How to cite this paper
Hermawan, D. (2022). The effects of web quality, perceived benefits, security and data privacy on behavioral intention and e-WOM of online travel agencies.International Journal of Data and Network Science, 6(3), 1005-1012.
Refrences
Al-Debei, M. M., Akroush, M. N., & Ashouri, M. I. (2015). Consumer attitudes towards online shopping: the effects of trust, perceived benefits, and perceived web quality. Internet Research, 25(5), 707-733.
Avery, P. (2009). Future Directions OECD 2009 E-commerce conference and possible next steps. OECD/ICPEN joint meeting Paris, 1 April 2009, OECD Secretariat.
Balaji, M. S., Khong, K. W., & Chong, A. Y. L. (2016). Determinants of negative word-of-mouth communication using social networking sites. Information & Management, 53(4), 528-540.
Bavarsad, B., Rahimi, F., & Mennatyan, M. A. (2013). A Study of the Effects of Website’s Perceived Features on the In-tention to Use E-shopping. World Applied Programming, 3(6), 252-263.
Calisir, F., Altin Gumussoy, C., Bayraktaroglu, A. E., & Karaali, D. (2014). Predicting the intention to use a web‐based learning system: Perceived content quality, anxiety, perceived system quality, image, and the technology acceptance model. Human Factors and Ergonomics in Manufacturing & Service Industries, 24(5), 515-531.
Chang, K. C., Chen, M. C., Hsu, C. L., & Kuo, N. T. (2012). Integrating loss aversion into a technology acceptance model to assess the relationship between website quality and website user's behavioural intentions. Total Quality Manage-ment & Business Excellence, 23(7-8), 913-930.
Chatterjee, S. (2020). Factors Impacting Behavioral Intention of Users to Adopt IoT In India: From Security and Privacy Perspective. International Journal of Information Security and Privacy (IJISP), 14(4), 92-112.
Chen, Y. C., Shang, R. A., & Li, M. J. (2014). The effects of perceived relevance of travel blogs’ content on the behavioral intention to visit a tourist destination. Computers in Human Behavior, 30, 787-799.
Cheung, C. M., Lee, M. K., & Thadani, D. R. (2009, September). The impact of positive electronic word-of-mouth on con-sumer online purchasing decision. In World Summit on Knowledge Society (pp. 501-510). Springer, Berlin, Heidelberg.
Cho, E., & Youn-Kyung, K. (2012). The effects of website designs, self-congruity, and flow on behavioral inten-tion. International journal of Design, 6(2).
Choi, J., Lee, A., & Ok, C. (2013). The effects of consumers' perceived risk and benefit on attitude and behavioral inten-tion: A study of street food. Journal of Travel & Tourism Marketing, 30(3), 222-237.
Constantinides, E., Lorenzo Romero, C., & Gomez, M. A. (2010). Effects of web experience on consumer choice: a multi-cultural approach. Internet research, 20(2), 188-209.
Dabholkar, P. A., & Bagozzi, R. P. (2002). An attitudinal model of technology-based self-service: moderating effects of consumer traits and situational factors. Journal of the academy of marketing science, 30(3), 184-201.
Dinev, T., & Hu, Q. (2007). The centrality of awareness in the formation of user behavioral intention toward protective in-formation technologies. Journal of the Association for Information Systems, 8(7), 23.
Erkan, I., & Evans, C. (2018). Social media or shopping websites? The influence of eWOM on consumers’ online purchase intentions. Journal of Marketing Communications, 24(6), 617-632.
Faqih, K. M. (2016). An empirical analysis of factors predicting the behavioral intention to adopt Internet shopping tech-nology among non-shoppers in a developing country context: Does gender matter?. Journal of Retailing and Consumer Services, 30, 140-164.
Forsythe, S., Liu, C., Shannon, D., & Gardner, L. C. (2006). Development of a scale to measure the perceived benefits and risks of online shopping. Journal of interactive marketing, 20(2), 55-75.
Ha, S., & Stoel, L. (2009). Consumer e-shopping acceptance: Antecedents in a technology acceptance model. Journal of business research, 62(5), 565-571.
Handi, H., Hendratono, T., Purwanto, E., & Ihalauw, J. J. (2018). The effect of E-WOM and perceived value on the pur-chase decision of foods by using the Go-Food application as mediated by trust. Quality Innovation Prosperity, 22(2), 112-127.
