References

• Ahmad, W., & Sun, J. (2018). Modeling consumer distrust of online hotel reviews. International Journal of Hospitality Management, 71, 77–90. doi: 10.1016/j.ijhm.2017.12.005
   Web of Science ®Google Scholar
• Aiken, L., West, S., & Reno, R. (1991). Multiple regression: Testing and interpreting interactions. Thousand Oaks, CA: Sage Publications.
   Google Scholar
• Akhtar, N., Kim, G., Ahmad, W., Akhtar, N., Siddiqi, I., & Riaz, M. (2019). Mechanisms of consumers’ trust development in reviewers’ supplementary reviews: A reviewer-reader similarity perspective. Tourism Management Perspectives, 31, 95–108. doi: 10.1016/j.tmp.2019.04.001
   Web of Science ®Google Scholar
• Akhtar, N., Sun, J., Akhtar, N., & Chen, J. (2019). How attitude ambivalence from conflicting online hotel reviews affects consumers’ behavioural responses: The moderating role of dialecticism⋆. Journal of Hospitality and Tourism Management, 41, 28–40. doi: 10.1016/j.jhtm.2019.09.003
   Web of Science ®Google Scholar
• Akhtar, N., Sun, J., Chen, J., & Akhtar, M. (2019). The role of attitude ambivalence in conflicting online hotel reviews. Journal of Hospitality Marketing & Management, 1–32. doi: 10.1080/19368623.2019.1650684
   Web of Science ®Google Scholar
• Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.540.4887&rep=rep1&type=pdf
   Web of Science ®Google Scholar
• Armitage, C. (2003). Beyond attitudinal ambivalence: Effects of belief homogeneity on attitude-intention-behaviour relations. European Journal of Social Psychology, 33, 551–563. doi: 10.1002/ejsp.164
   Web of Science ®Google Scholar
• Beardon, A. F. (1990). Symmetries of Julia sets. Bulletin of the London Mathematical Society, 22(6), 576–582. doi: 10.1112/blms/22.6.576
   Web of Science ®Google Scholar
• Bohner, G., Moskowitz, G., & Shelly, C. (2015). The interplay of heuristic and systematic processing of social information. European Review of Social Psychology, 37–41. doi: 10.1080/14792779443000003
   Google Scholar
• Book, L., Tanford, S., & Chang, W. (2018). Customer reviews are not always informative: The impact of effortful versus heuristic processing. Journal of Retailing and Consumer Services, 41, 272–280. doi: 10.1016/j.jretconser.2018.01.001
   Web of Science ®Google Scholar
• Boukamcha, F. (2017). The impact of attitudinal ambivalence on information processing and resistance to anti-smoking persuasion. Journal of Indian Business Research, 9(1), 2–19. doi: 10.1108/JIBR-02-2016-0010
   Web of Science ®Google Scholar
• Burnkrant, R., & Cousineau, A. (1975). Informational and normative social influence in buyer behavior. Journal of Consumer Research, 2, 206–215.
   Web of Science ®Google Scholar
• Buzova, D., Sanz-Blas, S., & Cervera-Taulet, A. (2019). Does culture affect sentiments expressed in cruise tours’ eWOM? The Service Industries Journal, 39(2), 154–173. doi: 10.1080/02642069.2018.1476497
   Web of Science ®Google Scholar
• Cavazza, N., & Butera, F. (2008). Bending without breaking: Examining the role of attitudinal ambivalence in resisting persuasive communication. European Journal of Social Psychology, 38(1), 1–15. doi: 10.1002/ejsp.424
   Web of Science ®Google Scholar
• Cezar, A. (2012). The factors affecting writing reviews in hotel websites. 8th International Strategic Management Conference, 58, 980–986. doi: 10.1016/j.sbspro.2012.09.1077
   Google Scholar
• Chaiken, S. (1980). Heuristic versus systematic information processing and the use of source versus message cues in persuasion.. Journal of Personality and Social Psychology, 39(5), 752–766. doi: 10.1037//0022-3514.39.5.752
   Web of Science ®Google Scholar
• Chaiken, S., & Maheswaran, D. (1994). Heuristic processing can bias systematic processing: Effects of source credibility, argument ambiguity, and task importance on attitude judgment.. Journal of Personality and Social Psychology, 66(3), 460–473.
