目前越南由於網站訂房的便利性、優惠的房價與縮短訂房時間等因素，引起熱愛網站訂房人數逐漸增加。但是，關於在越南訂房者的預訂需求以及於網站訂房的使用意圖之影響因素，尚未受到研究的關注。因此，研究者將進行探討越南訂房者決定在網站訂房的各種影響因素。本研究為了確認訂房者在網站計劃訂房的行為，通過訂房者在訂房時考量的各種核心要素（態度、效益性認識與使用便利性）及加上安全性、知覺風險、自我效能、網站品質等要素，試著了解訂房人對於科技接受模式（TAM）。為了證明這個模式，研究者依據目前多數訂房者正在使用的訂房網站設計出問卷調查。本問卷調查總共調查414 個訂房者，而這些問卷填寫者皆在越南使用過訂房網站訂房。研究結果表示，訂房者決定在越南使用訂房網站訂房的考量因素包括：網站品質、安全性、自我效能、知覺風險、知覺有用性、知覺易用性等因素。本研究結果期待能提供給關注於越南市場經營、文化研究及越南人訂房行為，之參考。其次，關於在越南旅遊網站訂房的各種影響因素，也提供更加全面的考量因素。此外，研究結果得出訂房人對訂房網站的信任程度，影響其對一網站的知覺風險、知覺有用性，但不影響其對知覺有用性。最後，本研究將彌補目前越南訂房網站所缺乏的考量因素，也啟發和提供未來研究的其他方向。

The number of people who prefer to book hotel online is increasing when considering the convenience, cost and time-saving. However, comprehensive studies about customers’ intentions and online hotel reservations are limited in Vietnam. Therefore, this study intends to investigate the determinants of consumers’ intentions toward online hotel reservations in Vietnam.
This study attempts to test the applicability of the technology acceptance model (TAM) using its core constructs (attitude, perceived usefulness, and perceived ease of use), with the addition of the trust, perceived risk, self-efficacy, website quality variable, on the behavioral intention of booking a hotel online. In order to validate the model, a web-based questionnaire was applied and a total of 414 respondents who are travel to Vietnam.
The results found out that the Vietnamese consumer's intention will be affected by the website quality, trust, self-efficacy, perceived risk, perceived usefulness and perceived ease of use. This study also beneficiary not only for the marketers but also researchers to understand the culture and also the consumer behavior of Vietnamese. The findings provide a more comprehensive picture of the attendances factor affecting hotel booking online in Vietnam. Besides, the finding also revealed that trust has a positive effect on perceived risk, perceived ease of use, whereas perceived usefulness did not. The study limitations and implications for the future research are suggested.
Keywords: The Technology Acceptance Model; Trust; Perceived risk; Self-efficacy; Website Quality, Booking intention.

LIST OF TABLES v
LIST OF FIGURES vi
CHAPTER 1: INTRODUCTION 1
1.1 Motivation and Background of Research 1
1.2 Research Gap and Purpose 3
1.3 Research scope and procedure 5
1.3.1 Research scope 5
1.3.2 Research procedure 5
CHAPTER 2: LITERATURE REVIEW 7
2.1 Theoretical background 7
2.1.1 The Technology Acceptance Model 7
2.1.2 Attitude 9
2.1.3 Behavioral Intention 10
2.1.4 Perceived Risk 11
2.1.5 Trust 12
2.1.6 Website quality 13
2.1.7 Self-efficacy 13
2.2 Hypothesis development and conceptual framework 14
2.2.1 Relationship among website quality, perceived risk, trust, perceived usefulness, and attention 14
2.2.1.1 Relationship among website quality, trust and perceived usefulness 14
2.2.1.3 Relationship between trust and perceived risk 17
2.2.1.4 Relationship among perceived risk, attitude and online hotel booking intention 18
2.2.2 Relationship among self-efficacy, trust and perceived ease of use 19
2.2.2.1 Self-efficacy and trust 19
2.2.2.2 Self-efficacy and perceived ease of use 20
2.2.3 Online hotel booking intention based on The Technology Acceptance Model 21
2.2.4 Research Framework 23
CHAPTER 3: METHODOLOGY 27
3.1 Sampling method and procedure 27
3.2 Measurement development 28
3.3. Pilot test 32
3.4 Statistical methodology 34
3.4.1 Descriptive statistical analysis 35
3.4.2 Reliability and Validity analysis 35
3.4.3 SEM and hypothesis testing 36
CHAPTER 4: DATA ANALYSIS AND RESULTS 38
4.1. Descriptive statistical analysis 38
4.2 Measurement model analyses 39
4.2.1 Reliability 40
4.2.2 Validation 41
4.3 Testing the Structural Model 44
CHAPTER 5: DISCUSSION AND CONCLUSION 50
5.1 Discussion 50
5.2 Conclusion 53
5.3 Implication 54
5.3.1 Theoretical Implications 54
5.3.2 Managerial Implications 55
5.3.3. Limitations of the research 56
REFERENCES 57
APPENDIX 66

