• The Journal of Asian Finance, Economics and Business
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• 제7권8호
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• pp.395-405
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• 2020

This study examines the relationships and the impacts of service quality, customer satisfaction and switching costs on customer loyalty of e-banking in commercial banks. This study uses questionnaires with 7-point Likert scale to collect data from 227 e-banking users, who are mainly students and paid employees in Hanoi City, Vietnam. The collected data are analyzed by using multivariate linear regression method. The results show that all five factors of service quality in e-banking - reliability, responsiveness, service capacity, empathy and tangibility - have positive correlations with customer satisfaction. Among these determinants, service capacity and tangibility have the strongest impact. It means that, by increasing the quality of their services through five above factors, especially through improving capacity and tangibility, commercial banks can satisfy their customer better. In addition, customer satisfaction is strongly and positively correlated to customer loyalty. It means that, if customers are satisfied with e-banking services of one bank, they not only continue to do more businesses with this bank, but also recommend this bank to other people. Lastly, customer loyalty also has a strong and positive correlation with switching costs, which means customers tend to be loyal to one bank if the barriers to switching banks increase.

• 동아시아경상학회지
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• 제9권4호
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• pp.93-102
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• 2021

Purpose - Among the various pricing approaches used to set fares for express trains, this study explores a method of utilizing a customer-based pricing approach. The purpose of this study is to figure out how to apply the customer-based pricing approach to fares of new railway services using express trains. Research design, data, and methodology - This study was conducted through a literature review and case studies. In the literature review, we examined three approaches, focusing on the customer-based pricing approach and its application. In the case studies, we show how a customer-based pricing approach can be applied to determining the fares for railway services. Result - Some studies have used a customer-based pricing approach to set railway service rates, adapting the concepts of customer-based pricing such as demand, elasticity, value and willingness to pay. When setting fares of new railway services, it is recommended to use the customer-based approach in conjunction with other pricing approaches. Conclusion - This study demonstrates that a customer-based pricing approach is a promising tool in making decisions on railway fares. By applying a customer-based pricing approach to fares for new railway services using express trains, railway operators can utilize new service rates and increase the profitability of the railway business.

• 한국IT서비스학회지
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• 제14권4호
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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.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2007년도 추계학술대회
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• pp.489-498
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• 2007

For better predictions and classifications in customer recommendation, this study proposes an integrative model that efficiently combines the currently-in-use statistical and artificial intelligence models. In particular, by integrating the models such as Association Rule, Frequency Matrix, and Rule Induction, this study suggests an integrative prediction model. The data set for the tests is collected from a convenience store G, which is the number one in its brand in S. Korea. This data set contains sales information on customer transactions from September 1, 2005 to December 7, 2005. About 1,000 transactions are selected for a specific item. Using this data set, it suggests an integrated model predicting whether a customer buys or not buys a specific product for target marketing strategy. The performance of integrated model is compared with that of other models. The results from the experiments show that the performance of integrated model is superior to that of all other models such as Association Rule, Frequency Matrix, and Rule Induction.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2003년도 추계학술대회 및 정기총회
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• pp.121-124
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• 2003

It is a major concern of e-shopping mall managers to satisfy a variety of customer's desire by recommending a proper commodity to the expected purchaser. Customer information like customer's fondness and idiosyncrasy in shopping has not been used effectively for the customers or the suppliers. Conventionally, e-shopping mall managers have recommended specific items of commodities to their customers without considering thoroughly in a customer point of view. This study introduces the ways of a choosing and recommending of commodities for customer themselves or others. A similarity measure between one member's idiosyncrasy and the other members' is developed based on the rule base and the case base. The case base is improved by recognizing and learning the changes of customer's desire and shopping trend.

• 한국경영과학회지
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• 제33권2호
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• pp.115-135
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• 2008

An interesting problem in capacitated supply chains is how to guarantee customer service levels with limited resources. One of the common approaches to solve the problem is differentiating service depending on customer classes. High-priority customers receive a better service at the cost of low-priority customers' service level. One of common criteria to determine a customer's priority in practice is whether he has made a reservation before arrival or not. Customers with a reservation usually receive service based on the time the reservation was made. We examine the effect this advance information of customer arrival has on customer service levels. We show the trade-offs between the leadtime and other system characteristics such as the proportion of high-priority customers. when the service level is high. We also suggest how to differentiate service using the asymptotic ratio of the service levels for both types of customers.

• 경영과학
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• 제19권2호
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• pp.205-220
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• 2002

As the business structure of many industries changes under IT progress and internet economy, the customer information has emerged a key factor in setting up the management policy. The customer has come to replace the product as a central figure in business competition. The domestic life insurance market has also experienced the rapid structural changes in IT time. The competition in the insurance industry to maintain the existing membership and to attract the new members gets stronger under such a new business circumstance. Accordingly, it is necessary for an individual insurance company to develop a systematic marketing plan, based on the customer information, to be competitive in the market. Unlike other studies in which customer characteristics are neglected, this study attempts to utilize the customer information by applying the data mining technique, and then suggests an efficient marketing strategy that could prevail in the competitive business environment.

