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Article History

Received: 30 September 2025

Accepted: 27 January 2026

First Online: 5 March 2026

Declarations

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: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

: This study was reviewed and approved by the Ethics Review Committee of the Business School, Guangzhou College of Technology and Business, China. The ethical approval document was issued on January 5, 2025. All research procedures strictly adhered to the ethical principles outlined in the Declaration of Helsinki (2013 revision) and China’s Data Security Law (2021). Specific ethical safeguards included: Full anonymization of expert information (e.g., using codes like E19 instead of real names) to protect personal identity; Encrypted storage of all raw data (AES-256 encryption) to prevent unauthorized access; Explicit exclusion of any research content involving human subjects beyond expert opinion collection.

: Informed consent was obtained from all 21 participating experts (including 3 newly added system integration experts) using a combined online-offline approach between January 5, 2025 and April 1, 2025: Offline participants: Received printed consent forms detailing the study objectives, data collection methods, potential risks (e.g., minimal time investment), and right to withdraw at any stage without prejudice. Signed hard copies were collected on-site and stored securely with the research team. Online participants: Accessed electronic consent forms via a dedicated encrypted webpage. Pre-recorded video explanations of the study were provided, and digital signatures were obtained before any data collection. All experts were informed that their participation was voluntary, and they could request data deletion or withdraw from the study within 30 days of submission. No expert withdrew or requested data deletion during the study period.

: All experts were informed during consent collection that their anonymized opinions might be published in academic journals or public datasets. No expert objected to the publication of such anonymized data. https://www.kaggle.com/datasets/qiangli01/green-certification. For supplementary materials, all identifying information was removed, ensuring compliance with academic publishing standards for privacy protection.