• Korean System Dynamics Review
• /
• v.5 no.1
• /
• pp.49-71
• /
• 2004

Demand-side Management can be defined as'any utility activity aimed at modifying customers' use of energy to produce desired changes in the utility's load shape'. Customers benefit by being able to control energy costs and improve quality of life and become more productive. Utilities benefit from DSM's value as a resource that enhances asset utilization and reduces both fuel costs and environmental emissions. The scope of DSM includes load management through rate schedules and conservation by improving energy effciency and using electricity consumption effectively. This paper study the DSM resource evaluation and customer behavior analysis todesign the DSM Program plan in response to customer needs. We develop basic system dynamics model to analysis the customer behavior based on a survey research. The DSM Program participants in the Hi- efficiency Inverter, Electric motor and efficient lighting applicancies operating by Conservation program 2002 become the survey objects. DSM resource evaluation evaluate firstt the distribution potentialities of each machine and then forecast the degree of diffusion. We apply the system dynamic approach to simulate the dynamic DSM market situation at the domestic beginning. This model will give the energy Planner the opportunity to create different scenarios for DSM program planning. Also it will lead to increased understanding of the dynamic DSM market

• Journal of Intelligence and Information Systems
• /
• v.16 no.4
• /
• pp.213-225
• /
• 2010

Data mining has empowered the managers who are charge of the tasks in their company to present personalized and differentiated marketing programs to their customers with the rapid growth of information technology. Most studies on customer' response have focused on predicting whether they would respond or not for their marketing promotion as marketing managers have been eager to identify who would respond to their marketing promotion. So many studies utilizing data mining have tried to resolve the binary decision problems such as bankruptcy prediction, network intrusion detection, and fraud detection in credit card usages. The prediction of customer's response has been studied with similar methods mentioned above because the prediction of customer's response is a kind of dichotomous decision problem. In addition, a number of competitive data mining techniques such as neural networks, SVM(support vector machine), decision trees, logit, and genetic algorithms have been applied to the prediction of customer's response for marketing promotion. The marketing managers also have tried to classify their customers with quantitative measures such as recency, frequency, and monetary acquired from their transaction database. The measures mean that their customers came to purchase in recent or old days, how frequent in a period, and how much they spent once. Using segmented customers we proposed an approach that could enable to differentiate customers in the same rating among the segmented customers. Our approach employed support vector regression to forecast the purchase amount of customers for each customer rating. Our study used the sample that included 41,924 customers extracted from DMEF04 Data Set, who purchased at least once in the last two years. We classified customers from first rating to fifth rating based on the purchase amount after giving a marketing promotion. Here, we divided customers into first rating who has a large amount of purchase and fifth rating who are non-respondents for the promotion. Our proposed model forecasted the purchase amount of the customers in the same rating and the marketing managers could make a differentiated and personalized marketing program for each customer even though they were belong to the same rating. In addition, we proposed more efficient learning method by separating the learning samples. We employed two learning methods to compare the performance of proposed learning method with general learning method for SVRs. LMW (Learning Method using Whole data for purchasing customers) is a general learning method for forecasting the purchase amount of customers. And we proposed a method, LMS (Learning Method using Separated data for classification purchasing customers), that makes four different SVR models for each class of customers. To evaluate the performance of models, we calculated MAE (Mean Absolute Error) and MAPE (Mean Absolute Percent Error) for each model to predict the purchase amount of customers. In LMW, the overall performance was 0.670 MAPE and the best performance showed 0.327 MAPE. Generally, the performances of the proposed LMS model were analyzed as more superior compared to the performance of the LMW model. In LMS, we found that the best performance was 0.275 MAPE. The performance of LMS was higher than LMW in each class of customers. After comparing the performance of our proposed method LMS to LMW, our proposed model had more significant performance for forecasting the purchase amount of customers in each class. In addition, our approach will be useful for marketing managers when they need to customers for their promotion. Even if customers were belonging to same class, marketing managers could offer customers a differentiated and personalized marketing promotion.

