• Title/Summary/Keyword: Logit Model

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VOT Derivation for Different Trip Purposes, Travel Modes and Testing of Their Significance (통행목적별 수단별 통행시간가치도출 및 유의성 검정)

  • Kim, Hyeon;Oh, Se-Chang;Choi, Gi-Ju
    • Journal of Korean Society of Transportation
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    • v.17 no.1
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    • pp.113-129
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    • 1999
  • It is widely recognized that the value of travel time (VOT) plays an important role both in choosing the transportation alternatives on an individual level, and in analyzing and evaluating transportation plans and other public policy makings on a collective level. There is, however, a great deal of difficulties to correctly estimate the VOT. In addition, although there are lots of methods to estimate the VOT so for, not many recommendations have been presented to reflect the localities associated with the VOT derivation in Korea. This study aims at deriving the VOT for different trip purposes and travel modes with their significances tested. To accomplish this purposes, a logit-based travel mode choice model based on revealed preference (RP) data has been formulated, calibrated using the discrete choice model of LIMDEP package for various trip purpose models. For each trip purpose and travel mode, the VOT has been calculated along with the significance testing of the derived VOTs. From the results given in this research, the VOTs for different purposes and modes are identified different, and they are statistically significant. The updated results here in this paper may be a yardstick in evaluating the transportation plans and policies by providing more detailed VOT information for different categories, especially in urban context.

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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.

A Study on the Measurement of Monetary Value for Service Quality of Construction Technology Information (건설기술정보 서비스 품질에 대한 금전적 가치 측정에 관한 연구)

  • Kim, Nam-Gon;Jeong, Seong-Yun
    • Journal of the Korean Society for Library and Information Science
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    • v.53 no.2
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    • pp.201-221
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    • 2019
  • The Korea Institute of Civil Engineering and Building Technology provides the documents and information on the construction technology through the Construction Technology Digital Library System to enhance the technological competitiveness of the construction engineers. The purpose of this study is to measure the monetary value of information service quality in order to improve the documents and information service quality provided by this system. For this purpose, a questionnaire model was designed to apply the DBDC- CVM. We surveyed the members of 300 this systems for the amount of information that they are willing to pay to maximize the quality of information service. The correlation between the dependent variable and the explanatory variables was analyzed with the basic statistics of the survey results. The independent variables affecting the dependent variable are statistically significant. The logit model is used to estimate the monetary value of individual respondents who are willing to pay for information service quality. In previous research, we measured the use value of information service. On the other hand, this study shows that the measurement of value based on information service quality is different from previous research.

Does the Obesity Paradox Exist in Cognitive Function?: Evidence from the Korean Longitudinal Study of Ageing, 2006-2016 (인지기능에 비만 역설은 존재하는가?: 고령화연구패널자료(2006-2016)를 이용하여)

  • Kang, Kyung Sik;Lee, Yongjae;Park, Sohee;Kimm, Heejin;Chung, Woojin
    • Health Policy and Management
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    • v.30 no.4
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    • pp.493-504
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    • 2020
  • Background: There have been many studies on the associations between body mass index (BMI) and cognitive function. However, no study has ever compared the associations across the methods of categorizing BMI. In this study, we aimed to fill the gap in the previous studies and examine whether the obesity paradox is valid in the risk of cognitive function. Methods: Of the 10,254 people aged 45 and older from the Korean Longitudinal Study of Ageing from 2006 to 2016, 8,970 people were finalized as the study population. The dependent variable was whether a person has a normal cognitive function or not, and the independent variables of interest were BMI categorized by the World Health Organization Western Pacific Regional Office (WHO-WPRO) method, the WHO method, and a 10-group method. Covariates included sociodemographic factors, health behavior factors, and health status factors. A generalized linear mixed model analysis with a logit link was used. Results: In the adjusted model with all covariates, first, in the case of BMI categories of the WHO-WPRO method, underweight (odds ratio [OR], 1.16; 95% confidence interval [CI], 1.15-1.17), overweight (OR, 1.36; 95% CI, 1.35-1.36), and obese (OR, 1.34; 95% CI, 1.33-1.34) groups were more likely to have a normal cognitive function than a normal-weight group. Next, in the case of BMI categories of the WHO method, compared to a normal-weight group, underweight (OR, 1.15; 95% CI, 1.14-1.16) and overweight (OR, 1.06; 95% CI, 1.06-1.07) groups were more likely to have a normal cognitive function; however, obese (OR, 0.62; 95% CI, 0.61-0.63) group was less likely to have it. Lastly, in the case of the 10-group method, as BMI increased, the likelihood to have a normal cognitive function changed like a wave, reaching a global top at group-7 (26.5 kg/㎡ ≤ BMI <28.0 kg/㎡). Conclusion: The associations between BMI and cognitive function differed according to how BMI was categorized among people aged 45 and older in Korea, which suggests that cognitive function may be positively associated with BMI in some categories of BMI but negatively in its other categories. Health policies to reduce cognitive impairment need to consider this association between BMI and cognitive function.

