Mapping the determinants influencing the adoption of blockchain innovations in SMEs: A multi-stage pythagorean fuzzy decision-making framework

Expanding blockchain applications is a novel issue in emerging countries and developed economies. Therefore, studying the effective adoption of this technology is a fundamental requirement for its successful implementation. The dimensions that should be considered in these studies are those that lead to the effective adoption of blockchain innovations, which have not been deeply investigated. Hence, the current research employs an embedded mixed method to identify and analyse these factors. First, a systematic literature review (SLR) and thematic analysis (TA) are conducted using the SPAR-4-SLR protocol to identify the key factors in blockchain adoption. In addition, the extracted factors are screened and finalised in the next step using a Pythagorean fuzzy Delphi (PFD) method. Afterwards, a Pythagorean fuzzy (PF)-interpretive structural modelling (ISM)-cross-impact matrix multiplication applied to classification (MICMAC) investigates the cause and effect of the screened factors and provides a level-based conceptual framework. As a result of implementing the SLR-TA, 15 factors/themes are extracted, nine of which are selected as the most determinant factors based on the PFD method. Three drivers, one dependent, and five linkage factors are identified using the PF-ISM-MICMAC method. Based on these findings, a four-level conceptual framework is proposed to map the key determinants influencing the adoption of blockchain innovations in SMEs within an emerging economy. • Maps key determinants influencing blockchain innovation adoption in SMEs. • Employs a multi-stage Pythagorean fuzzy decision-making framework. • Uses SLR and thematic analysis to extract innovation-related factors. • Proposes a four-level framework for blockchain innovation adoption in emerging economies.