反学校文化与阶级再生产：“小子”与“子弟”之比较

作者通过对北京某打工子弟学校的田野调查后发现,在农民工“子弟”中间盛行着类似《学做工》中所描述的工人阶级“小子”的反学校文化。但是,由于制度安排与社会条件的差异,“子弟”与“小子”的反学校文化却是形似质异的。“子弟”的“反抗”更多是一种自我放弃的表达形式而非对支配秩序的洞察与抗争。文章进一步分析了“子弟”反学校文化的生产机制后指出,农民工劳动力再生产的低成本组织模式导致“子弟”高度边缘化的生存状态,这使得他们难以通过教育向上流动,从而以拒绝知识的形式放弃了学业,也因此完成了作为底层的社会再生产。     

国际运输通道与中国进出口增长——来自中欧班列的证据

中欧班列是运行于欧亚大陆上的陆路贸易新通道和跨国货运合作新机制。在中国建设贸易强国和扩大向西开放背景下,中欧班列为研究国际运输通道对中国进出口的影响,提供了合适的准自然实验样本。本文利用2004~2017年中国城市层面的贸易数据、中欧班列数据等,采用双重差分方法识别了中欧班列开通的贸易增长效应。结果发现,相较于未开通中欧班列的城市,开通城市的出口和进口均显著增长;补贴激励是中欧班列贸易增长效应的中间机制,并主要通过铁路、公路和水路的物流规模增长实现传导作用;在没有班列补贴情况下,班列开行数量增加仍可促进开通城市进出口增长;市场引力对开通城市进出口增长有显著传导作用;中西部城市及经济发展水平较低的城市,开通中欧班列的进出口增长效应显著更大。本研究为我国推进中欧班列发展和建设国际运输通道提供了有益的政策启示。     

破解颠覆性技术创新的跨界网络治理路径——基于百度Apollo自动驾驶开放平台的案例研究

本文以百度Apollo自动驾驶开放平台为案例研究对象,研究了平台以跨界网络治理驱动颠覆性技术创新的演进过程及其内在机制,研究发现:(1)跨界平台网络是不同于单个企业的新型技术创新组织载体,可以通过技术网络丰富、市场网络丰富和两个网络价值共创的继起性演进在驱动颠覆性技术创新中发挥重要作用;(2)在跨界网络驱动颠覆性技术创新的不同时期,为解决技术与市场不确定性高以及网络参与者关系复杂等难题,平台可以通过网络治理路径的选择促进颠覆性创新的不同过程与结果,在技术网络丰富期,平台可以通过内容治理与关系治理促进技术的内容颠覆与结构颠覆;在市场网络丰富期,可以通过价值治理与关系治理促进市场的价值颠覆与结构颠覆;在技术网络与市场网络协同的价值共创期,可以通过"网络平台包络(内容治理)、跨界网络效应激发(关系治理)、异质性利润焦点获取(价值治理)"的综合治理促进技术与市场的颠覆可持续性;(3)平台治理中的内容治理与价值治理是跨界网络治理的"硬实力",而关系治理是跨界网络治理的"软实力",软硬实力的组合共同促进颠覆性技术的技术突破与市场突破。本文丰富了网络治理理论、颠覆性创新理论和平台理论,并对尝试借助平台推进新兴前沿技术突破、尤其是跨界推进颠覆性技术创新的实践行动具有管理启示。     

中国区域经济理论演进与未来展望

中国区域经济70年的发展离不开科学有效的区域经济理论支撑。在服务区域经济发展现实与借鉴国外区域经济理论方法的基础上,中国区域经济理论的演进呈现以解决现实问题为导向的阶段性特征,逐渐形成了"引进-吸收-消化-创新"的发展模式。中国区域经济理论在研究视角、研究范式、研究内容及发展模式等方面表现出不同于西方区域经济理论的差异性特征。面对跨越中等收入陷阱与区域经济高质量发展的现实要求,中国区域经济理论研究未来将在学科融合、假设前提、研究范畴、研究机制与区域政策等方面取得突破性进展。此外,本文还对"十四五"时期中国区域经济理论研究进行了展望。     

