A truly global crisis? Evidence from contagion dependence across international REIT markets

This study examines the global nature of the recent crisis under bivariate Markov-switching models for pre- and post-crisis periods using the breakpoint of August 9, 2007. It quantifies international synchronization of boom-bust regime switches to investigate contagion-type dynamic comovements of Real Estate Investment Trusts (REITs). Global REIT markets display persistent bust regimes from September 2008 to May 2009, whereas the regime-switching patterns are not significant in the pre-crisis period. The results provide new evidence for global REIT contagion phenomena and suggest greater difficulties in diversifying risks across global REIT markets during the post-crisis period.     

偏光显微镜法在空气粉尘中石棉纤维鉴别中的应用

本文采用偏光显微镜法鉴别空气粉尘中的微量石棉纤维。经滤膜收集的粉尘样品通过高温灰化及酸洗过程去除大部分干扰物质,经乙醇分散后均匀沉积在玻璃片上,滴加具有固定折射率的浸油制成试片。在正交偏光系统下观察到粉体中存在纤维状颗粒,且纤维呈现四次平行消光特性,比对6种常见石棉的偏光显微镜图,综合分析试样粉尘的光学性质,推断样品中含有温石棉。     

Comparing Compliance Behaviour of Students and Farmers. An Extra-laboratory Experiment in the Context of Agri-environmental Nudges in Germany

Increasing popularity of economic experiments for policy impact analysis has led to an on-going debate about the suitability of students to substitute professionals as experimental subjects. To date, subject pool effects in agricultural and resource economics experiments have not been sufficiently studied. In order to identify differences and similarities between students and non-students, we carry out an experiment in the form of a multi-period business management game that is adapted to an agri-environmental context. We compare the compliance behaviour of German agricultural students and German farmers with regard to water protection rules and analyse their responses to two different green nudge interventions. The experimental results reveal that the direction of the response to the policy treatments is similar. Even unexpected behaviour could be reproduced by the student sample. Nevertheless, the magnitude of the treatment effects differed between the two samples. This implies that experimenters in the field of agricultural and resource economics could use the subject pool of students to analyse the direction of nudge policies. If predictions should be made about the magnitude effects, we suggest using a professional subject pool.     

二代涉入、制度情境与中国家族企业创新投入——基于社会情感财富理论的研究

基于社会情感财富理论,本文以2012-2016年中国A股上市家族企业为样本,采用倾向得分匹配法,对一定制度情境下二代涉入对家族企业创新投入的影响进行实证研究。研究结果表明:二代涉入会抑制家族企业的创新投入,发生二代涉入的家族企业会更重视约束型社会情感财富,而该类社会情感财富会导致家族企业对创新投入持保守态度;制度环境对二代涉入与家族企业创新投入之间的关系具有正向调节效应,从而会缓和二代涉入对家族企业创新投入的抑制作用;政治关联对二代涉入与家族企业创新投入之间的关系具有负向调节效应,从而会加剧二代涉入对家族企业创新投入的抑制作用。据此,本文建议:发生二代涉入的家族企业不能为了加强对企业的控制而排斥引入外部优良人才或外部投资者,创始人应该注重二代成员对家族企业归属感等的培养,提升二代成员对延伸型社会情感财富的保护意愿;政府和家族企业必须共同努力推进市场化改革,藉此完善家族企业赖以生存的制度环境;家族企业应当尽量避免政治寻租等行为对创新的抑制作用。     

贫困山区农户茶叶生产技术效率及影响因素研究

基于湖北省382份茶叶种植户调研数据,采用随机前沿生产函数模型“一步估计”法分析贫困山区农户茶叶生产技术效率和影响因素。研究结果表明:样本户茶叶种植存在较大改进空间;样本户资本和劳动力投入剩余;茶园的海拔、树龄、茶农是否加入合作社、种植面积、户主是否受过种茶培训等因素对农户茶叶生产技术效率有重要影响。因此,提出紧抓乡村振兴战略机遇,推动贫困山区茶产业高质量发展;建立茶产业“三项补贴”,改善茶园基础设施条件;优化茶叶种植布局,提高合作社服务水平;成立茶产业发展基金,加快培育职业茶农,以提高贫困山区农户茶叶生产技术效率。     

