확장된 기술수용모델을 적용한국기원 홈페이지의 품질특성 및 이용의도의 관계

박채호 국기원 2023 국기원태권도연구 Vol.14 No.2

Purpose The purpose of this study is to investigate and verify a structural relationship between quality characteristics of Kukkiwon website that applied an extended technology acceptance model and use intention. Method A total of 29 questions, including personal characteristics, relationship norms, copartnership, communication, institutions image, attitude were analyzed 553 copies, excluding 47 responses, which lacked response contents through the Self-Administration Method. Analysis was performed using PASW/PC 18.0 and AMOS 18.0 programs. Results First, of the quality characteristics of Kukkiwon website, service quality characteristic turned out to have a significant influence on the perceived usefulness. Second, quality characteristic of Kukkiwon website had a significant influence on the perceived easiness. Third, perceived easiness had a significant influence on the perceived usefulness. Fourth, perceived usefulness and perceived easiness had a significant influence on the use intention. Conclusion Accordingly, continuous efforts are considered necessary for raising the quality of information and interactive communication by recognizing that quality characteristics of extended technology acceptance model-applied Kukkiwon website are the precedence factor having a significant influence on users’ use intention. 목적: 본 연구는 확장된 기술수용모델을 적용하여 국기원 홈페이지의 품질특성과 이용의도의 구조적 관계를 규명하는데 목적이 있다. 방법 : 국기원 홈페이지를 사용한 경험이 있는 태권도인을 모집단으로 선정하여 유의적 표본추출법을 사용하여 600부를 배포하여 불성실하거나 이중 응답한 47부를 제외한 553부를 연구에 사용하였다. 수집된 자료는 PASW/PC 18.0과 AMOS 18.0 프로그램을 사용하여 기술통계, 상관관계, 구조방정식모형을 분석하였다. 결과 : 첫째, 국기원 홈페이지의 서비스 품질특성은 지각된 유용성, 지각된 용이성에 유의한 영향을 미치는 것으로 나타났다. 둘째, 국기원 홈페이지의 시스템 품질특성과 정보 품질특성은 지각된 용이성에 유의한 영향을 미치는 것으로 나타났다. 셋째, 국기원 홈페이지 사용자가 지각한 용이성은 지각된 유용성에 유의한 영향을 미치는 것으로 나타났다. 넷째, 국기원 홈페이지 사용자가 지각한 유용성과 용이성은 이용의도에 유의한 영향을 미치는 것으로 나타났다. 결론 : 확장된 기술수용모델을 적용한 국기원 홈페이지의 품질특성이 사용자의 이용의도에 유의한 영향을 미치는 중요한 선행 요인임을 인지하여 국기원 홈페이지를 운영함에 있어 정보의 질을 높이고 쌍방향 커뮤니케이션이 이루어질 수 있도록 지속적인 노력이 필요할 것으로 판단된다.

금속 활자로 인쇄된 글자 영상을 위한 개선된 이미지 정합 방식

박채호(Chae-Ho Park),최강선(Kang-Sun Choi) 대한전자공학회 2023 대한전자공학회 학술대회 Vol.2023 No.6

In this paper, we propose an image registration method for determining the similarity between printed characters. After experimenting with various methods, we utilize the normalized cross correlation with hierarchical brute force search algorithm, which show the best performance. As a result of applying this method, the performance of the proposed method improves compared to the existing intensity-based registration method used in MATLAB method.

스포츠센터 지도자의 커뮤니케이션 유형이 회원과의 관계의 질에 미치는 영향

박채호(Park, Cha-Ho),김동규(Kim, Dong-Kyu) 한국체육과학회 2023 한국체육과학회지 Vol.32 No.1

대학 학생운동선수들의 스포츠태도가 인간관계에 미치는 영향

박채호 ( Park Chae-ho ) 대한체육학회(구 한국유산소운동과학회) 2020 대한스포츠융합학회지 (jcses) Vol.18 No.2

The purpose of this study is to investigate the influence of college student athletes' sports attitudes on human relationships. Therefore, it is possible to cultivate the sports attitude of student athletes and provide basic data to help form human relationships. In order to achieve the purpose of the study, a survey was conducted by personally visiting a university in the metropolitan area of Korea. For the sampling, a total of 300 questionnaires were distributed, and a total of 290 (96.7%) of the collected data were used. The results derived through this process are as follows. First, Sports attitudes and human relations of college student athletes were correlated in all factors. Second, Among the sports attitudes of college student athletes, social attitudes influenced satisfaction, openness, understanding, and trust. In addition, the psychological attitude influenced the sense of understanding and trust. Therefore, a lot of attention and guidance will be needed in our society, sports institutions, and universities to cultivate healthy sports attitudes of student athletes.

