基于机器学习的专利质量评价研究

随着专利数量的迅猛增长,专利质量问题日益凸显,专利质量评价成为学者关注焦点。面对海量专利数据,如何构建有效的专利质量评价方法,实现对专利质量的准确评价和分类是一项急迫的工作。首先,通过对国内外相关专利质量评价研究进行系统调研和梳理,提出一种新的专利质量评价指标体系;其次,根据新的专利质量评价指标体系,构建一种基于机器学习的专利质量评价方法;最后,以人工智能技术专利为例进行实证研究。结果表明,有效综合利用专利技术性、经济性、法定性和主体性评价指标,有助于更加全面、深入地评价专利质量;基于机器学习的专利质量评价方法能够迅速对专利进行分类并识别高质量专利,从而提高专利质量评价结果深度,为实现大规模专利质量分类评价智能化提供可能。     

基于机器学习的专利质量评价研究

随着专利数量的迅猛增长,专利质量问题日益凸显,专利质量评价成为学者关注焦点。面对海量专利数据,如何构建有效的专利质量评价方法,实现对专利质量的准确评价和分类是一项急迫的工作。首先,通过对国内外相关专利质量评价研究进行系统调研和梳理,提出一种新的专利质量评价指标体系;其次,根据新的专利质量评价指标体系,构建一种基于机器学习的专利质量评价方法;最后,以人工智能技术专利为例进行实证研究。结果表明,有效综合利用专利技术性、经济性、法定性和主体性评价指标,有助于更加全面、深入地评价专利质量;基于机器学习的专利质量评价方法能够迅速对专利进行分类并识别高质量专利,从而提高专利质量评价结果深度,为实现大规模专利质量分类评价智能化提供可能。     

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。     

明星发明人识别与角色分析:来自机器学习领域的实证

明星发明人有助于提高企业研发创新绩效。目前对明星发明人的地位与功能探讨不足,导致企业无法全面掌握发明人信息,难以为研发活动招聘合适的人才。鉴于此,对机器学习领域明星发明人的领导、传播、知识或任务排他等功能和地位进行识别,采用动态网络分析方法确立六类明星发明人,即焦点型发明人、领导型发明人、潜在跨界型发明人、传播型发明人、任务排他型发明人和知识排他型发明人,分析其角色功能。结果表明：部分发明人同时拥有多种地位;领导型、焦点型和知识排他型明星发明人影响范围更广、职业流动性更强,与其他发明人的交互时间更长;隔离同时具有3种地位的明星发明人对焦点型发明人影响显著。     

技术学习与企业技术能力链条:知识转化整合的作用

借鉴知识管理、组织学习等研究成果,提出并从理论上论证了一个整合性研究框架,揭示从技术学习上升到技术能力的演进过程。研究表明:技术能力演进需经过知识转化整合这一中介机制;在动态环境和知识转化整合过程中,即兴学习起着调节作用。研究成果为实证提供了新的研究命题和研究视角,丰富与发展了企业技术能力理论。     

随机化检验在药物经济学评价中的应用

目前,国内关于药物经济学评价大多采用点估计的方法简单对比不同用药方案的评价指标,但是基于统计推断的理论,这种简单处理并不能反映研究人群总体的比较结果。本文将随机化检验应用于药物经济学评价中,能在一定程度上解决药物经济学疗效评价的问题。     

国外创业学习模型研究述评

创业学习处于公司创业过程研究的中心,但有关创业学习的研究起步较晚。对国外有关创业学习的模型进行了梳理,阐述和分析了不同学者提出的创业学习模型,并对这些模型进行了简评,指出了进一步构建创业学习模型的方向。     

高校推进学习型党组织建设的若干思考

高校学习型党组织建设是知识经济时代发展的必然要求,是高等教育自身改革与发展的需要,是提升广大党员领导干部理论素养的需要,是教育理念与教育方法创新的需要。高校必须树立终身学习的理念,保持自身发展目标与党组织建设目标的一致性;必须深化教育教学改革,建立符合师生特点和需要的学习机制。     

铁矿石价格波动的因果推断: 影响因素与效应分析

中国钢铁工业对进口铁矿石需求巨大且不掌握进口铁矿石的定价权,铁矿石供应存在较高风险.由于影响进口铁矿石价格因素众多且相互关联,目前关于进口铁矿石现货价格波动成因尚缺少权威性的研究成果.在现有进口铁矿石价格研究基础上,选取铁矿石供需、运输成本、定价模式、金融、经济发展等因素作为铁矿石价格影响因素,确定了各因素的相关代表性指标.通过构建Lasso回归模型,明确了进口铁矿石现货价格主要影响因素及这些因素之间的复杂交互关系,并通过方差分解方法识别各个影响因素的影响程度.结果显示,铁矿石普氏价格指数、海运指数、美元指数、国内铁矿石产量是影响进口铁矿石现货价格的主要因素,其中铁矿石普氏价格指数是最为关键的影响因素.基于模型结果,从加强铁矿石市场监管、优化铁矿石运输成本等角度提出了相应的政策建议.     

