• Journal of Families and Better Life
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• v.34 no.3
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• pp.15-26
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• 2016

Food is a kind of unconditional element for the health and survival of humanity. Eating is the most principle desire for humans among others, which can make humans feel stability and pleasure when the desire is well satisfied. The attention to food safety is increasing and food safety accidents are happening constantly, which makes the anxiety to food safety become more serious. Especially after the WTO, the floating of food hazards between countries are increasing, which makes the problems of food safety not just limited to inland but has become a matter of common interest internationally in this liberalization era. Therefore, institutional preparation and persistent management and supervision are necessary for increasing dietary life satisfaction as well as securing food safety. Meanwhile, the consumers also need to understand and trust the food safety information, and have the ability of personally pursuing a safe diet. In this study, sentiment index about food safety and dietary satisfaction were centered on Korean consumers and the factors having an effect on dietary satisfaction were analyzed. Moreover, whether the reliance to food safety information had a moderating effect on the sensory level of food safety and satisfaction to dietary food was also confirmed. The main results were different with those concluded by J. Yun and S. Joo (2014). The sensory level of food safety was decided by the reliance to food production distribution provision safety, anxiety to food varieties, and food token. The reliance to food production distribution provision safety was lower than the average level. The anxiety to food varieties was slightly higher than the average level. The reliance to food safety information was generally lower than the medium level which showed the distrust to food safety information. The satisfaction of diet by the consumers showed a slightly lower level than the average level. In addition, the reliance to food safety information had a moderating effect on the sentiment index about food safety and dietary satisfaction. Therefore, the consumer organizations or the government should actively expand various consumer education related to food safety in order to apprehend the concrete variables which can have effects on the satisfaction of diet and transform the precise information into accurate knowledge.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.682-691
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• 2016

The purpose of this study is to explore the causal and precedence relationships between the housing sub-market and the results of a consumer sentiment survey about the housing market. This study investigates the relationships between the survey results and an apartment deal price index by size and bidding price rate in apartment auctions by extending research related to consumer sentiment surveys. We surveyed the Seoul Metropolitan Area and analyzed the results using a unit root test, cointegration test, Granger causality test, and cross-correlation test. It was confirmed that causality exists between the survey results and apartment deal price index by size and bidding price rate, and it was also confirmed that there are correlation and precedence relationships between them.

• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.63-71
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• 2010

Business entrepreneurs reflect their views of domestic and foreign economic activities on their operation for the growth of their business. The decision, forecasting, and planning based on their economic sentiment affect business operation such as production, investment, and hiring and consequently affect condition of national economy. Business survey index(BSI) is compiled to get the information of business entrepreneurs' economic sentiment for the analysis of business condition. BSI has been used as an important variable in the short-term forecasting models for business cycle analysis, especially during the the period of extreme business fluctuations. Recent financial crisis has arised extreme business fluctuations similar to those caused by currency crisis at the end of 1997, and brought back the importance of BSI as a variable for the economic forecasting. In this paper, the meaning of BSI as an economic sentiment index is reviewed and a GUIDE regression tree is constructed to find out the factors which affect on BSI. The result shows that the variables related to the stability of financial market such as kospi index(Korea composite stock price index) and exchange rate as well as manufacturing operation ratio and consumer goods sales are main factors which affect business entrepreneurs' economic sentiment.

• Fashion & Textile Research Journal
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• v.22 no.1
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• pp.38-54
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• 2020

This study examines the time causal relationship between the operation profit of the listed fashion companies and the macro variables. Operating profit data of 36 listed fashion companies from 2000 to 2017 has been used. Macro variables include household income, household expenditure, number of Korean overseas travelers, number of foreigner travelers and sentiment index. The study results are as follows. First, the number of outbound travelers from Korea has a negative effect on the operating profit of listed fashion companies; however the number of foreigner visiting Korea has a positive effect at 0 time lag. Second, the consumer sentiment index had a positive effect on the sales and the operating profits of the listed fashion companies with a time difference between the 3rd and the 4th quarter. Third, a disposable income has a positive effect on the operating profit of listed fashion companies. Last, educational expenses have a negative effect on operating profit with a time lag between the first and the second quarter. The findings can be used as useful information to analyze the fashion industry and help fashion companies improve their financial performances.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2011.04a
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• pp.285-289
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• 2011

he purpose of this study is to assess the effects of real estate policy on apartment price index in Seoul. To meet the research goal, this research reviewed real estate policy of the government from January of 1986 to August of 2010, and then it collected monthly apartment price index in 25 local districts of Seoul from January of 2003 to August of 2010. After 25 districts were grouped into 2 areas (14 districts in Gangnam and 11 districts in Gangbuk), the data of two areas were analyzed by using the SAS program, Cluster analysis with Ward method showed 3 clusters on each area, and with 6 clusters in total, the effects of real estate policy in the period were examined by using residual analysis. The analysis indicated two major shocks (one was from May to October of 2003, and the other was from March of 2006 to January of 2007), and the results showed that the intervention of government in the market had the asymmetric effects in bullish and bearish times. It implies that the market volatility is substantially influenced by irrational sentiments. Thus, it's suggested to devise the consumer sentiment index suitable in real estate market.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.125-135
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• 2022

