Abstract: The study aims to investigate how an individual’s technology awareness, subjective financial literacy and personal innovativeness characteristics impact the intention to use blockchainbased digital currencies such as cryptocurrency. The UTAUT 2 (Unified Theory of Acceptance and Use of Technology 2) model is extended with crucial constructs to develop the conceptual model. A total of 312 responses are analysed using Covariance-Based Structural Equation Modelling (CB-SEM). The moderation effects are assessed using multi-group analysis. The findings show a significant moderating effect of technology awareness and subjective financial literacy on the relationship between performance expectancy (PE) and behavioural intention to use cryptocurrency (BI). It further identified that performance expectancy (PE) mediates personal innovativeness (PI) and usage intentions (BI). The study adds to the growing literature of digital currency adoption by focusing on individual innovativeness, technology awareness and financial literacy. It also proposes a research model that can be generalised for new-age consumer-based financial technology adoption.
Acceptable Thresholds 3 0.050.10 >0.9 >0.7 01 2.3 0.085 0.908 0.83 0.911 Note(s): CMIN/df: Minimum Discrepancy Function by Degrees of Freedom divided, GFI: Goodness of Fit Index, CFI: Comparative Fit Index, RMSEA: Root Mean Square of Error Approximation, NFI: Normed Fit Index. CMIN/df RMSEA CFI GFI NFI 5.5. Hypothesis Testing Results The hypothesised relationships were examined between the variables using SPSS AMOS version 23 software . The results for the hypothesis are presented as 1 = 0.1261 + 0.0212 + 0.5043 + 0.2172 + 0.0783 + 0.1334 0.0175 2 = 0.7151
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J. Theor. Appl. Electron. Commer. Res. 2023, 18 3 = 0.4871 + 0.1952 The model explained a 51% variance in effort expectancy, 40% in performance expectancy and 73% in behavioural intention. The results of the hypothesis are given in Table 5 and represented in Figure 5. The mediating effects of performance expectancy (PE) on the relationship of personal innovativeness (PI) and BI (H9) were examined by applying the bootstrapping method . The direct effect was found insignicant ( = 0.139, p = 0.185) whereas the indirect effect ( = 0.359, p = 0.000) was found signicant. This implies an indirect-only mediation [92,103] (Table 6): Indirectonly: if indirect is signicant but not direct effect . The mediation results are given in Table 6. Table 5. Hypothesis testing results. Hypothesis Relationship Coefcient p-Value Result H1a Personal Innovativeness (PI) Behavioural Intention (BI) 0.126 0.215 Not Supported H1b H1c H2 H3 H4 H5 H6 H7 H8
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Personal Innovativeness (PI)Performance Expectancy (PE) 0.487 Supported *** Table 6. Mediation analysis results. Hypothesis Mediation Relationship Indirect Eect Direct Eect Result H9 Personal Innovativeness (PI) Behavioural Intention (BI) via Perfor-mance Expectancy (PE) 0.359 (p = 0.000) 0.139 (p = 0.185) Indirect only medi-ation Table 7. Moderation analysis results. Eect Moderator High Low 2 Moderation Performance Expec-tancy (PE) Behav-ioural Intention (BI) Estimate t-value Estimate t-value
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*** p < 0.001; ** p < 0.01. Figure 5. Results obtained after testing the hypothesesPath signicance: *** p < 0.001; ** p < 0.05, * p < 0.1, ns is nonsignicant. 6. Discussion Cryptocurrency is an innovations that may disrupt the nancial ecosystem with innumerable benets of faster payments, cross-border payment, robustness, no third-party involvement and trust-less transactions over the existing at-based systems. The study highlights the prime factors that could inuence a users behavioural intention to use new and innovative cryptocurrency (Figure 5). The study identied that an individ-uals innovativeness helps understand the perceived performance gains from using cryp-tocurrencies (H1b) and signicantly impacts the eort expectancy associated with crypto-currencies (H1c). Kalini et al. conrmed a similar phenomenon in the domain of peer-to-peer mobile payments. The study ndings indicate that personal innovativeness does not directly impact (H1a) the usage intention of cryptocurr
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