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Article
Publication date: 3 February 2021

Lixuan Zhang, Iryna Pentina and Yuhong Fan

This study aims to investigate the differences in consumers’ perceptions of trust, performance expectancy and intention to hire between human financial advisors with…

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Abstract

Purpose

This study aims to investigate the differences in consumers’ perceptions of trust, performance expectancy and intention to hire between human financial advisors with high/low expertise and robo-advisors.

Design/methodology/approach

Three experiments were conducted. The respondents were randomly assigned to human advisors with high/low expertise or a robo-advisor. Data were analyzed using MANCOVA.

Findings

The results suggest that consumers prefer human financial advisors with high expertise to robo-advisors. There are no significant differences between robo-advisors and novice financial advisors regarding performance expectancy and intention to hire.

Originality/value

This pioneering study extends the self-service technology adoption theory to examine adoption of robo-advisors vs human financial advisors with different expertise levels. To the best of the authors’ knowledge, it is among the first studies to address multi-dimensionality of trust in the context of artificial intelligence-based self-service technologies.

Details

Journal of Services Marketing, vol. 35 no. 5
Type: Research Article
ISSN: 0887-6045

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Article
Publication date: 21 September 2021

Carlos Flavián, Alfredo Pérez-Rueda, Daniel Belanche and Luis V. Casaló

The automation of services is rapidly growing, led by sectors such as banking and financial investment. The growing number of investments managed by artificial…

Abstract

Purpose

The 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/approach

Hypotheses were tested with a data set of 404 North American-based potential customers of robo-advisors. In addition to technology readiness dimensions, the potential customers' characteristics were included in the framework as moderating factors (age, gender and previous experience with financial investment services). A post-hoc analysis examined the roles of service awareness and the financial advisor's name (i.e., robo-advisor vs. AI-advisor).

Findings

The 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/value

This 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.

Details

Journal of Service Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1757-5818

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Article
Publication date: 6 August 2020

Yung-Ming Cheng

The purpose of this study is to propose a synthetic post-adoption model based on the expectation-confirmation model (ECM) and flow theory to examine whether the fit…

Abstract

Purpose

The purpose of this study is to propose a synthetic post-adoption model based on the expectation-confirmation model (ECM) and flow theory to examine whether the fit factor, network factors and psychological factors as antecedents to end-users’ beliefs can affect their continuance intention of the robo-advisor.

Design/methodology/approach

This study used the research model based on ECM and flow theory to examine the effects of the fit factor, network factors and psychological factors on end-users’ beliefs and continuance intention of the robo-advisor. Sample data were collected from end-users at three financial services companies in Taiwan. A total of 450 questionnaires were distributed and 360 (80.0%) usable questionnaires were analyzed using structural equation modeling.

Findings

This study proposes a solid research model that based on ECM and flow theory, three types of factors, namely, fit factor, network factors and psychological factors, as antecedents to end-users’ continuance intention of the robo-advisor have been examined and this study’s results strongly support the research model with all hypothesized links being significant.

Originality/value

It is particularly worth mentioning that a synthetic post-adoption model can be proposed in this study by introducing the fit factor extracted from task-technology fit model, network factors originated from the theory of network externalities and psychological factors derived from uses and gratifications theory as antecedents to perceived usefulness, confirmation, satisfaction and continuance intention referred in ECM and flow experience derived from flow theory. Thus, this study’s research model and findings can reveal deep insights into the evaluation of determinants in the field of end-users’ continuance intention of the robo-advisor.

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Article
Publication date: 5 September 2021

Ankita Bhatia, Arti Chandani, Rizwana Atiq, Mita Mehta and Rajiv Divekar

The purpose of this study is to gauge the awareness and perception of Indian individual investors about a new fintech innovation known as robo-advisors in the wealth…

Abstract

Purpose

The purpose of this study is to gauge the awareness and perception of Indian individual investors about a new fintech innovation known as robo-advisors in the wealth management scenario. Robo-advisors are comprehensive automated online advisory platforms that help investors in managing wealth by recommending portfolio allocations, which are based on certain algorithms.

Design/methodology/approach

This is a phenomenological qualitative study that used five focussed group discussions to gather the stipulated information. Purposive sampling was used and the sample comprised investors who actively invest in the Indian stock market. A semi-structured questionnaire and homogeneous discussions were used for this study. Discussion time for all the groups was 203 min. One of the authors moderated the discussions and translated the audio recordings verbatim. Subsequently, content analysis was carried out by using the NVIVO 12 software (QSR International) to derive different themes.

