• Title/Summary/Keyword: logit 모델

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The Evaluation of the Purchase Social Housing on the Characteristics of Location and Housing in Busan (부산지역 매입임대주택의 입지 및 주택 내·외부 특성에 따른 주거평가 분석)

  • Choi, Yeol;Park, Sung Ho;Ha, Kyu-Yang
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.4
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    • pp.1307-1315
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    • 2014

  • This study aims to analysis of determinants of the residents satisfaction of purchased rental housing and currently being implemented policy of supporting low-income families are empirically evaluated through the residential evaluation of purchased rental housing residents. Purchased rental housing users are possible to live in currently residing community consistently, have advantages for fewer problems of the phenomenon of social isolation, exclusion and preventing slumism of low-income families, are expected to increase in the future. First of all, the characteristics of residential environment, housing expenses and a head of household were examined for the residential environment evaluation of the residents of purchased rental housing, on the basis of this, the characteristics of internal and external house and residential location are examined each for the determinants of the residential environment satisfaction of purchased rental housing. The variables that affect residential satisfaction according to residential location are public facilities, educational facilities and welfare facilities respectively. In particular, the higher the satisfaction of access to welfare facilities, the higher the satisfaction of residential location of purchased rental housing was analyzed. The variables affecting the residential satisfaction according to the internal and external characteristics of house are significant in window status, cracking, heating facilities, housing scale and management.

  • https://doi.org/10.12652/Ksce.2014.34.4.1307 인용 PDF KSCI

An Analysis on the Determinants of Mountainous and Coastal Area's Housing Value Caused by the Characteristics of the Natural Environment (자연환경 특성에 따른 산지형 및 해안형 아파트의 주거가치 상승 결정요인 비교 분석)

  • Choi, Yeol;Kim, Hyeong Jun;Kim, Su Jin
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.33 no.2
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    • pp.811-819
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    • 2013

  • This study aims to analyze determinants of mountainous and coastal area's housing value caused by the characteristics of the natural environment. As the current issue of housing value is throwing the spotlight on the climate change recently, environmental features are significantly important than before. There were a lot of studies on the influence of environmental characteristics to the housing price but these studies were mostly dealing with the housing price in especially apartments nearby Han-river in Seoul, South Korea. To have differences with existing studies, environmental characteristics estimating housing value are classified as 8 elements including the view, the wind speed, and the humidity. The result of this study is in following; there were few significant environmental variables in mountainous housing value growth model. This means people living in mountainous area recognize on environmental factors more such as housing or complex characteristics. People living in coastal area are much more sensitive environment variables in their residence value than mountainous area. Especially, the view for the ocean is the most important variable in housing value, and wind speed is second positively significant. Humidity and safety of disaster are negatively significant variables.

  • https://doi.org/10.12652/Ksce.2013.33.2.811 인용 PDF KSCI

Measuring the Non-market Value of the Introduction of Electric Vehicles to National Parks Against Climate Change (기후변화의 대응수단으로서 국립공원 내 전기자동차 도입의 비시장적 가치 추정에 관한 탐색적 연구)

  • Kim, Sang-Tae;Min, Woong-Ki;Kim, Nam-Jo
    • Review of Culture and Economy
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    • v.17 no.2
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    • pp.81-102
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    • 2014

  • As carbon dioxide, the main greenhouse gas, is generally emitted by vehicles, the development and distribution of electric cars is important for the sustainability of environmentally-friendly tourism, especially in national parks. National parks in Korea, however, still see the use of traditional vehicles powered by internal combustion engines in the handling of visitors and the transportation of goods and staff. Such engines being the cause of environmental problems such as exhaust emission and noise pollution, the introduction of electric cars in national parks is needed. This study aims to analyze the economic value of electric cars in national parks as well as contribute to the development of the Green Transportation model in tourism destinations. The study used a logit model to estimate the willingness to pay for the introduction of electric cars in national parks. Adults over the age of twenty, with gender and age apportioned equally, were surveyed using questionnaires that included dichotomous as well as demographic questions. The findings show that the amount an individual is willing to pay for the purpose of environmental conservation is 3,948 won, while the value the national parks would derive from the use of electric cars is 56,138,130,000 won. The introduction of electric cars in national parks is expected to offer both direct and indirect benefits while helping to improving the environment of the national parks by eliminating exhaust emission and noise. This introduction would also be a response to climate change that can be taken by society as a whole.

Social Risks of Self-Employed Women in Korea and the Legacy of East Asian Welfare Model Policy Logic (한국 여성 자영업자의 사회적 위험과 동아시아복지국가 정책 논리의 유산)

  • Ahn, Jong-soon
    • 한국사회정책
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    • v.24 no.4
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    • pp.63-87
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    • 2017

  • Self-employed women are highly vulnerable to social risks like unemployment and poverty as job instability has increased in recent decades. Despite this, the Korean public policy focus has been on employees, not the self-employed. This may be closely linked to the legacy of the East Asian welfare model policy logic. Therefore, this study explores social risk levels by gender and employment status and examines the relation between social risks of self-employed women and the East Asian welfare model policy logic, through comparing-means analysis and ordered logit regression analysis using the 9th wave data of the Korea Welfare Panel Study Korea. The study yields evidence of divisions in social risk levels according to gender and employment status: that is, a gender difference, and a substantial gap between self-employed workers and regular employees. Furthermore, the findings of the study indicate that self-employed women — especially in small businesses — are more vulnerable to social risks than are self-employed men. This strongly supports the conclusion that the higher social risks of self-employed women in Korea are closely linked to the legacy of East Asian welfare model policy logic, which focuses on social protection for core workers and largely neglects women.

