失败学习对企业绩效的影响机制研究

已有文献认为失败学习对企业绩效具有重要作用，但失败学习通过何种途径促进企业绩效提升的研究并不完善。基于失败学习理论，引入资源拼凑和机会识别作为中介变量，构建失败学习影响企业绩效的多路径模型，探索失败学习对企业绩效的驱动路径及内在机理。实证结果表明：失败学习对企业绩效具有显著积极作用，资源拼凑和机会识别分别在失败学习与企业绩效之间起中介作用，资源拼凑和机会识别在失败学习对企业绩效驱动过程中存在链式中介作用，战略柔性能够强化资源拼凑与企业绩效之间的关系，并正向调节资源拼凑的中介作用。研究结论拓展了失败学习对企业绩效的影响路径，对企业复苏和成长具有重要启示。     

The long overhang of bad decisions in agro-industrial development: Sugar and tomato paste in Ghana

In theory, learning from past mistakes should result in adapted and improved development policy. However policy learning can be difficult to achieve, and the link between learning and policy change is neither direct nor immediate. In this study we look at learning in agro-industrial policy in Ghana, by tracing the interest in sugar production and tomato processing over six decades. Specifically we ask why four failed factories established in the early 1960s have continued to play central roles in both policy and public discourse. Using policy documents, academic material, and the popular press, we show that Ghana’s policy focus on sugar production and tomato processing has endured, despite the fact that the factories were misconceived, poorly sited, ill-equipped and poorly managed. Indeed, the political ideas that underpinned the establishment of these factories in the early days of independence can be seen in the current One District, One Factory policy. We suggest that it is their symbolic and political value, not their economic value, which keeps the discussion around these factories alive. Even when shut down, they are a physical manifestation of historic commitments by the state, and as such they guarantee the attention of politicians, and hold out hope of a next re-launch. Unfortunately as long as the factories continue to be incorporated into each new generation of agro-industrial policy, it is difficult for any alternatives to gain traction. This analysis highlights the very long overhang of bad decisions, particularly when they are associated with physical infrastructure. Learning from past mistakes will only happen if the short-term political cost of turning policy learning into policy action can be overcome.     

Testing the asymmetric effects of exchange rate pass‐through in BRICS countries: Does the state of the economy matter?

This paper investigates not only the question of whether there is exchange rate pass‐through (ERPT) but also the extent to which the pass‐through is asymmetric or state‐dependent in the BRICS countries. Using monthly data from 1999:M1 to 2019:M12 and non‐linear smooth transition vector autoregressive (STVAR) model, our results provide evidence of period‐specific ERPT between the upper and lower regime periods, governed by the selected transition variables. The results further suggest that the pass‐through of exchange rate is higher when the economy is experiencing large appreciations and expansions as well as large depreciations and recessions. Theimplication for these findings is that ERPT is strongly affected by the state of the economy.     

A Statistical Model to Investigate the Reproducibility Rate Based on Replication Experiments

The reproducibility crisis, that is, the fact that many scientific results are difficult to replicate, pointing to their unreliability or falsehood, is a hot topic in the recent scientific literature, and statistical methodologies, testing procedures and p‐values, in particular, are at the centre of the debate. Assessment of the extent of the problem–the reproducibility rate or the false discovery rate–and the role of contributing factors are still an open problem. Replication experiments, that is, systematic replications of existing results, may offer relevant information on these issues. We propose a statistical model to deal with such information, in particular to estimate the reproducibility rate and the effect of some study characteristics on its reliability. We analyse data from a recent replication experiment in psychology finding a reproducibility rate broadly coherent with other assessments from the same experiment. Our results also confirm the expected role of some contributing factor (unexpectedness of the result and room for bias) while they suggest that the similarity between original study and the replica is not so relevant, thus mitigating some criticism directed to replication experiments.     

Deep learning for modeling the collection rate for third-party buyers

This study evaluates a wide range of machine learning techniques such as deep learning, boosting, and support vector regression to predict the collection rate of more than 65,000 defaulted consumer credits from the telecommunications sector that were bought by a German third-party company. Weighted performance measures were defined based on the value of exposure at default for comparing collection rate models. The approach proposed in this paper is useful for a third-party company in managing the risk of a portfolio of defaulted credit that it purchases. The main finding is that one of the machine learning models we investigate, the deep learning model, performs significantly better out-of-sample than all other methods that can be used by an acquirer of defaulted credits based on weighted-performance measures. By using unweighted performance measures, deep learning and boosting perform similarly. Moreover, we find that using a training set with a larger proportion of the dataset does not improve prediction accuracy significantly when deep learning is used. The general conclusion is that deep learning is a potentially performance-enhancing tool for credit risk management.     