This study aims to explore variables using machine learning and provide analysis techniques suitable for predicting pharmacy sales whether government statistical indicators built to create an industrial ecosystem based on data, network, and artificial intelligence affect pharmacy sales. Therefore, this study explored predictive variables and performance through machine learning techniques such as Random Forest, XGBoost, LightGBM, and CatBoost using analysis data from January 2016 to December 2021 for 28 government statistical indicators and pharmacies in the retail sector. As a result of the analysis, economic sentiment index, economic accompanying index circulation change, and consumer sentiment index, which are economic indicators, were found to be important variables affecting pharmacy sales. As a result of examining the indicators MAE, MSE, and RMSE for regression performance, random forests showed the best performance than XGBoost, LightGBM, and CatBoost. Therefore, this study presented variables and optimal machine learning techniques that affect pharmacy sales based on machine learning results, and proposed several implications and follow-up studies.

• Journal of Information Technology Services
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• v.15 no.1
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• pp.197-210
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• 2016

With the advent of text analytics, VOC (Voice of Customer) data become an important resource which provides the managers and marketing practitioners with consumer's veiled opinion and requirements. In other words, making relevant use of VOC data potentially improves the customer responsiveness and satisfaction, each of which eventually improves business performance. However, unstructured data set such as customers' complaints in VOC data have seldom used in marketing practices such as predicting service time as an index of service quality. Because the VOC data which contains unstructured data is too complicated form. Also that needs convert unstructured data from structure data which difficult process. Hence, this study aims to propose a prediction model to improve the estimation accuracy of the level of customer satisfaction by combining unstructured from textmining with structured data features in VOC. Also the relationship between the unstructured, structured data and service processing time through the regression analysis. Text mining techniques, sentiment analysis, keyword extraction, classification algorithms, decision tree and multiple regression are considered and compared. For the experiment, we used actual VOC data in a company.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.27 no.4
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• pp.52-64
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• 2019

The purpose of this study is to analyze the impact of macroeconomic variables on air passenger demand and provide useful information to airport managers and policymakers. Therefore, using the quarterly macroeconomic indicators from 2002 to 2017, the relationship with air passenger demand was demonstrated by multiple regression analysis. In the previous studies, they used GDP, Korea Treasury Bond, KOSPI index, USD/KRW Exchange Rate, and WTI Crude Oil Price variables. In this study, we used the Coincident Composite Index, Employment Rate, Consumer Sentiment Index, and Private Consumption Rate used as additional variables. It has confirmed that if the consumption of research results expands or the economic environment is right, it will affect the increase in international passengers. In other words, it confirmed that the overall economic situation acts as the main factor determining air passenger demand. It confirmed that the economic environment at the past has a significant impact on air passenger demand.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.25-52
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• 2018

This study performs social network analysis based on consumer sentiment related to a location in Seoul using data reflecting consumers' web search activities and emotional evaluations associated with commerce. The study focuses on large commercial districts in Seoul. In addition, to consider their various aspects, social network indexes were combined with the trading area's public data to verify factors affecting the area's sales. According to R square's change, We can see that the model has a little high R square value even though it includes only the district's public data represented by static data. However, the present study confirmed that the R square of the model combined with the network index derived from the social network analysis was even improved much more. A regression analysis of the trading area's public data showed that the five factors of 'number of market district,' 'residential area per person,' 'satisfaction of residential environment,' 'rate of change of trade,' and 'survival rate over 3 years' among twenty two variables. The study confirmed a significant influence on the sales of the trading area. According to the results, 'residential area per person' has the highest standardized beta value. Therefore, 'residential area per person' has the strongest influence on commercial sales. In addition, 'residential area per person,' 'number of market district,' and 'survival rate over 3 years' were found to have positive effects on the sales of all trading area. Thus, as the number of market districts in the trading area increases, residential area per person increases, and as the survival rate over 3 years of each store in the trading area increases, sales increase. On the other hand, 'satisfaction of residential environment' and 'rate of change of trade' were found to have a negative effect on sales. In the case of 'satisfaction of residential environment,' sales increase when the satisfaction level is low. Therefore, as consumer dissatisfaction with the residential environment increases, sales increase. The 'rate of change of trade' shows that sales increase with the decreasing acceleration of transaction frequency. According to the social network analysis, of the 25 regional trading areas in Seoul, Yangcheon-gu has the highest degree of connection. In other words, it has common sentiments with many other trading areas. On the other hand, Nowon-gu and Jungrang-gu have the lowest degree of connection. In other words, they have relatively distinct sentiments from other trading areas. The social network indexes used in the combination model are 'density of ego network,' 'degree centrality,' 'closeness centrality,' 'betweenness centrality,' and 'eigenvector centrality.' The combined model analysis confirmed that the degree centrality and eigenvector centrality of the social network index have a significant influence on sales and the highest influence in the model. 'Degree centrality' has a negative effect on the sales of the districts. This implies that sales decrease when holding various sentiments of other trading area, which conflicts with general social myths. However, this result can be interpreted to mean that if a trading area has low 'degree centrality,' it delivers unique and special sentiments to consumers. The findings of this study can also be interpreted to mean that sales can be increased if the trading area increases consumer recognition by forming a unique sentiment and city atmosphere that distinguish it from other trading areas. On the other hand, 'eigenvector centrality' has the greatest effect on sales in the combined model. In addition, the results confirmed a positive effect on sales. This finding shows that sales increase when a trading area is connected to others with stronger centrality than when it has common sentiments with others. This study can be used as an empirical basis for establishing and implementing a city and trading area strategy plan considering consumers' desired sentiments. In addition, we expect to provide entrepreneurs and potential entrepreneurs entering the trading area with sentiments possessed by those in the trading area and directions into the trading area considering the district-sentiment structure.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.227-252
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• 2018