스포츠 헬스케어 산업에 관한 빅데이터 분석

장덕진(Jang, Deok-Jin),박채호(Park, Che-Ho),김동규(Kim, Dong-Kyu),박성언(Park, Sung-Un) 한국체육과학회 2022 한국체육과학회지 Vol.31 No.5

The purpose of this study is to derive issues related to sports and healthcare industry by applying big data analysis to create future value of the sports healthcare industry. The data collection period was set from January 1, 2012 to August 30, 2021, and data was collected focusing on the keywords ‘sports, health care, industry’ targeting unstructured texts that appeared on Naver and Google. The results obtained according to these procedures are as follows. First, as a result of the frequency analysis of text mining analysis, high frequencies appeared in the order of health care, sports, industry, education, and characteristics. Second, as a result of TF-IDF analysis, the top words appeared in the order of education, characteristics, sports, industry, and medical care. Third, as a result of the degree centrality analysis of the social network analysis, the top words appeared in the order of education, sports, characteristics, health care, and rehabilitation. Fourth, as a result of CONCOR analysis, four groups were derived: sports healthcare and industry, sports healthcare and education, sports healthcare and technology, and sports healthcare and talent cultivation. Our findings can provide academic and empirical baseline data for the sports healthcare industry.

공공스포츠클럽 ‘스포츠 온’ 활성화 방안에 관한 연구

장덕진(Jang, Deok-Jin),김동규(Kim, Dong-Kyu),김정균(Kim, Jung-Kyun),박채호(Park, Chae-Ho) 한국체육과학회 2023 한국체육과학회지 Vol.32 No.6

The purpose of this study is to present an effective activation plan through IPA analysis of public sports club (sports-on) selection attributes. To achieve this goal, data were collected from 197 members who had experience using public sports clubs and analyzed through SPSS. The results of the study are as follows. First, in the first quadrant, which means continuity, the program composition, program diversity, program interest, and leaders words and actions were derived. Second, in the second quadrant, which means intensive improvement, the attributes of cleanliness, location convenience, transportation convenience, tuition, and other expenditures were presented. Third, in the third quadrant, which means low priority, the properties of interior, air conditioning facilities, lighting atmosphere, and discounts appeared. Fourth, in the fourth quadrant, which avoids the meaning of excessive effort, the program difficulty, leader history, leader experience, leader appearance, club size, and parking convenience were derived. As such, this study provides academic and practical implications for suggesting ways to revitalize public sports clubs through IPA analysis.

빅데이터 분석을 통한 학생선수에 관한 개념과 속성 탐색

박성언(Park, Sung-Un),안효연(Ahn, Hyo-Yeon),박채호(Park, Chae-Ho) 한국체육과학회 2022 한국체육과학회지 Vol.31 No.5

The purpose of this study was to verify the concept and perception of student athlete through social media big data anlaysis, and to suggest value and direction of policy and system for student athletes. The data collection period was from January 1, 2017 to June 30, 2022, focusing on the keyword of “student athlete” for unfiltered and unstructured text data appearing on Naver, Daum, Google, and YouTube. Textom, a big data collection and analysis solution, was used for data collection. For data analysis, frequency analysis and TF-IDF (Term Frequency Inverse Document Frequency) analysis of text mining analysis were performed, and connection centrality and CONCOR (CONvergence of iterated CORrelations) analysis of social network analysis were performed using Textom and UCINET 6.0 program. The results of this study were as follows. First, the total amount of textual data collected through social media was 5,424 cases (2,743KB). Second, as a result of frequency and TF-IDF analysis, ‘athlete’, ‘student’, ‘student athlete’, ‘competitions’, ‘sports’ had the most in common. Third, As a result of the connection centrality analysis, centrality measures were shown in the order of athletes (374.220), students (288.441), student athletes (175.441), competitions (120.373), and exercise (99.949). Lastly, as a result of CONCOR analysis, it was categorized into seven clusters: ‘player training system’, ‘academic parallelism’, ‘identity’, ‘policy support’, ‘career / college-preparatory’, ‘research activities’, and ‘social issues’. Through these results of such big data analysis, it is possible to provide the academic basic data necessary for proposing policies and strategic directions and improvement measures necessary for the growth of student athletes.