1. NCCU Academic Hub
  2. 學術產出
  3. College of Commerce
  4. Theses
  5. Item

學術產出-Theses

Article View/Open

Publication Export

Google ScholarTM

政大圖書館

Citation Infomation

題名 藉由線上景點形象了解旅遊者的資訊需求與景點印象
Knowing tourists’ information needs and destination impression through online destination image
作者 鄭吉廷
Cheng, Chi-Ting
貢獻者 林怡伶
Lin, Yi-Ling
鄭吉廷
Cheng, Chi-Ting
關鍵詞 資訊需求
景點印象
景點形象
線上評論
線上景點形象
分類法
文字探勘
Information needs
destination impression
destination image
online opinion
online destination image
classification
text mining
日期 2019
上傳時間 5-Sep-2019 15:45:32 (UTC+8)
摘要 對於旅遊業來說，了解旅客的行為非常的重要。資訊需求是使用者在遇到問題時，透過了解問題本身後所提出如何解決該問題的需求。由於眾多旅遊網站並沒有針對使用者提供合適的資訊，因此其內容通常很難滿足使用者的資訊需求。本研究的目的是想要發現台灣旅客的對於景點的資訊需求與其景點印象以及線上景點形象之間的關係。除了利用傳統的問卷調查方法之外，本研究還利用文字探勘技術分析線上景點評論將線上景點進行分類，並與問卷調查的結果進行比較。本研究利用正規化收尋引擎指標(NDCG)來計算使用者排序的相似度，研究結果指出 (1) 如果網站提供足夠的資訊來滿足使用者的資訊需求，可以加深使用者對於景點的印象。同時也發現使用者對相同類型的景點有相似的景點印象。 (2) 使用者在流覽整體旅遊網站時的資訊需求跟流覽特定景點的資訊需求相似 (3) 對於某些景點來說，其線上景點形象跟景點印象的相似度及線上景點形象跟使用者的資訊需求的相似度呈現相反的情形。本研究結果將能幫助政府或者是旅遊業者，藉以提供不同的資訊來滿足使用者的資訊需求，並且令使用者對於景點有更深刻的印象。
Recognizing tourists’ behaviour is crucial in tourism. Information need reflect individual’s understanding of their information problem and the propose their need. Websites content is often hard to meet users’ information needs due to mismatched information. The purpose of this study is to discover the relationship between tourists’ information needs, destination impression and online destination image in Taiwan. Apart from the traditional questionnaire approach, this study adopts text-mining techniques to classify online opinion from Tripadvisor and compare to the results of questionnaires. This study uses normalized discounted cumulative gain (NDCG) to calculate the similarity of users’ preference ranking. The result shows that (1) If a website provides sufficient information to fulfill users’ information needs, it can increase users’ impression of the destination. Meanwhile, users have similar impression of the same type of destinations. (2) Tourists’ general information needs are similar to their information needs of a particular destination. (3) The relationships between online opinion and impression and between online opinion and information needs of a destination are opposite. The result of this study can help travel agents or the government to provide different information to satisfy tourists’’ information needs and promote the impression of a destination.
參考文獻 Agichtein, E. (2008). Finding the right facts in the crowd : Factoid question answering over social media. In Proceedings of the 17th international conference on World Wide Web (pp. 467–476).
Baloglu, S., &Mccleary, K. W. (1999). A model of destination image. Annals of Tourism Research, 26(4), 868–897.
Beerli, A., &Martı, J. D. (2004). Factors influencing destination image. Annals of Tourism Research, 31(3), 657–681.
Chang, Y. C., Ku, C. H., &Chen, C. H. (2017). Social media analytics: Extracting and visualizing Hilton hotel ratings and reviews from TripAdvisor. International Journal of Information Management.
Chen, C., &Tsai, D. (2007). How destination image and evaluative factors affect behavioral intentions ? Tourism Management, 28(4), 1115–1122.
Chen, P.-J., &Kerstetter, D. L. (1999). International students’ image of rural pennsylvania as a travel destination. Journal of Travel Research, 37(3), 256–266.
Chi, C. G.-Q. H. Q. (2008). Examining the structural relationships of destination image , tourist satisfaction and destination loyalty : An integrated approach. Tourism Management, 29(4), 624–636.
Chi, E. H., Pirolli, P., Chen, K., &Pitkow, J. (2001). Using information scent to model user information needs and actions on the web. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 490–497).
