experimental Investigation

Raymond R. Burke, W. DeSarbo, T. S. Robertson, 1988 .

Simultaneous multidimensional unfolding and cluster analysis: An investigation of strategic groups

W. DeSarbo, Karel Cool, Kamel Jedidi, 1991 .

Celebrity-Brand Congruence Analysis

W. DeSarbo, 1985 .

Who Competes with Whom? A Demand-Based Perspective for Identifying and Representing Asymmetric Competition

Rajdeep Grewal, W. DeSarbo, Y. Wind, 2006 .

An Empirical Pooling Approach for Estimating Marketing Mix Elasticities with PIMS Data

W. DeSarbo, D. Reibstein, V. Ramaswamy, 1993 .

Fuzzy Clusterwise Growth Curve Models via Generalized Estimating Equations: An Application to the Antisocial Behavior of Children

Y. Takane, W. DeSarbo, Heungsun Hwang, 2007, Multivariate behavioral research.

A Disaggregate Negative Binomial Regression Procedure for Count Data Analysis

W. DeSarbo, E. Anderson, V. Ramaswamy, 1994 .

A Latent Class Poisson Regression Model for Heterogeneous Count Data

Michel Wedel, Venkatram Ramaswamy, W. DeSarbo, 1993 .

A Multidimensional Scaling Model Accommodating Differential Stimulus Familiarity

Michel Wedel, Tammo H. A. Bijmolt, W. DeSarbo, 1998, Multivariate behavioral research.

GENFOLD2: A set of models and algorithms for the general UnFOLDing analysis of preference/dominance data

V. Rao, W. DeSarbo, Wayne S. DeSarbo, 1984 .

On Estimating Finite Mixtures of Multivariate Regression and Simultaneous Equation Models

Michel Wedel, Kamel Jedidi, Venkatram Ramaswamy, 1996 .

A stochastic multidimensional scaling procedure for the spatial representation of three-mode, three-way pick any/J data

W. DeSarbo, Kamel Jedidi, 1991 .

Componential Segmentation in the Analysis of Consumer Trade-Offs

W. DeSarbo, P. Green, 1979 .

A latent class procedure for the structural analysis of two-way compositional data

P. Lenk, W. DeSarbo, V. Ramaswamy, 1993 .

Tscale: A new multidimensional scaling procedure based on tversky's contrast model

Ajay K. Manrai, Lalita A. Manrai, W. DeSarbo, 1992 .

A Parametric Multidimensional Unfolding Procedure for Incomplete Nonmetric Preference/Choice Set Data in Marketing Research

W. DeSarbo, M. R. Young, A. Rangaswamy, 1997 .

Reply to “A Comment on a New Measure of Predictor Variable Importance in Multiple Regression”

J. Carroll, W. DeSarbo, P. Green, 1980 .

Exploring Intra‐Industry Competitive Heterogeneity: The Identification of Latent Competitive Groups

W. DeSarbo, S. Blanchard, Qiong Wang, 2010 .

Towards a brain-to-society systems model of individual choice

Ross A. Hammond, W. DeSarbo, A. Dagher, 2008 .

On the Measurement of Perceived Consumer Risk

William J. Havlena, W. DeSarbo, 1991 .

A parametric procedure for ultrametric tree estimation from conditional rank order proximity data

W. DeSarbo, M. R. Young, M. Young, 1995 .

A Friction Model for Describing and Forecasting Price Changes

V. Rao, W. DeSarbo, Y. Wind, 1987 .

A Model-Based Approach for Visualizing the Dimensional Structure of Ordered Successive Categories Preference Data

Crystal J. Scott, W. DeSarbo, Joonwook Park, 2008 .

A nonspatial methodology for the analysis of two-way proximity data incorporating the distance-density hypothesis

Wayne S. DeSarbo, Ajay K. Manrai, Raymond R. Burke, 1990 .

A stochastic multidimensional scaling vector threshold model for the spatial representation of “pick any/n” data

Jaewun Cho, W. DeSarbo, Jaewun Cho, 1989 .

