References
- Filieri R. What makes online reviews helpful? A diagnosticity-adoption framework to explain informational and normative influences in e-WOM. J Bus Res. 2015;68(6):1261–70. doi:https://doi.org/10.1016/j.jbusres.2014.11.006.
- Church EM, Iyer L. “When is Short, Sweet?” Selection uncertainty and online review presentations. J Comput Inf Syst. 2017;57(2):179–89. doi:https://doi.org/10.1080/08874417.2016.1183980.
- Park DH, Lee J, Han I. The effect of online consumer reviews on consumer purchasing intention: the moderating role of involvement. Int J Electron Commer. 2007;11(4):125–48. doi:https://doi.org/10.2753/JEC1086-4415110405.
- Zhu F, Zhang X. Impact of online consumer reviews on sales: the moderating role of product and consumer characteristics. J Mark Res. 2010;74:133–48.
- Jensen ML, Averbeck JM, Zhang Z, Wright KB. Credibility of anonymous online product reviews: A language expectancy. J Manag Inf Syst. 2013;30(1):293–323. doi:https://doi.org/10.2753/MIS0742-1222300109.
- Ketelaar PE, Willemsen LM, Sleven L, Kerkhof P. The good, the bad, and the expert: how consumer expertise affects review valence effects on purchase intentions in online product reviews. J Comput Mediat Commun. 2015;20(6):649–66. doi:https://doi.org/10.1111/jcc4.12139.
- Xia H, Pan X, An W, Zhang ZJ. Can online rating reflect authentic customer purchase feelings? Understanding how customer dissatisfaction relates to negative reviews. J Comput Inf Syst. 2019:1–14. doi:https://doi.org/10.1080/08874417.2019.1647766.
- Ren J, Nickerson JV. Arousal, valence, and volume: how the influence of online review characteristics differs with respect to utilitarian and hedonic products. Eur J Inf Syst. 2018;28(3):272–90. doi:https://doi.org/10.1080/0960085X.2018.1524419.
- Li X, Wu C, Mai F. The effect of online reviews on product sales: A joint sentiment-topic analysis. Inf Manag. 2019;56(2):172–84. doi:https://doi.org/10.1016/j.im.2018.04.007.
- Ruler BV. Communication theory: an underrated pillar on which strategic communication rests. Int J Strateg Commun. 2018;12:367–81. doi:https://doi.org/10.1080/1553118X.2018.1452240.
- Lai J, He P, Chou HM, Zhou L. Impact of national culture on online consumer review behavior. Glob J Bus Res. 2013;7:109–15.
- Mudambi SM, Schuff D. What makes a helpful online review? A study of customer reviews on Amazon.com. Manag Inf Syst Q. 2010;34(1):185–200. doi:https://doi.org/10.2307/20721420.
- Kumar N, Benbasat I. Research note-the influence of recommendations and consumer reviews on evaluations of websites. Inf Syst Res. 2006;17(4):425–39. doi:https://doi.org/10.1287/isre.1060.0107.
- Chen PY, Dhanasobhon S, Smith MD. All reviews are not created equal: the disaggregate impact of reviews and reviewers at amazon.com. SSRN Electron J. 2008 May. doi:https://doi.org/10.2139/ssrn.918083.
- Forman C, Ghose A, Wiesenfeld B. Examining the relationship between reviews and sales: the role of reviewer identity disclosure in electronic markets. Inf Syst Res. 2006;19(3):291–313. doi:https://doi.org/10.1287/isre.1080.0193.
- Cheung CMK, Lee MKO, Rabjohn N. The impact of electronic word-of-mouth: the adoption of online opinions in online customer communities. Internet Res. 2008;18:229–47. doi:https://doi.org/10.1108/10662240810883290.
- Willemsen LM, Neijens PC, Bronner F, Ridder JA. Highly recommended the content characteristics and perceived usefulness of online consumer reviews. J Comput Mediat Commun. 2011;17:19–38. doi:https://doi.org/10.1111/j.1083-6101.2011.01551.x.
- Thomas MJ, Wirtz BW, Weyerer JC. Determinants of online review credibility and its impact on consumers’ purchase intention. J Electron Commer Res. 2019;20:1–20.
- Pasuntsirikhun P, Phungbangkruay J. Attitudes towards online purchasing of products and services in Chonburi province. Burapha J Bus Res. 2017;6:30–42.
- Baek H, Ahn J, Choi Y. Helpfulness of online consumer reviews: readers’ objectives and review cues. Int J Electron Commer. 2012;17(2):99–126. doi:https://doi.org/10.2753/JEC1086-4415170204.
