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http://dx.doi.org/10.5351/CKSS.2012.19.6.849

Sales Forecasting Model Considering the Local Environment  

Kim, Chul Soo (Department of Computer Science and Statistics, Jeju National University)
Oh, Su Min (Department of Computer Science and Statistics, Jeju National University)
Park, So Yeon (Department of Computer Science and Statistics, Jeju National University)
Publication Information
Communications for Statistical Applications and Methods / v.19, no.6, 2012 , pp. 849-858 More about this Journal
Abstract
Today, local environmental factors has an influence on our society. Local environmental factors, as well as weather-related natural phenomena, social phenomena are also included. In this paper, numeric factors and categorical factors were analyzed, looking for a local environmental factors affecting the company's sales.Sales model by performing a regression analysis based on this was implemented.Sales model considering the local environment had an accuracy of 88.89%.
Keywords
Sales forecasting model; local environmental factor; clustering analysis; k-means algorithms;
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  • Reference
1 Ahn, K.-H. (2007). The Effect of Weather on Firm's Sales, Sejong university
2 An, K.-H. (2002). An empirical study on formulating hotel sales forecasting models, Korea Journal of Tourism Research, 17, 43-57.
3 Bradley (1998). Refining initial points for clustering, Proc, 15th Internat.Conf.on Machine Learning, Morgan Kaufmann, Los Altos, CA.
4 CJ Home Shopping (2003). Surplus achieved eight years byWeather, seasonal specialized products. Korea Meteorological Agency, 2002, weather management Grand prize
5 Hautamaki, V., Cherednichenko, S., Karkkainen, I., Kinnunen, T. and Franti, P. (2005). Improving K-Means by Outlier Removal, Spring-Verlag Berlin Heidelberg.
6 Hotel-Lotte Lotte-World (2002). Weather Management- Success factors of the management of the world's largest indoor theme park, Lotte World. Korea Meteorological Agency, 2002, weather management Grand prize
7 Jang, Y.-W. (2010). A study of weather marketing a hotel industry through data mining technique, Sejong university.
8 Jung, Y.-M. (2006). Weather information is money; This practics. Samsung Global Environment Research Center.
9 Lee, Y.-K., Kim, W.-T., Jung, Y.-J., Kim, K.-D. and Ryu, K.-H. (2005). Cluster analysis of climate data for applying weather marketing, Korea Spatial Information Society, 7, 33-44.
10 Pineresort (2010). Expanding the utilization rate of Condo and Sky resort by the prior notification of weather information. Korea Meteorological Agency, 2004, weather revenue award
11 Song, S.-S. (2007). The Impact of Weather Factors on Touism-With Focus on Jeju Island, Kyonggi university.
12 WMO (1964). Weather and man, WMO-No. 143 TP. 67 (Geneva: World Meteorological Organization).