• The Korean Journal of Applied Statistics
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• v.17 no.2
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• pp.229-238
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• 2004

Cross-sell models are used to predict the probability or value of a current customer buying a different product or service from the same company. Selling to current customers is one of the easiest way to increase profits and allows companies to carefully manage offers to avoid over-soliciting and possibly alienating their customers. In this study, by using the real database of an insurance company in Korea, we try to explain the steps of actual data mining process. Especially, this study aims to develop cross-sell models to predict the probability which a current customer of automobile insurance buys long-term insurance product.

• Proceedings of the Korea Database Society Conference
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• 2001.11a
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• pp.76-112
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• 2001

Web personalization entails the creation and dissemination of person- or group-specific content -- including, but not limited to, advertising, marketing campaigns, cross- and up-sell recommendations, or service and support information. (omitted)

• Korean Institute of Interior Design Journal
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• v.20 no.5
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• pp.178-187
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• 2011

This research suggested the hygienic spatial composition of sell-service restaurants applying HACCP(Hazard Analysis and Critical Control Point System). The circulation of the food, dishes, waste, workers and customers were each fractionated and arranged according to the hygienic sequence of cooking food in kitchen and process for eating food within the customer space. The spaces were separated by the degree of cleanness(clean area, semi-clean area, contaminated area). After that, hygiene facilities to remove contamination and pass facilities intended to control moving were added at the possible points of cross-contamination in oder to prevent the cross-contamination. For hygienic spatial composition of self-service restaurant, the following should be acknowledged: In the kitchen, spaces in which the food is handled after being heated should be located in the clean area. As of the customer space, spaces where dishes are prepared, food and water is received, and the table hall should be located in the clean area. Food circulation should flow from the contaminated area to the clean area. Food, dishes, waste should be moved through pass facilities so that workers do not have to come and go between other areas of cleanness. Also lockers for private clothes and lockers for uniforms should be separated. Hygiene facilities should be easily accessible so that workers can use them whenever they enter their working area. The contaminated area where dirty dishes are dealed with should be separated from the clean area. Waste should be thrown out without crossing cooking areas. As of customer circulation, the hygiene facility for hand washing should be located near the space where dishes for self-service are placed. The customer circulation should lead customers to leave restaurants after giving back the dirty dishes in the contaminated area.

• 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.

• 한국경영정보학회:학술대회논문집
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• 2008.06a
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• pp.371-376
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• 2008

As the e-business developed fast and more firms embrace CRM as a core e-business strategy, it is getting more important to assess the firms. The CRM is approaching customer-centric. This approach focuses on the long-term relationship with the customers by providing the benefits of the customer rather than based on what the company wants to sell. How to establish the overall efficiency and effectiveness of a global enterprise becomes more and more important to the E-business. The study investigates the cross-national psychometric prosperities of the establishment in the E-business. Using a cross-national survey of customers from Korea and China to compare the Korean customers' acceptance of e-business with the Chinese customers', and compare the development of e-business in Korea with the development in China it will be found that Korea and China samples shared a somewhat similar factor structure. And there are also some differences between Korea and China. These findings suggest that the way to establish the e-business strategy is influenced by the cultural effects. So focusing on the cultural differences among the countries becomes more and more important, this study will help to analysis how to use the different cultural dimension to establish the better CRM system in the e-business field.

• Journal of the Korea Society of Computer and Information
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• v.15 no.12
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• pp.227-235
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• 2010

This paper proposes the recommendation system which is advanced using RFM method and Association Rules in e-Commerce. Using a implicit method which is not used user's profile for rating, it is necessary for user to keep the RFM score and Association Rules about users and items based on the whole purchased data in order to recommend the items. This proposing system is possible to advance recommendation system using RFM method and Association Rules for cross-selling, and also this system can avoid the duplicated recommendation by the cross comparison with having recommended items before. And also, it's efficient for them to build the strategy for marketing and crm(customer relationship management). It can be improved and evaluated according to the criteria of logicality through the experiment with dataset collected in a cosmetic cyber shopping mall. Finally, it is able to realize the personalized recommendation system for one to one web marketing in e-Commerce.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.3
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• pp.97-107
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• 2024

This study aims to identify the factors that affect customer satisfaction as the market growth of rental subscription services for living environment home appliances increases. Unlike previous research, which focused on online subscriptions (e.g., digital content, over-the-top (OTT) services, e-books, and mobile devices), this study expands the scope to include rental subscriptions for household environmental appliances. Specifically, this study analyzes the factors influencing customer satisfaction among rental subscription service users by examining the effects of perceived usefulness, reliability, and convenience. The results show that users' perceived reliability and convenience of rental subscription services for living environment home appliances significantly affect customer satisfaction. Perceived usefulness, however, was not found to have a significant impact, as it is an abstract and subjective customer aspect. The implications of the results are as follows: First, standardized services must be strengthened to increase the reliability of rental subscription services. Additionally, it is necessary to improve convenience by developing additional services when managing regular visits tailored to the characteristics of each product. Providing customized services by integrating products and Information and Communications Technologies (ICT). Furthermore, effective customer management to increase customer satisfaction is crucial, as it can lead to cross-selling and up-selling opportunities. Lastly, venture start-ups should actively apply a subscription service business model.