   PubMed Web of Science ®Google Scholar
• Chang, C. (2012). Ambivalent attitudes in a Communication process: An Integrated model. Human Communication Research, 38, 332–359. doi: 10.1111/j.1468-2958.2012.01429.x
   Web of Science ®Google Scholar
• Chang, C. (2014). The influence of ambivalence toward a communication source: Media context priming and persuasion polarization. Communication Research, 41(6), 783–808. doi: 10.1177/0093650213495408
   Web of Science ®Google Scholar
• Chen, M. Y. (2016). Can two-sided messages increase the helpfulness of online reviews? Online Information Review, 40(2), 2–3. doi: 10.1108/14684520210418374
   Web of Science ®Google Scholar
• Chen, S., Duckworth, K., & Chaiken, S. (1999). Motivated heuristic and systematic processing. Psychological Inquiry, 10(1), 44–49. doi: 10.1207/s15327965pli1001
   Web of Science ®Google Scholar
• Cheung, C., Lee, M., & Rabjohn, N. (2008). The adoption of online opinions in online customer communities. Internet Research, 18(3), 229–247. doi: 10.1108/10662240810883290
   Web of Science ®Google Scholar
• Cohen, J. (1988). Statistical power analysis for the behavioural sciences. New York: Routledge Academic.
   Google Scholar
• Conner, M., Sparks, P., Povey, R., James, R., Shepherd, R., & Armitage, C. J. (2002). Moderator effects of attitudinal ambivalence on attitude-behaviour relationships. European Journal of Social Psychology, 32(5), 705–718. doi: 10.1002/ejsp.117
   Web of Science ®Google Scholar
• Cornelis, E., Heuvinck, N., & Majmundar, A. (2019). The ambivalence story: Using refutation to counter the negative effects of ambivalence in two-sided messages. International Journal of Advertising, 1–23. doi: 10.1080/02650487.2019.1624348
   Web of Science ®Google Scholar
• Costarelli, S., & Colloca, P. (2007). The moderation of ambivalence on attitude-intention relations as mediated by attitude importance. European Journal of Social Psychology, 37(5), 923–933. doi: 10.1002/ejsp.403
   Web of Science ®Google Scholar
• Crano, W. D., & Prislin, R. (2008). Attitude and attitude change. Retrieved from http://www.psypress.com
   Google Scholar
• Deshmukh, G. K. (2016). Students’ susceptibility to reference group influence on smartphone in Raipur City. IFRSA Business Review, 4, 68–73.
   Google Scholar
• Deutsch, M., & Gerard, H. B. (1955). A study of normative and informational social influences upon individual judgment. The Journal of Abnormal and Social Psychology, 51(3), 629–636.
   PubMedGoogle Scholar
• Eagly, A. H., & Chaiken, S. (1993). The psychology of attitudes. Orlando, FL: Harcourt Brace Jovanovich College Publishers.
