The rapid rise of live streaming commerce in China has transformed the retail environment, with electronic word-of-mouth (eWOM) emerging as a pivotal factor in shaping consumer behavior. As a digital evolution of traditional word-of-mouth, eWOM gains particular significance in live streaming contexts, where real-time interactions foster immediacy and engagement. This study investigates how eWOM influences consumer purchase intentions within Chinese live streaming platforms, employing the Information Adoption Model (IAM) as theoretical framework. Using a grounded theory approach, this research applies NVivo for data coding and analysis to explore the cognitive and emotional processes triggered by eWOM during live streaming. Findings indicate that argument quality, source credibility, and information quantity significantly enhance consumer trust and perceived usefulness of information, which, in turn, drives information adoption and purchase intention. Furthermore, the study reveals that social interaction between live streaming anchors and audiences amplifies the influence of consumers’ internal states on information adoption. This study enhances the Information Adoption Model (IAM) by introducing social interaction as a moderator between consumers’ internal states toward live streaming eWOM and their adoption of information, highlighting the value of social interaction in live streaming. It also incorporates information quantity, showing how eWOM quantity affects trust and perceived usefulness. Furthermore, the study contributes to exploring how factors like argument quality, source credibility, and information quantity shape consumer trust and perceived usefulness, offering insights into the cognitive and emotional processes of information adoption in live streaming.

Ajzen, I. (1985). From Intentions to Actions: A Theory of Planned Behavior. In J. Kuhl, & J. Beckman, Action control: From cognition to behavior. (pp. 11-39). Heidelberg, Germany: Springer.

Ajzen, I. (1991). The Theory of Planned Behavior. Organizational behavior and human decision processes, 50(2), pp. 179-211.

Bhattacherjee, A. (2012). Social science research: Principles, methods, and practices. Tampa: University of South Florida.

Bhattacherjee, A., & Sanford, C. (2006). Influence processes for information technology acceptance: An elaboration likelihood model. MIS Quartely, 30(4), 805-825.

Bulut, Z. A., & Karabulut, A. N. (2018). Examining the role of two aspects of eWOM in online repurchase intention: An integrated trust–loyalty perspective. Journal of Consumer Behaviour, 17(4), 407-417. doi:10.1002/cb.1721

Campbell, J. L., Quincy, C., Osserman, J., & Pedersen, O. K. (2013). Coding in-depth semi-structured interviews: Problems of unitization and intercoder reliability and agreement. Sociological Methods & Research, 294-320.

Charmaz, K. (2006). Constructing Grounded Theory: A Practical Guide through Qualitative Analysis. London: Sage.

Chen, C., & Lin, Y. (2018). What drives live-stream usage intention? The perspectives of flow, entertainment, social interaction, and endorsement. Telematics and Informatics, 35(1), pp. 293-303. Retrieved from http://dx.doi.org/10.1016/j.tele.2017.12.003

Cheung, C., & Thadani, D. (2012). The Impact of Electronic Word-of-Mouth Communication: A Literature Analysis and Integrative Model. Decision Support System, 54(1), 461-470.

Cheung, C., Lee, M., & 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. doi:10.1108/10662240810883290

Cheung, M., Luo, C., Sia, C., & Chen, H. (2009). Credibility of Electronic Word-of-Mouth: Informational and Normative Determinants of On-line Consumer Recommendations. International Journal of Electronic Commerce, 13(4), 9-38.

CINNIC. (2024). The 53th Statistical Reports on Internet Development in China. China Internet Network Information Center.

Cohen, J. (1960). A Coefficient Of Agreement For Nominal Scales. Educational and psychological measurement, 37-46.

Cohen, L., Manion, L., & Morrison, K. (2000). Research Methods. Routledge.

Corbin, J., & Strauss, A. (2014). Basics of qualitative research: Techniques and procedures for developing grounded theory. (4th ed.). Sage publications.

Creswell, J. W., & Poth, C. N. (2013). Qualitative Inquiry and Research Design: Choosing Among Five Approaches. Thousand Oaks: Sage.

Eagly, A. H., & Chaiken, S. (1993). The Psychology of Attitudes. Harcourt Brace Jovanovich College Publishers.

Erkan, I., & Evans, C. (2016). The influence of eWOM in social media on consumers’ purchase intentions: An extended approach to information adoption. Computers in Human Behavior, 61, 47-55.

Erkan, I., & Evans, C. (2018). Social media or shopping websites? The influence of eWOM on consumers’ online purchase intentions. Journal of Marketing Communications, 24(6), 617-632.