- Lee SG, Trimi S, Yang CG. Perceived usefulness factors of online reviews: A study of Amazon.com. J Comput Inf Syst. 2018;58(4):344–52. doi:https://doi.org/10.1080/08874417.2016.1275954.
- Li M, Huang L, Tan CH, Wei KK. Helpfulness of online product reviews as seen by consumers: source and content features. Int J Electron Commer. 2013;17(4):101–36. doi:https://doi.org/10.2753/JEC1086-4415170404.
- Weathers D, Swain SD, Grover V. Can online product reviews be more helpful? Examining characteristics of information content by product type. Decis Support Syst. 2015;79:12–23. doi:https://doi.org/10.1016/j.dss.2015.07.009.
- Lee SH, Ro H. The impact of online reviews on attitude changes: the differential effects of review attributes and consumer knowledge. Int J Hosp Manag. 2016;56:1–9. doi:https://doi.org/10.1016/j.ijhm.2016.04.004.
- Liu Y. Word of mouth for movies: its dynamics and impact on box office revenue. J Mark Res. 2006;70:74–89.
- Dellarocas C, Zhang XM, Awad N. Exploring the value of online product reviews in forecasting sales: the case of motion pictures. J Interact Mark. 2007;21(4):23–45. doi:https://doi.org/10.1002/dir.20087.
- Antioco M, Coussement K. Misreading of consumer dissatisfaction in online product reviews: writing style as a cause for bias. Int J Inf Manag. 2018;38(1):301–10. doi:https://doi.org/10.1016/j.ijinfomgt.2017.10.009.
- Doh SJ, Hwang JS. How consumers evaluate eWOM (electronic word-of-mouth) messages. Cyberpsychol Behav. 2009;12(2):193–97. doi:https://doi.org/10.1089/cpb.2008.0109.
- Khongthanarat C, Assarut N. Factors effecting e-Wom creditability of restaurants on Facebook. Songklanakarin J Soc Sci Humanit. 2017;23:145–98.
- Obiedat R. Impact of online consumer reviews on buying intention of consumers in UK: need for cognition as the moderating role. Int J Adv Corp Learn. 2013;6(2):16–21. doi:https://doi.org/10.3991/ijac.v6i2.2910.
- Nielsen Company. The reviews are in: yelp users are four-star consumers. 2013 Jun 27. [accessed 2020 Feb 20]. https://www.nielsen.com/us/en/insights/article/2013/the-reviews-are–in–yelp-users-are-four-star-consumers/.
- Duan W, Gu B, Whinston AB. Do online reviews matter? - An empirical investigation of panel data. Decis Support Syst. 2008;45(4):1007–16. doi:https://doi.org/10.1016/j.dss.2008.04.001.
- Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. Manag Inf Syst Q. 1989;13(3):319–40. doi:https://doi.org/10.2307/249008.
- Ayeh JK. Travellers’ acceptance of consumer-generated media: an integrated model of technology acceptance and source credibility theories. Comput Hum Behav. 2015;48:173–80. doi:https://doi.org/10.1016/j.chb.2014.12.049.
- Casalo LV, Flavian C, Guinalíu M. Determinants of the intention to participate in firm-hosted online travel communities and effects on consumer behavioral intentions. Tour Manag. 2010;31(6):898–911. doi:https://doi.org/10.1016/j.tourman.2010.04.007.
- Elwalda A, Lü K, Ali M. Perceived derived attributes of online customer reviews. Comput Hum Behav. 2016;56:306–19. doi:https://doi.org/10.1016/j.chb.2015.11.051.
- Hsu CL, Lin JCC, Chiang HS. The effects of blogger recommendations on customers’ online shopping intentions. Internet Res. 2013;23(1):69–88. doi:https://doi.org/10.1108/10662241311295782.
- Chen Y, Xie J. Online consumer review: word-of-mouth as a new element of marketing communication mix. Manag Sci. 2008;54(3):477–91. doi:https://doi.org/10.1287/mnsc.1070.0810.
- Godes D, Mayzlin D. Using online conversations to study word-of mouth communication. Mark. Sci. 2004;23(4):545–60. doi:https://doi.org/10.1287/mksc.1040.0071.
- Liu Z, Park S. What makes a useful online review? Implication for travel product websites. Tour Manag. 2015;47:140–51. doi:https://doi.org/10.1016/j.tourman.2014.09.020.
- Liang SWJ, Ekinci Y, Occhiocupo N, Whyatt G. Antecedents of travellers’ electronic word-of-mouth communication. J Mark Manage. 2013;29:584–606. doi:https://doi.org/10.1080/0267257X.2013.771204.