Abdullah, D., Jayaraman, K., Shariff, D. N., Bahari, K. A., & Nor, N. M. (2017). The effects of perceived interactivity, perceived ease of use and perceived usefulness on online hotel booking intention: A conceptual framework. International Academic Research Journal of Social Science, 3(1), 16–23.

Adams, D., Nelson, R. R., Todd, P. A. (1992). Perceived usefulness, ease of use, and usage of information technology: a replication. MIS Q. 16 (2), 227–247.
Agag, G. M., & El-Masry, A. A. (2017). Why Do Consumers Trust Online Travel Websites? Drivers and Outcomes of Consumer Trust towards Online Travel Websites. Journal of Travel Research, 56(3).
Agag, G., and A. El-Masry. (2016). “Understanding Consumer Intention to Participate in Online Travel Community and Effects on Consumer Intention to Purchase Travel Online and WOM: An Integration of Innovation Diffusion Theory and TAM with trust.” Computers in Human Behavior. Published online February 18.
Ajzen, I. (2002). Perceived behavioral control, self-efficacy, the locus of control, and the theory of planned behavior. Journal of Applied Social Psychology, 32, 665–683.
Ajzen, I. (2011). The theory of planned behavior: Reactions and reflections. Psychology & Health, 26, 1113–1127.
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice- Hall.
Amaro, S., & Duarte, P. (2013). Online travel purchasing: A literature review. Journal of Travel & Tourism Marketing, 30, 755–785.
Anderson, J. C., & Gerbing, D. (1988). Structural modeling in practice: A review and recommended two-steps approach. Psychological Bulletin, 103(3), 411–423.

Athiyaman, A. (2002). Internet users’ intention to purchase air travel online: An empirical investigation. Marketing Intelligence & Planning, 20(4/5), 234–242.

Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37(2), 122–147.
Bandura, A. (1986). The explanatory and predictive scope of self-efficacy theory. Journal of Social and Clinical Psychology, 4(3), 359–373.
Bandura, A. (2012). On the functional properties of perceived self-efficacy revisited. Journal of Management, 38(1), 9–44.
Bartlett, J., Kotrlik, J., Higgins, C., 2010. Organizational research: determining appropriate sample size in survey research. Inf. Technol. Learn. Perform. J. 19 (1), 43–50.
Bigné, E., Sanz, S., Ruiz, C., & Aldás, J. (2010). Why some internet users don’t buy air tickets online. In U. Gretzel, R. Law, & M. Fuchs (Eds.), Information and communication technologies in tourism 2010 (pp. 209–221). Vienna: Springer.
Bigne, E., Sanz, S., Ruiz, C., Aldas, J., 2010. Why some internet users don’t buy air. In: Gretzel, U., Law, R., Fuchs, M. (Eds.), Information and Communication Technologies in Tourism. Springer, Vienna, Austria, pp. 209–221.
Chen, C., 2006. Identifying significant factors influencing consumer trust in an online travel site. Inform. Technol. Tourism 8 (3/4), 197–214.
Cheng, T.C., Lam, D.Y., Yeung, A.C., 2006. Adoption of internet banking: an empirical study in Hong Kong. Decis. Support Syst. 42 (3), 1558–1572.
David, F.D. (1989), “Perceived usefulness, perceived ease of use, and user acceptance of information technology”, MIS Quarterly, Vol. 13 No. 3, pp. 319-39.
Dean, M., Raats, M. M., & Shepherd, R. (2012). The Role of Self-Identity, Past Behavior, and Their Interaction in Predicting Intention to Purchase Fresh and Processed Organic Food. Journal of Applied Social Psychology, 42(3), 669–688.