Hussain, S., Guangju, W., Jafar, R. M. S., Ilyas, Z., Mustafa, G., & Jianzhou, Y. (2018). Consumers' online information adoption behavior: Motives and antecedents of electronic word of mouth communications. Computers in Human Be-havior, 80, 22-32.
Jalilvand, M. R., & Heidari, A. (2017). Comparing face-to-face and electronic word-of-mouth in destination image for-mation. Information Technology & People.
Jeon, H., Jang, J., & Barrett, E. B. (2017). Linking website interactivity to consumer behavioral intention in an online travel community: the mediating role of utilitarian value and online trust. Journal of Quality Assurance in Hospitality & Tourism, 18(2), 125-148.
Jeon, M. M., & Jeong, M. (2017). Customers’ perceived website service quality and its effects on e-loyalty. International Journal of Contemporary Hospitality Management, 29(1), 438-457
Kim, J. J., Hwang, J., & Kim, I. (2020). Congruent charitable cause sponsorship effect: Air travelers’ perceived benefits, satisfaction and behavioral intention. Journal of Hospitality and Tourism Management, 42, 190-198.
Kitcharoen, K. (2019). The Effect of E-Word of Mouth (E-WOM) on Various Factors Influencing Customers’ Hotel Book-ing Intention. ABAC ODI Journal Vision. Action. Outcome, 6(1), 62.
Kusumatrisna, A.L., Rozama, N.A., Syakilah A., …., & Sutarsih, T. (2020). Statistik E-Commerce 2020. Badan Pusat Statistik/BPS-Statistics Indonesia.
Lee, J. D., & Heo, C. M. (2020). The Effect of Technology Acceptance Factors on Behavioral Intention for Agricultural Drone Service by Mediating Effect of Perceived Benefits. Journal of Digital Convergence, 18(8), 151-167.
Lee, M., Lee, S. A., Jeong, M., & Oh, H. (2020). Quality of virtual reality and its impacts on behavioral inten-tion. International Journal of Hospitality Management, 90, 102595.
Liu, C., Marchewka, J. T., Lu, J., & Yu, C. S. (2005). Beyond concern—a privacy-trust-behavioral intention model of elec-tronic commerce. Information & Management, 42(2), 289-304.
Luarn, P., & Lin, H. H. (2005). Toward an understanding of the behavioral intention to use mobile banking. Computers in human behavior, 21(6), 873-891.
McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). The impact of initial consumer trust on intentions to transact with a web site: a trust building model. The journal of strategic information systems, 11(3-4), 297-323.
Nugroho, A. H., Bakar, A., & Ali, A. (2017). Analysis of technology acceptance model: Case study of Trave-loka. Arthatama, 1(1), 27-34.
Park, N., & Kim, Y. (2020). The impact of social networks and privacy on electronic word-of-mouth in Facebook: Explor-ing gender differences. International Journal of Communication, 14, 24.
Pourabedin, Z., & Migin, M. W. (2015). Hotel experience and positive electronic word of mouth (e-WOM). International Business Management, 9(4), 596-600.
Punyatoya, P. (2019). Effects of cognitive and affective trust on online customer behavior. Marketing Intelligence & Planning.
Rahmawanti, W. (2017). Pengaruh Kualitas Website E-Commerce Terhadap Kepuasan Pelanggan Dengan Menggunakan Webqual 4.0. Jurnal Ilmiah Informatika Komputer, 21(2).
Roca, J. C., García, J. J., & De La Vega, J. J. (2009). The importance of perceived trust, security and privacy in online trading systems. Information Management & Computer Security, 17(2), 96-113.
Uslu, A., & Karabulut, A. N. (2018). Touristic destinations'perceived risk and perceived value as indicators of e-wom and revisit intentions. International Journal of Contemporary Economics & Administrative Sciences, 8(2).
Vijayasarathy, L. R. (2004). Predicting consumer intentions to use on-line shopping: the case for an augmented technolo-gy acceptance model. Information & management, 41(6), 747-762.
Wibowo, L., Widjajanta, B., Fadillah, A., Riswanto, A., Aprianti, V., Widjaja, Y., ... & Romi, M. (2020). Supply chain analysis of hedonic shopping value on behavioral intention creation of multinational footwear company. Uncertain Supply Chain Management, 8(4), 745-752.