A New Stochastic Multidimensional Unfolding Model for the Investigation of Paired Comparison Consumer Preference/Choice Data

J. Eliashberg, Geert De Soete, W. DeSarbo, 1987 .

Deriving joint space positioning maps from consumer preference ratings

Wayne S. DeSarbo, Vithala R. Rao, Joonwook Park, 2011 .

Adaptive Multidimensional Scaling: The Spatial Representation of Brand Consideration and Dissimilarity Judgments

W. DeSarbo, M. Wedel, T. Bijmolt, 2002 .

An Integrated Approach toward the Spatial Modeling of Perceived Customer Value

Wayne S. DeSarbo, Indrajit Sinha, W. DeSarbo, 1998 .

A Stochastic Three-Way Unfolding Model for Asymmetric Binary Data

William J. Havlena, S. Gupta, W. DeSarbo, 1987 .

Simple and Weighted Unfolding Threshold Models for the Spatial Representation of Binary Choice Data

Wayne S. DeSarbo, Donna L. Hoffman, W. DeSarbo, 1986 .

A Probabilistic Multidimensional Scaling Vector Model

Wayne S. DeSarbo, Richard L. Oliver, W. DeSarbo, 1986 .

Dynamic Models Incorporating Individual Heterogeneity: Utility Evolution in Conjoint Analysis

John Liechty, W. DeSarbo, J. Liechty, 2005 .

Latent class metric conjoint analysis

Michel Wedel, Venkatram Ramaswamy, Marco Vriens, 1992 .

A Bayesian Multidimensional Scaling Procedure for the Spatial Analysis of Revealed Choice Data

W. DeSarbo, Wayne S. DeSarbo, 1998 .

The Joint Spatial Representation of Multiple Variable Batteries Collected in Marketing Research

Wayne S. Desarbo, W. DeSarbo, Jianan Wu, 2001 .

Deriving ultrametric tree structures from proximity data confounded by differential stimulus familiarity

Rabikar Chatterjee, Juyoung Kim, W. DeSarbo, 1994 .

On the Creation of Acceptable Conjoint Analysis Experimental Designs

Vijay Mahajan, Joel Steckel, W. DeSarbo, 1991 .

Criteria for Corporate Venturing: Importance Assigned by Managers

Diana L. Day, W. DeSarbo, I. MacMillan, 1987 .

The estimation of ultrametric and path length trees from rectangular proximity data

George W. Furnas, Wayne S. DeSarbo, Geert De Soete, 1984 .

Three-Way Multivariate Conjoint Analysis

Wayne S. DeSarbo, Donald R. Lehmann, John O'Shaughnessy, 1982 .

Estimating Choice Probabilities in Multiattribute Decision Making

Wayne S. DeSarbo, J. Douglas Carroll, Paul E. Green, 1981 .

The relationship between the marketing mix and share of category requirements

Peter S. Fader, Leonard M. Lodish, C. B. Bhattacharya, 1996 .

Accommodating the effects of brand unfamiliarity in the multidimensional scaling of preference data

Rabikar Chatterjee, Wayne S. Desarbo, W. DeSarbo, 1992 .

Least squares algorithms for constructing constrained ultrametric and additive tree representations of symmetric proximity data

Wayne S. DeSarbo, Geert De Soete, J. Douglas Carroll, 1987 .

A stochastic multidimensional scaling procedure for the empirical determination of convex indifference curves for preference/choice analysis

Kamel Jedidi, W. DeSarbo, Kamel Jedidi, 1991 .

Tree Representations of Rectangular Proximity Matrices

Wayne S. DeSarbo, Geert De Soete, W. DeSarbo, 1984 .

A Smooth Transition Finite Mixture Model for Accommodating Unobserved Heterogeneity

W. DeSarbo, M. Medeiros, E. Kappe, 2020, Journal of Business & Economic Statistics.

A Bayesian Vector Multidimensional Scaling Procedure for the Analysis of Ordered Preference Data

Crystal J. Scott, W. DeSarbo, D. K. Fong, 2010 .

Latent Structure Regression

Michel Wedel, Wagner A. Kamakura, Wayne S. DeSarbo, 2006 .

