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A Study on Segmentation of Preferred Characteristics of Rural Tourists after COVID-19 Using Decision Tree Analysis

의사결정나무분석을 활용한 코로나19 이후 농촌관광객의 선호 특성 세분화 연구

  • Seung-Hun Lee (Department of Hotel Business, Joongbu University)
  • 이승훈 (중부대학교 항공관광학부 호텔비즈니스전공)
  • Received : 2023.02.28
  • Accepted : 2023.03.25
  • Published : 2023.03.31

Abstract

Purpose - The purpose of this study was to explore and diagnose the characteristics and behavioural patterns of rural tourists after COVID-19 using decision tree analysis to classify and identify key segmentation groups. Design/methodology/approach - The CHAID algorithm was used as the analysis technique for the decision tree. The explanatory variables used in the analysis of each decision tree model were demographic variables and rural tourism usage behaviour and perception variables, and the target variables were the preferences of rural tourists' activities after COVID-19. From the Rural Tourism 2020 survey data, 614 samples with rural tourism experience were extracted and used in the analysis. Findings - The variables that significantly explained the preference for each type of rural tourism activity after COVID-19 were rural tourism safety perception, repeated visits to the region, rural tourism priority activity, rural tourism accommodation experience, gender, age group, marital status, occupation, and education level. Among them, rural tourism safety perception was the most important explanatory variable in each analysis model. Research implications or Originality - Overall, to promote rural tourism, it is necessary to enhance the safety image of rural tourism, strengthen loyalty programs for repeat visitors, and develop customized products that reflect the preferred trends of rural tourism.

