• Title/Summary/Keyword: 판매예측

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Sales Prediction of Electronic Appliances using a Convergence Model based on Artificial Neural Network and Genetic Algorithm (인공신경망과 유전자 알고리즘 기반의 융합모델을 이용한 가전제품의 판매예측)

  • Seo, Kwang-Kyu
    • Journal of Digital Convergence
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    • v.13 no.9
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    • pp.177-182
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    • 2015
  • The brand and product awareness of Korean electronics companies in the North American market has grown significantly and North American consumers has been recognized as an innovative technology products good performance of Korean electronics appliances. The consumer need of energy saving has led to a rise in market share because Korean electronics appliances have the excellence in energy saving aspects. The expansion of smartphones and mobile devices and the development of smart grid technology can affect electronics market. Domestic companies are continuously develop new product to provide consumers convenient with a variety of additional features combined consumer products. This study proposes a convergence model for sales prediction of electronic appliances using sales data of A company from the North American market. We develop the convergence model for sales prediction based on based on artificial neural network and genetic algorithm. In addition, we validate the superiority of the proposed convergence model by comparing the prediction performance of traditional prediction models.

Development of a Sales Prediction Model of Electronic Appliances using Artificial Neural Networks (인공신경망을 이용한 가전제품의 판매예측모델 개발)

  • Seo, Kwang-Kyu
    • Journal of Digital Convergence
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    • v.12 no.11
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    • pp.209-214
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    • 2014
  • Despite the recession of the global market, the domestic electronic appliance companies dominated TV market in North America. They took both the premium and mid-priced product market and achieved both profitability and volume due to strong product competitiveness and brand power. Despite doing well in the North American market, the domestic TV manufacturers are worried about product development, marketing and sales strategies to remain the continuous competitiveness in the TV market. This study proposes the a sales prediction model of electronic appliances using sales data of S company from the North American market. We develop the sales prediction models based on multiple regression analysis and artificial neural network and compare two models. Especially, this study analyzes the relevance between the TV sales and TV main features in order to improve the price competitiveness or improve the value of TV products.

Research on Prediction of Consumable Release of Imported Automobile Utilizing System Dynamics - Focusing on Logistics Center of A Imported Automobile Part (시스템다이내믹스를 활용한 수입 자동차 소모품 출고예측에 관한 연구 - A 수입 자동차 부품 물류센터를 중심으로)

  • Park, Byooung-Jun;Yeo, Gi-Tae
    • Journal of Digital Convergence
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    • v.19 no.1
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    • pp.67-75
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    • 2021
  • Despite the increase in sales of imported vehicles in Korea, research on the sales forecast of parts logistics centers is very limited. This study aims to perform a sales prediction on bestselling goods in the automobile part logistics center. System dynamics was adopted as a methodology for the prediction method, which considered causal relationship of variables that affected the dynamic characteristics and feedback loops. The analysis results showed that the consumable sales amount of oil increased over time. As a result of conducting the MAPE, the model was assessed to be a reasonable predictive model of 31.3%. In addition, the sales of battery products increased from every October in both of actual and predicted data followed by the peak sales in December and then decrease from next February. This study has academic implications that it secured actual data of specific imported automobile part logistics center, which has not done before in previous studies and quantitatively analyzed the prediction of the quantity of released goods of future sales through system dynamics.

A Study on Clothes Sales Forecast System using Weather Information: Focused on S/S Clothes (기상정보를 활용한 의류제품 판매예측 시스템 연구: S/S 시즌 제품을 중심으로)

  • Oh, Jai Ho;Oh, Hee Sun;Choi, Kyung Min
    • Fashion & Textile Research Journal
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    • v.19 no.3
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    • pp.289-295
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    • 2017
  • This study aims to develop clothing sales forecast system using weather information. As the annual temperature variation affects changes in daily sales of seasonal clothes, sales period can be predicted growth, peak and decline period by changes of temperature. From this perspective, we analyzed the correlation between temperature and sales. Moving average method was applied in order to indicate long-term trend of temperature and sales changes. 7-day moving average temperature at the start/end points of the growth, peak, and decline period of S/S clothing sales was calculated as a reference temperature for sales forecast. According to the 2013 data analysis results, when 7-day moving average temperature value becomes $4^{\circ}C$ or higher, the growth period of S/S clothing sales starts. The peak period of S/S clothing sales starts at $17^{\circ}C$, up to the highest temperature. When temperature drops below $21^{\circ}C$ after the peak temperature, the decline period of S/S clothing sales is over. The reference temperature was applied to 2014 temperature data to forecast sales period. Through comparing the forecasted sales periods with the actual sales data, validity of the sales forecast system has been verified. Finally this study proposes 'clothing sales forecast system using weather information' as the method of clothing sales forecast.

