Emergent clustering methods for empirical OM research
暂无分享,去创建一个
Michael J. Brusco | J. Dennis Cradit | Douglas Steinley | Renu Singh | M. Brusco | D. Steinley | Renu Singh | J. Cradit
[1] K. Pearson. Contributions to the Mathematical Theory of Evolution , 1894 .
[2] F. Heider. Attitudes and cognitive organization. , 1946, The Journal of psychology.
[3] F. Harary,et al. STRUCTURAL BALANCE: A GENERALIZATION OF HEIDER'S THEORY1 , 1977 .
[4] F. Heider. The psychology of interpersonal relations , 1958 .
[5] J. H. Ward. Hierarchical Grouping to Optimize an Objective Function , 1963 .
[6] J. Morgan,et al. Problems in the Analysis of Survey Data, and a Proposal , 1963 .
[7] E. Forgy. Cluster analysis of multivariate data : efficiency versus interpretability of classifications , 1965 .
[8] J. Davis. Clustering and Structural Balance in Graphs , 1967 .
[9] J. MacQueen. Some methods for classification and analysis of multivariate observations , 1967 .
[10] H. L. Le Roy,et al. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability; Vol. IV , 1969 .
[11] Hrishikesh D. Vinod Mathematica. Integer Programming and the Theory of Grouping , 1969 .
[12] J. Wolfe. PATTERN CLUSTERING BY MULTIVARIATE MIXTURE ANALYSIS. , 1970, Multivariate behavioral research.
[13] H. White,et al. “Structural Equivalence of Individuals in Social Networks” , 2022, The SAGE Encyclopedia of Research Design.
[14] M. Rao. Cluster Analysis and Mathematical Programming , 1971 .
[15] Michael R. Anderberg,et al. Cluster Analysis for Applications , 1973 .
[16] Brian Everitt,et al. Cluster analysis , 1974 .
[17] P. Arabie,et al. An algorithm for clustering relational data with applications to social network analysis and comparison with multidimensional scaling , 1975 .
[18] John A. Hartigan,et al. Clustering Algorithms , 1975 .
[19] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[20] Phipps Arabie,et al. Constructing blockmodels: How and why , 1978 .
[21] G. Schwarz. Estimating the Dimension of a Model , 1978 .
[22] R E Miles,et al. Organizational strategy, structure, and process. , 1978, Academy of management review. Academy of Management.
[23] Roger N. Shepard,et al. Additive clustering: Representation of similarities as combinations of discrete overlapping properties. , 1979 .
[24] J. A. Hartigan,et al. A k-means clustering algorithm , 1979 .
[25] Rolph E. Anderson,et al. Multivariate Data Analysis with Readings , 1979 .
[26] Maurice K. Wong,et al. Algorithm AS136: A k-means clustering algorithm. , 1979 .
[27] P. Arabie,et al. Mapclus: A mathematical programming approach to fitting the adclus model , 1980 .
[28] Pierre Hansen,et al. Bicriterion Cluster Analysis , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[29] G. V. Kass. An Exploratory Technique for Investigating Large Quantities of Categorical Data , 1980 .
[30] P. Arabie,et al. Overlapping Clustering: A New Method for Product Positioning , 1981 .
[31] J. Bezdek,et al. DETECTION AND CHARACTERIZATION OF CLUSTER SUBSTRUCTURE I. LINEAR STRUCTURE: FUZZY c-LINES* , 1981 .
[32] Richard A. Johnson,et al. Applied Multivariate Statistical Analysis , 1983 .
[33] Girish N. Punj,et al. Cluster Analysis in Marketing Research: Review and Suggestions for Application , 1983 .
[34] Kathryn B. Laskey,et al. Stochastic blockmodels: First steps , 1983 .
[35] K. Reitz,et al. Graph and Semigroup Homomorphisms on Networks of Relations , 1983 .
[36] M. Aldenderfer. Cluster Analysis , 1984 .
[37] M. M. Meyer,et al. Statistical Analysis of Multiple Sociometric Relations. , 1985 .