Estimation of Consumer Value on Import Management of Seafood Obtained from IUU Fishing: Using Choice Experiment Method

  • Ji-Eun An;Se-Hyun Park;Heon-Dong Lee
    • Journal of Korea Trade
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    • v.27 no.2
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    • pp.115-129
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    • 2023
  • Purpose - This study empirically analyzes the consumer value of risk management associated with illegal, unreported, and unregulated (IUU) fishing of fishery products imported to Korea. The global regulatory paradigm for IUU fishing has shifted from production-centered to market-centered. As a result, changes in the international fisheries trade environment emphasizing "transparency" and "legality" of the production process are accelerating. Therefore, changes in the management systems of fishery products entering the country are also needed. Accordingly, this study estimated the consumer value for risk management of IUU fishing, targeting major fish species imported to Korea, and derived the feasibility of introducing related policies. Design/methodology - This study used the choice experiment as an analysis model to estimate consumers' willingness to pay for the "possibility to check for IUU fishing." The choice experiment assumes that the value of a good or service is composed of separable attributes and that the sum of the part-worth of these individual attributes becomes the total value. In this study, respondents were presented with profiles comprising three attributes (country of origin, price, and possibility of checking IUU fishing) and the levels of frozen poulp squid, the subject of the analysis. The participants were asked to select their preferred profile. The marginal willingness to pay for each attribute was derived from the results of the respondents' choices using conditional logit model estimates. Findings - There is a marked difference in utility based on the preference of the country of origin of fishery products among consumers. In addition, the utility of fishery products that have undergone IUU fishing verification was observed to be higher, with the utility marked to be higher for lower prices. Originality/value - Estimating the policy value of the risk management in IUU fishing of imported fisheries products in this study is a novel attempt that has never been conducted before. Several studies have been conducted to assess the risk of IUU fishing associated with the import of fishery products internationally. However, such studies are yet to be conducted in Korea. Instead, policies and studies have focused on issues related to complying with trading partners' legal and transparent standards for exporting fishery products. This study should be the beginning of more in-depth empirical and theoretical explorations to establish order in the domestic seafood market and respond to changes in international regulations on IUU fishing.

Technology Competitiveness in the AI-Edutech Field: Using Patent Indice and Hurdle Negative Binomial Model (특허 자료를 활용한 AI-에듀테크 분야 국가 간 기술 경쟁력 분석: 특허 통계 지표와 허들 음이항 모델의 활용)

  • Ilyong Ji;Hyun-young Bae
    • Journal of Industrial Convergence
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    • v.22 no.8
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    • pp.1-17
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    • 2024
  • Recently, interest in edutech has been focused on its fusion with AI technology, and the market in this field is expanding. This study aims to analyze the technological competitiveness and key technological areas of major countries in the AI-edutech field. Additionally, considering that AI-edutech is a convergence of AI technology and edutech, the study seeks to examine the path dependence of AI-edutech in each country to determine whether they are based on existing AI technologies or edutech. To this end, AI-edutech patents were collected and competitiveness was analyzed using patent activity, patent impact, and market acquisition indicators. Path dependence for each country was analyzed using the hurdle negative binomial regression model. The analysis results indicate that the major countries in the AI-edutech field are China, South Korea, the United States, India, and Japan. In terms of patent activity, China had the highest level, followed by South Korea. In terms of patent impact and market securing power, the United States was high in both aspects, Japan had high market securing power, and South Korea had high patent influence. The results of the hurdle negative binomial analysis presented unique findings. The logit part results indicated that the possession of existing AI and edutech did not positively affect the emergence of current AI-edutech, but the count part results showed a positive influence. This suggests that, overall, it is difficult to assert that current AI-edutechs are based on past AI and edutechs. However, once some AI-edutechs based on existing AI and edutechs emerge, they are influenced by the existing technologies. These findings provide implications for future research and technological strategies in this field.