Examining the Formation of Entrepreneurial Activities through Cognitive Approach (기업가적 활동 형성에 미치는 영향요인: 인지론적 접근)

  • Lee, Chaewon
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.12 no.3
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    • pp.65-74
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    • 2017

  • There have been questions how entrepreneurs think, act and why individuals become entrepreneurs. The trait-based explanation of entrepreneurial activities has been main stream. However, the trait-based theory has been criticized because it assumes that entrepreneurial traits are inherited, stable and enduring over time. This research accepts the cognitive theory to see how entrepreneurs learn or accept others' values, how entrepreneurial perceptions of opportunity impact entrepreneurial actions and how individuals acquire the social legitimation of the formation of entrepreneurial activities. In order to capture the attitudes, activities and motivations of people who are involved in entrepreneurial activities, the author uses the GEM Korea 2016 data. The data from the Global Entrepreneurship Monitor(GEM) has been well known for the data to capture individuals early-stage entrepreneurial activities. This paper used the sample from the APS(Adult Population Survey) of the GEM which was completed by a representative sample of two thousand adults in Korea by the qualified survey vendor, with strict procedures and oversight by the GEM central data team. The hypotheses are tested with logit regression analysis to estimate the probability of the influence of perceptual variables such as individual perception in social learning, the opportunity recognition in the environment, and social legitimation in the entrepreneurial activities. Based on the results, individuals tend to have high entrepreneurial activities if individuals have high self-efficacy. Also, the existence of role models around the entrepreneurs encourages the individuals involve in entrepreneurial activities more however the perception of opportunity in the environment is not strongly associated with entrepreneurial activities. The media exposure of successful entrepreneurs is more important than others' perception of entrepreneurs on the desirable career option or respect from communities. This paper can contribute to the cognitive processes, particular perception about oneself, as well as perception which is impacted by a community or a society.

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Determinants of Consumer Responses to Retail Out-of-Stocks (점포내 품절상황에서 소비자 반응행동유형별 결정요인)

  • Chun, Dal-Young;Choi, Jong-Rae;Joo, Young-Jin
    • Journal of Distribution Research
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    • v.16 no.4
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    • pp.29-64
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    • 2011

  • Overview of Research: Product availability is one of important competences of store to fulfill consumer needs. If stock-outs which means a product what consumer wants to buy is not available occurs, consumer will face decision-making uncertainty that leads to consumer's negative responses such as consumer dissatisfaction on store. Stockouts was much studied in the field of academia as well as practice in other countries. However, stock-outs has not been researched at all in Marketing and/or Distribution area in Korea. The main objectives of this study are to find out determinants of consumer responses such as Substitute, Delay, and Leave(SDL) when consumer encounters out-of-stock situation and then to examine the effects of these factors on consumer responses. Specifically, this study focuses on situational characteristics(e.g., purchase urgency and surprise), store characteristics (e.g., product assortment and store convenience), and consumer characteristics (e.g., brand loyalty and store loyalty). Then, this study empirically investigates relationships these factors with consumers behaviors such as product substitution, purchase delay, and store switching.

    shows the research model of this study. To accomplish above-mentioned research objectives, the following ten hypotheses were proposed and verified : ${\bullet}$ H 1 : When out-of-stock situation occurs, purchase urgency will increase product substitution but will decrease purchase delay and store switching among consumer responses. ${\bullet}$ H 2 When out-of-stock situation occurs, surprise will decrease product substitution and purchase delay but will Increase store switching among consumer responses. ${\bullet}$ H 3 : When out-of-stock situation occurs, purchase quantities will increase product substitution and store switching but will decrease purchase delay among consumer responses. ${\bullet}$ H 4 : When out-of-stock situation occurs, pre-purchase plan will decrease product substitution but will increase purchase delay and store switching among consumer responses. ${\bullet}$ H 5 : When out-of-stock situation occurs, product assortment will increase product substitution but will decrease purchase delay and store switching among consumer responses. ${\bullet}$ H 6 : When out-of-stock situation occurs, competitive store price image will increase product substitution and purchase delay but will decrease store switching among consumer responses. ${\bullet}$ H 7 : When out-of-stock situation occurs, store convenience will increase product substitution but will decrease purchase delay and store switching among consumer responses. ${\bullet}$ H 8 : When out-of-stock situation occurs, salesperson services will increase product substitution but will decrease purchase delay and store switching among consumer responses. ${\bullet}$ H 9 : When out-of-stock situation occurs, brand loyalty will decrease product substitution but will increase purchase delay and store switching among consumer responses. ${\bullet}$ H 10 When out-of-stock situation occurs, store loyalty will increase product substitution and purchase delay but will decrease store switching among consumer responses. Analysis: Data were collected from 353 respondents who experienced out-of-stock situations in various store types such as large discount stores, supermarkets, etc. Research model and hypotheses were verified using multinomial logit(MNL) analysis. Results and Implications: is the estimation results of l\1NL model, and
    shows the marginal effects for each determinant to consumer's responses(SDL). Significant statistical results were as follows. Purchase urgency, purchase quantities, pre-purchase plan, product assortment, store price image, brand loyalty, and store loyalty were turned out to be significant determinants to influence consumer alternative behaviors in case of out-of-stock situation. Specifically, first, product substitution behavior was triggered by purchase urgency, surprise, purchase quantities, pre-purchase plan, product assortment, store price image, brand loyalty, and store loyalty. Second, purchase delay behavior was led by purchase urgency, purchase quantities, and brand loyalty. Third, store switching behavior was influenced by purchase urgency, purchase quantities, pre-purchase plan, product assortment, store price image, brand loyalty, and store loyalty. Finally, when out-of-stock situation occurs, store convenience and salesperson service did not have significant effects on consumer alternative responses.