Health screening strategies for international air travelers during an epidemic or pandemic

Air travelers can carry an infectious disease's pathogenic microorganism in their bodies and spread the disease from one country to another in a few days. To delay the spread, health screening stations may be set up at airport terminals to screen travelers. This research tested three different health screening strategies, each with a different combination of screening stations at trip origins, destinations and connecting airports. Discrete event simulations were performed, based on the 2014 to 2016 Ebola virus epidemic, with special focus on travelers from the West African countries traveling to the United States, including travelers who transferred flights at airports in European Union member states. The effectiveness of the screening strategies was analyzed in terms of correct detection, missed detection and false alarm rate. The results showed that exit screening at trip origins brought big improvements in the performance measurements compared to no screening. However, additional screening at the destinations and connecting airports contributed marginal benefits.     

Sources of Productivity Growth Dynamics: Is Japan Suffering From Baumol's Growth Disease?

This study examines the sources of labor productivity growth dynamics in Japan (1970–2010) and investigates the extent to which Japanese economic performance has been affected by Baumol's growth disease (BGD). We find that BGD silently undermines Japanese economic growth. However, the magnitude is miniscule, and consequently the aggregate labor productivity growth rate has not been decreasing monotonically. We also explore how BGD is arising and why it is small in the Japanese economy. BGD is weak because (1) the positive Baumol growth effect is also working in certain services sectors and (2) BGD is not a durable phenomenon: even if a sector begins to suffer from BGD, it is likely to recover quickly.     

知识型员工双重社会网络对企业创新绩效作用机制研究

基于企业基础资源观和组织学习理论，从知识型员工个人和组织社会网络两个方面构建知识型员工双重社会网络影响企业创新绩效的理论模型，分析知识共享、组织学习及资源整合在员工双重社会网络对企业创新绩效影响机制中的作用。结果表明：知识型员工双重社会网络对科技型企业创新绩效的作用路径有3条，资源获取与整合、知识共享与学习及员工动态创新能力分别在其中发挥中介作用；在不同类型组织文化环境中，知识型员工双重社会网络对企业创新绩效的作用特征、作用重点以及作用机制存在显著差异，内部整合维度主要通过知识共享和组织学习影响企业创新绩效，外部适应维度主要通过隐性知识传播和资源整合影响企业创新绩效。     

延迟退休年龄下隔代抚育与劳动参与的抉择*——基于工资收入随机性假定的研究

隔代抚育会对延迟退休年龄政策在促进劳动力供给上产生挤出效应。为了对此进行验证，本文在工资收入随机性的假定及延迟退休5年的情景下，模拟了面临孙辈照护需求的女性临近退休者提前退休所产生的福利变化。进一步，本文采用CHIP和CHARLS的微观调查数据，对不同群组的收入增长率和收入风险进行了估计，继而分析了当面临孙辈照护需求时这些收入特征对退休决策者制度退休和退休后劳动参与抉择产生的影响。总体上，在延迟退休年龄政策下，隔代抚育将对女性劳动力供给产生挤出效应。当面临孙辈照护需求时，女性临近退休者的制度退休抉择主要受自身收入增长率和收入风险的影响，收入增长率越低，或收入风险越高，她们提前退休的意愿就越强烈；制度退休后的劳动参与则更多地受子女收入增长率的影响，子女收入增长率越高，劳动参与的概率越低。     

现金股利分配政策是评价投资的基本标准

文章论及股东投资的目的;企业与股东的关系;以及股东与企业的行为规范.论证了现金股利是股东能从企业那里获得的最切实的利益.因此,现金分红应成为对企业的基本要求--不低于银行同期存款利率;同时指出在股权分置的证券市场中,企业分红愈多,对中小股东的侵害便愈大.仅此一点,解决股权分置也就成为必然.股权分置改革将营造更加公平公正的投资环境.