Braving Bitcoin: A technology acceptance model (TAM) analysis

Daniel Folkinshteyn, Mark Lennon

Research output: Contribution to journalArticlepeer-review

134 Scopus citations


The technology acceptance model (TAM) is an important analytical tool in the study of the social mechanisms of technology adoption, and this model has received considerable attention in the literature. Although empirical support for the model has varied depending on situation specifics, it remains a popular and useful conceptual framework for analysis of factors contributing to technology acceptance or rejection by the relevant constituencies. Bitcoin is an entirely digital distributed currency, the disruptive and disintermediating nature of which has fueled the tremendous growth of the financial technology space over the past few years. Bitcoin’s distributed, verifiable, and immutable public transaction ledger, known as the blockchain, holds out the promise of fast, cheap, peer-to-peer financial transactions, as well as significant efficiencies in the transfer of other assets via overlay networks. Through an extensive review of the existing academic and practitioner literature about both TAM and Bitcoin, we use the TAM framework to analyze aspects of the technology acceptance process in the case of Bitcoin as a currency and the blockchain as a financial technology. We present our findings from the perspective of both developers and end users, in order to identify similarities and differences in how various stakeholders accept this new technology. We illustrate these findings with a series of condensed case studies drawn from secondary sources. These findings are then triangulated with an in-depth single case study of a blockchain-based auction system drawn from primary sources.

Original languageEnglish (US)
Pages (from-to)220-249
Number of pages30
JournalJournal of Information Technology Case and Application Research
Issue number4
StatePublished - Oct 1 2016

All Science Journal Classification (ASJC) codes

  • Management Science and Operations Research
  • Information Systems and Management


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