기업경기실사지수 예측에 대한 탐색적 연구

• 영문명: An Exploratory Study on the Prediction of Business Survey Index Using Data Mining
• 발행기관: 한국IT서비스학회
• 저자명: 박경보 김미량
• 간행물 정보: 『한국IT서비스학회지』제22권 제4호, 123~140쪽, 전체 18쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2023.08.31

영문 초록

In recent times, the global economy has been subject to increasing volatility, which has made it considerably more difficult to accurately predict economic indicators compared to previous periods. In response to this challenge, the present study conducts an exploratory investigation that aims to predict the Business Survey Index (BSI) by leveraging data mining techniques on both structured and unstructured data sources. For the structured data, we have collected information regarding foreign, domestic, and industrial conditions, while the unstructured data consists of content extracted from newspaper articles. By employing an extensive set of 44 distinct data mining techniques, our research strives to enhance the BSI prediction accuracy and provide valuable insights. The results of our analysis demonstrate that the highest predictive power was attained when using data exclusively from the t-1 period. Interestingly, this suggests that previous timeframes play a vital role in forecasting the BSI effectively. The findings of this study hold significant implications for economic decision-makers, as they will not only facilitate better-informed decisions but also serve as a robust foundation for predicting a wide range of other economic indicators. By improving the prediction of crucial economic metrics, this study ultimately aims to contribute to the overall efficacy of economic policy-making and decision processes.

목차

1. 서론

2. 이론적 배경

3. 연구 모형

4. 연구 결과

5. 결론

참고문헌

키워드

Business Survey Index Data mining Ensemble Prediction