Yang, S., & Wang, K. (2009). The influence of information sensitivity compensation on privacy concern and behavioral intention. ACM SIGMIS Database: the Database for Advances in Information Systems, 40(1), 38-51.
Avery, P. (2009). Future Directions OECD 2009 E-commerce conference and possible next steps. OECD/ICPEN joint meeting Paris, 1 April 2009, OECD Secretariat.
Balaji, M. S., Khong, K. W., & Chong, A. Y. L. (2016). Determinants of negative word-of-mouth communication using social networking sites. Information & Management, 53(4), 528-540.
Bavarsad, B., Rahimi, F., & Mennatyan, M. A. (2013). A Study of the Effects of Website’s Perceived Features on the In-tention to Use E-shopping. World Applied Programming, 3(6), 252-263.
Calisir, F., Altin Gumussoy, C., Bayraktaroglu, A. E., & Karaali, D. (2014). Predicting the intention to use a web‐based learning system: Perceived content quality, anxiety, perceived system quality, image, and the technology acceptance model. Human Factors and Ergonomics in Manufacturing & Service Industries, 24(5), 515-531.
Chang, K. C., Chen, M. C., Hsu, C. L., & Kuo, N. T. (2012). Integrating loss aversion into a technology acceptance model to assess the relationship between website quality and website user's behavioural intentions. Total Quality Manage-ment & Business Excellence, 23(7-8), 913-930.
Chatterjee, S. (2020). Factors Impacting Behavioral Intention of Users to Adopt IoT In India: From Security and Privacy Perspective. International Journal of Information Security and Privacy (IJISP), 14(4), 92-112.
Chen, Y. C., Shang, R. A., & Li, M. J. (2014). The effects of perceived relevance of travel blogs’ content on the behavioral intention to visit a tourist destination. Computers in Human Behavior, 30, 787-799.
Cheung, C. M., Lee, M. K., & Thadani, D. R. (2009, September). The impact of positive electronic word-of-mouth on con-sumer online purchasing decision. In World Summit on Knowledge Society (pp. 501-510). Springer, Berlin, Heidelberg.
Cho, E., & Youn-Kyung, K. (2012). The effects of website designs, self-congruity, and flow on behavioral inten-tion. International journal of Design, 6(2).
Choi, J., Lee, A., & Ok, C. (2013). The effects of consumers' perceived risk and benefit on attitude and behavioral inten-tion: A study of street food. Journal of Travel & Tourism Marketing, 30(3), 222-237.
Constantinides, E., Lorenzo Romero, C., & Gomez, M. A. (2010). Effects of web experience on consumer choice: a multi-cultural approach. Internet research, 20(2), 188-209.
Dabholkar, P. A., & Bagozzi, R. P. (2002). An attitudinal model of technology-based self-service: moderating effects of consumer traits and situational factors. Journal of the academy of marketing science, 30(3), 184-201.
Dinev, T., & Hu, Q. (2007). The centrality of awareness in the formation of user behavioral intention toward protective in-formation technologies. Journal of the Association for Information Systems, 8(7), 23.
Erkan, I., & Evans, C. (2018). Social media or shopping websites? The influence of eWOM on consumers’ online purchase intentions. Journal of Marketing Communications, 24(6), 617-632.
Faqih, K. M. (2016). An empirical analysis of factors predicting the behavioral intention to adopt Internet shopping tech-nology among non-shoppers in a developing country context: Does gender matter?. Journal of Retailing and Consumer Services, 30, 140-164.
Forsythe, S., Liu, C., Shannon, D., & Gardner, L. C. (2006). Development of a scale to measure the perceived benefits and risks of online shopping. Journal of interactive marketing, 20(2), 55-75.
Ha, S., & Stoel, L. (2009). Consumer e-shopping acceptance: Antecedents in a technology acceptance model. Journal of business research, 62(5), 565-571.
Handi, H., Hendratono, T., Purwanto, E., & Ihalauw, J. J. (2018). The effect of E-WOM and perceived value on the pur-chase decision of foods by using the Go-Food application as mediated by trust. Quality Innovation Prosperity, 22(2), 112-127.
Hussain, S., Guangju, W., Jafar, R. M. S., Ilyas, Z., Mustafa, G., & Jianzhou, Y. (2018). Consumers' online information adoption behavior: Motives and antecedents of electronic word of mouth communications. Computers in Human Be-havior, 80, 22-32.
