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Validation of the Korean Version of the Trauma Symptom Checklist-40 among Psychiatric Outpatients (정신건강의학과 외래환자 대상 한국판 외상 증상 체크리스트(Trauma Symptom Checklist-40)의 타당도 연구)

  • Park, Jin;Kim, Daeho;Kim, Eunkyung;Kim, Seokhyun;Yun, Mirim
    • Korean Journal of Psychosomatic Medicine
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    • v.26 no.1
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    • pp.35-43
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    • 2018
  • Objectives : Effects of multiple trauma are complex and extend beyond core PTSD symptoms. However, few psychological instruments for trauma assessment address this issue of symptom complexity. The Trauma Symptom Checklist-40 (TSC-40) is a self-report scale that assesses wide range of symptoms associated with childhood or adult traumatic experience. The purpose of the present study was to evaluate the validity of the Korean Version of the TSC-40 in a sample of psychiatric outpatients. Methods : Data of 367 treatment-seeking patients with DSM-IV diagnoses were obtained from an outpatient department of psychiatric unit at a university hospital. The diagnoses were anxiety disorder, posttraumatic stress disorder, depressive disorder, adjustment disorder and others. Included in the psychometric data were the TSC-40, the Life events checklist, the Impact of Event Scale-Revised, the Zung's Self-report Depression Scale, and the Zung's Self-report Anxiety Scale. Cronbach's ${\alpha}$ for internal consistency were calculated. Convergent and concurrent validity was approached with correlation between the TSC-40 and other scales (PTSD, anxiety and depression). Results : Exploratory factor analysis of the Korean Version of TSC-40 extracted seven-factor structure accounted for 59.55% of total variance that was contextually similar to a six-factor structure and five-factor structure of the original English version. The Korean Version of TSC-40 demonstrated a high level of internal consistency. (Cronbach's ${\alpha}=0.94$) and good concurrent and convergent validity with another PTSD scale and anxiety and depression scales. Conclusions : Excellent construct validity of The Korean Version of TSC-40 was proved in this study. And subtle difference in the factor structure may reflect the cultural issues and the sample characteristics such as heterogeneous clinical population (including non-trauma related disorders) and outpatient status. Overall, this study demonstrated that the Korean version of TSC-40 is psychometrically sound and can be used for Korean clinical population.

An Exploratory Study on Fashion Retail Borrowing in Korea (대우한국시상령수차대적연구(对于韩国时尚零售借贷的研究))

