Abstract
User-generated videos (UGVs) are popular in the e-business context. Product-related information in UGVs greatly facilitates online transactions. This study aims to investigate the mechanism of audience information processing in online video scenarios. Drawing on elaboration likelihood model, this study proposed an antecedent model for the perceived helpfulness of video-based online reviews from the perspective of audiences’ involvement. In addition, the features of the Danmu are acted as moderating variables, moderating the choice of route by influencing the audience's involvement. The results were obtained by an online survey. Results from partial least squares structural equation modeling (PLS-SEM) indicate that video content (i.e., media richness, perceived expertise, and emotional appeal) and video source (i.e., emotional trust, physical attractiveness, and vocal attractiveness) positively influence its perceived helpfulness and the features of Danmu (i.e., emotional intensity and content similarity) moderate the relationships both positively and negatively. This study provides theoretical contributions from several perspectives and practical implications to marketers.
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References
Aghakhani, N., O. Oh, D.G. Gregg, and J. Karimi. 2020. Online review consistency matters: An elaboration likelihood model perspective. Information Systems Frontiers. https://doi.org/10.1007/s10796-020-10030-7.
Alsharo, M., C. Sibona, and Y. Alnsour. 2016. Online video reviews helpfulness: Exploratory Study. In Twenty-second Americas conference on information systems. http://www.researchgate.net/publication/326305112_Online_Video_Reviews_Helpfulness_Exploratory_Study.
Bae, S., and T. Lee. 2011. Product type and consumers’ perception of online consumer reviews. Electronic Markets 21 (4): 255–266. https://doi.org/10.1007/s12525-011-0072-0.
Bansal, H.S., and P.A. Voyer. 2000. Word-of-mouth processes within a services purchase decision context. Journal of Service Research. https://doi.org/10.1177/109467050032005.
Biswas, B., P. Sengupta, and B. Ganguly. 2021. Your reviews or mine? Exploring the determinants of “perceived helpfulness” of online reviews: A cross-cultural study. Electronic Markets. https://doi.org/10.1007/s12525-020-00452-1.
Berger, Charles R., and Kathy Kellermann. 1989. Personal opacity and social information gathering: Explorations in strategic communication. Communication Research. https://doi.org/10.1177/009365089016003002.
Brooke, M.E., and S.H. Ng. 1986. Language and social influence in small conversational groups. Journal of Language & Social Psychology 5 (3): 201–210. https://doi.org/10.1177/0261927x8600500303.
Chen, C.-D., Q. Zhao, and J.-L. Wang. 2022. How livestreaming increases product sales: Role of trust transfer and elaboration likelihood model. Behaviour & Information Technology 41 (3): 558–573. https://doi.org/10.1080/0144929X.2020.1827457.
Chen, G., and S. Zhou. 2020. Loneliness assuaged: Eye-tracking an audience watching barrage videos. Journal of Visualized Experiments 159: 61089. https://doi.org/10.3791/61089.
Chen, G., S. Zhou, and T. Zhi. 2019. Viewing mechanism of lonely audience: Evidence from an eye movement experiment on barrage video. Computers in Human Behavior 101: 327–333. https://doi.org/10.1016/j.chb.2019.07.025.
Cheng, H. 2019. Freedom and carnival: Cultural communication strategy of Danmu video: A case study of bilibili website. Today’s Media 27 (2): 136–138.
Chih, W.-H., D.-K. Liou, and L.-C. Hsu. 2015. From positive and negative cognition perspectives to explore e-shoppers’ real purchase behavior: An application of tricomponent attitude model. Information Systems and E-Business Management 13 (3): 495–526. https://doi.org/10.1007/s10257-014-0249-0.
Cornelia, P., and D.W. Stewart. 1990. The effects of comparative advertising on attention, memory, and purchase intentions. Journal of Consumer Research 17 (2): 180–191. https://doi.org/10.1086/208548.
Daft, R.L., and R.H. Lengel. 1986. Organizational information requirements, media richness and structural design. Management Science 32 (5): 554–571. https://doi.org/10.1287/mnsc.32.5.554.
