Perbedaan Intensi untuk Melakukan Electronic Word of Mouth pada Program Rumah BUMN Telkom Indonesia
Article Sidebar
Read Counter : 2
Download : 0
Main Article Content
Abstract
Telkom Indonesia can leverage e-WOM to enhance its reputation through the Rumah BUMN CSR program. However, there has been a low level of e-WOM activity on Instagram and noticeable differences among MSME-fostered groups members in providing feedback to the company. This study aims to identify whether there are differences in the intention to Electronic Word of Mouth among the members of Telkom's MSME-fostered groups on the Instagram platform @telkomindonesia. This research uses a quantitative method with the Kruskal-Wallis Test to compare e-WOM intentions among the MSME-fostered groups. The findings reveal differences in the intention to engage in Electronic Word of Mouth among the members of Telkom's MSME-fostered groups —Go Modern, Go Digital, Go Online, and Go Global—on the Instagram platform @telkomindonesia in terms of Intensity, Emotional Value, and Content Quality. These results align with the Concept of Individual Differences, which states that each individual has different abilities to respond and react to stimuli. Behavioral intention reflects an individual's attitude that influences their willingness to act, such as sharing positive information through e-WOM.
Telkom Indonesia dapat memanfaatkan e-WOM untuk meningkatkan reputasi melalui program CSR Rumah BUMN. Namun, ditemukan adanya e-WOM yang rendah dalam media sosial Instagram serta adanya perbedaan antar anggota kelompok UMKM dalam hal pemberian feedback terhadap perusahaan. Tujuan: Tujuan dari penelitian ini untuk mengetahui ada/tidaknya perbedaan intensi untuk melakukan Electronic Word of Mouth di antara anggota kelompok UMKM Binaan Telkom dalam media sosial Instagram @telkomindonesia. Penelitian ini menggunakan metode kuantitatif dengan Uji Kruskal-Wallis untuk membandingkan niat e-WoM di antara anggota kelompok UMKM binaan. Hasil penelitian menunjukkan bahwa terdapat perbedaan intensi untuk melakukan Electronic Word of Mouth di antara anggota kelompok UMKM Binaan Telkom Go Modern, Go Digital, Go Online, dan Go Global dalam media sosial Instagram @telkomindonesia pada aspek Intensitas, Nilai Emosional, dan Isi Konten. Temuan ini sejalan dengan Konsep Individual Differences, yang menyatakan bahwa Setiap individu memiliki perbedaan dalam kemampuan merespons dan bereaksi terhadap stimulus. Niat berperilaku (behavioral intention) mencerminkan sikap individu yang memengaruhi kemauan seseorang untuk bertindak, misalnya menyebarkan informasi positif melalui e-WoM.
Article Details
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
This work is licensed under a Prologia Creative Commons Attribution-ShareAlike 4.0 International License.References
Andersen, C. A., Carnagey, N. L., & Eubanks, J. (2003). Exposure to Violent Media: The Effects of Songs with Violent Lyrics on Aggressive Thoughts and Feelings. Journal of Personality and Social Psychology, 84(5), 960–971. https://doi.org/10.1037/0022-3514.84.5.960
Ayu Kusumawati, D. (2022). Peran Digital Skill dan Workforce Transformation Terhadap Kinerja UMKM.
Bansal, H. S., & Voyer, P. A. (2000). Word-of-Mouth Processes within a Services Purchase Decision Context. Journal of Service Research, 3(2), 166–177. https://doi.org/10.1177/109467050032005
Bayu, D. J. (2020). Survei Google: 49% Perempuan Indonesia Telah Berwirausaha. Katadata. https://databoks.katadata.co.id/ekonomi-makro/statistik/bb19a0289aa233b/survei-google-49-perempuan-indonesia-telah-berwirausaha
Brown, J., Broderick, A. J., & Lee, N. (2007). Word of mouth communication within online communities: Conceptualizing the online social network. Journal of Interactive Marketing, 21(3), 2–20. https://doi.org/10.1002/dir.20082
Campbell, D. T., & Stanley, J. C. (1963). Experimental and Quasi-Experimental Designs For Research. Houghton Mifflin Company.
Catino, M., & Patriotta, G. (2013). Learning from Errors: Cognition, Emotions and Safety Culture in the Italian Air Force. Organization Studies, 34(4), 437–467. https://doi.org/10.1177/0170840612467156
Chang, H.-J. (2006). Determination of sample size in using central limit theorem for Weibull distribution. In Article in International Journal of Information and Management Sciences. https://www.researchgate.net/publication/267021000
Farnell, P., & Kowalczyk, D. (2023). Quasi-Experimental Design | Definition, Types & Examples. Study.Com.
