Mediating Effect of Blockchain Technology on Cryptocurrency Purchase Intention

1. Introduction

This research examines the mediating role of blockchain technology's perceived ease of use and usefulness in cryptocurrency purchase intentions among Turkish investors. The study addresses the gap in understanding how technical blockchain features translate into consumer adoption decisions in emerging markets.

2. Theoretical Framework

3. Research Methodology

4. Results and Analysis

5. Technical Framework

The blockchain architecture can be mathematically represented through cryptographic hash functions:

$H(m) = y$ where $H$ is the cryptographic hash function, $m$ is the transaction data, and $y$ is the fixed-size output

The blockchain consensus mechanism ensures transaction validation through proof-of-work algorithms:

$\text{Find } x \text{ such that } H(block + x) \leq target$

This computational puzzle ensures network security and prevents double-spending attacks, forming the foundation for cryptocurrency trust mechanisms.

6. Experimental Results

The study employed structural equation modeling to test the hypothesized relationships. The conceptual framework diagram illustrates:

• Independent Variables: Customer service, reduced costs, efficiency, security
• Mediating Variables: Perceived ease of use, perceived usefulness
• Dependent Variable: Cryptocurrency purchase intention

The path coefficients revealed that perceived usefulness ($\beta = 0.42$, p < 0.01) had stronger mediation effects than perceived ease of use ($\beta = 0.31$, p < 0.05) in translating security perceptions to purchase intention.

The model fit indices demonstrated acceptable levels (CFI = 0.92, RMSEA = 0.06), supporting the theoretical framework's adequacy.

7. Code Implementation

While the original study didn't include programming code, the mediation analysis logic can be represented through pseudocode:

// Pseudocode for Mediation Analysis
procedure MEDIATION_ANALYSIS
    inputs: IV (independent variables), M (mediators), DV (dependent variable)
    
    // Step 1: Test effect of IV on M (path a)
    for each mediator in M do
        regression_result = LINEAR_REGRESSION(IV → mediator)
        if regression_result.p_value < 0.05 then
            significant_mediators.add(mediator)
        end if
    end for
    
    // Step 2: Test effect of M on DV controlling for IV (path b)
    for each mediator in significant_mediators do
        regression_result = LINEAR_REGRESSION(IV + mediator → DV)
        mediation_effect = path_a * path_b
        
        if mediation_effect.significant then
            report "Significant mediation found"
        end if
    end for
end procedure
            

This analytical approach aligns with the SPSS Process Macro methodology used in the original research, implementing bootstrapping for robust mediation testing.

8. Future Applications

The findings have significant implications for cryptocurrency platforms and financial technology developers:

• User Interface Design: Streamlining blockchain interactions to enhance perceived ease of use
• Educational Tools: Developing resources that demonstrate blockchain usefulness for novice investors
• Regulatory Frameworks: Informing policy decisions that balance innovation with consumer protection
• Cross-Border Applications: Extending the model to international cryptocurrency adoption patterns

Future research should explore cultural variations in blockchain perception and examine how technological advancements like smart contracts influence adoption dynamics.

9. References

1. Efendioğlu, I. H., Akel, G., Değirmenci, B., et al. (2023). The Mediating Effect of Blockchain Technology on the Cryptocurrency Purchase Intention. Social Sciences Research Journal, 12(13), 1536-1559.
2. Iansiti, M., & Lakhani, K. R. (2017). The Truth About Blockchain. Harvard Business Review, 95(1), 118-127.
3. Garg, P., Gupta, B., Chauhan, A. K., et al. (2021). Measuring the perceived benefits of implementing blockchain technology in the banking sector. Technological Forecasting and Social Change, 163, 120407.
4. Reid, F., & Harrigan, M. (2013). An Analysis of Anonymity in the Bitcoin System. In Security and Privacy in Social Networks (pp. 197-223). Springer, New York, NY.
5. Nakamoto, S. (2008). Bitcoin: A Peer-to-Peer Electronic Cash System. Bitcoin Whitepaper.

10. Expert Analysis