• Asia Marketing Journal
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• v.10 no.2
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• pp.125-151
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• 2008

Both companies and consumers are highly interested in on-line customer reviews which enable consumers to share their experience and knowledge about products. In this study, after classifying real reviews into context units and deriving categories, we analyzed differences between categories based on channel(manufacturers' homepage/ shopping mall), product attribute(search/experience) and price(high/low). The method to derive categories is based on roughly adopting constructs of ACSI model and elaborate and repetitive classification of real reviews. We set up the classification category with 3 levels. Level 1 consists of product and service, level 2 consists of function, design, price, purchase motive, suggestion/user-tip and recommendation/repurchase in product and AS/up-grade and delivery/others in service and level 3 is composed of details of level 2 of category. We could find remarkable differences between channels in all 8 items of level 2 of category. As the number of context units in homepage is more than in shopping mall, we found reviews in homepage is more concrete. Moreover, overall satisfaction in review was higher at homepage's. Also, in product attribute dimension, we found different patterns of reviews in design, purchase motive, suggestion/user-tip, recommendation/repurchase, AS/up-grade and delivery/others and no difference in overall customer's satisfaction. In price dimension, we found differences between high and low price in design, price and AS/up-grade and no difference in overall customer's satisfaction.

• Information Systems Review
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• v.17 no.1
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• pp.49-64
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• 2015

Customer reviews which include subjective opinions for the product or service in online store have been generated rapidly and their influence on customers has become immense due to the widespread usage of SNS. In addition, a number of studies have focused on opinion mining to analyze the positive and negative opinions and get a better solution for customer support and sales. It is very important to select the key terms which reflected the customers' sentiment on the reviews for opinion mining. We proposed a document-level terms-based sentiment classification model by select in the optimal terms with part of speech tag. SVMs (Support vector machines) are utilized to build a predictor for opinion mining and we used the combination of POS tag and four terms extraction methods for the feature selection of SVM. To validate the proposed opinion mining model, we applied it to the customer reviews on Amazon. We eliminated the unmeaning terms known as the stopwords and extracted the useful terms by using part of speech tagging approach after crawling 80,000 reviews. The extracted terms gained from document frequency, TF-IDF, information gain, chi-squared statistic were ranked and 20 ranked terms were used to the feature of SVM model. Our experimental results show that the performance of SVM model with four POS tags is superior to the benchmarked model, which are built by extracting only adjective terms. In addition, the SVM model based on Chi-squared statistic for opinion mining shows the most superior performance among SVM models with 4 different kinds of terms extraction method. Our proposed opinion mining model is expected to improve customer service and gain competitive advantage in online store.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.233-241
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• 2012

The object of the project management is to succeed in the project. However, could you definitely judge that the result of project performance is a success? In addition, do both customer and developer agree with the result of your judgement? There are a lot of definitions and measure for the success and failure of the software development suggested, but there is no definite standard for the classification. This paper examines the measures in order to decide the development success and re-defines the success and the failure of the project. We suggest the measure and the standard that judge the project achievement based on these definitions. Applying the suggested measure and standard, it is possible to reduce arguments between the customer and the developer on the classification of the success and the failure.

• 한국HCI학회:학술대회논문집
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• 2006.02b
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• pp.179-184
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• 2006

"사용자 중심의 디자인(User-Centered Design)" 은 좋은 사용성을 가진 제품을 만들기 위한 사용되는 보편적인 접근방법중의 하나이다. 그러나 투자대비 최대의 가치 창조라는 경제성 원리와 개발 기간의 제약을 고려하면 개발 중 사용성 평가를 통해 발견된 문제들을 모두 제품에 반영하는 것은 거의 불가능 하다고 볼 수 있다. 그러므로 발견된 문제들에 대한 우선 순위를 정의한 후 가장 중요한 문제점에 대해 먼저 개선하는 전략이 필요하다. 기존의 사용성 문제에 대한 우선 순위는 주로 문제 자체의 심각도를 고려하여 결정되었다. 그러나 사용자가 인식하는 사용성(Perceived Usability)를 높이기 위해서는 사용자가 중요하게 생각하는 효용을 우선적으로 제품에 반영하는 것이 필수적이다. 본 연구에서는 카노의 사용자 만족 모델을 활용한 사용자 효용과 사용성 문제들의 잠재가치를 고려한 사용성 문제 분류를 기구 사용성 평가 가이드라인의 제작에 적용하였다. 제안된 분류에 의해 디자인 가이드라인을 1) 반드시 만족 시켜야하는 제품 사용성 기준, 2) 경쟁사 대비 우위를 유지하기 위한 비교평가 기준으로 나누어 정의함으로써 단일 제품의 절대적 평가가 아닌 경쟁사 제품과의 비교 평가를 통한 개선 방향의 제시에 Kano 모델을 기반으로 정의된 사용성 문제들의 효용가치분류가 효과적이라는 것을 본 연구를 통해 보이고자 한다.