DeGroot, T., and S. Motowidlo. 1999. Why visual and vocal interview cues can affect interviewers’ judgments and predict job performance. Journal of Applied Psychology - J APPL PSYCHOL 84: 986–993. https://doi.org/10.1037/0021-9010.84.6.986.
Dion, K., E. Berscheid, and E. Walster. 1972. What is beautiful is good. Journal of Personality and Social Psychology 24 (3): 285–290. https://doi.org/10.1037/H0033731.
Diwanji, V.S., and J. Cortese. 2020. Contrasting user generated videos versus brand generated videos in ecommerce. Journal of Retailing and Consumer Services 54: 102024. https://doi.org/10.1016/j.jretconser.2019.102024.
Djamasbi, S., A. Hall-Phillips, Z. Liu, W. Li, and J. Bian. 2016. Social viewing, bullet screen, & user experience: A first look. In 2016 49th Hawaii international conference on system sciences (HICSS), 648–657.
Doney, P.M., and J.P. Ca Nnon. 1997. An examination of the nature of trust in buyer–seller relationships. Journal of Marketing 61 (2): 35–51. https://doi.org/10.2307/1251829.
Eagly, A.H., R.D. Ashmore, M.G. Makhijani, and L.C. Longo. 1991. What is beautiful is good, but …: A meta-analytic review of research on the physical attractiveness stereotype. Psychological Bulletin 110 (1): 109–128. https://doi.org/10.1037/0033-2909.110.1.109.
Escalas, J.E., and B.B. Stern. 2003. Sympathy and empathy: Emotional responses to advertising dramas. Journal of Consumer Research 29 (4): 566–578. https://doi.org/10.1086/346251.
Folkes, V.S. 1988. Recent attribution research in consumer behavior: A review and new directions. Journal of Consumer Research 4: 548–565. https://doi.org/10.1086/209135.
Gang, R., and H. Taeho. 2018. Examining the relationship between specific negative emotions and the perceived helpfulness of online reviews. Information Processing & Management 56 (4): 1425–1438. https://doi.org/10.1016/j.ipm.2018.04.003.
Gao, X., X.-Y. Xu, S.M.U. Tayyab, and Q. Li. 2021. How the live streaming commerce viewers process the persuasive message: An ELM perspective and the moderating effect of mindfulness. Electronic Commerce Research and Applications 49: 101087. https://doi.org/10.1016/j.elerap.2021.101087.
Gefen, D., and D.W. Straub. 2004. Consumer trust in B2C e-commerce and the importance of social presence: Experiments in e-products and e-services. Omega 32 (6): 407–424. https://doi.org/10.1016/j.omega.2004.01.006.
Gozegir, Ö., and A. Gocer. 2018. YouTube marketing: Examining the impact of user-generated-content sponsorship. International Journal of Marketing, Communication and New Media 6 (11): 7–30.
Haghirian, P., M. Madlberger, and A. Tanuskova. 2005. Increasing advertising value of mobile marketing—an empirical study of antecedents. Hawaii International Conference on System Sciences. https://doi.org/10.1109/HICSS.2005.311.
Hair, J.F., Jr., Lucy M. Matthews, Ryan L. Matthews, and Marko Sarstedt. 2017. PLS-SEM or CB-SEM: Updated guidelines on which method to use. International Journal of Multivariate Data Analysis 1 (2): 107–123.
Hall, Judith A. 1980. Voice tone and persuasion. Journal of Personality & Social Psychology 38 (6): 924–934. https://doi.org/10.1037/0022-3514.38.6.924.
Hao, X., S. Xu, and X. Zhang. 2019. Barrage participation and feedback in travel reality shows: The effects of media on destination image among Generation Y. Journal of Destination Marketing & Management 12: 27–36. https://doi.org/10.1016/j.jdmm.2019.02.004.
Henseler, J., Ringle, C.M. and Sarstedt, M. 2015. A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science 43: 115–135. https://doi.org/10.1007/s11747-014-0403-8.