Fan, Y.-W., Miao, Y.-F., Fang, Y.-H., & Lin, R.-Y. (2013). Establishing the Adoption of Electronic Word-of-Mouth through Consumers’ Perceived Credibility. International Business Research, 6(3), 58-65. doi:10.5539/ibr.v6n3p58

Filieri, R., Mcleay, F., Tsui, B., & Lin, Z. (2018). Consumer perceptions of information helpfulness and determinants of purchase intention in online consumer reviews of services. Information and Management, 55(8), 956-970. doi:https://doi.org/10.1016/j.im.2018.04.010

Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Canada: Addison-Wesley Publishing Company.

Glaser, G. B., Strauss, L. A., & Strutzel, E. (1968). The discovery of grounded theory; strategies for qualitative research. Nursing research, 17(4), p. 364.

Guest, G., Bunce, A., & Johnson, L. (2006). How many interviews are enough? An experiment with data saturation and variability. Field methods, 18(1), 59-82.

Hennig-Thurau, T., Gwinner, K. P., & Gremler, D. 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.

Hu, M., & Chaudhry, S. (2020). Enhancing Consumer Engagement in E-commerce Live Streaming via Relational Bonds. Internet Research, 30(3), 1019-1041. doi:10.1108/INTR-03-2019-0082

Huang, T., Chen, W., Chen, C., & Silalahi, A. K. (2022). Understanding How Product Reviews on YouTube Affect Consumers’ Purchase Behaviors in Indonesia: An Exploration Using the Stimulus-Organism-Response Paradigm. Human Behavior and Emerging Technologies, 1-19.

Hussain, S., Ahmed, W., Jafar, R., Rabnawaz, A., & Yang, J. (2017). eWOM source credibility, perceived risk and food product customer’s information adoption. Computers in Human Behavior, 66, 96-102.

Johnston, L. (2006). Software and method: Reflections on teaching and using QSR NVivo in doctoral research. International Journal of Social Research Methodology, 9(5), pp. 379-391. doi:10.1080/13645570600659433

Khwaja, M., & Zaman, U. (2020). Configuring the evolving role of eWOM on the consumers information adoption. Journal of Open Innovation: Technology, Market, and Complexity, 6(4), 1-13.

King, A. R., Racherla, P., & Bush, V. D. (2014). What we know and don’t know about online word-of-mouth: A review and synthesis of the literature. Journal of Interactive Marketing, 167-183.

Landis, J., & Koch, G. (1977). The Measurement of Observer Agreement for Categorical Data. Biometrics, 159-174.

Lee, C., & Chen, C. (2021). Impulse buying behaviors in live streaming commerce based on the stimulus-organism-response framework. Information, 12(6), pp. 1-17.

Leong, C., Loi, M. A., & Woon, S. (2021). The influence of social media eWOM information on purchase intention. Journal of Marketing Analytics.

Li, Y., & Liu, C. (2019). The power of coworkers in service innovation: the moderating role of social interaction. International Journal of Human Resource Management, 30(12), 1956-1976.

Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic Inquiry. United Kindom: Sage Publications.

Liu, C., Sun, K., & Liu, L. (2023). The Formation and Transformation Mechanisms of Deep Consumer Engagement and Purchase

Luo, X., Lim, W., Cheah, J.-h., Lim, X.-j., & Dwivedi, Y. (2023). Live Streaming Commerce: A Review and Research Agenda Live Streaming Commerce: A Review and Research Agenda. Journal of Computer Information Systems, 1-25.

Metzger, M. J., Flanagin, A. J., Eyal, K., Lemus, D. R., & Mccann, R. M. (2003). Credibility for the 21st Century: Integrating Perspectives on Source, Message, and Media Credibility in the Contemporary Media Environment. Annals of the International Communication Association, 293-335.

Ming, J., Zeng, J., Bilal, M., Akram, U., & Fan, M. (2021). How social presence influences impulse buying behavior in live streaming commerce? The role of S-O-R theory. International Journal of Web Information Systems, 17(4), 300-320. doi:10.1108/IJWIS-02-2021-0012

Ohanian, R. (1990). Construction and validation of a scale to measure celebrity endorsers’ perceived expertise, trustworthiness and attractiveness. Journal of Advertising, 19(3), 39-52. doi:https://doi.org/10.1080/00913367.1990.10673191

Ou, X. (2024, April 5). Market size of live streaming e-commerce in China from 2019 to 2023 with estimates until 2026. Retrieved from statista: https://www.statista.com/statistics/1127635/china-market-size-of-live-commerce/

Ou, X. (2024, February 27). Distribution of leading livestreaming e-commerce platforms’ gross merchandise in China in 2022, by platform. Retrieved from statista: https://www.statista.com/statistics/1339406/china-market-share-of-leading-live-commerce-platforms/

Ou, X. (2024, July 22). Kuaishou’s gross merchandise value (GMV) of live streaming commerce in China from 2018 to 2023. Retrieved from statisa: https://www.statista.com/statistics/1273678/china-live-commerce-gmv-of-kuaishou/

Ou, X. (2024, September 27). statista. Retrieved from Number of live-commerce service users in China from 2020 to 2023(in millions): https://www.statista.com/statistics/1301256/china-number-of-live-commerce-users/

Park, M., & Lennon, S. J. (2009). Brand name and promotion in online shopping contexts. Journal of Fashion Marketing and Management, 149-160.