Keywords

References

  1. 김경희, 황대용, 이혜영 (2021), "농촌 치유관광객 시장세분화 연구", 농촌지도와 개발, 28, 13-23.
  2. 김용진, 이성희, 손용훈 (2021), "소셜데이터 분석을 통한 포스트 코로나 시대 농촌관광의 변화와 적용방안", 농촌계획, 27(4), 43-54.
  3. 농림수산식품교육문화정보원 (2022), "농촌관광", FATI(Farm Trend&Issue), 2, 1-15.
  4. 농촌진흥청 국립농업과학원 (2022), "농촌관광실태조사".
  5. 박기용 (2006), "의사결정나무모형을 이용한 레스토랑 프랜차이즈 가맹자의 선택요인에 관한 연구", 호텔경영학연구, 15(4), 105-117.
  6. 박덕병, 이민수, 김정섭 (2004), "농촌관광 시장 세분화 연구", 관광학연구, 28(2), 193-212.
  7. 여행신문 (2021, May, 12), "[China 리포트] 코로나19로 중국 농촌 관광 붐", Available from http://www.traveltimes.co.kr/news/articleView.html?idxno=111942
  8. 우은주, 이상탁 (2022), "보호동기이론(PMT)과 건강신념모델(HBM)을 이용한 관광객 위기대응 행동 분석: COVID-19 위기", 아태비즈니스연구, 13(1), 301-315.
  9. 유준완, 황대용 (2022), "포스트 코로나 시대의 추구편익에 따른 농촌관광 시장세분화 연구", 농촌지도와 개발, 29(4), 191-201.
  10. 유호종 (2019), "의사결정나무분석을 이용한 방한 일본관광객들의 재방문을 위한 예측모형", 상품학연구, 37(1), 21-30. https://doi.org/10.36345/KACST.2019.37.1.004
  11. 윤혜원, 진현정 (2020), "프리미엄 상영관 관람 현황 및 소비자 시장세분화 분석", 문화산업연구, 20(2), 73-84.
  12. 이승곤, 오민재 (2016), "농촌관광에 대한 영향인식이 관광사업 지지도에 미치는 영향 비교분석: 1사와 1촌 간의 비교", 관광연구저널, 30(5), 5-16.
  13. 이승욱 (2020), "코로나19로 인한 충북의 농촌융복합산업(6차산업) 실태와 활성화방안", 한국농공학회지, 62(3), 17-23.
  14. 이승훈 (2021), "위드 코로나 시대 트래블 버블의 안전지각이 관광목적지의 이미지, 신뢰와 안전관광 행동의도에 미치는 영향", 관광레저연구, 33(4), 99-118.
  15. 이승훈 (2022a), "OTA(online travel agency)의 선택속성과 특성에 따른 시장세분화 연구", 관광연구저널, 36(8), 101-121. https://doi.org/10.21298/IJTHR.2022.8.36.8.101
  16. 이승훈 (2022b), "코로나19의 피로감 인식과 여행관여도가 포스트팬데믹시대 보복여행 욕구와 해외여행 행동의도에 미치는 영향", 관광연구저널, 36(12), 111-126. https://doi.org/10.21298/IJTHR.2022.12.36.12.111
  17. 이승훈, 배준호 (2022), "코로나19에 따른 건강의식과 JOMO여행 성향이 엔데믹시대 웰니스관광의도에 미치는 영향: ETPB 모델 적용", 관광레저연구, 34(12), 69-89.
  18. 전창영, 송운강, 양희원 (2021), "코로나19 위험인식에 따른 친사회적 관광행동의도 결정과정 : 규범 활성화 모델을 활용하여", 아태비즈니스연구, 12(2), 145-15.
  19. 정인호, 이대웅, 권기헌 (2018), "청년 취업자의 이직의사 예측모형 탐색 연구: 의사결정나무모형을 중심으로", 국정관리연구, 13(3), 147-174. https://doi.org/10.16973/JGS.2018.13.3.006
  20. 최찬원, 최재문 (2021), "코로나 19 대응형 농촌관광 유형 특성 및 콘텐츠 개발 연구", 한국공간디자인학회 논문집, 16(3), 375-386.
  21. 한국농촌경제연구원 (2021), "포스트 코로나 시대 농촌관광의 패러다임 전환과 정책 과제".
  22. 한국문화관광연구원 (2021), "포스트 코로나 시대 관광산업의 성장 아젠다와 정책과제".
  23. 황진수, 주규현 (2021), "드론 음식배달 서비스에서 기대편익에 관한 시장세분화 연구: 의사결정나무 CHAID 알고리즘 분석을 중심으로", MICE관광연구, 21(3), 47-66.
  24. Brozovic, D. and H. Saito (2022), "The Impacts of Covid-19 on the Tourism Sector: Changes, Adaptations and Challenges", Tourism: An International Interdisciplinary Journal, 70(3), 465-479. https://doi.org/10.37741/t.70.3.9
  25. Ceylan, D., B. Cizel and H. Karakas (2021), "Destination image perception patterns of tourist typologies", International Journal of Tourism Research, 23(3), 401-416. https://doi.org/10.1002/jtr.2414
  26. Chen, J. S. (2003), "Market segmentation by tourists' sentiments", Annals of Tourism Research, 30(1), 178-193. https://doi.org/10.1016/S0160-7383(02)00046-4
  27. Chin, C. H. (2022), "Empirical research on the competitiveness of rural tourism destinations: a practical plan for rural tourism industry post-COVID-19", Consumer Behavior in Tourism and Hospitality, 17(2), 211-231. https://doi.org/10.1108/CBTH-07-2021-0169
  28. Diaz-Perez, F. M. and M. Bethencourt-Cejas (2016), "CHAID algorithm as an appropriate analytical method for tourism market segmentation", Journal of Destination Marketing & Management, 5(3), 275-282. https://doi.org/10.1016/j.jdmm.2016.01.006
  29. Diaz-Perez, F. M., A. Fyall, X. Fu, C. G. Garcia-Gonzalez and G. Deel (2021), "Florida state parks: A CHAID approach to market segmentation", Anatolia, 32(2), 246-261. https://doi.org/10.1080/13032917.2020.1856158
  30. Ginting, G. and I. J. Dewi (2022), "Reformulating a Market-Driven Service Strategy of Community-Based Tourist Destinations Post-Pandemic Covid-19: Evidence from Indonesia", Ilomata International Journal of Management, 3(3), 298-318. https://doi.org/10.52728/ijjm.v3i3.495
  31. Honarvar, P. (2001), A spatial approach to mineral potential modelling using decision tree and logistic regression analysis (Doctoral dissertation), Memorial University of Newfoundland.
