Exploring the Trust Influencing Mechanism of Robo-Advisor Service: A Mixed Method Approach

Cheng, Xusen; Guo, Fei; Chen, Jin; Li, Kejiang; Zhang, Yihui; Gao, Peng

doi:10.3390/su11184917

Cited by 39 publications

(32 citation statements)

References 96 publications

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“…This finding suggests that investment experience lowers the barriers to acceptance of this new technology; thus, experienced customers, who will be less troubled by technology threats, may be a good target sector for robo-advisors. This finding is in line with previous research that found that consumers must have confidence in both the vendor (firm) and the technology to adopt new technology-based services (Belanche et al , 2014) such as robo-advisors (Cheng et al , 2019).…”

Section: Discussionsupporting

confidence: 91%

Intention to use analytical artificial intelligence (AI) in services – the effect of technology readiness and awareness

Flavián

Pérez-Rueda

Belanche

et al. 2021

JOSM

151

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PurposeThe automation of services is rapidly growing, led by sectors such as banking and financial investment. The growing number of investments managed by artificial intelligence (AI) suggests that this technology-based service will become increasingly popular. This study examines how customers' technology readiness and service awareness affect their intention to use analytical AI investment services.Design/methodology/approachThe automation of services is rapidly growing, led by sectors such as banking and financial investment. The growing number of investments managed by AI suggests that this technology-based service will become increasingly popular. This study examines how customers' technology readiness and service awareness affect their intention to use analytical AI investment services.FindingsThe results indicated that customers' technological optimism increases, and insecurity decreases, their intention to use robo-advisors. Surprisingly, feelings of technological discomfort positively influenced robo-advisor adoption. This interesting finding challenges previous insights into technology adoption and value co-creation as analytical AI puts customers into a very passive role and reduces barriers to technology adoption. The research also analyzes how consumers become aware of robo-advisors, and how this influences their acceptance.Originality/valueThis is the first study to analyze the role of customers' technology readiness in the adoption of analytical AI. The authors link the findings to previous technology adoption and automated services' literature and provide specific managerial implications and avenues for further research.

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Section: Discussionsupporting

confidence: 91%

Intention to use analytical artificial intelligence (AI) in services – the effect of technology readiness and awareness

Flavián

Pérez-Rueda

Belanche

et al. 2021

JOSM

151

View full text Add to dashboard Cite

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“…e mining of financial data is to promote the development of financial economy. e content of data mining includes things and dimensions, distribution and relationships, description and prediction, and phenomena and knowledge [21]. e main techniques of data mining include forecasting, clustering, association rules, and time series analysis.…”

Section: Data Mining Technology and Data Storage Technologymentioning

confidence: 99%

[Retracted] Development and Supervision of Robo‐Advisors under Digital Financial Inclusion in Complex Systems

Dai

2021

Complexity

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With the rapid development of the market economy, there are more and more projects in the financial industry, and their complexity and technical requirements are getting higher and higher. The development of computer technology has promoted the birth of robot consultants, and it is of great significance to use robot consultants to manage and supervise financial industry projects. In order to further analyze the development and supervision of robo-advisors under the digital inclusive financial system, this paper uses complex systems and clustering algorithms as technical support to carry out research. First, the traditional K-means algorithm is used to select the initial clustering center, to improve the noise and outlier processing capabilities, and to build a data mining system based on the improved algorithm. Then, a product design model for robo-advisors is built and the risks of robo-advisors are analyzed from three aspects: technology, market, and law. Analyzing the performance of the improved K-means algorithm, in the operation of the experimental dataset B, the accuracy of the clustering result after 6 iterations reached 97.08%, which shows that the algorithm has good performance. During the trial operation of the data mining system, the four types of customers of financial institutions were accurately clustered, and it was concluded that the main type of customers who brought benefits to financial institutions was high-income customers accounting for 10.75%. Robo-advisory product models are used to build five risk-level investment portfolios and conduct risk backtests. Except for the growth and income portfolio, other portfolios have consistently outperformed the performance benchmark during the analyzed time period. Running the research system of this paper in a financial institution, comparing the capital budget before and after the operation, found that the system can improve the accuracy of the budget and reduce the risk of the robo-advisor for the financial institution.

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“…This may have yielded slightly more positive perceptions of current EU legitimacy (HDM condition) as compared to the German population, as previous evidence suggests that higher levels of education are associated with more positive attitudes to the EU (Boomgaarden et al, 2011). Furthermore, the sample may be over-sophisticated in terms of digital literacy and general interest in ADM, which are likely to be associated with perceived legitimacy of as well as trust in algorithmic processes (Cheng et al, 2019). To make stronger claims in terms of the generalizability of the results, future research should use representative national samples.…”

Section: Implications For Future Empirical Researchmentioning

confidence: 88%

Artificial intelligence for political decision-making in the European Union: Effects on citizens’ perceptions of input, throughput, and output legitimacy

Starke

Lünich

2020

Data & Policy

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A lack of political legitimacy undermines the ability of the European Union (EU) to resolve major crises and threatens the stability of the system as a whole. By integrating digital data into political processes, the EU seeks to base decision-making increasingly on sound empirical evidence. In particular, artificial intelligence (AI) systems have the potential to increase political legitimacy by identifying pressing societal issues, forecasting potential policy outcomes, and evaluating policy effectiveness. This paper investigates how citizens’ perceptions of EU input, throughput, and output legitimacy are influenced by three distinct decision-making arrangements: (a) independent human decision-making by EU politicians; (b) independent algorithmic decision-making (ADM) by AI-based systems; and (c) hybrid decision-making (HyDM) by EU politicians and AI-based systems together. The results of a preregistered online experiment (n = 572) suggest that existing EU decision-making arrangements are still perceived as the most participatory and accessible for citizens (input legitimacy). However, regarding the decision-making process itself (throughput legitimacy) and its policy outcomes (output legitimacy), no difference was observed between the status quo and HyDM. Respondents tend to perceive ADM systems as the sole decision-maker to be illegitimate. The paper discusses the implications of these findings for (a) EU legitimacy and (b) data-driven policy-making and outlines (c) avenues for future research.

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Exploring the Trust Influencing Mechanism of Robo-Advisor Service: A Mixed Method Approach

Cited by 39 publications

References 96 publications

Intention to use analytical artificial intelligence (AI) in services – the effect of technology readiness and awareness

Intention to use analytical artificial intelligence (AI) in services – the effect of technology readiness and awareness

[Retracted] Development and Supervision of Robo‐Advisors under Digital Financial Inclusion in Complex Systems

Artificial intelligence for political decision-making in the European Union: Effects on citizens’ perceptions of input, throughput, and output legitimacy

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