Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2023, Cilt: 11 Sayı: 4, 476 - 504, 11.12.2023
https://doi.org/10.30519/ahtr.1053634

Öz

Kaynakça

  • Agag, G. M., & El-Masry, A. A. (2017). Why do consumers trust online travel websites? Drivers and outcomes of consumer trust toward online travel websites. Journal of Travel Research, 56(3), 347-369.
  • Agarwal, R., & Karahanna, E. (2000). Time flies when you're having fun: cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665-694.
  • Alsabawy, A. Y., Cater-Steel, A., & Soar, J. (2016). Determinants of perceived usefulness of e-learning systems. Computers in Human Behavior, 64, 843-858.
  • Angst, C. M., & Agarwal, R. (2009). Adoption of electronic health records in the presence of privacy concerns: The elaboration likelihood model and individual persuasion. MIS quarterly, 339-370.
  • Ayeh, J. K., Au, N., & Law, R. (2013). Predicting the intention to use consumer-generated media for travel planning. Tourism Management, 35, 132-143.
  • Bhattacherjee, A., & Sanford, C. (2006). Influence Processes for Information Technology Acceptance: An Elaboration Likelihood Model. MIS Quarterly, 30(4), 805–825.
  • Bollen, K. A., & Davis, W. R. (2009). Causal indicator models: Identification, estimation, and testing. Structural Equation Modeling: A Multidisciplinary Journal, 16(3), 498-522.
  • Brand, D. J. (2016). Automatic Prediction of Comment Quality (Doctoral dissertation, Stellenbosch: Stellenbosch University).
  • Butler, G., & Paris, C. M. (2016). Reaching the end of the unbeaten path? An analysis of Lonely Planet's digital media "requiem". Anatolia, 27(3), 377–388.
  • Byrne, B. M. (2010). Structural Equation Modeling with AMOS: Basic concepts, applications and programming (2nd ed.). New York: Routledge. doi: 10.4324/9781410600219
  • Capriello, A., Mason, P. R., Davis, B., & Crotts, J. C. (2013). Farm tourism experiences in travel reviews: A cross-comparison of three alternative methods for data analysis. Journal of Business Research, 66(6), 778-785.
  • Chan, Y. & Ngai, E. (2011). Conceptualising electronic word of mouth activity. Marketing Intelligence and Planning, 29(5), 488-516.
  • Chen, C. D., & C. S. Ku. (2012). Building Member's Relationship Quality Toward Online Community from the Elaboration Likelihood Model Perspective. Proceedings of the Pacific Asia Conference on Information Systems paper 126, Hochiminh City, Vietnam.
  • Chen, J. S. (1998). The tourists' cognitive decision-making model. The Tourist Review, 53(1), 4-9.
  • Cheung, C. M., & Thadani, D. R. (2012). The impact of electronic word-of-mouth communication: A literature analysis and integrative model. Decision support systems, 54(1), 461-470.
  • Cheung, C.M., Lee, M.K., & Rabjohn, N. (2008). The impact of electronic word-of-mouth: the adoption of online opinions in online customer communities. Internet Research, 18(3), 229-247.
  • Cheung, M. Y., Luo, C., Sia, C. L., & Chen, H. (2009). Credibility of electronic word-of-mouth: Informational and normative determinants of online consumer recommendations. International journal of electronic commerce, 13(4), 9-38.
  • Cheung, R. (2014). The influence of electronic word-of-mouth on information adoption in online customer communities. Global Economic Review, 43(1), 42-57.
  • Chong, A. Y. L., Khong, K. W., Ma, T., McCabe, S., & Wang, Y. (2018). Analyzing key influences of tourists' acceptance of online reviews in travel decisions. Internet Research, 28(3), 564-586. https://doi.org/10.1108/IntR-05-2017-0212
  • Choudhary, P., & Gangotia, A. (2017). Do travel decision-making styles and gender of generation Y have any association with travel information share on social networking sites?. Journal of Hospitality and Tourism Technology, 8(2), 152-167.
  • Chung, N., Han, H., & Koo, C. (2015). Adoption of travel information in user-generated content on social media: the moderating effect of social presence. Behaviour & Information Technology, 34(9), 902-919.
