In order to satisfy customers, it is important to identify the quality elements that affect customers’ satisfaction. The Kano model has been widely used in identifying multi-dimensional quality attributes in this purpose. However, the model suffers from various shortcomings and limitations, especially those related to survey practices such as the data amount, reply attitude and cost. In this research, a model based on the text sentiment analysis is proposed, which aims to substitute the survey-based data gathering process of Kano models with sentiment analysis. In this model, from the set of opinion text, quality elements for the research are extracted using the morpheme analysis. The opinions’ polarity attributes are evaluated using text sentiment analysis, and those polarity text items are transformed into equivalent Kano survey questions. Replies for the transformed survey questions are generated based on the total score of the original data. Then, the question-reply set is analyzed using both the original Kano evaluation method and the satisfaction index method. The proposed research model has been tested using a large amount of data of public IT service project evaluations. The result shows that it can replace the existing practice and it promises advantages in terms of quality and cost of data gathering. The authors hope that the proposed model of this research may serve as a new quality analysis model for a wide range of areas.

Current evaluation practices for IT projects suffer from several problems, which include the difficulty of self-explanation for the evaluation results and the improperly scaled scoring system. This study aims to develop a methodology of opinion mining to extract key factors for the causal relationship analysis and to assess the feasibility of quantifying evaluation scores from text comments using opinion mining based on big data analysis. The research has been performed on the domain of publicly procured IT proposal evaluations, which are managed by the National Procurement Service. Around 10,000 sets of comments and evaluation scores have been gathered, most of which are in the form of digital data but some in paper documents. Thus, more refined form of text has been prepared using various tools. From them, keywords for factors and polarity indicators have been extracted, and experts on this domain have selected some of them as the key factors and indicators. Also, those keywords have been grouped into into dimensions. Causal relationship between keyword or dimension factors and evaluation scores were analyzed based on the two research models-a keyword-based model and a dimension-based model, using the correlation analysis and the regression analysis. The results show that keyword factors such as planning, strategy, technology and PM mostly affects the evaluation result and that the keywords are more appropriate forms of factors for causal relationship analysis than the dimensions. Also, it can be asserted from the analysis that evaluation scores can be composed or calculated from the unstructured text comments using opinion mining, when a comprehensive dictionary of polarity for Korean language can be provided. This study may contribute to the area of big data-based evaluation methodology and opinion mining for IT proposal evaluation, leading to a more reliable and effective IT proposal evaluation method.

정부에서는 발주하고 관리하는 정보화 사업은 년 3조원 규모로, 이러한 정보화 사업은 대부분 사업수행 업체가 제출한 제안서를 분야별 전문가들에 의해 평가를 진행한 후 사업 수행자를 선정하게 된다. 제안서 평가는 제시된 평가기준에 의해 평가위원의 정성적 판단에 따라 점수를 부여 하고 있으나, 실제 평가위원이 어떠한 부분에 중점적으로 관심을 가지고 점수를 부여하는지는 알 수 없다. 이에 본 연구에서는 평가위원의 제안서 평가 시 어떠한 요인이 평가점수 부여에 영향을 미치는지 분석 하고자 한다. 연구를 진행하기 위해서는 평가를 진행하는 평가위원을 직접 대면 조사를 통해 자료를 수집해야 한다. 그러나 평가위원 명단이 보안상 공개되지 않아서 조사에 현실적으로 어려움이 있고, 또한 설문조사 등으로 직접 조사하기에는 부적절한 측면이 있다. 본 연구에서는 온라인 평가시스템에 등록된 평가위원의 평가의견(Text) 분석을 통해 요인을 분석 하고자 한다. 데이터 분석 도구인 R을 이용하여 온라인 평가시스템에 등록된 평가의견에서 형태소를 추출, 평가에 영향을 줄 수 있는 주요 요인과 극성을 나타내는 Keyword 사전을 구축 하였고 주요 요인을 이해력, 수행력, 관리력 3개의 차원으로 분류 하였다. 이를 통해 평가위원이 실제 입력한 점수와 주요 요인, 극성 조합에 의해 산출된 점수가 어떠한 상관 관계가 있는지 분석하기 위하여 회귀 분석을 실시, 주요 요인들이 평가 점수에 미치는 영향도에 대한 신뢰도를 검증할 계획이다. 본 연구의 결과는 비정형 형태로 입력된 의견을 실제 평가결과 점수로 수치화 할 수 있는 방법론 수립의 기초가 될 것으로 기대 한다.