Disaggregate Market Share Response Models

Wayne S. DeSarbo, W. DeSarbo, Alexandru M. Degeratu, 2002 .

A spatial interaction model for deriving joint space maps of bundle compositions and market segments from pick-any/J data: An application to new product options

Tammo H. A. Bijmolt, W. DeSarbo, M. Wedel, 1996 .

The Pennsylvania State University The Graduate School The Mary Jean and Frank P. Smeal College of Business Administration A HIERARCHICAL BAYESIAN FINITE MIXTURE MULTIDIMENSIONAL SCALING APPROACH FOR ACCOMMODATING STRUCTURAL AND PREFERENCE HETEROGENEITY IN THREE WAY PREFERENCE DATA

Frank P. Smeal, J. Schafer, W. DeSarbo, 2007 .

A Heterogeneous Bayesian Regression Model for Cross-sectional Data Involving a Single Observation per Response Unit

W. DeSarbo, D. K. Fong, P. Ebbes, 2012 .

A Bayesian Vector Multidimensional Scaling Procedure Incorporating Dimension Reparameterization with Variable Selection

W. DeSarbo, D. K. Fong, Zhe Chen, 2015, Psychometrika.

On the Use of Hierarchical Clustering for the Analysis of Nonsymmetric Proximities

W. DeSarbo, Wayne S. DeSarbo, 1984 .

A Bayesian methodology for simultaneously detecting and estimating regime change points and variable selection in multiple regression models for marketing research

W. DeSarbo, D. K. Fong, Wayne S. DeSarbo, 2007 .

The Wandering Ideal Point Model: A Probabilistic Multidimensional Unfolding Model for Paired Comparisons Data

Geert De Soete, W. DeSarbo, G. Soete, 1986 .

A stochastic multidimensional unfolding approach for representing phased decision outcomes

Indrajit Sinha, Gregory S. Carpenter, W. DeSarbo, 1996 .

The Wandering Ideal Point Model for Analyzing Paired Comparisons Data

W. DeSarbo, G. De Soete, J. Carroll, 1988 .

STEMM: A General Finite Mixture Structural Equation Model

Kamel Jedidi, W. DeSarbo, Kamel Jedidi, 1997 .

Statistical perceptual maps: using confidence region ellipses to enhance the interpretations of brand positions in multidimensional scaling

W. DeSarbo, Douglas B. Grisaffe, D. Iacobucci, 2017 .

An Alternating Least-Squares Procedure for Estimating Missing Preference Data in Product-Concept Testing

W. DeSarbo, P. Green, J. Carroll, 1986 .

A latent structure factor analytic approach for customer satisfaction measurement

W. DeSarbo, Jianan Wu, Pu-Ju Chen, 2006 .

Implications for Asymmetry, Nonproportionality, and Heterogeneity in Brand Switching from Piece-wise Exponential Mixture Hazard Models

Michel Wedel, Wagner A. Kamakura, Frenkel Ter Hofstede, 1995 .

MEMD: An APL Program for Multivariate Estimation of Missing Data

W. DeSarbo, Wayne S. DeSarbo, 1978 .

Proper Mix of Promotional Offerings Can Produce for Teams

Wayne S. DeSarbo, Ashley Stadler Blank, W. DeSarbo, 2012 .

Sculptre: A New Methodology for Deriving and Analyzing Hierarchical Product-Market Structures from Panel Data

Wayne S. DeSarbo, Venkatram Ramaswamy, W. DeSarbo, 1990 .

GRADUATE SCHOOL OF BUSINESS COLUMBIA UNIVERSITY VENKATRAM RAMASWAMY MARKETING DEPARTMENT SCHOOL OF BUSINESS ADMINISTRATION UNIVERSITY OF MICHIGAN WAYNE S. DESARBO MARKETING AND STATISTICS DEPARTMENTS SCHOOL OF BUSINESS ADMINISTRATION UNIVERSITY OF MICHIGAN

W. DeSarbo, Kamel Jedidi, V. Ramaswamy, 2005 .

Applied Latent Class Analysis: Mixture Regression Models

Michel Wedel, Wayne S. DeSarbo, W. DeSarbo, 2002 .

