Exploring individuals’ purchase willingness for cryptocurrency in an emerging context

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This study aims to investigate the influencing factors of consumers’ willingness to buy cryptocurrency in Malaysia. The targeted population of this study was Malaysian citizens who had knowledge about digital currency such as cryptocurrency. In this study, the data collection process was completed using an online survey questionnaire from several social media groups in Malaysia. They were sent a survey invitation to take part in, and after their approval, their responses were gathered. Five-point Likert scale has been used, where ‘1’ stands for “strongly disagree” and ‘5’ stands for “strongly agree”, to find out the item-wise questionnaire. The final sample size was n = 620. Moreover, 5% significance level and SPSS software were used to analyze the data and evaluate the hypotheses. The outcome of this study exposes that the perception of the price value of the cryptocurrency, perceived trust, and perceived security measure positively and significantly affect consumers’ willingness to buy cryptocurrency. Overall, these variables can explain 49.50% (R2 = 0.495) of the variance in predicting consumers’ willingness to buy cryptocurrency. It is found that among the three determinants, perceived trust (β = 0.569) in cryptocurrency had the highest impact on the intention among Malaysian consumers compared to other variables. This study contributes to the limited existing literature concerning Bitcoin and digital currencies, offering insights that can aid scholars in comprehending the significance of cryptocurrency and delineating its predominant impacts within the Malaysian cryptocurrency space.

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    • Figure 1. Study framework
    • Table 1. Sources of study variables
    • Table 2. Reliability and validity analysis
    • Table 3. Demographic information
    • Table 4. Descriptive analysis of the study variables
    • Table 5. Analysis of the normality test
    • Table 6. Correlation matrix
    • Table 7. Regression coefficient analysis
    • Table 8. Hypotheses results
    • Conceptualization
      K. M. Anwarul Islam, Fandi Omeish, Serajul Islam, Adel Mohammed Yaslam Sarea, Tariq Abdrabbo
    • Data curation
      K. M. Anwarul Islam
    • Formal Analysis
      K. M. Anwarul Islam, Fandi Omeish, Serajul Islam, Adel Mohammed Yaslam Sarea, Tariq Abdrabbo
    • Investigation
      K. M. Anwarul Islam, Fandi Omeish, Serajul Islam, Adel Mohammed Yaslam Sarea, Tariq Abdrabbo
    • Methodology
      K. M. Anwarul Islam, Fandi Omeish, Serajul Islam, Adel Mohammed Yaslam Sarea
    • Project administration
      K. M. Anwarul Islam, Adel Mohammed Yaslam Sarea
    • Resources
      K. M. Anwarul Islam, Fandi Omeish, Serajul Islam, Adel Mohammed Yaslam Sarea, Tariq Abdrabbo
    • Software
      K. M. Anwarul Islam
    • Supervision
      K. M. Anwarul Islam, Adel Mohammed Yaslam Sarea
    • Validation
      K. M. Anwarul Islam, Fandi Omeish, Serajul Islam, Adel Mohammed Yaslam Sarea, Tariq Abdrabbo
    • Visualization
      K. M. Anwarul Islam, Fandi Omeish, Serajul Islam, Adel Mohammed Yaslam Sarea, Tariq Abdrabbo
    • Writing – original draft
      K. M. Anwarul Islam, Fandi Omeish, Serajul Islam, Adel Mohammed Yaslam Sarea, Tariq Abdrabbo
    • Writing – review & editing
      K. M. Anwarul Islam, Fandi Omeish, Serajul Islam, Adel Mohammed Yaslam Sarea, Tariq Abdrabbo
    • Funding acquisition
      Fandi Omeish, Serajul Islam, Tariq Abdrabbo