Findings

Factors such as cost-effectiveness, trust, data security, behavioural biases and sentiments of the investors were observed as crucial points which significantly impacted the perception of the investors. Furthermore, several suggestions on different ways to enhance the awareness levels of investors were brought up by the participants during the discussions. It was observed that some investors perceive robo-advisors as only an alternative for fund/wealth managers/brokers for quantitative analysis. Also, they strongly believe that human intervention is necessary to gauge the emotions of the investors. Hence, at present, robo-advisors for the Indian stock market, act only as a supplementary service rather than a substitute for financial advisors.

Research limitations/implications

Due to the explorative nature of the study and limited participants, the findings of the study cannot be generalised to the overall population. Future research is imperative to study the dynamic nature of artificial intelligence (AI) theories and investigate whether they are able to capture the sentiments of individual investors and human sentiments impacting the market.

Practical implications

This study gives an insight into the awareness, perception and opinion of the investors about robo-advisory services. From a managerial perspective, the findings suggest that additional attention needs to be devoted to the adoption and inculcation of AI and machine learning theories while building algorithms or logic to come up with effective models. Many investors expressed discontent with the current design of risk profiles of the investors. This helps to provide feedback for developers and designers of robo-advisors to include advanced and detailed programming to be able to do risk profiling in a more comprehensive and precise manner.

Social implications

In the future, robo-advisors will change the wealth management scenario. It is well-established that data is the new oil for all businesses in the present times. Technologies such as robo-advisor, need to evolve further in terms of predicting unstructured data, improvising qualitative analysis techniques to include the ability to gauge emotions of investors and markets in real-time. Additionally, the behavioural biases of both the programmers and the investors need to be taken care of simultaneously while designing these automated decision support systems.

Originality/value

This study fulfils an identified gap in the literature regarding the investors’ perception of new fintech innovation, that is, robo-advisors. It also clarifies the confusion about the awareness level of robo-advisors amongst Indian individual investors by examining their attitudes and by suggesting innovations for future research. To the best of the authors’ knowledge, this study is the first to investigate the awareness, perception and attitudes of individual investors towards robo-advisors.

Details

Qualitative Research in Financial Markets, vol. 13 no. 5
Type: Research Article
ISSN: 1755-4179

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Article
Publication date: 28 July 2021

Ankita Bhatia, Arti Chandani, Rajiv Divekar, Mita Mehta and Neeraja Vijay

Innovation is the way of life and we see various innovative techniques and methods being introduced in our daily life. This study aims to focus on digital innovation in…

Abstract

Purpose

Innovation is the way of life and we see various innovative techniques and methods being introduced in our daily life. This study aims to focus on digital innovation in the wealth management domain. This study examines the effect of usage of robo-advisory services in investment decision-making and behavioural biases, i.e. overconfidence and loss aversion. Such studies are more pronounced in developed countries and little has been studied about investor behaviour in association with advisory services in developing countries such as India.

Design/methodology/approach

Overconfidence and loss-aversion biases, investment decision-making and advisory services questions are measured using a five-point Likert scale. The number of respondents was 172 investors. A purposive sampling is used for gathering responses from investors. Structural equation modeling model was run using AMOS 22 version software package.

Findings

The authors found that behavioural biases positively and significantly influence the irrationalities of investment decision-making. The findings of this study also provide empirical evidence that the usage of robo-advisory services, by individual investors, is still incapable of mitigating behavioural biases, such as overconfidence bias and loss-aversion bias.

Research limitations/implications

The sample size of this study could be a limiting factor. This study is limited only to two biases, while other behavioural biases affect the investment decision-making of the investors, which can be considered for future research along with the impact of robo-advisory services in different socio-cultural backgrounds.

Practical implications

This study will assist fintech start-ups, banks, architecture of robo advisors, product owners and wealth management service providers improvise their products, platforms and offerings of these automated advisory services. This could help individual investors to mitigate their behavioural biases in investment decision-making.

Social implications

This study is useful to society as the awareness of robo-advisory services is very less, at present, and there is a need to increase the usage of these services to extend the benefit of this to the lower stratum of society. These services would be useful to all investors who find it difficult to afford financial advisors and help them mitigate their behavioural biases for investment decision-making.