   Google Scholar
• Fang, B., Ye, Q., Kucukusta, D., & Law, R. (2016). Analysis of the perceived value of online tourism reviews: Influence of readability and reviewer characteristics. Tourism Management, 52, 498–506. doi: 10.1016/j.tourman.2015.07.018
   Web of Science ®Google Scholar
• Filieri, R. (2014). What makes online reviews helpful? A diagnosticity-adoption framework to explain informational and normative influences in e-WOM. Journal of Business Research, 68(6), 1261–1270. doi: 10.1016/j.jbusres.2014.11.006
   Web of Science ®Google Scholar
• Filieri, R., Hofacker, C., & Alguezaui, S. (2017). What makes information in online consumer reviews diagnostic over time? The role of review relevancy, factuality, currency, source credibility and ranking score. Computers in Human Behavior. doi: 10.1016/j.chb.2017.10.039
   Web of Science ®Google Scholar
• 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. doi: 10.1177/0047287513481274
   Web of Science ®Google Scholar
• Filieri, R., Mcleay, F., & Tsui, B. (2018). Consumer perceptions of information helpfulness and determinants of purchase intention in online consumer reviews of services. Information & Management, 55(8), 956–970. doi: 10.1016/j.im.2018.04.010
   Web of Science ®Google Scholar
• Fodness, D., & Murray, B. (1997). Tourist information search. Annals of Tourism Research, 24(3), 503–523. doi: 10.1016/S0160-7383(97)00009-1
   Web of Science ®Google Scholar
• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. doi: 10.2307/3151312
   Web of Science ®Google Scholar
• Guillet, D., & Law, R. (2011). Analyzing hotel star ratings on third-party distribution websites. International Journal of Contemporary Hospitality Management, 22(6), 797–813. doi: 10.1108/09596111011063098
   Web of Science ®Google Scholar
• Gursoy, D. (2004). Travelers’ prior knowledge and its impact on their information search behavior. Journal of Hospitality and Tourism Research, 28(1), 66–94. doi: 10.1177/1096348003261218
   Google Scholar
• Gursoy, D. (2018). A critical review of determinants of information search behavior and utilization of online reviews in decision making process. International Journal of Hospitality Management, 0–1. doi: 10.1016/j.ijhm.2018.06.003
   Web of Science ®Google Scholar
• Gursoy, D., Chiappa, G. D., & Zhang, Y. (2017). Preferences regarding external information sources: A conjoint analysis of visitors to Sardinia, Italy. Journal of Travel and Tourism Marketing, 34(6), 806–820. doi: 10.1080/10548408.2016.1237405
   Web of Science ®Google Scholar
• Hair, J. F. (2010). Multivariate data analysis: A global perspective. New York: Pearson Education.
   Google Scholar
• Hair, J., Ringle, C., & Sarstedt, M. (2011). PLS-SEM : Indeed a silver bullet. Journal of Marketing Theory and Practice, 19, 37–41. doi: 10.2753/MTP1069-6679190202
   Google Scholar
• Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis (6th ed.). New York, NY: Guilford Press.
   Google Scholar
• Hennig, T., Gwinner, K., Walsh, G., & Gremler, D. (2004). Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the Internet? Journal of Interactive Marketing, 18(1), 38–52. doi: 10.1002/dir.10073
   Google Scholar
• Hill, K. (2013). Using a modified heuristic-systematic model to characterize information seeking on the Internet. ProQuest dissertations and theses, 95. Retrieved from http://search.proquest.com/docview/1418472424?accountid=14643%5Cnhttp://mlbsfx.sibi.usp.br:3410/sfxlcl41?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&genre=dissertations+%26+theses&sid=ProQ:ProQuest+Dissertations+%26+Theses+Global&ati
   Google Scholar
• Hu, L.-t., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. doi: 10.1080/10705519909540118
   Web of Science ®Google Scholar
• Huang, G. H., Korfiatis, N., & Chang, C.-T. (2018). Mobile shopping cart abandonment: The roles of conflicts, ambivalence, and hesitation. Journal of Business Research, 85, 165–174. doi: 10.1016/j.jbusres.2017.12.008
   Web of Science ®Google Scholar
• Jimmy, H., Miao, L., Kuo, P., & Lee, B. (2011). Consumers’ responses to ambivalent online hotel reviews : The role of perceived source credibility and pre-decisional disposition. International Journal of Hospitality Management, 30(1), 178–183. doi: 10.1016/j.ijhm.2010.04.008
   Web of Science ®Google Scholar
• Kaplan, K. (1972). On the ambivalence-indifference problem in attitude theory and measurement: A suggested modification of the semantic differential technique. Psychological Bulletin, 77(5), 361–372.
   Web of Science ®Google Scholar
• Kim, K., King, K. W., & Kim, J. (2018). Processing contradictory brand information from advertising and social media: An application of the multiple-motive heuristic-systematic model. Journal of Marketing Communications, 24(8), 801–822. doi: 10.1080/13527266.2015.1129356
   Google Scholar
• Kim, J., & Paek, H. (2009). Information processing of genetically modified food messages under different motives: An adaptation of the multiple-motive heuristic-systematic model. Risk Analysis, 29(12), 1793–1806. doi: 10.1111/j.1539-6924.2009.01324.x
   PubMed Web of Science ®Google Scholar
• Kim, S. M., & Um, K.-H. (2015). The effects of ambivalence on behavioral intention in medical tourism. Asia Pacific Journal of Tourism Research, 21(9), 1020–1045. doi: 10.1080/10941665.2015.1093515
   Web of Science ®Google Scholar
• Kline, R. B. (2005). PsycNET record display - PsycNET.
