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研究生： KARTIKA AKBARIA
KARTIKA - AKBARIA
論文名稱： 應用PSKO與多構面尺度於台灣旅客關於印尼旅遊知覺市場區隔之研究
Market Segmentation of Taiwanese’ Perception about Indonesia Tourism Using PSKO and Multidimensional Scaling
指導教授： 郭人介
Ren-Jieh Kuo
口試委員: 王孔政
Kung-Jeng Wang
許鉅秉
Jiuh-Biing Sheu
學位類別： 碩士
Master
系所名稱： 管理學院 - 工業管理系
Department of Industrial Management
論文出版年： 2010
畢業學年度： 98
語文別： 英文
論文頁數： 130
外文關鍵詞： Taiwanese, tourists’ motivation, PSKO, Perceptual Map
相關次數： 點閱：217  下載：10 
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    • This study intends to investigate market segmentation of Taiwanese tourists based on their motivation to visit Indonesia, to investigate Taiwanese tourists’ preference of several types of tourism destinations offered in Indonesia, and to propose marketing strategy based on market segmentation and tourists’ preferences revealed. One thousand questionnaires were distributed to Taiwanese in several cities in Taiwan, especially in three big cities: Taipei, Kaohsiung, and Taichung. There were 678 data collected (67.8% response rate) and 641 data could be used for further data processing. By using factor analysis, it was known that there were 19 important variables included in three factors solution: learning-in-relax, external appeals, and special visit. Afterwards, by using the selected variables, number of clusters was determined and market segmentation was revealed. Methods used were Self Organizing Maps and Particle Swarm K-means Optimization, respectively.
    There were four clusters formed: passive tourists (26.68%), learning-in-relax tourists (32.92%), high perception tourists (18.56%), and high variation tourists (21.84%). It is strongly suggested to target learning-in-relax tourists and high perception tourists since they have already had good perception toward image of Indonesia tourism. Moreover, by using perceptual map, it was also known that most of respondents tend to visit heritage, culture, and nature-based tourism destinations offered in Indonesia

    ABSTRACT i ACKNOWLEDGEMENTS ii CONTENTS iii LIST OF FIGURES vi LIST OF TABLES vii CHAPTER I INTRODUCTION 1 1.1. Research Background 1 1.1.1. Tourism trend 1 1.1.2. Taiwanese as potential tourists 4 1.2. Research Objectives 6 1.3. Scope and Constraints 6 1.4. Research Framework 6 CHAPTER II LITERATURE SURVEY 9 2.1. Market Segmentation 9 2.2. Market Segmentation Variables 10 2.3. Tourist’s Preferences 12 2.4. Tourist’s Motivation 14 2.5. Clustering Methods 15 2.5.1. Artificial neural network for clustering 17 2.5.2. Evolutionary-based clustering algorithm 17 2.5.3. Fuzzy clustering algorithm 19 2.5.4. Two-stage clustering algorithm 19 2.6. Particle Swarm Optimization (PSO) 19 2.6.1. Concept of PSO 19 2.6.2. Application of PSO 22 2.7. Multidimensional Scaling (MDS) 23 CHAPTER III RESEARCH METHODOLOGY 25 3.1. Preparation of Data Collection 26 3.1.1. Choosing variables 26 3.1.2. Sampling 26 3.1.3. Questionnaire design 28 3.2. Data Collection and Data Processing 28 3.2.1. Statistical tests 29 3.2.2. Initial and main questionnaire 32 3.2.3. Determining number of clusters 32 3.2.4. Clustering the respondents 33 3.2.5. Evaluating tourist’s preferences 36 CHAPTER IV RESULTS AND DISCUSSION 38 4.1. Questionnaire 38 4.1.1. Choosing variables 38 4.1.2. Questionnaire distribution 40 4.2. Statistical Tests 44 4.1.2. Initial test for 30 data 44 4.1.2. Main test for 641 data 44 4.3. Determining Number of Clusters 49 4.4. Clustering using Particle Swarm K-means Optimization 51 4.4.1. Determination of parameters 51 4.4.2. Revealing four clusters of market segmentation 51 4.5. Perceptual map 58 4.5.1. Metric Scaling Data (MRSCAL) 59 4.5.2. Hierarchical Cluster Analysis (HICLUS) 62 4.6. Marketing Strategy 66 4.7. Findings 69 CHAPTER V CONCLUSIONS AND SUGGESTIONS 70 5.1. Conclusions 70 5.2. Managerial Implication 71 5.2.1. Suggestions for Government 71 5.2.2. Suggestions for Travel Agent/Tour Operator 74 5.2.3. Suggestions for Hotel Management Team 74 5.3. Suggestions for Future Research 74 REFERENCES 75 APPENDIX A: Foreign Tourists’ visit to Indonesia (2006-2007) 81 APPENDIX B: Researches which used ANN as clustering method in market segmentation 83 APPENDIX C: Variables identification 87 APPENDIX D: Questionnaire (english version) 90 APPENDIX E: Statistical test for 30 data in questionnaire part II (tourist’s motivation) 94 APPENDIX F: Statistical test for 30 data in questionnaire part III (tourist’s preferences) 98 APPENDIX G: Reliability test for 641 data in questionnaire part II (tourist’s motivation) 100 APPENDIX H: Factor analysis for 641 data in questionnaire part II (tourist’s motivation) 101 APPENDIX I: Reliability test for four-clusters (n=641) 107 APPENDIX J: Statistical test for 641 data in questionnaire part III (tourist’s preferences) 108 APPENDIX K: Dendogram for determining number of cluster 109 APPENDIX L: Cluster membership 110 APPENDIX M: Recapitulation of respondent’s demography 116

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