Identifying the Determinants of Blockchain Technology Adoption and Proposing a Hybrid Adoption Model Based on TAM and TOE Using the K-means Clustering Method

Abstract :

With the rapid advancement of technology and its integration into both personal and professional life, the decision to accept or reject new technologies remains an open question. Technology adoption theories aim to explain the reasons behind an individual's acceptance of information systems. Numerous studies have been conducted in the domain of technology adoption, resulting in the development of various models. This research investigates the adoption of blockchain technology by integrating the Technology Acceptance Model (TAM) and the Technology–Organization–Environment (TOE) framework. After a brief review of the criteria and limitations of these models, a hybrid adoption model is proposed. Following a comprehensive literature review, 85 blockchain adoption criteria were initially identified. Expert evaluations narrowed these down to 53 key criteria. Using the K-means clustering method in SPSS, the criteria were categorized, and a hybrid model was constructed. The findings indicate that external factors do not influence perceived usefulness and perceived ease of use; however, other components within the TAM framework—categorized under technological, organizational, and environmental dimensions—are affected by external variables. Moreover, the results reveal that the TAM and TOE models are complementary in nature. This study contributes to the broader understanding of blockchain adoption and provides practical guidance for organizations operating in this domain.

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