A Study on Adoption of Mobile Learning Apps (MLA) : Development of an Integrated Framework in a Multinational Context

Authors

  •   Ganesh Dash Assistant Professor, College of Administrative and Financial Sciences, Saudi Electronic University, Riyadh - 11673
  •   Syed Akmal Assistant Professor, College of Administrative and Financial Sciences, Saudi Electronic University, Riyadh - 11673
  •   Debarun Chakraborty Associate Professor, Symbiosis Institute of Business Management (SIBM), Nagpur, Constituent of Symbiosis International (Deemed University), Pune - 440 008, Maharashtra

DOI:

https://doi.org/10.17010/ijom/2023/v53/i5/172724

Keywords:

compatibility

, complexity, system quality, information quality, intention to adopt, intention to recommend, Saudi Arabia, India

Paper Submission Date

, January 10, 2023, Paper sent back for Revision, March 20, Paper Acceptance Date, March 30, Paper Published Online, May 15, 2023

Abstract

Purpose: In this study, we provided an integrated framework to assess the determinants of intention to adopt and recommend mobile learning apps (MLA) in an emerging economy context.

Methodology: We integrated diffusion of innovation (DOI) & DeLone and McLean’s information systems success model (D&M ISS Model). Four independent measures, compatibility, complexity, system quality, and information quality, were taken from the mentioned theories. Intention to adopt and intention to recommend are the dependent constructs. Intention to adopt also plays the role of mediator. Three hundred seventy-two participants from Saudi Arabia and India were included in the survey. Partial least squares (PLS) structural equation modeling (SEM) was used for the analysis.

Findings: The results suggested that all the antecedents influenced the intention to adopt and recommend except for compatibility. Compatibility affected adoption intention only. The intention to adopt had a substantial impact on the recommendation intention. It also successfully mediated all the proposed relationships. In addition, a multi-group analysis (MGA) was also conducted to have country-specific results.

Originality: We provided a new, comprehensive, and integrated model to assist learning app companies in implementing new technology. Two significant theories were integrated to provide a holistic and futuristic framework.

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Published

2023-05-01

How to Cite

Dash, G., Akmal, S., & Chakraborty, D. (2023). A Study on Adoption of Mobile Learning Apps (MLA) : Development of an Integrated Framework in a Multinational Context. Indian Journal of Marketing, 53(5), 8–24. https://doi.org/10.17010/ijom/2023/v53/i5/172724

Issue

Volume 53, Issue 5, May 2023

Section

Articles
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References

Akour, I. A., Al-Maroof, R. S., Alfaisal, R., & Salloum, S. A. (2022). A conceptual framework for determining metaverse adoption in higher institutions of gulf area: An empirical study using hybrid SEM-ANN approach. Computers and Education: Artificial Intelligence, 3, 100052. https://doi.org/10.1016/j.caeai.2022.100052

Al-Ansi, A., Olya, H. G., & Han, H. (2019). Effect of general risk on trust, satisfaction, and recommendation intention for halal food. International Journal of Hospitality Management, 83, 210–219. https://doi.org/10.1016/J.IJHM.2018.10.017

Aldholay, A., Abdullah, Z., Isaac, O., & Mutahar, A. M. (2020). Perspective of Yemeni students on use of online learning: Extending the information systems success model with transformational leadership and compatibility. Information Technology & People, 33(1), 106–128. https://doi.org/10.1108/ITP-02-2018-0095

Almaiah, M. A., Hajjej, F., Shishakly, R., Lutfi, A., Amin, A., & Awad, A. B. (2022). The role of quality measurements in enhancing the usability of mobile learning applications during COVID-19. Electronics, 11(13), 1951. https://doi.org/10.3390/electronics11131951

Althunibat, A., Almaiah, M. A., & Altarawneh, F. (2021). Examining the factors influencing the mobile learning applications usage in higher education during the covid-19 pandemic. Electronics, 10(21), 2676. https://doi.org/10.3390/electronics10212676

Arain, A. A., Hussain, Z., Rizvi, W. H., & Vighio, M. S. (2019). Extending UTAUT2 toward acceptance of mobile learning in the context of higher education. Universal Access in the Information Society, 18, 659–673. https://doi.org/10.1007/s10209-019-00685-8