[38] T. Klastorin. The p-Median Problem for Cluster Analysis: A Comparative Test Using the Mixture Model Approach , 1985 .
[39] W. Kamakura. A Least Squares Procedure for Benefit Segmentation with Conjoint Experiments , 1988 .
[40] George B. Macready,et al. Concomitant-Variable Latent-Class Models , 1988 .
[41] W. DeSarbo,et al. A maximum likelihood methodology for clusterwise linear regression , 1988 .
[42] M. Wedel,et al. A fuzzy clusterwise regression approach to benefit segmentation , 1989 .
[43] M. Wedel,et al. Consumer benefit segmentation using clusterwise linear regression , 1989 .
[44] Arshad M. Khan,et al. Innovative and Noninnovative Small Firms: Types and Characteristics , 1989 .
[45] Wayne S. DeSarbo,et al. A simulated annealing methodology for clusterwise linear regression , 1989 .
[46] W. Pitts,et al. A Logical Calculus of the Ideas Immanent in Nervous Activity (1943) , 2021, Ideas That Created the Future.
[47] Peter J. Rousseeuw,et al. Finding Groups in Data: An Introduction to Cluster Analysis , 1990 .
[48] Barbara B. Flynn,et al. Empirical research methods in operations management , 1990 .
[49] H. Späth. Mathematical algorithms for linear regression , 1991 .
[50] A. Ferligoj,et al. Direct multicriteria clustering algorithms , 1992 .
[51] J. Ross Quinlan,et al. C4.5: Programs for Machine Learning , 1992 .
[52] G. Celeux,et al. A Classification EM algorithm for clustering and two stochastic versions , 1992 .
[53] A. Ferligoj,et al. Direct and indirect methods for structural equivalence , 1992 .
[54] A. Raftery,et al. Model-based Gaussian and non-Gaussian clustering , 1993 .
[55] Stanley Wasserman,et al. Social Network Analysis: Methods and Applications , 1994 .
[56] Varghese S. Jacob,et al. A study of the classification capabilities of neural networks using unsupervised learning: A comparison withK-means clustering , 1994 .
[57] A. Roth,et al. A taxonomy of manufacturing strategies , 1994 .
[58] P. Paatero,et al. Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values† , 1994 .
[59] E. L. Ulungu,et al. Multi‐objective combinatorial optimization problems: A survey , 1994 .
[60] Teuvo Kohonen,et al. Self-Organizing Maps , 2010 .
[61] S. Wathen. Manufacturing strategy in business units , 1995 .
[62] Christopher M. Bishop,et al. Neural networks for pattern recognition , 1995 .
[63] W. DeSarbo,et al. Typologies of Compulsive Buying Behavior: A Constrained Clusterwise Regression Approach , 1996 .
[64] Varghese S. Jacob,et al. Comparative performance of the FSCL neural net and K-means algorithm for market segmentation , 1996 .
[65] G. W. Milligan,et al. CLUSTERING VALIDATION: RESULTS AND IMPLICATIONS FOR APPLIED ANALYSES , 1996 .
[66] Paul E. Green,et al. Modifying Cluster-Based Segments to Enhance Agreement with an Exogenous Response Variable , 1996 .
[67] P. Doreian,et al. A partitioning approach to structural balance , 1996 .
[68] David West,et al. A comparison of SOM neural network and hierarchical clustering methods , 1996 .
[69] Kenneth K. Boyer,et al. Approaches to the factory of the future. An empirical taxonomy , 1996 .
[70] David J. Ketchen,et al. THE APPLICATION OF CLUSTER ANALYSIS IN STRATEGIC MANAGEMENT RESEARCH: AN ANALYSIS AND CRITIQUE , 1996 .
[71] M. Wedel,et al. Metric Conjoint Segmentation Methods: A Monte Carlo Comparison , 1996 .
[72] Pierre Hansen,et al. Cluster analysis and mathematical programming , 1997, Math. Program..
[73] J. Carroll,et al. A Feature-Based Approach to Market Segmentation via Overlapping K-Centroids Clustering , 1997 .
