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Reseach Article

An Empirical Investigation on Kohonen Clustering in Indian Retail Industry

Published on November 2012 by Ruchi Agarwal, Jayanthi Ranjan, Tarun Pandeya, S. L. Gupta
Issues and Challenges in Networking, Intelligence and Computing Technologies
Foundation of Computer Science USA
ICNICT - Number 1
November 2012
Authors: Ruchi Agarwal, Jayanthi Ranjan, Tarun Pandeya, S. L. Gupta
b5c4034c-b604-4063-bc84-226ab45d2670

Ruchi Agarwal, Jayanthi Ranjan, Tarun Pandeya, S. L. Gupta . An Empirical Investigation on Kohonen Clustering in Indian Retail Industry. Issues and Challenges in Networking, Intelligence and Computing Technologies. ICNICT, 1 (November 2012), 7-12.

@article{
author = { Ruchi Agarwal, Jayanthi Ranjan, Tarun Pandeya, S. L. Gupta },
title = { An Empirical Investigation on Kohonen Clustering in Indian Retail Industry },
journal = { Issues and Challenges in Networking, Intelligence and Computing Technologies },
issue_date = { November 2012 },
volume = { ICNICT },
number = { 1 },
month = { November },
year = { 2012 },
issn = 0975-8887,
pages = { 7-12 },
numpages = 6,
url = { /specialissues/icnict/number1/9013-1004/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 Issues and Challenges in Networking, Intelligence and Computing Technologies
%A Ruchi Agarwal
%A Jayanthi Ranjan
%A Tarun Pandeya
%A S. L. Gupta
%T An Empirical Investigation on Kohonen Clustering in Indian Retail Industry
%J Issues and Challenges in Networking, Intelligence and Computing Technologies
%@ 0975-8887
%V ICNICT
%N 1
%P 7-12
%D 2012
%I International Journal of Computer Applications
Abstract

Kohonen clustering is one of the important functions of data mining. From the aspect of data mining, clustering research extracts valuable knowledge from large data sets intelligently and automatically. Kohonen clustering was proposed along with the development of databases and the emergence of data mining and Knowledge discovery technology. Kohonen clustering is applied in many areas, such as: pattern recognition, marketing, market segmentation and so on. In this paper, an empirical investigation was done using a data mining tool Clementine (a data mining tool of SPSS) and Kohonen neural network clustering algorithm to analyze the real sales database of the Indian retail organization, in order to find out the clusters of similar product categories.