Petty, R., & Cacioppo, J. (1986). The elaboration likelihood model of persuasion. Advances in Experimental Social Psychology, 19(C), 123-205. doi:10.1016/S0065-2601(08)60214-2

Phillips, M., & Lu, J. (2018). A quick look at NVivo. Journal of Electronic Resources Librarianship, 104-106.

Shen, W., Hu, Y. J., & Ulmer, J. (2015). Competing for Attention: An Empirical Study of Online Reviewers’ Strategic Behavior. MIS Quarterly, 39(3), 683-696.

Steuer, J. (1992). Defining Virtual Reality: Dimensions Determining Telepresence. Journal of Communication, 42(4), 73-93.

Strauss, A. L. (1987). Qualitative analysis for social scientists. Cambridge university press.

Sun, Y., Shao, X., Li, X., Guo, Y., & Nie, K. (2019). How live streaming influences purchase intentions in social commerce: An IT affordance perspective. Electronic Commerce Research and Applications, 37, 100886. doi:10.1016/j.elerap.2019.100886

Sundar, S. (2012). Social psychology of interactivity in human-website interaction. Oxford Handbook of Internet Psychology, 1-18.

Sussman, S. W., & Siegal, W. S. (2003). Informational influence in organizations: An integrated approach to knowledge adoption. Information systems research, 14(1), 47-65. doi:10.1287/isre.14.1.47.14767

TechNode. (2024, January 4). Douyin reports 256% growth in sales from local life services. Retrieved from TechNode: https://technode.com/2024/01/04/douyin-reports-256-growth-in-sales-from-local-life-services/

Tien, D., Amaya Rivas, A., & Liao, Y. (2019). Examining the influence of customer-to-customer electronic word-of-mouth on purchase intention in social networking sites. Asia Pacific Management Review, 24(3), 238-249. doi:10.1016/j.apmrv.2018.06.003

Verma, D., Prakash, P., Behl, A., & Dwivedi, Y. K. (2023). Computers in Human Behavior Understanding the impact of eWOM communication through the lens of information adoption model: A meta-analytic structural equation modeling perspective. Computers in Human Behavior, 1-16.

Wongkitrungrueng, A., & Assarut, N. (2018). The role of live streaming in building consumer trust and engagement with social commerce sellers. Journal of Business Research, 117, 543-556. doi:https://doi.org/10.1016/j.jbusres.2018.08.032

Wongkitrungrueng, A., Dehouche, N., & Assarut, N. (2020). Live streaming commerce from the sellers’ perspective: implications for online relationship marketing. Journal of Marketing Management, 36(5-6), 488-519. Retrieved from https://doi.org/10.1080/0267257X.2020.1748895

Wu, W., Lin, C., Hsu, B., & Yeh, R. (2009). Interpersonal trust and knowledge sharing: Moderating effects of individual altruism and a social interaction environment. Social Behavior and Personality, 37(1), 83-94.

Xiao, L., Guo, F., Yu, F., & Liu, S. (2019). The effects of online shopping context cues on consumers’ purchase intention for cross-border E-Commerce sustainability. Sustainability, 11(10), 1-24.

Xin, B., Hao, Y., & Xie, L. (2023). Strategic product showcasing mode of E-commerce live streaming. Journal of Retailing and Consumer Services, 1-20.

Yen, Y. (2018). Route factors influencing trust and attitude toward TV shopping. Service Industries Journal, 7-8, pp. 402-430. Retrieved from https://doi.org/10.1080/02642069.2017.1393525

Zhang, M., Liu, Y., Wang, Y., & Zhao, L. (2022). How to retain customers: Understanding the role of trust in live streaming commerce with a socio-technical perspective. Computers in Human Behavior, 1-14.

Zhang, M., Qin, F., Wang, G. A., & Luo, C. (2020). The impact of live video streaming on online purchase intention. The Service Industries Journal, 40(9-10), 656-681. doi:https://doi.org/10.1080/02642069.2019.1576642

Zhu, D. H., Chang, Y. P., & Luo, J. J. (2016). Understanding the influence of C2C communication on purchase decision in online communities from a perspective of information adoption model. Telematics and Informatics, 33(1), 8-16. doi:10.1016/j.tele.2015.06.001