Examining the tourist experience factors : a mixed-methods

다국어 초록 (Multilingual Abstract)

Tourist experience as a popular research issue has been valued since it can help with promoting a thriving tourism industry. Chinese tourists as a leading player in the tourism industry accounted for almost one-fifth of global tourism spending before COVID-19. With the gradual end of COVID-19, tourism markets in worldwide are recovering. Destinations need to start preparing in advance to attract more tourists by improving the tourist experience. Thus, this study aims to focus on new Chinese tourists, and uses a mixed-methods approach, including a text-mining approach and an interview approach, to explore general key tourist experience factors (including the positive TE factors and negative TE factors) of Chinese tourists during their travel to Korea and Japan. This study applied the tourist experience conceptual model to in-depth understand the results of the experiments and summarized the general key tourist experience factors, the positive TE factors, and the negative TE factors of Seoul and Tokyo respectively. Based on the findings of this study, recommendations are tailor-made specifically for Seoul to help local tourism providers improve services and offer a better experience to tourists.

국문 초록 (Abstract)

관광 경험은 관광산업을 촉진하는 데 영향을 미칠 수 있기 때문에 많은 관심을 받아왔다. 코로나 19 이전까지 관광산업의 선두주자로서 중국 관광객은 전 세계 관광 지출의 약 5분의 1을 차지했다. 코로나 19가 점차 종식되면서 전 세계 관광 시장이 회복세를 보이고 있기 때문에, 여행지의 관광 경험을 개선함으로써 더 많은 관광객을 유치하기 위해 사전 준비를 할 필요가 있다. 따라서 본 연구의 목적은 중국인 관광객의 관광 경험요인을 탐색하는데 있다. 본 연구에서는 이를 위해 중국인 관광객을 중심으로 텍스트마이닝과 인터뷰를 포함한 혼합적 접근법을 사용하여 한국과 일본 여행 중 중국인 관광객의 일반적인 주요 관광 경험 요인(긍정적 TE 요인 및 부정적 TE 요인 포함)을 탐색한다. 추가적으로 실험 결과를 심층적으로 이해하기 위해 관광 경험 모형(Tourist experience conceptual model)을 적용하여 서울과 도쿄의 일반적인 주요 관광 경험 요인, 긍정적 TE요인, 부정적 TE요인을 각각 요약하였다. 또한 본 연구는 위의 결과를 바탕으로 서울의 지역 관광 사업자를 위한 실무적 전략을 제안한다.

목차 (Table of Contents)

• CONTENT
• FIGURES iii
• TABLES iv
• ABSTRACT v
• CHAPTER 1: INTRODUCTION 1
• CHAPTER 2: CONCEPTUAL BACKGROUND 4
• 2.1 TOURIST EXPERIENCE 4
• 2.2 TOURIST EXPERIENCE CONCEPTUAL MODEL 4
• 2.3 PREVIOUS RESEARCH ON TOURIST EXPERIENCE 6
• CHAPTER 3: METHODOLOGY 11
• 3.1 RESEARCH PROCEDURE 11
• 3.2 DATA COLLECTION 13
• 3.2.1 Text Mining Data Collection 13
• 3.2.2 Interview Data Collection 14
• 3.3 DATA ANALYSIS 15
• 3.3.1 Text Mining Data Analysis 16
• 3.3.2 Interview Data Analysis 19
• CHAPTER 4: QUANTITATIVE ANALYSIS AND RESULTS (TEXT MINING) 20
• 4.1 TF-IDF ANALYSIS AND RESULTS 20
• 4.1.1 TF-IDF Analysis of Seoul 20
• 4.1.2 TF-IDF Analysis of Tokyo 22
• 4.2 LDA TOPIC MODELING AND RESULTS 24
• 4.2.1 LDA Topic Modeling of Seoul 24
• 4.2.2 LDA Topic Modeling of Tokyo 26
• 4.3 NETWORK ANALYSIS RESULTS 29
• 4.3.1 Network Analysis of Seoul 29
• 4.3.2 Network Analysis of Tokyo 30
• 4.4 EXTRACTED KEY FACTORS OF SEOUL AND TOKYO 31
• 4.5 SENTIMENT ANALYSIS AND RESULTS 34
• 4.5.1 Sentiment Analysis of Seoul 34
• 4.5.2 Sentiment Analysis of Tokyo 37
• CHAPTER 5: QUALITATIVE ANALYSIS AND RESULTS (INTERVIEW) 39
• 5.1 INTERVIEW RESULTS OF SEOUL 39
• 5.1.1 Interview Results of Seoul Key TE Factors 39
• 5.1.2 Interview Results of Seoul Positive TE Factors 41
• 5.1.3 Interview Results of Seoul Negative TE Factors 43
• 5.2 INTERVIEW RESULTS OF TOKYO 44
• 5.2.1 Interview Results of Tokyo Key TE Factors 44
• 5.2.2 Interview Results of Tokyo Positive TE Factors 46
• 5.2.3 Interview Results of Tokyo Negative TE Factors 48
• CHAPTER 6: COMPARISON BETWEEN QUANTITATIVE STUDY AND QUALITATIVE STUDY 49
• 6.1 GENERAL TE FACTORS 49
• 6.1.1 General Seoul TE Factors 49
• 6.1.2 General Tokyo TE Factors 51
• 6.2 POSITIVE TE FACTORS AND NEGATIVE TE FACTORS 53
• 6.2.1 Positive Seoul TE Factors 53
• 6.2.2 Negative Seoul TE Factors 54
• 6.2.3 Positive Tokyo TE Factors 56
• 6.2.4 Negative Tokyo TE Factors 57
• 6.3 RECOMMENDATIONS FOR SEOUL 58
• CHAPTER 7: DISCUSSION AND IMPLICATIONS 60
• 7.1 DISCUSSION OF FINDING 60
• 7.2 LIMITATIONS AND FUTURE RESEARCH 61
• 7.3 IMPLICATIONS FOR RESEARCH 62
• 7.4 IMPLICATIONS FOR PRACTICE 62
• APPENDIX 64
• ANALYSIS OF JEJU ISLAND 64