Exploration of the investment patterns of potential retail banking customers using two-stage cluster analysis

[1]  Michael C. C. Thomsett,et al.  The Digital Banking Revolution: How Fintech Companies Are Transforming the Retail Banking Industry Through Disruptive Financial Innovation , 2019 .

[2]  Camelia M. Kuhnen,et al.  Socioeconomic Status and Learning from Financial Information , 2015 .

[3]  Sandra Loureiro,et al.  Artificial intelligence in business: State of the art and future research agenda , 2020, Journal of Business Research.

[4]  Angela Tregear,et al.  Inter‐firm relations in SME clusters and the link to marketing performance , 2011 .

[5]  Tie-jun Zhang,et al.  Case study on cluster analysis of the telecom customers based on consumers' behavior , 2011, 2011 IEEE 18th International Conference on Industrial Engineering and Engineering Management.

[6]  Esther Calderón-Monge,et al.  Analysis of sustainable consumer behavior as a business opportunity , 2020 .

[7]  A. Edmondson,et al.  METHODOLOGICAL FIT IN MANAGEMENT FIELD RESEARCH. , 2007 .

[8]  Zengyou He,et al.  Clustering Mixed Numeric and Categorical Data: A Cluster Ensemble Approach , 2005, ArXiv.

[9]  G. Barczak,et al.  Developing typologies of consumer motives for use of technologically based banking services , 1997 .

[10]  S. K. Mehta,et al.  Saving and Investment Pattern: Assessment and Prospects , 2019, ACRN Journal of Finance and Risk Perspectives.

[11]  Stan Maklan,et al.  Customer Experience : Are we Measuring the Right Things ? 1 Customer Experience : Are We Measuring the Right Things ? , 2012 .

[12]  Alireza Pooya,et al.  Design of an artificial intelligence system for predicting success of new product development and selecting proper market-product strategy in the food industry , 2018, International Food and Agribusiness Management Review.

[13]  Enrique Herrera-Viedma,et al.  A risk-aware fuzzy linguistic knowledge-based recommender system for hedge funds , 2019, ITQM.

[14]  Johannes Gehrke,et al.  CACTUS—clustering categorical data using summaries , 1999, KDD '99.

[15]  Natalya V. Razmochaeva,et al.  Research of artificial intelligence in the retail management problems , 2017, 2017 IEEE II International Conference on Control in Technical Systems (CTS).

[16]  Teuvo Kohonen,et al.  Self-organized formation of topologically correct feature maps , 2004, Biological Cybernetics.

[17]  Ian R. Hodgkinson,et al.  Customer experience driven business model innovation , 2020, Journal of Business Research.

[18]  Laurie J. Sampsel.  Voyant Tools , 2018, Music Reference Services Quarterly.

[19]  Manminder Singh Saluja,et al.  Decoding Investment Pattern of FIIs and DIIs in Indian Stock Market using Decision Tree , 2017 .

[20]  Alina Elena Oprescu,et al.  The strategic marketing planning – General Framework for Customer Segmentation , 2014 .

[21]  Ying Li,et al.  Research on Customer Segmentation Based on a Two-Stage SOM Clustering Algorithm , 2009, 2009 International Conference on Management and Service Science.

[22]  Y. Lai,et al.  Factors affecting firm's R&D investment decisions , 2015 .

[23]  Roberto S. Santos,et al.  Risk Capital and Emerging Technologies: Innovation and Investment Patterns Based on Artificial Intelligence Patent Data Analysis , 2019 .

[24]  Teuvo Kohonen,et al.  The self-organizing map , 1990 .

[25]  Pāvels Gončarovs.  Using Data Analytics for Customers Segmentation: Experimental Study at a Financial Institution , 2018, 2018 59th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS).

[26]  Natalia Vila-López,et al.  Mature market segmentation: a comparison of artificial neural networks and traditional methods , 2010, Neural Computing and Applications.

[27]  Feng Lin,et al.  Customer segmentation analysis based on SOM clustering , 2008, 2008 IEEE International Conference on Service Operations and Logistics, and Informatics.

[28]  J. Sharma,et al.  Segmenting Investors on their Biases Manifested in Investment Decision-Making by Individual Investors , 2021, SEISENSE Journal of Management.

