Intention to Use Robo Advisory Services in Malaysia

  • Chin Yoke Kuah Assistant Professor
  • Ving Chi Chow
  • Yii Xin Genevieve
  • Xin Min Tan

Abstract

In Malaysia, robo-advisory services have become increasingly popular in the financial industry. This study examines the factors that determine the intention to use robo-advisory services in Malaysia, including the performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and trust. The target respondents of this study are individuals from the M40 income group in Malaysia. A total of 400 responses was collected and analyzed through Partial Least Squares Structural Equation Modelling (PLS-SEM) using SmartPLS software. The findings demonstrated that performance expectancy, social influence, hedonic motivation, price value, and trust are significant in affecting the behavioral intention to use robo-advisory services in Malaysia, except for effort expectancy and facilitating conditions, which showed an insignificant result. Moreover, this study would contribute to the understanding of the emergence of robo-advisory services in Malaysia and provide practical and theoretical implications for portfolio managers, robo-advisory firms, and researchers to aid in the future development of robo-advisory services and the financial industry in Malaysia.


 

References

Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99-110. https://isiarticles.com/bundles/Article/pre/pdf/134194.pdf
Ambarwati, R., Thamrin, S., & Harja, Y. D. (2020). The role of facilitating conditions and user habits: A case of Indonesian online learning platform. Journal of Asian Finance, Economics and Business, 7(10), 481-489. http://dx.doi.org/10.13106/jafeb.2020.vol7.no10.481
Aseng, A. C. (2020). Factors influencing Generation Z intention in using fintech digital payment services. CogITo Smart Journal, 6(2), 155-166. https://doi.org/10.31154/cogito.v6i2.260.155-166
Baptista, G., & Oliveira, T. (2015). Understanding mobile banking: The Unified Theory of Acceptance and Use of Technology combined with cultural moderators. Computers in Human Behavior, 50, 418-430. http://dx.doi.org/10.1016/j.chb.2015.04.024
Belanche, D., Casaló, L. V., & Flavián, C. (2019). Artificial intelligence in fintech: Understanding robo-advisors adoption among customers. Industrial Management & Data Systems, 119(7), 1411-1430. http://dx.doi.org/10.1108/IMDS-08-2018-0368
Bhatia, A., Chandani, A., & Chhateja, J. (2020). Robo advisory and its potential in addressing the behavioral biases of investors — A qualitative study in Indian context. Journal of Behavioral and Experimental Finance, 25, Article e100281. https://doi.org/10.1016/j.jbef.2020.100281
Bhatia, A., Chandani, A., Atiq, R., Mehta, M., & Divekar, R. (2021). Artificial intelligence in financial services: A qualitative research to discover robo-advisory services. Qualitative Research in Financial Markets, 13(5), 632-654. https://doi.org/10.1108/QRFM-10-2020-0199
Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351-370. https://doi.org/10.2307/3250921
Boonsiritomachai, W., & Pitchayadejanant, K. (2017). Determinants affecting mobile banking adoption by Generation Y based on the Unified Theory of Acceptance and Use of Technology model modified by the Technology Acceptance Model concept. Kasetsart Journal of Social Sciences, 40(2), 349-358. https://doi.org/10.1016/j.kjss.2017.10.005
Brown, S. A., & Venkatesh, V. (2005). Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS Quarterly, 29(3), 399-426. https://doi.org/10.2307/25148690
