Such effects would be paid off in the right way only when management of the firms perform marketing activities focusing on long term effectiveness, which would drive company profits up and keep them for long. Demands of customers are being changed and varied. In this result with the advantage of mass marketing and database marketing have been drawing attentions from company. To fulfill these demands of customer, they need a concept of eCRM(Web based Customer Relationship Management), and go from selling products and services, or gathering customer requests, up to the phase of solving customer's problem by real time or previous action. With the help of internet, the frequency and speed of the problem solving has improved greatly. For these purposes, we try to determine the most important and most urgent factors in eCRM: utilization by using SN Ratio Decision making, one of the Multi-criteria decision-making methods SN Ratio Decision making is widely used for determining relative magnitude per evaluation item, i. e. priority on problems and is expected to make more systematic and objective evaluations than conventional methods do. Even in the present situation where any general criterion on eCRM dose not exist, utilization of eCRM is expected to be actively continued, which will cause many problems. In this regard, evaluating eCRM counts.

Utilization rate for the restrictive gate and required time and walking distance to board are to be a measure for the gate management and passenger's convenience estimation. So, the main purpose of the gate management are maximization of utilization rate and increment of airport terminal user's convenience through the efficient gate management. This study intends to maximize the utilization rate on usable gates by concerning about layout, terminal configuration, local passenger of the airport and development of gate assignment algorithm and DSS which maximize the gate utilization and minimize the passenger's walking distance.

경영활동에 있어서 직관력은 잘 알려진 인지능력이지만 효과적인 의사결정지원시스템의 개발 목적으로는 거의 고려되고 있지 않다. 본 연구는 의사결정자의 인지 유형에 따른 시계열 예측의 정확성과 뇌파의 차이를 통계적 검증, 인공신경망, 데이터 마이닝의 세 가지 접근방법으로 탐색하여 그 결과를 비교 분석함으로써 시계열 직관 예측에 영향을 주는 의사결정자의 인지적/생리적 특성을 도출함으로써 효과적인 의사결정환경을 조성하는데 공헌하고자 하였다. 실험결과 통계적 분석에서는 아무런 유의성을 찾을 수 없었으나, 인공신경망 분석에서는 인지유형과 감성유형이 모두 시계열 예측 정확도와 상관성이 있는 것으로 나타났으며, 데이터 마이닝 분석에서는 보다 의미 있는 상관관계를 찾아낼 수 있었다.