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Blockchain technology is poised to transform accounting and auditing by enabling secure, transparent, and immutable financial records. This study models accounting professionals’ intentions to switch from traditional systems to blockchain-based accounting systems (BBAS) using a Push–Pull–Mooring (PPM) framework. Employing a hybrid methodology, Partial Least Squares Structural Equation Modeling (PLS-SEM) and Artificial Neural Network (ANN) analyses were conducted on survey data of 294 respondents. PLS-SEM results indicate that security risk, traceability, immutability, inertia, and supportive government norms significantly and positively influence switching intentions, while switching costs exert a negative effect. Perceived inefficiencies did not significantly predict intentions to switch. ANN analysis corroborates these findings, highlighting traceability, government norms, and immutability as the most critical predictors of adoption.

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Modeling Switching Intentions Toward Blockchain-Based Accounting: A Push–Pull–Mooring Perspective with Hybrid PLS-SEM and ANN Approach

  • 会议论文

  • 发表日期：

    2026年

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  • Vikas,
  • Ganesh Prasad Sahu

摘要

Blockchain technology is poised to transform accounting and auditing by enabling secure, transparent, and immutable financial records. This study models accounting professionals’ intentions to switch from traditional systems to blockchain-based accounting systems (BBAS) using a Push–Pull–Mooring (PPM) framework. Employing a hybrid methodology, Partial Least Squares Structural Equation Modeling (PLS-SEM) and Artificial Neural Network (ANN) analyses were conducted on survey data of 294 respondents. PLS-SEM results indicate that security risk, traceability, immutability, inertia, and supportive government norms significantly and positively influence switching intentions, while switching costs exert a negative effect. Perceived inefficiencies did not significantly predict intentions to switch. ANN analysis corroborates these findings, highlighting traceability, government norms, and immutability as the most critical predictors of adoption.