Bruckes, M., Westmattelmann, D., Oldeweme, A., & Schewe, G. (2019, December 15-18). Determinants and barriers of adopting robo-advisory services [Paper presentation]. International Conference on Information Systems 2019 Proceedings, Munic, Germany. https://aisel.aisnet.org/icis2019/blockchain_fintech/blockchain_fintech/2?utm_source=aisel.aisnet.org%2Ficis2019%2Fblockchain_fintech%2Fblockchain_fintech%2F2&utm_medium=PDF&utm_campaign=PDFCoverPages
Bui, T. T. H., & Bui, H. T. (2018). Gamification impact on the acceptance of mobile payment in Ho Chi Minh City, Vietnam. International Journal of Social Science and Economic Research, 3(9), 4822-4837. https://ijsser.org/2018files/ijsser_03__334.pdf
Butarbutar, N., Lie, D., Bagenda, C., Hendrayani, E., & Sudirman, A. (2022). Analysis of the effect of performance expectancy, effort expectancy, and lifestyle compatibility on behavioral intention QRIS in Indonesia. International Journal of Scientific Research and Management, 10(11), 4203-4211. http://dx.doi.org/10.18535/ijsrm/v10i11.em07
Chan, R., Troshani, I., Hill, S. R., & Hoffmann, A. (2022). Towards an understanding of consumers’ fintech adoption: The case of open banking. International Journal of Bank Marketing, 40(4), 886-917. https://doi.org/10.1108/IJBM-08-2021-0397
Chang, H. H., & Chen, S. W. (2008). The impact of online store environment cues on purchase intention: Trust and perceived risk as a mediator. Online Information Review, 32(6), 818-841. https://doi.org/10.1108/14684520810923953
Chao, C. M. (2019). Factors determining the behavioral intention to use mobile learning: An application and extension of the UTAUT model. Frontiers in Psychology, 10, 1652. http://dx.doi.org/10.3389/fpsyg.2019.01652
Chen, W. C., Chen, C. W., & Chen, W. K. (2019). Drivers of mobile payment acceptance in China: An empirical investigation. Information (Switzerland), 10(12), 1-20. http://dx.doi.org/10.3390/info10120384
Chong, A. Y. L., Ooi, K. B., Lin, B. S., & Tan, B. I. (2010). Online banking adoption: An empirical analysis. International Journal of Bank Marketing, 28(4), 267-287. https://doi.org/10.1108/02652321011054963
Chuang, L. M., Chun, C. L., & Hsiao, K. K. (2016). The adoption of fintech service: TAM perspective. International Journal of Management and Administrative Sciences, 3(7), 1-15. https://www.ijmas.org/3-7/IJMAS-3601-2016.pdf
D’Acunto, F., Prabhala, N., & Rossi, A. G. (2019). The promises and pitfalls of robo-advising. The Review of Financial Studies, 32(5), 1983-2020. https://doi.org/10.1093/rfs/hhz014
Fadzil, F. H. (2017). A study on factors affecting the behavioral intention to use mobile apps in Malaysia [Bachelor thesis, Universiti Teknologi MARA]. UiTM Institutional Repository. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3090753
Fahruri, A., Mohammad Hamsal, Furinto, A., & Kartono, R. (2022). Conceptual model of Technology Acceptance Model modification on robo advisor acceptance in Indonesia. Journal of International Conference Proceedings, 5(1), 467-477. https://www.ejournal.aibpmjournals.com/index.php/JICP
Fatima, T., Kashif, S., Muhammad Kamran, & Awan, T. M. (2021). Examining factors influencing adoption of m-payment: Extending UTAUT2 with perceived value. International Journal of Innovation, Creativity and Change, 15(8), 276-299. https://www.ijicc.net/images/Vol_15/Iss_8/15818_Fatima_2021_E1_R.pdfz
Fisch, J. E., Labouré, M., & Turner, J. A. (2018). The Emergence of the Robo-advisor. (Wharton Pension Research Council Working Papers No. WP2018-12, 10). https://repository.upenn.edu/prc_papers/10
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behaviour: An introduction to theory and research. Reading, MA: Addison-Wesley. https://people.umass.edu/aizen/f&a1975.html
