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.