• Journal of Electrical Engineering and Technology
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• v.4 no.1
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• pp.43-48
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• 2009

The purpose of the this paper is to make decision of the maintenance priority of power distribution system using Time-Varying Failure Rate(TVFR) with interruption cost. This paper emphasizes the practical use of the reliability indices and interruption cost. To make a decision of maintenance priority on power distribution system equipment, the quantification of the reliability level should be represented as a cost. In this paper, the TVFR of power distribution system equipment applied in this paper utilizes analytic method to use the historical data of KEPCO. From this result, the sensitivity analysis on TVFR of equipment was done for the priority, which represents that high priority of the equipment has more effect on system reliability, such as SAIDI or SAIFI, than other equipment. By this priority, the investment plan is established. In this result, customer interruption cost(CIC) could be extracted, and CIC is used as weighting factor to consider a importance of customer. After that, the result calculated the proposal method in this paper is compared with other priority method, such as lifetime, failure rate or only sensitivity.

• Journal of Distribution Science
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• v.20 no.2
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• pp.11-18
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• 2022

Purpose: The purpose of this paper is to investigate the influence of brand equity on customer purchase decision (CPD) of products for retailers distribution (RB) in Ho Chi Minh city, Vietnam. There are five elements in the brand equity model such as brand awareness, brand association, brand loyalty, perceived quality, and pricing policy. Research design, data and methodology: Qualitative methodology was used for exploring the research model and variables. The survey was conducted to collect data from 251 respondents who bought products at RB in Ho Chi Minh city, which is based on a Likert scale. The collected data were analyzed with the reliability of the scale, exploratory factor analysis, and research hypothesis testing by SPSS 22. Results: The results obtained revealed that brand awareness, brand association, perceived quality, and pricing policy have a significant impact on CPD for RB. Furthermore, the results showed that perceived quality is the most significant component in influencing CPD at retailers. Conclusions: From the research results, some management implications that RB should focus on are perceived quality, choice of pricing policies and strategies, brand building and development to attract more customers as well as enhance its image to improve customers' purchasing decisions of products at retail distributors chain.

• 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.

• Journal of Fashion Business
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• v.6 no.5
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• pp.136-150
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• 2002

In this study, we proposed a method to be standing customers as the supporting system for the improvement of fashion garment industry which was the marginal growth getting into full maturity of market. As for the customer creation method of Fashion garment company is developing a marketing program to be standing customer as customer scoring to estimate a existing customer‘s buying power, and figure out minimum fixed sales of company to use a future purchasing predict. This study was a result of data from total sixty thousands data to be created for the 11 months from september. 2000 to July. 2001. The data is part of which the company leading the Korean fashion garment industry has a lot of a customer purchasing history data. But this study used only 48,845 refined purchased data to discriminate from sixty thousands data and 21,496 customer case with the exception of overlapping purchased data among of those. The software used to handle sixty thousands data was SAS e-miner. As the analysis process is put in to operation the analysis of the purchasing customer’s profile firstly, and the second come into basket analysis to consider the buying associations for Association goods, the third estimate the customer grade of Customer loyalty by 3 ways of logit regression analysis, decision tree, Artificial Neural Network. The result suggested a method to be estimate the customer loyalty as 3 independent variables, 2 coefficients. The 3 independent variables are total purchasing amount, purchasing items per one purchase, payment amount by one purchasing item. The 2 coefficients are royal and normal for customer segmentation. The result was that this model use a logit regression analysis was valid as the method to be estimate the customer loyalty.

• Journal of Global Scholars of Marketing Science
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• v.16 no.2
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• pp.27-54
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• 2006

As maintaining customer long term relationship is critical factor for improving to firm value as well as customer lifetime value, the academicians and practitioners have paid attention to customer defection. It is said that service failures are key factors to customer defection or customer switching(Keaveney 1995 etc.). This study examines that the effect on customer defection of service failures is differential according to the various customer-firms relationship characteristics. We consider relationship duration, usage level, decision making influence, industry knowledge and switching cost as customer-firm relationship characteristics based on marketing literature. Predictions are developed and tested using Internet service provider(ISP) user survey data(n=212). Results show that the customer-firms relationship characteristics/above variables) play a moderating roles in the service failures and customer defection links.