- Benlian A, Titah R, Hess T. Differential effects of provider recommendations and consumer reviews in e commerce transactions: an experimental study. J Manag Inf Syst. 2012;29(1):237–72. doi:https://doi.org/10.2753/MIS0742-1222290107.
- Bickart B, Schindler RM. Internet forums as influential sources of consumer information. J Interact Mark. 2001;15(3):31–40. doi:https://doi.org/10.1002/dir.1014.
- Ott M, Choi Y, Cardie C, Hancock J Finding deceptive opinion spam by any stretch of the imagination. Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies; 2011 Jun 19-24;; Portland, OR. 309–19
- Moro S, Ramos P, Esmerado J, Jalali SMJ. Can we trace back hotel online reviews’ characteristics using gamification features? Int J Inf Manag. 2019;44:88–95. doi:https://doi.org/10.1016/j.ijinfomgt.2018.09.015.
- Malbon J. Taking fake online consumer reviews seriously. J Consum Policy. 2013;36(2):139–57. doi:https://doi.org/10.1007/s10603-012-9216-7.
- Vinayak HV, Thompson F, Tonby O. McKinsey&Company. Understanding ASEAN: Seven things you need to know. 2014 Jul 4 [accessed 2020 Feb 20]. https://www.internationaldiplomacyforum.org/post/understanding-asean-seven-things-you-need-to-know.
- Randall S. The expansion of modern trade food retailing in Thailand. Int Rev of Retail Dist & Consum Res. 2014;24:531–43.
- Electronic Transactions Development Agency. The value of e-commerce survey in Thailand 2016. Bangkok (TH): Ministry of Digital Economy and Society; 2016. p. 1–116.
- Hofstede G. Cultures and organizations: Software of the mind. London (UK): McGraw-Hill; 1991.
- Yoon C. The effects of national culture values on consumer acceptance of E-commerce: online shoppers in China. Inf & Manag. 2009;46:294–301. doi:https://doi.org/10.1016/j.im.2009.06.001.
- Harvey F. National cultural differences in theory and practice: evaluating Hofstede’s national cultural framework. Inf Technol & People. 1999;10(2):132–46. doi:https://doi.org/10.1108/09593849710174986.
- Palvia P. Research issues in global information technology management. Inf Resour Manag J. 1998;11(2):27–36. doi:https://doi.org/10.4018/irmj.1998040103.
- Straub D, Keil M, Brenner W. Testing the technology acceptance model across cultures: A three country study. Inf & Manag. 1997;33(1):1–11. doi:https://doi.org/10.1016/S0378-7206(97)00026-8.
- Chen JQ, Zhang R, Lee J. A cross-culture empirical study of m-commerce privacy concerns. J of Internet Commer. 2013;12(4):348–64. doi:https://doi.org/10.1080/15332861.2013.865388.
- Jarvenpaa S, Todd P. Consumer reaction to electronic shopping on the world wide web. Int J of Electron Commer. 1996;1(2):59–88. doi:https://doi.org/10.1080/10864415.1996.11518283.
- Bontempo RN, Bottom WP, Weber EU. Cross-cultural differences in risk perception: a model-based approach. Risk Anal. 1997;17:479–89. doi:https://doi.org/10.1111/j.1539-6924.1997.tb00888.x.
- Swierczek FW, Onishi J. culture and conflict: Japanese managers and Thai subordinates. Personnel Rev. 2002;32:187–210. doi:https://doi.org/10.1108/00483480310460216.
- Weber EU, Hsee CK. Cross-cultural differences in risk perception but cross-cultural similarities in attitudes toward perceive risk. Manag Sci. 1998;44(9):1205–17. doi:https://doi.org/10.1287/mnsc.44.9.1205.
- Chaisiwamongkol W, Manmart L, Chantatub W. A user-centric approach to develop indicators for accessing information quality on e-commerce website. Chulalongkorn Rev. 2018;40:57–101.
- Balasudarsun NL, Sathish M, Jambulingam M, Yamalee E. Impact of social context on online shopping behavior in selected Asian countries. Manag Sci. 2018;18:188–200.
- Promma I, Worrapishet T. The application of user generating contents which impact to the services of hotel industry in Thailand. Using customer feedback on social media that affects the service of hotel business in Thailand. J Mod Manag. 2016;8:129–41.
- Sirichanchuen B, Norwong J, Sankule N, Chinwong D. Reason influencing purchase decisions of dietary supplements on the internet in Thailand. J Pharm Pract. 2017;9:259–68.
- Hsia JW, Chang CC, Tseng AH. Effects of individuals’ locus of control and computer self-efficacy on their e-learning acceptance in high-tech companies. Behav Inf Technol. 2014;33(1):51–64. doi:https://doi.org/10.1080/0144929X.2012.702284.