Choi, W. M., Chan, A., &Wu, J. (1999). A qualitative and quantitative assessment of Hong Kong’s image as a tourist destination. Tourism Management, 20(3), 361–365.
Crompton, J. L. (1979). An assessment of the image of Mexico as geographical location upon that image. Journal of Travel Research, 17(4), 18–23.
Dadgostar, B., &Isotalo, R. M. (1992). Factors affecting time spent by near-home tourists in city destinations. Journal of Travel Research, 31(2), 34–39.
Echtner, C. M., &Ritchie, J. R. B. (1993). The Measurement of Destination Image: An Empirical Assessment. Journal of Travel Research, 31(4), 3–13.
Eichhorn, V. (2008). Enabling access to toruism through information schemes? Annals of Tourism Research, 35(1), 189–210.
Fakeye, P. C., &Crompton, J. L. (1991). Image differences between prospective , first-time , and repeat visitors to the lower rio grande valley. Journal of Travel Research, 30(2), 10–16.
Fornell, C., &David F, L. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics., 382–388.
Fornell, C., &Larcker., D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics.
Fotis, J., Buhalis, D., &Rossides, N. (2012). Social media use and impact during the holiday travel planning process. Springer-Verlag.
George, D. (2011). SPSS for windows step by step: A simple study guide and reference.
Giachanou, A., &Crestani, F. (2016). Like it or not: A survey of Twitter sentiment analysis methods. ACM Computing Surveys (CSUR), 49(2), 28.
Guo, Y., Barnes, S. J., &Jia, Q. (2017). Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent dirichlet allocation. Tourism Management, 59, 467–483.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., &Tatham, R. L. (2009). Análise multivariada de dados.
He, W., Zha, S., &Li, L. (2013). Social media competitive analysis and text mining: A case study in the pizza industry. International Journal of Information Management, 33(3), 464–472.
Hofstede, G. (n.d.). Culture’s consequences: Comparing values, behaviors, institutions, and organizations across nations. In 1980.
Holsapple, C., Hsiao, S.-H., &Pakath, R. (2014). Business social media analytics: Definition, benefits, and challenges. 20th Americas Conference on Information Systems, AMCIS 2014, (2010), 1–12.
Hunt, J. D. (1975). Image as a Factor in Tourism Development. Journal of Travel Research, 13(3), 1–7.
Inversini, A., &Dimitrios, B. (2009). Information convergence in the long tail: The case of tourism destination information. Information and Communication Technologies in Tourism, 381–392.
Järvelin, K., &Kekäläinen, J. (2002). Cumulated gain-based evaluation of IR techniques. ACM Transactions on Information Systems (TOIS), 20(4), 422–446.
Kaplan, A. M., &Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59–68.
Kim, H., &Fesenmaier, D. R. (2008). Persuasive Design of Destination Websites : An Analysis of First Impression. Journal of Travel Research, 47(1), 3–13.
Ko, A. J., Deline, R., &Venolia, G. (2007). Information Needs in Collocated Software Development Teams. In Proceedings of the 29th international conference on Software Engineering (pp. 344–353).
Kuzmanovic, B., Schilbach, L., &Lehnhardt, F. (2018). A matter of words: Impact of verbal and nonverbal information on impression formation in high-functioning autism. Research in Autism Spectrum Disorders, 5(1), 604–613.
Lee, C., Lee, Y., &Lee, B. (2005). Korea’s destination image formed by the 2002 World Cup. Annals of Tourism Research, 32(4), 839–858.
Lee, C. S., Goh, D. H.-L., Chua, A. Y. K., &Ang, R. P. (2010). Indagator : Investigating perceived gratifications of an application that blends mobile content sharing with gameplay. Journal of the American Society for Information Science and Technology, 61(6), 1244–1257.
Lee, G., &Lee, C. K. (2009). Cross-cultural comparison of the image of Guam perceived by Korean and Japanese leisure travelers: Importance-performance analysis. Tourism Management, 30(6), 922–931.
Line, M. B. (1974). Draft definitions: information and library needs, wants, demands and uses. In Aslib proceedings (p. 87).
Liu, Z., &Park, S. (2015). What makes a useful online review? Implication for travel product websites. Tourism Management, 47, 140–151.