Hsieh, J.-K., Y.-C. Hsieh, and Y.-C. Tang. 2012. Exploring the disseminating behaviors of eWOM marketing: Persuasion in online video. Electronic Commerce Research 12 (2): 201–224. https://doi.org/10.1007/s10660-012-9091-y.
Hsu, C., J. Chuan-Chuan Lin, and H. Chiang. 2013. The effects of blogger recommendations on customers’ online shopping intentions. Internet Research: Electronic Networking Applications and Policy 23 (1): 69–88. https://doi.org/10.1108/10662241311295782.
Huang, J.L., P.G. Curran, J. Keeney, E.M. Poposki, and R.P. Deshon. 2012. Detecting and deterring insufficient effort responding to surveys. Journal of Business & Psychology 27 (1): 99–114. https://doi.org/10.1007/s10869-011-9231-8.
Komiak, S.Y.X., and I. Benbasat. 2006. The effects of personalization and familiarity on trust and adoption of recommendation agents. MIS Quarterly 30 (4): 941–960. https://doi.org/10.1080/14639230600991726.
Krishnan, H.S., and D. Chakravarti. 2003. A process analysis of the effects of humorous advertising executions on brand claims memory. Journal of Consumer Psychology 13 (3): 230–246. https://doi.org/10.1207/S15327663JCP1303_05.
Kuan, H.H., and G.W. Bock. 2007. Trust transference in brick and click retailers: An investigation of the before-online-visit phase. Information & Management 44 (2): 175–187. https://doi.org/10.1016/j.im.2006.12.002.
Kuan, K., K.-L. Hui, P. Prasarnphanich, and H.-Y. Lai. 2015. What makes a review voted an empirical investigation of review voting in online review systems. Journal of the Association for Information Systems 16 (1): 48–71. https://doi.org/10.17705/1jais.00386.
Lee, D., K. Hosanagar, and H.S. Nair. 2018. Advertising content and consumer engagement on social media: Evidence from Facebook. Social Science Electronic Publishing 64 (11): 1–56. https://doi.org/10.2139/ssrn.2290802.
Lee, J., and I.B. Hong. 2016. Predicting positive user responses to social media advertising: The roles of emotional appeal, informativeness, and creativity. International Journal of Information Management 36 (3): 360–373. https://doi.org/10.1016/j.ijinfomgt.2016.01.001.
Lee, M., C. Cheung, and Z. Chen. 2007. Understanding user acceptance of multimedia messaging services: An empirical study. Journal of the American Society for Information Ence & Technology 58 (13): 2066–2077. https://doi.org/10.1002/asi.v58:13.
Leguina, A. 2015. A primer on partial least squares structural equation modeling (PLS-SEM). International Journal of Research & Method in Education 38 (2): 220–221. https://doi.org/10.1080/1743727X.2015.1005806.
Li, H., H. Liu, and Z. Zhang. 2020. Online persuasion of review emotional intensity: A text mining analysis of restaurant reviews. International Journal of Hospitality Management 89: 102558. https://doi.org/10.1016/j.ijhm.2020.102558.
Lim, K.H., and I. Benbasat. 2000. The effect of multimedia on perceived equivocality and perceived usefulness of information systems. MIS Quarterly 24 (3): 449–471. https://doi.org/10.2307/3250969.
Liou, D.K., W.H. Chih, L.C. Hsu, and C.Y. Huang. 2016. Investigating information sharing behavior: The mediating roles of the desire to share information in virtual communities. Information Systems and E-Business Management 14 (2): 187–216. https://doi.org/10.1007/s10257-015-0279-2.
Liu, Y., and R. Du. 2019. The effects of image-based online reviews on customers’ perception across product type and gender. Journal of Global Information Management 27 (3): 139–158. https://doi.org/10.4018/JGIM.2019070108.
Maclachlan, J., and M.H. Siegel. 1980. Reducing the costs of TV commercials by use of time compressions. Journal of Marketing Research 17 (1): 52–57. https://doi.org/10.1177/002224378001700106.
