中国研发人员性别结构分布演变、关联影响与差异来源——基于半参数核回归与Oaxaca分解的研究

激发女性研发人员创造活力，对于中国创新经济发展具有重要意义。然而，科研领域性别结构失衡是长期以来科学共同体内外所面临的问题。基于2010-2019年中国内地30个省份面板数据，围绕企业、研发机构、高校等创新主体，在对创新全要素生产率指数（以下简称创新TFP）进行测度的基础上，运用核密度估计对三大创新主体的性别结构、创新TFP分布的演进进行描绘。其次，采用半参数核回归法探析科研人员性别结构与创新投入、产出和创新TFP间的关联。最后，选用Oaxaca分解法探究STEM研究生性别差异对R&D人员性别差异的解释程度。结果表明：相比研发机构和高校，企业研发人员性别失衡更为严重，相比人口大省、经济发展落后地区，发达地区对研发人员性别结构的“兜底作用”更显著；创新投入、产出与性别结构之间存在非对称关系，在研发人员女性占比越高的地区，区域全要素生产率指数越高；STEM领域研究生数量上的性别差异可以解释约6成的研发人员性别差异，且解释程度呈逐渐增提升势。     

Can older workers stay productive? The role of ICT skills and training

This paper quantitatively examines the effects of aging on labor productivity using individual worker data in Korea. We find that information and communications technology (ICT) skills and participation in job-related training can help older workers stay productive. The estimation results present that ICT skills, a measure incorporating an individual’s proficiency in ICT skills and their utilization in the workplace, has a positive effect on the wages of the older workers aged 50–64 with a high level of education or in a skill-intensive occupation. Job training also has a significant positive effect on the wages of older workers. These results imply that compared to younger workers, well-educated older workers can obtain greater productivity increase through ICT skill attainment and their adequate use, and job-training. The evidence suggests that a productivity decrease in line with the aging process can be mitigated by training aging workers to equip themselves with ICT skills.     

The era of Omni-learning: Frameworks and practices of the expanded human resource development

According to the ever-changing organizational environment, we also adopt an ever-expanding HRD in contents and scope. Focusing on the drivers of the recent HRD reforms, the growing demand for organizational agility and holistic capabilities of human resources is driving the need for change, and the pandemic crisis is pushing the revolutionary changes of HRD. Such trends of the expanded HRD can be characterized as a ‘march toward Omni-learning’. In specific, there are at least four noticeable and intertwined waves of HRD reforms toward Omni-learning: (1) embracing holistic capabilities such as benchmarking, modeling, forecasting, and backcasting (BMFB); (2) integrating working and learning by promoting on-the-job learning (OJL), on-the-life learning (OLL), and on-the-life training (OLT); (3) standardizing communication tools such as LMF (logic tree; multi-dimensional matrix/map; flowchart) and EEOSP (everything/everyone on the same page); and (4) diversifying communication space-time across diverse places (close; remote) and times (synchronized; a-synchronized). And all the HRD waves are commonly facilitated and promoted by technological breakthroughs of artificial intelligence (AI) and the metaverse. Beyond the current innovations of HRD, no one would be certain about the answer to the question “What’s next?”. But what is certain is that HRD will continue to be deepened and widened as long as human resources are needed to respond to the ever-changing organizational environment.