Llodrà-Riera, I., Martínez-Ruiz, M. P., Jiménez-Zarco, A. I., &Izquierdo-Yusta, A. (2015). A multidimensional analysis of the information sources construct and its relevance for destination image formation. Tourism Management, 48, 319–328.
Lu, W., &Stepchenkova, S. (2014). User-generated content as a research mode in tourism and hospitality applications: Topics, methods, and software. Journal of Hospitality Marketing & Management, 24(2), 119–154.
Mankad, S., &Goh, J. (2016). Understanding online hotel reviews through automated text analysis. Service Science, 8(2), 124–138.
Moghavvemi, S., Ormond, M., Musa, G., Ruhana, C., Isa, M., Thirumoorthi, T., …Chandy, C. (2017). Connecting with prospective medical tourists online: A cross-sectional analysis of private hospital websites promoting medical tourism in India, Malaysia and Thailand. Tourism Management, 58, 154–163.
Money, R. B., &Crotts, J. C. (2003). The effect of uncertainty avoidance on information search , planning , and purchases of international travel vacations. Tourism Management, 24(2), 191–202.
Moore-West, M., Northup, D., Skipper, B., & Teaf, D. (1984). Information-seeking behavior among physicians practicing in urban and nonurban areas. In Research in medical education: proceedings of the... annual Conference. Conference on Research in Medical Education. (pp. 237–242).
Nadeau, J., Heslop, L., &Luk, P. (2008). Destination in a country image context. Annals of Tourism Research, 35(1), 84–106.
Noar, S. M. (2003). The role of structural equation modeling in scale development. Structural Equation Modeling, 10(4), 622–647.
Pyo, S. (2005). Knowledge map for tourist destinations—needs and implications. Tourism Management, 26(4), 583–594.
Riley, R. W., &Doren, C. S.Van. (1992). Movies as tourism promotion: A"pull" factor in a “push” location. Tourism Management, 13(3), 267–274.
Shoemaker, S., &Lewis, R. C. (1999). Customer loyalty : The future of hospitality marketing. International Journal of Hospitality Management, 18(4), 345–370.
Taylor, R. S. (1968). Question-Negotiation and information seeking in libraries, 178–194.
Vlachos, G. (2012). Online travel statistics.
Wong, C. U. I., &Qi, S. (2017). Tracking the evolution of a destination’s image by text-mining online reviews - the case of Macau. Tourism Management Perspectives, 23, 19–29.
Xiang, Z., &Gretzel, U. (2010). Role of social media in online travel information search. Tourism Management, 31(2), 179–188.
Zhang, H. yu, Ji, P., Wang, J. qiang, &Chen, X. hong. (2017). A novel decision support model for satisfactory restaurants utilizing social information: A case study of TripAdvisor.com. Tourism Management, 59, 281–297.
描述 碩士
國立政治大學
資訊管理學系
106356032
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0106356032
資料類型 thesis
dc.contributor.advisor 林怡伶zh_TW
dc.contributor.advisor Lin, Yi-Lingen_US
dc.contributor.author (Authors) 鄭吉廷zh_TW
dc.contributor.author (Authors) Cheng, Chi-Tingen_US
dc.creator (作者) 鄭吉廷zh_TW
dc.creator (作者) Cheng, Chi-Tingen_US
dc.date (日期) 2019en_US
dc.date.accessioned 5-Sep-2019 15:45:32 (UTC+8)-
dc.date.available 5-Sep-2019 15:45:32 (UTC+8)-
dc.date.issued (上傳時間) 5-Sep-2019 15:45:32 (UTC+8)-
dc.identifier (Other Identifiers) G0106356032en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/125533-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊管理學系zh_TW
dc.description (描述) 106356032zh_TW
dc.description.abstract (摘要) 對於旅遊業來說，了解旅客的行為非常的重要。資訊需求是使用者在遇到問題時，透過了解問題本身後所提出如何解決該問題的需求。由於眾多旅遊網站並沒有針對使用者提供合適的資訊，因此其內容通常很難滿足使用者的資訊需求。本研究的目的是想要發現台灣旅客的對於景點的資訊需求與其景點印象以及線上景點形象之間的關係。除了利用傳統的問卷調查方法之外，本研究還利用文字探勘技術分析線上景點評論將線上景點進行分類，並與問卷調查的結果進行比較。本研究利用正規化收尋引擎指標(NDCG)來計算使用者排序的相似度，研究結果指出 (1) 如果網站提供足夠的資訊來滿足使用者的資訊需求，可以加深使用者對於景點的印象。同時也發現使用者對相同類型的景點有相似的景點印象。 (2) 使用者在流覽整體旅遊網站時的資訊需求跟流覽特定景點的資訊需求相似 (3) 對於某些景點來說，其線上景點形象跟景點印象的相似度及線上景點形象跟使用者的資訊需求的相似度呈現相反的情形。本研究結果將能幫助政府或者是旅遊業者，藉以提供不同的資訊來滿足使用者的資訊需求，並且令使用者對於景點有更深刻的印象。zh_TW
