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Determinants of conventional and digital investment advisory decisions: a systematic literature review

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  • Fabian Wagner

    (LMU München BWL: Ludwig-Maximilians-Universität München, Faculty for Business Administration)

Abstract

The growing demand for digital investment advisory services and the advancing technological process led to increased attention to this topic in recent literature. In light of these developments, the question arises whether conventional and digital advisors behave differently in their investment advisory decisions. I therefore conducted a systematic literature review and evaluated 97 publications on the determinants of conventional and digital investment advisory decisions. Based on the literature, five main determinants were identified that are important for investment advisory decisions. These determinants are identical for both variants of the advice, but there are differences in the way they are addressed. This systematic literature review provides an overview of the current state of research and can therefore help identify areas where investment advice can be improved in the future.

Suggested Citation

  • Fabian Wagner, 2024. "Determinants of conventional and digital investment advisory decisions: a systematic literature review," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-32, December.
  • Handle: RePEc:spr:fininn:v:10:y:2024:i:1:d:10.1186_s40854-023-00538-7
    DOI: 10.1186/s40854-023-00538-7
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    References listed on IDEAS

    as
    1. Humoud Alsabah & Agostino Capponi & Octavio Ruiz Lacedelli & Matt Stern, 2021. "Robo-Advising: Learning Investors’ Risk Preferences via Portfolio Choices [Mean-variance versus Full-scale Optimisation: In and out of Sample]," Journal of Financial Econometrics, Oxford University Press, vol. 19(2), pages 369-392.
    2. Chester S. Spatt, 2020. "Conflicts of Interest in Asset Management and Advising," Annual Review of Financial Economics, Annual Reviews, vol. 12(1), pages 217-235, December.
    3. Francesco D’Acunto & Nagpurnanand Prabhala & Alberto G Rossi, 2019. "The Promises and Pitfalls of Robo-Advising," The Review of Financial Studies, Society for Financial Studies, vol. 32(5), pages 1983-2020.
    4. Cooper, W.W. & Kingyens, Angela T. & Paradi, Joseph C., 2014. "Two-stage financial risk tolerance assessment using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 233(1), pages 273-280.
    5. Bolton, Patrick & Freixas, Xavier & Shapiro, Joel, 2007. "Conflicts of interest, information provision, and competition in the financial services industry," Journal of Financial Economics, Elsevier, vol. 85(2), pages 297-330, August.
    6. Bhatia, Ankita & Chandani, Arti & Chhateja, Jagriti, 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, Elsevier, vol. 25(C).
    7. Paul Chen & Martin Richardson, 2019. "Conflict of Interest, Disclosure and Vertical Relationships: An Experimental Analysis," Economic Papers, The Economic Society of Australia, vol. 38(3), pages 167-181, September.
    8. Hackethal, Andreas & Haliassos, Michael & Jappelli, Tullio, 2012. "Financial advisors: A case of babysitters?," Journal of Banking & Finance, Elsevier, vol. 36(2), pages 509-524.
    9. Thorsten Hens & János Mayer, 2018. "Decision Theory Matters for Financial Advice," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 195-226, June.
    10. Ismayilov, Huseyn & Potters, Jan, 2013. "Disclosing advisor's interests neither hurts nor helps," Journal of Economic Behavior & Organization, Elsevier, vol. 93(C), pages 314-320.
    11. Daylian M. Cain & George Loewenstein & Don A. Moore, 2011. "When Sunlight Fails to Disinfect: Understanding the Perverse Effects of Disclosing Conflicts of Interest," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 37(5), pages 836-857.
    12. Gerhard van de Venter & David Michayluk, 2008. "An Insight into Overconfidence in the Forecasting Abilities of Financial Advisors," Australian Journal of Management, Australian School of Business, vol. 32(3), pages 545-557, March.
    13. Mikhail Beketov & Kevin Lehmann & Manuel Wittke, 2018. "Robo Advisors: quantitative methods inside the robots," Journal of Asset Management, Palgrave Macmillan, vol. 19(6), pages 363-370, October.
    14. Daylian M. Cain & George Loewenstein & Don A. Moore, 2005. "The Dirt on Coming Clean: Perverse Effects of Disclosing Conflicts of Interest," The Journal of Legal Studies, University of Chicago Press, vol. 34(1), pages 1-25, January.
    15. Bryan K. Church & Xi (Jason) Kuang, 2009. "Conflicts of Interest, Disclosure, and (Costly) Sanctions: Experimental Evidence," The Journal of Legal Studies, University of Chicago Press, vol. 38(2), pages 505-532, June.
    16. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & David Martinez-Rego & Fan Wu & Lingbo Li, 2022. "Cryptocurrency trading: a comprehensive survey," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-59, December.
    17. Michael Puhle, 2019. "The Performance and Asset Allocation of German Robo-Advisors," Society and Economy, Akadémiai Kiadó, Hungary, vol. 41(3), pages 331-351, September.
    18. Baeckström, Ylva & Marsh, Ian W. & Silvester, Joanne, 2021. "Variations in investment advice provision: A study of financial advisors of millionaire investors," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 716-735.
    19. Gelman, Michael & Khan, Zaheer & Shoham, Amir & Tarba, Shlomo Y., 2021. "Does local competition and firm market power affect investment adviser misconduct?," Journal of Corporate Finance, Elsevier, vol. 66(C).
    20. Wonbin Ahn & Hee Soo Lee & Hosun Ryou & Kyong Joo Oh, 2020. "Asset Allocation Model for a Robo-Advisor Using the Financial Market Instability Index and Genetic Algorithms," Sustainability, MDPI, vol. 12(3), pages 1-15, January.
    21. Helder Sebastião & Pedro Godinho, 2021. "Forecasting and trading cryptocurrencies with machine learning under changing market conditions," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-30, December.
    22. Koch, Christopher & Schmidt, Carsten, 2010. "Disclosing conflicts of interest - Do experience and reputation matter?," Accounting, Organizations and Society, Elsevier, vol. 35(1), pages 95-107, January.
    23. Daniel Hoechle & Stefan Ruenzi & Nic Schaub & Markus Schmid, 2018. "Financial Advice and Bank Profits," The Review of Financial Studies, Society for Financial Studies, vol. 31(11), pages 4447-4492.
    24. repec:eme:hppsss:08288660610710746 is not listed on IDEAS
    25. Crawford, Vincent P & Sobel, Joel, 1982. "Strategic Information Transmission," Econometrica, Econometric Society, vol. 50(6), pages 1431-1451, November.
    26. Snelbecker, Glenn E. & Roszkowski, Michael J. & Cutler, Neal E., 1990. "Investors' risk tolerance and return aspirations, and financial advisors' interpretations: A conceptual model and exploratory data," Journal of Behavioral Economics, Elsevier, vol. 19(4), pages 377-393.
    27. Angelova, Vera & Regner, Tobias, 2013. "Do voluntary payments to advisors improve the quality of financial advice? An experimental deception game," Journal of Economic Behavior & Organization, Elsevier, vol. 93(C), pages 205-218.
    28. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & Lingbo Li & David Martinez-Regoband & Fan Wu, 2020. "Cryptocurrency Trading: A Comprehensive Survey," Papers 2003.11352, arXiv.org, revised Jan 2022.
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