  • Lee, Mi-Young;Kim, K.P. Johnson
    • Journal of Global Scholars of Marketing Science
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    • v.20 no.1
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    • pp.70-79
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    • 2010
  • There has been some research conducted that addressed immoral consumer behaviors in Korea; however, most of this research focused on purchasing counterfeits or shoplifting. High return rates of apparel and used apparel returns have been acknowledged as problem areas within the fashion industry. However, very few researchers have addressed this issue. Therefore, the goal of this research was to explore consumer's retail borrowing experience using a mixed methods approach. In study 1 Korean consumer's retail borrowing experiences was explored through focus group interviews. Findings informed study 2 an examination of apparel consumers' attitudes toward retail borrowing behavior via an online survey. Findings assist both researchers' and practitioners' understanding of retail borrowing behaviors and provide insight into retail borrowing issues in the apparel retail industry. For study 1, five focus-group interviews were conducted with seven panels of individuals that had retail borrowing experience within the past year. Thirty-five Korean consumers who lived in a metropolitan area participated in the focus group interviews. Most of consumers were in their 20's (n=21) and were women (n=24). Most participants purchased apparel items from a retail store and returned the worn items for either a full refund or exchanged the worn item for another item. Motives underlying retail borrowing behavior included social needs, job-related needs, fashion needs, and "smart shopping." Similar to existing research findings from other countries, social needs were the most frequently mentioned cause of retail borrowing in fashion stores. Consumers' moral values, attitude toward large corporations, and prior retail borrowing experience were mentioned as possible factors affecting consumers' retail borrowing behavior. For study 2, the questionnaire used to gather the data was developed based on the findings of part I and existing research. Questions concerning consumers' moral beliefs, sensation seeking tendencies, self-worth, past retail job experience, retail borrowing experience, and some demographic characteristics were included in the questionnaire. The data were collected via an online survey using an online panel provided by a commercial online research company located in Seoul, Korea. In order to obtain various consumers, a quota sample was (male: female=1:1, 20's:30's:40's=1:1:1, retail experience: no retail experience=1:3) obtained from the company. A total of 401 consumers who had shopped for apparel items during the prior 6 months participated in the online survey. The results indicated that 19.7% of the respondents reported they had experience borrowing fashion merchandise. Among these individuals, male borrowers (57%) outnumbered female borrowers. In terms of age distribution, x2 revealed that there was a statistical difference between respondents with and without retail borrowing experiences: 41.8% of the respondents with retail borrowing experience were in their 40's, while respondents without retail borrowing experience were evenly distributed between their 20's to 40's. There was also a significant difference between respondents with and without retail borrowing experience in terms of income: respondents with retail borrowing experience tended to have higher incomes than those without retail borrowing experience. T-tests were performed to compare respondents' fashion shopping behavior, moral beliefs, sensation-seeking tendencies, and attitudes toward retail borrowing behavior between participants with and without retail borrowing experience. As compared to those with no borrowing experience, respondents with experience tended to shop for fashion items more frequently and spent more on shopping for fashion items. Consumers with experience borrowing tended to have higher sensation-seeking tendencies than consumers without retail borrowing experience. A regression analysis revealed that attitudes toward fashion retail borrowing were negatively related to consumers' moral beliefs, but positively related to monthly fashion shopping frequency, sensation-seeking tendencies, and past fashion retail borrowing experience. Among these variables, past retail borrowing experience was the most significant predictor, followed by moral beliefs. This research serves as an initial attempt to address the motives that underlie retail borrowing behaviors and the factors affecting those behaviors. The findings of this study may facilitate an understanding of the consumer's retail borrowing, which will provide a basis for approaches that may help decrease retail borrowing and inappropriate returns at fashion retail stores. The findings may also provide materials for consumer education over the long term. In order to better understand fashion retail borrowing behavior, more research is needed in the future.

Flipped Learning in Socioscientific Issues Instruction: Its Impact on Middle School Students' Key Competencies and Character Development as Citizens (플립러닝 기반 SSI 수업이 중학생의 과학기술 사회 시민으로서의 역량 및 인성 함양에 미치는 효과)

  • Park, Donghwa;Ko, Yeonjoo;Lee, Hyunju
    • Journal of The Korean Association For Science Education
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    • v.38 no.4
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    • pp.467-480
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    • 2018
  • This study aims to investigate how flipped learning-based socioscientific issue instruction (FL-SSI instruction) affected middle school students' key competencies and character development. Traditional classrooms are constrained in terms of time and resources for exploring the issues and making decision on SSI. To address these concerns, we designed and implemented an SSI instruction adopting flipped learning. Seventy-three 8th graders participated in an SSI program on four topics for over 12 class periods. Two questionnaires were used as a main data source to measure students' key competencies and character development before and after the SSI instruction. In addition, student responses and shared experience from focus group interviews after the instruction were collected and analyzed. The results indicate that the students significantly improved their key competencies and experienced character development after the SSI instruction. The students presented statistically significant improvement in the key competencies (i.e., collaboration, information and technology, critical thinking and problem-solving, and communication skills) and in two out of three factors in character and values as global citizens (social and moral compassion, and socio-scientific accountability). Interview data supports the quantitative results indicating that SSI instruction with a flipped learning strategy provided students in-depth and rich learning opportunities. The students responded that watching web-based videos prior to class enabled them to deeply understand the issue and actively engage in discussion and debate once class began. Furthermore, the resulting gains in available class time deriving from a flipped learning approach allowed the students to examine the issue from diverse perspectives.

