在我国致力于实现“碳达峰、碳中和”目标的背景下,企业能否通过提升环境、社会、治理(Environment,Social and Governance,ESG)表现提高创新绩效,对推动企业高质量发展和经济社会可持续发展具有重要意义。文章基于2011—2020年我国A股...在我国致力于实现“碳达峰、碳中和”目标的背景下,企业能否通过提升环境、社会、治理(Environment,Social and Governance,ESG)表现提高创新绩效,对推动企业高质量发展和经济社会可持续发展具有重要意义。文章基于2011—2020年我国A股上市公司样本,实证考察了企业ESG表现对创新绩效的影响机制。研究结果表明:企业ESG表现与创新绩效呈正相关关系。影响机制分析结果表明,企业良好的ESG表现通过声誉效应和资源效应来提升创新绩效。进一步分析发现,与国有企业相比,非国有企业的ESG表现对企业创新绩效的促进作用更明显。展开更多
In this paper, a kind of Partheno Genetic Algorithm(PGA)based on Path Representation scheme is pro-posed for solving Traveling Salesman Problem(TSP). This algorithm employs only mutation and selection operatorsto prod...In this paper, a kind of Partheno Genetic Algorithm(PGA)based on Path Representation scheme is pro-posed for solving Traveling Salesman Problem(TSP). This algorithm employs only mutation and selection operatorsto produce the offspring, instead of traditional crossover operator. A specific mutation operator is designed combiningthe insertion operator with inversion operator, which ensures its strong searching capability. This algorithm simu-lates the recurrence of nature evolution process, while providing fewer control parameters. Experiments based onChinese 144 cities(CHN144)and 7 instances selected from TSPLIB are used to test the performance of this algorithm.They prove that it can reach the satisfying optimization at a faster speed. Especially, for the CHN144, the best pathit finds is better than any other available one.展开更多
文摘在我国致力于实现“碳达峰、碳中和”目标的背景下,企业能否通过提升环境、社会、治理(Environment,Social and Governance,ESG)表现提高创新绩效,对推动企业高质量发展和经济社会可持续发展具有重要意义。文章基于2011—2020年我国A股上市公司样本,实证考察了企业ESG表现对创新绩效的影响机制。研究结果表明:企业ESG表现与创新绩效呈正相关关系。影响机制分析结果表明,企业良好的ESG表现通过声誉效应和资源效应来提升创新绩效。进一步分析发现,与国有企业相比,非国有企业的ESG表现对企业创新绩效的促进作用更明显。
文摘In this paper, a kind of Partheno Genetic Algorithm(PGA)based on Path Representation scheme is pro-posed for solving Traveling Salesman Problem(TSP). This algorithm employs only mutation and selection operatorsto produce the offspring, instead of traditional crossover operator. A specific mutation operator is designed combiningthe insertion operator with inversion operator, which ensures its strong searching capability. This algorithm simu-lates the recurrence of nature evolution process, while providing fewer control parameters. Experiments based onChinese 144 cities(CHN144)and 7 instances selected from TSPLIB are used to test the performance of this algorithm.They prove that it can reach the satisfying optimization at a faster speed. Especially, for the CHN144, the best pathit finds is better than any other available one.