Mayer, R.E. 2009. Multimedia learning. Cambridge: Cambridge University Press.
Mcginnies, E., and C.D. Ward. 1980. Better liked than right trustworthiness and expertise as factors in credibility. Personality & Social Psychology Bulletin 6 (3): 467–472. https://doi.org/10.1177/014616728063023.
Meng, Y., H. Wang, and L. Zheng. 2018. Impact of online word-of-mouth on sales: The moderating role of product review quality. New Review of Hypermedia & Multimedia. https://doi.org/10.1080/13614568.2018.1460403.
Mobius, M., and T. Rosenblat. 2010. Why beauty matters. Staff General Research Papers Archive 96: 222–235.
Molina, L. M., Lloréns-Montes, J., Ruiz-Moreno, A. 2007. Relationship between quality management practices and knowledge transfer. Journal of Operations Management 25 (3): 682–701. https://doi.org/10.1016/j.jom.2006.04.007.
Ni, Y. 2017. A study of Danmaku Video on attention allocation, social presence, transportation to narrative, cognitive workload and enjoyment. Syracuse: Syracuse University.
Niu, J., Li, S., Mo, S., Yang, S., and Fan, B. 2018. Affective Content Analysis of Online Video Clips with Live Comments in Chinese. 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation. (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI).
Nunnally, J. C. 1994. Psychometric theory 3E. Tata McGraw-hill education.
Paivio, Allan. 1991. Dual coding theory: Retrospect and current status. Canadian Journal of Psychology 45 (3): 255–287. https://doi.org/10.1037/h0084295.
Park, C., and T.M. Lee. 2009. Antecedents of online reviews’ usage and purchase influence: an empirical comparison of U.S. and Korean Consumers. Journal of Interactive Marketing 23 (4): 332–340. https://doi.org/10.1016/j.intmar.2009.07.001.
Park, C.W., and S.M. Young. 1986. Consumer response to television commercials: The impact of involvement and background music on brand attitude formation. Journal of Marketing Research 23 (1): 11–24. https://doi.org/10.2307/3151772.
Petty, R., and J. Cacioppo. 1981. Issue involvement as a moderator of the effects on attitude of advertising content and context. Advances in Consumer Research 8: 20–24.
Petty, R.E., and J.T. Cacioppo. 1986. Communication and persuasion: Central and peripheral routes to attitude change. The American Journal of Psychology. https://doi.org/10.2307/1422805.
Petty, R.E., J.T. Cacioppo, and S. David. 1983. Central and peripheral routes to advertising effectiveness: The moderating role of involvement. Journal of Consumer Research 10 (2): 135–146. https://doi.org/10.1086/208954.
Podsakoff, P.M., S.B. MacKenzie, J.-Y. Lee, and N.P. Podsakoff. 2003. Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology 88: 879–903. https://doi.org/10.1037/0021-9010.88.5.879.
Rempel, J.K., J.G. Holmes, and M.D. Zanna. 1985. Trust in close relationships. Journal of Personality & Social Psychology. https://doi.org/10.1037/0022-3514.49.1.95.
Riding, D., D. Lonsdale, and B. Brown. 2006. The effects of average fundamental frequency and variance of fundamental frequency on male vocal attractiveness to women. Journal of Nonverbal Behavior 30 (2): 55–61. https://doi.org/10.1007/s10919-006-0005-3.
Spotts, H.E., M.G. Weinberger, and A.L. Parsons. 2013. Assessing the use and impact of humor on advertising effectiveness: A contingency approach. Journal of Advertising 26 (3): 17–32. https://doi.org/10.1080/00913367.1997.10673526.
Sprott, M.D.E. 2004. THE POWER OF REFLECTION: An empirical examination of nostalgia advertising effects. Journal of Advertising 33 (3): 25–35. https://doi.org/10.1080/00913367.2004.10639165.
