Trust, Tech and Tradition: A Multifactor Analysis of Indian Investors' Intentions to Adopt Robo Advisors
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Purpose: This study aims to explore the factors influencing Indian investors' intentions to adopt robo-advisors, focusing on the interplay between trust, technology acceptance, and traditional financial preferences. The research seeks to provide actionable insights for fintech companies, policymakers, and traditional financial advisors to facilitate the adoption of robo-advisory services in India. Design/methodology/approach: The research is a pilot study that employs a quantitative approach, utilising a structured questionnaire to collect data from a diverse sample of Indian investors. Exploratory Factor Analysis (EFA) was conducted to identify key constructs, followed by multiple regression analysis to examine the relationships between trust, technology acceptance, traditional preferences, and the intention to adopt robo-advisors. Findings: The analysis revealed that trust and technology acceptance significantly positively influence the intention to adopt robo-advisors. Traditional preferences negatively impact adoption intentions, with a notable mediating effect between trust, technology acceptance, and adoption intentions. Additionally, demographic factors such as age and investment experience play a significant role, with younger investors and those with less investment experience more inclined to adopt robo-advisors. Research limitations/implications: The study's findings highlight the critical importance of building trust and ensuring technology acceptance among potential users. Fintech companies should prioritise enhancing the perceived trustworthiness of their services through robust security measures and transparent operations. Policymakers should promote financial literacy and digital inclusion, particularly in underserved areas. Traditional advisors can integrate robo-advisory services to create a hybrid model. The study's limitations include reliance on self-reported data and a sample that may not fully represent the entire Indian investor population. Originality/value: This paper provides new insights into the adoption of robo-advisors in the Indian context, emphasising the interplay between trust, technology, and traditional financial preferences. It offers valuable guidance for fintech companies, policymakers, and traditional advisors to enhance their strategies and foster broader adoption of robo-advisory services in India.
Abstract
Purpose: This study aims to explore the factors influencing Indian investors' intentions to adopt robo-advisors, focusing on the interplay between trust, technology acceptance, and traditional financial preferences. The research seeks to provide actionable insights for fintech companies, policymakers, and traditional financial advisors to facilitate the adoption of robo-advisory services in India. Design/methodology/approach: The research is a pilot study that employs a quantitative approach, utilising a structured questionnaire to collect data from a diverse sample of Indian investors. Exploratory Factor Analysis (EFA) was conducted to identify key constructs, followed by multiple regression analysis to examine the relationships between trust, technology acceptance, traditional preferences, and the intention to adopt robo-advisors. Findings: The analysis revealed that trust and technology acceptance significantly positively influence the intention to adopt robo-advisors. Traditional preferences negatively impact adoption intentions, with a notable mediating effect between trust, technology acceptance, and adoption intentions. Additionally, demographic factors such as age and investment experience play a significant role, with younger investors and those with less investment experience more inclined to adopt robo-advisors. Research limitations/implications: The study's findings highlight the critical importance of building trust and ensuring technology acceptance among potential users. Fintech companies should prioritise enhancing the perceived trustworthiness of their services through robust security measures and transparent operations. Policymakers should promote financial literacy and digital inclusion, particularly in underserved areas. Traditional advisors can integrate robo-advisory services to create a hybrid model. The study's limitations include reliance on self-reported data and a sample that may not fully represent the entire Indian investor population. Originality/value: This paper provides new insights into the adoption of robo-advisors in the Indian context, emphasising the interplay between trust, technology, and traditional financial preferences. It offers valuable guidance for fintech companies, policymakers, and traditional advisors to enhance their strategies and foster broader adoption of robo-advisory services in India.
참고문헌 (22)
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