低碳背景下制造业商业模式创新策略研究——以卡特彼勒公司为例

低碳经济要求制造企业克服经济增长与环境超载之间的矛盾,但在传统商业模式下往往无法达到"双赢"。本文以战略分析和创新理论为依据,论述了低碳约束下制造业商业模式创新的驱动因素、作用机理以及创新要素,设计了理论框架,在此基础上探讨了低碳背景下商业模式创新的难点,提出了三方面的创新策略,并通过对卡特彼勒的案例分析验证了上述策略。结果表明:制造业可以通过改造价值链以建立逆向供应链、增强服务以及构建低碳技术壁垒的方式实现商业模式创新。研究在一定程度上丰富了相关学术成果,为我国现代制造业顺应低碳经济需求提供了具有可操作性的指导。     

Competitive and Collaborative Quality and Warranty Management in Supply Chains

Product quality and product warranty coverage are two important and closely related operational decisions. A longer warranty protection period can boost sales, but it may also result in dramatically increased warranty cost, if product quality is poor. To investigate how these two decisions interact with each other and influence supply chain performance, we develop a single‐period model with a supplier that provides a product to an original equipment manufacturer, which in turn sells it to customers. Customer demand is random and affected by the length of the product warranty period. Warranty costs are incurred by both the supplier and the manufacturer. We analyze two different scenarios based on which party sets the warranty period: manufacturer warranty and supplier warranty. Product quality is controlled by the supplier, and the manufacturer determines the ordering quantity. We analyze these decentralized systems and provide the structural properties of the equilibrium strategies. We also compare the results of centralized and decentralized systems and identify the conditions under which one system provides a longer warranty and better product quality than the other. Our numerical study further shows that, in decentralized settings, when the warranty period is determined by the firm sharing the larger proportion of total warranty costs, the supply chain can achieve greater system‐wide profit. Both parties can therefore benefit from properly delegating the warranty decision and sharing the resulting additional profit. We further design a supplier‐development and buy‐back contract for coordinating decentralized supply chains. Several extensions are also discussed.     

城乡居民储蓄行为差异的实证研究

城乡居民储蓄行为差异的实证研究周伏平王美今ＡＢＳＴＲＡＣＴＴｈｉｓｐａｐｅｒｓｈｏｗｓｕｐｔｈｅｄｉｆｅｒｅｎｃｅｏｆｔｏｔａｌｓａｖｉｎｇ（ｏｎｌｙｒｅｆｅｒｉｎｇｔｏｔｈｅｒｅｓｉｄｅｎｔｓ＇ｓａｖｉｎｇｄｅｐｏｓｉｔｓ,ｎｏｔｉｎｃｌｕｄｉｎｇ...     

A sequential conditional probability ratio test procedure for comparing diagnostic tests

In this paper, we derive sequential conditional probability ratio tests to compare diagnostic tests without distributional assumptions on test results. The test statistics in our method are nonparametric weighted areas under the receiver-operating characteristic curves. By using the new method, the decision of stopping the diagnostic trial early is unlikely to be reversed should the trials continue to the planned end. The conservatism reflected in this approach to have more conservative stopping boundaries during the course of the trial is especially appealing for diagnostic trials since the end point is not death. In addition, the maximum sample size of our method is not greater than a fixed sample test with similar power functions. Simulation studies are performed to evaluate the properties of the proposed sequential procedure. We illustrate the method using data from a thoracic aorta imaging study.     

A quasi-Newton acceleration for high-dimensional optimization algorithms

In many statistical problems, maximum likelihood estimation by an EM or MM algorithm suffers from excruciatingly slow convergence. This tendency limits the application of these algorithms to modern high-dimensional problems in data mining, genomics, and imaging. Unfortunately, most existing acceleration techniques are ill-suited to complicated models involving large numbers of parameters. The squared iterative methods (SQUAREM) recently proposed by Varadhan and Roland constitute one notable exception. This paper presents a new quasi-Newton acceleration scheme that requires only modest increments in computation per iteration and overall storage and rivals or surpasses the performance of SQUAREM on several representative test problems.