• 기술혁신학회지
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• 제7권3호
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• pp.681-709
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• 2004

The purpose of this study is to classify customers by e-mail responsiveness on time-series analysis and testify the effectiveness of grouping by ROI analysis. Response recency, response frequency and Activity(RFA) of e-mailing systems are adapted for Customer segmentations. ROI analysis are consisted of open, click-through, duration time, personalization, conversion rate and email loyalty index of email systems. Major findings are as follows: RFA analysis is used for customer segmentations that is fundamental process of e-CRM applications. Customers can be grouped into loyal customers, odds customers, dormant customers, secession customers, and observation customers by RFA grouping. Loyal customer group has high point in all ROI index compared to other groups. These results indicated that customer responsiveness of e-mail systems were appropriate methods to group the customer with demographic variables. Therefore, effective e-mail marketing strategy of e-Biz should have suitable active DB and Behavior targeting is best approach to enforce the target e-mail marketing.

• 한국경영과학회지
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• 제39권1호
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• pp.29-48
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• 2014

The recent keyword advertising does not reflect the individual customer searching pattern because it is focused on each keyword at the aggregate level. The purpose of this research is to observe processes of customer searching patterns. To be specific, individual deal-proneness is mainly concerned. This study incorporates location as a control variable. This paper examines the relationship between customers' searching patterns and probability of purchase. A customer searching session, which is the collection of sequence of keyword queries, is utilized as the unit of analysis. The degree of deal-proneness is measured using customer behavior which is revealed by customer searching keywords in the session. Deal-proneness measuring function calculates the discount of deal prone keyword leverage in accordance with customer searching order. Location searching specificity function is also calculated by the same logic. The analyzed data is narrowed down to the customer query session which has more than two keyword queries. The number of the data is 218,305 by session, which is derived from Internet advertising agency's (COMAS) advertisement managing data and the travel business advertisement revenue data from advertiser's. As a research result, there are three types of the deal-prone customer. At first, there is an unconditional active deal-proneness customer. It is the customer who has lower deal-proneness which means that he/she utilizes deal-prone keywords in the last phase. He/she starts searching a keyword like general ones and then finally purchased appropriate products by utilizing deal-prone keywords in the last time. Those two types of customers have the similar rates of purchase. However, the last type of the customer has middle deal-proneness; who utilizes deal-prone keywords in the middle of the process. This type of a customer closely gets into the information by employing deal-prone keywords but he/she could not find out appropriate alternative then would modify other keywords to look for other alternatives. That is the reason why the purchase probability in this case would be decreased Also, this research confirmed that there is a loyalty effect using location searching specificity. The customer who has higher trip loyalty for specificity location responds to selected promotion rather than general promotion. So, this customer has a lower probability to purchase.

• 한국병원경영학회지
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• 제18권3호
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• pp.1-26
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• 2013

To improve the competitiveness of the hospital provides high quality medical services in a hospital coordinator role is emphasized. This study on customer orientation of the role ambiguity in order to identify the impact of degree of customer orientation were analyzed for demographic differences. Dependent variable, customer orientation affects role ambiguity as independent variables, and regression analysis were set. And the control variables are set to support situational factors, customer orientation on the role ambiguity and hierarchical regression analysis was performed. Obtained through empirical results are as follows: First, according to the demographic characteristics of the hospital coordinator customer orientation, the difference between gender and medical subjects are not shown. Age, education, work experience, job title, and the hospital on the pattern of customer orientation has shown a difference. Second, according to the hospital coordinator role ambiguity about its impact on customer orientation analysis can be a role implementation, job implementation, opinion communication in achieving customer orientation was negatively affected. Third, role ambiguity, and customer orientation factors for the moderating effects of organizational support for the role of customer orientation can role implementation, job implementation, opinion communication was a statistically significant. Fourth, the role ambiguity factors and customer orientation for the administrative support for the moderating effect of customer orientation and role implementation is significant, but job implementation, opinion communication were statistically significant. Fifth, the role ambiguity factors and customer support for customer orientation and customer orientation for the moderating effects of role performance and the opinion communication was not statistically significant. However, job implementation was statistically significant. The limitations of this study are as follows: First, role ambiguity, situational factors and support due to limitations of the variable factors that may affect the customer orientation of a number of factors were excluded. So many exogenous variables in the measurement process can affect. Second, the variables measured as problems of self-assessment by the variable measuring the respondent's bias may occur. Third, This study is difficult to generalize. In other words, several areas of the province conducted by the empirical results of the survey as a limit on the overall generalization can follow.