Exploring Antecedents Affecting Indian Consumers' Adoption of Mobile Apps: A Study of The Vuca Generation
DOI:
https://doi.org/10.61841/vwn8vp40Keywords:
PLS-SEM, personal innovativeness, lifestyle compatibility, attitude, security, India, Northern Capital Region of IndiaAbstract
This research aims to integrate the functional, social, security, and personal dimensions to study mobile app usage antecedents in the Northern Capital Region of India. Convenience sampling was used, and an online survey resulted in 407 valid responses. The measurement and structural models were estimated using PLS-SEM. Perceived usefulness and social influence had no significant impact on usage, implying that contemporary consumers are much more discerning and do not get swayed by the benefits offered or the influence of those around them. The findings show that perceived ease of use had a significant impact on perceived usefulness and attitude formation. Since security is the most important factor determining usage and trust, the industry should have stringent standards to maintain security protocols in every interaction with the user. Also, security concerns need to be allayed, and grievances need to be resolved immediately to gain customer satisfaction and loyalty. Personal innovativeness and lifestyle compatibility are important determinants of attitude and usage. Firms should target mobile apps to students and the active working population who possess innovativeness and for whom mobile apps are compatible with their lifestyle. These users can act as influencers and help in improving their adoption.
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References
1. Aboelmaged, M., & Gebba, T. (2013). Mobile banking adoption: an examination of technology acceptance model
and theory of planned behaviour. International Journal of Business Research and Development, 2(1), 35-50.
Retrieved from https://www.researchgate.net/
publication/285974611_Mobile_Banking_Adoption_An_Examination_of_Technology_Acceptance_Model_and_
Theory_of_ Planned_Behavior
2. Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the
domain of Information Technology. Information Systems Research, 9(2), 204-215. https://doi.org/10.1287/
isre.9.2.204
3. Amoroso, D. L., & Lim, R. (2014). Innovativeness of consumers in the adoption of mobile technology in the
Philippines. International Journal of Economics, Commerce and Management, II(I), 1-11. Retrieved from
https://www. semanticscholar.org/paper/INNOVATIVENESS-OF-CONSUMERSIN-THE-ADOPTION-OF-INDo nald/9a2683d21df8ac8064fb383e5 956288c2485b70e
4. App Annie. (2019). The State of Mobile 2019. Retrieved from https://www.appannie.com/en/go/ state-of-mobile-
2019/
5. Arora, N., Malik, G., & Chawla, D. (2020). Factors affecting consumer adoption of mobile apps in NCR: A
Qualitative Study. Global Business Review, 21(1), 176-196. Retrieved from https://www.researchgate.net/
publication/336480118_Factors_Affecting_Consumer_Adoption_of_Mobile_Apps_in_
NCR_A_Qualitative_Study
6. Audi, M. F., Wahbi, M., Abdallah, S., Kassem, L., & Makkawi, R. (2016). Adoption of mobile banking
applications in Lebanon. Journal of Internet Banking and Commerce, 21(1), 1-15. Retrieved from
https://www.researchgate. net/publication/301678447_Adoption_of_mobile_banking_applications_in_Lebanon
7. Bagozzi, R. P. (2007). The Legacy of the Technology Acceptance Model and a Proposal for a Paradigm Shift.
Journal of the Association for Information Systems, 8(4), 244-254. Retrieved from https://aisel.aisnet.org/jais/
vol8/iss4/12/
8. Belanche, D., Casal, L. V., & Flavian, C. (2012). Integrating trust and personal values into the Technology
Acceptance Model: the case of e-government services adoption. Cuadernos de Economía y Dirección de la
Empresa, 15, 192-204. https://doi.org/10.1016/j. cede.2012.04.004
9. Carter, S., & Yeo, A. C. (2016). Mobile apps usage by Malaysian business undergraduates and postgraduates.
Internet Research, 26(3), 733-757. https://doi. org/10.1108/IntR-10-2014-0273
10. Chawla, D., & Joshi, H. (2017). High versus low consumer attitude and intention towards adoption of mobile
banking in India: an empirical study. Vision, 21(4), 1-15. https://doi.org/10.1177%2F0972262917733188
11. Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. Marcoulides (Ed.),
Methodology for business and management. Modern methods for business research (pp. 295-336). London, UK:
Lawrence Earlbaum Association.
12. Comscore. (2019). Global State of Mobile. Retrieved from https:// www.comscore.com/por/Insights/
Apresentacoes-e-documentos/2019/Global-State-of-Mobile
13. Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use and User Acceptance of Information
Technologies. MIS Quarterly, 13(3), 319-340. Retrieved from https://www.jstor. org/stable/249008?seq=1
14. Fazio, R. H., & Olson, M. A. (2014). The MODE model: Attitude –Behaviour Processes as a function of
motivation and opportunity. In J. W. Sherman, B. Gawronski, & Y. Trope (Eds.), Dual Process theories of the
social mind. Guilford Press.
15. Garson, G. D. (2016). Partial Least Squares Regression and Structural Model, Statistical Associates. Blue Book
Series. Retrieved from https://www.amazon.com/PartialSquares-Regression-StructuralEquationebook/dp/B00IC5DLHE
16. Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: an integrated model. MIS
Quarterly, 27(1), 51- 90. Retrieved from https://www. jstor.org/stable/30036519?seq=1
17. Ghalandari, K. (2012). The effect of performance expectancy, effort expectancy, social influence and facilitating
conditions on acceptance of e-banking services in Iran: the moderating role of age and gender. Middle East
Journal of Scientific Research, 12(6), 801-807. Retrieved from https:// www.semanticscholar.org/paper/ TheEffect-of-PerformanceExpectancy%2C-Effort-SocialGhalandari/33e517029aab95714fd 3209963b3868d4fda14c5
18. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2016). Multivariate Data Analysis (7th ed.). Pearson
Education.
19. Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural
Equation Modeling (PLS-SEM) (2nd ed.). Los Angeles, London, New Delhi, Singapore, Washington DC: SAGE.
20. Henseler, J., Ringle, C. M., & Sarstedt, M. (2016). Testing measurement invariance of composites using Partial
Least Squares. International Marketing Review, 33(3), 405-431. https://doi. org/10.1108/IMR-09-2014-0304
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