The Spatial Representation of Heterogeneous Consideration Sets

Wayne S. DeSarbo, Kamel Jedidi, W. DeSarbo, 1995 .

Redundancy Analysis

W. DeSarbo, Kamel Jedidi, Heungsun Hwang, 2016 .

A customized market response model: Development, estimation, and empirical testing

V. Rao, W. DeSarbo, J. Wind, 1988 .

Towards a brain-to-society systems model of individual choice

Ulf Böckenholt, Wayne S. DeSarbo, Alain Dagher, 2009 .

Combinatorial Optimization Approaches to Normative Market Segmentation : An Application to Industrial Market Segmentation

W. DeSarbo, Douglas B. Grisaffe, 1996 .

Multidimensional Scaling of Preference Data

Crystal J. Scott, W. DeSarbo, 2010 .

A Marketer'S Guide to Log-Linear Models for Qualitative Data Analysis

W. DeSarbo, D. K. Hildebrand, 1979 .

Research methodology : conjoint analysis, multidimensional scaling, and related techniques

Naresh K. Malhotra, Wayne S. DeSarbo, James Agarwal, 2011 .

Representing heterogeneity in consumer response models

Michel Wedel, Wagner A. Kamakura, Kannan Srinivasan, 1997 .

Research Note Heterogeneous and Nonproportional Effects of Marketing Variables on Brand Switching: An Application of a Discrete Time Duration Model

W. DeSarbo, M. Wedel, W. Kamakura, 1993 .

Advances in Marketing Research and Modeling: the Academic and Industry Impact of Paul E. Green

Wagner A. Kamakura, Wayne S. DeSarbo, Michel Wedel, 2004 .

Canonical/redundancy factoring analysis

W. DeSarbo, 1981 .

Identifying consumer heterogeneity in unobserved categories

Simon J. Blanchard, W. DeSarbo, S. Blanchard, 2012 .

Stochastic Tree Unfolding (STUN) Models

W. DeSarbo, J. Carroll, Geert De Soete, 1987 .

A Heterogeneous Bayesian Regression Model for Cross-sectional Data Involving a Single Observation per Response Unit

W. DeSarbo, D. K. Fong, P. Ebbes, 2012, Psychometrika.

The past, present, and future of measurement and methods in marketing analysis

John G. Lynch, W. DeSarbo, D. Lehmann, 2020, Marketing Letters.

Bayesian inference for finite mixtures of generalized linear models with random effects

Wayne S. DeSarbo, Peter J. Lenk, P. Lenk, 2000 .

Model-Based Segmentation Featuring Simultaneous Segment-Level Variable Selection

Wayne S. DeSarbo, Sunghoon Kim, Duncan K. H. Fong, 2012 .

A Latent Structure Double Hurdle Regression Model for Exploring Heterogeneity in Consumer Search Patterns

Wayne S. DeSarbo, Jungwhan Choi, W. DeSarbo, 1998 .

A maximum likelihood method for latent class regression involving a censored dependent variable

Kamel Jedidi, Venkatram Ramaswamy, Wayne S. Desarbo, 1993 .

Three-way scaling and clustering.

Wayne S. DeSarbo, Scott M. Smith, Wayne S. DeSarbo, 1988 .

A Generalized Normative Segmentation Methodology Employing Conjoint Analysis

W. DeSarbo, Wayne S. DeSarbo, Christian DeSarbo, 2007 .

An Exponential-Family Multidimensional Scaling Mixture Methodology

Michel Wedel, W. DeSarbo, M. Wedel, 1996 .

Analyzing Constant-Sum Multiple Criterion Data: A Segment-level Approach

Rabikar Chatterjee, Wayne S. DeSarbo, Venkatram Ramaswamy, 1995 .

Market segmentation with choice-based conjoint analysis

Steven H. Cohen, Venkatram Ramaswamy, Wayne S. Desarbo, 1995 .

Wayne S. DeSarbo, Steven H. Cohen, Venkatram Ramaswamy, 1995 .