[74] W. Loh,et al. SPLIT SELECTION METHODS FOR CLASSIFICATION TREES , 1997 .
[75] M. Wedel,et al. Market Segmentation: Conceptual and Methodological Foundations , 1997 .
[76] Daniel J. Brass,et al. Social Networks and Perceptions of Intergroup Conflict: The Role of Negative Relationships and Third Parties , 1998 .
[77] W. DeSarbo,et al. Combinatorial Optimization Approaches to Constrained Market Segmentation: An Application to Industrial Market Segmentation , 1998 .
[78] Jason F. Schreer,et al. Classification of Dive Profiles: A Comparison of Statistical Clustering Techniques and Unsupervised Artificial Neural Networks , 1998 .
[79] Niels G. Waller,et al. A comparison of the classification capabilities of the 1-dimensional kohonen neural network with two pratitioning and three hierarchical cluster analysis algorithms , 1998 .
[80] Adrian E. Raftery,et al. MCLUST: Software for Model-Based Cluster Analysis , 1999 .
[81] P. Green,et al. A Generalized Rand-Index Method for Consensus Clustering of Separate Partitions of the Same Data Base , 1999 .
[82] H. Sebastian Seung,et al. Learning the parts of objects by non-negative matrix factorization , 1999, Nature.
[83] Larry P. Ritzman,et al. REVISITING ALTERNATIVE THEORETICAL PARADIGMS IN MANUFACTURING STRATEGY , 2000 .
[84] Rohit Verma,et al. Configurations of low-contact services , 2000 .
[85] Robert Tibshirani,et al. Estimating the number of clusters in a data set via the gap statistic , 2000 .
[86] Martin G. Everett,et al. Models of core/periphery structures , 2000, Soc. Networks.
[87] G. Stock,et al. Enterprise logistics and supply chain structure: the role of fit , 2000 .
[88] Ravi Kathuria. Competitive priorities and managerial performance: a taxonomy of small manufacturers , 2000 .
[89] B. Muthén,et al. Integrating person-centered and variable-centered analyses: growth mixture modeling with latent trajectory classes. , 2000, Alcoholism, clinical and experimental research.
[90] Geoffrey J. McLachlan,et al. Finite Mixture Models , 2019, Annual Review of Statistics and Its Application.
[91] Aleda V. Roth,et al. Agility in Retail Banking: A Numerical Taxonomy of Strategic Service Groups , 2001, Manuf. Serv. Oper. Manag..
[92] J. R. Dixon,et al. A taxonomy of manufacturing strategies revisited , 2001 .
[93] M. Frohlich,et al. Arcs of integration: an international study of supply chain strategies , 2001 .
[94] Angel R. Martinez,et al. Computational Statistics Handbook with MATLAB , 2001 .
[95] T. Snijders,et al. Estimation and Prediction for Stochastic Blockstructures , 2001 .
[96] Jay Magidson,et al. Latent class models for clustering : a comparison with K-means , 2002 .
[97] R. Narasimhan,et al. Effect of supply chain integration on the relationship between diversification and performance: evidence from Japanese and Korean firms , 2002 .
[98] B. Muthén. BEYOND SEM: GENERAL LATENT VARIABLE MODELING , 2002 .
[99] Michael J. Brusco,et al. A Simulated Annealing Heuristic for a Bicriterion Partitioning Problem in Market Segmentation , 2002 .
[100] Melody Y. Kiang,et al. Extending the Kohonen self-organizing map networks for clustering analysis , 2002 .
[101] Michael J. Brusco,et al. Multicriterion Clusterwise Regression for Joint Segmentation Settings: An Application to Customer Value , 2003 .
[102] Peter T. Ward,et al. A mapping of competitive priorities, manufacturing practices, and operational performance in groups of Danish manufacturing companies , 2003 .
[103] Douglas Steinley,et al. Local optima in K-means clustering: what you don't know may hurt you. , 2003, Psychological methods.
[104] M. S. Díaz,et al. A view of developing patterns of investment in AMT through empirical taxonomies: new evidence , 2003 .
[105] R. Cagliano,et al. E‐business strategy , 2003 .
