• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.982-984
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• 1997

DSM activities have grown and matured over several years in Korea. KEPCO is currently offering some DSM programs in industrial, commercial, and residential customers such as rebate program in purchasing efficient measures. The systematic evaluation process of energy savings and peak reduction will be very important for deciding on the optimal investment of DSM activities in utilities in the future. In general, the estimation process of the potential savings of DSM activities include the determination of baseline electricity consumption, the instantaneous technical potential (ITP), the phased technical potential (PTP), the economic potential (EP), and the achievable potential (AP). The purpose of this article is to provide evaluation process of those DSM potential savings based on bottom-up approach and applicate to residential sector in Korea. In case study, ITP, EP are estimated to be respectively 21.5%, 5.7% of total energy consumption, and 4.1%, 2.5% of peak load in 2010.

• Journal of Distribution Science
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• v.8 no.4
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• pp.17-23
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• 2010

The Banking industry is expanding rapidly. To keep the competitive advantages, participating companies concentrate their resource to provide the distinguishable services by increasing the service quality. This study is to find that how three kinds of service quality(process, output, and service environment) affect on the customer satisfaction. In this paper, WPCSI (Weighted Potential Customer Satisfaction Index) was developed using Kano model and PCSI. Kano's model of service quality classification was used to improve customer satisfaction, customer satisfaction index was calculated. Customer satisfaction index was calculated using the existing potential for improving customer satisfaction index (PCSI Index) to complement the limitations of the weighted potential improve customer satisfaction index (WPCSI) were used. Analysis using PCSI improve the quality of service levels may be useful in assessing. However, this figure is a marginal degree of importance on customers and quality characteristics have been overlooked but has its problems. A service provided to customers with some important differences depending on the interpretation of the scope for improvement is to be classified. In other words, the level of customer satisfaction and the satisfaction of the current difference between the comparison factor for the company to provide information about the priority of the improvement was not significant. Companies are also considered important that the customer does not consider the uniform quality of service provided can be fallible. In this study, the weighted potential to improve it improve customer satisfaction index (WPCSI) proposed a new customer satisfaction index. This is for customers to recognize the importance of quality characteristics by weighting factors, to identify practical and improved priority to provide more useful information than has been. Weighted potentially improve customer satisfaction index (WPCSI) presented in this study by the customers aware of the importance of considering the quality factor is an exponent. The results, 'Employees' working ability', 'provided the desired service level', 'staff to handle this task quickly enough' to the customer of the factors had significant effects on satisfaction are met. On the other hand 'aggressiveness on the product description of employees', 'service environment as a whole, beautiful enough to' meet and shows no significant difference between satisfaction. But 'aggressiveness on the product description of employees' and reverse (逆) were attributable to the quality. Small dogs and overly aggressive products that encourage the customer dissatisfaction that can result in widening should be careful because the quality factor can be said. As a result, WPCSI is more effect to find critical factors which can affect customer satisfaction than PCSI. After that, we discuss effects and advantages of customer satisfaction using WPCSI. This study, along with these positive aspects, the limitations are implied. First, this study directly to the bank so that I could visit any other way for customers, utilizing the Internet or mobile to take advantage of the respondents were excluded from the analysis. Second, in survey questionnaires can help improve understanding of the measures will be taken. In addition to the survey targeted mainly focused on Seoul, according to a sample, so sampling can cause problems is the viscosity revealed intends.

• Industrial Engineering and Management Systems
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• v.3 no.2
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• pp.129-133
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• 2004

Studies on the optimal location of retail store have been made in case of no obstacle(Minagawa etal. 1999). This paper deals with the location problem of retail store considering obstacles (e.g. rivers, railways, highways, etc.) and obstacle-overcoming points (e.g. bridges, railway crossings, zebra crossings, overpasses, etc.). We assume that (1) commercial goods dealt here are typically convenience goods, (2) the population is granted as potential demand, (3) the apparent demand is a function of the maximum migration length and the distance from the store to customers, (4) the scale of a store is same in every place and (5) there is no competitor. First, we construct the basic model of customers' behavior considering obstacles and obstacle-overcoming points. Analyzing the two dimensional model, the arbitrary force attracting customers is represented as a height of a cone where the retail store is located on the center. Second, we formulate the total demand of customers and determine the optimal location that maximizes the total demand. Finally, the properties of the optimal location are investigated by simulation.

