Advances in Cluster Analysis Relevant to Marketing Research

[1]  J. W. Hutchinson,et al.  Pairwise partitioning: A nonmetric algorithm for identifying feature-based similarity structures , 1997 .

[2]  Daniel Baier,et al.  Marktforschung und Marketing Management: Computerbasierte Entscheidungsunterstützung , 1994 .

[3]  Michel Wedel,et al.  Fuzzy clusterwise regression in benefit segmentation: Application and investigation into its validity , 1993 .

[4]  D. Iacobucci,et al.  Modeling Dyadic Interactions and Networks in Marketing , 1992 .

[5]  V. Srinivasan,et al.  Evaluating the Multiple Effects of Retail Promotions on Brand Loyal and Brand Switching Segments , 1992 .

[6]  Paul E. Green,et al.  A Computational Study of Replicated Clustering with an Application to Market Segmentation , 1991 .

[7]  M. Wedel,et al.  A Clusterwise Regression Method for Simultaneous Fuzzy Market Structuring and Benefit Segmentation , 1991 .

[8]  Paul E. Green,et al.  Segmenting Markets with Conjoint Analysis , 1991 .

[9]  Michel Wedel,et al.  Segmenting retail markets on store image using a consumer-based methodology , 1991 .

[10]  W. Kamakura,et al.  Value Segmentation: A Model for the Measurement of Values and Value Systems , 1991 .

[11]  Rashi Glazer,et al.  Cognitive Geometry: An Analysis of Structure Underlying Representations of Similarity , 1991 .

[12]  Imran S. Currim,et al.  A Taxonomy of Consumer Purchase Strategies in a Promotion Intensive Environment , 1991 .

[13]  W. DeSarbo,et al.  Simultaneous multidimensional unfolding and cluster analysis: An investigation of strategic groups , 1991 .

[14]  Paul E. Green,et al.  Conjoint Analysis in Marketing: New Developments with Implications for Research and Practice , 1990 .

[15]  John R. Dickinson.  The Bibliography of Marketing Research Methods , 1990 .

[16]  Wayne S. DeSarbo,et al.  A nonspatial methodology for the analysis of two-way proximity data incorporating the distance-density hypothesis , 1990 .

[17]  Wayne S. DeSarbo,et al.  A simulated annealing methodology for clusterwise linear regression , 1989 .

[18]  Geert De Soete,et al.  Ultrametric tree representations of three-way three-mode data , 1989 .

[19]  Paul E. Green,et al.  Cross-Validation Assessment of Alternatives to Individual-Level Conjoint Analysis: A Case Study , 1989 .

[20]  W. R. Dillon,et al.  On the Use of Component Scores in the Presence of Group Structure , 1989 .

[21]  E. Ziegel.  Design, data, and analysis , 1989 .

[22]  Martin Schader,et al.  Clusterwise aggregation of relations , 1988 .

[23]  G. W. Milligan,et al.  A study of standardization of variables in cluster analysis , 1988 .

[24]  E. Fowlkes,et al.  Variable selection in clustering , 1988 .

[25]  W. DeSarbo,et al.  A maximum likelihood methodology for clusterwise linear regression , 1988 .

[26]  M. C. Cooper,et al.  The effect of measurement error on determining the number of clusters in clusteranalysis , 1988 .

[27]  W. Gaul,et al.  Data, expert knowledge and decisions , 1988 .

[28]  W. Kamakura.  A Least Squares Procedure for Benefit Segmentation with Conjoint Experiments , 1988 .

[29]  G. Soete.  OVWTRE: A program for optimal variable weighting for ultrametric and additive tree fitting , 1988 .

[30]  Claes Fornell,et al.  The Nature and Methodological Implications of the Cognitive Representation of Products , 1987 .

[31]  Wayne S. DeSarbo,et al.  Least squares algorithms for constructing constrained ultrametric and additive tree representations of symmetric proximity data , 1987 .

[32]  Jon R. Kettenring,et al.  Variable selection in clustering and other contexts , 1987 .

[33]  V. Srinivasan,et al.  A Simultaneous Approach to Market Segmentation and Market Structuring , 1987 .

[34]  D. Ennis,et al.  Market Segmentation: A Review , 1987 .

