Journal of the Korean Society of Marine Environment & Safety (해양환경안전학회지)

The Korean Society of Marine Environment and safety (해양환경안전학회)
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Study on Tourism Demand Forecast and Influencing Factors in Busan Metropolitan City

부산 연안도시 관광수요 예측과 영향요인에 관한 연구

  • Kyu Won Hwang (Ocean Law and Policy Institute, Korea Institute of Ocean Science and Technology(KIOST)) ;
  • Sung Mo Nam (Ocean Law and Policy Institute, Korea Institute of Ocean Science and Technology(KIOST)) ;
  • Ah Reum Jang (Ocean Law and Policy Institute, Korea Institute of Ocean Science and Technology(KIOST)) ;
  • Moon Suk Lee (Ocean Law and Policy Institute, Korea Institute of Ocean Science and Technology(KIOST))
  • 황규원 (한국해양과학기술원 해양법.정책연구소) ;
  • 남성모 (한국해양과학기술원 해양법.정책연구소) ;
  • 장아름 (한국해양과학기술원 해양법.정책연구소) ;
  • 이문숙 (한국해양과학기술원 해양법.정책연구소)
  • Received : 2023.11.17
  • Accepted : 2023.12.29
  • Published : 2023.12.31
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Abstract

Improvements in people's quality of life, diversification of leisure activities, and changes in population structure have led to an increase in the demand for tourism and an expansion of the diversification of tourism activities. In particular, for coastal cities where land and marine tourism elements coexist, various factors influence their tourism demands. Tourism requires the construction of infrastructure and content development according to the demand at the tourist destination. This study aims to improve the prediction accuracy and explore influencing factors through time series analysis of tourism scale using agent-based data. Basic local governments in the Busan area were examined, and the data used were the number of tourists and the amount of tourism consumption on a monthly basis. The univariate time series analysis, which is a deterministic model, was used along with the SARIMAX analysis to identify the influencing factor. The tourism consumption propensity, focusing on the consumption amount according to business types and the amount of mentions on SNS, was set as the influencing factor. The difference in accuracy (RMSE standard) between the time series models that did and did not consider COVID-19 was found to be very wide, ranging from 1.8 times to 32.7 times by region. Additionally, considering the influencing factor, the tourism consumption business type and SNS trends were found to significantly impact the number of tourists and the amount of tourism consumption. Therefore, to predict future demand, external influences as well as the tourists' consumption tendencies and interests in terms of local tourism must be considered. This study aimed to predict future tourism demand in a coastal city such as Busan and identify factors affecting tourism scale, thereby contributing to policy decision-making to prepare tourism demand in consideration of government tourism policies and tourism trends.

최근 국민 삶의질 향상, 여가 활동 다변화, 인구구조의 변화 등으로 관광수요 증가 및 관광활동이 다양화되고 있다. 특히 연안도시의 경우, 육상 관광 요소와 해양관광 요소가 공존하는 지역으로 다양한 요인이 관광수요에 영향을 미치고 있다. 본 연구 목적은 본 연구는 행위자 기반의 데이터를 활용하여 관광규모의 시계열 분석을 통해 예측 정확도를 향상시키고, 영향요인을 탐색하고자 한다. 연구 대상은 부산 지역 내 기초자치단체이며, 데이터는 월단위의 관광객수와 관광소비금액을 활용하였다. 연구방법으로 확정적(결정적) 모형인 단변량 시계열 분석과 영향요인을 파악하기 위해 SARIMAX 분석을 수행하였다. 영향요인은 관광소비성향을 설정하였으며, 업종별 소비금액과 SNS 언급량을 중심으로 설정하였다. 연구결과 COVID-19를 고려하지 않은 시계열 모형과 고려한 모형 간의 정확도(RMSE 기준) 차이가 지역별로 최소 1.8배에서 최대 32.7배 향상되었다. 또한 영향요인을 보면 관광소비업종과 SNS 트렌드가 관광객수와 관광소비금액에 유의한 영향을 미치고 있다. 따라서 미래 수요예측을 위해서는 외적 영향을 고려하고, 관광객의 소비성향과 관심도가 지역관광 측면에서 고려 대상이 된다. 본 연구는 연안도시인 부산 지역의 미래 관광수요 예측과 관광규모에 미치고 있는 영향요인을 파악하여 정부 관광정책 및 관광추세를 고려한 관광수요태세 마련을 위한 정책 의사결정에 기여하고자 한다.

Keywords

Acknowledgement

이 연구는 2023년도 해양수산부의 재원으로 해양수산과학기술원의 지원(해양공간 정책시뮬레이터 기술개발(과제번호: 20220431))으로 수행되었습니다.

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