References
  1. Aldenderfer, M. S. and Blashfield, R. K. (1984). Cluster Analysis. Sage Series on quantitative applications in the social sciences. Beverly Hills: Sage Publications.
  2. Blattberg R. C, Sen S. K. (1974) Market segmentation using models of multidimensional purchasing behavior, Journal of Marketing 38, pp. 17-28.
  3. Chen, M. (1996). Neural Network Model. Dalian University of Technology Press. Dalian
  4. Desmet, P. (2002), Buying behavior study with basket analysis: pre-clustering with a Kohonen map, European Journal of Economic and Social Systems 15 N° 2 (2001) 17-30.
  5. Dolni-ar, S. and Leisch, F. (2001). Knowing What You Get - a Conceptual Clustering Framework for Increased Transparency of Market Segmentation Studies. Paper presented at the Marketing Science, Edmonton, Canada.
  6. Dominic K (2007), "Indian Retail: An Overview", Network magazine, March.
  7. FICCI Retail Report 2007, www. ficci. com (accessed on 25 th June 2008).
  8. Frank, R. E. , Massy, W. F. and Wind, Y. (1972). Market Segmentation. Englewood Cliffs: Prentice-Hall.
  9. Gunnesson, T. and Soderlund, K. (2001), "Creating Competitive Advantage in Mature e-Retail Markets", Information Management, Handelshogskolan I Stockholm, Stockholm School of Economics.
  10. Haley, R. J. (1968). Benefit Segmentation: A Decision-Oriented Research Tool. Journal of Marketing, 32, 30-35.
  11. Han, J. , Kamber, M. (2001). Data Mining Concepts and Techniques. Academic Press, New York.
  12. Hanna, J. (2004), "Ground-Floor Opportunities for Retail in India", Harvard Business School Newsletter.
  13. Hou, J. J. and Tu, H. H. J. (2008) 'Customer relationship management strategy and firm performance: an empirical study', Int. J. Electronic Customer Relationship Management, Vol. 2, No. 4, pp. 364–375.
  14. Jones, S. and Ranchhod, A. (2007) 'Marketing strategies through customer attention: beyond technology enabled customer relationship management', International Journal of Electronic Customer Relationship Management, Vol. 1, No. 3, pp. 279–286.
  15. Kaur, P. and Singh, R. (2007), "Uncovering retail shopping motives of Indian youth", Young Consumers: Insight and Ideas for Responsible Marketers, Vol. 8, No. 2, pp. 128–138.
  16. Li, Z. , Deng, Q. and Li, H. (2004). Kohonen SOFM Neural Network Evolution and Research. Computer Engineering and Design. 1729-1830.
  17. Malone, J. , etc. . (2005). Data mining Using Rule Extraction from Kohonen Self organising Maps. Neural Comput & Applic 15: 9-17.
  18. Manchanda, P. , Ansari A. , Gupta S. (1999) The "Shopping Basket": A Model for multicategory purchase incidence decisions, Marketing Science 18, pp. 95-114.
  19. Mazanec, J. and Strasser, H. (2000). A Nonparametric Approach Market Segmentation: Foundations. Berlin: Springer.
  20. Myers, J. H. and Tauber, E. (1977). Market structure analysis. Chicago: American Marketing Association.
  21. Noonan, J. (2000), "Data Mining Strategies", DM Review.
  22. Pande, S. and Collins, T. (2007), "Strategic implementation of information technology to improve retail supply chain in India", International Journal of Logistics Systems and Management, Vol. 3, No. 1, pp. 85–100.
  23. Puleo, P. (2002), "How Retailers are using Customer Insight to Build Competitive Advantage", Peppes & Rogers Group.
  24. Ranjan, J. and Bhatnagar, V. (2008), 'Data Mining tools: a CRM perspective', International Journal Electronic Customer Relationship Management, Vol. 2, No. 4, pp. 315-331.
  25. Rao, I. K. R. (2003), "Data Mining and Clustering Techniques", DRTC Workshop on Semantic Web, December.
  26. Rogers, M. (2005), "Customer strategy: observations from the trenches", Journal of Marketing, Vol. 69 No. 4, pp. 262.
  27. Ross, D. (2006), "Retail Data Warehouse, Analyzing your customers' 360 degree view of you", Business Intelligence Network Newsletter, May 16.
  28. Sangle, P. S. and Verma, S. (2008) 'Analysing the adoption of customer relationship management in Indian service sector: an empirical study', Int. J. Electronic Customer Relationship Management, Vol. 2, No. 1, pp. 85–99.
  29. Sohoni, A. (2007), "Indian Retailers - Ready for Take Off?" available from http://www. tech2. com/biz/india/features/retail/indian-retailers-ready-for-take-off/1313/0 (accessed on 02-august-2008).
  30. Two Crows corporation, "Introduction to Data Mining and Knowledge Discovery", available at http://www. twocrows. com/ (Accessed on 25/july/2008).
  31. Vector, D. (2007), "Indian Retail Industry: Strategies, Trends and Opportunities 2007", available at http:// www. Marketresearch . com /product /display. asp? productid = 1497236 (accessed on 4th July 2008).
  32. Wedel, M. and Kamakura, W. (1998). Market Segmentation - Conceptual and Methodological Foundations. Boston: Kluwer Academic Publishers.
  33. West, D. (2005) 'Enhancing value through data mining: Insurers can use data mining technology to improve their competitive position', Insurance Networking News: Executive Strategies for Technology Management, October.
  34. Yan, P. , Zhang, Ch. (2000). Artificial Neuron Network and Simulated Evolution Computing. Tsinghua University Press. Beijing.
  35. Yuan, C. (2000). Artificial Neuron Network and Application. Tsinghua University Press. Beijing.
Index Terms

Computer Science
Information Sciences

Keywords

Kohonen Clustering Data Mining