Towards an understanding of consumers’ FinTech adoption: the case of Open Banking

Chan, Rebecca Sze Oi; Troshani, Indrit; Hill, Sally Rao; Hoffmann, Arvid O. I.

doi:10.1108/ijbm-08-2021-0397

Cited by 102 publications

(105 citation statements)

References 67 publications

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“…Previous researches have shown that the mobile learning attitude depends upon the ease of use of the technology (Tan et al, 2012;Chao, 2019). Effort expectancy was also considered to be an important antecedent for behavioral intentions and actual use behavior for technology adoption (Chan et al, 2022;Dutta et al, 2022;Maita et al, 2022). The findings from various researchers expressed that effort expectancy impacts the investor one way or the other (Palau-Saumell et al, 2019;Saparudin et al, 2020).…”

Section: Literature Review and Hypotheses Development 21 Theories Of ...mentioning

confidence: 99%

Determinants of mobile apps adoption by retail investors for online trading in emerging financial markets

Nair

Shiva

Yadav

et al. 2022

BIJ

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PurposeThe purpose of this study is to investigate the influence of mobile applications on investment decisions by retail investors in stocks and mutual funds. This study focuses on how mobile technologies are applied on mobile apps by retail investors for e-trading in emerging financial markets.Design/methodology/approachThe study explored predictive relevance for the adoption behavior of retail investors under the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. Further, goal contagion theory was applied to investigate the adoption behavior of investors towards e-trading. An adapted questionnaire was used to collect the date from April to June 2021 and data analysis was performed on 507 usable responses. The methodology adopted in this study is variance based partial least square structural equational modelling (PLS-SEM). Additionally, the study explains important and performing constructs based on the response of retail investors towards mobile app usage for investment decisions.FindingsThe study shows that effort expectancy, performance expectancy followed by perceived return were the primary determinants of behavioral intentions to use mobile applications by retail investors for e-trading. Further, habit of investors determined the adoption behavior of investors towards mobile apps. Additionally, the study revealed that perceived risk is not an important aspect for retail investors in comparison to perceived return.Research limitations/implicationsThe study in future can address to the aspect of personality traits of retail investors for technology adoption for investment decisions. Further investigation is required on addressing unobserved heterogeneity of retail investors towards technology adoption process in emerging financial markets.Practical implicationsThe study provides theoretical and practical implications for retail investors, financial advisors and technology companies to understand the behavioral pattern and mobile apps adoption behavior of retail investors in emerging financial market. The findings in the study will help broking firms to sensitize their clients for effective use of their respective mobile apps for e-trading purposes. The study will strengthen the knowledge of financial advisors to understand investment behavior of retail investors in emerging financial markets.Originality/valueThis study unfolds a novel framework of research to understand the technology adoption pattern of retail investors for e-trading by mobile applications in emerging financial markets. The present study provides significant understanding in the domain of technology adoption by retail investors under behavioral finance environment.

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Section: Literature Review and Hypotheses Development 21 Theories Of ...mentioning

confidence: 99%

Determinants of mobile apps adoption by retail investors for online trading in emerging financial markets

Nair

Shiva

Yadav

et al. 2022

BIJ

View full text Add to dashboard Cite

show abstract

“…In the case of the used model, the value of this parameter is 0.582, which means that the correlations established in it can explain 58.2% of the ITU variance. This is an above-average level because, as Chan et al (2022) observes, for social studies, the value of this parameter fluctuates in the range of 0.3-0.5. R-Squared for all latent variables of the structural model is presented in Table 7.…”

Section: Structural Modelmentioning

confidence: 78%

Adoption factors in digital lending services offered by FinTech lenders

Adamek

Solarz²

2023

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Research background: Traditional financial institutions are facing new competitors ? FinTech lenders. The development of these entities and their services depends on many factors, including the level of their acceptance and use by potential and/or current customers. This acceptance determines the ability to create desired financial results and defines the set of FinTech lenders? activities and also their environment aimed at shaping the offer which meets their consumers? expectations. The limited number of studies addressing the identification and assessment of the impact exerted by the adoption factors of lending services offered by FinTech lenders and the lack of such analyzes relating to these decisions made by consumers from Central and Eastern Europe argue for the need to conduct such research. Purpose of the article: Identify factors driving consumers? adoption of digital lending services offered by FinTech lenders in Poland. Methods: Critical analysis of the source literature, descriptive and comparative analysis, diagnostic survey, econometric methods (PCA, SEM used in the TAM). Empirical data come from the surveys carried out in May 2022 using the CAWI method and covering a representative sample of 1,000 Poles. Findings & value added: The study identified factors driving consumers? adoption of digital lending services, including perceived trust, risk, usefulness and financial health. It has been proven that the perceived ease of use and innovation do not represent the statistically significant constructs influencing the accepted adoption attitudes. The adopted research model shows a considerable power to explain the intention of using digital loans. The article is the first scientific study of this type discussing the identification of adoption factors for loan services offered by FinTech lenders operating on the Central and Eastern European market. The presented example of Poland being the leader in this dynamically developing market provides the background for conducting international comparative studies in the future.

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“…In particular, there are some recent studies aimed at investigating the effect of EE on the adoption of financial products and services. For example, Alalwan et al (2018) reported a study on the adoption of internet banking, Senyo and Osabutey (2020) investigated the intention to use mobile money services, Chan et al (2022) addressed the factors affecting the use of open banking. All these studies support the significant relationship between EE and behavioral intention.…”

Section: Hypothesis Developmentmentioning

confidence: 99%

Investigating the intention of purchasing private pension scheme based on an integrated FBM-UTAUT model: The case of China

Guo

Gong

2023

Front. Psychol.

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The newly established private pension scheme in China has received great attention as it would be an important supplement to China’s social safety net and corporate annuity amid an aging population. It provides a way of helping to address the challenge of ensuring adequate retirement income, and the scheme is expected to grow significantly in the coming years. This study investigates factors affecting the intention of purchasing the private pension scheme using a conceptual model based on the integration of Fogg Behavioral Model (FBM) and Unified Theory of Acceptance and Use of Technology (UTAUT) model. The questionnaire-based data from a sample of 462 respondents had been analyzed. Both exploratory factor analysis and confirmatory factor analysis were used to assess validity. The hypothesized relationships in the integrated FBM-UTAUT model were tested using structural equation modeling. The research findings indicate that anticipation, social influence, effort expectancy, performance expectancy, side benefits and facilitating conditions have significant positive impacts on intention to purchase. According to the exploratory factor analysis, the integrated FBM-UTAUT model can explain more than 70% of the total variance. Meanwhile, effort expectancy can be affected by time effort, thought effort and physical effort collectively, while performance expectancy can be affected by risk and trust. It is revealed that the integrated FBM-UTAUT model can be effective in explaining purchase intentions in a private pension scheme context, and this study is expected to offer helpful advice on the design of pension products and the reform of pension policies.

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Towards an understanding of consumers’ FinTech adoption: the case of Open Banking

Cited by 102 publications

References 67 publications

Determinants of mobile apps adoption by retail investors for online trading in emerging financial markets

Determinants of mobile apps adoption by retail investors for online trading in emerging financial markets

Adoption factors in digital lending services offered by FinTech lenders

Investigating the intention of purchasing private pension scheme based on an integrated FBM-UTAUT model: The case of China

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