Balaban, I., Mu, E., & Divjak, B. (2013). Development of an electronic portfolio system success model: An information systems approach. Computers & Education, 60(1), 396–411. https://doi.org/10.1016/j.compedu.2012.06.013

Basurra, S., & Bamansoor, S. (2021). Factors influencing students’ intention to use mobile learning: A study at Yemen higher education institutions. In, 2021 2nd International Conference on Smart Computing and Electronic Enterprise (ICSCEE) (pp. 206–211). https://doi.org/10.1109/ICSCEE50312.2021.9498251

Bharadwaj, S., & Deka, S. (2021). Behavioural intention towards investment in cryptocurrency: An integration of Rogers’ diffusion of innovation theory and the technology acceptance model. Forum Scientiae Oeconomia, 9(4), 137–159. https://www.ceeol.com/search/article-detail?id=1009152

Camilleri, M. A., & Camilleri, A. C. (2020). The students’ readiness to engage with mobile learning apps. Interactive Technology and Smart Education, 17(1), 28–38. https://doi.org/10.1108/ITSE-06-2019-0027

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 Distributed Learning, 8(2), 1–13. https://doi.org/10.19173/irrodl.v8i2.348

Chakraborty, D. (2018). Impact of celebrity endorsed advertisements on rural consumers’ purchase intention towards mobile SIM cards: A study conducted in West Bengal. Indian Journal of Marketing, 48(10), 52–63. https://doi.org/10.17010/ijom/2018/v48/i10/132335

Chakraborty, D. (2021). Factors influencing passengers’ purchase intention towards app-cab services in metro cities of India: A study on smartphone users. Indian Journal of Marketing, 51(1), 41–54. https://doi.org/10.17010/10.17010/ijom/2021/v51/i1/156933

Chakraborty, D. (2022). Purchase behavior of consumers toward GSAs: A longitudinal assessment. Journal of Computer Information Systems, 1–26. https://doi.org/10.1080/08874417.2022.2123065

Chakraborty, D., & Altekar, S. (2021a). Work from home (WFH), COVID-19, and its impact on women. Prabandhan: Indian Journal of Management, 14(9), 22–29. https://doi.org/10.17010/pijom/2021/v14i9/166294

Chakraborty, D., & Altekar, S. (2021b). What drives people to use grocery apps? The moderating & mediating role of customer involvement and trust. Indian Journal of Marketing, 51(11), 23–37. https://doi.org/10.17010/ijom/2021/v51/i11/166734

Chakraborty, D., & Dash, G. (2022). ‘The New Normal’ and the strategies of marketers to attract consumers. Indian Journal of Marketing, 52(1), 58–62. https://doi.org/10.17010/ijom/2022/v52/i1/167652

Chakraborty, D., Rana, N. P., Khorana, S., Singu, H. B., & Luthra, S. (2022). Big data in food: Systematic literature review and future directions. Journal of Computer Information Systems, 1–21. https://doi.org/10.1080/08874417.2022.2132428

Cheng, Y.-M. (2015). Towards an understanding of the factors affecting m-learning acceptance: Roles of technological characteristics and compatibility. Asia Pacific Management Review, 20(3), 109–119. https://doi.org/10.1016/j.apmrv.2014.12.011

Cheon, J., Lee, S., Crooks, S. M., & Song, J. (2012). An investigation of mobile learning readiness in higher education based on the theory of planned behavior. Computers & Education, 59(3), 1054–1064. https://doi.org/10.1016/j.compedu.2012.04.015

Corlett, D., Sharples, M., Bull, S., & Chan, T. (2005). Evaluation of a mobile learning organiser for university students. Journal of Computer Assisted Learning, 21(3), 162–170. https://doi.org/10.1111/j.1365-2729.2005.00124.x

Dash, G. (2022). Pandemic induced e-learning and the impact on the stakeholders: Mediating role of satisfaction and moderating role of choice. Athens Journal of Education, 10(1), 27–48. https://doi.org/10.30958/aje.10-1-2

Dash, G., & Chakraborty, D. (2021). Transition to e-learning: By choice or by force – A crosscultural and trans-national assessment. Prabandhan: Indian Journal of Management, 14(3), 8–23. https://doi.org/10.17010/pijom/2021/v14i3/158151

Dash, G., & Paul, J. (2021). CB-SEM vs. PLS-SEM methods for research in social sciences and technology forecasting. Technological Forecasting and Social Change, 173, 121092. https://doi.org/10.1016/j.techfore.2021.121092

