• Journal of the Korean association of regional geographers
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• v.16 no.5
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• pp.517-536
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• 2010

While periodic marketing systems have lasted for more than hundreds of years in Korea, the weekly (periodic) markets have emerged since the latter half of the 1990s in the densely populated urban areas. In Jinju, weekly markets are opened on eight densely populated area: Ehyeon Wellga Apt.(Monday market), Gumsan Apt.(Tuesday market), Juyak Hanbo Apt.(Wednesday market), Chojeon Apt.(Thursday market), Manggyeong Hanbo Apt.(Thursday market), Pyeonggeo Dulmalhanbo Apt.(Friday market), Gajoa Jugonggreenville Apt.(Saturday market), and Gaho Apt.(Saturday). The merchants of Jinju's weekly markets can be classified into three groups as follows: the migrating specialized(full-time) merchants, who sell fruits, fish, and other daily necessities: the farmer part-time women merchants in the sixties or in the seventies, who sell the agricultural products that they themselves have grown around the rural areas; and the vendor merchants, who sell mostly dduk-bok-ki, eo-mug(odeng), and other fast food. The origin and persistence of periodic markets are explained in terms of the concepts of central place theory, the economic/comparative advantage of periodic markets, and the traditional organization of time and inertia.

• Journal of the Korean association of regional geographers
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• v.2 no.2
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• pp.113-131
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• 1996

The purpose of this study is to identify the existence, personal characteristics and behavior of market-participants, and function of urban weekly markets in Taegu City through observation, interview and questionnaire survey. There are four weekly periodic markets such as Seongso(Monday), Chilgok(Wednesday), Siji(Thursday), and Chilgok(Friday) which have recently developed near the new apartment areas on the outskirts of Taegu. The major findings of this study can be summarized as follows: These markets originated from the agricultural cooperative's Friday markets, but were substantially established by mobile traders or merchants for the sake of their livelihood. Therefore, the existence of these markets is not explained by Stine's central place perspective but partially explained by Hay's economic locational and Bromley's socio-cultural perspective. Most traders are male, aged 30 to 40 years and have an educational level higher than high school. Most of them are living in Taegu and itinerantly visit more than two markets among the four markets by small truck. And most of them sell agricultural products and other food materials, except some who sell manufactured goods. Most consumers are housewives, aged 20 to 30 years and have an educational level higher than high school. Most of them are living within 1,000m and go there on foot. Most of them visit the markets around 3 to 5 p.m. on every market day. And they mostly buy vegetables, fruits, and fishes. Weekly markets provide employment opportunities for those who want to be merchants, and also contribute to the increase of farmers' income, because some traders(18.8%) are farmers who periodically visit markets to sell agricultural products. On the other hand, they function as a general food materials markets to neighboring residents. From these facts, both traders and consumers want weekly markets sustained. Therefore, these markets need to be protected by institutional assistance in spite of being informal markets.

• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.227-233
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• 2016

Google Trends provides weekly information on keyword search frequency on the Google search engine. Search volume patterns for the search keyword can also be analyzed based on category and by the location of those making the search. Also, Google provides “Hot searches” and “Top charts” including top and rising searches that include the search keyword. All this information is kept up to date, and allows trend comparisons by providing past weekly figures. In this study, we present a predictive model for TV markets using the searched data in Google search engine (Google Trend data). Using a predictive model for the market and analysis of the Google Trend data, we obtained an efficient and meaningful result for the TV market, and also determined highly ranked countries and cities. This method can provide very useful information for TV manufacturers and others.

• Journal of Information Technology Services
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• v.20 no.5
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• pp.177-187
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• 2021

The global economy has been very difficult due to the recent impact of COVID-19. Korea is also pushing for strong quarantine policies such as K- quarantine and social distancing, but the economy is hardly recovering. In particular, the economic situation began to change rapidly depending on the export and domestic market, the public's interest in the economy increased, and companies became more sensitive. In order to estimate this rapidly changing economic situation, major advanced countries have also developed models that can periodically monitor the economy at the government level. Through this, by periodically reporting the economic trends, the public and companies can be aware of the economic trends to some extent. This study analyzed the cases of weekly business trends in advanced countries and developed a model of weekly economic activity suitable for Korea. To verify this, indices closely related to the economy such as mobility, industrial activity, face-to-face consumption, and psychology were discovered and estimated. As a result of the study, the weekly economic activity index was judged to be very useful in capturing short-term real economic activity. In the future, in order to secure the robustness and stability of the index and to increase the reflection of reality, model improvement and parameter estimation should be performed regularly.

• Journal of the Korean Society of Food Culture
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• v.15 no.4
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• pp.259-268
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• 2000

The purpose of this study was to describe the levels of market goods substitution of housework and find out the determinants on it in the domain of food among married female home-based workers. The data were collected from 169 married female home-based workers in Pusan and Kyungnam province, by self-administered questionnaires. Frequencies, percentiles, Cronbach's alpha, Pearson's correlations, and multiple regression were used to analyze the data. In the convenience foods, frozen foods had the highest substitution level, whereas prepared stew had the lowest. The substitution level of Korean traditional storage foods was the middle. And in dining-out service, the substitution level was mostly high: the level of delivery service was higher than that of dining-out. Compared to the previous research, these results showed that market goods substitution tended to increase, and its level in the domain of food will promote continually over time. The variables affecting the substitution level of convenience food were the number of family members, occupation, the existence of elderly/disabled person in the family, sex-role attitude, and weekly hours at home-based work. The substitution level of Korean traditional storage foods was influenced by sex-role attitude, occupation, education, monthly household income, and the existence of elderly/disabled person in the family. The significant variables affecting the substitution level of dining-out service were weekly hours at home-based work, the number of family members, occupation, monthly household income, education, and sex-role attitude.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.194-210
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• 2022