dc.description.abstract (摘要) Recognizing tourists’ behaviour is crucial in tourism. Information need reflect individual’s understanding of their information problem and the propose their need. Websites content is often hard to meet users’ information needs due to mismatched information. The purpose of this study is to discover the relationship between tourists’ information needs, destination impression and online destination image in Taiwan. Apart from the traditional questionnaire approach, this study adopts text-mining techniques to classify online opinion from Tripadvisor and compare to the results of questionnaires. This study uses normalized discounted cumulative gain (NDCG) to calculate the similarity of users’ preference ranking. The result shows that (1) If a website provides sufficient information to fulfill users’ information needs, it can increase users’ impression of the destination. Meanwhile, users have similar impression of the same type of destinations. (2) Tourists’ general information needs are similar to their information needs of a particular destination. (3) The relationships between online opinion and impression and between online opinion and information needs of a destination are opposite. The result of this study can help travel agents or the government to provide different information to satisfy tourists’’ information needs and promote the impression of a destination.en_US
dc.description.tableofcontents Acknowledgement 6
摘要 7
Abstract 8
CHAPTER 1: INTRODUCTION 1
1.1 Research background and motivation 1
1.2 Research purpose and questions 3
CHAPTER 2: LITERATURE REVIEW 5
2.1 Destination image and impression 5
2.2 Information needs of tourists 6
2.3 Relationship between destination impression and information needs 7
2.4 Social media data analytics in tourism 7
CHAPTER 3: RESEARCH METHODOLOGY 9
3.1 Research design 9
3.2 Target attraction selection 10
3.3 Questionnaire 10
3.3.1 Questionnaire design 10
3.3.2 Measurement 11
3.3.3 Pilot test 13
3.3.4 Sample design and data collection 15
3.4 Text mining 17
3.4.1 Sample design and data collection 17
3.4.2 Construct lexicon 19
3.5 Application and evaluation 20
CHAPTER 4: ANALYSIS AND RESULTS 22
4.1 Questionnaire analysis 22
4.1.1 Reliability analysis and factor analysis 22
4.1.2 Narrative statistical analysis 22
4.1.3 Target destination pre-impression and post impression 28
4.1.3.1 Friedman test and Bonferroni correction 28
4.1.3.2 Pre- and Post- impression Anova analysis 33
4.1.4 Target destination pre and post- impression among destination types 33
4.1.5 Similarity between information needs and general information needs of the target destination 34
4.1.6 Similarity between impression and information needs of the target destination 35
4.2 Review analysis by text mining 36
4.3 Integrated analysis 37
4.3.1 Similarity between impression and online opinion of the target destination 37
4.3.2 Similarity between information needs and online opinion of the target destination 38
CAPTURE 5 DISCUSSIONS 40
CHAPTER 6 CONCLUSION 46
6.1 Summary 46
6.2 Contribution 46
6.3 Limitations and implications of future research 47
REFERENCE 49
APPENDIX A: COMPLETE QUESTIONNAIRE (CHINESE VERSION) 54		zh_TW
dc.format.extent 1617639 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0106356032en_US
dc.subject (關鍵詞) 資訊需求zh_TW
dc.subject (關鍵詞) 景點印象zh_TW
dc.subject (關鍵詞) 景點形象zh_TW
dc.subject (關鍵詞) 線上評論zh_TW
dc.subject (關鍵詞) 線上景點形象zh_TW
dc.subject (關鍵詞) 分類法zh_TW
dc.subject (關鍵詞) 文字探勘zh_TW
dc.subject (關鍵詞) Information needsen_US
dc.subject (關鍵詞) destination impressionen_US
dc.subject (關鍵詞) destination imageen_US
dc.subject (關鍵詞) online opinionen_US
dc.subject (關鍵詞) online destination imageen_US
dc.subject (關鍵詞) classificationen_US
dc.subject (關鍵詞) text miningen_US
dc.title (題名) 藉由線上景點形象了解旅遊者的資訊需求與景點印象zh_TW
dc.title (題名) Knowing tourists’ information needs and destination impression through online destination imageen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Agichtein, E. (2008). Finding the right facts in the crowd : Factoid question answering over social media. In Proceedings of the 17th international conference on World Wide Web (pp. 467–476).