The quality of service in ERP services is a key issue in innovating the ERP performance as an IT service for corporations. Currently, most of the research works for this area are based on the existing quality models such as SERVQUAL, which are said not to measure service quality properly. Also, it does not consider the factor of the system acceptance, which is thought to be closely related to the quality of service in this type of IT services. Therefore, a research model is required, which can address the issues related to the ERP service quality measurements. In this paper, new research models have been proposed, and empirical data obtained from SME’s ERP users have been applied to the proposed model to analyze the causal relationship between quality factors and to identify the most suitable quality measures. Also, the relationship between the service quality and the system acceptance was analyzed using a combined model. The results show that factors such as productivity and convenience affects the quality mostly and that the most appropriate measure for the service quality of ERP service is satisfaction. Also, for the system acceptance, the ease-of-use is the main factor. And, the service quality and system acceptance shows a strong correlation. This means that, in order to enhance the quality of ERP services, the service provider needs to provide customers with productivity-enhanced user-friendly IT services and active product support. The work of this research can help to improve the service quality and the user acceptance of ERP services and to lead further research works in this area.

IT security service provides customers with the capability of protecting the networked information asset and infrastructures, and the scope of security service is expanding from a technology-intensive task to a comprehensive protection system for IT environment. To improve the quality of this service, a research model which help assess the quality is required. Several research models have been proposed and used in various service areas, but few cases are found for IT security service. In this work, a research model for the IT security quality has been proposed, based on research models such as SERVQUAL and E-S-QUAL. With the proposed model, factors which affect the service quality and the best quality measure have been identified. And the feasibility of using quantitative measures for quality has been examined. For analysis, structural equation modeling and various statistical methods such as principal component analysis were used. The result shows that satisfaction is the most significant measure affected by the proposed quality factors. Two quality factors, fulfillment and empathy, are the main determinants of the service quality. This leads to a strategy of quality improvement based on factors of emotion and perception, not of technology. The quantitative measures are considered as promising alternative measures, when combined with other measures. In order to design reliable quantitative measures, more work should be done on target processing time and users’ expectation. It is hoped that work of this research will provide efficient tools and methods to improve the quality of IT security service and help future research works for other IT service areas.

The mobile SNS is a promising e-service platform of the future. However, measuring its service quality is a challenge. An appropriate model for measuring service quality is required. This paper proposes e-service quality models for analyzing mobile SNS platform quality, based on previous service quality researches. An empirical study is performed on the proposed models. The results show that constructs of existing e-service models such as responsiveness and assurance do not fit the mobile SNS platform, and that loyalty and value are better measures for mobile service quality.

For service innovation, it is crucial to measure the quality of service and identify the factors which affect it. In this study, for that purpose, a composite research model based on SERVQUAL and the technology acceptance model is proposed. The model is applied to three different service areas-Internet shopping, Internet banking, and cloud service. Analysis has been performed using the SEM methodology. The analysis shows that reliability, responsiveness and assurance affects the service quality in different ways for each, the result of which enables us to identify quality-determining factors in various service areas.

Assessing service quality and satisfaction is the essential part of service science. In this study, for G2B electronic commerce service composed of information systems and human resources, a composite research model for exploring factors of service quality satisfaction is proposed. The proposed model uses SERVQUAL’s five quality dimensions as independent antecedent factors and usefulness and ease-of-use of the technology acceptance model as mediating factors. A case of a G2B purchase service is empirically studied using the proposed model. The result shows that the proposed composite model is good and appropriate for explaining the characteristics of G2B services.

Fuzzy partition is a conceptual vehicle that encapsulates data into information granules. Fuzzy equalization concerns a process of building information granules that are semantically and experimentally meaningful. A few algorithms generating fuzzy partiti