[35]  Kohsuke Ogawa,et al.  An Approach to Simultaneous Estimation and Segmentation in Conjoint Analysis , 1987 .

[36]  D. Whitlark,et al.  Benefit segmentation for industrial products , 1986 .

[37]  G. W. Milligan,et al.  A Study of the Comparability of External Criteria for Hierarchical Cluster Analysis. , 1986, Multivariate behavioral research.

[38]  G. Soete.  Optimal variable weighting for ultrametric and additive tree clustering , 1986 .

[39]  F. Robles,et al.  Segmenting the commuter aircraft market with cluster analysis , 1986 .

[40]  Paul E. Green,et al.  Buyer similarity measures in conjoint analysis: Some alternative proposals , 1985 .

[41]  W. DeSarbo,et al.  Optimal variable weighting for hierarchical clustering: An alternating least-squares algorithm , 1985 .

[42]  A. D. Gordon,et al.  Obtaining common pruned trees , 1985 .

[43]  G. W. Milligan,et al.  An examination of procedures for determining the number of clusters in a data set , 1985 .

[44]  John Saunders,et al.  Market Segmentation and Positioning in Specialized Industrial Markets , 1985 .

[45]  W. DeSarbo,et al.  The representation of three-way proximity data by single and multiple tree structure models , 1984 .

[46]  Paul R. Prabhaker,et al.  Notes on Aggregation Criteria in Market Segmentation , 1984 .

[47]  W. DeSarbo,et al.  On the Use of Hierarchical Clustering for the Analysis of Nonsymmetric Proximities , 1984 .

[48]  Wayne S. DeSarbo,et al.  Constrained classification: The use of a priori information in cluster analysis , 1984 .

[49]  Girish N. Punj,et al.  A Typology of Individual Search Strategies Among Purchasers of New Automobiles , 1984 .

[50]  J. Carroll,et al.  Synthesized clustering: A method for amalgamating alternative clustering bases with differential weighting of variables , 1984 .

[51]  Allan D. Shocker,et al.  A Customer-oriented Approach for Determining Market Structures , 1984 .

[52]  Wei-Chien Chang.  On using Principal Components before Separating a Mixture of Two Multivariate Normal Distributions , 1983 .

[53]  Girish N. Punj,et al.  Cluster Analysis in Marketing Research: Review and Suggestions for Application , 1983 .

[54]  W. DeSarbo.  Gennclus: New models for general nonhierarchical clustering analysis , 1982 .

[55]  Yoram Wind,et al.  The linking pin role in organizational buying centers , 1982 .

[56]  A. Tversky,et al.  Spatial versus tree representations of proximity data , 1982 .

[57]  Russell S. Winer,et al.  An Empirical Evaluation of Aggregation Approaches for Developing Market Segments , 1982 .

[58]  Imran S. Currim,et al.  Using Segmentation Approaches for Better Prediction and Understanding from Consumer Mode Choice Models , 1981 .

[59]  P. Arabie,et al.  Overlapping Clustering: A New Method for Product Positioning , 1981 .

[60]  Vithala R. Rao,et al.  Inference of Hierarchical Choice Processes from Panel Data , 1981 .

[61]  David Stewart,et al.  The Application and Misapplication of Factor Analysis in Marketing Research , 1981 .

[62]  William L. Moore,et al.  Levels of Aggregation in Conjoint Analysis: An Empirical Comparison , 1980 .

[63]  Gary L. Lilien,et al.  Industrial market segmentation by the structure of the purchasing process , 1980 .

[64]  P. Arabie,et al.  Mapclus: A mathematical programming approach to fitting the adclus model , 1980 .

[65]  Roger N. Shepard,et al.  Additive clustering: Representation of similarities as combinations of discrete overlapping properties. , 1979 .

[66]  Ronald L. Tatham,et al.  Optimal Construction of Experimental Clusters , 1979 .

[67]  P. Green,et al.  Conjoint Analysis in Consumer Research: Issues and Outlook , 1978 .

[68]  Yoram Wind,et al.  Issues and Advances in Segmentation Research , 1978 .

[69]  Vijay Mahajan,et al.  An Approach to Normative Segmentation , 1978 .