• Journal of Korean Society for Quality Management
• /
• v.30 no.2
• /
• pp.11-25
• /
• 2002

This paper is to find how does service orientation of organization and human resource job satisfaction affect its customer orientation, that is, its service attitude and behavior toward customer. Purpose of this study is also to measure the level of employees' customer orientation more systemic. Consequently, the correlation between service orientation and performance can be identified and more effective guideline for service quality management can be draw through this study. The findings of this paper are as followings; Firstly, it is found that reward system and CEO's vision toward service orientation affect employee's job satisfaction positively, It's analyzed on Gap analysis model of PZB. Secondly, in point of inner marketing, employee who is satisfied with his job shows higher customer orientation. Thirdly, strategy change of organization in response to environment change in hospital industry influences on performance positively.

• Asia-Pacific Journal of Business
• /
• v.8 no.2
• /
• pp.75-94
• /
• 2017

This study aims to develop a conceptual framework linking antecedents and consequences of online platform experience in the context of hospitality businesses. In doing so, an introduction to online platform experience in the hospitality industry was made, and environmental stimuli, that is, enablers of online platform experience were identified: information, entertainment and relation. Additionally, the theoretical review attempted to explain how customers are likely to be engaged in, and to be loyal to, the hospitality organizations' provisions in the context of online platforms. When presenting the theoretical model, a Stimulus-Organism-Response paradigm was employed to propose the hypotheses predicting positive online platform experience, which seems to derive from internally provoked cognition and affection within individuals, leading to behavioral consequences. This model is expected to be applicable to the online context, where hospitality businesses tend to adopt the concept of gamification and to implement associated loyalty programs. Finally, theoretical and practical implications, along with potential avenues of future research, were discussed.

• The Korean Journal of Franchise Management
• /
• v.11 no.3
• /
• pp.7-18
• /
• 2020

Purpose: Recently, information on 'Delicious Restaurants (Mat-zip)' and 'Famous Bakeries' can be obtained through various media such as TV, Internet search, and SNS, and the culture of finding and sharing them has become a trend. Since PZB's SERVQUAL, there have been many studies measuring service quality, leading to hotels, restaurants and coffee shops. These studies of service quality include product quality in the service quality dimension. Hotels, restaurants, and coffee shops are provided with intangible services while customers visit and stay, but 'Delicious Restaurants (Mat-zip)' and 'Famous Bakeries' often stop by to buy products and return home. Therefore, the study on the effect of quality on customer behavior on 'Delicious Restaurants (Mat-zip)' should consider product quality separately. In this study, we want to study how each quality element affects the perceived value and response of customers by separating product quality and service quality. Research design, data, and methodology: This study tested the structural model of how the quality of products and services of famous bakeries affect customers' perceived value and response. As the quality factors, products, tangible services, and employee services were adopted, and perceived values adopted utilitarian and hedonic values, and customer responses adopted customer satisfaction and behavior intention. For this study, 203 survey data with experience using famous bakeries were analyzed using SPSS 22.0 and AMOS 22.0. Result: The research results are as follows. First, product quality positively influenced utilitarian value, hedonic value, and customer satisfaction, tangible service quality positively influenced utilitarian value, and employee service quality positively influenced hedonic value. Second, utilitarian value had a positive effect on behavioral intention, and hedonic value had a positive effect on customer satisfaction. Conclusions: In a famous bakery, it is basic that product quality should be given priority, and for customer satisfaction, employee service quality is half as important. In addition, for Behavior Intension (revisit by the customer), in addition to product quality, the quality of tangible services and employee services should be maintained at a quarter level.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.42 no.3
• /
• pp.176-183
• /
• 2019