Baloglu, S., &Mccleary, K. W. (1999). A model of destination image. Annals of Tourism Research, 26(4), 868–897.
Beerli, A., &Martı, J. D. (2004). Factors influencing destination image. Annals of Tourism Research, 31(3), 657–681.
Chang, Y. C., Ku, C. H., &Chen, C. H. (2017). Social media analytics: Extracting and visualizing Hilton hotel ratings and reviews from TripAdvisor. International Journal of Information Management.
Chen, C., &Tsai, D. (2007). How destination image and evaluative factors affect behavioral intentions ? Tourism Management, 28(4), 1115–1122.
Chen, P.-J., &Kerstetter, D. L. (1999). International students’ image of rural pennsylvania as a travel destination. Journal of Travel Research, 37(3), 256–266.
Chi, C. G.-Q. H. Q. (2008). Examining the structural relationships of destination image , tourist satisfaction and destination loyalty : An integrated approach. Tourism Management, 29(4), 624–636.
Chi, E. H., Pirolli, P., Chen, K., &Pitkow, J. (2001). Using information scent to model user information needs and actions on the web. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 490–497).
Choi, W. M., Chan, A., &Wu, J. (1999). A qualitative and quantitative assessment of Hong Kong’s image as a tourist destination. Tourism Management, 20(3), 361–365.
Crompton, J. L. (1979). An assessment of the image of Mexico as geographical location upon that image. Journal of Travel Research, 17(4), 18–23.
Dadgostar, B., &Isotalo, R. M. (1992). Factors affecting time spent by near-home tourists in city destinations. Journal of Travel Research, 31(2), 34–39.
Echtner, C. M., &Ritchie, J. R. B. (1993). The Measurement of Destination Image: An Empirical Assessment. Journal of Travel Research, 31(4), 3–13.
Eichhorn, V. (2008). Enabling access to toruism through information schemes? Annals of Tourism Research, 35(1), 189–210.
Fakeye, P. C., &Crompton, J. L. (1991). Image differences between prospective , first-time , and repeat visitors to the lower rio grande valley. Journal of Travel Research, 30(2), 10–16.
Fornell, C., &David F, L. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics., 382–388.
Fornell, C., &Larcker., D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics.
Fotis, J., Buhalis, D., &Rossides, N. (2012). Social media use and impact during the holiday travel planning process. Springer-Verlag.
George, D. (2011). SPSS for windows step by step: A simple study guide and reference.
Giachanou, A., &Crestani, F. (2016). Like it or not: A survey of Twitter sentiment analysis methods. ACM Computing Surveys (CSUR), 49(2), 28.
Guo, Y., Barnes, S. J., &Jia, Q. (2017). Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent dirichlet allocation. Tourism Management, 59, 467–483.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., &Tatham, R. L. (2009). Análise multivariada de dados.
He, W., Zha, S., &Li, L. (2013). Social media competitive analysis and text mining: A case study in the pizza industry. International Journal of Information Management, 33(3), 464–472.
Hofstede, G. (n.d.). Culture’s consequences: Comparing values, behaviors, institutions, and organizations across nations. In 1980.
Holsapple, C., Hsiao, S.-H., &Pakath, R. (2014). Business social media analytics: Definition, benefits, and challenges. 20th Americas Conference on Information Systems, AMCIS 2014, (2010), 1–12.
Hunt, J. D. (1975). Image as a Factor in Tourism Development. Journal of Travel Research, 13(3), 1–7.
Inversini, A., &Dimitrios, B. (2009). Information convergence in the long tail: The case of tourism destination information. Information and Communication Technologies in Tourism, 381–392.
Järvelin, K., &Kekäläinen, J. (2002). Cumulated gain-based evaluation of IR techniques. ACM Transactions on Information Systems (TOIS), 20(4), 422–446.
Kaplan, A. M., &Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59–68.