Factors Influencing the Adoption of Location-Based Smartphone Applications: An Application of the Privacy Calculus Model (스마트폰 위치기반 어플리케이션의 이용의도에 영향을 미치는 요인: 프라이버시 계산 모형의 적용)

  • Cha, Hoon S.
    • Asia pacific journal of information systems
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    • v.22 no.4
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    • pp.7-29
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    • 2012
  • Smartphone and its applications (i.e. apps) are increasingly penetrating consumer markets. According to a recent report from Korea Communications Commission, nearly 50% of mobile subscribers in South Korea are smartphone users that accounts for over 25 million people. In particular, the importance of smartphone has risen as a geospatially-aware device that provides various location-based services (LBS) equipped with GPS capability. The popular LBS include map and navigation, traffic and transportation updates, shopping and coupon services, and location-sensitive social network services. Overall, the emerging location-based smartphone apps (LBA) offer significant value by providing greater connectivity, personalization, and information and entertainment in a location-specific context. Conversely, the rapid growth of LBA and their benefits have been accompanied by concerns over the collection and dissemination of individual users' personal information through ongoing tracking of their location, identity, preferences, and social behaviors. The majority of LBA users tend to agree and consent to the LBA provider's terms and privacy policy on use of location data to get the immediate services. This tendency further increases the potential risks of unprotected exposure of personal information and serious invasion and breaches of individual privacy. To address the complex issues surrounding LBA particularly from the user's behavioral perspective, this study applied the privacy calculus model (PCM) to explore the factors that influence the adoption of LBA. According to PCM, consumers are engaged in a dynamic adjustment process in which privacy risks are weighted against benefits of information disclosure. Consistent with the principal notion of PCM, we investigated how individual users make a risk-benefit assessment under which personalized service and locatability act as benefit-side factors and information privacy risks act as a risk-side factor accompanying LBA adoption. In addition, we consider the moderating role of trust on the service providers in the prohibiting effects of privacy risks on user intention to adopt LBA. Further we include perceived ease of use and usefulness as additional constructs to examine whether the technology acceptance model (TAM) can be applied in the context of LBA adoption. The research model with ten (10) hypotheses was tested using data gathered from 98 respondents through a quasi-experimental survey method. During the survey, each participant was asked to navigate the website where the experimental simulation of a LBA allows the participant to purchase time-and-location sensitive discounted tickets for nearby stores. Structural equations modeling using partial least square validated the instrument and the proposed model. The results showed that six (6) out of ten (10) hypotheses were supported. On the subject of the core PCM, H2 (locatability ${\rightarrow}$ intention to use LBA) and H3 (privacy risks ${\rightarrow}$ intention to use LBA) were supported, while H1 (personalization ${\rightarrow}$ intention to use LBA) was not supported. Further, we could not any interaction effects (personalization X privacy risks, H4 & locatability X privacy risks, H5) on the intention to use LBA. In terms of privacy risks and trust, as mentioned above we found the significant negative influence from privacy risks on intention to use (H3), but positive influence from trust, which supported H6 (trust ${\rightarrow}$ intention to use LBA). The moderating effect of trust on the negative relationship between privacy risks and intention to use LBA was tested and confirmed by supporting H7 (privacy risks X trust ${\rightarrow}$ intention to use LBA). The two hypotheses regarding to the TAM, including H8 (perceived ease of use ${\rightarrow}$ perceived usefulness) and H9 (perceived ease of use ${\rightarrow}$ intention to use LBA) were supported; however, H10 (perceived effectiveness ${\rightarrow}$ intention to use LBA) was not supported. Results of this study offer the following key findings and implications. First the application of PCM was found to be a good analysis framework in the context of LBA adoption. Many of the hypotheses in the model were confirmed and the high value of $R^2$ (i.,e., 51%) indicated a good fit of the model. In particular, locatability and privacy risks are found to be the appropriate PCM-based antecedent variables. Second, the existence of moderating effect of trust on service provider suggests that the same marginal change in the level of privacy risks may differentially influence the intention to use LBA. That is, while the privacy risks increasingly become important social issues and will negatively influence the intention to use LBA, it is critical for LBA providers to build consumer trust and confidence to successfully mitigate this negative impact. Lastly, we could not find sufficient evidence that the intention to use LBA is influenced by perceived usefulness, which has been very well supported in most previous TAM research. This may suggest that more future research should examine the validity of applying TAM and further extend or modify it in the context of LBA or other similar smartphone apps.