Srivastava, V., and A.D. Kalro. 2019. Enhancing the helpfulness of online consumer reviews: The role of latent (content) factors. Journal of Interactive Marketing 48: 33–50. https://doi.org/10.1016/j.intmar.2018.12.003.
Street, R.L., Jr. 1984. Speech convergence and speech evaluation in fact-finding interviews. Human Communication Research. https://doi.org/10.1111/j.1468-2958.1984.tb00043.x.
Sun, P.C., and H.K. Cheng. 2007. The design of instructional multimedia in e-Learning: A Media Richness Theory-based approach. Computers & Education 49 (3): 662–676. https://doi.org/10.1016/j.compedu.2005.11.016.
Sundar, S.S., Sriram Kalyanaraman, and Justin Brown. 2003. Explicating web site interactivity: Impression formation effects in political campaign sites. Communication Research. https://doi.org/10.1177/0093650202239025.
Tsang, M.M., S.-C. Ho, and T.-P. Liang. 2004. Consumer attitudes toward mobile advertising: An empirical study. International Journal of Electronic Commerce 8 (3): 65–78.
Tsao, W.-C., and M.-T. Hsieh. 2015. eWOM persuasiveness: Do eWOM platforms and product type matter? Electronic Commerce Research 15 (4): 509–541. https://doi.org/10.1007/s10660-015-9198-z.
Tseng, C.H. 2019. The efficiency of mobile media richness across different stages of online consumer behavior. International Journal of Information Management 50 (February): 353–364. https://doi.org/10.1016/j.ijinfomgt.2019.08.010.
Vilnai-Yavetz, I., and S. Gilboa. 2010. The effect of servicescape cleanliness on customer reactions. Services Marketing Quarterly 31 (2): 213–234. https://doi.org/10.1080/15332961003604386.
Wang, L., Z. Guo, G. Zhang, and X. Xu. 2022. Effective destination user-generated advertising: Matching effect between goal framing and self-esteem. Tourism Management 92: 104557. https://doi.org/10.1016/j.tourman.2022.104557.
Wang, M., L.L. Sun, and J.D. Hou. 2021. How emotional interaction affects purchase intention in social commerce: The role of perceived usefulness and product type. Psychology Research and Behavior Management 14: 467–481. https://doi.org/10.2147/PRBM.S301286.
Wang, X., J. Guo, Y. Wu, and N. Liu. 2019. Emotion as signal of product quality: Its effect on purchase decision based on online customer reviews. Internet Research 30 (2): 463–485. https://doi.org/10.1108/INTR-09-2018-0415.
Wang, X., and D. Liang. 2019. The effect of the number of Danmu and the emotional intensity of Danmu on the popularity of videos. Journal of Marketing Science 15 (2): 132–156.
Weathers, D., S. Sharma, and S.L. Wood. 2007. Effects of online communication practices on consumer perceptions of performance uncertainty for search and experience goods. Journal of Retailing 83 (4): 393–401. https://doi.org/10.1016/j.jretai.2007.03.009.
Webster, J., and J.S. Ahuja. 2006. Enhancing the design of web navigation systems: The influence of user disorientation on engagement and performance. MIS Quarterly 30 (3): 661–678. https://doi.org/10.2307/25148744.
Xiao, L., L. Luo, and T. Ke. 2022. The influence of eWOM information structures on consumers’ purchase intentions. Electronic Commerce Research. https://doi.org/10.1007/s10660-022-09576-2.
Xie, F., N. Donthu, R. Lohtia, and T. Osmonbekov. 2004. Emotional appeal and incentive offering in banner advertisements. Journal of Interactive Advertising 4: 30–37. https://doi.org/10.1080/15252019.2004.10722085.
Xie, K.L., Z. Zhang, Z. Zhang, A. Singh, and S.K. Lee. 2016. Effects of managerial response on consumer eWOM and hotel performance. International Journal of Contemporary Hospitality Management 28 (9): 2013–2034. https://doi.org/10.1108/IJCHM-06-2015-0290.
