Factors influencing the adoption of cryptocurrency in Bangladesh: an investigation using the technology acceptance model (TAM)

Abstract

PurposeUsing the technology acceptance model (TAM), this study investigates factors influencing the adoption of cryptocurrency in Bangladesh.Design/methodology/approachData were collected from 346 members of the general public through a structured web survey using snowball sampling. Structural equation modeling was used to analyze the data and assess the reliability and validity of the measurement model.FindingsThe results show that knowledge of cryptocurrency, benefits of use (perceived usefulness), attitude and challenges all have a significant impact on the adoption of cryptocurrency.Research limitations/implicationsThis study was conducted in a single country, relied on self-reported data and used a cross-sectional design, which limits the ability to draw causal inferences. Future research could explore the factors that influence the adoption of cryptocurrency in different countries and regions and incorporate additional variables to provide a more comprehensive understanding of the drivers of intention to use cryptocurrency.Originality/valueThis study contributes to understanding the factors driving the adoption of and intention to use technology-based services, providing insights that can inform the design and implementation of future technology-based services.

Nexus between perception, purpose of use, technical challenges and satisfaction for mobile financial services: theory and empirical evidence from Bangladesh

“…To better understand the factors influencing users’ attitudes and behaviors toward MFS, it is essential to examine the underlying determinants and their relationships. Previous studies have identified a broad range of significant predictors, including perceived usefulness (PU), perceived ease of use (PEOU), subjective norms, perceived benefits (functional and emotional), consumer innovativeness, demographics, perceived risk and facilitating conditions (Islam et al ., 2023; Al-Saedi et al ., 2020; Chi, 2018; Davis et al ., 1989; Gupta and Manrai, 2018; Himel et al ., 2021; Işık et al ., 2024; Jung et al ., 2020; Manrai and Gupta, 2020; Yen and Wu, 2016; Rana et al ., 2023). These factors influence users’ attitudes and behavioral intentions through the lens of the technology acceptance model (TAM) and related behavioral theories.…”