El Ansari, O., Roushdy, A., 2013. Factors affecting Egyptian consumers’ intentions for accepting online shopping. J. Am. Acad. Bus. Cambridge 19 (1), 191–201.
Elbeltagi, I., Agag, G., 2015. E-retailing ethics and its impact on customer satisfaction and repurchase intention: a cultural and commitment-trust theory perspective. Internet Res. 26 (1), 1–31.
Escobar-Rodríguez, T., Carvajal-Trujillo, E., 2014. Online purchasing tickets for low-cost carriers an application of the unified theory of acceptance and use of technology (UTAUT) model. Tourism Manage. 43 (August), 70–88.
Fishbein M and Ajzen I (1975) Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading: Addison-Wesley.
George, J. F. (2004). The theory of planned behavior and internet purchasing. Internet Research, 14, 198–212.
Grabner-Kraeuter, S. (2002). The role of consumers’ trust in online shopping. Journal of Business Ethics, 39, 43–50.
Grazioli, S., & Jarvenpaa, S.L. (2000). Perils of internet fraud: An empirical investigation of deception and trust with experienced Internet consumers. IEEE Transactions on Systems, Man, and Cybernetics Part A: Systems and Humans, 30, 395–410.

Hair, J. F., Black, W. C., Babin, H. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Englewood Cliffs, NJ: Prentice Hall.

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2013). A primer on partial least squares structural equation modeling (PLS-SEM). Thousand Oaks, CA: Sage.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. The Journal of Marketing Theory and Practice, 19, 139–152.
Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40, 414–433.

Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20, 277–319.

Hung, K., & Law, R. (2011). An overview of Internet-based surveys in hospitality and tourism journals. Tourism Management, 32(4), 717–724.
Igbaria, M., & Iivari, J. (1995). The effects of self-efficacy on computer usage. Omega, 23(6), 587–605.
Jensen, J. M. (2012). Shopping orientation and online travel shopping: The role of travel experience. International Journal of Tourism Research, 14, 56–70.
Kenneth, B., Scott Long, J., 1992. Tests for structural equation models: an introduction. Social. Methods Res. 21 (November), 123–131.
Khalifa, M., Liu, V., 2007. Online consumer retention: contingent effects of online shopping habit and online shopping experience. Eur. J. Inform. Syst. 16 (6), 780–792.
Kim, D.J., Ferrin, D.L., Rao, H.R., 2008a. A trust-based consumer decision-making model in electronic commerce: the role of trust, perceived risk, and their antecedents. Decis. Support Syst. 44 (2), 544–564.
Kim, H.B., Kim, T., Shin, S.W., 2009a. Modeling roles of subjective norms and eTrust in customers’ acceptance of airline B2C eCommerce websites. Tourism Manage. 30, 266–277.
Kim, J., Fiore, A., Lee, H., 2007. Influence of online store perception, shopping enjoyment, and shopping involvement on consumer patronage behavior towards an online retailer. J. Retailing Consum. Serv. 14, 95–107.
Kim, L.H., Qu, H., Kim, D.J., 2009b. A study of perceived risk and risk reduction of purchasing air-tickets online. J. Travel Tourism Mark. 26 (3), 203–224.
Kim, M.J., Chung, N., Lee, C.K., 2011a. The effect of perceived trust on electronic shopping online for tourism products and services in South Korea. Tourism Manage. 32 (2), 256–265.
Kim, M.J., Chung, N., Lee, C.K., 2011b. The effect of perceived trust on electronic commerce: shopping online for tourism products and services in South Korea. Tourism Manage. 32 (2), 256–265.
Kim, T.G., Lee, J.H., Law, R., 2008b. An empirical examination of the acceptable behavior of hotel front office systems: an extended technology acceptance model. Tourism Manage. 29 (3), 500–513.
Kim, W. G., & Kim, D. J. (2004). Factors affecting online hotel reservation intention between online and non-online customers. International Journal of Hospitality Management, 23(4), 381–395.

Kim, W., Chihyung, O., 2009. The effects of relational benefits on customer perceptions of favorable inequity, affective commitment, and repurchase intention in full-service restaurants. J. Hospitality Tourism Res. 33 (2), 227–244.
Kim, Xu, Y., Gupta, S., 2012. Which is more important in Internet shopping, perceived price or trust? Electron. Com. Res. Appl. 11 (3), 241–252.
Lam, T., & Hsu, C. H. C. (2006). Predicting behavioral intention of choosing a travel destination. Tourism Management, 27(4), 589–599.

