• Journal of the East Asian Society of Dietary Life
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• v.20 no.5
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• pp.812-822
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• 2010

This study explored choice attributes in specially coffee shops and examined the relations between choice attributes and positive emotions customers felt in specially coffee shops. The study also attempted to find differences in choice attributes and positive emotions according to general characteristics of customers and coffee-drinking behavior. Measured items were derived from preliminary interviews and a literature review. Questionnaires were distributed to customers in Seoul who had visited a specially coffee shop in the last 3 months. The derived factors of choice attributes were 'taste of coffee and atmosphere', 'brand', 'price benefit', 'pleasant space', and 'coffee itself. Among those, the two factors 'taste of coffee and atmosphere', and 'brand' had a statistically significant influence on positive emotions of customers. This implies that specially coffee shop customers have primarily emotional rather than utilitarian motivations. Therefore, to better satisfy customers' desires, more effort is needed to improve the physical environment in coffee shops. Female and younger customers showed higher perception of price benefits than others did. The perception of price benefits and pleasant space mainly varied by the location of coffee-drinking and frequency of visiting specially coffee shops. Further differences in positive emotion according to general characteristics and behaviors of having coffee also discussed.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.11
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• pp.297-305
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• 2021

The study aims to investigate loyalty rewards programs on customers' satisfaction in Jordanian banks, and to investigate the statistical differences in loyalty rewards programs and customers' satisfaction according to demographics such as age, sex, education level, duration of engagement with bank, and the type of bank. The study is based on the data obtained from the sample. The questionnaire is the tool for collecting data from the respondents. The study materials include website resources, regular books, journals, and articles. The study population consists customers in the banking sector. The figures indicate that number of actual customers reaches 2.06 million. The sample size requirement is 386 items. Customers are split between traditional and Islamic banks, with 231 and 155 customers respectively. The stratified random sampling technique and the structural equations modeling methodology were used. The results show moderated impact of the loyalty rewards programs on customers' satisfaction. The results show statistical differences in the loyalty rewards programs and customers' satisfaction according to the engagement period with the bank only. The findings suggest better managing the loyalty programs and developing one credit card for all banks in Jordan.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.213-225
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• 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 Distribution Science
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• v.16 no.6
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• pp.85-96
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• 2018

Purpose - There are many antecedences and consequences of the positive emotions of customers. The purpose of this research is to examine how Chinese service companies improve not only the positive emotions of customers but also the quality of life through effective verbal and nonverbal communication. Furthermore, we tried to analyze the moderating role of negative expectancy disconfirmation perceived by customers in those causal relationships among the variables. Research design, data, and methodology - The eight hypotheses were proposed and we tested them empirically in this research. Four hypotheses were about the relationship among communication, positive emotion, trust and quality of life. The other four hypotheses were about the moderating effect of negative expectancy disconfirmation in the causal relationships among four variables such as communication, positive emotion, trust and quality of life. A total of 356 samples who had visited the service companies in China were surveyed and 8 hypotheses were tested by empirical analysis using SPSS and AMOS. Results - The results of this research are as follows. First, positive verbal communication and nonverbal communication of employees in the service company have a positive effects on the positive emotions of customers. Second, positive emotion has a positive effect on the overall quality of life on the customer side as well as the trust on the corporate side. Third, negative expectancy disconfirmation perceived by customers has negative moderating effect in the causal relationship between employees' positive verbal communication and customers' positive emotion, and it also has a negative moderating role in the causal relationship between customers' positive emotion and overall quality of life. Conclusions - Based on these results, there can be such implications as follows. First, managers and employees of service companies can induce positive emotion of customers through effective communication. Second, service companies should try to improve not only the corporate-side performance like trust but also the customer-side performance like quality of life. Third, it will be significant for them to lower the level of negative expectancy disconfirmation for the purpose of improving not only the positive emotions of customers but also the quality of customers' life.

