Impact of banking functions on online investment intention in India: Examining the mediating role of service experience
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DOIhttp://dx.doi.org/10.21511/imfi.21(1).2024.11
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Article InfoVolume 21 2024, Issue #1, pp. 131-145
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The study aimed to determine the various antecedents of banking functions that may lead to consumers’ intention to use online banking channels for investment with the role of service experience in mediating the relationship between banking function, online investment intention, cost perception, and behavioral factors. Data were collected through an online survey to understand consumer perceptions and behavioral intentions among online banking users in India. The population of this study is Indian residents who are customers of banks providing online services. Purposive sampling and snowball sampling were used as sampling methods. The study used an online survey with a list-based sample frame using social media chat functions or messaging applications in which the Google forms link was shared. A total of 561 valid responses were successfully accumulated from 1,136 Google forms, indicating a response rate of 61.78%. The study employs SEM-PLS using PLS 2.0 software for data analysis. The results validated the direct effect of online investment intention through a bank on different components of banking channel function linkages: information and service awareness, transactional efficacy, trust, brand effect, convenience, and information technology support (p < 0.05). The findings also highlighted that customer service experience mediates the relationship between banking channel function and consumers’ investment intention through online banking channels, significantly impacting customers’ cost perception and behavioral factors (p < 0.05). The research implications are expected to improve the banking service experience of customers and might motivate them to use the online banking channel for investment.
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JEL Classification (Paper profile tab)M31, G21, G41
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References77
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Tables7
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Figures2
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- Figure 1. Conceptual framework
- Figure 2. Empirical model
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- Table 1. Demographic profile of respondents
- Table 2. Factor analysis results (N = 561)
- Table 3. PLS-SEM model fit indices
- Table 4. Hypotheses testing results
- Table 5. Results of R squares and adjusted R square
- Table 6. Discriminant validity: heterotrait-monotrait (HTMT) criterion
- Table A1. Measurement scales
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