Gan, L. Y., Khan, M. T. I., & Liew, T. W. (2021). Understanding consumer's adoption of financial robo-advisors at the outbreak of the COVID-19 crisis in Malaysia. Financial Planning Review, 4(3), Article e1127. http://dx.doi.org/10.1002/cfp2.1127
Garcia, T. (2022). Robo-advising: Past, present, and future US trends [Master thesis, University of Strathclyde]. ResearchGate. http://dx.doi.org/10.13140/RG.2.2.28601.03682
Gerlach, J. M., & Lutz, J. K. T. (2021). Digital financial advice solutions – Evidence on factors affecting the future usage intention and the moderating effect of experience. Journal of Economics and Business, 117, 1-19. https://doi.org/10.1016/j.jeconbus.2021.106009
Gomber, P., Kauffman, R. J., Parker, C., & Weber, B. W. (2018). On the fintech revolution: Interpreting the forces of innovation, disruption, and transformation in financial services. Journal of Management Information Systems, 35(1), 220-265. http://dx.doi.org/10.1080/07421222.2018.1440766
Hohenberger, C., Lee, C. W., & Coughlin, J. F. (2019). Acceptance of robo-advisors: Effects of financial experience, affective reactions, and self-enhancement motives. Financial Planning Review, 2(2). http://dx.doi.org/10.1002/cfp2.1047
Hu, Z. Q., Ding, S., Li, S. Z., Chen, L. T., & Yang, S. L. (2019). Adoption intention of fintech services for bank users: An empirical examination with an extended Technology Acceptance Model. Symmetry, 11(3). https://doi.org/10.3390/sym11030340
Huang, C., & Kao, Y. S. (2015). UTAUT2 based predictions of factors influencing the technology acceptance of phablets by DNP. Mathematical Problems in Engineering, 2015(1), 1-23. http://dx.doi.org/10.1155/2015/603747
Isaia, E., & Oggero, N. (2022). The potential use of robo-advisors among the young generation: Evidence from Italy. Finance Research Letters, 48, 103046. https://doi.org/10.1016/j.frl.2022.103046
Islam, M. S. (2013). Mobile banking: An emerging issue in Bangladesh. ASA University Review, 7(1), 123-130. http://www.asaub.edu.bd/data/asaubreview/v7n1sl11.pdf
Jadil, Y., Rana, N. P., & Dwivedi, Y. K. (2022). Understanding the drivers of online trust and intention to buy on a website: An emerging market perspective. International Journal of Information Management Data Insights, 2(1), Article e100065. https://doi.org/10.1016/j.jjimei.2022.100065
Jahanbakhsh, M., Peikari, H. R., Hazhir, F., & Saghaeiannejad-Isfahani, S. (2018). An investigation into the effective factors on the acceptance and use of integrated health system in the primary health-care centers. Journal of Education and Health Promotion, 7(1), 128. https://doi.org/10.4103%2Fjehp.jehp_32_18
Jüngera, M., & Mietznerb, M. (2020). Banking goes digital: The adoption of fintech services by German households. Finance Research Letters, 34, Article e101260. https://doi.org/10.1016/j.frl.2019.08.008
Kaabachi, S., Mrad, S. B., & Petrescu, M. (2017). Consumer initial trust toward internet-only banks in France. International Journal of Bank Marketing, 35(6), 903-924. https://doi.org/10.1108/IJBM-09-2016-0140
Kiranga, I. W., & Chotiyaputta, V. (2021). Factors affecting technology in the mobile banking sector in Kenya. Journal of ASEAN PLUS Studies, 2(2), 66-80. https://so06.tci-thaijo.org/index.php/aseanplus/article/view/251948/171530
Kurniasari, F., Sharina Tajul Urus, Utomo, P., Nadiah Abdul Hamid, Jimmy, S. Y., & Othman, I. W. (2022). Determinant factors of adoption of fintech payment services in Indonesia using the UTAUT approach. Asia Pacific Management Accounting Journal, 17(1), 97-125. https://ir.uitm.edu.my/id/eprint/66086/1/66086.pdf
Lee, M. K. O., Cheung, C. M. K., & Chen, Z. H. (2005). Acceptance of internet-based learning medium: The role of extrinsic and intrinsic motivation. Information & Management, 42(8), 1095-1104. https://doi.org/10.1016/j.im.2003.10.007
