• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.118-129
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• 2022

The purpose of this report is to study a strategic model of promotion activities through various analysis and sales forecasting by selecting wearable products for domestic online companies and collecting sales data. For data analysis, various algorithms are used for analysis and the results are selected as the optimal model. The gradation boosting model, which is selected as the best result, will allow nine independent variables to be entered, including promotion type, price, amount, gender, model, company, grade, sales date, and region, when predicting dependent variables through supervised learning. In this study, the review values set as dependent variables for each type of sales promotion were studied in more detail through the ensemble analysis technique, and the main purpose is to analyze and predict them. The purpose of this study is to study the grades. As a result of the analysis, the evaluation result is 95% of AUC, and F1 is about 93%. In the end, it was confirmed that among the types of sales promotion activities, value-added benefits affected the number of reviews and review grades, and that major variables affected the review and review grades.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.1 no.1
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• pp.55-65
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• 1978

• The Journal of Bigdata
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• v.7 no.2
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• pp.195-204
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• 2022

The tourism industry is facing a crisis due to the recent COVID-19 pandemic, and it is vital to improving profitability to overcome it. In situations such as COVID-19, it would be more efficient to sell additional products other than guest rooms to customers who have visited to increase the unit price rather than adopting an aggressive sales strategy to increase room occupancy to increase profits. Previous tourism studies have used machine learning techniques for demand forecasting, but there have been few studies on cross-selling forecasting. Also, in a broader sense, a resort is the same accommodation industry as a hotel. However, there is no study specialized in the resort industry, which is operated based on a membership system and has facilities suitable for lodging and cooking. Therefore, in this study, we propose a cross-selling prediction model using various machine learning techniques with an actual resort company's accommodation data. In addition, by applying the explainable artificial intelligence XAI(eXplainable AI) technique, we intend to interpret what factors affect cross-selling and confirm how they affect cross-selling through empirical analysis.

• The tire
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• s.89
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• pp.7-10
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• 1980

미국 Tire Review 사의 년차보고서에 의하면 80년도 미국 타이어 상인들의 판매전망은 금리가 인상됨에 따라 신용거래(월부 거래)기간의 연장으로 재고는 감소되나, 서비스업(Brakes, Alignment, Shocks, Tune up등)을 겸한 판매방법의 개선 등으로 낙관된다고 하였다. 그리고 타이어 상인의 대부분은 80년도의 매출액 및 이익은 전년도에 비해 다같이 증가될 것이라고 예측하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.701-704
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• 2014

This Paper proposed the analysis and prediction method of beverage sales. We assumed weather had a relationship with beverage sales. We got the output as sales amount from a temperature and humidity of weather as input by using polynomial equation. We had modelling as quadric function with input and output data. In order to verify the effectiveness of proposed method, the sales data were collected over a 4 months during February 2014. The results showed that the proposed method can estimate sales data.

• Journal of Internet of Things and Convergence
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• v.5 no.2
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• pp.7-13
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• 2019

As online shopping is activated by the development of the Internet, consumers' purchase form is changing from the traditional face-to-face purchase method to online purchase method. Many sellers have flowed into shopping malls, and competition among sellers is very intense. Therefore, sellers in shopping malls need to establish rational marketing strategies by analyzing consumer purchase patterns and product sales trends. In this paper, we analyzed the purchase price of consumers by analyzing the product price, rating, and sales quantity of competitors who sell the same product in open shopping malls by time zone. In addition, the collected information was visualized in a chart so that the company's and competitors' sales trends could be easily compared. Using the above system, it is possible to predict the sales volume through the analyzed purchasing pattern and to select the reasonable price of the product by grasping the sales trend.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.157-165
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• 2016

Among high-tech products, the mobile phone has experienced a rapid rate of innovation and a shortening of its product life cycle. The shortened product life cycle poses major challenges to those involved in the creation of forecasting methods fundamental to strategic management and planning systems. This study examined whether the best model applies to the entire diffusion life span of a mobile phone. Mobile phone sales data from a specific mobile service provider in Korea from March of 2013 to August of 2014 were analyzed to compare the performance of two S-shaped diffusion models and two non-linear regression models, the Gompertz, logistic, Michaelis-Menten, and logarithmic models. The experimental results indicated that the logistic model outperforms the other three models over the fitted region of the diffusion. For forecasting, the logistic model outperformed the Gompertz model for the period prior to diffusion saturation, whereas the Gompertz model was superior after saturation approaches. This analysis may help those estimate the potential mobile phone market size and perform inventory and order management of mobile phones.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04a
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• pp.337-339
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• 2000

현재 전자상거래에서의 이용률이 저조한 경매시스템을 지능적인 소프트웨어 에이전트를 이용하여 사용자 측면에서 더욱 효율적이고 효과적인 경매시스템을 연구 및 개발은 커다란 이슈가 되고 있다. 따라서, 단순한 게시판 형식의 인터넷 경매 시스템의 인공지능 에이전트를 도입하여 해당 경매 상품에 대해 판매자에게 적정한 경매 시기와 초기값을 계산 및 예측하여 최대한의 마진을 남길 수 있도록 해주는 에이전트 시스템의 연구가 본 논문의 목적이다. 상품을 인터넷 경매에 올리는 판매자가 판매 하고자 하는 경매 상품에 대한 정보를 인터넷 경매 시스템의 에이전트에게 메일로 보내면 에이전트 해당 상품고 유사한 상품에 대해 클러스터링하여 이미 학습되어져 있는 유사 상품에 대한 정보 즉, 데이터 베이스에 저장되어 있는 경매 상품에 대한 입찰 히스토리와 경매시간, 경매방법, 낙찰가격 등을 계산하여 해당 상품에 대해 판매자가 어느 시기에 얼마의 초기 가격으로 경매를 시작하면 최대한의 마진을 남길 수 있는지에 대해 정보를 메일로 푸쉬해 주는 시스템을 설계하면 마진 알고리즘을 이용하여 만진 결정 에이전트에 의해 마진을 생성하며 생성된 마진은 푸쉬에이전트에 의해 경매자에게 메일로 결과값을 전송해 주는 시스템을 제안한다.

• 한국벤처창업학회:학술대회논문집
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• 2022.04a
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• pp.135-139
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• 2022

현재 COVID-19 전염병으로 인해 전 세계적으로 오프라인 상점 대신 소비자는 전자 상거래를 선호하는 추세이다. 이에 실시간 상호작용과 상거래의 통합인 '라이브 커머스'가 각광받고 있다. 국내 라이브 커머스 시장규모가 2023년에는 10조원이 넘어설 것이라는 전망에 비하여 연구가 현저히 적은 실정이다. 이에 본 연구에선 라이브커머스의 가치와 소비자의 동기가 적극적인 소비자 행동인 E-WOM 의도를 어떻게 예측하는지 살펴보았다. 라이브 커머스의 가치로는 쾌락적가치, 실용적가치, 상징적가치와 감정적가치로 분류하였다. 또한 수단-목적사슬 이론 및 이용과 충족 이론을 적용하여 설명하였다. 종속변수인 E-WOM 의도와에 사이에서 라이브커머스의 주역할을 하는 판매자를 매개변수로 설정하였다. 이때 판매자의 상호작용성과 신뢰도로 구분짓고 연구를 설정하였다. 그리고 지각된 위험성을 조절변수로 활용하여 지각된 가치들과 판매자의 사이에서 영향이 있는지 살펴보였다. 본 연구의 설문 응답 대상은 네이버 라이브 커머스 이용 대상자 410명을 대상으로 진행하였다.

• 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.