Forster, J. J. (2001). Sample Surveys: Nonprobability Sampling. In International Encyclopedia of the Social & Behavioral Sciences (pp. 13467–13470). Elsevier. https://doi.org/10.1016/B0-08-043076-7/00499-X
Galloway, A. (2005). Non-Probability Sampling. In Encyclopedia of Social Measurement (pp. 859–864). Elsevier. https://doi.org/10.1016/B0-12-369398-5/00382-0
Generasi Muda yang Berkualitas Tinggi Berperan Penting dalam Pertumbuhan Ekonomi di Era Society 5.0. (2022). https://doi.org/https://ekon.go.id/publikasi/detail/3913/generasi-muda-yang-berkualitas-tinggi-berperan-penting-dalam-pertumbuhan-ekonomi-di-era-society-50
Goyette, I., Ricard, L., Bergeron, J., & Marticotte, F. (2010). e‐WOM Scale: word‐of‐mouth measurement scale for e‐services context. Canadian Journal of Administrative Sciences / Revue Canadienne Des Sciences de l’Administration, 27(1), 5–23. https://doi.org/10.1002/cjas.129
Hasibuan, L. (2022). 65% UMKM RI Dikelola Perempuan, Tapi Ini Masalahnya. CNBCIndonesia. https://www.cnbcindonesia.com/lifestyle/20220922175954-33-374277/65-umkm-ri-dikelola-perempuan-tapi-ini-masalahnya
Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004a). 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. https://doi.org/10.1002/dir.10073
Jensen, A. R. (2002). Galton’s legacy to research on intelligence. Journal of Biosocial Science, 34(2), 145–172. https://doi.org/10.1017/s0021932002001451
Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59–68. https://doi.org/10.1016/j.bushor.2009.09.003
Kashima, Y., & Kashima, E. S. (1988). Individual differences in the predictions of behavioral intentions. Journal of Social Psychology, 128(6), 711–720. https://doi.org/10.1080/00224545.1988.9924551
Landy, F. J., & Conte, J. M. (2013). Work in the 21st century: An Introduction to Industrial and Organizational Psychology (4th ed., Vol. 27). Wiley. https://doi.org/https://doi.org/10.2307/2521637
Lee, M., Jeong, M., & Lee, J. (2017). Roles of negative emotions in customers’ perceived helpfulness of hotel reviews on a user-generated review website. International Journal of Contemporary Hospitality Management, 29(2), 762–783. https://doi.org/10.1108/IJCHM-10-2015-0626
Matzler, K., Bidmon, S., & Grabner-Kräuter, S. (2006). Individual determinants of brand affect: The role of the personality traits of extraversion and openness to experience. Journal of Product and Brand Management, 15(7), 427–434. https://doi.org/10.1108/10610420610712801
Memon, M. A., Ting, H., Cheah, J. H., Thurasamy, R., Chuah, F., & Cham, T. H. (2020). Sample size for survey research: Review and recommendations. Journal of Applied Structural Equation Modeling, 4(2), i–xx. https://doi.org/10.47263/jasem.4(2)01
Peran Platform Digital Terhadap Pengembangan UMKM di Indonesia. (2024).
Reza Jalilvand, M., & Samiei, N. (2012). The effect of electronic word of mouth on brand image and purchase intention. Marketing Intelligence & Planning, 30(4), 460–476. https://doi.org/10.1108/02634501211231946
Robinson, P. (2012). Abilities to Learn: Cognitive Abilities. In Encyclopedia of the Sciences of Learning. Springer. https://doi.org/https://doi.org/10.1007/978-1-4419-1428-6
Rocklage, M. D., & Fazio, R. H. (2014). Individual differences in valence weighting: When, how, and why they matter. Journal of Experimental Social Psychology, 50(1), 144–157. https://doi.org/10.1016/j.jesp.2013.09.013
Rummel, R. J. (1976). Intentions, Attitudes, And Interests. SagePublication. https://www.hawaii.edu/powerkills/TCH.REF.HTM
Ryan, A. M., & Sackett, P. R. (2012). Individual Differences: Challenging Our Assumptions. In The Oxford Handbook of Organizational Psychology (Vol. 1). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199928309.013.0005
Serra Cantallops, A., & Salvi, F. (2014). New consumer behavior: A review of research on eWOM and hotels. International Journal of Hospitality Management, 36, 41–51. https://doi.org/10.1016/j.ijhm.2013.08.007
Stanton, S. J., Kim, J., Thor, J. C., & Deng, X. (2019). Incentivized methods to generate electronic word-of-mouth: Implications for the resort industry. International Journal of Hospitality Management, 78, 142–149. https://doi.org/10.1016/j.ijhm.2018.11.004
Sun, J., Song, S., House, D., & Kwon, M. (2019). Role of gender differences on individuals’ responses to electronic word-of-mouth in social interactions. Applied Economics, 51(28), 3001–3014. https://doi.org/10.1080/00036846.2018.1564015
Vo, T. T., Xiao, X., & Ho, S. Y. (2019). How Does Corporate Social Responsibility Engagement Influence Word of Mouth on Twitter? Evidence from the Airline Industry. Journal of Business Ethics, 525–542. https://doi.org/10.1007/s10551-017-3679-z
Wolf, C., Joye, D., Smith, T. W., & Fu, Y. (Eds.). (2016). The SAGE Handbook of Survey Methodology. SAGE Publications Ltd. https://methods.sagepub.com/book/the-sage-handbook-of-survey-methodology