Jalilvand, M. R., & Heidari, A. (2017). Comparing face-to-face and electronic word-of-mouth in destination image for-mation. Information Technology & People.
Jeon, H., Jang, J., & Barrett, E. B. (2017). Linking website interactivity to consumer behavioral intention in an online travel community: the mediating role of utilitarian value and online trust. Journal of Quality Assurance in Hospitality & Tourism, 18(2), 125-148.
Jeon, M. M., & Jeong, M. (2017). Customers’ perceived website service quality and its effects on e-loyalty. International Journal of Contemporary Hospitality Management, 29(1), 438-457
Kim, J. J., Hwang, J., & Kim, I. (2020). Congruent charitable cause sponsorship effect: Air travelers’ perceived benefits, satisfaction and behavioral intention. Journal of Hospitality and Tourism Management, 42, 190-198.
Kitcharoen, K. (2019). The Effect of E-Word of Mouth (E-WOM) on Various Factors Influencing Customers’ Hotel Book-ing Intention. ABAC ODI Journal Vision. Action. Outcome, 6(1), 62.
Kusumatrisna, A.L., Rozama, N.A., Syakilah A., …., & Sutarsih, T. (2020). Statistik E-Commerce 2020. Badan Pusat Statistik/BPS-Statistics Indonesia.
Lee, J. D., & Heo, C. M. (2020). The Effect of Technology Acceptance Factors on Behavioral Intention for Agricultural Drone Service by Mediating Effect of Perceived Benefits. Journal of Digital Convergence, 18(8), 151-167.
Lee, M., Lee, S. A., Jeong, M., & Oh, H. (2020). Quality of virtual reality and its impacts on behavioral inten-tion. International Journal of Hospitality Management, 90, 102595.
Liu, C., Marchewka, J. T., Lu, J., & Yu, C. S. (2005). Beyond concern—a privacy-trust-behavioral intention model of elec-tronic commerce. Information & Management, 42(2), 289-304.
Luarn, P., & Lin, H. H. (2005). Toward an understanding of the behavioral intention to use mobile banking. Computers in human behavior, 21(6), 873-891.
McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). The impact of initial consumer trust on intentions to transact with a web site: a trust building model. The journal of strategic information systems, 11(3-4), 297-323.
Nugroho, A. H., Bakar, A., & Ali, A. (2017). Analysis of technology acceptance model: Case study of Trave-loka. Arthatama, 1(1), 27-34.
Park, N., & Kim, Y. (2020). The impact of social networks and privacy on electronic word-of-mouth in Facebook: Explor-ing gender differences. International Journal of Communication, 14, 24.
Pourabedin, Z., & Migin, M. W. (2015). Hotel experience and positive electronic word of mouth (e-WOM). International Business Management, 9(4), 596-600.
Punyatoya, P. (2019). Effects of cognitive and affective trust on online customer behavior. Marketing Intelligence & Planning.
Rahmawanti, W. (2017). Pengaruh Kualitas Website E-Commerce Terhadap Kepuasan Pelanggan Dengan Menggunakan Webqual 4.0. Jurnal Ilmiah Informatika Komputer, 21(2).
Roca, J. C., García, J. J., & De La Vega, J. J. (2009). The importance of perceived trust, security and privacy in online trading systems. Information Management & Computer Security, 17(2), 96-113.
Uslu, A., & Karabulut, A. N. (2018). Touristic destinations'perceived risk and perceived value as indicators of e-wom and revisit intentions. International Journal of Contemporary Economics & Administrative Sciences, 8(2).
Vijayasarathy, L. R. (2004). Predicting consumer intentions to use on-line shopping: the case for an augmented technolo-gy acceptance model. Information & management, 41(6), 747-762.
Wibowo, L., Widjajanta, B., Fadillah, A., Riswanto, A., Aprianti, V., Widjaja, Y., ... & Romi, M. (2020). Supply chain analysis of hedonic shopping value on behavioral intention creation of multinational footwear company. Uncertain Supply Chain Management, 8(4), 745-752.
Yang, S., & Wang, K. (2009). The influence of information sensitivity compensation on privacy concern and behavioral intention. ACM SIGMIS Database: the Database for Advances in Information Systems, 40(1), 38-51.