• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.3
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• pp.1-11
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• 2019

The purpose of this study is to propose a sustainable village-unit urban regeneration plan for the Ewha Mural Village, where mural artists recovered concrete fences to be followed by some residents damaging the mural paintings. Through a review of the existing literature and a preliminary survey, we derived the urban regeneration factors (environmental sustainability, economic sustainability, and social sustainability) applicable at the village level. After an empirical survey on the residents, we tried to identify various problems of the Ewha Mural Village. Residents selected the factors of accessibility, parking management, diversity of industries, creation of new jobs, community participation of residents for the mural village's activation, and stable living spaces. In the case of Ewha Mural Village, physical environment factors for the residents at the time of construction were not considered and the village was mainly planned using budget-based murals. Since then, the inequality of economic benefits intensified the conflicts among the residents. In addition, public benefits, such as establishing new industries and employing outsiders, were not provided, and these facts appear to have led to an unsustainable murals village, in which the murals that are the protagonists of the village revitalization are being destroyed. Therefore, the urban regeneration of Ewha Mural Village should be designed considering a region where some residential areas can be transformed into tourist areas. In addition, it is essential to employ a win-win method to improve the living environment, such as road maintenance, not only partial economic benefits, such as increased land-value, and to increase resident's value as a common asset within the village itself.

• 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.