• The Korean Journal of Community Living Science
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• v.19 no.4
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• pp.537-546
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• 2008

The purposes of the study was to identify customers' satisfaction factors regarding foods and services in food courts in big department stores and discount stores in Seoul and Cheonan. A survey of 235 customers was conducted regarding customer satisfaction levels and factors of food and services. Customers' perceived level of attributes were identified into eight underlying dimensions by factor analysis as follows: factor 1 was "cleanliness": factor 2 "service quality": factor 3 "accuracy": factor 4 "atomosphere": factor 5 "food quality": factor 6 "menu information": factor 7 "price" and the eighth factor was "food result". Regression analysis indicated that "cleanliness" was found to be the most important factor contributing to customers' overall satisfaction. There were significant differences in customers' perceived satisfaction level of "food quality"(p<0.01), "accuracy", and "price" factors(p<0.05) between department stores and discount store. The customers' perceived satisfaction levels of "accuracy", "food quality" and "price" factor at a large store food court are higher than those of department store food court. Comparing location of food court, there were significant differences in customers' perceived satisfaction level of "accuracy" and "price" factors between in Seoul and Cheonan(p<0.001). The customers' perceived satisfaction levels of "accuracy" and "price" at the discount store in Seoul are lower than those of food court at Cheonan. It is suggested that the management should pay attention to the sanitation of their dinning halls, kitchens, hygienic dishes, hygienic water fountain, employee hygiene, and a proper place to put used dishes to increase the customers' satisfaction.

• Journal of applied mathematics & informatics
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• v.30 no.5_6
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• pp.749-757
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• 2012

We consider the M/PH,G/1 queue with two classes of customers in which class-1 customers have deterministic impatience time and have preemptive priority over class-2 customers who are assumed to be infinitely patient. The service times of class-1 and class-2 customers have a phase-type distribution and a general distribution, respectively. We obtain performance measures of class-2 customers such as the queue length distribution, the waiting time distribution and the sojourn time distribution, by analyzing the busy period of class-1 customers. We also compute the moments of the queue length and the waiting and sojourn times.

• Management Science and Financial Engineering
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• v.11 no.3
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• pp.47-60
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• 2005

Well-known e-CRM strategy is to focus on profitable customers and pay less attention to unprofitable ones. Moreover, some researchers recommend not serving unprofitable ones any more. However, it often neglects customers indirect value. Deselecting unprofitable customers can raise the issue of bad word-of-mouth publicity especially in the age of the Internet. Some studies pointed out that a customers decision to buy a product or service is often strongly influenced by others. In this paper, we consider customers' word-of-mouth effect on quality learning of inexperienced customers. We show that firms implementing e-CRM must take the effect into the consideration when deselecting unprofitable customers.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.05a
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• pp.274-282
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• 2005

Customer retention is one of the major issued in life insurance industry, in which competition is increasingly fierce. There are many things to do to retain customers. One of those things is to be continuously in touch with all customers. The objective of this study is to design the contact scheduling system(CSS) to support the planers who must touch the customers without having subjective information. Support-planers suffer from lack of information which can be used to intimately touch. CSS that is developed in this study generates contact schedule to touch customers by taking into account existing contact history. CSS has a two stage process. In the first stage, it segments customers according to his or her demographics and contract status data. Then it finds typical pattern and pattern is combined to business rules for each segment. We expert that CSS would support support-planers to make uncontacted customers' experience positive.

• Journal of Korea Technology Innovation Society
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• v.7 no.3
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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.

• Proceedings of the Korean Statistical Society Conference
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• 2004.11a
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• pp.289-294
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• 2004

We consider M/G/1 queue in which the customers are classified into n+1 classes by their impatience time. First, we analyze the model of two types of customers; one is the customer with constant impatience duration k and the other is patient customer. The expected busy period of the server and the limiting distribution of the virtual waiting time process are obtained. Then, the model is generalized to the one in which there are classes of customers according to their impatience duration.