Google Trends is a useful tool not only for setting search periods, but also for providing search volume to specific countries, regions, and cities. Extant research showed that the big data from Google Trends could be used for an on-line market analysis of opinion sensitive products instead of an on-site survey. This study investigated the market share of tumor necrosis factor-alpha (TNF-α) inhibitor, which is in a great demand pharmaceutical product, based on big data analysis provided by Google Trends. In this case study, the consumer interest data from Google Trends were compared to the actual product sales of Top 3 TNF-α inhibitors (Enbrel, Remicade, and Humira). A correlation analysis and relative gap were analyzed by statistical analysis between sales-based market share and interest-based market share. Besides, in the country-specific analysis, three major countries (USA, Germany, and France) were selected for market share analysis for Top 3 TNF-α inhibitors. As a result, significant correlation and similarity were identified by data analysis. In the case of Remicade’s biosimilars, the consumer interest in two biosimilar products (Inflectra and Renflexis) increased after the FDA approval. The analytical data showed that Google Trends is a powerful tool for market share estimation for biosimilars. This study is the first investigation in market share analysis for pharmaceutical products using Google Trends big data, and it shows that global and regional market share analysis and estimation are applicable for the interest-sensitive products.

일반적으로 고속도로는 대용량의 교통량을 높은 수준의 안전성과 효율성을 가지고 고속으로 이동시키기 위해 건설되었다. 국내 경부고속도로와 남해고속도로는 부산항을 기 종점으로 하는 핵심고속도로로 컨테이너차량을 포함한 수출입화물트럭의 집중으로 교통문제가 종종 발생하고 있어서 교통문제 완화를 위해서는 교통특성연구의 필요성이 제기되고 있는 상황이다. 그리하여 본 연구에서는 경부고속도로와 남해고속도로의 8차로 기본구간을 대상으로 차로별 점유율과 평균밀도의 상관관계를 통해 고속도로의 밀도추정모형을 제시하고자 하였다.