Suppr超能文献

研究采用 PLS-SEM 和 ANN 建模,考察知识产权保护在推动国家研究项目团队激进技术创新方面的重要作用。

Study examining the significant role of intellectual property protection in driving radical technological innovation among national research project teams, employing PLS-SEM and ANN modeling.

机构信息

School of Management, East University of Heilongjiang, Harbin, China.

School of Economics and International Trade, East University of Heilongjiang, Harbin, China.

出版信息

PLoS One. 2024 Aug 7;19(8):e0307026. doi: 10.1371/journal.pone.0307026. eCollection 2024.

Abstract

This study examines the role of intellectual property protection (IPP) in enhancing radical technological innovation (RTI) within national research project teams, using an innovation-driven theory and an ability-motivation-opportunity (AMO) perspective. This study utilizes a sample of 336 national research project team members from various Chinese universities, research institutes, and corporations to analyze the theoretical model. Additionally, a two-stage hybrid partial least squares structural equation modeling (PLS-SEM) approach, combined with artificial neural network techniques (ANN), is employed to evaluate the hypotheses. The empirical findings of this study reveal a positive association between the intensity of IPP and RTI within national research project teams. Research and development investment intensity (R&DII) is identified as the primary predictor, while integrated leadership (IL) and group potential (GP) play crucial moderating roles. These groundbreaking findings extend the scope of innovation-driven and AMO theories, providing a proactive model for national research project teams to propose improvements to the IPP system, ultimately enhancing the realization of RTI.

摘要

本研究运用创新驱动理论和能力-动机-机会(AMO)视角,考察了知识产权保护(IPP)在增强国家研究项目团队中激进技术创新(RTI)方面的作用。本研究采用来自中国各大学、研究所和企业的 336 名国家研究项目团队成员的样本,对理论模型进行了分析。此外,还采用了两阶段混合偏最小二乘结构方程建模(PLS-SEM)方法,并结合人工神经网络技术(ANN)来评估假设。本研究的实证结果表明,国家研究项目团队中 IPP 的强度与 RTI 之间呈正相关关系。研发投资强度(R&DII)被确定为主要预测因素,而综合领导力(IL)和团队潜力(GP)则起着至关重要的调节作用。这些开创性的发现扩展了创新驱动和 AMO 理论的范围,为国家研究项目团队提供了一个积极主动的模型,以提出改进 IPP 系统的建议,最终增强 RTI 的实现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1022/11305571/5914c65b249b/pone.0307026.g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验