粤港澳大湾区制造业集聚与区域创新

以2009—2020年粤港澳大湾区11个城市为研究对象，探讨制造业集聚与区域创新的关系。研究发现，制造业集聚显著提高区域创新水平，可通过提高企业竞争这一路径实现。进一步分析发现，金融业集聚对区域创新发展具有显著的正向关系，金融产业和制造业产融协同集聚显著提高区域创新水平。研究结果表明，制造业集聚加剧产业内部企业创新竞争，带动区域创新发展，且金融业在创新中起到积极的推动作用。指出应鼓励区域企业创新竞争，优化营商环境，为产业融合发展提供保障。     

Does justice affect brand advocacy? Online brand advocacy behaviors as a response to hotel customers’ justice perceptions

This study focuses on customers' information-sharing behavior in the context of online brand advocacy behavior regarding hotel brands. We aim to explain hotel customers' online brand advocacy behavior through three-sided justice evaluations (i.e., justice for employees, justice for the self, and global belief in a just world), and their hotel satisfaction. Hypotheses are tested by using survey data acquired from 688 individuals on Amazon's Mechanical Turk (MTurk) through partial least squares structural equation modeling (PLS-SEM). The findings show that customers' perceptions of justice for the self positively affect their hotel satisfaction, perceptions of justice for employees and the global belief in a just world positively affect online brand advocacy behavior, and hotel satisfaction also positively affects online brand advocacy behavior. We expand current research efforts on online brand advocacy research and provide theoretical and managerial implications for the development of marketing and management research and practice.     

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.     

创新战略下的英国研发组织创新——Catapults的组织管理模式研究

Catapults（弹射中心）作为一种新型研发组织形式，在英国创新发展战略的实施中扮演着重要角色。精准的组织功能定位、高效的组织管理运作模式和紧密的网络化组织关系，是Catapults组织管理模式创新的重要三大重要内容。为我国新型研发机构的培育和发展提供了良好的参考样本。     

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.     

刑事涉财产执行中的案外人权益救济——以案外人权益救济程序的当事人构造为视角

刑事涉财产执行程序因采取移送执行模式而被误认为不存在申请执行人，使得刑事涉财产执行程序及其衍生的案外人权益救济程序过分依赖执行法院的职权主义。在刑事附带民事诉讼裁判、追缴或责令退赔违法所得并返还被害人判项、责令被免予刑事处罚的被告人赔偿被害人损失判项的执行程序中，案外人权益救济程序原则上应以被害人为申请执行人，并参照适用民事强制执行程序中的案外人权益救济制度。其他刑事涉财产执行程序应以检察机关为申请执行人。除非出现被执行人逃避执行或者案外人对执行标的提出排除执行请求等特殊情形，作为申请执行人的检察机关通常无须现实参加执行程序。     

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.     

加强师德师风建设提高以德治校能力

教育大计，教师为本；教师培养，师德师风为先。师德师风建设是高校思想政治教育的重要内容，是进一步推动廉政文化进校园工作的重中之重，是增强以德治校水平和提高以德治校能力的关键，是贯彻落实学校党风廉政建设和深入推进反腐败工作的重要举措。