Factors influencing consumers' purchase decision-making in O2O business model: Evidence from consumers' overall evaluation

Online-to-offline (O2O) has become a rapidly growing e-commerce model worldwide, but the factors influencing consumers' purchase decision-making have not been examined well. After exploring the working mechanism of the O2O model, we extract eleven indexes of consumers' overall evaluation in the O2O model with Crawlzilla and R techniques. Social network analysis (SNA) is adopted to build social networks reflecting consumers' overall evaluation in the O2O model. Based on the modified social network and the extracted subgraph, this study (N = 768) reveals consumers' overall evaluation behavior patterns in the O2O model by calculating network density, central potential, edge betweenness. The results show that shoppers overall evaluate the eleven indexes, especially perceived product quality, online product price, promotion intensity, business reputation, and product brand, which reflects the significant associations between the indexes. Among all the eleven evaluation indexes, perceived product quality, online product price, and business reputation dominate consumers’ decision-making behavior. When making purchase decisions, consumers not only overall consider online product price, perceived product quality, and business reputation but also balance perceived product quality, business reputation, and promotion intensity. Finally, we make some suggestions on marketing strategy for e-commerce companies.     

基于社会网络视角的科研合作网络结构及特性分析——以战略性新兴产业领域为例

战略性新兴产业是近几年新出现的研究热点,对其科研合作网络的研究,有助于探究该领域的科研合作现状与发展趋势。基于社会网络分析方法,以中国知网(CNKI)作为数据来源,构建了战略性新兴产业领域作者合作网络、关键词共现网络、作者-关键词耦合网络及机构合作网络,对合作网络的结构及特性等进行了分析。结果表明:战略性新兴产业领域论文合著率基本呈上升趋势,但该领域整体合作仍较为松散,存在较多的小团体;合作网络具有小世界和无标度特性,具有较大影响力的节点作为合作网络的中心,影响着网络内的学术交流和科研工作的开展。     

市域(郊)铁路车辆选型方案探讨

随着城镇化进程的加快和城市经济辐射能力的增强,以特大城市中心城为核心的都市圈逐渐形成,都市圈内的经济联系更加紧密,都市圈核心区与外围的出行需求迅速增长,市域(郊)铁路的概念被引进,选择符合市域(郊)铁路特点的车辆类型是设计的重点。     

Comparative study of deep learning models for analyzing online restaurant reviews in the era of the COVID-19 pandemic

Online reviews remain important during the COVID-19 pandemic as they help customers make safe dining decisions. To help restaurants better understand customers’ needs and sustain their business under current circumstance, this study extracts restaurant features that are cared for by customers in current circumstance. This study also introduces deep learning methods to examine customers’ opinions about restaurant features and to detect reviews with mismatched ratings. By analyzing 112,412 restaurant reviews posted during January-June 2020 on Yelp.com, four frequently mentioned restaurant features (e.g., service, food, place, and experience) along with their associated sentiment scores were identified. Findings also show that deep learning algorithms (i.e., Bidirectional LSTM and Simple Embedding + Average Pooling) outperform traditional machine learning algorithms in sentiment classification and review rating prediction. This study strengthens the extant literature by empirically analyzing restaurant reviews posted during the COVID-19 pandemic and discovering suitable deep learning algorithms for different text mining tasks.     

Banking sector reactions to COVID-19: The role of bank-specific factors and government policy responses

This paper examines the impact of bank-specific factors and variations in the context of stringency of government policy responses on bank stock returns because of the COVID-19 pandemic. A sample of 1,927 publicly listed banks from 110 countries is used for the period of the first major wave of COVID-19, that is, January to May 2020. Our findings indicate that stock returns of banks with higher capitalization and deposits, more diversification, lower non-performing loans, and larger size are more resilient to the pandemic. While banks’ environment and governance scores do not have a significant impact, higher social and corporate social responsibility strategy scores intensify the negative stock price reaction to COVID-19. We further observe that the pandemic-induced reduction in bank stock prices is mitigated as the strictness of government policy responses increases, mainly through economic responses such as income support, debt and contract relief, and fiscal measures from governments.