• Journal of Distribution Science
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• v.15 no.12
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• pp.21-30
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• 2017

Purpose - This research approaches to the new niche market of medical tourism to investigate how factors of cultural similarity influence the international distribution management. This study also estimates the interaction effects of distribution channel on the relationships of facility attributes and customers' destination choice behavior. Research design, data, and methodology - We collected the sample of 881 potential customers from the more economically developed regions in China. Regression analysis is used to confirm the relationships in the research model. Results - The result shows that cultural similarity plays an important moderating role in the relationships of facility attributes and destination choice intention. For instance, power distance and masculinity interact with the distribution facility characteristics of medical quality and reputation to influence customers' selection of the destination country. Individualism, powder distance, and masculinity play moderating roles when social environment affects destination choice intention. Especially, all the elements of cultural similarity moderate the relationships between travel cost and destination choice intention. This research also proves that depending on distribution channel, determinants of distribution facility are the critical predictors of intention to select the medical service outside of China. Conclusions - The study enables managers to develop the more effective strategies reflecting the interaction effects of cultural similarity and distribution channel on customers' decision-making process.

• Journal of Smart Tourism
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• v.1 no.1
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• pp.53-64
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• 2021

Upselling is often a critical factor in revenue generation for businesses in the tourism and travel industry. Utilizing passenger data from a major international airline company, we develop the PAX (Passenger, Airline, eXternal) model to predict passengers that are most likely to accept an upgrade offer from economy to premium. Formulating the problem as an extremely unbalanced, cost-sensitive, supervised binary classification, we predict if a customer will take an upgrade offer. We use a feature vector created from the historical data of 3 million passenger records from 2017 to 2019, in which passengers received approximately 635,000 upgrade offers worth more than $422,000,000 U.S. dollars. The model has an F1-score of 0.75, outperforming the airline's current rule-based approach. Findings have several practical applications, including identifying promising customers for upselling and minimizing the number of indiscriminate emails sent to customers. Accurately identifying the few customers who will react positively to upgrade offers is of paramount importance given the airline 'industry's razor-thin margins. Research results have significant real-world impacts because there is the potential to improve targeted upselling to customers in the airline and related industries.

• Asia pacific journal of information systems
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• v.29 no.4
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• pp.752-770
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• 2019

The purpose of this study is to incorporate telemarketing processes to improve telemarketing performance. For this application, we have attempted to mix the model of machine learning to extract potential customers with personalisation techniques to derive recommended products from actual contact. Most of traditional recommendation systems were mainly in ways such as collaborative filtering, which predicts items with a high likelihood of future purchase, based on existing purchase transactions or preferences for products. But, under these systems, new users or items added to the system do not have sufficient information, and generally cause problems such as a cold start that can not obtain satisfactory recommendation items. Also, indiscriminate telemarketing attempts can backfire as they increase the dissatisfaction and fatigue of customers who do not want to be contacted. To this purpose, this study presented a multi-purpose hybrid recommendation algorithm to achieve two goals: to select customers with high possibility of contact, and to recommend products to selected customers. In addition, we used subscription data from telemarketing agency that handles insurance products to derive realistic applicability of the proposed recommendation system. Our proposed recommendation system would certainly solve the cold start and scarcity problem of existing recommendation algorithm by using contents information such as customer master information and telemarketing history. Also. the model could show excellent performance not only in terms of overall performance but also in terms of the recommendation success rate of the unpopular product.

