São Carlos School of Engineering, University of São Paulo, Department of Production Engineering, Av. Trabalhador São Carlense, 400, São Carlos, 13566-590, SP, Brazil.
São Carlos School of Engineering, University of São Paulo, Department of Production Engineering, Av. Trabalhador São Carlense, 400, São Carlos, 13566-590, SP, Brazil.
J Environ Manage. 2023 Apr 15;332:117437. doi: 10.1016/j.jenvman.2023.117437. Epub 2023 Feb 15.
Industry 4.0 and digital technologies might significantly impact resource optimization in a smart circular economy. However, adopting digital technologies is not easy due to barriers that may arise during this process. While prior literature offers initial insights into barriers at the firm level, these studies pay less attention to these barriers' multi-level nature. Focusing only on one particular level while ignoring others may not unleash the full potential of DTs in a circular economy. To overcome barriers, it's necessary to have a systemic understanding of the phenomenon, which is missing in previous literature. By combining a systematic literature review and multiple case studies of nine firms, this study aims to unpack the multi-level nature of barriers to a smart circular economy. The primary contribution of this study is a new theoretical framework composed of eight dimensions of barriers. Each dimension provides unique insights related to the multi-level nature of the smart circular economy transition. In total, 45 barriers were identified and categorized into the following dimensions: 1. Knowledge management (five barriers), 2. Financial (three barriers), 3. Process management & Governance (eight barriers), 4. Technological (ten barriers), 5. Product & Material (three barriers), 6. Reverse logistic infrastructure (four barriers), 7. Social behaviour (seven barriers), and 8. Policy & Regulatory (five barriers). This study examines how each dimension and multi-level barrier affects the transitions toward a smart circular economy. An effective transition copes with complex, multidimensional, multi-level barriers, which might require mobilization beyond a single firm. Government actions need to be more effective and correlated with sustainable initiatives. Policies also should focus on mitigating barriers. Overall, the study contributes to smart circular economy literature by increasing theoretical and empirical understanding of digital transformation barriers towards circularity.
工业 4.0 和数字技术可能会对智能循环经济中的资源优化产生重大影响。然而，由于在这个过程中可能出现的障碍，采用数字技术并不容易。虽然之前的文献提供了有关企业层面障碍的初步见解，但这些研究对这些障碍的多层次性质关注较少。仅关注一个特定层面而忽略其他层面可能无法在循环经济中充分发挥数字技术的潜力。为了克服障碍，有必要对这一现象有一个系统的认识，而这在之前的文献中是缺失的。本研究通过结合系统文献综述和对九家公司的多个案例研究，旨在揭示智能循环经济障碍的多层次性质。本研究的主要贡献是提出了一个由八个障碍维度组成的新理论框架。每个维度都提供了与智能循环经济转型多层次性质相关的独特见解。总的来说，共确定了 45 个障碍，并将其分为以下八个维度：1. 知识管理（5 个障碍）；2. 财务（3 个障碍）；3. 过程管理与治理（8 个障碍）；4. 技术（10 个障碍）；5. 产品和材料（3 个障碍）；6. 逆向物流基础设施（4 个障碍）；7. 社会行为（7 个障碍）；8. 政策与监管（5 个障碍）。本研究考察了每个维度和多层次障碍如何影响向智能循环经济的过渡。有效的过渡需要应对复杂、多维、多层次的障碍，这可能需要超越单个企业的动员。政府的行动需要更加有效，并与可持续倡议相关联。政策还应侧重于减轻障碍。总的来说，本研究通过增加对数字化转型向循环性的障碍的理论和经验理解，为智能循环经济文献做出了贡献。