The evolution of instant communication has mirrored the development of the Internet and messenger applications are among the most representative manifestations of instant communication technologies. In messenger applications, senders use emoticons to supplement the emotions conveyed in the text of their messages. The fact that communication via messenger applications is not face-to-face makes it difficult for senders to communicate their emotions to message recipients. Emoticons have long been used as symbols that indicate the moods of speakers. However, at present, emoticon-use is evolving into a means of conveying the psychological states of consumers who want to express individual characteristics and personality quirks while communicating their emotions to others. The fact that companies like KakaoTalk, Line, Apple, etc. have begun conducting emoticon business and sales of related content are expected to gradually increase testifies to the significance of this phenomenon. Nevertheless, despite the development of emoticons themselves and the growth of the emoticon market, no suitable emoticon recommendation system has yet been developed. Even KakaoTalk, a messenger application that commands more than 90% of domestic market share in South Korea, just grouped in to popularity, most recent, or brief category. This means consumers face the inconvenience of constantly scrolling around to locate the emoticons they want. The creation of an emoticon recommendation system would improve consumer convenience and satisfaction and increase the sales revenue of companies the sell emoticons. To recommend appropriate emoticons, it is necessary to quantify the emotions that the consumer sees and emotions. Such quantification will enable us to analyze the characteristics and emotions felt by consumers who used similar emoticons, which, in turn, will facilitate our emoticon recommendations for consumers. One way to quantify emoticons use is metadata-ization. Metadata-ization is a means of structuring or organizing unstructured and semi-structured data to extract meaning. By structuring unstructured emoticon data through metadata-ization, we can easily classify emoticons based on the emotions consumers want to express. To determine emoticons' precise emotions, we had to consider sub-detail expressions-not only the seven common emotional adjectives but also the metaphorical expressions that appear only in South Korean proved by previous studies related to emotion focusing on the emoticon's characteristics. We therefore collected the sub-detail expressions of emotion based on the "Shape", "Color" and "Adumbration". Moreover, to design a highly accurate recommendation system, we considered both emotion-technical indexes and emoticon-emotional indexes. We then identified 14 features of emoticon-technical indexes and selected 36 emotional adjectives. The 36 emotional adjectives consisted of contrasting adjectives, which we reduced to 18, and we measured the 18 emotional adjectives using 40 emoticon sets randomly selected from the top-ranked emoticons in the KakaoTalk shop. We surveyed 277 consumers in their mid-twenties who had experience purchasing emoticons; we recruited them online and asked them to evaluate five different emoticon sets. After data acquisition, we conducted a factor analysis of emoticon-emotional factors. We extracted four factors that we named "Comic", Softness", "Modernity" and "Transparency". We analyzed both the relationship between indexes and consumer attitude and the relationship between emoticon-technical indexes and emoticon-emotional factors. Through this process, we confirmed that the emoticon-technical indexes did not directly affect consumer attitudes but had a mediating effect on consumer attitudes through emoticon-emotional factors. The results of the analysis revealed the mechanism consumers use to evaluate emoticons; the results also showed that consumers' emoticon-technical indexes affected emoticon-emotional factors and that the emoticon-emotional factors affected consumer satisfaction. We therefore designed the emoticon recommendation system using only four emoticon-emotional factors; we created a recommendation method to calculate the Euclidean distance from each factors' emotion. In an attempt to increase the accuracy of the emoticon recommendation system, we compared the emotional patterns of selected emoticons with the recommended emoticons. The emotional patterns corresponded in principle. We verified the emoticon recommendation system by testing prediction accuracy; the predictions were 81.02% accurate in the first result, 76.64% accurate in the second, and 81.63% accurate in the third. This study developed a methodology that can be used in various fields academically and practically. We expect that the novel emoticon recommendation system we designed will increase emoticon sales for companies who conduct business in this domain and make consumer experiences more convenient. In addition, this study served as an important first step in the development of an intelligent emoticon recommendation system. The emotional factors proposed in this study could be collected in an emotional library that could serve as an emotion index for evaluation when new emoticons are released. Moreover, by combining the accumulated emotional library with company sales data, sales information, and consumer data, companies could develop hybrid recommendation systems that would bolster convenience for consumers and serve as intellectual assets that companies could strategically deploy.