Game theoretic derivations of competitive strategies in conjoint analysis

S. Chan Choi, Wayne S. Desarbo, W. DeSarbo, 1993 .

A New Approach to Country Segmentation Utilizing Multinational Diffusion Patterns

Wayne S. DeSarbo, Kamel Jedidi, Kristiaan Helsen, 1993 .

A simulated annealing methodology for clusterwise linear regression

Wayne S. DeSarbo, Arvind Rangaswamy, Richard L. Oliver, 1989 .

An Interdisciplinary Review of Research in Conjoint Analysis: Recent Developments and Directions for Future Research

V. Rao, W. DeSarbo, N. Malhotra, 2015 .

Examining the behavioral manifestations of fan avidity in sports marketing

Wayne S. DeSarbo, Robert Madrigal, W. DeSarbo, 2011 .

A New Constrained Stochastic Multidimensional Scaling Vector Model. An Application to the Perceived Importance of Leadership Attributes

Crystal J. Scott, W. DeSarbo, 2011 .

Journal of Quantitative Analysis in Sports

Wayne S. DeSarbo, W. DeSarbo, 2010 .

Journal of Quantitative Analysis in Sports

W. DeSarbo, 2010 .

PSYCHOMETRIKA on an eigenstructure analysis of the normalized frequency matrix

W. DeSarbo, 2005 .

Incorporating Context Effects in the Multidimensional Scaling of 'Pick Any/N' Choice Data

Ju-Young Kim, Rabikar Chatterjee, Wayne S. DeSarbo, 1999 .

A New Stochastic Path Length Tree Methodology for Constructing Communication Networks

Wayne S. DeSarbo, Jaewun Cho, W. DeSarbo, 1991 .

The Stochastic Modeling of Purchase Intentions and Behavior

Wayne S. DeSarbo, Vicki G. Morwitz, Martin R. Young, 1998 .

Estimating Multiple Consumer Segment Ideal Points from Context-Dependent Survey Data

Simon J. Blanchard, Selin Atalay, Wayne S. DeSarbo, 2008 .

A latent class probit model for analyzing pick any/N data

Wayne S. DeSarbo, Geert De Soete, W. DeSarbo, 1991 .

Modeling Dynamic Effects in Repeated-Measures Experiments Involving Preference/Choice: An Illustration Involving Stated Preference Analysis

Wayne S. DeSarbo, Donald R. Lehmann, W. DeSarbo, 2004 .

Adaptive Multidimensional Scaling: Brand Positioning Based on Decision Sets and Dissimilarity Judgments

Michel Wedel, Wayne S. DeSarbo, Tammo H. A. Bijmolt, 2020, Customer Needs and Solutions.

Evolutionary preference/utility functions: A dynamic perspective

Wayne S. DeSarbo, Duncan K. H. Fong, John Liechty, 2005 .

Catscale: A Stochastic Multidimensional Scaling Methodology for the Spatial Analysis of Sorting Data and the Study of Stimulus Categorization

Wayne S. DeSarbo, Robert Libby, Kamel Jedidi, 1994 .

Two Stochastic Multidimensional Choice Models for Marketing Research

Wayne S. DeSarbo, J. Carroll, Geert De Soete, 1990 .

A New Multidimensional Scaling Methodology for the Representation of Inter-Product Substitutability

Wayne S. DeSarbo, Richard R. Batsell, W. DeSarbo, 1988 .

Constructing MDS Joint Spaces from Binary Choice Data: A Multidimensional Unfolding Threshold Model for Marketing Research

Donna L. Hoffman, Wayne S. Desarbo, W. DeSarbo, 1987 .

Constrained classification: The use of a priori information in cluster analysis

Wayne S. DeSarbo, Vijay Mahajan, W. DeSarbo, 1984 .

A Spatial Choice Model

W. DeSarbo, E. Keramidas, 1983 .

Strategic Capabilities and Radical Innovation: An Empirical Study in Three Countries

Wayne S. DeSarbo, Michael Song, C. Anthony Di Benedetto, 2008, IEEE Transactions on Engineering Management.

