소셜데이터 및 ARIMA 분석을 활용한 소비자 관점의 헬스케어 기술수요 예측 연구

• 영문명: A Study on the Demand Forecasting of Healthcare Technology from a Consumer Perspective : Using Social Data and ARIMA Model Approach
• 발행기관: 한국IT서비스학회
• 저자명: 양동원(Dong Won Yang) 이준기(Zoon Ky Lee)
• 간행물 정보: 『한국IT서비스학회지』한국IT서비스학회지 제19권 제4호, 49~61쪽, 전체 13쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2020.08.31

영문 초록

Prior studies on technology predictions attempted to predict the emergence and spread of emerging technologies through the analysis of correlations and changes between data using objective data such as patents and research papers. Most of the previous studies predicted future technologies only from the viewpoint of technology development. Therefore, this study intends to conduct technical forecasting from the perspective of the consumer by using keyword search frequency of search portals such as NAVER before and after the introduction of emerging technologies. In this study, we analyzed healthcare technologies into three types : measurement technology, platform technology, and remote service technology. And for the keyword analysis on the healthcare, we converted the classification of technology perspective into the keyword classification of consumer perspective. (Blood pressure and blood sugar, healthcare diagnosis, appointment and prescription, and remote diagnosis and prescription) Naver Trend is used to analyze keyword trends from a consumer perspective. We also used the ARIMA model as a technology prediction model. Analyzing the search frequency (Naver trend) over 44 months, the final ARIMA models that can predict three types of healthcare technology keyword trends were estimated as ARIMA (1,2,1) (1,0,0) , ARIMA (0,1,0) (1,0,0) , ARIMA (1,1,0) (0,0,0) . In addition, it was confirmed that the values predicted by the time series prediction model and the actual values for 44 months were moving in almost similar patterns in all intervals. Therefore, we can confirm that this time series prediction model for healthcare technology is very suitable.

목차

1. 서 론

2. 선행연구

3. 분석 방법

4. 분석 결과

5. 결 론

참고문헌

키워드

Emerging Technology Demand Forecast Technology Forecast Healthcare Naver Trend ARIMA Model Time Series Analysis Social Data Keyword Trend Analysis