• Journal of the Korean Dietetic Association
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• v.12 no.3
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• pp.235-242
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• 2006

The purpose of this study of was to provide basic data for preparing event menus to increase customer's satisfaction by investigating university students' participation and preference for the event menus in the foodservice operations. The questionnaires were distributed to 300 customers from August 1 to 31, 2005. 88.0% of the questionnaires were analyzed. Statistical analysis of data was performed using SAS package program(version 8.2) for descriptive analysis and $χ^2$-test, t-test, one-way ANOVA, Duncan multiple range test. The results of this study can be summarized as follows : 50.4% of the students have participated in foodservice operation's event and the average degree of the satisfaction was 2.67 out of 5. The type of the events customers have most frequently participated in were the national holiday·subdivisions of the season event(47.3%), the day event(34.1%), environment event(26.9%) and so on. In large classification, preferred were season event(85.2%), international food event(76.9%), and healthy food event(73.1%) and so on. In small classification, orgarnic food event(53.0%), summer fruits festival(41.3%), midsummer event(36.6%) and christmas event(34.4%) and so on. From now on, the event reflecting customers' expectation and requirement should be planned and implemented.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.1
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• pp.13-21
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• 2010

The prediction of contract cancellation of customers is essential in insurance companies but it is a difficult problem because the customer database is large and the target or cancelled customers are a small proportion of the database. This paper proposes a new data mining approach to the binary classification by handling a large-scale unbalanced data. Over-sampling, clustering, regularized logistic regression and boosting are also incorporated in the proposed approach. The proposed approach was applied to a real data set in the area of insurance and the results were compared with some other classification techniques.

• Knowledge Management Research
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• v.20 no.3
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• pp.139-154
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• 2019

With the increasing use of smartphone apps, many apps are coming out in various fields. In order to analyze the current status and trends of apps in a specific field, it is necessary to establish a classification scheme. Various schemes considering users' behavior and characteristics of apps have been proposed, but there is a problem in that many apps are released and a fixed classification scheme must be updated according to the passage of time. Although it is necessary to consider many aspects in establishing classification scheme, it is possible to grasp the trend of the app through the proposal of a classification scheme according to the characteristic of the app. This research proposes a method of establishing an app classification scheme through the description of the app written by the app developers. For this purpose, we collected explanations about apps in the tourism field and identified major categories through topic modeling. Using only the apps corresponding to the topic, we construct a network of words contained in the explanatory text and identify subcategories based on the networks of words. Six topics were selected, and Clauset Newman Moore algorithm was applied to each topic to identify subcategories. Four or five subcategories were identified for each topic.

• 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.

• The Journal of Information Systems
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• v.27 no.1
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• pp.43-65
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• 2018

Purpose The emergence of mobile applications has simplified our life in various ways. Regarding tourism activities, mobile applications are already efficient in providing personalized tourism related information and are very much effective in booking hotels, flights, etc. However, there are very few studies on classifying the actual service requirements and improving the customer satisfaction in mobile tourism applications. The purpose of this study is to implement a practical mobile tourism application. To serve the purpose, we classify and categorize the service requirement of mobile tourism applications in Korea. We employed Kano model and analytic hierarchy process (AHP). Specifically, we conducted a focus group study to find out the service requirements in mobile tourism applications. Design/methodology/approach The data for this study were collected from Koreans and Foreigners who has the experience using mobile tourism applications. Participants needed to be familiar with mobile tourism applications because such users may be more aware of the mobile tourism applications services. We analyzed 147 valid data using Kano model and conducted AHP analysis on five experts in the field of tourism using Expert Choice software. Findings In this paper, we identified the 17 service quality requirements in the mobile tourism applications. The results reveal that the service requirement such as Geo-location map, Multilingual option, Compatibility with different operating systems were unavoidable service, absent of such requirements leads to the dissatisfaction. Based on the results of the integrated application of both Kano model and AHP analysis, this study provide specific implications for improving the service quality of the mobile tourism applications in Korea.

• Korea Journal of Hospital Management
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• v.14 no.4
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• pp.88-102
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• 2009

This study aims at providing necessary informations to decide what services would be conducted preferentially in the hospital by limited resources. So this study revalued the customer's perception about the qualities of the hospital services by the Kano Model and examined the customer satisfaction coefficients suggested by Timko. The researcher conducted a survey from the patients of the 4 university hospitals in Incheon and southern Gyeonggi Province In 2008. The results of this study can be summarized as follows; It was found that the total 31 items are could be classified into 7 attractive quality elements, 22 one-dimensional quality elements and 2 indifferent quality elements, while the natural quality element wasn't found. The highest score element of the customer's satisfaction coefficients was identified as easy parking(0.69) and the lowest score item was the offer of the hospital newsletter and information about medical care(0.47). When the hospital service was not sufficient to the customer, the highest score element of the customer's dissatisfaction coefficients was proved the convenient ward and facilities(-0.75) and the lowest score item was the buses running to the entrance of the hospital(-0.32). Also it was found that the attractive quality elements appraised by the preceding study were revalued the one-dimensional quality elements. The reason was because the customer's expectation on the services was changed high, as time went by.