Sales Volume Prediction Model for Temperature Change using Big Data Analysis (빅데이터 분석을 이용한 기온 변화에 대한 판매량 예측 모델)

  • Back, Seung-Hoon;Oh, Ji-Yeon;Lee, Ji-Su;Hong, Jun-Ki;Hong, Sung-Chan
    • The Journal of Bigdata
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    • v.4 no.1
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    • pp.29-38
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    • 2019
  • In this paper, we propose a sales forecasting model that forecasts the sales volume of short sleeves and outerwear according to the temperature change by utilizing accumulated big data from the online shopping mall 'A' over the past five years to increase sales volume and efficient inventory management. The proposed model predicts sales of short sleeves and outerwear according to temperature changes in 2018 by analyzing sales volume of short sleeves and outerwear from 2014 to 2017. Using the proposed sales forecasting model, we compared the sales forecasts of 2018 with the actual sales volume and found that the error rates are ±1.5% and ±8% for short sleeve and outerwear respectively.

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Sales Forecasting for Inventory Control on Seasonal fashion product (계절유행상품 재고관리를 위한 판매예측)

  • 안봉근
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • pp.953-959
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    • 2002
  • 계절유행상품의 수요는 연중 성수기가 길지 않고 매년 유행과 제품디자인 변화가심한 경향이 있어 수요예측에 과거의 판매정보의 유용성이 크지 않다. 성수기 초반의 수요가 연간 수요결정에 매우 중요하며 후반부수요가 급격히 감소하는 특성이 있다. 반면 이월상품의 잔존가치가 매우 낮지만 매출마진이 높아 수요예측의 정확도에 따라 수익률이 큰 영향을 받는다. 이러한 이유로 기존의 수요예측방법을 계절상품에 적용하기에 무리가 따르며 예측오차의 비용이 매우 커서 계절상품 관리에 이용할 수 없다. 본 연구에서 성수기를 하위기간으로 구분하여 시즌 초반부 수요발생시점을 측정하여 초반부 기간별수요량을 구하고 이를 근거로 기간 누적수요비율을 quantile regression에 의거 추정하여 기간별 수요량과 전제 수요량을 예측하는 방법을 제시하고 모의자료를 사용하여 이 모형의 우수성을 평가하였다.

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Sales Forecasting of Competing Durable Products : The Impact of Market Response and Replacement Demand (경쟁 환경하에서의 내구재의 판매예측에 관한 연구 : 소비자의 반응 및 제품대체에 의한 영향)

  • Park, Seong-Ki;Jun, Duk-Bin
    • Journal of the Korean Operations Research and Management Science Society
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    • v.16 no.1
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    • pp.45-58
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    • 1991
  • The importance of marketing mix variables, replacement demand, and competition in a new product growth model has been cited by many researchers. In this paper, these factors are integrated with an aim to model company sales of competing durables. Based on the most popular new product growth model, numerous extensions and incorporations of contributions from related research fields are tried. Model parameters are estimated by the Kalman filter. And, the proposed model is applied to the sales of four consumer durable goods. Empirical applications show the benefits, as well as the limitations of the proposed model.

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현장탐방 고객감동 현장 - 에스엠비티(주) 전남지점

  • Kim, Hyeon-Ok
    • Life and Agrochemicals
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    • v.29 no.10
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    • pp.33-35
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    • 2008
  • 전통문화와 첨단산업이 공존하는 자족형 혁신도시를 추구하는 나주시. 영산강 문화의 뿌리를 둔 생명의 당이다. 배 주산단지인 이곳 나주에 '천우지베레린'을 확인시킨 에스엠비티(주) 전남지점(지점장 김현옥 44)이 자리하고 있다. 2006년 최초 1호 지점으로 설립, 에스엠비티(주)와 인연을 시작한 김지점장은 "고객과의 만남을 위해 현장으로 떠나는 매일 아침이 적지 않게 설레인다"면서 "하루 이동거리가 보통 250여km를 상회, 때론 지치기도 하지만 항상 생명이 살아 숨쉬는 현장의 목소리에 귀 기울이며 함께 꿈을 이룰 수 있어 행복하다'며 그의 환한 웃음 속에 열정을 내비친다. 이 같은 열정은 지난해 전국 우수지점에 선정된 영예와 무관치 않다. "영업력은 성실, 정보력, 대인관계, 적시적소의 운영 등 개인의 능력에 좌우된다"며 선두지점의 자부심을 드러내는 김 지점장은 "농가들은 작물보호제품의 인지도를 쉽게 바꾸려 하지 않아 우선 고객의 마음에 신뢰와 믿음을 심어주어야 한다. 끊임없는 제품연구와 정확한 정보 전달, 수요와 판매예측의 시장분석을 통해 적시적소에 적합한 제품을 공급해야 한다"면서 타사와의 차별화 전략에 대해 역설하며 그의 일상이 빼곡히 적혀있는 다이어리를 넘기며 또 다른 미래를 준비하고 있다.

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