Law, R., Leung, R., Buhalis, D., 2009. Information technology applications in hospitality and tourism: a review of publications from 2005 to 2007. J. Travel Tourism Mark. 26 (5/6), 599–623.
Law, R., Wong, J., 2003. Successful factors for a travel website: perceptions of online purchasers in Hong Kong. J. Hospitality Tourism Res. 27 (1), 118–124.
Lee, J., Morrison, A.M., 2010. A comparative study of web site performance. J. Hospitality Tourism Technol. 1 (1), 50–67.
Leonidas, L.C., Samiee, S., Ayko, B., 2014. Antecedents and outcomes of exporter–importer relationship quality: synthesis, meta-analysis, and directions for further research. J. Int. Mark. 22 (2), 21–46.
Liang, H., Saraf, N., Hu, Q., Xue, Y., 2007. Assimilation of enterprise systems: the effect of institutional pressures and the mediating role of top management. MIS Q. 31 (1), 59–87.
Lien, C. H., Wen, M. J., Huang, L. C., & Wu, K. L. (2015). Online hotel booking: The effects of brand image, price, trust and value on purchase intentions. Asia Pacific Management Review, 20(4), 210–218.

Lim, Y. J., Osman, A., Salahuddin, S. N., Romle, A. R., & Abdullah, S. (2016). Factors Influencing Online Shopping Behavior: The Mediating Role of Purchase Intention. Procedia Economics and Finance, 35, 401–410.

Limayem, M., Hirt, S.G., Cheung, C.M., 2007. How habit limits the predictive power of intention: the case of information systems continuance. Manage. Inform. Syst. Q. 31 (4), 705–737.
Lin, H.F., 2007. Predicting consumer intentions to shop online: an empirical test of competing theories. Electron. Com. Res. Appl. 6 (4), 433–442.
Lin, P.-J., Jones, E., & Westwood, S. (2009). Perceived risk and risk-relievers in online travel purchase intentions. Journal of Hospitality Marketing & Management, 18, 782–810
Ong, B. S. (2012). The perceived influence of user reviews in the hospitality industry. Journal of Hospitality Marketing & Management, 21(5): 463–485
Panayides, P. (2013). Coefficient alpha: Interpret with caution. Europe’s Journal of Psychology, 9(4), 687–696.

Ponte, E.B., Carvajal-Trujil, E., Escobar-Rodríguez, T. (2015). Influence of
trust and perceived value on the intention to purchase travel online: integrating the effects of assurance on trust antecedents. Tourism Manage. 47, 286–302.
Samadi, M., & Nejadi, Y. (2009). Saw, S. L., Goh, Y. N., & Isa, S. M. (2015). Exploring consumers’ intention toward online hotel reservations: Insights from Malaysia. Problems and Perspectives in Management. LLC CPC Business Perspectives.

Shim, S., Eastlick, M. A., Lotz, S. L., & Warrington, P. (2001). An online prepurchase intentions model: The role of intention to search. Journal of Retailing, 77(3), 397–416.

Toh, R. S., Raven, P., DeKay, F., Raven, P., & Toh, R. S. (2011). Selling Rooms: Hotels vs. Third-Party Websites. Cornell Hospitality Quarterly, 52(2), 181–189.

Tse, T. S. M. (2013). The Marketing Role of the Internet in Launching a Hotel: The Case of Hotel ICON. Journal of Hospitality Marketing & Management, 22(8), 895–908.

VNS (2017). Foreign websites dominate Vietnam’s online tourism market. http://english.vietnamnet.vn/fms/travel/185824/foreign-websites-dominate-vietnam-s-online-tourism-market.html
Wanida, S. (2014). Factor Driving Consumer Intention in Online Shopping. International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering Vol:8, No:6.
Westland, J.C., 2010. Lower bounds on sample size in structural equation modeling. Electron. Com. Res. Appl. 9 (6), 476–487.
Wilsom, R. H. (2007). Internet Hotel Reservations. The “Terms and Conditions” Trap. Cornell Hotel and Restaurant Administration Quarterly, 48(4), 361–369.

Wong, J., & Law, R. (2005). Analyzing the intention to purchase on hotel websites: A study of travelers to Hong Kong. International Journal of Hospitality Management, 24(3), 311–329.