Lisauskiene N., & Darskuviene V. (2021). Linking the robo-advisors phenomenon and behavioural biases in investment management: An interdisciplinary literature review and research agenda. Organizations and Markets in Emerging Economies, 12(2), 459-477. https://doi.org/10.15388/omee.2021.12.65
Mansour, A. T., Ibrahim, H., & Hassan, S. (2021). The behavioral intention’s role: Facilitating condition and use of e-government services among SMEs in Saudi Arabia. Turkish Journal of Computer and Mathematics Education, 12(1), 1520-1528. https://doi.org/10.17762/turcomat.v12i3.955
Megadewandanu, S., Suyoto, & Pranowo. (2016, October 27-28). Exploring mobile wallet adoption in Indonesia using UTAUT2: An approach from a consumer perspective [Paper Presentation]. 2016 2nd International Conference on Science and Technology-Computer (ICST), Yogyakarta, Indonesia. http://dx.doi.org/10.1109/ICSTC.2016.7877340
Milani, A. (2019). The role of risk and trust in the adoption of robo-advisory in Italy: An extension of the Unified Theory of Acceptance and Use of Technology [Master thesis, City University of London]. PricewaterhouseCoopers Advisory SpA. https://www.pwc.com/it/it/publications/assets/docs/Report-robo-advisors.pdf
Mohammad Husam Odeh. (2019). Factors affecting the adoption of financial information systems based on UTAUT Model. International Journal of Academic Research in Accounting, Finance and Management Sciences, 9(2), 108-116. http://dx.doi.org/10.6007/IJARAFMS/v9-i2/6064
Mohammed Al-Hawari, & Ward, T. (2006). The effect of automated service quality on Australian banks’ financial performance and the mediating role of customer satisfaction. Marketing Intelligence & Planning, 24(2),127-147. http://dx.doi.org/10.1108/02634500610653991
Momani, A. M. (2020). The Unified Theory of Acceptance and Use of Technology: A new approach in technology acceptance. International Journal of Sociotechnology and Knowledge Development, 12(3), 79-98. http://dx.doi.org/10.4018/IJSKD.2020070105
Nourallah, M. (2023). One size does not fit all: Young retail investors’ initial trust in financial robo-advisors. Journal of Business Research, 156, 113470. https://doi.org/10.1016/j.jbusres.2022.113470
Nourallah, M., Öhman, P., & Amin, M. (2022). No trust, no use: How young retail investors build initial trust in financial robo-advisors. Journal of Financial Reporting and Accounting, 21(1), 1985-2517. https://doi.org/10.1108/JFRA-12-2021-0451
Oehler, A., Horn, M., & Wendt, S. (2022). Investor characteristics and their impact on the decision to use a robo-advisor. Journal of Financial Services Research, 62, 91-125. https://doi.org/10.1007/s10693-021-00367-8
Oliva, M. A., Borondo, J. P., & Clavero, G. M. (2019). Variables influencing cryptocurrency use: A Technology Acceptance Model in Spain. Frontiers in Psychology, 10, Article 475. https://doi.org/10.3389/fpsyg.2019.00475phu
Park, J. Y., Ryu, J. P., & Shin, H. J. (2016). Robo-advisors for portfolio management. Advanced Science and Technology Letters, 141, 104-108. https://www.semanticscholar.org/paper/Robo-Advisors-for-Portfolio-Management-Park-Ryu/b1e945b5990edd024627c0c9c438fbb40a68bec6
Phuong, N. T. H., Thuy, N. D., Giang, T. L., Han, B. T. N., Hieu, T. H., & Long, N. T. (2022). Determinants of intention to use fintech payment services: Evidence from Vietnam' Generation Z. International Journal of Business, Economics and Law, 26(1), 354-366. https://www.ijbel.com/wp-content/uploads/2022/06/IJBEL26.ISU1_301.pdf
