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The exploration of digital transformation peer effects on the innovation performance of emerging industries is crucial for analyzing the underlying mechanisms of digital transformation, optimizing resource allocation among peer enterprises, and enhancing industrial competitiveness. This study empirically examines the influence of digital transformation peer effects on the innovation performance of the photovoltaic industry, using data from 150 photovoltaic companies listed in Shanghai and Shenzhen between 2011 and 2022. The study found that: (1) The digital transformation of the photovoltaic industry is influenced by regional and industry-specific peer effects. Regional peer effects in digital transformation have a positive impact on the innovation performance of the photovoltaic industry, while industry-specific peer effects exert a negative impact on innovation performance. Moreover, these effects exhibit dynamic persistence; (2) Further analysis of the transmission mechanism reveals that the digital transformation peer effect positively influences the innovation performance of the photovoltaic industry, primarily through the mediating role of enhanced absorptive capacity. Additionally, the level of marketization and executive tenure significantly moderate this relationship; (3) The study further investigates the photovoltaic industry within the context of subsidy policy implementation, firm types, and strategic pacing. The results indicate that the digital transformation peer effect on innovation performance is most pronounced for technology-intensive firms adopting an analytical strategy after the withdrawal of photovoltaic subsidies. For labor-intensive firms employing a defensive strategy, the peer effect is more significant before the withdrawal of subsidies. In contrast, the negative impact of industry-specific digital transformation peer effects on innovation performance is more evident in photovoltaic companies that pursue an offensive strategy; (4) The heterogeneity analysis reveals that the digital transformation peer effect on innovation performance is more significant for small-scale photovoltaic enterprises with state-owned property rights. In contrast, the peer effect negatively impacts innovation performance in large-scale photovoltaic enterprises. These findings provide theoretical insights and practical guidance for governments and enterprises in formulating digital transformation strategies for emerging industries.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11698440 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0313615 | PLOS |
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San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, California, USA.
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View Article and Find Full Text PDFNeurol Sci
September 2025
Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.
The rapid evolution of digital tools in recent years after COVID-19 pandemic has transformed diagnostic and therapeutic practice in neurology. This shift has highlighted the urgent need to integrate digital competencies into the training of future specialists. Key innovations such as telemedicine, artificial intelligence, and wearable health technologies have become central to improving healthcare delivery and accessibility.
View Article and Find Full Text PDFOral Surg Oral Med Oral Pathol Oral Radiol
August 2025
Department of Oral Medicine, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing, PR China. Electronic address: yz
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Comput Methods Programs Biomed
September 2025
eXiT Research Group, Universitat de Girona (UdG), EPS - Edifici P-IV, Carrer Universitat de Girona, 6, Girona, 17003, Catalunya, Spain.
Background And Objective: Hybrid forecasting methods aim to overcome the limitations of classical statistical approaches and deep learning models. While statistical methods provide interpretability, they often lack predictive power. Conversely, deep learning models achieve high accuracy but act as "black boxes.
View Article and Find Full Text PDFJ Behav Addict
September 2025
1School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China.
Background And Aims: Digital addiction among youth, characterized by excessive and compulsive use of digital devices such as smartphones, computers, and social media platforms, has become a global concern. The present study aimed to investigate the association between digital addiction subtypes in youth and various health outcomes using "digital addiction" as an umbrella term.
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