   Google Scholar
• Lee, J., Park, D.-H., & Han, I. (2008). The effect of negative online consumer reviews on product attitude: An information processing view. Electronic Commerce Research and Applications, 7(3), 341–352. doi: 10.1016/J.ELERAP.2007.05.004
   Web of Science ®Google Scholar
• Lessig, P. (1977). Students and housewives : differences in susceptibility to reference group influence. Journal of Consumer Behaviour, 4(2), 102–110.
   Google Scholar
• Lo, A., & Yao, S. (2019). What makes hotel online reviews credible?: An investigation of the roles of reviewer expertise, review rating consistency and review valence. International Journal of Contemporary Hospitality Management, 31(1), 41–60. doi: 10.1108/IJCHM-10-2017-0671
   Web of Science ®Google Scholar
• Lynch, J. G., Alba, J. W., Krishna, A., Morwitz, V. G., & Gürhan, Z. (2012). Knowledge creation in consumer research: Multiple routes, multiple criteria. Journal of Consumer Psychology, 22(4), 473–485. doi: 10.1016/J.JCPS.2012.06.004
   Web of Science ®Google Scholar
• MacCallum, R. C., & Hong, S. (1997). Power analysis in covariance structure modeling using GFI and AGFI. Multivariate Behavioral Research, 32(2), 193–210. doi: 10.1207/s15327906mbr3202_5
   PubMed Web of Science ®Google Scholar
• Moody, G., Galletta, D., Benjamin, P., Lowry, B., & Benjamin, P. (2014). When trust and distrust collide online: The engenderment and role of consumer ambivalence in online consumer behavior. Electronic Commerce Research and Applications, 13(4), 266–282. doi: 10.1016/j.elerap.2014.05.001
   Web of Science ®Google Scholar
• Mucchi-Faina, A., & Pagliaro, S. (2008). Minority influence: The role of ambivalence toward the source. European Journal of Social Psychology, 38, 612–623. doi: 10.1002/ejsp
   Web of Science ®Google Scholar
• Mudambi, S., & Schuff, D. (2014). Why aren’t the stars aligned ? An analysis of online review content and star ratings. 47th Hawaii International Conference on system Science. doi: 10.1109/HICSS.2014.389
   Google Scholar
• Mudambi, S., Schuff, D., & Hall, S. (2010). Research note: What makes a helpful online review? A study of customer reviews on Amazon.com. MIS Quarterly, 34(1), 185–200.
   Web of Science ®Google Scholar
• Nazlan, N. H., Tanford, S., & Montgomery, R. (2018). The effect of availability heuristics in online consumer reviews. Academic Paper, 1–12. doi: 10.1002/cb.1731
   Google Scholar
• Netemeyer, R. G., & Teel, J. E. (2014). Journal of Consumer Research, Inc, 15(4), 473–481.
   Google Scholar
• Nikbin, D., Hyun, S., Baharun, R., & Tabavar, A. (2015). The determinants of customers’ behavioral intentions after service failure: The role of emotions. Asia Pacific Journal of Tourism Research, 20(9), 971–989. doi: 10.1080/10941665.2014.951663
   Web of Science ®Google Scholar
• Nordgren, L. F., Harreveld, F., & Pligt, J. (2006). Ambivalence, discomfort, and motivated information processing. Journal of Experimental Social Psychology, 42, 252–258. doi: 10.1016/j.jesp.2005.04.004
   Web of Science ®Google Scholar
• Öǧüt, H., & Onur Taş, B. K. (2012). The influence of internet customer reviews on the online sales and prices in hotel industry. The Service Industries Journal, 32(2), 197–214. doi: 10.1080/02642069.2010.529436
   Web of Science ®Google Scholar
• Olsen, O., & Wilcox, J. (2005). Consequences of ambivalence on satisfaction and loyalty. Psychology and Marketing, 22, 247–269. doi: 10.1002/mar.20057
   Web of Science ®Google Scholar
• Pang, J., Keh, H., Li, X., & Maheswaran, D. (2016). “Every coin has two sides”: The effects of dialectical thinking and attitudinal ambivalence on psychological discomfort and consumer choice. Journal of Consumer Psychology. doi: 10.1016/j.jcps.2016.10.001
   Web of Science ®Google Scholar
• Park, D., & Han, I. (2008). Integrating conflicting reviews : Attributional hypotheses of consumer response to information uncertainty Depending on prior brand attitude. Proceedings of the 41st Hawaii International Conference on system Sciences – 2008 (pp. 1–10).
