In the current context of environmental constraints, implementing effective environmental regulations (ERs) is essential to fostering greener technologies. Green technology innovation efficiency (GTIE) measures how efficiently an industry utilizes resources in the process of green technology innovation. However, previous research has often treated innovation as a black box, overlooking the potential contributions and diversity of ERs.To address this gap, this study categorizes ERs into three types: command-and-control, market-based, and voluntary. Using China’s construction industry from 2017 to 2024 as a case study, the research evaluates the evolution of GTIE through a network Epsilon-Based Measure (EBM) model and examines the effects of ERs using Tobit regression analysis. The findings reveal that:There is a notable disconnect between the Research & Development (R&D) phase and the commercialization phase of green technology in the construction industry. While the industry effectively converts most R&D achievements into profits at the commercialization stage, a significant portion of R&D investment fails to yield tangible R&D outcomes.Different types of ERs influence GTIE in distinct ways, and their effectiveness depends on an appropriate combination of regulatory approaches to achieve the desired outcomes.
Shaxinya Igamova, THE UZBEK ECONOMIC MODEL , International Journal of Artificial Intelligence: Vol. 1 No. 1 (2025): International journal of artificial intelligence
Shaxinya Igamova , OPPORTUNITIES AND ADOPTION CHALLENGES OF ARTIFICIAL INTELLIGENCE IN THE CONSTRUCTION INDUSTRY , International Journal of Artificial Intelligence: Vol. 1 No. 4 (2025): International journal of artificial intelligence
Copyright (c) 2025 Shaxinya Igamova
This work is licensed under a Creative Commons Attribution 4.0 International License.
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