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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  • Analysis of Chinese Consumer Preference of Country of Origin for Apples based on National Organic Certification (사과의 국가별 유기인증 결합에 대한 중국 소비자 선호분석)

    • Kwon, Jae-Hyun;Kim, Jeong-Nyeon;Hong, Na-Kyoung;Kim, Tae-Kyun
      • Current Research on Agriculture and Life Sciences
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      • v.32 no.4
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      • pp.225-230
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      • 2014
    • This study investigates the effect of organic certification of apples on consumer preference in China as a way to support the expanded export of Korean apples to China. A choice experiment was designed to analyze the apple consumption in China. A total of 298 Chinese consumers answered the survey, and multinomial logit models were used to analyze the results. Organic certification was identified as an important determinant of consumer preference for apples in China, affecting both the evaluation and choice of country of origin. The results also indicated that Korean organic certification significantly increased the probability of Chinese consumers choosing Korean apples. Thus, organic certification by the Korean government should be strengthened to promote apple exports to China, plus the results of this study may provide useful information to promote agricultural product exports and improve the organic certification system.

    Analyzing the Economic Value and Planning Factors of Hubs within Urban Green Infrastructure - Focusing on the Case of Sejong Lake Park - (도시 그린인프라 핵심지역의 경제적 가치와 계획 요소 분석 - 세종호수공원 사례를 중심으로 -)

    • Lee, Dong-Kyu;An, Byung-Chul
      • Journal of the Korean Institute of Landscape Architecture
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      • v.49 no.4
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      • pp.41-54
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      • 2021
    • This study targets the urban park corresponding to the core areas (Hubs) of Green Infrastructure and estimates their value utilizing the Contingent Valuation Method (CVM) and determines the planning factors which affect them. The research aims to provide basic data for supporting the value improvement in the planning stage for urban parks representing green infrastructure. The primary purpose of this research is to derive variables that affect economic value and planning factors to improve the use-value of urban parks, one of the Hubs of the green infrastructure. In this study, Sejong Lake Park, located in Sejong City, is the target site. This study collected the responses of 105 people by conducting a survey on the intention to pay for the use-value and the planning factors that affect it, targeting visitors to Sejong Lake Park. The study conducts Contingent Valuation Method (CVM) on this survey responses. The results are as follows: first, as a result of analyzing the variables which affect willingness to pay for use-value, residence and age influence the willingness to pay significantly among socioeconomic characteristics. Next, the survey responses of Double-bounded dichotomous choices (DB-DC) CVM are converted into variables through statistic techniques. Furthermore, the variables are used for a Logit model to draw coefficients. The average willingness to pay per person for the use-value of Sejong Lake Park using the derived coefficients was approximately found to be 8,597 won. Therefore, as of 2019, Sejong Lake Park, with a total of 430,000 visitors, is estimated to have an annual economic value of 3.7 billion won. Third, the average Likert scale of the planning factor affecting the decision to pay for the economic value of Sejong Lake Park was the highest along the waterfront landscape, and the convenience facilities and waterfront landscape showed the highest willingness to pay, 10,000 won. In the range between 2,500 won and 5,000 won, the waterfront area ranks highest. Therefore, it can be said that visitors to Sejong Lake Park take account of the economic value of using the waterfront landscape the most. This study is meaningful as a thesis on use-value and the planning factors that affected value evaluation results of urban parks, and the analysis of the correlation between the planning factors of urban parks as hubs located in urban areas.

    Development of Sentiment Analysis Model for the hot topic detection of online stock forums (온라인 주식 포럼의 핫토픽 탐지를 위한 감성분석 모형의 개발)

    • Hong, Taeho;Lee, Taewon;Li, Jingjing
      • Journal of Intelligence and Information Systems
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      • v.22 no.1
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      • pp.187-204
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      • 2016
    • Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.


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