Dash, G., Akmal, S., & Chakraborty, D. (2022). A study on adoption of e-health services: Developing an integrated framework in a multinational context. Indian Journal of Marketing, 52(5), 25–40. https://doi.org/10.17010/ijom/2022/v52/i5/169415

Dash, G., Akmal, S., Mehta, P., & Chakraborty, D. (2022). COVID-19 and e-learning adoption in higher education: A multi-group analysis and recommendation. Sustainability, 14(14), 8799. https://doi.org/10.3390/su14148799

Dash, G., Chakraborty, D., & Alhathal, F. (2022). Assessing repurchase intention of learning apps during COVID-19. Electronics, 11(9), 1309. https://doi.org/10.3390/electronics11091309

Dash, G., Kiefer, K., & Paul, J. (2021). Marketing-to-millennials: Marketing 4.0, customer satisfaction and purchase intention. Journal of Business Research, 122, 608–620. https://doi.org/10.1016/j.jbusres.2020.10.016

Dash, G., Sharma, K., & Yadav, N. (2023). The diffusion of mobile payments: Profiling the adopters and non-adopters, Roger’s way. Journal of Retailing and Consumer Services, 71, 103219. https://doi.org/10.1016/j.jretconser.2022.103219

DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9–30. https://doi.org/10.1080/07421222.2003.11045748

Drolia, M., Papadakis, S., Sifaki, E., & Kalogiannakis, M. (2022). Mobile learning applications for refugees: A systematic literature review. Education Sciences, 12(2), 96. https://doi.org/10.3390/educsci12020096

Edrees, M. E. (2013). Assessing eLearning systems success: An educators’ perspective. International Journal of Technology Diffusion (IJTD), 4(1), 56–67. https://doi.org/10.4018/jtd.2013010104

Gharaibeh, M. K., & Gharaibeh, N. K. (2020). An empirical study on factors influencing the intention to use mobile learning. Advances in Science, Technology and Engineering Systems Journal, 5(5), 1261–1265. https://doi.org/10.25046/aj0505151

Hair Jr., J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2010). Multivariate data analysis (7th ed.). Pearson.

Hamidi, H., & Chavoshi, A. (2018). Analysis of the essential factors for the adoption of mobile learning in higher education: A case study of students of the University of Technology. Telematics and Informatics, 35(4), 1053–1070. https://doi.org/10.1016/j.tele.2017.09.016

Henseler, J., Ringle, C. M., & 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

Hosany, S., Prayag, G., Van Der Veen, R., Huang, S. (Sam), & Deesilatham, S. (2017). Mediating effects of place attachment and satisfaction on the relationship between tourists’ emotions and intention to recommend. Journal of Travel Research, 56(8), 1079–1093. https://doi.org/10.1177/0047287516678088

Hsu, P.-F., Yen, H. R., & Chung, J.-C. (2015). Assessing ERP post-implementation success at the individual level: Revisiting the role of service quality. Information & Management, 52(8), 925–942. https://doi.org/10.1016/j.im.2015.06.009

Huang, H.-C. (2013). E-reading and e-discussion: EFL learners’ perceptions of an e-book reading program. Computer Assisted Language Learning, 26(3), 258–281. https://doi.org/10.1080/09588221.2012.656313

Kang, S., & Choi, H. (2018). The effect on intention to recommendation and satisfaction of communication type of service provider: Based on food-service industry. International Journal of Smart Business and Technology, 6(1), 31–38. https://doi.org/10.21742/ijsbt.2018.6.1.03

Kim, H.-J., Lee, J.-M., & Rha, J.-Y. (2017). Understanding the role of user resistance on mobile learning usage among university students. Computers & Education, 113, 108–118. https://doi.org/10.1016/j.compedu.2017.05.015

Lee, E.-Y., & Jeon, Y. J. (2020). The difference of user satisfaction and net benefit of a mobile learning management system according to self-directed learning: An investigation of cyber university students in hospitality. Sustainability, 12(7), 2672. https://doi.org/10.3390/su12072672

Lin, T. T., & Bautista, J. R. (2017). Understanding the relationships between mHealth apps’ characteristics, trialability, and mHealth literacy. Journal of Health Communication, 22(4), 346–354. https://doi.org/10.1080/10810730.2017.1296508

Lutfi, A., Saad, M., Almaiah, M. A., Alsaad, A., Al-Khasawneh, A., Alrawad, M., Alsyouf, A., & Al-Khasawneh, A. L. (2022). Actual use of mobile learning technologies during social distancing circumstances: Case study of King Faisal University Students. Sustainability, 14(12), 7323. https://doi.org/10.3390/su14127323

Maki, K., & Vishwanath, A. (2020). Discontinuance in fitness tracking apps: An analysis using a diffusion of innovations approach. Iowa Journal of Communication, 52(1), 107 – 125.