[29]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[30]  P. Klaus,et al.  Measuring customer experience quality: The EXQ scale revisited , 2020 .

[31]  George T. S. Ho,et al.  A Financial Data Mining Model for Extracting Customer Behavior , 2011 .

[32]  Angeline G. Close.  Online consumer behavior : theory and research in social media, advertising, and e-tail , 2012 .

[33]  Philipp Klaus,et al.  Measuring Customer Experience , 2015 .

[34]  Robert Tibshirani,et al.  Estimating the number of clusters in a data set via the gap statistic , 2000 .

[35]  Thomas H. Stevenson,et al.  Financial services consumption behavior across Hispanic American consumers , 2005 .

[36]  Seung-hwan Lee,et al.  How investor behavioral factors influence investment satisfaction, trust in investment company, and reinvestment intention , 2008 .

[37]  Sudipto Guha,et al.  ROCK: a robust clustering algorithm for categorical attributes , 1999, Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337).

[38]  R. J. Kuo,et al.  Integration of self-organizing feature map and K-means algorithm for market segmentation , 2002, Comput. Oper. Res..

[39]  Ron Wehrens,et al.  Flexible Self-Organizing Maps in kohonen 3.0 , 2018 .

[40]  D. Merunka,et al.  When consumers love their brands: Exploring the concept and its dimensions , 2008 .

[41]  Gebräuchliche Fertigarzneimittel,et al.  V , 1893, Therapielexikon Neurologie.

[42]  P. Rousseeuw,et al.  Partitioning Around Medoids (Program PAM) , 2008 .

[43]  Michael C. C. Thomsett,et al.  The Digital Banking Revolution , 2017 .

[44]  Donald C. Wunsch,et al.  Clustering Data of Mixed Categorical and Numerical Type With Unsupervised Feature Learning , 2015, IEEE Access.

[45]  Andrew N. Green,et al.  Social CRM as a business strategy , 2011 .

[46]  Ting-Hsuan Chen,et al.  Investor personality predicts investment performance? A statistics and machine learning model investigation , 2019, Comput. Hum. Behav..

[47]  A. Athanassopoulos.  Customer Satisfaction Cues To Support Market Segmentation and Explain Switching Behavior , 2000 .

[48]  D. Arli.  Investigating consumer ethics: a segmentation study , 2017 .

[49]  A. Persson,et al.  Making customer relationship decisions: Analytics v rules of thumb , 2014 .

[50]  A. Higuchi,et al.  A factor-cluster analysis profile of consumers , 2021 .

[51]  Lutgarde M. C. Buydens,et al.  Self- and Super-organizing Maps in R: The kohonen Package , 2007 .

[52]  Dirk Van den Poel,et al.  Handling class imbalance in customer churn prediction , 2009, Expert Syst. Appl..

[53]  Selim Aren,et al.  The Factors Influencing Given Investment Choices of Individuals , 2015 .

[54]  K. Mishra,et al.  A study on the impact of investment experience, gender, and level of education on overconfidence and self-attribution bias , 2015 .

[55]  P. Rousseeuw.  Silhouettes: a graphical aid to the interpretation and validation of cluster analysis , 1987 .

[56]  Belaid Bouikhalene,et al.  Combining RFM model and clustering techniques for customer value analysis of a company selling online , 2015, 2015 IEEE/ACS 12th International Conference of Computer Systems and Applications (AICCSA).

[57]  Eunil Park,et al.  Who will be your next customer: A machine learning approach to customer return visits in airline services , 2020 .

[58]  P. Klaus.  Customer Experience: The Origins and Importance for Your Business , 2015 .

[59]  Luigi Laura,et al.  Cognitive analytics management of the customer lifetime value: an artificial neural network approach , 2021, J. Enterp. Inf. Manag..

[60]  Derrick S. Boone,et al.  Retail segmentation using artificial neural networks , 2002 .

[61]  B. Wirtz,et al.  Rational and emotional factors of customer satisfaction and brand loyalty in a business-to-business setting , 2017 .

[62]  Richard W. Hamming,et al.  Error detecting and error correcting codes , 1950 .