  • Cohn, J. (1988). Statistical power analysis for the behavioral sciences. Lawrence Earlbam Associates, Hillsdale, NJ.
  • Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
  • Dedeoglu, B.B. (2019). Are information quality and source credibility really important for shared content on social media? The moderating role of gender. International Journal of Contemporary Hospitality Management, 31(1), 513-534. https://doi.org/10.1108/IJCHM-10-2017-0691
  • Diamantopoulos, A., & Riefler, P. (2011). Using formative measures in international marketing models: A cautionary tale using consumer animosity as an example. In Measurement and Research Methods in International Marketing (pp. 11-30). Emerald Group Publishing Limited. Bingley.
  • Fang, J., Chen, L., Wang, X., & George, B. (2018). Not all posts are treated equal: An empirical investigation of post replying behavior in an online travel community. Information & Management, 55(7), 890-900.
  • Filieri, R., & McLeay, F. (2014). E-WOM and accommodation: An analysis of the factors that influence travelers' adoption of information from online reviews. Journal of travel research, 53(1), 44-57.
  • Gal-Tzur, A., Bar-Lev, S., & Shiftan, Y. (2020). Using question & answer forums as a platform for improving transport-related information for tourists. Journal of Travel Research, 59(7), 1221-1237.
  • Geisser, S. (1974). A predictive approach to the random effect model. Biometrika, 61(1), 101-107.
  • George, D., & Mallery, P. (2010). SPSS for Windows step by step. A simple study guide and reference (10. ed.). GEN, Boston, MA: Pearson Education, Inc.
  • Gretzel, U., Yoo, K. H., & Purifoy, M. (2007). Online Travel Review Study: Role & Impact of Online Travel Reviews. Laboratory for Intelligent Systems in Tourism, Texas A&M University. LIST 02-07-01.
  • Gvili, Y., & Levy, S. (2016). Antecedents of attitudes toward eWOMcommunication: differences across channels. Internet Research, 26(5), 1030–1051.
  • Hair, J. F., Hult, T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least square structural equation modeling (PLS-SEM). Sage Publications.
  • Hair, J.F., Sarstedt, M., Ringle, C.M., & Gudergan, S.P. (2018). Advanced Issues in Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage, Thousand Oaks, CA.
  • Hair, J.F., Risher, J.J., Sarstedt, M., & Ringle, C.M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203
  • Hajli, N., Wang, Y., & Tajvidi, M. (2018). Travel envy on social networking sites. Annals of Tourism Research, 73, 184–189. https://doi.org/10.1016/j.annals.2018.05.006
  • Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., ... & Calantone, R. J. (2014). Common beliefs and reality about PLS: Comments on Rönkkö and Evermann (2013). Organizational research methods, 17(2), 182-209.
  • Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the academy of marketing science, 43(1), 115-135.
  • Henseler, J., Ringle, C.M., & Sarstedt, M. (2016). Testing measurement invariance of composites using partial least squares. International Marketing Review, 33(3), 405-431.
  • Hu, Y. H., Chen, K., & Lee, P. J. (2017). The effect of user-controllable filters on the prediction of online hotel reviews. Information & Management, 54(6), 728-744.
  • Kim, J. J., Fesenmaier, D. R., & Johnson, S. L. (2013, July). The effect of feedback within social media in tourism experiences. In International conference of design, user experience, and usability (pp. 212-220). Springer, Berlin, Heidelberg.
  • Kim, S., Oh, J. S., & Oh, S. (2007). Best‐answer selection criteria in a social Q&A site from the user‐oriented relevance perspective. Proceedings of the American Society for Information Science and Technology, 44(1), 1-15.
  • Koo, T. K., & Li, M. Y. (2016). A guideline of selecting and reporting intraclass correlation coefficients for reliability research. Journal of chiropractic medicine, 15(2), 155-163.
  • Lee, H., Reid, E., & Kim, W. G. (2014). Understanding knowledge sharing in online travel communities: antecedents and the moderating effects of interaction modes. Journal of Hospitality & Tourism Research, 38(2), 222-242.