   Google Scholar
• Penz, E., Hogg, M. K., & Hogg, M. K. (2011). The role of mixed emotions in consumer behaviour: Investigating ambivalence in consumers’ experiences of approach-avoidance conflicts in online and offline settings. European Journal of Marketing, 45(1), 104–132. doi: 10.1108/03090561111095612
   Web of Science ®Google Scholar
• Petty, R. E., Cacioppo, J. T., & Schumann, D. (1983). Central and peripheral routes to advertising effectiveness: The moderating role of involvement. Journal of Consumer Research, 10, 135–146. doi: 10.2307/2488919
   Web of Science ®Google Scholar
• Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. doi: 10.1037/0021-9010.88.5.879
   PubMed Web of Science ®Google Scholar
• Prashar, P. (2018). The impact of online reviews on the hospitality industry. hospitalitynet. Retrieved from https://www.hospitalitynet.org/opinion/4078144.html
   Google Scholar
• Priester, J., & Petty, R. (1996). The gradual threshold model of ambivalence: Relating the positive and negative bases of attitudes to subjective ambivalence.. Journal of Personality and Social Psychology, 71(3), 431–449.
   PubMed Web of Science ®Google Scholar
• Prislin, R., & Christensen, P. N. (2005). Social change in the aftermath of successful minority influence. European Review of Social Psychology, 16, 43–73. doi: 10.1080/10463280440000071
   Google Scholar
• Purnawirawan, N., Pelsmacker, P. D., & Dens, N. (2012). Balance and sequence in online reviews: How perceived usefulness affects attitudes and intentions. Journal of Interactive Marketing, 26(4), 244–255. doi: 10.1016/j.intmar.2012.04.002
   Web of Science ®Google Scholar
• Riketta, M., & Ziegler, R. (2007). Self-ambivalence and reactions to success versus failure. European Journal of Social Psychology, 37(3), 547–560. doi: 10.1002/ejsp.376
   Web of Science ®Google Scholar
• Rudolph, T., & Popp, E. (2007). An information processing theory of ambivalence. Political Psychology, 28(5), 563–585. doi: 10.1111/j.1467-9221.2007.00590.x
   Web of Science ®Google Scholar
• Ruiz-mafe, C., Chatzipanagiotou, K., & Curras-perez, R. (2018). The role of emotions and conflicting online reviews on consumers’ purchase intentions. Journal of Business Research, 89, 336–344. doi: 10.1016/j.jbusres.2018.01.027
   Web of Science ®Google Scholar
• Shen, X., Kem, Z., & Sesia, Z. (2015). Herd behavior in consumers’ adoption of online reviews. Journal of the Association for Information Science and Technology, 14(4), 90–103. doi: 10.1002/asi
   Google Scholar
• Tabachnick, B. G., Fidell, L. S., & Osterlind, S. J. (2001). Using multivariate statistics. New York: Pearsons. Retrieved from http://www.sciepub.com/reference/181550
   Google Scholar
• Taheri, B., Gannon, J., & Kesgin, M. (2019). Visitors’ perceived trust in sincere, authentic, and memorable heritage experiences. The Service Industries Journal, 1–21. doi: 10.1080/02642069.2019.1642877
   Web of Science ®Google Scholar
• Tajfel, H. (1972). Social identity and intergroup behaviour. Socius: Sociological Research for a Dynamic World, 13(2), 65–93. doi: 10.1177/053901847401300204
   Google Scholar
• Tan, H., Lv, X., Liu, X., & Gursoy, D. (2018). Evaluation nudge: Effect of evaluation mode of online customer reviews on consumers’ preferences. Tourism Management, 65, 29–40. doi: 10.1016/j.tourman.2017.09.011
   Web of Science ®Google Scholar
• TravelChinaGuide. (2015). China tourism facts & figures. Retrieved from https://www.travelchinaguide.com/tourism/2018statistics/
   Google Scholar
• TravelChinaGuide. (2019). Where to stay in Beijing – 10 best areas & places. Retrieved from https://www.travelchinaguide.com/package/beijing/where-to-stay.htm
   Google Scholar
• Trumbo, C. (2002). Information processing and risk Perception: An adaptation of the heuristic-systematic model. Journal of Communication, 52(2), 367–382.