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Methodology for Issue-related R&D Keywords Packaging Using Text Mining (텍스트 마이닝 기반의 이슈 관련 R&D 키워드 패키징 방법론)

  • Hyun, Yoonjin;Shun, William Wong Xiu;Kim, Namgyu
    • Journal of Internet Computing and Services
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    • v.16 no.2
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    • pp.57-66
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    • 2015
  • Considerable research efforts are being directed towards analyzing unstructured data such as text files and log files using commercial and noncommercial analytical tools. In particular, researchers are trying to extract meaningful knowledge through text mining in not only business but also many other areas such as politics, economics, and cultural studies. For instance, several studies have examined national pending issues by analyzing large volumes of text on various social issues. However, it is difficult to provide successful information services that can identify R&D documents on specific national pending issues. While users may specify certain keywords relating to national pending issues, they usually fail to retrieve appropriate R&D information primarily due to discrepancies between these terms and the corresponding terms actually used in the R&D documents. Thus, we need an intermediate logic to overcome these discrepancies, also to identify and package appropriate R&D information on specific national pending issues. To address this requirement, three methodologies are proposed in this study-a hybrid methodology for extracting and integrating keywords pertaining to national pending issues, a methodology for packaging R&D information that corresponds to national pending issues, and a methodology for constructing an associative issue network based on relevant R&D information. Data analysis techniques such as text mining, social network analysis, and association rules mining are utilized for establishing these methodologies. As the experiment result, the keyword enhancement rate by the proposed integration methodology reveals to be about 42.8%. For the second objective, three key analyses were conducted and a number of association rules between national pending issue keywords and R&D keywords were derived. The experiment regarding to the third objective, which is issue clustering based on R&D keywords is still in progress and expected to give tangible results in the future.

The Standard of Judgement on Plagiarism in Research Ethics and the Guideline of Global Journals for KODISA (KODISA 연구윤리의 표절 판단기준과 글로벌 학술지 가이드라인)