  • Li, C. Y. (2013). Persuasive messages on information system acceptance: A theoretical extension of elaboration likelihood model and social influence theory. Computers in Human Behavior, 29(1), 264-275.
  • Li, H. & Liu, Y. (2014). Understanding post-adoption behaviors of e-service users in the context of online travel services. Information and Management, 51(8),1043-1052.
  • Li, L., He, D., & Zhang, C. (2019). Characterizing High-Quality Answers for Different Question Types on Academic Social Q&A Site. In ISSI (pp. 2670-2671).
  • Li, L., Zhang, C., & He, D. (2020). Factors influencing the importance of criteria for judging answer quality on academic social Q&A platforms. Aslib Journal of Information Management, 72(6),887-907.
  • Litvin, S. W., Goldsmith, R. E., & Pan, B. (2008). Electronic word-of-mouth in hospitality and tourism management. Tourism management, 29(3), 458-468.
  • Matute, J., Polo-Redondo, Y., & Utrillas, A. (2016). The influence of EWOM characteristics on online repurchase intention mediating roles of trust and perceived usefulness. Online Information Review, 40(7), 1090-1110.
  • McHugh, M. L. (2012). Interrater reliability: the kappa statistic. Biochemiamedica, 22(3), 276-282.
  • McKinney, V., Yoon, K., & Zahedi, F. M. (2002). The measurement of web-customer satisfaction: An expectation and disconfirmation approach. Information systems research, 13(3), 296-315.
  • Mendes-Filho, L., Mills, A. M., Tan, F. B., & Milne, S. (2018). Empowering the traveler: an examination of the impact of user-generated content on travel planning. Journal of Travel & Tourism Marketing, 35(4), 425-436.
  • Moreno, M. A., Goniu, N., Moreno, P. S., & Diekema, D. (2013). Ethics of social media research: common concerns and practical considerations. Cyberpsychology, behavior, and social networking, 16(9), 708-713.
  • Munar, A. M., & Jacobsen, J. K. S. (2014). Motivations for sharing tourism experiences through social media. Tourism management, 43, 46-54.
  • Oriade, A., & Robinson, P. (2019). Prosuming tourist information: Asking questions on Trip Advisor. International Journal of Tourism Research, 21(1), 134-143.
  • Owusu, R. A., Mutshinda, C. M., Antai, I., Dadzie, K. Q., & Winston, E. M. (2016). Which UGC features drive web purchase intent? A spike-and-slab Bayesian Variable Selection Approach. Internet Research, 26(1), 22–37.
  • Papathanassis, A., & Knolle, F. (2011). Exploring the adoption and processing of online holiday reviews: A grounded theory approach. Tourism Management, 32(2), 215-224.
  • Park, J. H., Gu, B., Leung, A. C. M., & Konana, P. (2014). An investigation of information sharing and seeking behaviors in online investment communities. Computers in Human Behavior, 31, 1-12.
  • Petty, R.E., & Cacioppo, J.T. (1986). The Elaboration Likelihood Model of Persuasion. Advances in Experimental Social Psychology, 19, 123–205.
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  • Savolainen, R. (2015). Providing informational support in an online discussion group and a Q & A site: The case of travel planning. Journal of the Association for Information Science and Technology, 66(3), 450-461.
  • Sher, P. J., & Lee, S. H. (2009). Consumer skepticism and online reviews: An elaboration likelihood model perspective. Social Behavior and Personality: an international journal, 37(1), 137-143.
  • Stone, M. (1974). Cross‐validatory choice and assessment of statistical predictions. Journal of the royal statistical society: Series B (Methodological), 36(2), 111-133.
  • Sussman, S. W., & Siegal, W. S. (2003). Informational influence in organizations: An integrated approach to knowledge adoption. Information systems research, 14(1), 47-65.
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Investigation of antecedents and consequences of usefulness in online travel communities: The moderating role of decision making stage

