专利转化特征精准识别与预测——以人工智能芯片为例

探讨前沿科技领域专利转化特征并对其进行精准识别与预测，对于我国破解“卡脖子”技术难题及实现科技自立自强具有重要意义。选取人工智能芯片专利领域，采用机器学习算法测度最优转化预测方案，分析全球范围内主要国家或地区专利成功转化影响因素，从企业/高校、国内/国际等不同层面总结专利成功转化的主要特征。结果发现：随机森林算法预测效果较好，人工智能芯片领域专利转化概率服从对数曲线分布，影响高校/企业、国内/国外专利转化特征的因素有所不同。最后，提出高校/科研机构应注重高价值专利维持和团队合作、企业应提升专利技术质量和撰写质量等政策建议。     

企业高层领导跨界学习能力的结构维度与影响作用——基于中国情境的扎根理论研究

企业高层领导跨界学习能力已成为企业保持持久生存和发展的必然要求。对30位企业高层领导一对一访谈资料进行扎根理论分析，构建“驱动力—行为策略—结果”的企业高层领导跨界学习能力结构维度及其影响作用模型，并运用组织学习理论与高阶理论对模型进行诠释。结果表明：企业高层领导跨界学习能力由跨界学习愿景构建能力、跨界学习领域选择能力、边界惯性重构能力、跨界学习执行能力和跨界知识挖掘能力5个能力结构要素构成；企业高层领导跨界学习能力通过新思维引入、本位跨越提升组织双元学习水平，影响企业持续创新和管理创新绩效。     

Neural networks for estimating Macro Asset Pricing model in football clubs

The recent crisis caused by COVID-19 directly affected consumption habits and the stability sof financial markets. In particular, the football industry has been hit hard by this pandemic and therefore has more volatile stock prices. Given this new scenario, further research is needed to accurately estimate the value of the shares of football clubs. In this paper, we estimate an asset pricing model in football clubs with different compositions of risk nature using non-linear techniques of artificial neural networks. Usually, asset pricing models have been estimated with linear methods such as ordinary least squares. Our results show a precision higher than 90% for all the estimated models, which far exceeds those shown by linear methods in the previous literature. We find that the residual represents about 40% of the variance of the price-dividend ratio. Long-term risks follow in importance, and above all, the habit component and its behaviour in the face of changes. The importance of the residual component exists due to a low correlation between the asset price and consumer behaviour, but to a much lesser extent than that shown in previous studies. The estimation carried out with artificial neural networks, both the Deep Learning methods and especially the Quantum Neural Network, opens up new possibilities to estimate more efficiently the pricing of financial assets in the football industry.     

Social media networks,fake news,and polarization

We study how the structure of social media networks and the presence of fake news affects the degree of misinformation and polarization in a society. For that, we analyze a dynamic model of opinion exchange in which individuals have imperfect information about the true state of the world and exhibit bounded rationality. Key to the analysis is the presence of internet bots: agents in the network that spread fake news (e.g., a constant flow of biased information). We characterize how agents’ opinions evolve over time and evaluate the determinants of long-run misinformation and polarization in the network. To that end, we construct a synthetic network calibrated to Twitter and simulate the information exchange process over a long horizon to quantify the bots’ ability to spread fake news. A key insight is that significant misinformation and polarization arise in networks in which only 15% of agents believe fake news to be true, indicating that network externality effects are quantitatively important. Higher bot centrality typically increases polarization and lowers misinformation. When one bot is more influential than the other (asymmetric centrality), polarization is reduced but misinformation grows, as opinions become closer the more influential bot’s preferred point. Finally, we show that threshold rules tend to reduce polarization and misinformation. This is because, as long as agents also have access to unbiased sources of information, threshold rules actually limit the influence of bots.     

机器学习在人力资源管理领域中的应用研究

本研究关注的是机器学习在人力资源管理领域的应用,通过目前已有研究的梳理,以了解在人力资源管理领域中人工智能/机器学习的应用程度和研究热点。同时,基于管理实践,本研究提出了人力资源管理者如何利用算法,以有价值的方式处理和解释数据,将其真正应用于人力资源管理的六大模块工作中,以降低管理成本,提供不断增长的优势和潜力。最后,在现有学术研究和管理实践的基础上,本研究列举了机器学习在人力资源管理领域应用可能面临的挑战,以及未来的研究方向,以期为后续的研究提供一定的参考。     

中国机构投资者的学习机制研究——理性贝叶斯还是简单强化式学习

理论文献通常假设机构投资者遵循理性贝叶斯法则更新其信念,在此学习模式下,盈亏经验本身并不能直接影响机构行为。但该假设的合理性尚未得到实证研究的充分支持。中国新股发行中的抽签分配制度为检验上述命题提供了比较理想的随机实验机会。本文基于新股抽签分配数据,系统检验了随机的盈亏经验对机构投资行为的影响,结果发现:(1)机构投资者显著受制于幼稚的强化式学习机制的影响,即通过随机抽签在前期获得新股分配的机构(处置组)相对未获配机构(控制组),其下期参与新股申购的概率显著提高,并且前期收益率能够有效地强化这种盈利经历与参与概率之间的正向关系。(2)盈亏经验能够显著改变专业机构的估值信念,即前期通过随机抽签获得高收益体验的机构相对未获配机构,在后续新股询价过程中给出了显著更高的报价上调水平。(3)盈亏经验对机构行为产生影响的一种可能渠道是借助机构投资管理人的强化式学习过程,基于基金经理个人特征变量的调节机制研究表明,丰富的长期从业经验、高学历的教育水平以及多位基金经理的相互竞争都能在一定程度上缓解盈亏经历对基金行为的影响。本文基于随机实验的设计为经验与行为之间的因果关系提供了可信证据,证实了即使是被奉为理性投资者代表的专业机构也会受制于简单强化式学习的显著影响。     

Gender differences in the first course in accounting: An achievement goal approach

We examine whether gendered patterns can be observed in first-year students' achievement goals in an introductory accounting course; a question largely overlooked by prior literature. This investigation is motivated by perceptions of accounting as a masculine field involving gender role stereotypes and business schools as competitive and performance-oriented environments. Our findings suggest that male students tend to adopt performance-approach goal, implying that they are more competitive than female students, and that their performance is thus driven by a desire to outperform others. Our findings further suggest that male students' expectations of learning accounting are higher than those of female students. The expectations explain the gender differences in the performance-approach goal. Finally, we find that this performance-approach goal mediates gender differences in course performance depending on the mode of assessment; male students received higher grades for exams but not for teamwork. Overall, our study highlights the importance of considering contextual aspects related to competitiveness, masculinity, and the mode of assessment on an accounting course when addressing students’ achievement goals and expectations of learning accounting. We thus contribute to the understanding of how learning environment, accounting pedagogy, and the broader field of professional accounting intersects with individual student attributes, creating differential learning outcomes.     

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.     

Speed of internationalization of new ventures and survival in export markets

Speed of internationalization may refer to how early a new venture goes abroad as well as how fast it expands its activities post-entry. The present paper incorporates both aspects and analyzes to what extent several dimensions of speed influence the ability of new ventures to survive in export markets. Based upon extant theories, two perspectives are deduced – a Learning perspective and a Resource perspective – leading to partly contrasting hypotheses. The hypotheses are tested based upon a unique data set consisting of all new ventures established in Norway a specific year that started to export goods in the following nine years. Among the findings are that survival rates increase when ventures go international immediately after inception and when they expand rapidly into new countries rather than focusing on expanding their export share in a limited number of markets, thus lending support to the Resource perspective.