- Yang K. The effects of technology self-efficacy and innovativeness on consumer mobile data service adoption between American and Korean consumers. J Int Consum Mark. 2010;22(2):117–27. doi:https://doi.org/10.1080/08961530903476147.
- Agarwal R, Prasad J. Are individual differences germane to the acceptance of information technologies? Decis Sci. 1999;30(2):361–91. doi:https://doi.org/10.1111/j.1540-5915.1999.tb01614.x.
- Venkatesh V, Davis FD. A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag Sci. 2000;46(2):186–204. doi:https://doi.org/10.1287/mnsc.46.2.186.11926.
- Flanagin AJ, Metzger MJ, Pure R, Markov A, Hartsell E. Mitigating risk in ecommerce transactions: perceptions of information credibility and the role of user-generated ratings in product quality and purchase intention. J Electron Commer Res. 2014;14:1–23. doi:https://doi.org/10.1007/s10660-014-9139-2.
- Wang Q, Wang L, Zhang X, Mao Y. The impact research of online reviews’ sentiment polarity presentation on consumer purchase decision. Inf Technol People. 2017;30(3):522–41. doi:https://doi.org/10.1108/ITP-06-2014-0116.
- Ruiz-Mafe C, Chatzipanagiotou K, Curras-Perez R. The role of emotions and conflicting online reviews on consumers’ purchase intentions. J Bus Res. 2018;89:336–44. doi:https://doi.org/10.1016/j.jbusres.2018.01.027.
- Venkatesh V, Morris M, Davis G, Davis F. User acceptance of information technology: toward a unified view. Manag Inf Syst Q. 2003;27(3):425–78. doi:https://doi.org/10.2307/30036540.
- Klaus T, Changchit C. Toward an understanding of consumer attitudes on online review usage. J Comput Inf Syst. 2019;59:277–86.
- Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate data analysis: A global perspective. 7th. Upper Saddle River (NJ): Prentice Hall; 2009.
- Browne MW, Cudeck R. Single sample cross-validation indices for covariance structures. Multivariate Behav Res. 1989;24:445–55. doi:https://doi.org/10.1207/s15327906mbr2404_4.
- Byrne BM. Structural equation modeling with EQS and EQS/Windows. Thousand Oaks (CA): Sage Publications; 1994.
- Hu LT, Bentler PM. Evaluating model fit. In: Hoyle RH, editor. Structural equation modeling: concepts, issues, and applications. Thousand Oaks (CA): Sage. 1995.
- Kline RB. Principles and practice of structural equation modeling. New York (NY): Guilford Press; 1998.
- Schumacker R, Lomax R. A beginner’s guide to structural equation modeling. 2nd. Mahwah (NJ): Lawrence Erlbaum Associates; 2004.
- Ullman JB. Structural equation modeling. In: Tabachnick BG, Fidell LS editors. Using multivariate statistics. 4th. Needham Heights (MA): Allyn & Bacon; 2001. p. 653–771.
- Malaquias FF, Hwang Y. An empirical study on trust in mobile banking: a developing country perspective. Comput Hum Behav. 2016;54:453–61. doi:https://doi.org/10.1016/j.chb.2015.08.039.
- Masrek MN, Mohamed IS, Daud NM, Omar N. Technology trust and mobile banking satisfaction: A case of Malaysian consumers. Procedia Soc Behav Sci. 2014;129:53–58. doi:https://doi.org/10.1016/j.sbspro.2014.03.647.
- Oliveira T, Faria M, Thomas MA, Popovič A. Extending the understanding of mobile banking adoption: when UTAUT meets TTF and ITM. Int J Inf Manag. 2014;34(5):689–703. doi:https://doi.org/10.1016/j.ijinfomgt.2014.06.004.
- Yadav A. Factors influencing the usage of mobile banking among customers. The IUP J Bank Manag. 2016;15:7–18.
- Luo X, Li H, Zhang J, Shim JP. Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: an empirical study of mobile banking services. Decis Support Syst. 2010;49(2):222–34. doi:https://doi.org/10.1016/j.dss.2010.02.008.
- Remus W. Graduate students as surrogates for managers in experiments on business decision making. J Bus Res. 1986;14(1):19–25. doi:https://doi.org/10.1016/0148-2963(86)90053-6.
- Zhou T. Understanding users’ initial trust in mobile banking: an elaboration likelihood perspective. Comput Hum Behav. 2012;28(4):1518–25. doi:https://doi.org/10.1016/j.chb.2012.03.021.