• The Research Journal of the Costume Culture
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• v.11 no.1
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• pp.103-117
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• 2003

The aim of this study was to identify dimensions of salesperson´s effort according to older female(55+) customer's and fashion store salesperson's perspective and to examine what kind of effort dimensions are assessed to be more important than others. As a method, both literature review and empirical research were made. This study was performed in three stage from December in 2001 to May in 2002. For exploratory step. In-depth interview and observation study were done for gathering responses related to salesperson´s effort. in pilot study, 83 older female customers were surveyed and the data was analyzed in order to develop questionnaire. In the main research. 202 older female customers and 103 fashion store salespersons were surveyed in order to identify the dimensions of salesperson's effort. Statistical analyses were performed with SAS program using factor analysis. cronbach´a mean, t-test. paired t-test and multiple regression analysis. The results of this study were as follows. First, 5 factors was selected for the dimensions of salesperson´s effort in customer´s perception; friendliness, attentiveness. product competence. effective access and special treatment. Second, 5 factors was selected for the dimensions of salesperson's effort in salesperson´s performance; friendliness/ attentiveness. product competence. effective access. communication, and purchase exaction. Third. dimensions of salesperson's effort were different according to customer and salesperson's characteristics. Last, there were significant differences in the salesperson's efforts between customers´perception and salespersons´Performance.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.291-300
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• 2005

Recently, e-Biz Companies are paying attention to e-CRM in an effort to utilize meaningful customers' information obtained using their websites. e-Biz companies try to increase the profit by collecting customers' data, serving customers better through interactive communications and differentiating customers' management using their websites. Although it is found that corporates' websites play a critical role in e-CRM, only a few researches have been conducted related to the effective website design. Tn this study, desirable website design factors were identified through literature review, and an empirical study was conducted to identify how these factors are related to customer's loyalty measured via customer's intention for continuous use and recommendation the website to others. Also this study was designed to suggest a benchmark for the companies which plan to build a website for e-CRM in the future.

• The Journal of Industrial Distribution & Business
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• v.14 no.9
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• pp.31-39
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• 2023

Purpose: Social media's increasing adoption and the development of digital technology have completely changed how businesses interact with their clients. The current study is to examine the impact of live broadcasts on consumers' perceptions and actions across a range of fresh food goods. Research design, data and methodology: The scrutiny relies on the existing peer-reviewed literature, which may prevent a comprehensive evaluation of some recent advancements in the subject. Despite these caveats, the outcomes of this scrutiny are anticipated to contribute significantly to our understanding of the effect of live broadcast marketing on consumers' propensity to make purchases. Results: Previous literature review clearly states that 'Live Broadcast of Fresh Food' to attract relevant customers should be followed: (1) Increased Product Transparency and Trust, (2) Enhanced Customer Engagement, (3) Impact on Customer's Perception of Product Quality, and (4) sense of urgency and scarcity. Conclusions: All in all, the study's advice for firms in the food industry to improve their marketing efforts through live broadcasts have important practical ramifications. Promoting openness and trust in the production process and with the audience boosts a brand's reliability. Customers are more likely to participate and feel more connected to a brand.

• The Journal of the Korea Contents Association
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• v.14 no.3
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• pp.401-413
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• 2014

The principal objective of this study is to examine the relationship between the emotional intelligence and customer orientation in airline service context. Moreover, this study was designed to test the moderating effect of social support to provide fundamental and practical data for airline industry. In this study, 2 hypotheses based on literature reviews were employed. A questionnaire was also developed based on previous studies. A convenience sample of 233 flight attendants was surveyed and a total of 214 usable questionnaires were analyzed. Then the data and hypotheses were examined using multiple regression analysis using SPSS 18.0. The results are as follows. Firstly, emotional intelligence was divided into 'self-emotional appraisal', 'other's emotional appraisal', 'regulation of emotion' and 'use of emotion' according to the literature review. Analysis showed that emotional intelligence has partial effect on customer orientation accordingly. Secondly, social support has partial moderating effects between emotional intelligence and customer orientation. Continuous and systematic training program which build up team work should be conducted to administer 'emotional intelligence'.

• Information Systems Review
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• v.12 no.2
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• pp.75-88
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• 2010

This paper proposed a method that segmented customers utilizing SOM(Self-organizing Map) and predicted the customers' response of a marketing promotion for each customer's segments. Our proposed method focused on predicting the response of customers dividing into customers' segment whereas most studies have predicted the response of customers all at once. We deployed logistic regression, neural networks, and support vector machines to predict customers' response that is a kind of dichotomous classification while the integrated approach was utilized to improve the performance of the prediction model. Sample data including 45 variables regarding demographic data about 600 customers, transaction data, and promotion activities were applied to the proposed method presenting classification matrix and the comparative analyses of each data mining techniques. We could draw some significant promotion strategies for segmented customers applying our proposed method to sample data.