   Web of Science ®Google Scholar
• UNWTO. (2018). UNWTO / WTCF city tourism performance research.
   Google Scholar
• Vali, H., Xu, D., & Yildirim, M. (2015). Twenty-first Americas conference on information systems, Puerto Rico, 2015. The effect of conflicting consumer reviews on the accuracy of a purchase decision.
   Google Scholar
• Wang, H., Batra, R., & Chen, Z. (2015). The moderating role of dialecticism in consumer responses to product information. Journal of Consumer Psychology, 26(3), 381–394. doi: 10.1016/j.jcps.2015.10.003
   Web of Science ®Google Scholar
• Wiederhold, B. (2012). Social media is shifting power from advertisers to consumers. Cyberpsychology, Behavior, and Social Networking, 15, 577–578. doi: 10.1089/cyber.2012.1560
   PubMed Web of Science ®Google Scholar
• WTTC. (2018). Travel & tourism economic impact 2018 world. Retrieved from https://www.wttc.org/
   Google Scholar
• Xiao, M., Wang, R., & Chan, S. (2018). Factors affecting YouTube influencer marketing credibility: A heuristic-systematic model. Journal of Media Business Studies, 2354, 1–26. doi: 10.1080/16522354.2018.1501146
   Google Scholar
• Xinhua. (2019). Beijing receives more overseas tourists in 2018. Chinadaily.com.cn. Retrieved from http://www.chinadaily.com.cn/a/201902/06/WS5c5a9295a3106c65c34e8447.html
   Google Scholar
• Yang, J., Kim, W., & Amblee, N. (2012). The heterogeneous effect of WOM on product sales: Why the effect of WOM valence is mixed? European Journal of Marketing, 46, 1523–1538. doi: 10.1108/03090561211259961
   Web of Science ®Google Scholar
• Yang, S., Shin, S., Joun, Y., & Koo, C. (2017). Exploring the comparative importance of online hotel reviews’ heuristic attributes in review helpfulness: A conjoint analysis approach. Journal of Travel and Tourism Marketing, 34(7), 963–985. doi: 10.1080/10548408.2016.1251872
   Web of Science ®Google Scholar
• Yang, L., & Unnava, H. R. (2016a). Ambivalence, selective exposure, and negativity effect. Psychology & Marketing, 33(5), 331–343. doi: 10.1002/mar
   Web of Science ®Google Scholar
• Yang, L., & Unnava, H. R. (2016b). Tipping the purchase With external cues: Influencing the behaviors of ambivalent consumers with Contextual Primes. Journal of Marketing Theory and Practice, 24(4), 442–461. doi: 10.1080/10696679.2016.1205451
   Web of Science ®Google Scholar
• Yao, E., Fang, R., Dineen, B., & Yao, X. (2009). Effects of customer feedback level and (in)consistency on new product acceptance in the click-and-mortar context. Journal of Business Research, 62(12), 1281–1288. doi: 10.1016/j.jbusres.2008.12.008
   Web of Science ®Google Scholar
• Zhang, W., & Watts, S. A. (2008). Capitalizing on content: Information adoption in two online communities. Journal of the Association for Information Systems, 9. Retrieved from https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1432&context=jais
   Web of Science ®Google Scholar
• Zhang, K. Z. K., Zhao, S. J., Cheung, C. M. K., & Lee, M. K. O. (2014). Examining the influence of online reviews on consumers’ decision-making: A heuristic-systematic model. Decision Support Systems, 67, 78–89. doi: 10.1016/j.dss.2014.08.005
   Web of Science ®Google Scholar