Issue

Vol. 12 No. 2 (2025): December

Date Log

Submitted
21 March 2025
Accepted
5 September 2025
Published
21 September 2025

Copyright (c) 2025 Azade Asadi Damavandi, Hyacinth Balediata Bangero, Ghazale Asadi Damavandi (Author)

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The Influence of E-Wom on the Users’ Purchase Decision of M-Learning Apps

https://doi.org/10.24252/minds.v12i2.56216
Azade Asadi Damavandi
Bowling Green State University, Iran, Islamic Republic of
https://orcid.org/0000-0001-7999-5933
Hyacinth Balediata Bangero
Bowling Green State University; University of San Agustin, Philippines
https://orcid.org/0009-0007-9487-4639
Ghazale Asadi Damavandi
Boston University, Iran, Islamic Republic of

Corresponding Author(s) : Hyacinth Balediata Bangero

[email protected]

Jurnal Minds: Manajemen Ide dan Inspirasi, Vol. 12 No. 2 (2025): December

Abstract

This study examines the influence of electronic word-of-mouth (e-WOM) on information adoption and purchase intentions in mobile learning (M-learning) applications. By extending the Information Adoption Model (IAM) to an educational technology context, it contributes theoretically to understanding how digital peer communication shapes technology uptake. A survey of 345 Iranian young adults reveals that e-WOM significantly affects adoption decisions, with perceived usefulness emerging as a central driver of purchase intentions. The findings underscore the dual role of positive and negative user reviews in shaping app reputation and credibility. Beyond its contextual focus on Iran, where app usage is restricted, the study advances research on e-WOM dynamics in digital learning ecosystems of developing countries. The results provide practical insights for marketers, developers, and educational institutions seeking to leverage user-generated content to enhance trust, strengthen credibility, and foster wider acceptance of M-learning solutions.

