본문 바로가기
KERD
논문KCI 등재

해양관광 방문지 네트워크의 구조적 특성 분석 -수산물 구매자를 중심으로-

An Analysis of Structural Characteristics of Marine Tourism Destination Network: Focusing on the Seafood Purchaser

0

조회

0

다운로드

0

인용

0

참고문헌

키워드

주제분류학제간연구

초록

This study aimed to analyze the structural characteristics of the network of visitors to marine tourist destinations by using the social network analysis method. Researchers referred to the data based on the Ministry of Culture, Sports and Tourism’s ‘2020 National Travel Survey.' The samples were limited to those who purchased seafood products while traveling for tourism. For the total of 612 samples, the structural characteristics of each group's travel to destinations were analyzed by dividing them into upper, middle, and lower groups based on the proportion of seafood purchases. The statistical tool used for the analysis was NetMiner 4.3. The results of this study and its implications are as follows. Visitors to the marine tourist destinations are concentrated mainly in the Busan region. Firstly, this study implies that the brand image of tourist destinations is still playing a significant role, beyond the expectation that travel destinations will be dispersed after COVID-19. Secondly, this study shows that the group that purchases a lot of seafood tends to visit places where visitors are active. This result indicates a stronghold where certain activities are concentrated within the region and that the area has a reputation among visitors. Lastly, the result of this study also shows that the group with high consumption potential in tourist destinations has a high visit rate, mainly in October. In conclusion, based on the above research, to enhance Marine Tourism to attract tourists, this analysis proves by creating promotions and marketing activities to strengthen tourism will entice tourists. This can be done by linking the unique region-specific attractions, and by leveraging taste tours in these regions that will entice tourists during the fall season to attract tourists, with the scenery and food that can be enjoyed during the fall season.

Abstract

This study aimed to analyze the structural characteristics of the network of visitors to marine tourist destinations by using the social network analysis method. Researchers referred to the data based on the Ministry of Culture, Sports and Tourism’s ‘2020 National Travel Survey.' The samples were limited to those who purchased seafood products while traveling for tourism. For the total of 612 samples, the structural characteristics of each group's travel to destinations were analyzed by dividing them into upper, middle, and lower groups based on the proportion of seafood purchases. The statistical tool used for the analysis was NetMiner 4.3. The results of this study and its implications are as follows. Visitors to the marine tourist destinations are concentrated mainly in the Busan region. Firstly, this study implies that the brand image of tourist destinations is still playing a significant role, beyond the expectation that travel destinations will be dispersed after COVID-19. Secondly, this study shows that the group that purchases a lot of seafood tends to visit places where visitors are active. This result indicates a stronghold where certain activities are concentrated within the region and that the area has a reputation among visitors. Lastly, the result of this study also shows that the group with high consumption potential in tourist destinations has a high visit rate, mainly in October. In conclusion, based on the above research, to enhance Marine Tourism to attract tourists, this analysis proves by creating promotions and marketing activities to strengthen tourism will entice tourists. This can be done by linking the unique region-specific attractions, and by leveraging taste tours in these regions that will entice tourists during the fall season to attract tourists, with the scenery and food that can be enjoyed during the fall season.

참고문헌 (20)

  1. 고재우, "사회 네트워크 분석 방법을 활용한 국내 여객항로 분석 연구", 한국항해항만학회지, 39(3), pp.217~222 (2015), 한국항해항만학회[DOI]
  2. 김민철, "산업연관분석을 활용한 스포츠이벤트 참가자의 지역관광지 방문과 관광상품 구입의 경제적 파급효과분석", 한국스포츠산업경영학회지, 12(1), pp.27~41 (2007), 한국스포츠산업경영학회
  3. 김벽진, "국제 항공 여객운송의 네트워크 구조 분석", 한국항공경영학회지, 15(5), pp.133~162 (2017), 한국항공경영학회
  4. 김용연, "ITS 빅데이터를 활용한 도시 교통네트워크 구조분석", 한국빅데이터학회 학회지, 2(2), pp.1~7 (2017), 사)한국빅데이터학회[DOI]
  5. 김용학, "과학기술 공동연구의 연결망 구조:좁은 세상과 위치효과", 한국사회학, 41(4), pp.68~103 (2007), 한국사회학회
  6. 김용학, "소셜네트워크분석" (2011), 박영사
  7. 박용규, "동해안 해양수산·관광 발전 심포지엄 “청정·웅장…스토리텔링 통해 동해만의 브랜드 필요”", 대구신문, ~ (2020)
  8. 박광서, "해양수산 SNS 빅데이터 분석 결과 및 시사점", 한국해양환경•에너지학회지, 20(2), pp.117~125 (2017), 한국해양환경·에너지학회
  9. 박태수, "해양관광 활성화 방안 도출을 위한 빅데이터 분석 연구", 관광레저연구, 32(7), pp.179~194 (2020), (사)한국관광레저학회
  10. 송재호, "관광목적지 마케팅 연구경향 분석 연구 - 2000년~2009년 관광관련 국내 주요 학회지 분석을 중심으로 -", 관광학연구, 34(4), pp.143~166 (2010), 한국관광학회
  11. "관광객이 강릉 찾는 이유는?", 연합뉴스, ~ (2021)
  12. 이승현, "MZ세대의 해양관광 만족이 여행지역에서의 수산물 구매행동에 미치는 영향 -2020 국민여행조사 데이터를 중심으로-", 해양관광학연구, 15(1), pp.31~45 (2022), 한국해양관광학회[DOI]
  13. 장신이, "해양관광 관련 논문의 연구동향에 관한 내용분석: 2000-2019년 국내 관광분야 KCI등재지 학술논문을 중심으로", 해양관광학연구, 14(2), pp.195~215 (2021), 한국해양관광학회[DOI]
  14. 최훈, "라이프스타일 유형에 따른 수산물 밀키트 구매 의도에 관한 연구", 해양관광학연구, 14(3), pp.131~146 (2021), 한국해양관광학회[DOI]
  15. 하경희, "빅데이터 분석을 활용한 해양관광 트렌드 분석: 코로나19 이후 해양관광정책을 중심으로", 해양관광학연구, 14(1), pp.9~30 (2021), 한국해양관광학회[DOI]
  16. "포스트 코로나 시대, 미래가 기대되는 해양레저 관광" (2022)[URL]
  17. "위드 코로나 시대 해양관광산업이 뜬다" (2021)[URL]
  18. Burt, R. A, "Structural Holes; The Social Structureof Competition" (1992), Harvard University Press
  19. Reka Albert, "Statistical mechanics of complex networks", Reviews of modern physics, 74, pp.1~54 (2002)

관련 논문AI추천

이 간행물의 다른 논문 (7건)