Two Classes of Stochastic Tree Unfolding Models

J. Carroll, W. DeSarbo, G. Soete, 1989 .

A Factorial Hidden Markov Model for the Analysis of Temporal Change in Choice Models

W. DeSarbo, D. K. Fong, Amirali Kani, 2018, Customer Needs and Solutions.

A hierarchical bayesian procedure for two-mode cluster analysis

Wayne S. DeSarbo, Duncan K. H. Fong, John Liechty, 2004 .

A new clustering methodology for the analysis of sorted or categorized stimuli

Kamel Jedidi, Michael D. Johnson, Wayne S. Desarbo, 1991 .

A Bayesian Approach to the Spatial Representation of Market Structure from Consumer Choice Data

Wayne S. DeSarbo, Michel Wedel, Duncan K. H. Fong, 1998, Eur. J. Oper. Res..

A Constrained Unfolding Methodology for Product Positioning

Wayne S. DeSarbo, Vithala R. Rao, V. Rao, 1986 .

Consideration Sets in Conjoint Analysis

Rajeev Kohli, Kamel Jedidi, Wayne S. Desarbo, 1996 .

A Heterogeneous Resource Based View for Exploring Relationships between Firm Performance and Capabilities

Michael Song, Anthony Di Benedetto, Wayne S. DeSarbo, 2007 .

The representation of three-way proximity data by single and multiple tree structure models

W. DeSarbo, Linda A. Clark, Wayne S. DeSarbo, 1984 .

Incorporating Group-Level Similarity Judgments in Conjoint Analysis

Wayne S. DeSarbo, Paul E. Green, Vithala R. Rao, 1978 .

Evaluating SBU Heterogeneity: Comparing the Miles and Snow Strategic Framework Against Alternative Quantitative Modeling Approaches

W. DeSarbo, Michael Song, 2008 .

Extending the Miles and Snow Strategic Framework: Strategic Types, Capabilities, Environmental Uncertainty, and Firm Performance

Anthony Di Benedetto, Michael Song, W. DeSarbo, 2006 .

Strategy Maps: A Spatial Representation of Intra-Industry Competitive Strategy

Wayne S. DeSarbo, Terence A. Oliva, Diana L. Day, 1987 .

A New Spatial Classification Methodology for Simultaneous Segmentation, Targeting, and Positioning (STP Analysis) for Marketing Research

Simon J. Blanchard, Selin Atalay, Wayne S. DeSarbo, 2008 .

Revisiting Customer Value Analysis in a Heterogeneous Market

Peter Ebbes, W. DeSarbo, C. C. Snow, 2010 .

Statistical perceptual maps: using confidence region ellipses to enhance the interpretations of brand positions in multidimensional scaling

W. DeSarbo, Douglas B. Grisaffe, D. Iacobucci, 2017, Journal of Marketing Analytics.

Fuzzy Clusterwise Generalized Structured Component Analysis

Heungsun Hwang, Yoshio Takane, Wayne S. Desarbo, 2007 .

Constrained canonical correlation

W. DeSarbo, Shen Lin, Wesley Thompson, 1982 .

REPRESENTING PHASED DECISION OUTCOMES

Wayne S. DeSarbo, Donald R. Lehmann, Wayne S. DeSarbo, 1996 .

Selecting Competitive Tactics: Try a Strategy Map

Wayne S. DeSarbo, Terence A. Oliva, Diana L. Day, 1987 .

A Gravity‐Based Multidimensional Scaling Model for Deriving Spatial Structures Underlying Consumer Preference/Choice Judgments

Juyoung Kim, W. DeSarbo, Juyoung Kim, 2002 .

Identifying Sources of Heterogeneity for Empirically Deriving Strategic Types: A Constrained Finite-Mixture Structural-Equation Methodology

Wayne S. DeSarbo, C. Anthony Di Benedetto, Michael Song, 2006, Manag. Sci..

A three-way clusterwise multidimensional unfolding procedure for the spatial representation of context dependent preferences

Wayne S. DeSarbo, A. Selin Atalay, Simon J. Blanchard, 2009, Comput. Stat. Data Anal..