Putra, W. E., Setiawan, D., & Olimsar, F. (2022). Analysis of the factors that influence the behavior of the millennial generation to use the go-pay digital wallet. International Journal of Recent Technology and Engineering, 11(1), 15-18. https://www.ijrte.org/wp-content/uploads/papers/v11i1/A68930511122.pdf
Rachman, K. M., & Sukmadilaga, C. (2022). Influence of robo advisory in investment decision: A case study in Indonesian mutual fund market. Journal of Digital Innovation Studies, 1(1), 1-20. https://doi.org/10.24198/digits.v1i1.37806
Rizkiana, A. (2020). Analysis of millennials intention in using financial technology payment “OVO” by implementing Unified Theory of Acceptance and Use of Technology (UTAUT). Jurnal Ilmiah Mahasiswa FEB, 9(1), 1-10. https://jimfeb.ub.ac.id/index.php/jimfeb/article/view/7042
Rousseau, D. M., Sitkin, S. B., Burt, R. S., & Camerer, C. (1998). Not so different after all: A cross-discipline view of trust. Academy of Management Review, 23(3), 393-404. http://dx.doi.org/10.5465/AMR.1998.926617
Ruslan, R. A. H. M., Ibrahim, M. A., & Hamid, N. H. (2022). Application of artificial intelligence in fintech: The decision of youth investors to use robo-advisor platform as micro-investing alternative. Journal of Entrepreneurship, Business and Economics 2022, 10(2s2), 38-54. https://scientificia.com/index.php/JEBE/article/view/188/177
Sa, J. H., Lee, K. B., Cho, S. I., Lee, S. H., & Gim, G. Y. (2018). A study on the influence of personality factors on intention to use of robo-advisor. Journal of Engineering and Applied Sciences, 13(19), 7795-7802. http://dx.doi.org/10.3923/jeasci.2018.7795.7802
Sani, I. A., & Koesrindartoto, D. P. (2019, August 7-9). The empirical study towards the acceptance of robo-advisory for digital wealth advisor: An Indonesian university student perspective [Paper Presentation]. The 4th International Conference on Management in Emerging Markets 2019 and The 11th Indonesia International Conference on Innovation, Entrepreneurship and Small Business 2019, Bali, Indonesia. https://journal.sbm.itb.ac.id/index.php/ProceedingSBMITB/article/download/3460/1341
Sebastian, M. G. B., Guede, J. R. S., & Antonovica, A. (2022). Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants. Frontiers in Psychology, 13, 993935. https://doi.org/10.3389/fpsyg.2022.993935
Senyo, P. K., & Osabutey, E. L. (2020). Unearthing antecedents to financial inclusion through fintech innovations. Technovation, 98, 1-14. https://doi.org/10.1016/j.technovation.2020.102155
Shamsurin Ahmad, Urus, S. T., & Nazri, S. N. F. S. M. (2021). Technology acceptance of financial technology (fintech) for payment services among employed fresh graduates. Asia-Pacific Management Accounting Journal, 16(2), 27-58. http://dx.doi.org/10.24191/APMAJ.V16i2-02
Sharma, S. K., & Sharma, M. (2019). Examining the role of trust and quality dimensions in the actual usage of mobile banking services: An empirical investigation. International Journal of Information Management, 44, 65-75. https://doi.org/10.1016/j.ijinfomgt.2018.09.013
Shih, K. (2019). The robo-advisor origin story you must read (Part 1). LinkedIn. https://www.linkedin.com/pulse/robo-advisor-origin-story-you-must-read-part-1-ken-shih/
Singh, N., & Sinha, N. (2020). How perceived trust mediates merchant's intention to use a mobile wallet technology. Journal of Retailing and Consumer Services, 52, Article e101894. https://doi.org/10.1016/j.jretconser.2019.101894
Statista. (2023a). Robo-Advisors – Worldwide. https://www.statista.com/outlook/dmo/fintech/digital-investment/robo-advisors/malaysia
Statista. (2023b). Robo-Advisors – Malaysia. https://www.statista.com/outlook/dmo/fintech/digital-investment/robo-advisors/malaysia