  • Hwang, Hee-Joong;Kim, Dong-Ho;Youn, Myoung-Kil;Lee, Jung-Wan;Lee, Jong-Ho
    • Journal of Distribution Science
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    • v.12 no.6
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    • pp.15-20
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    • 2014
  • Purpose - In general, researchers try to abide by the code of research ethics, but many of them are not fully aware of plagiarism, unintentionally committing the research misconduct when they write a research paper. This research aims to introduce researchers a clear and easy guideline at a conference, which helps researchers avoid accidental plagiarism by addressing the issue. This research is expected to contribute building a climate and encouraging creative research among scholars. Research design, data, methodology & Results - Plagiarism is considered a sort of research misconduct along with fabrication and falsification. It is defined as an improper usage of another author's ideas, language, process, or results without giving appropriate credit. Plagiarism has nothing to do with examining the truth or accessing value of research data, process, or results. Plagiarism is determined based on whether a research corresponds to widely-used research ethics, containing proper citations. Within academia, plagiarism goes beyond the legal boundary, encompassing any kind of intentional wrongful appropriation of a research, which was created by another researchers. In summary, the definition of plagiarism is to steal other people's creative idea, research model, hypotheses, methods, definition, variables, images, tables and graphs, and use them without reasonable attribution to their true sources. There are various types of plagiarism. Some people assort plagiarism into idea plagiarism, text plagiarism, mosaic plagiarism, and idea distortion. Others view that plagiarism includes uncredited usage of another person's work without appropriate citations, self-plagiarism (using a part of a researcher's own previous research without proper citations), duplicate publication (publishing a researcher's own previous work with a different title), unethical citation (using quoted parts of another person's research without proper citations as if the parts are being cited by the current author). When an author wants to cite a part that was previously drawn from another source the author is supposed to reveal that the part is re-cited. If it is hard to state all the sources the author is allowed to mention the original source only. Today, various disciplines are developing their own measures to address these plagiarism issues, especially duplicate publications, by requiring researchers to clearly reveal true sources when they refer to any other research. Conclusions - Research misconducts including plagiarism have broad and unclear boundaries which allow ambiguous definitions and diverse interpretations. It seems difficult for researchers to have clear understandings of ways to avoid plagiarism and how to cite other's works properly. However, if guidelines are developed to detect and avoid plagiarism considering characteristics of each discipline (For example, social science and natural sciences might be able to have different standards on plagiarism.) and shared among researchers they will likely have a consensus and understanding regarding the issue. Particularly, since duplicate publications has frequently appeared more than plagiarism, academic institutions will need to provide pre-warning and screening in evaluation processes in order to reduce mistakes of researchers and to prevent duplicate publications. What is critical for researchers is to clearly reveal the true sources based on the common citation rules and to only borrow necessary amounts of others' research.

Predictive Clustering-based Collaborative Filtering Technique for Performance-Stability of Recommendation System (추천 시스템의 성능 안정성을 위한 예측적 군집화 기반 협업 필터링 기법)

  • Lee, O-Joun;You, Eun-Soon
    • Journal of Intelligence and Information Systems
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    • v.21 no.1
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    • pp.119-142
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    • 2015
  • With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.

Predicting link of R&D network to stimulate collaboration among education, industry, and research (산학연 협업 활성화를 위한 R&D 네트워크 연결 예측 연구)

  • Park, Mi-yeon;Lee, Sangheon;Jin, Guocheng;Shen, Hongme;Kim, Wooju
    • Journal of Intelligence and Information Systems
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    • v.21 no.3
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    • pp.37-52
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    • 2015
  • The recent global trends display expansion and growing solidity in both cooperative collaboration between industry, education, and research and R&D network systems. A greater support for the network and cooperative research sector would open greater possibilities for the evolution of new scholar and industrial fields and the development of new theories evoked from synergized educational research. Similarly, the national need for a strategy that can most efficiently and effectively support R&D network that are established through the government's R&D project research is on the rise. Despite the growing urgency, due to the habitual dependency on simple individual personal information data regarding R&D industry participants and generalized statistical data references, the policies concerning network system are disappointing and inadequate. Accordingly, analyses of the relationships involved for each subject who is participating in the R&D industry was conducted and on the foundation of an educational-industrial-research network system, possible changes within and of the network that may arise were predicted. To predict the R&D network transitions, Common Neighbor and Jaccard's Coefficient models were designated as the basic foundational models, upon which a new prediction model was proposed to address the limitations of the two aforementioned former models and to increase the accuracy of Link Prediction, with which a comparative analysis was made between the two models. Through the effective predictions regarding R&D network changes and transitions, such study result serves as a stepping-stone for an establishment of a prospective strategy that supports a desirable educational-industrial-research network and proposes a measure to promote the national policy to one that can effectively and efficiently sponsor integrated R&D industries. Though both weighted applications of Common Neighbor and Jaccard's Coefficient models provided positive outcomes, improved accuracy was comparatively more prevalent in the weighted Common Neighbor. An un-weighted Common Neighbor model predicted 650 out of 4,136 whereas a weighted Common Neighbor model predicted 50 more results at a total of 700 predictions. While the Jaccard's model demonstrated slight performance improvements in numeric terms, the differences were found to be insignificant.

