The Effect of MWOM Through the WhatsApp Platform Toward Customers Purchase Intention

Itsna Salsabila; Annisa Rahmani Qastharin

Itsna Salsabila
Annisa Rahmani Qastharin

Abstract

The rapid growth of technology has transformed conventional word of mouth (WOM) into Electronic Word of Mouth (eWOM). E-WOM on mobile devices is known as Electronic Word of Mouth Mobile Messaging Application (MWOM), such as WhatsApp, Facebook Messenger, Line, and WeChat. Many researchers assess the eWOM, but there's very little research about the MWOM. In fact, it's a big opportunity to do MWOM marketing strategies, especially on WhatsApp, which is the most popular media chat application in Indonesia. However, the SYFO company has not yet been effective with its MWOM WhatsApp marketing. This study aims to study the case of the SYFO company by identifying the MWOM factor through WhatsApp toward customer purchase intention and giving recommendations to optimize the MWOM. The researchers assessed nine variables, and a total of 119 respondents were chosen. With quantitative methods, the data gained from a survey through a questionnaire. The collected data will then be analyzed using the PLS-SEM feature in SmartPLS 4.0. The results show that information usefulness can have an effect on information adoption. Then, information adoption can have an effect on purchase intention (mobile purchase intention, offline purchase intention, and social purchase intention). Unexpectedly, attitude toward information cannot have an effect on offline purchase intention. The SYFO company or another company with a similar background may use the results of the analysis of this research to gain insight and implement the findings within the company.

References

APJII. (2022). Indonesian Internet Profile 2022. Retrieved from https://www.dns.net.id/identik_sedot.php?file=Survei%20Profil%20Internet%20Indonesia%202022.pdf&id=34
Badan Pusat Statistik, (2023) ‘Jumlah Rumah Tangga Menurut Kabupaten/Kota di Provinsi Jawa Barat (Rumah Tangga), 2021-2023’, BPS Provinsi Jawa Barat. Available at: https://jabar.bps.go.id/indicator/12/131/1/jumlah-rumah-tangga-menurut-kabupaten-kota-di-provinsi-jawa-barat.html (Accessed: May 10, 2023).
Ding, L., Velicer, W. F., & Harlow, L. L. (1995). Effects of estimation methods, number of indicators per factor, and improper solutions on structural equation modeling fit indices. Structural Equation Modeling: A Multidisciplinary Journal, 2(2), 119-143.
Elhadidy, D. Y. (2017). To investigate how eWOM affects young buyers purchasing decision in FMCGS. The Business and Management Review, 8(5), 252-257.
Erkan, I. (2014). Vine’: Do You Miss It? Electronic Word of Mouth on The Social Networking Site, Vine. International Journal of Business and Information, 9(4), 461-473.
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., Elwalda, A., Rahman, M., Doğan, S., & Nardali, S. (2019). Text me on WhatsApp, let us talk about brands! The power of mobile word of mouth on mobile purchase intention. International Journal of Internet Marketing and Advertising, 13(3), 218-234.
Field, A. (2009). Discovering Statistics Using SPSS (3rd ed.). Sage, London.
Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics.
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.
Hair Jr, J. F., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107-123.
Pentina, I., Basmanova, O., & Sun, Q. (2017). Message and source characteristics as drivers of mobile digital review persuasiveness: does cultural context play a role?. International Journal of Internet Marketing and Advertising, 11(1), 1-21.
Roy, G., Datta, B., & Mukherjee, S. (2019). Role of electronic word-of-mouth content and valence in influencing online purchase behavior. Journal of Marketing Communications, 25(6), 661-684.
Verhoef, M. J., & Casebeer, A. L. (1997). Broadening horizons: integrating quantitative and qualitative research. Canadian Journal of Infectious Diseases and Medical Microbiology, 8, 65-66.
Wang, N., Shen, X. L., & Sun, Y. (2013). Transition of electronic word-of-mouth services from web to mobile context: A trust transfer perspective. Decision support systems, 54(3), 1394-1403.
Wiedemann, D. G. (2007). Exploring the concept of mobile viral marketing through case study research. In MMS 2007: Mobilität und mobile informationssysteme–2nd conference of GI-Fachgruppe MMS. Gesellschaft für Informatik e. V.
Williams, C. (2007). Research methods. Journal of Business & Economics Research (JBER), 5(3).
Wong, K. K. K. (2013). Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing bulletin, 24(1), 1-32.
Yang, H., & Zhou, L. (2011). Extending TPB and TAM to mobile viral marketing: An exploratory study on American young consumers’ mobile viral marketing attitude, intent and behavior. Journal of Targeting, Measurement and Analysis for Marketing, 19, 85-98.
Zhang, J. Q., Craciun, G., & Shin, D. (2010). When does electronic word-of-mouth matter? A study of consumer product reviews. Journal of Busines