• The Research Journal of the Costume Culture
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• v.18 no.3
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• pp.526-540
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• 2010

Due to fierce competition, many domestic fashion businesses are suffering difficulty in securing and maintaining customers. Accordingly, fashion companies are devoting all their energy to secure customers by using high quality and diverse strategies for distribution and promotion, and to secure loyalty by satisfying customers with the offer of excellent service. Thus, it is very important to provide systematic service recovery strategy available for handling service failure effectively. Therefore, the purpose of this study is comprehensively analyzing influences of expectation dis-confirmation and perceived justice for service recovery upon consumers' satisfaction and loyalty. The findings are as follows. First, as for the service failure that customers experienced, the more consumers who expect it to be recovered led to the higher formation of expectation-compensation dis-confirmation. Second, it was indicated that the higher seriousness in service failure that customers experienced led to the lower satisfaction and loyalty to service recovery. Third, as a result of examining influence of expectation-compensation dis-confirmation for service-failure recovery upon consumer satisfaction and loyalty, the customers who showed more positive dis-confirmation to expectation-compensation were indicated to form the more satisfaction and loyalty. Fourth, as a result of examining the influence of the perceived justice in the process of service-failure recovery upon customer satisfaction, all in 3 dimensions of justice had effect on customer satisfaction.

• The Journal of Information Systems
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• v.26 no.4
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• pp.17-37
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• 2017

Purpose Customer Loyalty is the most important factor of customer relationship management (CRM). Especially in retailing industry, where customers have many options of where to spend their money. Classifying loyal customers through customers' data can help retailing companies build more efficient marketing strategies and gain competitive advantages. This study aims to construct classification models of distinguishing the loyal customers within a Korean retailing company using data mining techniques with R language. Design/methodology/approach In order to classify retailing customers, we used combination of support vector machines (SVMs) and other classification algorithms of machine learning (ML) with the support of recursive feature elimination (RFE). In particular, we first clean the dataset to remove outlier and impute the missing value. Then we used a RFE framework for electing most significant predictors. Finally, we construct models with classification algorithms, tune the best parameters and compare the performances among them. Findings The results reveal that ML classification techniques can work well with CRM data in Korean retailing industry. Moreover, customer loyalty is impacted by not only unique factor such as net promoter score but also other purchase habits such as expensive goods preferring or multi-branch visiting and so on. We also prove that with retailing customer's dataset the model constructed by SVMs algorithm has given better performance than others. We expect that the models in this study can be used by other retailing companies to classify their customers, then they can focus on giving services to these potential vip group. We also hope that the results of this ML algorithm using R language could be useful to other researchers for selecting appropriate ML algorithms.

• The Journal of Information Technology
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• v.10 no.4
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• pp.69-83
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• 2007

As a hospital environment is reconstructed from supplier-centered values to consumer-centered ones for the existence in the rapidly changing medical market, it can be said that not only must old slogans such as unconditional restructuring, remodelling, etc. be reconsidered, but a new strategy for the development and renovation of a hospital must be urgently required. Accordingly, development of customer-oriented practical strategies is needed and it appears possible to develop marketing and manage contacts, as a practical management strategy, for raising satisfaction of internal and external customers. The ultimate goal of such strategy development may be to ensure consistent potential development by maintenance of existing customers and securing new customers through a strategy of satisfying both existing and new customers. It appears that the competition in the medial will be keener in the future by human resources, members of an organization, Under these circumstances, and in relation to appearance of a new type of occupation of a coordinator, if a hospital could offer appropriate service which can meet the demand of the customers by efficiently utilizing the limited resources through efficient management of contacts between the customers and personnel, the competitive power of a hospital would be much stronger. Therefore, it is necessary to seek customer-impressing management by utilizing a coordinator as a more specialized intermediary as well as many-sided contact management through positive introduction of an expert coordinator system for internal and external customer contact management. It is expected that a hospital can secure a competitive advantage in the market through strategy development supported by an expert coordinator and increasing competitive power by means of practice of a developed creative strategy.

• Journal of Intelligence and Information Systems
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• v.8 no.2
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• pp.15-35
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• 2002

Data mining has received a lot of attention from practitioners. That is partly because it allows company to extract a set of useful knowledge about customers from database, thereby retaining current customers and magneting potential customers. This logic is especially essential in the field of credit card industry, where just 5% increase of number of customers is hewn to cause 120% increase in profit. The problem is how to retain current customers and even make them more loyal to company. However, previous studies lacked proposing extensive strategies of reducing the churning rate. In this sense, this study attempts to suggest such strategies by applying neural network, logistic regression, and C5.0 techniques to credit card data. We used a real data set of four years from 1997 to 2000, which were gathered from a credit card company. Experimental results revealed that our approach could yield robust strategies for retaining customers by reducing the churning rate.