[106] Kenneth K. Boyer,et al. Factors influencing the utilization of Internet purchasing in small organizations , 2003 .
[107] S. Borgatti,et al. The Network Paradigm in Organizational Research: A Review and Typology , 2003 .
[108] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[109] Xiande Zhao,et al. Quality management and organizational context in selected service industries of China , 2004 .
[110] F. Leisch. FlexMix: A general framework for finite mixture models and latent class regression in R , 2004 .
[111] Vladimir Batagelj,et al. Generalized blockmodeling of two-mode network data , 2004, Soc. Networks.
[112] Mauricio G. C. Resende,et al. A Hybrid Heuristic for the p-Median Problem , 2004, J. Heuristics.
[113] W. DeSarbo,et al. Revisiting the Miles and Snow Strategic Framework: Uncovering Interrelationships between Strategic Types, Capabilities, Environmental Uncertainty, and Firm Performance , 2005 .
[114] James D. Westphal,et al. Identity Confirmation Networks and Cooperation in Workgroups , 2005 .
[115] Vladimir Batagelj,et al. Exploratory Social Network Analysis with Pajek , 2005 .
[116] Helmuth Späth,et al. Algorithm 39 Clusterwise linear regression , 1979, Computing.
[117] Helmuth Späth,et al. A fast algorithm for clusterwise linear regression , 1982, Computing.
[118] Soo Wook Kim,et al. An exploratory study of manufacturing practice and performance interrelationships: Implications for capability progression , 2005 .
[119] H. Boer,et al. Patterns of change in manufacturing strategy configurations , 2005 .
[120] Sueli Aparecida Mingoti,et al. Comparing SOM neural network with Fuzzy c , 2006, Eur. J. Oper. Res..
[121] Lothar Thiele,et al. A systematic comparison and evaluation of biclustering methods for gene expression data , 2006, Bioinform..
[122] Claude Tadonki,et al. Solving the p-Median Problem with a Semi-Lagrangian Relaxation , 2006, Comput. Optim. Appl..
[123] John P. Boyd,et al. Computing core/periphery structures and permutation tests for social relations data , 2004, Soc. Networks.
[124] M. Brusco,et al. Inducing a blockmodel structure of two-mode binary data using seriation procedures , 2006 .
[125] Karen E. Papke-Shields,et al. Evolution in the strategic manufacturing planning process of organizations , 2006 .
[126] Chee-Chuong Sum,et al. A taxonomy of manufacturing strategies in China , 2006 .
[127] D. Steinley. Profiling local optima in K-means clustering: developing a diagnostic technique. , 2006, Psychological methods.
[128] Gary L. Lilien,et al. Location, Location, Location: How Network Embeddedness Affects Project Success in Open Source Systems , 2006, Manag. Sci..
[129] Soo Wook Kim,et al. Disentangling leanness and agility: An empirical investigation , 2006 .
[130] Daniel J. Brass,et al. Exploring the Social Ledger: Negative Relationships and Negative Asymmetry in Social Networks in Organizations , 2006 .
[131] W. Kamakura,et al. Household Life Cycles and Lifestyles in the United States , 2006 .
[132] R. Srinivasan,et al. Dual Distribution and Intangible Firm Value: Franchising in Restaurant Chains , 2006 .
[133] Joshua D. Knowles,et al. An Evolutionary Approach to Multiobjective Clustering , 2007, IEEE Transactions on Evolutionary Computation.
[134] Deborah F. Swayne,et al. Interactive and Dynamic Graphics for Data Analysis - With R and GGobi , 2007, Use R.
[135] M. Brusco,et al. A variable neighborhood search method for generalized blockmodeling of two-mode binary matrices , 2007 .
[136] Igor Vasil'ev,et al. Computational study of large-scale p-Median problems , 2007, Math. Program..
[137] J. Ledolter,et al. Estimating Promotion Response When Competitive Promotions Are Unobservable , 2007 .
[138] Michele Leone,et al. Clustering by soft-constraint affinity propagation: applications to gene-expression data , 2007, Bioinform..