Originality/value

This study is the first of its type that establishes the linkage between behavioural biases, digital innovation in fintech, i.e. robo-advisory services and individual investor’s investment decision-making in individual investor of the Indian stock market.

Details

International Journal of Innovation Science, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1757-2223

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Article
Publication date: 19 March 2018

Enrico Beltramini

The purpose of this paper is to introduce the work of Mark Coeckelbergh into the field of management.

Abstract

Purpose

The purpose of this paper is to introduce the work of Mark Coeckelbergh into the field of management.

Design/methodology/approach

This is a conceptual paper with interviews.

Findings

The author suggests that Coeckelberghs’ considerations of an anthropology of vulnerability have the potential to provide a rich and insightful exploration of the machine-human interface, which is not afforded by many of the current approaches taken in this field. Their development of an anthropology of vulnerability suggests an approach to the machine-human interface that re-frames the machine-human interface in terms of human vulnerability, rather than machine’s performance, and sustains that the machine-human interface can be understood in terms of the transfer of human vulnerability.

Research limitations/implications

This paper reveals some of the possibilities inherent in Coeckelbergh’s theories by providing an analysis of a specific event, the recent introduction of robo-advisors in portfolio management, from a Coeckelberghian perspective and by exploring some of the implications of this type of approach for the machine-human interface.

Originality/value

As far as the author knows, there is no previous paper on this topic.

Details

Baltic Journal of Management, vol. 13 no. 2
Type: Research Article
ISSN: 1746-5265

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Abstract

Details

Investment Traps Exposed
Type: Book
ISBN: 978-1-78714-253-4

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Article
Publication date: 29 November 2021

Janin Karoli Hentzen, Arvid Hoffmann, Rebecca Dolan and Erol Pala

The objective of this study is to provide a systematic review of the literature on artificial intelligence (AI) in customer-facing financial services, providing an…

Abstract

Purpose

The objective of this study is to provide a systematic review of the literature on artificial intelligence (AI) in customer-facing financial services, providing an overview of explored contexts and research foci, identifying gaps in the literature and setting a comprehensive agenda for future research.

Design/methodology/approach

Combining database (i.e. Scopus, Web of Science, EBSCO, ScienceDirect) and manual journal search, the authors identify 90 articles published in Australian Business Deans Council (ABDC) journals for investigation, using the TCCM (Theory, Context, Characteristics and Methodology) framework.

Findings

The results indicate a split between data-driven and theory-driven research, with most studies either adopting an experimental research design focused on testing the accuracy and performance of AI algorithms to assist with credit scoring or investigating AI consumer adoption behaviors in a banking context. The authors call for more research building overarching theories or extending existing theoretical perspectives, such as actor networks. More empirical research is required, especially focusing on consumers' financial behaviors as well as the role of regulation, ethics and policy concerned with AI in financial service contexts, such as insurance or pensions.

Research limitations/implications

The review focuses on AI in customer-facing financial services. Future work may want to investigate back-office and operations contexts.

Originality/value

The authors are the first to systematically synthesize the literature on the use of AI in customer-facing financial services, offering a valuable agenda for future research.

Details

International Journal of Bank Marketing, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0265-2323

Keywords

Content available
Article
Publication date: 19 May 2020

Sumit Agarwal and Yeow Hwee Chua

This paper reviews recent advances in the empirical literature of FinTech and household finance.

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Abstract

Purpose

This paper reviews recent advances in the empirical literature of FinTech and household finance.

Design/methodology/approach

We survey the effects of FinTech on three different aspects of household finance: payments, lending and portfolio decisions. Specifically, we examine the impact of digital payments, mobile money, FinTech lending, marketplace lending, robo-advising and crowd-funding.

Findings

Studies suggest that FinTech has positively benefited households by increasing consumption and borrowing. This allows them to smoothen their consumption across time. Furthermore, there is an improvement in their portfolio diversification. Nonetheless, there is also evidence that certain households overconsume and borrow beyond their means.

Originality/value

Despite the importance of this topic, there has been a lack of empirical evidence until recently. In this paper, we take stock of the empirical evidence in the literature through the lens of household finance

Details

China Finance Review International, vol. 10 no. 4
Type: Research Article
ISSN: 2044-1398

Keywords

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Abstract

Details

Investment Traps Exposed
Type: Book
ISBN: 978-1-78714-253-4

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