A Value-Cost Model for Cryptocurrency Adoption

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The wide adoption of cryptocurrency is predicted to change the world’s economy. Cryptocurrency mass adoption can provide several advantages to societies, such as decentralization of trust, lower transaction fees, financial inclusion for unbanked and underbanked individuals, increased innovation and improved economic growth. Thus, empirical research on predictors of cryptocurrency adoption is essential to guide practitioners and policymakers in discovering what factors influence the adoption. Previous research relies on existing adoption and human behavioral intentions theories, such as the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM), to name a few. However, these theories fall short in explaining technology-oriented behaviors which are in some way related to economic outcomes. Without such considerations, the aforementioned models are rendered insufficient when attempting to explain cryptocurrency adoption. This study helps to address this gap by developing a Value-Cost Model for Cryptocurrency Adoption. The model is based on Transaction Cost Economics Theory (TCE) and the concept of perceived value. In this study, both cryptocurrency users (n = 173) and non-users (n = 140) completed an online survey assessing their perceptions of cryptocurrency’s perceived value, transaction costs and other related attitudes. The Partial Least Squared Structural Equation Modeling (PLS-SEM) was used to validate the Value-Cost Model. The findings supported the proposed model for both groups, revealing that adoption behavior is explained by perceived value. The users’ model demonstrated significant explanatory power, showing that perceived value accounts for 74% of the variance in the users’ continuous adoption of cryptocurrency—similar explanatory power was found for non-users, with perceived value explaining 63% of the variation in non-users’ intentions to adopt. Perceived economic and non-economic benefits significantly contributed to users’ and non-users’ perceived value. In both groups, the subsequent decrease in the perceived value R2 would be substantial if perceived economic benefit was excluded from the model, suggesting that perceived economic benefit plays a crucial role in explaining the variance in perceived value. The results also showed that users’ and non-users’ perceptions of transaction costs had a negative impact on their overall assessment of the value of cryptocurrencies. This impact was, however, negligible for both groups, as economic and non-economic benefits more strongly influenced the perceived value. Both uncertainty and asset specificity were shown to significantly and positively influence the perceived transaction costs of users and non-users. However, asset specificity was discovered to have a stronger impact on users’ and non-users’ perceptions of transaction costs than uncertainty. Finally, the results showed that transaction frequency was significantly linked with lower perceived transaction costs for users, although the impact of this predictor on the transaction costs was small in magnitude. The Value-Cost Model for cryptocurrency adoption considers the economic characteristics of cryptocurrency and its resemblance to other financial instruments such as stocks. Such consideration required support from preexisting economic models, which allowed for the use of TCE to understand the role of transaction costs in the adoption behavior. While TCE has been applied to investigate technology adoption in the past, it had not yet been utilized in the context of cryptocurrency, highlighting the economic factors affecting adoption behaviors. The proposed model also provides a novel conceptualization of the economic benefit relevant to cryptocurrency. By referencing financial instruments such as stocks, the proposed model introduces two variables (liquidity and prospect of growth) that can be utilized to measure cryptocurrency’s perceived economic benefits. Overall, this study advances our knowledge of the valuation process of cryptocurrencies and how practitioners can create value in them. The study concludes with several recommendations proposed based on the findings of the Value-Cost Model for cryptocurrency adoption.
Cryptocurreny, Adoption, Value, Transaction Costs