  32. Kass, G. V. (1980), "An exploratory technique for investigating large quantities of categorical data", Journal of the Royal Statistical Society: Series C (Applied Statistics), 29(2), 119-127. https://doi.org/10.2307/2986296
  33. Kosciolek, S., K. Nessel, E. Wszendybyl-Skulska and S. Kopera (2018), "Who are the tourists booking their accommodations online? A segmentation study of the Cracow market", Barometr Regionalny. Analizy i Prognozy, 16(3), 91-100. https://doi.org/10.56583/br.354
  34. Lan, Y. F. and C. J. Su (2021), "Fathers' predominance in transport arrangements for family tourism: E-CHAID-based profiling in East Asia", Communications-Scientific letters of the University of Zilina, 23(4), 13-24.
  35. Lee, J. E. (2019), Examining the effects of discussion strategies and learner interactions on performance in online introductory mathematics courses: an application of learning analytics (Doctoral dissertation), Utah State University.
  36. Legoherel, P., C. H. Hsu and B. Dauce (2015), "Variety-seeking: Using the CHAID segmentation approach in analyzing the international traveler market", Tourism Management, 46, 359-366. https://doi.org/10.1016/j.tourman.2014.07.011
  37. Loncaric, D., P. Popovic and J. Kapes (2022), "Impact of the COVID-19 Pandemic on Tourism: A Systematic Literature Review", Tourism: An International Interdisciplinary Journal, 70(3), 512-526. https://doi.org/10.37741/t.70.3.12
  38. Luo, X. and Y. Z. Huang (2022), "Study on the Development Path of Rural Tourism in Chengdu in the Post-COVID-19 Era", Urban Studies and Public Administration. 5(2), 46-53. https://doi.org/10.22158/uspa.v5n2p46
  39. Pesonen, J. A. (2012), "Segmentation of rural tourists: Combining push and pull motivations", Tourism and Hospitality Management, 18(1), 69-82. https://doi.org/10.20867/thm.18.1.5
  40. Popescu, A. (2021), "The impact of COVID-19 pandemic on Romania's tourist flows in the year 2020", Scientific Papers Series Management, Economic Engineering in Agriculture and Rural Development, 21(1), 655-666.
  41. Rondovic, B., T. Djurickovic and L. Kascelan (2019), "Drivers of E-business diffusion in tourism: a decision tree approach", Journal of theoretical and applied electronic commerce research, 14(1), 30-50. https://doi.org/10.4067/S0718-18762019000100104
  42. Rosalina, P. D., K. Dupre and Y. Wang (2021), "Rural tourism: A systematic literature review on definitions and challenges", Journal of Hospitality and Tourism Management, 47, 134-149. https://doi.org/10.1016/j.jhtm.2021.03.001
  43. Sanchez-Canizares, S. M., L. J. Cabeza-Ramirez, G. Munoz-Fernandez and F. J. Fuentes-Garcia (2021), "Impact of the perceived risk from Covid-19 on intention to travel", Current Issues in Tourism, 24(7), 970-984. https://doi.org/10.1080/13683500.2020.1829571
  44. Sann, R., P. C. Lai, S. Y. Liaw and C. T. Chen (2022), "Predicting online complaining behavior in the hospitality industry: Application of big data analytics to online reviews", Sustainability, 14(3), 1800.
  45. Ulu, E. K. and S. A. Polat (2021), "Food & Beverage Expectations of Potential Tourists Based on Differences Between Generations", Journal of Tourism and Gastronomy Studies, 9(4), 2488-2502. https://doi.org/10.21325/jotags.2021.904
  46. Wang, J., Y. Wang, Y. He and Z. Zhu (2022), "Exploring the Factors of Rural Tourism Recovery in the Post-COVID-19 Era Based on the Grounded Theory: A Case Study of Tianxi Village in Hunan Province, China", Sustainability, 14(9), 5215.
  47. Zaman, U., S. J. Barnes, S. Abbasi, M. Anjam, M. Aktan and M. G. Khwaja (2022), "The Bridge at the End of the World: Linking Expat's Pandemic Fatigue, Travel FOMO, Destination Crisis Marketing, and Vaxication for Greatest of All Trips", Sustainability, 14(4), 2312.
  48. Zhang, Y., M. Lingyi, L. Peixue, Y. Lu and J. Zhang (2021), "COVID-19's impact on tourism: will compensatory travel intention appear?", Asia Pacific Journal of Tourism Research, 26(7), 732-747. https://doi.org/10.1080/10941665.2021.1908383