• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.14-24
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• 2020

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.

• Food Science and Industry
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• v.50 no.1
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• pp.57-66
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• 2017

Home meal replacements (HMR) are kinds of convenient foods as cooked or semi-cooked foods, which are produced outside of home, to eat directly or after simple cooking in substitution for traditional home meals. Recently the market size for HMR is expanding rapidly around the world due to the changes of global consumer trends, growth of single-person household, increase in economic participation of women, aging population, and so on. The Europe takes over 52.4% of the global market share for HMR in global HMR market, and North America, Asia-Pacific, and Africa-Middle East are following. The most popular HMR products in US and Europe are frozen foods, whereas the market share of chilled products in Asia including Japan, South Korea, and Vietnam are much higher than that in US and Europe. Currently, the trends in HMR is focus on the expansion of the list of products that replace for meals with simple cooking, but it is expected that nutrition-enforced HMR product for aged persons or patients who live alone are requested for the further growth of the HMR market.

• Korean Management Science Review
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• v.32 no.3
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• pp.91-103
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• 2015

This study recognizes that there is a correlation between the movement of the financial market and the sentimental changes of the public participating directly or indirectly in the market, and applies the relationship to investment strategies for stock market. The concerns that market participants have about the economy can be transformed to the search terms that internet users query on search engines, and search volume of a specific term over time can be understood as the economic trend of big data. Under the hypothesis that the time when the economic concerns start increasing precedes the decline in the stock market price and vice versa, this study proposes three investment strategies using casuality between price of domestic stock market and search volume from Naver trends, and verifies the hypothesis. The computational results illustrate the potential that combining extensive behavioral data sets offers for a better understanding of collective human behavior in domestic stock market.

• Journal of Korea Multimedia Society
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• v.19 no.7
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• pp.1107-1115
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• 2016

Efficient Market Hypothesis (EMH), states that at any point in time in a liquid market security prices fully reflect all available information. This paper presents a study of proving the hypothesis through daily Twitter sentiments using the hybrid approach of the lexicon-based approach and the naïve Bayes classifier. In this research we analyze the currency exchange rate movement of Indonesia Rupiah vs US dollar as a way of testing the Efficient Market Hypothesis. In order to find a correlation between the prediction sentiments from Twitter data and the actual currency exchange rate trends we collect Twitter data every day and compute the overall sentiment to label them as positive or negative. Experimental results have shown 69% correct prediction of sentiment analysis and 65.7% correlation with positive sentiments. This implies that EMH is semi-strong Efficient Market Hypothesis, and that public information provide by Twitter sentiment correlate with changes in the exchange market trends.

• The Journal of Fisheries Business Administration
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• v.25 no.1
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• pp.85-109
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• 1994

Recently, it has become a matter of importance concerning a distribution system of the fisheries products in our day, Especially, this paper disregards the fact of changes in demand and distribution system for fisheries products under the period of the high economic growth in Japan. The commercial capital of fisheries products has been modernized by the development of the public market place. The distribution system of fisheries products will rather play an important role than now. In this state, this study is to introduce the development of fish market theroy and attempts to explan the market trends in the production in Japan.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.151-151
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• 2009

In this presentation, CD BLU optical film market and technology trends are introduced at first. Then hghly precise, cost-advantaged MNTECH's specialized Soft Mold replication Technology and its optic films are contained.

• Electronics and Telecommunications Trends
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• v.38 no.6
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• pp.119-127
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• 2023

Market-oriented networks support various tasks in the market domain. We analyze trends in structural changes of such networks to adapt to preferences in general market movements. This analysis is different from conventional ones that focus on specific technologies. Instead, we focus on the paradigm shift of network technology from connectivity functionalities to platforms supporting business domains for direct modeling. Moreover, we analyze current development efforts of technologies based on popular and realistic solutions such as FIWARE, 5GinFIRE, IBN, IDN, and HNSP. Remarkably, we detail HNSP as an open research and development platform to experiment with business models and enable co-building with developers. We observe a clear paradigm shift of communications technology from a closed to an open job-shop style.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.15-22
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• 2021

This study aims to obtain a stock investment strategy model based on the industrial sector in Indonesia Stock Exchange (IDX). This study uses IDX data for the period of January 1996 to December 2016. This study uses the Markov Regime Switching Model to identify trends in market conditions that occur in industrial sectors on IDX. Furthermore, by using the Logit Regression Model, we can see the influence of economic factors in determining trends in market conditions sectorally and the probability of trends in market conditions. This probability can be the basis for determining stock investment decisions in certain sectors. The results showed descriptively that the stocks of the consumer goods industry sector had the highest average return and the lowest standard deviation. The trend in sectoral stock market conditions that occur in IDX can be divided into two conditions, namely bullish condition (high returns and low volatility) and bearish condition (low returns and high volatility). Differences in the conditions are mainly due to differences in volatility. The use of a Logit Regression Model to produce probability of market conditions and to estimate the influence of economic factors in determining stock market conditions produces models that have varying predictive abilities.

• Electronics and Telecommunications Trends
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• v.34 no.2
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• pp.51-59
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• 2019

Edge computing, which is computing on the edge of the network, is becoming a market value as a means of overcoming the fear of communication disconnection and delay reduction, which are the technical weaknesses of cloud computing. Edge computing is continuously expanding applications in various applications such as safety industry, smart factories, autonomous vehicles, mobile communications, and AR/VR. Looking at edge computing trends from Microsoft, IBM, HPE, and Dell EMC, current edge computing must be understood as an integral binding technology and not as a simple complement to the cloud. This paper examines market trends in edge computing and analyzes the impact of edge computing on major related industries.

• Journal of the Korean Society of Clothing and Textiles
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• v.20 no.1
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• pp.183-196
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• 1996

The purpose of this study was to analyze the influnce of Postmodernism on 90's fashion trends, and to present applications of it's inspiration to print design. 90's fashion trends represented in fashion magazines, in fashion trend reports, and in related books were anlyzed. Informations referring to two selected target markets were collected by phone interview. In 90's fashion trends, seven fashion images seemed to be influenced from Postmodernism emerged. Based on these seven fashion images, several print designs were created and developed for one domestic market and for one export market.