Psychological and System-Related Barriers to Adopting Blockchain for Operations Management: An Artificial Neural Network Approach
Lai‐Wan Wonga b, Garry Wei‐Han Tanc, Voon‐Hsien Leed, Keng‐Boon Ooic, Amrik Singh Sohale
- aCenter for Advanced Computing &
- bTelecommunications (CACT), Xiamen University Malaysia, Sepang, Malaysia
- cFaculty of Business and Management, UCSI University, Kuala Lumpur, Malaysia
- dFaculty of Business and Finance, Universiti Tunku Abdul Rahman, Kampar, Malaysia
- eFaculty of Business and Economics, Monash University, Clayton, VIC, Australia
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Abstract
This article aims to identify the barriers to adopting blockchain for operations management (BCOM). The barriers discussed include psychological barriers [information barrier (IB), usage barrier (UB), and functional risk barrier (FRB)] and system-related barriers [security and privacy barrier (SPB), compatibility and interoperability barrier (CIB), and system quality barrier (SQB)]. Data collected from 178 responses from manufacturing firms were analyzed using artificial neural network (ANN) to capture both linear and nonlinear relationships in the proposed model that comprises of psychological and systems-related barriers and resistance to BCOM. Nonlinear relationships of the barriers toward BCOM resistance were found. This is a significant contribution as previous studies only found linear relationships. Results also revealed that FRB has the highest level of importance toward blockchain resistance, followed by UB, SPB, and IB. CIB and SQB were found to have the least importance to BCOM. In addition, the negligible values of root-mean square of error concluded that the ANN model exhibits a good model fit. This article contributes to the understanding of BCOM by integrating psychological barriers and systems-related barriers to the current conceptual model. The study also offers practical guidelines and suggestions for future research.