[70]  M. Venkatesan,et al.  Behavioral Models for Market Analysis: Foundations for Marketing Action , 1978 .

[71]  Yoram Wind,et al.  Introduction to Special Section on Market Segmentation Research , 1978 .

[72]  L. Hubert,et al.  A Graph-Theoretic Approach to Goodness-of-Fit in Complete-Link Hierarchical Clustering , 1976 .

[73]  J. Hartigan.  Clustering Algorithms , 1975 .

[74]  Bell Telephone,et al.  ROBUST ESTIMATES, RESIDUALS, AND OUTLIER DETECTION WITH MULTIRESPONSE DATA , 1972 .

[75]  George S. Day,et al.  Using Cluster Analysis to Improve Marketing Experiments , 1971 .

[76]  S. Fienberg.  An Iterative Procedure for Estimation in Contingency Tables , 1970 .

[77]  Paul E. Green,et al.  Cluster Analysis in Test Market Selection , 1967 .

[78]  J. H. Ward.  Hierarchical Grouping to Optimize an Objective Function , 1963 .

[79]  Robert R. Sokal,et al.  A statistical method for evaluating systematic relationships , 1958 .

[80]  W. Deming,et al.  On a Least Squares Adjustment of a Sampled Frequency Table When the Expected Marginal Totals are Known , 1940 .

[81]  G. W. Milligan,et al.  CLUSTERING VALIDATION: RESULTS AND IMPLICATIONS FOR APPLIED ANALYSES , 1996 .

[82]  G. De Soete,et al.  Clustering and Classification , 2019, Data-Driven Science and Engineering.

[83]  J. Carroll,et al.  K-means clustering in a low-dimensional Euclidean space , 1994 .

[84]  M. Schader,et al.  New Approaches in Classification and Data Analysis , 1994 .

[85]  P. Arabie,et al.  Cluster analysis in marketing research , 1994 .

[86]  Yoram Wind,et al.  Marketing and Social Networks , 1994 .

[87]  M Wedel,et al.  MARKET-SEGMENTATION RESEARCH - A REVIEW OF BASES AND METHODS WITH SPECIAL EMPHASIS ON LATENT CLASS MODELS , 1993 .

[88]  Wayne S. DeSarbo,et al.  Chapter 5 Non-spatial tree models for the assessment of competitive market structure: An integrated review of the marketing and psychometric literature , 1993, Marketing.

[89]  Martin Schader,et al.  Analyzing and Modeling Data and Knowledge , 1992 .

[90]  L. Hubert,et al.  Combinatorial Data Analysis , 1992 .

[91]  F. Rohlf,et al.  NTSYS-pc Numerical Taxonomy and Multivariate Analysis System, version 2.1: Owner manual , 1992 .

[92]  Allan D. Shocker,et al.  Determining the competitive structure of product-markets : practices, issues, and suggestions , 1990 .

[93]  Martin Schader,et al.  Knowledge, Data and Computer-Assisted Decisions , 1990, NATO ASI Series.

[94]  Hans-Hermann Bock,et al.  Classification and Related Methods of Data Analysis , 1988 .

[95]  Fionn Murtagh,et al.  A Survey of Algorithms for Contiguity-Constrained Clustering and Related Problems , 1985, Comput. J..

[96]  T. Klastorin.  The p-Median Problem for Cluster Analysis: A Comparative Test Using the Mixture Model Approach , 1985 .

[97]  P. Slater.  Tree representations of internal migration flows and related topics , 1984 .

[98]  Lawrence Mayer,et al.  Proximity and Preference: Problems in the Multidimensional Analysis of Large Data Sets , 1982 .

[99]  Rajendra K. Srivastava,et al.  Usage-Situational Influences on Perceptions of Product-Markets: N theoretical and Empirical Issues , 1981 .

[100]  Gary L. Lilien,et al.  Market planning for new industrial products , 1980 .

[101]  Anil K. Jain,et al.  Validity studies in clustering methodologies , 1979, Pattern Recognit..

[102]  H. L. Le Roy,et al.  Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability; Vol. IV , 1969 .

[103]  J. MacQueen.  Some methods for classification and analysis of multivariate observations , 1967 .