[139] Michael J. Brusco,et al. Initializing K-means Batch Clustering: A Critical Evaluation of Several Techniques , 2007, J. Classif..
[140] Delbert Dueck,et al. Clustering by Passing Messages Between Data Points , 2007, Science.
[141] M. Brusco,et al. Selection of Variables in Cluster Analysis: An Empirical Comparison of Eight Procedures , 2008 .
[142] Ulrike von Luxburg,et al. A tutorial on spectral clustering , 2007, Stat. Comput..
[143] Wayne S. DeSarbo,et al. A Clusterwise Bilinear Multidimensional Scaling Methodology for Simultaneous Segmentation and Positioning Analyses , 2008 .
[144] Hans-Friedrich Köhn,et al. Comment on "Clustering by Passing Messages Between Data Points" , 2008, Science.
[145] Lodewyk F. A. Wessels,et al. Biclustering Sparse Binary Genomic Data , 2008, J. Comput. Biol..
[146] Friedrich Leisch,et al. A toolbox for bicluster analysis in R , 2008 .
[147] Chi-Ming Chen. Classification of scientific networks using aggregated journal-journal citation relations in the Journal Citation Reports , 2008 .
[148] W. DeSarbo,et al. Hybrid Strategic Groups , 2008 .
[149] Douglas Steinley,et al. A New Variable Weighting and Selection Procedure for K-means Cluster Analysis , 2008, Multivariate behavioral research.
[150] Gavin L. Fox,et al. Cautionary Remarks on the Use of Clusterwise Regression , 2008, Multivariate behavioral research.
[151] Carol T. Kulik,et al. Known by the Company We Keep: Stigma-By-Association Effects in the Workplace , 2008 .
[152] W. Stuetzle,et al. Clustering with Confidence: A Binning Approach , 2008 .
[153] Zeinep Aksin Karaesman,et al. Effective strategies for internal outsourcing and offshoring of business services: An empirical investigation , 2008 .
[154] Edoardo M. Airoldi,et al. Mixed Membership Stochastic Blockmodels , 2007, NIPS.
[155] Oded Netzer,et al. A Hidden Markov Model of Customer Relationship Dynamics , 2008, Mark. Sci..
[156] A. Bhalla,et al. Is more IT offshoring better? An exploratory study of western companies offshoring to South East Asia , 2008 .
[157] Kenneth K. Boyer,et al. Supply chain information flow strategies: an empirical taxonomy , 2009 .
[158] Patrick J. F. Groenen,et al. Optimization Strategies for Two-Mode Partitioning , 2009, J. Classif..
[159] G. Tutz,et al. An introduction to recursive partitioning: rationale, application, and characteristics of classification and regression trees, bagging, and random forests. , 2009, Psychological methods.
[160] Edoardo M. Airoldi,et al. A Survey of Statistical Network Models , 2009, Found. Trends Mach. Learn..
[161] Michael J. Brusco,et al. Cross validation issues in multiobjective clustering. , 2009, The British journal of mathematical and statistical psychology.
[162] Sanghamitra Bandyopadhyay,et al. A new multiobjective clustering technique based on the concepts of stability and symmetry , 2010, Knowledge and Information Systems.
[163] M. Brusco,et al. Clustering Qualitative Data Based on Binary Equivalence Relations: Neighborhood Search Heuristics for the Clique Partitioning Problem , 2009 .
[164] S. Borgatti,et al. On Social Network Analysis in a Supply Chain Context , 2009 .
[165] Gyula Vastag,et al. Revisiting ISO 14000 Diffusion: A New “Look” at the Drivers of Certification , 2009 .
[166] Michael J. Brusco,et al. Exemplar-Based Clustering via Simulated Annealing , 2009 .
[167] P. Bickel,et al. A nonparametric view of network models and Newman–Girvan and other modularities , 2009, Proceedings of the National Academy of Sciences.
[168] W. DeSarbo,et al. Dynamic Strategic Groups: Deriving Spatial Evolutionary Paths , 2009 .
[169] Patrick Doreian,et al. Partitioning signed social networks , 2009, Soc. Networks.
