Barriers Affecting Blockchain Adoption in Emission Data Collection Using Fuzzy Delphi and Fuzzy DEMATEL

Abstract

Despite the promising improvements that blockchain can introduce such as enhancing efficiency, transparency, immutability and traceability, the technology is still not widely adopted in many industries and sectors. Emission management being one of these industries that has been rapidly improving by using state-of-the-art solutions are one of these industries but still lagging in utilizing blockchain to transform its processes due to its underlying adoption barriers. Hence, this study aims to identify and prioritize the barriers that are related to blockchain adoption in emission data collection based on the causal relationships between them. Utilizing a mixed method approach, we first conduct a comprehensive literature review and expert interviews to pinpoint key barriers. Utilizing the extension of Technology-Organizational-Environment (TOE) and Diffusion of Innovation (DOI) theory, these barriers are then categorized into technological, organizational, environmental and external domains through the development of a novel extended framework termed ETOE-D, which integrates TOE and DOI and expands them by adding an “External Factors” dimension to capture and highlight regulatory influences which stresses on the huge importance of such dimension in this domain. To prioritize these barriers, we employ a mix of Fuzzy Delphi techniques and Fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods which help in understanding the cause-effect relationship among the identified barriers. Building on these findings, the study also proposes a novel blockchain-based architectural model for emission data collection that integrates IIoT devices, edge computing, permissioned blockchain, and smart contracts into a unified Data collection within MRV pipeline, providing a practical blueprint for addressing the most influential barriers identified. Our findings reveal that barriers such as uncertainties about ROI, resource constraints, financial constraints and compatibility hinders the blockchain adoption the most. This study provides a holistic view and valuable insights to industry stakeholders, policymakers and researchers to strategically address the most impactful barriers, thereby insuring a more successful adoption in emission data collection while advancing both theoretical understanding through the ETOE-D framework and practical implementation through the proposed architectural design. Keywords: emission management, fuzzy Delphi, fuzzy DEMATEL, MCDM, TOE, DOI