• Culinary science and hospitality research
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• v.13 no.1 s.32
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• pp.41-54
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• 2007

This study informs us what has influence on a decision that a customer using a hotel restaurant makes on a menu. Also, you can know how long it takes to decide what they are going to eat, how prompt and different they are. When the customers order food, they are getting very careful about their decisions. According to the study results, sometimes they are influenced by the person whom they accompany with. The most important factors to make customers choose one dish from a wide range of menu are taste of food, food sanitation, price, freshness of food materials. An atmosphere of a restaurant or its reputation, service of employees are key factors, too. You need change to reflect desire of a customer, and problems of a restaurant must be checked thoroughly. Many different kinds of food must be developed and managed thoroughly.

• Journal of the Ergonomics Society of Korea
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• v.17 no.3
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• pp.71-80
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• 1998

This study proposed a method to apply certain fuzzy-related Quality control concepts to design customer-oriented products considering user requirements and information starting with the product development stage. This approach showed how to define the importance level of design elements and how to Quantify complex subjective perception of products using the fuzzy linguistic rating method and quality function deployment concepts. Using this approach, various customer requirements could be interpreted and reflected on the early design phase of a new product. To validate the proposed method, an experiment was conducted for designing the shape of the beeper using 14 subjects and 10 commercial beeper products. Front area, width/length ratio, thickness, curve variance, weight, and display area were selected as design elements of the beeper. The results showed that among design elements, front area and weight are significantly related with the subjective perception of the products. Consequently, this study indicates that customer decision on product selection could be made by quantification of user perception for beeper products.

• Asia pacific journal of information systems
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• v.12 no.1
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• pp.1-16
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• 2002

Most of searching systems used by shopping-mall provide too much information for user requirements or fail to provide appropriate items reflecting customer's preference. This paper aims to design and implement the product searching systems based on customer preference which will enable efficient product selection in the internet shopping-mall. The proposed system consists of user/provider interface, searching and model agent, data management system, and model management system. Especially, we construct the searching pattern database to support fast search using association mining method. And this system includes the customer-oriented decision model which shows the highly preferred products. Input weight value per attribute and preference level should be needed to compute priority grade of preference.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.51
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• pp.29-40
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• 1999

The distribution center location and routing problem involves interdependent decisions among facility, transportation, and inventory decisions. The design of distribution system affects the customers' purchase decision by sets the level of customer service to be offered. Thus the lower product availability may cause a loss of demand as falls off the customers' purchase intention, and this is related to the firm's profit reduction. This study considers the product availability of the distribution centers as the measure of the demand level change of the demand points, and represents relation between customer service and demand level with linear demand function. And this study represents the distribution center location and routing to demand point in order to maximize the total profit that considers the products' sales revenue by customer service, the production cost and the distribution system related costs.

• Journal of Information Technology Services
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• v.14 no.4
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• pp.159-169
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• 2015

Customer reviews are one of the important sources for purchase decision makings in online stores. Online stores have tried to provide useful reviews in product pages to customers. To assess the usefulness of customer reviews before other users have voted enough on the reviews, diverse aspects of reviews were utilized in prevous studies. Style and semantic information were utilized in many studies. This study aims to test diverse alogrithms and datasets for identifying a proper classification method and threshold to classify useful reviews. In particular, most researches utilized ratio type helpfulness index as Amazon.com used. However, there is another type of usefulness index utilized in TripAdviser.com or Yelp.com, count type helpfulness index. There was no proper threshold to classify useful reviews yet for count type helpfulness index. This study used reivews and their usefulness votes on restaurnats from Yelp.com to devise diverse datasets and applied text mining approaches to classify useful reviews. Random Forest, SVM, and GLMNET showed the greater values of accuracy than other approaches.