[170] Gregory R. Heim,et al. SERVICE PROCESS CONFIGURATIONS IN ELECTRONIC RETAILING: A TAXONOMIC ANALYSIS OF ELECTRONIC FOOD RETAILERS , 2002 .
[171] Kenneth K. Boyer,et al. Analysis of Effects of Operational Execution on Repeat Purchasing for Heterogeneous Customer Segments , 2006 .
[172] R. Cagliano,et al. Evolutionary patterns in e‐business strategy , 2009 .
[173] M. Brusco,et al. K-balance partitioning: an exact method with applications to generalized structural balance and other psychological contexts. , 2010, Psychological methods.
[174] Ying Liu,et al. Multicriterion Market Segmentation: A New Model, Implementation, and Evaluation , 2010, Mark. Sci..
[175] A. Roth,et al. The effect of an ambidextrous supply chain strategy on combinative competitive capabilities and business performance , 2010 .
[176] M. Brusco,et al. The p-median model as a tool for clustering psychological data. , 2010, Psychological methods.
[177] W. DeSarbo,et al. Modeling strategic group dynamics: A hidden Markov approach , 2010 .
[178] Rick L. Andrews,et al. An Empirical Comparison of Methods for Clustering Problems: Are There Benefits from Having a Statistical Model? , 2010 .
[179] Benjamin M. Galvin,et al. Spreading the Word: The Role of Surrogates in Charismatic Leadership Processes , 2010 .
[180] Barbara B. Flynn,et al. The impact of supply chain integration on performance: A contingency and configuration approach , 2010 .
[181] Stephen J Tueller,et al. Evaluation of Structural Equation Mixture Models: Parameter Estimates and Correct Class Assignment , 2010, Structural equation modeling : a multidisciplinary journal.
[182] Michael J. Brusco,et al. Amalgamation of partitions from multiple segmentation bases: A comparison of non-model-based and model-based methods , 2010, Eur. J. Oper. Res..
[183] Sach Mukherjee,et al. Temporal clustering by affinity propagation reveals transcriptional modules in Arabidopsis thaliana , 2010, Bioinform..
[184] Wei-Yin Loh,et al. Classification and regression trees , 2011, WIREs Data Mining Knowl. Discov..
[185] Michael J. Brusco,et al. Analysis of two-mode network data using nonnegative matrix factorization , 2011, Soc. Networks.
[186] Michael J. Brusco,et al. An exact algorithm for a core/periphery bipartitioning problem , 2011, Soc. Networks.
[187] M. Brusco,et al. K-Means Clustering and Mixture Model Clustering: Reply to McLachlan (2011) and Vermunt (2011) , 2011 .
[188] P. Valero-Mora,et al. Using Interactive Graphics to Teach Multivariate Data Analysis to Psychology Students , 2011 .
[189] M. Brusco,et al. Two Algorithms for Relaxed Structural Balance Partitioning: Linking Theory, Models, and Data to Understand Social Network Phenomena , 2011 .
[190] Timothy M. Laseter,et al. Through the service operations strategy looking glass: Influence of industrial sector, ownership, and service offerings on B2B e-marketplace failures , 2011 .
[191] P. Hanges,et al. Latent Class Procedures: Applications to Organizational Research , 2011 .
[192] M. Brusco,et al. Evaluating mixture modeling for clustering: recommendations and cautions. , 2011, Psychological methods.
[193] J. Vermunt. K-means may perform as well as mixture model clustering but may also be much worse: comment on Steinley and Brusco (2011). , 2011, Psychological methods.
[194] Michael J. Brusco,et al. Clusterwise p* models for social network analysis , 2011, Stat. Anal. Data Min..
[195] John H. Morris,et al. Improving the quality of protein similarity network clustering algorithms using the network edge weight distribution , 2011, Bioinform..
[196] G. McLachlan,et al. Commentary on Steinley and Brusco (2011): Recommendations and Cautions , 2022 .
[197] M. Brusco,et al. Choosing the number of clusters in Κ-means clustering. , 2011, Psychological methods.