Xu, D., T. Chen, J. Pearce, Z. Mohammadi, and P.L. Pearce. 2021. Reaching audiences through travel vlogs: The perspective of involvement. Tourism Management 86: 104326. https://doi.org/10.1016/j.tourman.2021.104326.
Xu, P., L. Chen, and R. Santhanam. 2015. Will video be the next generation of e-commerce product reviews? Presentation format and the role of product type. Decision Support Systems 73: 85–96. https://doi.org/10.1016/j.dss.2015.03.001.
Xu, P. 2018. A study on the effect of emotional intensity of negative online reviews on consumers' purchase intention. Guangdong: Guangdong University of Foreign Studies.
Xu, Y., Z. Zhang, R. Law, and J. Zhang. 2021. Effects of online reviews and managerial responses from a review manipulation perspective. Current Issues in Tourism 23: 2207–2222. https://doi.org/10.1080/13683500.2019.1626814.
Xiang, Z., Du, Q., Ma, Y., & Fan, W. 2017. A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism. Tourism Management 58:51–65. https://doi.org/10.1016/j.tourman.2016.10.001
Yang, S., C. Zhou, and Y. Chen. 2021. Do topic consistency and linguistic style similarity affect online review helpfulness? An elaboration likelihood model perspective. Information Processing & Management 58 (3): 102521. https://doi.org/10.1016/j.ipm.2021.102521.
Yang, T., F. Yang, and J. Men. 2021. The impact of Danmu technological features on consumer loyalty intention toward recommendation vlogs: A perspective from social presence and immersion. Information Technology & People. https://doi.org/10.1108/ITP-01-2021-0008.
Yeh, W.-C., C.-C. Lee, C. Yu, P.-S. Wu, J.-Y. Chang, and J.-H. Huang. 2021. The impact of the physical attractiveness and intellectual competence on loyalty. Sustainability 12 (10): 39–70. https://doi.org/10.3390/su12103970.
Zaichkowsky, J.L. 1994. The personal involvement inventory: Reduction, revision, and application to advertising. Journal of Advertising 23 (4): 59–70. https://doi.org/10.1080/00913367.1943.10673459.
Zhang, L.-T., and D. Cassany. 2020. Making sense of danmu: Coherence in massive anonymous chats on Bilibili.com. Discourse Studies 22 (4): 483–502. https://doi.org/10.1177/1461445620940051.
Zhang, N. 2015. Analysis of Danmu culture in the perspective of Bakhtin’s carnival theory. Today’s Massmedia 10: 121–122.
Zhao, X., L. Wang, X. Guo, and R. Law. 2015. The influence of online reviews to online hotel booking intentions. International Journal of Contemporary Hospitality Management 27 (6): 1343–1364. https://doi.org/10.1108/IJCHM-12-2013-0542.
Zheng, C.D., Q. Han, and H. Wang. 2015. How the network’s water army speech can influence your purchase intention. Nankai Business Review 18 (1): 89–97.
Zhou, W., and W. Duan. 2016. Do Professional reviews affect online user choices through user reviews? An empirical study. Journal of Management Information Systems 33 (1): 202–228. https://doi.org/10.2139/ssrn.2396069.
Zuckerman, M., and R.E. Driver. 1989. What sounds beautiful is good: The vocal attractiveness stereotype. Journal of Nonverbal Behavior 13 (2): 67–82. https://doi.org/10.1007/BF00990791.
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This work was supported by the National Natural Science Foundation of China [Grant Numbers 71671121, 72171165]; the Chinese Ministry of Education of Humanities and Social Science Fund, Beijing [grant number 21YJA630021]; and the Tianjin City Philosophy and Social Science Planning Project [grant number TJGL17-011] which are gratefully acknowledged.
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Guo, J., Gou, S. & Li, W. Helpful advertising messages reach consumers through user-generated videos: an empirical study from the audience involvement perspective. J Market Anal (2022). https://doi.org/10.1057/s41270-022-00194-3
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DOI: https://doi.org/10.1057/s41270-022-00194-3