Analysis of the Elderly Travel Characteristics and Travel Behavior with Daily Activity Schedules (the Case of Seoul, Korea) (활동 스케줄 분석을 통한 고령자의 통행특성과 통행행태에 관한 연구)

  • Seo, Sang-Eon;Jeong, Jin-Hyeok;Kim, Sun-Gwan
    • Journal of Korean Society of Transportation
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    • v.24 no.5 s.91
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    • pp.89-108
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    • 2006
  • Korea has been entering the ageing society as the population of age over 65 shared over 7% since the year 2000. The ageing society needs to have transportation facility considering elderly people's travel behavior. This study aims to understand the elderly people's travel behavior using recent data in Korea. The activity schedule approach begins with travel outcomes are part of an activitv scheduling decision. For tho?e approach. used discrete choice models (especially. Nested Logit Model) to address the basic modeling problem capturing decision interaction among the many choice dimensions of the immense activity schedule choice set The day activity schedule is viewed as a sot of tours and at-home activity episodes tied togather with overarching day activity pattern using the Seoul Metropolitan Area Transportation Survey data, which was conducted in June, 2002. Decisions about a specific tour in the schedule are conditioned by the choice of day activity pattern. The day activity scheduling model estimated in this study consists of tours interrelated in a day activity pattern. The day activity pattern model represents the basic decision of activity participation and priorities and places each activity in a configuration of tours and at-home episodes. Each pattern alternative is defined by the primary activity of the day, whether the primary activity occurs at home or away, and the type of tour for the primary activity. In travel mode choice of the elderly and non-workers, especially, travel cost was found to be important in understanding interpersonal variations in mode choice behavior though, travel time was found to be less important factor in choosing travel mode. In addition, although, generally, the elderly was likely to choose transit mode, private mode was preferred for the elderly over 75 years old owing to weakened physical health for such things as going up and down of stairs. Therefore. as entering the ageing society, transit mode should be invested heavily in transportation facility Planning tor improving elderly transportation service. Although the model has not yet been validated in before-and-after prediction studies. this study gives strong evidence of its behavioral soundness, current practicality. and potential for improving reliability of transportation Projects superior to those of the best existing systems in Korea.

Disability-Rights Based International Cooperation: With Some References to North Korea (장애 권리 기반한 국제협력: 북한 관련하여)

  • Kim, Hyung Shik;Woo, Joo Hyung
    • 재활복지
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    • v.22 no.2
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    • pp.1-30
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    • 2018
  • This paper attempts to explore the place of human and disability rights from the perspective of Social Welfare within the context of the UN Disability Rights Convention of 2006. The overall discussion is focused especially upon the situations of human and disability rights in the Democratic People's Republic of Korea (North Korea) as it is being challenged to drastically address the issues of human rights in general, and disability rights in particular. The UN Disability Rights Convention challenges every ratified State party to commence legal reforms, legal harmonization, and policy and program developments to implement the Convention. Both North and South Korea are not exceptions to this. Even without drawing upon the UN's the Commission of Inquiry on Human Rights in the Democratic People's Republic of Korea, the dire situation of human rights in North Korea is well documented. However, this paper does not assume South Korea's human rights are any way superior to that of North Korea. This paper spells out areas for further action common to two Koreas and to any other nations for that matter. Apart from the general discussion on disability rights, the distinctive contribution of this paper lies in the fact that it has endeavored to draw upon any latest information and data on North Korea. It relied on various sources from UN and also from North Korea itself. One can note that North Korean disability authorities are making strenuous efforts to improve human rights of persons with disabilities in their desires to seek assistance from outside. It also shows an enormous need for international cooperation in seeking financial and material supports. This paper notes the latest political development between North and South Korea in taking "phased" steps for peace and stability as a positive sign for North and South Koreans' DPOs collaboration under the banner of International Cooperation of the article 32 of the UN Disability Rights Convention. More critically, this paper points to the further need to improve the overall data bases to ensure balanced legal reforms, policy developments and sharpen the areas of international collaboration.