Kim, H., &Fesenmaier, D. R. (2008). Persuasive Design of Destination Websites : An Analysis of First Impression. Journal of Travel Research, 47(1), 3–13.
Ko, A. J., Deline, R., &Venolia, G. (2007). Information Needs in Collocated Software Development Teams. In Proceedings of the 29th international conference on Software Engineering (pp. 344–353).
Kuzmanovic, B., Schilbach, L., &Lehnhardt, F. (2018). A matter of words: Impact of verbal and nonverbal information on impression formation in high-functioning autism. Research in Autism Spectrum Disorders, 5(1), 604–613.
Lee, C., Lee, Y., &Lee, B. (2005). Korea’s destination image formed by the 2002 World Cup. Annals of Tourism Research, 32(4), 839–858.
Lee, C. S., Goh, D. H.-L., Chua, A. Y. K., &Ang, R. P. (2010). Indagator : Investigating perceived gratifications of an application that blends mobile content sharing with gameplay. Journal of the American Society for Information Science and Technology, 61(6), 1244–1257.
Lee, G., &Lee, C. K. (2009). Cross-cultural comparison of the image of Guam perceived by Korean and Japanese leisure travelers: Importance-performance analysis. Tourism Management, 30(6), 922–931.
Line, M. B. (1974). Draft definitions: information and library needs, wants, demands and uses. In Aslib proceedings (p. 87).
Liu, Z., &Park, S. (2015). What makes a useful online review? Implication for travel product websites. Tourism Management, 47, 140–151.
Llodrà-Riera, I., Martínez-Ruiz, M. P., Jiménez-Zarco, A. I., &Izquierdo-Yusta, A. (2015). A multidimensional analysis of the information sources construct and its relevance for destination image formation. Tourism Management, 48, 319–328.
Lu, W., &Stepchenkova, S. (2014). User-generated content as a research mode in tourism and hospitality applications: Topics, methods, and software. Journal of Hospitality Marketing & Management, 24(2), 119–154.
Mankad, S., &Goh, J. (2016). Understanding online hotel reviews through automated text analysis. Service Science, 8(2), 124–138.
Moghavvemi, S., Ormond, M., Musa, G., Ruhana, C., Isa, M., Thirumoorthi, T., …Chandy, C. (2017). Connecting with prospective medical tourists online: A cross-sectional analysis of private hospital websites promoting medical tourism in India, Malaysia and Thailand. Tourism Management, 58, 154–163.
Money, R. B., &Crotts, J. C. (2003). The effect of uncertainty avoidance on information search , planning , and purchases of international travel vacations. Tourism Management, 24(2), 191–202.
Moore-West, M., Northup, D., Skipper, B., & Teaf, D. (1984). Information-seeking behavior among physicians practicing in urban and nonurban areas. In Research in medical education: proceedings of the... annual Conference. Conference on Research in Medical Education. (pp. 237–242).
Nadeau, J., Heslop, L., &Luk, P. (2008). Destination in a country image context. Annals of Tourism Research, 35(1), 84–106.
Noar, S. M. (2003). The role of structural equation modeling in scale development. Structural Equation Modeling, 10(4), 622–647.
Pyo, S. (2005). Knowledge map for tourist destinations—needs and implications. Tourism Management, 26(4), 583–594.
Riley, R. W., &Doren, C. S.Van. (1992). Movies as tourism promotion: A"pull" factor in a “push” location. Tourism Management, 13(3), 267–274.
Shoemaker, S., &Lewis, R. C. (1999). Customer loyalty : The future of hospitality marketing. International Journal of Hospitality Management, 18(4), 345–370.
Taylor, R. S. (1968). Question-Negotiation and information seeking in libraries, 178–194.
Vlachos, G. (2012). Online travel statistics.
Wong, C. U. I., &Qi, S. (2017). Tracking the evolution of a destination’s image by text-mining online reviews - the case of Macau. Tourism Management Perspectives, 23, 19–29.
Xiang, Z., &Gretzel, U. (2010). Role of social media in online travel information search. Tourism Management, 31(2), 179–188.
Zhang, H. yu, Ji, P., Wang, J. qiang, &Chen, X. hong. (2017). A novel decision support model for satisfactory restaurants utilizing social information: A case study of TripAdvisor.com. Tourism Management, 59, 281–297.		zh_TW
dc.identifier.doi (DOI) 10.6814/NCCU201901141en_US