Presentation | 2004/10/12 Identification of time-dependent and -independent factors based on decomposition of daily sales of a restaurant Tomoyuki HIGUCHI, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Daily sales of a catering establishment is affected by several factors: A day of the week, national holidays, weather, events taken place near the site, etc. Therefore, it is no doubt beneficial to make a model decomposing a time series of the sales into such factors. Then the model allows us to predict the future sales with a good accuracy in order to plan various levels of management strategies such as purchase, staff assignments, new store openings, etc. In this study, we have proposed a prediction method for daily sales of a catering establishment based on a state space model framework in which an optimal model chosen by an information criterion; we have applied it to daily sales data for two years of a restaurant which is adjacent to a large-scale convention center and office buildings. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | state space model / marketing / knowledge discovery / daily sales of a restaurant |
Paper # | NC2004-75 |
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Conference Information | |
Committee | NC |
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Conference Date | 2004/10/12(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Neurocomputing (NC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Identification of time-dependent and -independent factors based on decomposition of daily sales of a restaurant |
Sub Title (in English) | |
Keyword(1) | state space model |
Keyword(2) | marketing |
Keyword(3) | knowledge discovery |
Keyword(4) | daily sales of a restaurant |
1st Author's Name | Tomoyuki HIGUCHI |
1st Author's Affiliation | Research Organization of Information and Systems, The Institute of Statistical Mathematics() |
Date | 2004/10/12 |
Paper # | NC2004-75 |
Volume (vol) | vol.104 |
Number (no) | 349 |
Page | pp.pp.- |
#Pages | 5 |
Date of Issue |