• Korean Management Science Review
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• v.19 no.1
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• pp.129-142
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• 2002

Data fusion Is a technique used for creating an Integrated database by combining two or more databases that include a different set of variables or attributes. This paper attempts to apply data fusion technique to customer relationships management (CRM), in that we can not only plan a database structure but also collect and manage customer data In a more efficient way In particular our study Is useful when no s1n91e database Is complete, i.e., each and every subject in the pre-integrated database contains somewhat missing observations. According to the way of treating the common variables, donors can be differently selected for the substitution of the missing attributes of recipients. One way is to find the donor that has the highest correlation coefficient with the recipient by. treating common variables metrically The other is based on the closest distance by the correspondence analysis in case of treating common variables nominally. The predictability of data fusion for CRM can be evaluated by measuring the correlation of the original database and the substituted one. A Monte Carlo Simulation analysis is used to examine the stability of the two substitution methods in building an integrated database.

• Information Systems Review
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• v.8 no.2
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• pp.119-138
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• 2006

Association Rule Mining has been successfully used for mining knowledge in static environment but it provides limited features to discovery time-dependent knowledge from multi-point data set. The aim of this paper is to develop a methodology which detects changes of customer behavior automatically from customer profiles and sales data at different multi-point snapshots. This paper proposes a procedure named 'Recursive Change Mining' for detecting continuous change of customer purchase behavior. The Recursive Change Mining Procedure is basically extended association rule mining and it assures to discover continuous and repetitive changes from data sets which collected at multi-periods. A case study on L department store is also provided.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.9
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• pp.1153-1158
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• 2018

Online customer evaluations and social media information among a variety of information sources are critical for businesses as it influences the customer's decision making. There are limitations on the time and money that the survey will ask to identify a variety of customers' needs and complaints. The customer review data at online shopping malls provide the ideal data sources for analyzing customer sentiment about their products. In this study, we collected product reviews data on the smartphone of Samsung and Apple from Amazon. We applied five classification algorithms which are used as representative sentiment analysis techniques in previous studies. The five algorithms are based on support vector machines, bagging, random forest, classification or regression tree and maximum entropy. In this study, we proposed entropy score which can comprehensively evaluate the performance of classification algorithm. As a result of evaluating five algorithms using an entropy score, the SVMs algorithm's entropy score was ranked highest.

• Journal of Korean Society for Quality Management
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• v.50 no.3
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• pp.593-615
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• 2022

Purpose: The purpose of this study was to explore and examine the factors influencing customer satisfaction and subscription intention in order to propose useful implication regarding subscription economy model. Methods: This study adopts the extended Unified Theory of Acceptance and Use of Technology model (UTAUT2) as the theoretical framework. On the basis of literature review, this study suggested 9 related hypothesis. To examine the hypothesis proposed, the study designed surveys with 32 questions and 456 answers were collected for the analysis. The study adopted a structural equation model and path analysis, using AMOS and SPSS programs. Results: The results of this study are as follow: All hypothesis except performance expectancy and effort expectancy have significant influence on customer satisfaction. Performance expectancy and effort expectancy have no significant influence on customer satisfaction and facilitate condition is significant but negatively associated with customer satisfaction. Conclusion: Result of this study is expected to suggest data regarding subscription economy and customer satisfaction for business with subscription model. In detail the result implies that highly sophisticated curation system would create more customer satisfaction and subscription intention rather than how a subscription-based platform is easily used. Moreover, curation system of subsription-based music platform should function with high accuracy on recommendation in a creative visual form in order to gain comparative advantage while most platforms have built own curation service.

• Journal of Korean Society for Quality Management
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• v.49 no.4
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• pp.595-607
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• 2021

Purpose: This study introduces a systematic framework to evaluate service satisfaction of cosmetic brands through online review analysis utilizing Text-Mining technique. Methods: The framework assumes that the service satisfaction is evaluated by positive comments from online reviews. That is, the service satisfaction of a cosmetic brand is evaluated higher as more positive opinions are commented in the online reviews. This study focuses on two approaches. First, it collects online review comments from the top 50 global cosmetic brands and evaluates customer service satisfaction for each cosmetic brands by applying Sentimental Analysis and Latent Dirichlet Allocation. Second, it analyzes the determinants that induce or influence service satisfaction and suggests the guidelines for cosmetic brands with low satisfaction to improve their service satisfaction. Results: For the satisfaction evaluation, online review data were extracted from the top 50 global cosmetic brands in the world based on 2018 sales announced by Brand Finance in the UK. As a result of the satisfaction analysis, it was found that overall there were more positive opinions than negative opinions and the averages for polarity, subjectivity, positive ratio, and negative ratio were calculated as 0.50, 0.76, 0.57, and 0.19, respectively. Polarity, subjectivity and positive ratio showed the opposite pattern to negative ratio, and although there was a slight difference in fluctuation range and ranking between them, the patterns are almost same. Conclusion: The usefulness of the proposed framework was verified through case study. Although some studies have suggested a method to analyze online reviews, they didn't deal with the satisfaction evaluation among competitors and cause analysis. This study is different from previous studies in that it evaluates service satisfaction from a relative point of view among cosmetic brands and analyze determinants.