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1 – 2 of 2Huosong Xia, Qian Zhang, Justin Zuopeng Zhang and Leven J. Zheng
This paper aims to investigate investors' willingness to use robo-advisors from customers' perspectives and analyzes the factors that drive them to use robo-advisors, including…
Abstract
Purpose
This paper aims to investigate investors' willingness to use robo-advisors from customers' perspectives and analyzes the factors that drive them to use robo-advisors, including perceived usefulness and emotional response.
Design/methodology/approach
The authors extend the Cognition-Affect-Conation (CAC) framework to the behavioral domain of robo-advisor users on financial technology platforms and conduct an empirical study based on 248 valid questionnaires.
Findings
The authors find two types of factors driving the willingness to use robo-advisors: perceived usefulness, trust and perceived risk as external driving forces and investor sentiment as an internal driving force. Trust has a significant positive effect on willingness to use, and arousal in emotional response plays a mediating role between perceived usefulness and willingness to use.
Originality/value
This research provides valuable insights for financial institutions to engage in robo-advisor innovation from customers' perspectives.
Details
Keywords
Huosong Xia, Siyi Chen, Justin Z. Zhang and Yulong Liu
The rise of the mobile Internet has accumulated much text information in various online financial forums. Such information often contains the emotional attitudes of investors…
Abstract
Purpose
The rise of the mobile Internet has accumulated much text information in various online financial forums. Such information often contains the emotional attitudes of investors toward financial technology (fintech) platforms, so extracting the sentimental tendency information has great practical value for the development of fintech platforms. Based on the investor sentiment theory, the paper aims to analyze the relevant social media data and test the influence path of online news evaluation on the stock price fluctuation of fintech platforms.
Design/methodology/approach
Taking Oriental Fortune as the research object, this paper selects multiple variables such as stock bar popularity, snowball popularity, news popularity and news sentiment scores collected by UQER and combines the sentiment scores of single daily news into a daily sentiment score. Based on the period from November 1, 2019 to March 31, 2020, during the emergence of the coronavirus disease 2019 (COVID-19) pandemic as the background, the authors conduct the Granger causality test based on the vector autoregressive (VAR) model and analyze the relevant evaluation of Oriental Fortune through the empirical model.
Findings
The authors' results show that different online evaluations impact the rise and fall of stock prices differently, while news popularity has the most significant impact. Besides, news sentiment scores on share price fluctuation have a relatively substantial influence. These findings indicate that the authoritative news evaluation can strongly guide investors to make relevant investment behavior operations in the information dissemination process, significantly affecting stock prices.
Originality/value
The research findings of this paper have good inspiration and reference values for investors and financial regulators.
Details