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https://hdl.handle.net/10356/180734
Title: | How photovoltaic industry policies foster the development of silicon solar cell manufacturing technology: based on self-attention mechanism | Authors: | Zhao, Xuefeng Li, Xin Liu, Tianyuan Shen, Guibin |
Keywords: | Engineering | Issue Date: | 2024 | Source: | Zhao, X., Li, X., Liu, T. & Shen, G. (2024). How photovoltaic industry policies foster the development of silicon solar cell manufacturing technology: based on self-attention mechanism. Energy, 308, 132866-. https://dx.doi.org/10.1016/j.energy.2024.132866 | Journal: | Energy | Abstract: | With the advancement of silicon solar cell manufacturing technology (SSCM-Tec) driven by subsidy policies, some developing countries have implemented subsidy reduction policies. Concurrently, intense international competition has prompted the implementation of restriction policies. However, due to SSCM involving multiple manufacturing steps, each step comprising various SSCM-Tec, it presents challenges in researching how different types of policies affect SSCM-Tec in each step. We construct the SSCM-Mechanism based on patent claims to capture the nuanced changes in SSCM-Tec caused by the implementation of policies. The results show that: (1) Policies lead to an imbalance in SSCM-Tec advancements among manufacturing steps; (2) Different types of policies have varying impacts on SSCM-Tec. Supportive policies boost enterprises' interest in developing SSCM-Tec, and restrictive policies and subsidy reduction policies speed up SSCM-Tec innovation; (3) The collaboration of various policy types can better drive the advancement of SSCM-Tec. Employing the right type of policy at the opportune moment serves as a crucial driving force for fostering innovation in SSCM-Tec. These findings reveal the multifaceted impact of policies on SSCM-Tec, providing policymakers with a clearer perspective to formulate more precise policies for guiding the direction of SSCM-Tec development and accelerating its innovation pace. | URI: | https://hdl.handle.net/10356/180734 | ISSN: | 0360-5442 | DOI: | 10.1016/j.energy.2024.132866 | Schools: | School of Electrical and Electronic Engineering | Rights: | © 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. | Fulltext Permission: | none | Fulltext Availability: | No Fulltext |
Appears in Collections: | EEE Journal Articles |
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