The user-centered EV charging infrastructure construction policy the government is aiming for can increase convenience for electric vehicle users and bring new electric vehicle users into the market. This study was conducted to provide an in-depth understanding of the charging behaviors of actual electric vehicle users, which can be used as basic information for the electric vehicle charging infrastructure. Based on charging diary data collected for a week, the charging of electric vehicles was analyzed on a daily and weekly basis, and sequence analysis and latent class analysis were used. As a result, five daily charging profiles and four weekly charging profiles were identified, which are expected to contribute to revitalizing the electric vehicle market by providing key information for decision-making by potential electric vehicle users as well for establishing user-centered charging infrastructure policies in the future.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.463-474
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• 2020

This study aims to investigate the impact of COVID-19 pandemic on the stock markets of sixteen countries. Pooled OLS regression, conventional t-test and Mann-Whitney test are used to estimate the results of the study. We construct a weekly panel data of COVID-19 new cases and stock returns. Pooled OLS estimation result shows that the growth rate of weekly new cases of COVID-19 negatively predicts the return in stock market. Next, the returns on leading stock indices of these countries during the COVID-19 outbreak period are compared with returns during the non-COVID period. We use a t-test and Mann-Whitney test to compare the returns. The results reveal that investors in these countries do not react to the media news of COVID-19 at the early stage of the pandemic. However, once the human-to-human transmissibility had been confirmed, all of the stock market indices negatively reacted to the news in the short- and long-event window. Interestingly, we noticed that the Shanghai Composite Index, which was severely affected during the short-event window, bounced back during the long-event window. This indicates that the Chinese government's drastic measures to contain the spread of the pandemic regained the confidence of investors in the Shanghai Stock Market.

• The Journal of Asian Finance, Economics and Business
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• v.1 no.2
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• pp.31-37
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• 2014

The portfolio selection is one of the most important and vital decisions that a real or legal person, who invests in stock market, should make. The main purpose of this article is the determination of the optimal portfolio with regard to relations among stock returns of companies which are active in Tehran's stock market. For achieving this goal, weekly statistics of company's stocks since Farvardin 1389 until Esfand 1390, has been used. For analyzing statistics and information and examination of stocks of companies which has change in returns, factors analysis approach and clustering analysis has been used (FC approach). With using multivariate analysis and with the aim of reducing the unsystematic risk, a financial portfoliois formed. At last but not least, results of choosing the optimal portfolio rather than randomly choosing a portfolio are given.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.4
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• pp.1-12
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• 2008

The study suggests an answer to the question of what determines category diversification of Internet portals in Korea. First, as external factors, competition intensity and market growth are hypothesized to have influence on the degree of category diversification. Second, an internal factor, user loyalty to portals, is hypothesized to influence negatively category diversification. The study performed empirical analysis based on weekly portal-specific panel data of eighteen internet portals in Korea during the period between 2001 and 2004. The result shows that category diversification increases as competition intensity increases, and that category diversification decreases as user loyalty increases. There was no effect of market-level growth rate on category diversification.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.67-83
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• 2018

The Korean film industry with significant increase every year exceeded the number of cumulative audiences of 200 million people in 2013 finally. However, starting from 2015 the Korean film industry entered a period of low growth and experienced a negative growth after all in 2016. To overcome such difficulty, stakeholders like production company, distribution company, multiplex have attempted to maximize the market returns using strategies of predicting change of market and of responding to such market change immediately. Since a film is classified as one of experiential products, it is not easy to predict a box office record and the initial number of audiences before the film is released. And also, the number of audiences fluctuates with a variety of factors after the film is released. So, the production company and distribution company try to be guaranteed the number of screens at the opining time of a newly released by multiplex chains. However, the multiplex chains tend to open the screening schedule during only a week and then determine the number of screening of the forthcoming week based on the box office record and the evaluation of audiences. Many previous researches have conducted to deal with the prediction of box office records of films. In the early stage, the researches attempted to identify factors affecting the box office record. And nowadays, many studies have tried to apply various analytic techniques to the factors identified previously in order to improve the accuracy of prediction and to explain the effect of each factor instead of identifying new factors affecting the box office record. However, most of previous researches have limitations in that they used the total number of audiences from the opening to the end as a target variable, and this makes it difficult to predict and respond to the demand of market which changes dynamically. Therefore, the purpose of this study is to predict the weekly number of audiences of a newly released film so that the stakeholder can flexibly and elastically respond to the change of the number of audiences in the film. To that end, we considered the factors used in the previous studies affecting box office and developed new factors not used in previous studies such as the order of opening of movies, dynamics of sales. Along with the comprehensive factors, we used the machine learning method such as Random Forest, Multi Layer Perception, Support Vector Machine, and Naive Bays, to predict the number of cumulative visitors from the first week after a film release to the third week. At the point of the first and the second week, we predicted the cumulative number of visitors of the forthcoming week for a released film. And at the point of the third week, we predict the total number of visitors of the film. In addition, we predicted the total number of cumulative visitors also at the point of the both first week and second week using the same factors. As a result, we found the accuracy of predicting the number of visitors at the forthcoming week was higher than that of predicting the total number of them in all of three weeks, and also the accuracy of the Random Forest was the highest among the machine learning methods we used. This study has implications in that this study 1) considered various factors comprehensively which affect the box office record and merely addressed by other previous researches such as the weekly rating of audiences after release, the weekly rank of the film after release, and the weekly sales share after release, and 2) tried to predict and respond to the demand of market which changes dynamically by suggesting models which predicts the weekly number of audiences of newly released films so that the stakeholders can flexibly and elastically respond to the change of the number of audiences in the film.