Keywords

e-WOM Purchase intention m-Learning apps Information Adoption Model
Damavandi, A. A., Bangero, H., & Damavandi, G. A. (2025). The Influence of E-Wom on the Users’ Purchase Decision of M-Learning Apps. Jurnal Minds: Manajemen Ide Dan Inspirasi, 12(2), 463–474. https://doi.org/10.24252/minds.v12i2.56216
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX
References
  1. Aghakhani, N., Oh, O., Gregg, D., & Jain, H. (2022). How review quality and source credibility interacts to affect review usefulness: An expansion of the elaboration likelihood model. Information Systems Frontiers, 25(4), 1513-1531. https://doi.org/10.1007/s10796-022-10299-w
  2. Ajzen, I., & Fishbein, M. (1975). A Bayesian analysis of attribution processes. Psychological Bulletin, 82(2), 261-277. https://doi.org/10.1037/h0076477
  3. Alsheikh, D. H., Abd Aziz, N., & Alsheikh, L. H. (2021). The impact of electronic word of mouth on tourists visit intention to Saudi Arabia: Argument quality and source credibility as mediators. African Journal of Hospitality, Tourism and Leisure, 10(4)(10(4)), 1152-1168. https://doi.org/10.46222/ajhtl.19770720.154
  4. Anastasiei, B., Dospinescu, N., & Dospinescu, O. (2021). Understanding the adoption of Incentivized word-of-Mouth in the online environment. Journal of Theoretical and Applied Electronic Commerce Research, 16(4), 992-1007. https://doi.org/10.3390/jtaer16040056
  5. Asadi Damavandi, A., & Ha, L. (2024). E–WOM and app stores in Iran: How online reviews influence purchase intention of paid mobile apps. Journal of Islamic Marketing. https://doi.org/10.1108/jima-02-2024-0069
  6. Bangero, H. B. (2023). EPuzsolved: Learning communication models through interactive online puzzles. Communication Teacher, 38(2), 95-101. https://doi.org/10.1080/17404622.2023.2288349
  7. Bhandari, M., & Pan, P. (2022). Underlying mechanisms of brand feedback's mixed effects in e-Commerce: Roles of perceived controllability, stability, and brand trust. Cyberpsychology, Behavior, and Social Networking, 25(9), 605-612. https://doi.org/10.1089/cyber.2021.0352
  8. Bhattacherjee, & Sanford. (2006). Influence processes for information technology acceptance: An elaboration likelihood model. MIS Quarterly, 30(4), 805. https://doi.org/10.2307/25148755
  9. Bickart, B., & Schindler, R. M. (2001). Internet forums as influential sources of consumer information. Journal of Interactive Marketing, 15(3), 31. https://doi.org/10.1002/dir.1014.abs
  10. Bilal, M., Jianqiu, Z., Dukhaykh, S., Fan, M., & Trunk, A. (2021). Understanding the effects of eWOM antecedents on online purchase intention in China. Information, 12(5), 192. https://doi.org/10.3390/info12050192
  11. Caudill, J. G. (2007). The growth of M-learning and the growth of mobile computing: Parallel developments. The International Review of Research in Open and Distance Learning, 8(2), 1-13. https://doi.org/10.19173/irrodl.v8i2.348
  12. Chan, Y. Y., & Ngai, E. (2011). Conceptualising electronic word of mouth activity. Marketing Intelligence & Planning, 29(5), 488-516. https://doi.org/10.1108/02634501111153692
  13. Cheung, R. (2014). The influence of electronic word-of-Mouth on information adoption in online customer communities. Global Economic Review, 43(1), 42-57. https://doi.org/10.1080/1226508x.2014.884048
  14. Damavandi, A. G., Mohammmadkazemi, R., & Mojtaba, D. S. (2022). The impact of social media marketing on brand equity considering the mediating role of brand experience and social media benefits. Journal of International Business and Management, 5(12), 1-12. https://doi.org/10.37227/aricon-jibm-2022-11-6739
  15. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008
  16. E-Learning Center. (2019, January 25). Mobile learning in 2019: Complete guide to mLearning. Retrieved August 26, 2019, from https://www.e-learningcentre.co.uk/mlearning
  17. Filieri, R. (2015). 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. https://doi.org/10.1016/j.jbusres.2014.11.006
  18. Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & 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. https://doi.org/10.1002/dir.10073
  19. Hsu, C., & Lin, J. C. (2008). Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation. Information & Management, 45(1), 65-74. https://doi.org/10.1016/j.im.2007.11.001
  20. Hussain, A., O.C. Mkpojiogu, E., & Hassan, F. (2018). Dimensions and sub-dimensions for the evaluation of M-learning apps for children: A review. International Journal of Engineering & Technology, 7(3.20), 291. https://doi.org/10.14419/ijet.v7i3.20.19168