Yıl 2023, Cilt: 11 Sayı: 4, 476 - 504, 11.12.2023
https://doi.org/10.30519/ahtr.1053634

Öz

This study examines the perceived usefulness (PU) of online discourse and the decision-making behavior of users in Online Travel Communities (OTCs). Partial least squares structural equation modeling (PLS-SEM) was used on secondary data available in OTCs in the form of 852 threads to empirically test the proposed integrated model. The antecedents of the perceived usefulness of online travel communities were found to be the argument quality and credibility. These influence the PU of user-generated content significantly and are helpful in information adoption in OTCs. The PU of OTC discourse positively impacts travelers' information adoption and decision-making. The current study offers implications for OTCs and online service providers for enhancing the usefulness of user-generated content in OTCs and social media sites, leading to online information use and travel decision-making. Prior literature has explored the nature and magnitude of the influence of electronic word-of-mouth (eWOM) on information adoption and intention to use information for travel purchases from users' perspectives and has investigated the PU of third-party travel sites. This paper is an effort to examine PU and decision-making by analyzing the User-Generated-Content (UGC) posted by the actual users.

Kaynakça

  • Agag, G. M., & El-Masry, A. A. (2017). Why do consumers trust online travel websites? Drivers and outcomes of consumer trust toward online travel websites. Journal of Travel Research, 56(3), 347-369.
  • Agarwal, R., & Karahanna, E. (2000). Time flies when you're having fun: cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665-694.
  • Alsabawy, A. Y., Cater-Steel, A., & Soar, J. (2016). Determinants of perceived usefulness of e-learning systems. Computers in Human Behavior, 64, 843-858.
  • Angst, C. M., & Agarwal, R. (2009). Adoption of electronic health records in the presence of privacy concerns: The elaboration likelihood model and individual persuasion. MIS quarterly, 339-370.
  • Ayeh, J. K., Au, N., & Law, R. (2013). Predicting the intention to use consumer-generated media for travel planning. Tourism Management, 35, 132-143.
  • Bhattacherjee, A., & Sanford, C. (2006). Influence Processes for Information Technology Acceptance: An Elaboration Likelihood Model. MIS Quarterly, 30(4), 805–825.
  • Bollen, K. A., & Davis, W. R. (2009). Causal indicator models: Identification, estimation, and testing. Structural Equation Modeling: A Multidisciplinary Journal, 16(3), 498-522.
  • Brand, D. J. (2016). Automatic Prediction of Comment Quality (Doctoral dissertation, Stellenbosch: Stellenbosch University).
  • Butler, G., & Paris, C. M. (2016). Reaching the end of the unbeaten path? An analysis of Lonely Planet's digital media "requiem". Anatolia, 27(3), 377–388.
  • Byrne, B. M. (2010). Structural Equation Modeling with AMOS: Basic concepts, applications and programming (2nd ed.). New York: Routledge. doi: 10.4324/9781410600219
  • Capriello, A., Mason, P. R., Davis, B., & Crotts, J. C. (2013). Farm tourism experiences in travel reviews: A cross-comparison of three alternative methods for data analysis. Journal of Business Research, 66(6), 778-785.
  • Chan, Y. & Ngai, E. (2011). Conceptualising electronic word of mouth activity. Marketing Intelligence and Planning, 29(5), 488-516.
  • Chen, C. D., & C. S. Ku. (2012). Building Member's Relationship Quality Toward Online Community from the Elaboration Likelihood Model Perspective. Proceedings of the Pacific Asia Conference on Information Systems paper 126, Hochiminh City, Vietnam.
  • Chen, J. S. (1998). The tourists' cognitive decision-making model. The Tourist Review, 53(1), 4-9.
  • Cheung, C. M., & Thadani, D. R. (2012). The impact of electronic word-of-mouth communication: A literature analysis and integrative model. Decision support systems, 54(1), 461-470.