On the Measurement of Perceived Service Quality: A Conjoint Analysis Approach

Wayne S. DeSarbo, Jungwhan Choi, Lenard C. Huff, 1993 .

Choice-Constrained Conjoint Analysis

Wayne S. DeSarbo, Paul E. Green, W. DeSarbo, 1984 .

A Latent Class Binomial Logit Methodology for the Analysis of Paired Comparison Choice Data: An Application Reinvestigating the Determinants of Perceived Risk

Wayne S. DeSarbo, Michel Wedel, W. DeSarbo, 1993 .

Restricted Principal Components Analysis for Marketing Research

Wayne S. DeSarbo, Robert Hausman, W. DeSarbo, 2007 .

Exploring the Demand Aspects of Sports Consumption and Fan Avidity

Wayne DeSarbo, Robert Madrigal, W. DeSarbo, 2012, Interfaces.

A New Heterogeneous Multidimensional Unfolding Procedure

W. DeSarbo, Joonwook Park, Priyali Rajagopal, 2012 .

A Quasi-Metric Approach to Multidimensional Unfolding for Reducing the Occurrence of Degenerate Solutions.

Wayne S. DeSarbo, Arvind Rangaswamy, Chulwan Kim, 1999, Multivariate behavioral research.

Genfold2: A General Unfolding Methodology for the Analysis of Preference/Dominance Data

V. Rao, W. DeSarbo, 1988 .

Additive Decomposition of Perceptions Data Via Conjoint Analysis

Paul E. Green, Wayne S. DeSarbo, W. DeSarbo, 1978 .

A General Multiple Distributed Lag Framework for Estimating the Dynamic Effects of Promotions

Wayne S. DeSarbo, Eelco Kappe, Ashley Stadler Blank, 2014, Manag. Sci..

The Impact of Product-Related Announcements on Consumer Purchase Intentions

Vijay Mahajan, Raymond R. Burke, Jaewun Cho, 1990 .

A Factorial Hidden Markov Model for the Analysis of Temporal Change in Choice Models

Wayne S. DeSarbo, Duncan K. H. Fong, Amirali Kani, 2018 .

Disaggregate Market Share Response Models

W. DeSarbo, Alexandru M. Degeratu, M. Saxton, 2002 .

An exponential family mixture MDS methodology for simultaneous segmentation and product positioning

W. DeSarbo, M. Wedel, M. Wedel, 1996 .

A Bayesian Multinomial Probit MODEL FOR THE ANALYSIS OF PANEL CHOICE DATA

Zhe Chen, Sunghoon Kim, Duncan K H Fong, 2016, Psychometrika.

Chapter 5 Non-spatial tree models for the assessment of competitive market structure: An integrated review of the marketing and psychometric literature

Wayne S. DeSarbo, Ajay K. Manrai, Lalita A. Manrai, 1993, Marketing.

Dynamic Strategic Groups: Deriving Spatial Evolutionary Paths

W. DeSarbo, Rajdeep Grewal, Rui Wang, 2009 .

A New Bayesian Spatial Model for Brand Positioning

Priyali Rajagopal, Wayne S. DeSarbo, Joonwook Park, 2017 .

A Hierarchical Bayesian Multidimensional Scaling Methodology for Accommodating Both Structural and Preference Heterogeneity

Wayne S. DeSarbo, John Liechty, Joonwook Park, 2008 .

CRISP: Customer response based iterative segmentation procedures for response modeling in direct marketing

Wayne S. DeSarbo, Venkatram Ramaswamy, W. DeSarbo, 1994 .

Mixture Regression Models

Michel Wedel, W. DeSarbo, M. Wedel, 2000 .

An Application of PARAFAC to a Small Sample Problem, Demonstrating Preprocessing, Orthogonality Constraints, and Split-Half Diagnostic Techniques (Appendix)

Wayne S. DeSarbo, W. DeSarbo, 1984 .

A Clusterwise Bilinear Multidimensional Scaling Methodology for Simultaneous Segmentation and Positioning Analyses

Wayne S. DeSarbo, Rajdeep Grewal, Crystal J. Scott, 2008 .