  21. Ismail, H. A. (2016). Intention to use smartphone through perceived compatibility, perceived usefulness, and perceived ease of use. Jurnal Dinamika Manajemen, 7(1), 1. https://doi.org/10.15294/jdm.v7i1.5748
  22. Kaushal, R. K., Bhardwaj, R., Kumar, N., Aljohani, A. A., Gupta, S. K., Singh, P., & Purohit, N. (2022). Using mobile computing to provide a smart and secure Internet of things (IoT) framework for medical applications. Wireless Communications and Mobile Computing, 2022, 1-13. https://doi.org/10.1155/2022/8741357
  23. Kemp, S. (2023, February 13). The state of digital in Iran in 2023. Datareportal. https://datareportal.com/reports/digital-2023-iran
  24. Korucu, A. T., & Alkan, A. (2011). Differences between M-learning (mobile learning) and E-lEarning, basic terminology and usage of M-learning in education. Procedia - Social and Behavioral Sciences, 15, 1925-1930.
  25. https://doi.org/10.1016/j.sbspro.2011.04.029
  26. Lecinski, J. (2011). Winning the zero moment of truth: ZMOT. Zero Moment of Truth.
  27. Liao, Y., Wu, W., Le, T. Q., & Phung, T. T. (2022). The integration of the technology acceptance model and value-based adoption model to study the adoption of E-learning: The moderating role of e-WOM. Sustainability, 14(2), 815. https://doi.org/10.3390/su14020815
  28. Miedany, Y. E. (2018). e-Learning, adaptive learning and mobile learning. In Rheumatology teaching: The art and science of medical education (pp. 235-258). Springer. https://link.springer.com/chapter/10.1007/978-3-319-98213-7_13
  29. Oh, J., Koh, B., & Raghunathan, S. (2015). Value appropriation between the platform provider and app developers in mobile platform mediated networks. Journal of Information Technology, 30(3), 245-259. https://doi.org/10.1057/jit.2015.21
  30. Oliveira, T., & Martins, M. F. (2011). Literature review of information technology adoption models at firm level. Electronic Journal of Information Systems Evaluation, 14(1), 110-121. https://academic-publishing.org/index.php/ejise/article/view/389/352
  31. O'Malley, C., Vavoula, G., Glew, J., Taylor, J., Sharples, M., & Lefrere, P. (2003). Guidelines for learning/teaching/tutoring in a mobile environment. http://www.mobilearn.org/download/results/guidelines.pdf
  32. Park, D., Lee, J., & Han, I. (2007). The effect of on-line consumer reviews on consumer purchasing intention: The moderating role of involvement. International Journal of Electronic Commerce, 11(4), 125-148. https://doi.org/10.2753/jec1086-4415110405
  33. Petty, R. E., Fabrigar, L. R., & Wegener, D. T. (2002). Emotional factors in attitudes and persuasion. In R. J. Davidson, K. R. Scherer, & H. H. Goldsmith (Eds.), Handbook of affective sciences (pp. 752-772). Oxford University Press.
  34. Petty, R. E., Cacioppo, J. T., & Goldman, R. (1981). Personal involvement as a determinant of argument-based persuasion. Journal of Personality and Social Psychology, 41(5), 847-855. https://doi.org/10.1037//0022-3514.41.5.847
  35. Petty, R. E., & Cacioppo, J. T. (1986). The elaboration likelihood model of persuasion. In Advances in Experimental Social Psychology (pp. 123-205). Elsevier. https://doi.org/10.1016/S0065-2601(08)60214-2
  36. PocketGamer. (2019, January 30). Low CPI and high ARPU: Iran, the fastest growing mobile apps market in the Middle East.
  37. https://www.pocketgamer.biz/asia/comment-and-opinion/69914/low-cpi-and-high-aru-iran-the-fastest-growing-mobile-apps-market-in-the-middle-east/
  38. Rahaman, M. A., Hassan, H. M., Asheq, A. A., & Islam, K. M. (2022). The interplay between eWOM information and purchase intention on social media: Through the lens of IAM and TAM theory. PLOS ONE, 17(9), e0272926. https://doi.org/10.1371/journal.pone.0272926
  39. Reichelt, J., Sievert, J., & Jacob, F. (2013). How credibility affects eWOM reading: The influences of expertise, trustworthiness, and similarity on utilitarian and social functions. Journal of Marketing Communications, 20(1-2), 65-81. https://doi.org/10.1080/13527266.2013.797758
  40. Roy, S. (2017). App adoption and switching behavior: Applying the extended tam in smartphone app usage. Journal of Information Systems and Technology Management, 14(2), 239-261. https://doi.org/10.4301/s1807-17752017000200006
  41. Salehi-Esfahani, S., Ravichandran, S., Israeli, A., & Bolden III, E. (2016). Investigating information adoption tendencies based on restaurants’ user-generated content utilizing a modified information adoption model. Journal of Hospitality Marketing & Management, 25(8), 925-953. https://doi.org/10.1080/19368623.2016.1171190
