A Study on Efficient Stock Arrangement of Distribution Center Using MBA Analysis and Simulation in Retail Business

유통업에서 MBA분석과 시뮬레이션을 이용한 물류센타 재고배치 효율화에 관한 연구

  • Yeo, Sung-Joo (Department of Industrial Engineering Ajou University) ;
  • Seong, Kil-Young (Department of Industrial Engineering Ajou University) ;
  • Wang, Gi-Nam (Department of Industrial and Information Systems Engineering Ajou University)
  • Received : 2009.03.10
  • Accepted : 2009.08.07
  • Published : 2009.09.01

Abstract

It is most important for distribution center in retail business to delivery commodities in a timely manner. Accordingly, many companies try to make distribution center effective using the Warehouse Management System(WMS) integrated legacy system. Also, the Customer Relationship Management(CRM) is the most typical paradigm in management lately. Even though the WMS and CRM are independent system of each other, WMS, coupled with CRM makes customer satisfied more effectively. In this paper, we proposed the methodology for inventory location after analyzing and applying customer buying pattern data in the CRM through the MBA(Market Basket Analysis), which is part of data mining. We used an example modeling a real distribution center in retail through a 3D simulation tool and examined correlation between commodities using customer buying pattern. After that, we applied it to the inventory location system through the MBA in an example. Finally, we identified decrease in the time for picking, which is the majority of distribution center. Besides, we proposed a simulation methodology before applying new methodology. Consequently, it removes potential errors in advance and makes a optimized inventory location system.

Keywords

References

  1. Chen, Y. L., Chen, J. M., and Tung, C.W. (2006), A data Mining approach for retail knowledge discovery with consideration of the effect of shelf-space adjacency on sales,Decision Support Systems, 42(3), 1503-1520 https://doi.org/10.1016/j.dss.2005.12.004
  2. Churilov, L., Bagirov, A., and Schwartz,D. et al. (2005),Dataminingwith combined use of optimization techniques and self-organizingmaps for improving risk grouping rules : application to prostate cancer patients, journal ofManagement Information System, 21(4), 85-100 https://doi.org/10.1080/07421222.2005.11045826
  3. Han, Kyongrok (2008), An Application of DataMining to Strategic Integration of CRMand SCM, Entrue Journal of Information Technology, 7(1), 151-161
  4. Hyunchul Ahn and IngooHan (2002),Development of PersonalizedRecommendation Systemfor InternetShoppingMallsUsingtheDataMining,KAISTMGSM02137
  5. Kewi Tang, Yen-Lian Chen, and Hsiao-Wei Hu (2008), Context-based Market basket Analysis in a multiple-store environment,Decision Support Systems, 45, 150-163. https://doi.org/10.1016/j.dss.2007.12.016
  6. Kilyoung Seong and Sungjoo Yeo (2008), Simulation Analysis of the effect on distribution center withMBA, Proc. of KIIE 2008 Fall Conference
  7. Kimar,N.,Gangopadhyay, A., andKarabatis,G. (2007), SupportingMobile decision making with association rules and multi-layered caching, Decision Support Systems, 43(1), 189-204
  8. Kyu-Yong Lee and Jun-Yong Seo (2007), A Case Study on the Inventory Management Using the Datamining, Journal of thesociety of Korea Industrial and SystemEngineering, 30(3), 20-27
  9. Myounghoon Kim and Jongwha Kim (2003), The Block-Based Storage Policy and Order Processing in Logistics Warehouse, Journal of the Korea Society of Computer and Information, 8(4), 159-164
  10. Sarathy, R. andMuralhar,K. (2002), The Security of confidential numerical data in databases, Information SystemResearch, 13(4), 389-403 https://doi.org/10.1287/isre.13.4.389.74
  11. Shaw,M. J., Subramaniam, C., Tan,G.W., and Welge,M. E. (2001),Knowledge Management and data mining for marketing,Decision Support systems, 31(1) https://doi.org/10.1016/S0167-9236(00)00123-8
  12. Spangler, S.,Kreulen, J. T., LesslermJ. Li,Xb.et al. (2006), Privacy protection in datamining : Aperturbation approach for categorical data, informationSystem Research, 17(3), 254-270 https://doi.org/10.1287/isre.1060.0095
  13. Sungjoo Yeo, Jiwon Kim, Haegu Lee, GinamWang (2008), An Analysis on the factor affecting eMarketing performance with customer activity analysis in Insurance Industry,Korea Society of IT Service, autumn Conference, 2008
  14. Terri, C.Albert, Paulo, B.Goes, lockGupta,GIST (2004), aModel for design and management of content and interactivity of customer centric web site,MIS Quarterly, 28(2), 161-183 https://doi.org/10.2307/25148632
  15. Viance, S., Dedence, G., andDerrige, R. A. (2005), Auto claimFraudDetection using Bayesian learning neural network, Expert Systems with Applications, 29(3), 653-666 https://doi.org/10.1016/j.eswa.2005.04.030