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A Study on the Method of Forecasting Restaurant Revenue Using Big Data

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With the spread of ‘government 3.0’ which has been a core project by the government, researchers are now able to use public data that had previously been hard to access. Various services that are linked to Big Data are also on the increase. Major corporations around the world see Big Data as something that will open new opportunities in the market. Leading corporations consider it the core in business strategy and opportunities. As such, this paper seeks to use Big Data and public data to select major variables that affect revenue in order to forecast revenue. The time series data of these variables are used to present analysis methods that help to forecast revenue and the confidence levels are analyzed and compared across different forecast methods. Using these methods will help with decision-making on how much food ingredients to purchase and managing revenue flow.

Keywords: Big Data; Prediction; Regression Analysis; Sales Analysis

Document Type: Research Article

Affiliations: 1: Department of Multimedia Engineering, Andong National University, Andong, Gyeongsangbuk-do, 36729, Korea 2: Appsol.kr INC, Youngju, Gyeongsangbuk-do, Korea

Publication date: 01 March 2017

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  • ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
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