  42. Sardar, A., Manzoor, A., Shaikh, K. A., & Ali, L. (2021). An empirical examination of the impact of eWOM information on young consumers’ online purchase intention: Mediating role of eWOM information adoption. SAGE Open, 11(4), 215824402110525. https://doi.org/10.1177/21582440211052547
  43. Sharples, M. (2006). Big issues in mobile learning. HAL Open Science. https://telearn.hal.science/hal-00190254/document
  44. Song, B. L., Liew, C. Y., Sia, J. Y., & Gopal, K. (2021). Electronic word-of-mouth in travel social networking sites and young consumers’ purchase intentions: An extended information adoption model. Young Consumers, 22(4), 521-538. https://doi.org/10.1108/yc-03-2021-1288
  45. Sotiriadis, M. D., & Van Zyl, C. (2013). Electronic word-of-mouth and online reviews in tourism services: The use of Twitter by tourists. Electronic Commerce Research, 13(1), 103-124. https://doi.org/10.1007/s10660-013-9108-1
  46. StatCounter Global Stats. (2023). Mobile operating system market share Islamic Republic of Iran. https://gs.statcounter.com/os-market-share/mobile/iran#mobile_os_combined-IR-mobile_os_combined-IRmobile_os_combined–bar-bar
  47. Statista. (2024). Forecasted expenditure on advanced education technology worldwide from 2018 to 2025.
  48. https://www-statista-com/statistics/1085930/edtech-expenditure-forecast/
  49. Statista. (2024). Size of the global e-learning market in 2019 and 2026. https://www.statista.com/topics/3115/e-learning-and-digital-education/
  50. Sussman, S. W., & Siegal, W. S. (2003). Informational influence in organizations: An integrated approach to knowledge adoption. Information Systems Research, 14(1), 47-65. https://doi.org/10.1287/isre.14.1.47.14767
  51. Talwar, S., Dhir, A., Scuotto, V., & Kaur, P. (2021). Barriers and paradoxical recommendation behaviour in online to offline (O2O) services. A convergent mixed-method study. Journal of Business Research, 131, 25-39. https://doi.org/10.1016/j.jbusres.2021.03.049
  52. Tien, D. H., Amaya Rivas, A. 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. https://doi.org/10.1016/j.apmrv.2018.06.003
  53. Todoranova, L., & Penchev, B. (2019). International Conference Information and Communication Technologies in Business and Education. University of Economics - Varna. https://ue-varna.bg/uploads/filemanager/303/publishing-complex/2019/Information_communication_technologies_business_education_2019.pdf#page=188
  54. Tuten, T. L. (2023). Social media marketing (5th ed.). SAGE.
  55. Vo, T. H., & Wu, K. (2022). Exploring consumer adoption of mobile shopping apps from a perspective of elaboration likelihood model. International Journal of E-Services and Mobile Applications, 14(1), 1-18. https://doi.org/10.4018/ijesma.296577
  56. 90-121. http://llt.msu.edu/vol8num3/wang/
  57. Wang, Y. (2016). Information adoption model, a review of the literature. Journal of Economics, Business and Management, 4(11), 618-622. DOI: 10.18178/joebm.2016.4.11.462
  58. Yang, F. X. (2017). Effects of restaurant satisfaction and knowledge sharing motivation on eWOM intentions. Journal of Hospitality & Tourism Research, 41(1), 93-127. https://doi.org/10.1177/1096348013515918
Read More

Author Biographies

Azade Asadi Damavandi, Bowling Green State University

Azade has a bachelor’s in electrical engineering from Islamic Azad University and a master’s in Entrepreneurship from the University of Tehran. She is currently a PhD student in Media and Communication at BGSU. Her research interest is New Media, Marketing Communication, and Technological Communication.
She worked in accelerator and startup as a mentor and cofounder.

Hyacinth Balediata Bangero, Bowling Green State University; University of San Agustin

Hyacinth Bangero is a PhD candidate in Media and Communication at Bowling Green State University. Her research interests include government and political communication, social media influencers, Generative AI, marketing, and family communication. Hyacinth has published in journals such as Government Information Quarterly and Communication Teacher and has presented her work at both national and international conferences. She is a Fulbright scholar from the Philippines and an Assistant Professor at the University of San Agustin in Iloilo City, Philippines.

Download
PDF
Statistic
Read Counter : 0 Download : 0