Mobile investment technology adoption among investors

Fan, Lu

doi:10.1108/ijbm-11-2020-0551

Cited by 30 publications

(34 citation statements)

References 40 publications

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“…, 2019; Seiler and Fanenbruck, 2021; Wang et al. , 2021; Fan, 2021). We add to this literature by showing that even if an individual was to adopt an AI-enabled system (robo-advisor), their intention to invest may be inhibited because they did not receive the information from a human advisor.…”

Section: Discussionmentioning

confidence: 99%

“…First, we tested a novel prediction that financial information provided by a robo-advisor (rather than a human) would result in less willingness to invest. This is significant because most research has previously focussed on the antecedents of adoption (Zhang et al, 2021;Belanche et al, 2019;Seiler and Fanenbruck, 2021;Wang et al, 2021;Fan, 2021). We add to this literature by showing that even if an individual was to adopt an AI-enabled system (robo-advisor), their intention to invest may be inhibited because they did not receive the information from a human advisor.…”

Section: Theoretical Contributionsmentioning

confidence: 95%

“…Part of this growth may be attributed to the fact the ease and usefulness of robo-advisors has a positive influence on attitudes towards and adoption of the technology (Belanche et al, 2019). In fact, there is a large body of research that has examined why consumers are willing to adopt robo-advisors (see Hentzen et al, 2021 for a review) across a range of countries including Germany (Seiler and Fanenbruck, 2021), Pakistan (Wang et al, 2021), Malaysia (Gan et al, 2021) and USA (Fan, 2021). However, recent research (Zhang et al, 2021) has suggested consumers prefer human advisers with high expertise over robo-advisors.…”

Section: Introductionmentioning

confidence: 99%

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Man vs machine: how artificial intelligence in banking influences consumer belief in financial advice

Northey

Hunter

Mulcahy

et al. 2022

IJBM

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PurposeThis research set out to examine how financial advice provided by a human advisor (vs robo-advisor) influences investment intentions in a retail banking context.Design/methodology/approachIn two experiments, between-subjects experimental designs were employed to test the primary hypothesis and identify the underlying causal mechanisms that influence consumer investment decisions.FindingsThe results from two experiments indicate consumers have more belief in financial advice provided by a human financial advisor (vs robo-advisor), when the level of involvement is high. The authors also identify customer belief in the information and the customer's perception of the bank's “customer focus” as the causal mechanisms that have downstream effects on investment intentions.Originality/valueThis research is the first to examine how financial advice received from a human advisor (vs robo-advisor) influences investment intentions in a retail banking context. Furthermore, this research identifies high involvement as a key boundary condition moderating the effects on investment intention and identifies consumer belief in the advice, as well as the bank's perceived level of customer focus as the causal mechanisms influencing investment intentions.

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Section: Discussionmentioning

confidence: 99%

Section: Theoretical Contributionsmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

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Man vs machine: how artificial intelligence in banking influences consumer belief in financial advice

Northey

Hunter

Mulcahy

et al. 2022

IJBM

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“…Indeed, research suggests that users' trust that smartphones meet usage expectations, and their familiarity with smartphones, will positively influence the continued use of technology (Idemudia and Raisinghani 2014). A recent study noted that users' experience with mobile payments and transfers were significant factors that influenced their adoption of mobile investment technologies (Fan 2021). Thus, individuals not accustomed to digital technologies such as the internet or mobile phones for payment, purchase, or cash transactions may not be interested in adopting innovative services such as FinTechs.…”

Section: Discussionmentioning

confidence: 99%

Opportunities and Barriers for FinTech in SAARC and ASEAN Countries

Imam

McInnes

Colombage

et al. 2022

JRFM

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This article assesses the opportunities and challenges for different categories of FinTechs in the SAARC and ASEAN regions. We consider the global financial inclusion data released by the World Bank and map the responses to gain insights into the opportunities and challenges for FinTechs in the respective regions. We develop a new index, termed the FinTech Opportunity Index (FOI), to conceptualise the opportunities and barriers based on individual savings, borrowings, purchasing behaviour, and payment preferences. We note that FinTech services have potential opportunities for expansion in the ASEAN regions but less so in the SAARC regions. The need for different types of FinTech services varies between regions. Services such as crowdfunding, neobanks, and InsurTech have potential in the ASEAN regions, especially with the positive attitude towards entrepreneurship and asset investments. In the SAARC regions, InsurTechs linked to health care has potential along with LendTechs and neobanks. We further note that males, and the young are more likely adopters of FinTechs in both regions. The analysis suggests the need for innovative promotions and education to motivate the more sceptical, especially women and the elderly population, to adopt FinTech services.

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“…Racial/ethnic differences in financial technology adoption Previous studies have documented a difference in general use behaviors related to innovative technology by race and ethnicity. Several studies have reported that compared to Caucasian/ Whites, racial/ethnic minorities have adopted mobile banking to a greater extent (Blanco et al, 2017;Federal Deposit Insurance Corporation, 2020;Federal Reserve Board, 2016), rely on mobile investment recommendations, make investments using a mobile device (Fan, 2022) and use personal financial management (PFM) technology (Walsh and Lim, 2020). However, the percentage of online banking users was higher among Whites (26.7%) compared to Blacks (12%), Hispanics (11.1%), Asians (25.7%) and Native Americans/Alaska Natives (17%) in 2019 (Federal Deposit Insurance Corporation, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

Racial/ethnic differences in mobile payment usage: what do we know, and what do we need to know?

Nam

Lee

Kim

2022

IJBM

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PurposeThe purpose of this study is to investigate the racial/ethnic differences in mobile payment use and to explore the contributing factors to the differences.Design/methodology/approachThis study used the 2018 National Financial Capability Study (NFCS) dataset to examine racial/ethnic disparities in mobile payment use. Logistic regression analyses were conducted to confirm racial/ethnic differences, and Blinder–Oaxaca decomposition analyses were performed to identify which factors explain the differences among the groups.FindingsThe authors discovered that Whites use mobile payment less than Blacks, Hispanics and Asians/others. The results revealed that prior experiences with mobile financial services, including transfer, banking and budgeting applications, all play considerable roles in explaining the disparities between Whites and other racial/ethnic groups.Originality/valueThis is one of the few studies to examine racial/ethnic disparities in mobile payment use with a particular focus on the influence of users' past experience with technology. The results provide insights for researchers, professionals, educators and policymakers into ways to promote future use of mobile payment.

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Mobile investment technology adoption among investors

Cited by 30 publications

References 40 publications

Man vs machine: how artificial intelligence in banking influences consumer belief in financial advice

Man vs machine: how artificial intelligence in banking influences consumer belief in financial advice

Opportunities and Barriers for FinTech in SAARC and ASEAN Countries

Racial/ethnic differences in mobile payment usage: what do we know, and what do we need to know?

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