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    • A Time Series Graph based Convolutional Neural Network Model for Effective Input Variable Pattern Learning : Application to the Prediction of Stock Market (효과적인 입력변수 패턴 학습을 위한 시계열 그래프 기반 합성곱 신경망 모형: 주식시장 예측에의 응용)

    • Lee, Mo-Se;Ahn, Hyunchul
      • Journal of Intelligence and Information Systems
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      • v.24 no.1
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      • pp.167-181
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      • 2018

    • Over the past decade, deep learning has been in spotlight among various machine learning algorithms. In particular, CNN(Convolutional Neural Network), which is known as the effective solution for recognizing and classifying images or voices, has been popularly applied to classification and prediction problems. In this study, we investigate the way to apply CNN in business problem solving. Specifically, this study propose to apply CNN to stock market prediction, one of the most challenging tasks in the machine learning research. As mentioned, CNN has strength in interpreting images. Thus, the model proposed in this study adopts CNN as the binary classifier that predicts stock market direction (upward or downward) by using time series graphs as its inputs. That is, our proposal is to build a machine learning algorithm that mimics an experts called 'technical analysts' who examine the graph of past price movement, and predict future financial price movements. Our proposed model named 'CNN-FG(Convolutional Neural Network using Fluctuation Graph)' consists of five steps. In the first step, it divides the dataset into the intervals of 5 days. And then, it creates time series graphs for the divided dataset in step 2. The size of the image in which the graph is drawn is $40(pixels){\times}40(pixels)$, and the graph of each independent variable was drawn using different colors. In step 3, the model converts the images into the matrices. Each image is converted into the combination of three matrices in order to express the value of the color using R(red), G(green), and B(blue) scale. In the next step, it splits the dataset of the graph images into training and validation datasets. We used 80% of the total dataset as the training dataset, and the remaining 20% as the validation dataset. And then, CNN classifiers are trained using the images of training dataset in the final step. Regarding the parameters of CNN-FG, we adopted two convolution filters ($5{\times}5{\times}6$ and $5{\times}5{\times}9$) in the convolution layer. In the pooling layer, $2{\times}2$ max pooling filter was used. The numbers of the nodes in two hidden layers were set to, respectively, 900 and 32, and the number of the nodes in the output layer was set to 2(one is for the prediction of upward trend, and the other one is for downward trend). Activation functions for the convolution layer and the hidden layer were set to ReLU(Rectified Linear Unit), and one for the output layer set to Softmax function. To validate our model - CNN-FG, we applied it to the prediction of KOSPI200 for 2,026 days in eight years (from 2009 to 2016). To match the proportions of the two groups in the independent variable (i.e. tomorrow's stock market movement), we selected 1,950 samples by applying random sampling. Finally, we built the training dataset using 80% of the total dataset (1,560 samples), and the validation dataset using 20% (390 samples). The dependent variables of the experimental dataset included twelve technical indicators popularly been used in the previous studies. They include Stochastic %K, Stochastic %D, Momentum, ROC(rate of change), LW %R(Larry William's %R), A/D oscillator(accumulation/distribution oscillator), OSCP(price oscillator), CCI(commodity channel index), and so on. To confirm the superiority of CNN-FG, we compared its prediction accuracy with the ones of other classification models. Experimental results showed that CNN-FG outperforms LOGIT(logistic regression), ANN(artificial neural network), and SVM(support vector machine) with the statistical significance. These empirical results imply that converting time series business data into graphs and building CNN-based classification models using these graphs can be effective from the perspective of prediction accuracy. Thus, this paper sheds a light on how to apply deep learning techniques to the domain of business problem solving.

    • https://doi.org/10.13088/jiis.2018.24.1.167 인용 PDF KSCI