• Korean Journal of Artificial Intelligence
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• v.9 no.1
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• pp.9-14
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• 2021

This paper predicted a model that indicates whether to buy a car based on primary health insurance customer data. Currently, automobiles are being used to land transportation and living, and the scope of use and equipment is expanding. This rapid increase in automobiles has caused automobile insurance to emerge as an essential business target for insurance companies. Therefore, if the car insurance sales are predicted and sold using the information of existing health insurance customers, it can generate continuous profits in the insurance company's operating performance. Therefore, this paper aims to analyze existing customer characteristics and implement a predictive model to activate advertisements for customers interested in such auto insurance. The goal of this study is to maximize the profits of insurance companies by devising communication strategies that can optimize business models and profits for customers. This study was conducted through the Microsoft Azure program, and an automobile insurance purchase prediction model was implemented using Health Insurance Cross-sell Prediction data. The program algorithm uses Two-Class Logistic Regression and Two-Class Boosted Decision Tree at the same time to compare two models and predict and compare the results. According to the results of this study, when the Threshold is 0.3, the AUC is 0.837, and the accuracy is 0.833, which has high accuracy. Therefore, the result was that customers with health insurance could induce a positive reaction to auto insurance purchases.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.210-214
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• 2008

It is actually impossible to model and store all objects which exist in real home environment into robot's database in advance. To resolve this problem, this paper proposes new object modeling method that can be available for robot self-modeling, which is capable of estimating whole model's shape from partial surface data using Generic Model. And this whole produce is conducted to cylindrical objects like cup, bottles and cans which can be easily found at indoor environment. The detailed process is firstly we obtain cylinder's initial principle axis using points coordinates and normal vectors from object's surface after we separate cylindrical object from 3D image. This 3D image is obtained from 3D sensor. And second, we compensate errors in the principle axis repeatedly. Then finally, we do modeling whole cylindrical object using cross sectional principal axis and its radius To show the feasibility of the algorithm, We implemented it and evaluated its accuracy.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.59-71
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• 2014

System trading is becoming more popular among Korean traders recently. System traders use automatic order systems based on the system generated buy and sell signals. These signals are generated from the predetermined entry and exit rules that were coded by system traders. Most researches on system trading have focused on designing profitable entry and exit rules using technical indicators. However, market conditions, strategy characteristics, and money management also have influences on the profitability of the system trading. Unexpected price deviations from the predetermined trading rules can incur large losses to system traders. Therefore, most professional traders use strategy portfolios rather than only one strategy. Building a good strategy portfolio is important because trading performance depends on strategy portfolios. Despite of the importance of designing strategy portfolio, rule of thumb methods have been used to select trading strategies. In this study, we propose a SVM-based strategy portfolio management system. SVM were introduced by Vapnik and is known to be effective for data mining area. It can build good portfolios within a very short period of time. Since SVM minimizes structural risks, it is best suitable for the futures trading market in which prices do not move exactly the same as the past. Our system trading strategies include moving-average cross system, MACD cross system, trend-following system, buy dips and sell rallies system, DMI system, Keltner channel system, Bollinger Bands system, and Fibonacci system. These strategies are well known and frequently being used by many professional traders. We program these strategies for generating automated system signals for entry and exit. We propose SVM-based strategies selection system and portfolio construction and order routing system. Strategies selection system is a portfolio training system. It generates training data and makes SVM model using optimal portfolio. We make $m{\times}n$ data matrix by dividing KOSPI 200 index futures data with a same period. Optimal strategy portfolio is derived from analyzing each strategy performance. SVM model is generated based on this data and optimal strategy portfolio. We use 80% of the data for training and the remaining 20% is used for testing the strategy. For training, we select two strategies which show the highest profit in the next day. Selection method 1 selects two strategies and method 2 selects maximum two strategies which show profit more than 0.1 point. We use one-against-all method which has fast processing time. We analyse the daily data of KOSPI 200 index futures contracts from January 1990 to November 2011. Price change rates for 50 days are used as SVM input data. The training period is from January 1990 to March 2007 and the test period is from March 2007 to November 2011. We suggest three benchmark strategies portfolio. BM1 holds two contracts of KOSPI 200 index futures for testing period. BM2 is constructed as two strategies which show the largest cumulative profit during 30 days before testing starts. BM3 has two strategies which show best profits during testing period. Trading cost include brokerage commission cost and slippage cost. The proposed strategy portfolio management system shows profit more than double of the benchmark portfolios. BM1 shows 103.44 point profit, BM2 shows 488.61 point profit, and BM3 shows 502.41 point profit after deducting trading cost. The best benchmark is the portfolio of the two best profit strategies during the test period. The proposed system 1 shows 706.22 point profit and proposed system 2 shows 768.95 point profit after deducting trading cost. The equity curves for the entire period show stable pattern. With higher profit, this suggests a good trading direction for system traders. We can make more stable and more profitable portfolios if we add money management module to the system.