The Innovative Personality of Indonesia's Cross-Generational Population in the Adoption of Investment Application Innovations
Keywords:
Personality, Innovation, Investment, Mobile Apps, ConsumerAbstract
Introduction/Main Objectives: The success of the diffusion of innovation is highly dependent on the speed of adoption by adopters. Adopters have individual innovative characteristics that determine the willingness to adopt new innovations. This study aims to analyze the differences in FFM across Generations X, Y, Z on the adoption of innovation mobile investment apps.
Background Problems: The existence of digital consumers has led to consumer behaviour that relies on innovation and digital technology. Consumer innovativeness characteristics are related to consumption behaviour and adoption of innovations that are formed persistently and grow from childhood. Therefore, it is important to know the characteristics of innovation in Generation X, Y and Z in Indonesia.
Research Methods: this research takes the form of survey research. The number of respondents was 88 people who installed investment mobile applications. The variable of this study is the Five Factor Model (FFM) which is one of the instruments measuring the characteristics of consumer innovation. There are 5 characteristic factors: Open to Experience (OE), Extraversion (EXT), conscientiousness (CSC), Agreeableness (AGR), and Neuroticism (NEU). The Data were analysed using ANOVA.
Finding/Results: the results showed that there are differences in the components of the Five-factors of Personality, namely OE, CSC, AGR in Gen Y and Z; where Gen Y has a greater mean value. There is also a difference in OE between Gen X and Y, where Gen Y has a greater mean. There is a difference in NEU between Gen X and Z, where Gen Z has a greater mean.
Conclusion:GenerationYis the most persistent generation and showsthe characteristics of FFM.This researchis usefulfor marketers in implementing communication strategies based on consumer personality and to seethe map of intergenerational consumer innovativenessin Indonesia becausetheyare the determinantsof the success of innovation diffusion.
References
Al-Jabri, I. M., & Sohail, M. S. (2012). MOBILE BANKING ADOPTION: APPLICATION OF DIFFUSION OF INNOVATION THEORY. In Journal of Electronic Commerce Research (Vol. 13). http://ssrn.com/abstract=2523623
Chiu, C.-Y., Chen, S., & Chen, C.-L. (2017). IJMESS) Provided in Cooperation with. In Economics and Social Sciences (IJMESS) (IJMESS) (Vol. 6, Issue 1). IJMESS International Publishers. http://hdl.handle.net/10419/157921http://creativecommons.org/licenses/by-nc/3.0/http://www.ijmess.com
Dedehayir, O., Ortt, R. J., Riverola, C., & Miralles, F. (2017). Innovators and early adopters in the diffusion of innovations: A literature review. In International Journal of Innovation Management (Vol. 21, Issue 8). World Scientific Publishing Co. Pte Ltd. https://doi.org/10.1142/S1363919617400102
Dobre, C., Dragomir, A., & Preda, G. (2009). CONSUMER INNOVATIVENESS: A MARKETING APPROACH (Vol. 4, Issue 2).
F Lou, A. T., Li, E. Y., & F, A. T. (2017). Association for Information Systems AIS Electronic Library (AISeL) Integrating Innovation Diffusion Theory and the Technology Acceptance Model: The adoption of blockchain technology from business managers’ perspective Recommended Citation “Integrating Innovation Diffusion Theory and the Technology Acceptance Model: The adoption of blockchain technology from business managers’’ perspective".” http://aisel.aisnet.org/iceb2017http://aisel.aisnet.org/iceb2017/44
Filová, J. (2015). MEASURING CONSUMER INNOVATIVENESS: IDENTIFYING INNOVATORS AMONG CONSUMERS OF MODERN TECHNOLOGIES (Vol. 4).