Thong, J. Y. L., Hong, S. J., & Tam, K. Y. (2006). The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. International Journal of Human-Computer Studies, 64(9), 799-810. https://doi.org/10.1016/j.ijhcs.2006.05.001
Tsai, S. C., & Chen, C. H. (2022). Exploring the innovation diffusion of big data robo-advisor. Applied System Innovation, 5(1), 15. https://doi.org/10.3390/asi5010015
Urban, G. L., Amyx, C., & Lorenzon, A. (2009). Online trust: State of the art, new frontiers, and research potential. Journal of Interactive Marketing, 23(2), 179-190. https://doi.org/10.1016/j.intmar.2009.03.001
Van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28(4), 695-704. https://doi.org/10.2307/25148660
Venkatesh, V., Morris, M. G., Davis, B. G., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3375136
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the Unified Theory of Acceptance and Use of Technology. Forthcoming in MIS Quarterly, 36(1), 157-178. https://ssrn.com/abstract=2002388
Wang, S., & Pradhan, S. (2020, December 1-4). Exploring factors influencing older adults' willingness to use robo-advisors [Paper Presentation]. Australasian Conference on Information Systems 2020, Wellington, New Zealand. https://aisel.aisnet.org/acis2020/50
Wang, T., Chung, Y., & Jung, C. (2014). Exploring determinants of adoption intentions towards enterprise 2.0 applications: An empirical study. Behavior & Information Technology, 33(10), 1048-1064. https://doi.org/10.1080/0144929X.2013.781221
Wardani, D., Wulandari, N., & Baskara, C. A. (2021). Understanding customer acceptance to financial technology; Study in Indonesia. International Journal of Innovative Technologies in Economy, 2(34), 1-10. https://doi.org/10.31435/rsglobal_ijite/30062021/7550
Welsch, A. (2022, February 18). Robo-advisors changed investing. But can they survive independently? Barron’s. https://www.barrons.com/articles/robo-advisors-changed-investing-but-can-they-survive-independently-51645172100
Williams, M. D., Rana, N. P., & Dwivedi, Y. (2015) The Unified Theory of Acceptance and Use of Technology (UTAUT): A literature review. Journal of Enterprise of Information Management, 28(3), 443-488. https://doi.org/10.1108/JEIM-09-2014-0088
Yeh, H. C., Yu, M. C., Liu, C. H., & Huang, C. I. (2022). Robo-advisor based on Unified Theory of Acceptance and Use of Technology. Asia Pacific Journal of Marketing and Logistics, 35(4), 962-979. https://doi.org/10.1108/APJML-07-2021-0493
Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence. Journal of Marketing, 52(3), 2-22. http://dx.doi.org/10.1177/002224298805200302
Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1996). The behavioral consequences of service quality. Journal of Marketing, 60(2), 31-46. https://doi.org/10.2307/1251929
Zhang, L. Y., Zhu, J., & Liu, Q. H. (2012). A meta-analysis of mobile commerce adoption and the moderating effect of culture. Computers in Human Behavior, 28(5), 1902-1911. https://doi.org/10.1016/j.chb.2012.05.008
Zhou, Y., Lu, Y., & Wang, B. (2010). Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior, 26(4), 760-767. http://dx.doi.org/10.1016/j.chb.2010.01.013
Zuiderwijk, A., Janssen, M., & Dwivedi, Y. K. (2015). Acceptance and use predictors of open data technologies: Drawing upon the Unified Theory of Acceptance and Use of Technology. Government Information Quarterly, 32(4), 429-440. http://dx.doi.org/10.1016/j.giq.2015.09.005
Published
2024-03-31
How to Cite
KUAH, Chin Yoke et al. Intention to Use Robo Advisory Services in Malaysia. International Journal of Advanced Research in Economics and Finance, [S.l.], v. 6, n. 1, p. 146-165, mar. 2024. ISSN 2682-812X. Available at: <https://myjms.mohe.gov.my/index.php/ijaref/article/view/25801>. Date accessed: 21 may 2024.
Section
English Section