Malhotra, N. K., Kim, S. S., & Patil, A. (2006). Common method variance in IS research: A comparison of alternative approaches and a reanalysis of past research. Management Science, 52(12), 1865–1883. https://doi.org/10.1287/mnsc.1060.0597

Min, S., So, K. K., & Jeong, M. (2021). Consumer adoption of the Uber mobile application: Insights from diffusion of innovation theory and technology acceptance model. In, S. Kim & D. Wang (eds.), Future of tourism marketing (pp. 2–15). Routledge. https://doi.org/10.4324/9781003176039

Narayanan, N. (2023, January 8). Saudi Arabia set to overtake India as fastest-growing major economy this year. Arab News. https://www.arabnews.com/node/2228546/businesseconomy

Oh, Y. K., & Kim, J.-M. (2022). What improves customer satisfaction in mobile banking apps? An application of text mining analysis. Asia Marketing Journal, 23(4), Article 3. https://doi.org/10.53728/2765-6500.1581

Reychav, I., & Wu, D. (2016). The interplay between cognitive task complexity and user interaction in mobile collaborative training. Computers in Human Behavior, 62, 333–345. https://doi.org/10.1016/J.CHB.2016.04.007

Ringle, C. M., Wende, S., & Becker, J.-M. (2022). SmartPLS 4. Oststeinbek: SmartPLS GmbH. http://www.smartpls.com

Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.

Singh, N., Sinha, N., & Liébana-Cabanillas, F. J. (2020). Determining factors in the adoption and recommendation of mobile wallet services in India: Analysis of the effect of innovativeness, stress to use and social influence. International Journal of Information Management, 50, 191–205. https://doi.org/10.1016/J.IJINFOMGT.2019.05.022

Singu, H. B., & Chakraborty, D. (2022). I have the bank in my pocket: Theoretical evidence and perspectives. Journal of Public Affairs, 22(3), e2568. https://doi.org/10.1002/pa.2568

Teo, H. H., Wei, K. K., & Benbasat, I. (2003). Predicting intention to adopt interorganizational linkages: An institutional perspective. MIS Quarterly, 27(1), 19–49. https://doi.org/10.2307/30036518

Urbach, N., & Müller, B. (2012). The updated DeLone and McLean model of information systems success. In, Y. Dwivedi, M. Wade, & S. Schneberger (eds.), Information systems theory. Integrated series in information systems (Vol. 28, pp. 1–18). Springer. https://doi.org/10.1007/978-1-4419-6108-2_1

Wai, I. S., Ng, S. S., Chiu, D. K., Ho, K. K., & Lo, P. (2018). Exploring undergraduate students’ usage pattern of mobile apps for education. Journal of Librarianship and Information Science, 50(1), 34–47. https://doi.org/10.1177/0961000616662699

Wang, E. S.-T. (2022). Influences of innovation attributes on value perceptions and usage intentions of mobile payment. Journal of Electronic Commerce Research, 23(1), 45–58. http://www.jecr.org/sites/default/files/2022vol23no1_Paper4.pdf

Yuliana, A., & Wahyudi, L. (2021). The relationship between trust and intention to recommend: The role of content quality, website design and enjoyment. Journal of Business and Management Studies, 3(2), 241–248. https://doi.org/10.32996/jbms.2021.3.2.25

Zhang, X. (2018). Frugal innovation and the digital divide: Developing an extended model of the diffusion of innovations. International Journal of Innovation Studies, 2(2), 53–64. https://doi.org/10.1016/j.ijis.2018.06.001

Zhou, T. (2012). Understanding users’ initial trust in mobile banking: An elaboration likelihood perspective. Computers in Human Behavior, 28(4), 1518–1525. https://doi.org/10.1016/J.chb.2012.03.021