A Parametric Constrained Segmentation Methodology for Application in Sport Marketing

Qian Chen, Wayne S. DeSarbo, Ashley Stadler Blank, 2017 .

Market Segmentation for Customer Satisfaction Studies via a New Latent Structure Multidimensional Scaling Model

Wayne S. DeSarbo, Jianan Wu, W. DeSarbo, 2005 .

A new stochastic ultrametric tree unfolding methodology for assessing competitive market structure and deriving market segments

G. De Soete, Wayne S. DeSarbo, V. Ramaswamy, 1988 .

Applications of Multivariate Latent Variable Models in Marketing

Michel Wedel, Wagner A. Kamakura, Wayne S. DeSarbo, 2003 .

Care and Justice Moral Reasoning: A Multidimensional Scaling Approach

W. DeSarbo, Nancy Yacker, Sharon Lawner Weinberg, 1993, Multivariate behavioral research.

A New Multidimensional Scaling Methodology for the Analysis of Asymmetric Proximity Data in Marketing Research

Ajay K. Manrai, W. DeSarbo, A. Manrai, 1992 .

Market Segmentation for Customer Satisfaction Studies via a New Latent Structure Multidimensional Scaling Model

W. DeSarbo, Jianan Wu, 2005 .

Estimating Finite Mixtures of Ordinal Graphical Models

W. DeSarbo, Lingzhou Xue, Kevin H. Lee, 2021, Psychometrika.

The Heterogeneous P-Median Problem for Categorization Based Clustering

Simon J. Blanchard, W. DeSarbo, Daniel Aloise, 2012 .

INCENTIVE-ALIGNED CONJOINT ANALYSIS

Gary E. Bolton, Eric T. Bradlow, W. DeSarbo, 2004 .

A new clustering methodology for the analysis of sorted or categorized stimuli

W. DeSarbo, Kamel Jedidi, Michael D. Johnson, 1991 .

The Spatial Representation of Consumer Dispersion Patterns via a New Multi-level Latent Class Methodology

Ashley Stadler Blank, W. DeSarbo, J. Vermunt, 2021, Journal of Classification.

A random coefficients mixture hidden Markov model for marketing research

Wayne S. DeSarbo, Ashley Stadler Blank, Eelco Roel Kappe, 2018, International Journal of Research in Marketing.

An Integrated Approach toward the Spatial Modeling of Perceived Customer Value

W. DeSarbo, Indrajit Sinha, 1998 .

Latent Class Multidimensional Scaling. A Review of Recent Developments in the Marketing and Psychometric Literature

Wayne S. DeSarbo, Ajay K. Manrai, Lalita A. Manrai, 1994 .

Non-Spatial Tree Models for the Assessment of Competitive Market Structure: An Integrated Review of Marketing and Psychometric Literature

Lalita A. Manrai, W. DeSarbo, A. Manrai, 1993 .

A Parametric Constrained Segmentation Methodology for Application in Sport Marketing

W. DeSarbo, Ashley Stadler Blank, Qian Chen, 2017, Customer Needs and Solutions.

Constrained Stochastic Extended Redundancy Analysis

Heungsun Hwang, Eelco Kappe, Wayne S DeSarbo, 2013, Psychometrika.

The past, present, and future of measurement and methods in marketing analysis

Wayne S. DeSarbo, Donald R. Lehmann, John G. Lynch, 2020, Marketing Letters.

Optimal Advertising and Pricing for a Three-Stage Time-Lagged Monopolistic Diffusion Model Incorporating Income

W. DeSarbo, J. Eliashberg, Kamel Jedidi, 1989 .

A generalized ordinal finite mixture regression model for market segmentation

Wayne S. DeSarbo, Duncan K.H. Fong, Yifan Zhang, 2021 .

Three-Way Scaling and Clustering.

Wayne S. DeSarbo, Phipps Arabie, Wayne S. DeSarbo, 1989 .

Mixture Regression Models

W. DeSarbo, M. Wedel, 2000 .