  • Cheung, C.M., Lee, M.K., & Rabjohn, N. (2008). The impact of electronic word-of-mouth: the adoption of online opinions in online customer communities. Internet Research, 18(3), 229-247.
  • Cheung, M. Y., Luo, C., Sia, C. L., & Chen, H. (2009). Credibility of electronic word-of-mouth: Informational and normative determinants of online consumer recommendations. International journal of electronic commerce, 13(4), 9-38.
  • Cheung, R. (2014). The influence of electronic word-of-mouth on information adoption in online customer communities. Global Economic Review, 43(1), 42-57.
  • Chong, A. Y. L., Khong, K. W., Ma, T., McCabe, S., & Wang, Y. (2018). Analyzing key influences of tourists' acceptance of online reviews in travel decisions. Internet Research, 28(3), 564-586. https://doi.org/10.1108/IntR-05-2017-0212
  • Choudhary, P., & Gangotia, A. (2017). Do travel decision-making styles and gender of generation Y have any association with travel information share on social networking sites?. Journal of Hospitality and Tourism Technology, 8(2), 152-167.
  • Chung, N., Han, H., & Koo, C. (2015). Adoption of travel information in user-generated content on social media: the moderating effect of social presence. Behaviour & Information Technology, 34(9), 902-919.
  • Cohn, J. (1988). Statistical power analysis for the behavioral sciences. Lawrence Earlbam Associates, Hillsdale, NJ.
  • Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
  • Dedeoglu, B.B. (2019). Are information quality and source credibility really important for shared content on social media? The moderating role of gender. International Journal of Contemporary Hospitality Management, 31(1), 513-534. https://doi.org/10.1108/IJCHM-10-2017-0691
  • Diamantopoulos, A., & Riefler, P. (2011). Using formative measures in international marketing models: A cautionary tale using consumer animosity as an example. In Measurement and Research Methods in International Marketing (pp. 11-30). Emerald Group Publishing Limited. Bingley.
  • Fang, J., Chen, L., Wang, X., & George, B. (2018). Not all posts are treated equal: An empirical investigation of post replying behavior in an online travel community. Information & Management, 55(7), 890-900.
  • Filieri, R., & McLeay, F. (2014). E-WOM and accommodation: An analysis of the factors that influence travelers' adoption of information from online reviews. Journal of travel research, 53(1), 44-57.
  • Gal-Tzur, A., Bar-Lev, S., & Shiftan, Y. (2020). Using question & answer forums as a platform for improving transport-related information for tourists. Journal of Travel Research, 59(7), 1221-1237.
  • Geisser, S. (1974). A predictive approach to the random effect model. Biometrika, 61(1), 101-107.
  • George, D., & Mallery, P. (2010). SPSS for Windows step by step. A simple study guide and reference (10. ed.). GEN, Boston, MA: Pearson Education, Inc.
  • Gretzel, U., Yoo, K. H., & Purifoy, M. (2007). Online Travel Review Study: Role & Impact of Online Travel Reviews. Laboratory for Intelligent Systems in Tourism, Texas A&M University. LIST 02-07-01.
  • Gvili, Y., & Levy, S. (2016). Antecedents of attitudes toward eWOMcommunication: differences across channels. Internet Research, 26(5), 1030–1051.
  • Hair, J. F., Hult, T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least square structural equation modeling (PLS-SEM). Sage Publications.
  • Hair, J.F., Sarstedt, M., Ringle, C.M., & Gudergan, S.P. (2018). Advanced Issues in Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage, Thousand Oaks, CA.
  • Hair, J.F., Risher, J.J., Sarstedt, M., & Ringle, C.M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203
  • Hajli, N., Wang, Y., & Tajvidi, M. (2018). Travel envy on social networking sites. Annals of Tourism Research, 73, 184–189. https://doi.org/10.1016/j.annals.2018.05.006
  • Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., ... & Calantone, R. J. (2014). Common beliefs and reality about PLS: Comments on Rönkkö and Evermann (2013). Organizational research methods, 17(2), 182-209.
  • Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the academy of marketing science, 43(1), 115-135.
  • Henseler, J., Ringle, C.M., & Sarstedt, M. (2016). Testing measurement invariance of composites using partial least squares. International Marketing Review, 33(3), 405-431.
  • Hu, Y. H., Chen, K., & Lee, P. J. (2017). The effect of user-controllable filters on the prediction of online hotel reviews. Information & Management, 54(6), 728-744.
  • Kim, J. J., Fesenmaier, D. R., & Johnson, S. L. (2013, July). The effect of feedback within social media in tourism experiences. In International conference of design, user experience, and usability (pp. 212-220). Springer, Berlin, Heidelberg.
  • Kim, S., Oh, J. S., & Oh, S. (2007). Best‐answer selection criteria in a social Q&A site from the user‐oriented relevance perspective. Proceedings of the American Society for Information Science and Technology, 44(1), 1-15.
  • Koo, T. K., & Li, M. Y. (2016). A guideline of selecting and reporting intraclass correlation coefficients for reliability research. Journal of chiropractic medicine, 15(2), 155-163.
  • Lee, H., Reid, E., & Kim, W. G. (2014). Understanding knowledge sharing in online travel communities: antecedents and the moderating effects of interaction modes. Journal of Hospitality & Tourism Research, 38(2), 222-242.
  • Li, C. Y. (2013). Persuasive messages on information system acceptance: A theoretical extension of elaboration likelihood model and social influence theory. Computers in Human Behavior, 29(1), 264-275.
  • Li, H. & Liu, Y. (2014). Understanding post-adoption behaviors of e-service users in the context of online travel services. Information and Management, 51(8),1043-1052.
  • Li, L., He, D., & Zhang, C. (2019). Characterizing High-Quality Answers for Different Question Types on Academic Social Q&A Site. In ISSI (pp. 2670-2671).
  • Li, L., Zhang, C., & He, D. (2020). Factors influencing the importance of criteria for judging answer quality on academic social Q&A platforms. Aslib Journal of Information Management, 72(6),887-907.
  • Litvin, S. W., Goldsmith, R. E., & Pan, B. (2008). Electronic word-of-mouth in hospitality and tourism management. Tourism management, 29(3), 458-468.
  • Matute, J., Polo-Redondo, Y., & Utrillas, A. (2016). The influence of EWOM characteristics on online repurchase intention mediating roles of trust and perceived usefulness. Online Information Review, 40(7), 1090-1110.
  • McHugh, M. L. (2012). Interrater reliability: the kappa statistic. Biochemiamedica, 22(3), 276-282.
  • McKinney, V., Yoon, K., & Zahedi, F. M. (2002). The measurement of web-customer satisfaction: An expectation and disconfirmation approach. Information systems research, 13(3), 296-315.
  • Mendes-Filho, L., Mills, A. M., Tan, F. B., & Milne, S. (2018). Empowering the traveler: an examination of the impact of user-generated content on travel planning. Journal of Travel & Tourism Marketing, 35(4), 425-436.
  • Moreno, M. A., Goniu, N., Moreno, P. S., & Diekema, D. (2013). Ethics of social media research: common concerns and practical considerations. Cyberpsychology, behavior, and social networking, 16(9), 708-713.
  • Munar, A. M., & Jacobsen, J. K. S. (2014). Motivations for sharing tourism experiences through social media. Tourism management, 43, 46-54.
  • Oriade, A., & Robinson, P. (2019). Prosuming tourist information: Asking questions on Trip Advisor. International Journal of Tourism Research, 21(1), 134-143.
  • Owusu, R. A., Mutshinda, C. M., Antai, I., Dadzie, K. Q., & Winston, E. M. (2016). Which UGC features drive web purchase intent? A spike-and-slab Bayesian Variable Selection Approach. Internet Research, 26(1), 22–37.
  • Papathanassis, A., & Knolle, F. (2011). Exploring the adoption and processing of online holiday reviews: A grounded theory approach. Tourism Management, 32(2), 215-224.
  • Park, J. H., Gu, B., Leung, A. C. M., & Konana, P. (2014). An investigation of information sharing and seeking behaviors in online investment communities. Computers in Human Behavior, 31, 1-12.