It's all about mechanisms – what process-tracing case studies should be tracing

ABSTRACT

Process-tracing (PT) as a distinct case-study methodology involves tracing causal mechanisms that link causes (X) with their effects (i.e. outcomes) (Y). We trace causal mechanisms whereby a cause (or set of causes) produces an outcome to both: (1) make stronger evidence-based inferences about causal relationships because the analysis produces within-case evidence of each step of the causal process (or absence thereof) in between a cause and outcome, and (2) because tracing mechanisms gives us a better understanding of how a cause produces an outcome. Yet, when we look at the methodological literature on PT, there is considerable ambiguity and discord about what causal mechanisms actually are. The result of this ambiguity and discord about what mechanisms are clearly maps onto existing applications of PT, with most PT case studies completely ignoring the underlying theoretical causal processes. In the few PT applications where mechanisms are unpacked, they are typically only developed in a very cursory fashion, with the result that there is considerable ambiguity about what theoretical process the ensuing case study actually is tracing. If we want to claim we are tracing causal mechanisms, the causal processes in between X and Y need to be unpacked theoretically. How can we claim we are tracing a causal ’process’ when we are not told what the process (i.e. mechanism) actually is? To alleviate this problem, the article attempts to develop a clearer definition of causal mechanisms to provide scholars with a framework for theorising mechanisms in a fashion that is amenable to in-depth empirical analysis using PT.     

On designing economic agents that behave like human agents

This paper explores the idea of constructing theoretical economic agents that behave like actual human agents and using them in neoclassical economic models. It does this in a repeated-choice setting by postulating artificial agents who use a learning algorithm calibrated against human learning data from psychological experiments. The resulting calibrated algorithm appears to replicate human learning behavior to a high degree and reproduces several stylized facts of learning. It can therefore be used to replace the idealized, perfectly rational agents in appropriate neoclassical models with calibrated agents that represent actual human behavior. The paper discusses the possibilities of using the algorithm to represent human learning in normal-form stage games and in more general neoclassical models in economics. It explores the likelihood of convergence to long-run optimality and to Nash behavior, and the characteristic learning time implicit in human adaptation in the economy.     

量子思维对大数据背景下信息决策新思路的启示

随着大数据时代的到来,当前许多信息处理方法和思路都面临着革命性变化。这些变革由于数据庞大,突显出以“4V”为代表的非经典特征,而这些特征导致的复杂性给大数据时代信息决策提出了前所未有的新挑战。20世纪以来,量子力学理论的发展对物理学发展产生了革命性影响,由于其非经典特征而引发的诸多新型思维方式在方法论上可为解决大数据时代到来所引发的复杂问题提供新的可行思路。     

环境规制能够改善技术学习的绿色绩效吗？

环境规制政策是解决环境污染问题的重要制度保障。然而,学者们对环境规制是否能够达到预期效果莫衷一是。为了进一步验证环境规制实施效果,建立了包含环境规制的多要素环境学习曲线模型,基于2001-2016年我国省域工业企业面板数据,从新视角研究了不同类型环境规制对不同技术学习模式绿色绩效的调节作用。研究结果表明：与经济环境规制相比,行政环境规制对提升工业企业技术学习绿色绩效的作用更显著;在干中学、研发中学和引进中学3种技术学习模式中,行政环境规制可以促进研发中学的绿色绩效;行政环境规制及经济环境规制的非线性调节效应都不显著。上述结论对合理设计和选择不同类型环境法规、促进企业技术学习和减少大气污染物排放具有重要意义。     

Financing Constraints and the Timing of Innovations in the German Services Sector

Using newly available data at the firm level, this study provides convincing evidence of the importance of financial constraints in explainingthe timing of innovations in the German services sector. Based on a dynamic model of firms' optimalR & D behavior under financial constraints, we estimate various versions of aneconometric specification of the model with dichotomous innovation data by using a univariateordered probit model. Additionally, a new estimation technique is applied to account forthe scaling of the regressor variables. Our results are consistent with the theoretical view that,because of capital market imperfections, internal finance should be an important determinant ofinnovative activities by private firms not only in the manufacturing sector but as well as inthe services sector.     

组织学习论--组织行为在社会生态学意义上的一个解说

\"组织学习\"的最普适性、最具辩证意义的解析,应该是社会生态学意义上的.近年来关于\"学习型组织\"理论的提出,实际上也主要是基于组织特定生命周期上管理行为的运作阶段和背景来说的.基于赫斯特组织生态循环周期模型,组织学习包括由情景激发的自发性组织学习、基于经验和专业化知识的常规性组织学习以及回归价值理性的创新性组织学习等基本类型.     

学习导向、双元学习、新产品竞争优势与企业绩效

学习导向对于企业增强新产品竞争优势,提升市场表现有着积极影响。现有关于学习导向的实证研究多将其作为格式塔构念进行探讨,忽视了各构成维度间关系复杂性对企业绩效的影响,不利于深入理解学习导向战略实践过程。因此,将学习导向解构为学习承诺、开放心智及共享愿景3个维度,基于资源观理论框架,采用模糊集定性比较分析法,以211家中国企业为样本,探讨了学习导向绩效机制过程中影响双元学习、新产品竞争优势和企业绩效的多重因果路径。研究结论可为企业合理构建学习导向型组织,实践新产品开发策略提供理论支撑。     

Global convergence of adaptive learning in models of pure exchange

Summary. This paper develops an adaptive learning scheme for a standard version of the OLG model with pure exchange. Perfect forecasting rules which generate perfect foresight orbits are approximated by cubic spline functions. These approximations are successively constructed using historical data only. Trajectories generated by this scheme converge to perfect foresight orbits globally for all initial conditions. This result holds for all parameterizations guaranteeing the existence of a monetary steady state and hence is independent of consumers' savings behavior. It generalizes to all one-dimensional models of the Cobweb type. Received: October 5, 2000; revised version: February 15, 2001     

Convergence for difference equations with vanishing time-dependence, with applications to adaptive learning

Summary. We provide conditions for local stability and instability of an equilibrium point in certain systems of nonautonomous nonstochastic difference equations. In the systems under study the influence of time is present through a positive scalar “gain” parameter which converges in the limit to zero. These systems have recently been used to study the dynamics of adaptive learning in economic models, and we provide two economic illustrations of the formal results. Received: October 7, 1997; revised version: February 8, 1999