Garrett, J. L., Rodermund, R., Anderson, N., Berkowitz, S., & Robb, C. A. (2014). Adoption of Mobile Payment Technology by Consumers. Family and Consumer Sciences Research Journal, 42(4), 358–368. https://doi.org/10.1111/fcsr.12069
Guhathakurta, R. (2016). Understanding the Profile of a “Consumer-Innovator.” https://www.researchgate.net/publication/303548816
Johri, A., Wasiq, M., Kaur, H., & Asif, M. (2023). Assessment of users’ adoption behaviour for stock market investment through online applications. Heliyon, 9(9). https://doi.org/10.1016/j.heliyon.2023.e19524
Karaarslan, M. H., & Şükrüakdoğan, M. (2015). Consumer Innovativeness: A Market Segmentation. In International Journal of Business and Social Science (Vol. 6, Issue 8). www.ijbssnet.com
Lee, J., & Son, J. (2017). The Effects of Consumer Innovativeness on Mobile App Download: Focusing on Comparison of Innovators and Noninnovators. Mobile Information Systems, 2017. https://doi.org/10.1155/2017/3894685
Luiz Dias da Silva, M., & Da, D. (2017). Diffusion and adoption of technology amongst engineering and business management students. https://www.redalyc.org/articulo.oa?id=499151081002
Malouf, N. El. (2023). Diffusion of Innovations. https://open.ncl.ac.uk
Nikolć, S. T., & Miladinović, S. (2012). “CUSTOMIZED” CONSUMER AND CONSUMER “INNOVATOR” IN THE LIGHT OF SOCIAL CAPITAL AND DOMINANT CULTURAL PATTERN *.
Novikova, I. A. (2013). Big Five (The Five-Factor Model and The Five-Factor Theory).
Okonkwo, C. W., Huisman, M., & Taylor, E. (2020). A framework for adoption and diffusion of mobile applications in Africa. Advances in Science, Technology and Engineering Systems, 5(6), 1577–1592. https://doi.org/10.25046/aj0506189
Putteeraj, M., Bhungee, N., Somanah, J., & Moty, N. (2022). Assessing E-Health adoption readiness using diffusion of innovation theory and the role mediated by each adopter’s category in a Mauritian context. International Health, 14(3), 236–249. https://doi.org/10.1093/inthealth/ihab035
Ramanathan, K. V, Scholar, R., & MeenakshiSundaram, K. S. (2015). A STUDY ON FACTORS INFLUENCING INVESTMENT DECISION OF BANK EMPLOYEES. In International Journal of Research in IT & Management (Vol. 5, Issue 9). http://www.euroasiapub.org
Robertson, T. S. (1967). The Process of Innovation and the Diffusion of Innovation.
Rogers, E. M. (1983). Diffusion of innovations. Free Press.
Roos, J. M., & Kazemi, A. (2022). The five-factor model of personality as predictor of online shopping: Analyzing data from a large representative sample of Swedish internet users. Cogent Psychology, 9(1). https://doi.org/10.1080/23311908.2021.2024640
Soto, C. J. (2018). Big Five personality traits. https://www.researchgate.net/publication/324115204
Stock, R. M., Von Hippel, E., & Gillert, N. L. (2016a). Impacts of personality traits on consumer innovation success. Research Policy, 45(4), 757–769. https://doi.org/10.1016/j.respol.2015.12.002
Stock, R. M., Von Hippel, E., & Gillert, N. L. (2016b). Impacts of personality traits on consumer innovation success. Research Policy, 45(4), 757–769. https://doi.org/10.1016/j.respol.2015.12.002
Umami, Z., & Darma, G. S. (2021). DIGITAL MARKETING: ENGAGING CONSUMERS WITH SMART DIGITAL MARKETING CONTENT. Jurnal Manajemen Dan Kewirausahaan, 23(2), 94–103. https://doi.org/10.9744/jmk.23.2.94-103
Vannella Ericsson, F., & Vannella, F. (2017). The traits of the innovator: Five-Factor Model Analysis and Exemplification. https://www.researchgate.net/publication/319313923
Von Hippel, E., Ogawa, S., & De Jong, J. P. J. (2011). The Age of the Consumer-Innovator.
Downloads
Published
How to Cite
Conference Proceedings Volume
Section
License
Copyright (c) 2025 Anna Triwijayati

This work is licensed under a Creative Commons Attribution 4.0 International License.
ECOSIA is licensed under a Creative Commons Attribution- 4.0 International Public License (CC - BY).