The environmental changes in the Korean cosmetic medical service industry in the $21^{st}$ century are forming intense competition among medical institutions due to the quantitative expansion of its market. For stable growth of the cosmetic medical service industry, continuous quality improvement is necessary based on empirical research on the quality of cosmetic medical services rather than external expansion. The purpose of this study is to classify the quality attributes of cosmetic medical service using Kano model and to derive the degree of satisfaction and dissatisfaction of each quality attributes through Customer Satisfaction Coefficient (CSC). Through this, the study identified strategic priorities and suggested specific step-by-step approaches and quality improvement priorities that can increase customer satisfaction using the Potential Customer Satisfaction Improvement Index (PCSI Index). Based on SERVPERF, this study used measurement tools consisting of five dimensions : tangibles, reliability, responsiveness, assurance, and empathy. In addition, it was used of measurement items reconstructed into positive, negative, and satisfaction questions for Kano model analysis, CSC analysis, and PCSI Index analysis. A total of 300 medical consumers who experienced cosmetic medical services for the past one year in medical institutions such as plastic surgery and dermatology were collected with convenient sampling. As a result, urgent items for improving the quality of service using the PCSI Index, 'Consideration for customer benefits' in empathy category was followed by 'Immediate help' and 'Sincere response' in responsiveness category, and 'Understanding customer needs' in empathy category, respectively. That is, it is required to improve human service quality attributes such as empathy and responsiveness rather than physical service quality attributes. This study contributes practically in that it provides specific and discriminatory approaches to improve customer satisfaction on cosmetic medical service quality and suggests improvement priorities.

• Journal of the Korean Data and Information Science Society
• /
• v.20 no.4
• /
• pp.673-684
• /
• 2009

Lower Prices are offered through sales by telemarketing. This is to serve our customers by the fastest and most appropriate referral product that is most important to attract insurance. Therefore, Considering the time the customer's preferred products and preferred customer for screening and targeting, depending on what is the difference between the premiums. This study of the logistic regression model using datamining techniques, the life insurance companies in outbound telemarketing to support sales of the effect you want to validate. To join existing life insurance companies for the customer response and sales strategy based on the L segment and by age group, family-love insurance, accident insurance, and cancer insurance were in progress for the modeling. Set model based on the progress of the campaign to existing customers marketing methods and how to extract and run the model results has proven the superiority of the model. In addition, over time, depending on the aging model is set to a decline in operating profit to maximize the profits th update the model which was derived.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.62 no.8
• /
• pp.1074-1079
• /
• 2013

Demand response(DR) is potential generation alternative to improve the reliability indices of system and load points. However, when demand resources scheduled in DR market fail to reduce demand, it can create new problems associated with maintaining a reliable supply. In this paper, a reliability model of demand resource is constructed considering customers' behaviors in the same form as conventional generation units, where availability and unavailability are associated with the simple two-state model. As a result, the generalized reliability model of demand resources is represented by multi-state model.

• IE interfaces
• /
• v.18 no.2
• /
• pp.205-220
• /
• 2005

This study presents a web log analysis model for e-CRM, which combines the on-line customer's purchasing pattern data and transaction data between companies in B2B environment of make-to-order company. With this study, the customer evaluation and the customer subdivision are available. We can forecast the estimate demands with periodical products sales records. Also, the purchasing rate per each product, the purchasing intention rate, and the purchasing rate per companies can be used as the basic data for the strategy for receiving the orders in future. These measures are used to evaluate the business strategy, the quality ability on products, the customer's demands, the benefits of customer and the customer's loyalty. And it is used to evaluate the customer's purchasing patterns, the response analysis, the customer's secession rate, the earning rate, and the customer's needs. With this, we can satisfy various customers' demands, therefore, we can multiply the company's benefits. And we presents case of the 'H' company, which has the make-to-order manufacture environment, in order to verify the effect of the proposal system.

• Journal of the Korea Safety Management & Science
• /
• v.19 no.4
• /
• pp.209-219
• /
• 2017

Logistics companies want to be competitive companies in fierce logistics market and are worrying about securing of differentiated competitiveness for it. The standards judging if logistics industry maintains the competitiveness are based on the satisfaction of users due to the well-established service system that can response not only economic feasibility of logistics costs such as transportation costs, storage costs, unloading charges, information costs, etc. but also diversity and upgradability of logistics needs. Therefore, this study focuses on seeking of service quality improvements with VBSD(Value Based Service Design) model focusing on customer value factors based on Kano model and QFD based service design approach from angles of customer value improvement and service costs reduction.