  • Petty, R.E., & Cacioppo, J.T. (1986). The Elaboration Likelihood Model of Persuasion. Advances in Experimental Social Psychology, 19, 123–205.
  • Richter, N. F., Cepeda-Carrion, G., Roldán Salgueiro, J. L., & Ringle, C. M. (2016). European management research using partial least squares structural equation modeling (PLS-SEM). European Management Journal, 34(6), 589-597.
  • Savolainen, R. (2015). Providing informational support in an online discussion group and a Q & A site: The case of travel planning. Journal of the Association for Information Science and Technology, 66(3), 450-461.
  • Sher, P. J., & Lee, S. H. (2009). Consumer skepticism and online reviews: An elaboration likelihood model perspective. Social Behavior and Personality: an international journal, 37(1), 137-143.
  • Stone, M. (1974). Cross‐validatory choice and assessment of statistical predictions. Journal of the royal statistical society: Series B (Methodological), 36(2), 111-133.
  • Sussman, S. W., & Siegal, W. S. (2003). Informational influence in organizations: An integrated approach to knowledge adoption. Information systems research, 14(1), 47-65.
  • Tilly, R., Fischbach, K., & Schoder, D. (2015). Mineable or messy? Assessing the quality of macro-level tourism information derived from social media. Electronic Markets, 25(3), 227-241.
  • Tormala, Z. L., & Petty, R. E. (2004). Source credibility and attitude certainty: A metacognitive analysis of resistance to persuasion. Journal of Consumer Psychology, 14(4), 427-442.
  • Twumasi, A., & Adu-Gyamfi, K. (2013). The impact of social networking sites on the purchasing behaviours of online travel community members. Information and Knowledge Management, 3(11), 105-111.
  • Usakli, A., & Kucukergin, K. G. (2018). Using partial least squares structural equation modeling in hospitality and tourism: do researchers follow practical guidelines?. International Journal of Contemporary Hospitality Management, 30(11), 3462-3512.
  • Wang, P., & Li, H. (2019). Understanding the antecedents and consequences of the perceived usefulness of travel review websites. International Journal of Contemporary Hospitality Management, 31(3), 1086-1103. https://doi.org/10.1108/IJCHM-06-2017-0380
  • Wold, H. (1985). Encyclopedia of statistical sciences. Partial least squares. Wiley, New York, 581-591. Xie, G. X., & Boush, D. M. (2011). How susceptible are consumers to deceptive advertising claims? A retrospective look at the experimental research literature. The Marketing Review, 11(3), 293-314.
  • Yang, C. C., & Brown, B. B. (2015). Factors involved in associations between Facebook use and college adjustment: Social competence, perceived usefulness, and use patterns. Computers in Human Behavior, 46, 245-253.
  • Yang, J., Mai, E., & Ben-Ur, J. (2012). Did you tell me the truth?: The influence of online community on eWOM. International Journal of Market Research, 54(3), 369-389.
  • Zhao, X., Lynch Jr, J. G., & Chen, Q. (2010). Reconsidering Baron and Kenny: Myths and truths about mediation analysis. Journal of consumer research, 37(2), 197-206.
  • Zhou, T. (2017). Understanding location-based services users' privacy concern. Internet Research, 27(3), 506–519.
Toplam 75 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Turizm (Diğer)
Bölüm Araştırma Makalesi
Yazarlar

Bindu Ranga Bu kişi benim 0000-0002-2834-7554

Ranbir Singh 0000-0001-7629-1973

Indu Ranga Bu kişi benim 0000-0002-8946-050X

Erken Görünüm Tarihi 3 Mayıs 2023
Yayımlanma Tarihi 11 Aralık 2023
Gönderilme Tarihi 5 Ocak 2022
Yayımlandığı Sayı Yıl 2023 Cilt: 11 Sayı: 4

Kaynak Göster

APA Ranga, B., Singh, R., & Ranga, I. (2023). Investigation of antecedents and consequences of usefulness in online travel communities: The moderating role of decision making stage. Advances in Hospitality and Tourism Research (AHTR), 11(4), 476-504. https://doi.org/10.30519/ahtr.1053634


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