Adverse effect of social media on generation Z user's behavior: Government information support as a moderating variable

Social media emerged as a primary source of information among young users, but its severe effect on mental state due to information overload, still an area of concern for the researchers. Generation Z users' addiction to the mobile phone/gadgets is increasing with a rise in social media and consequently their behavioral outcomes have transformed completely. Nowadays behavioral issues including stress, fatigue, ‘fear of missing out’ and ‘phubbing’, anxiety etc. rising each day but the relationship among these issues and information overload is less examined. The social media users are unable to filter the trustworthy information due to its enormous size and thus role of information support from government becomes essential. The current study extends the S-O-R theory exploring relationship between the stimulus of enormous information on the responses generated among the Generation Z such as social media fatigue, ‘fear of missing out’, ‘phubbing’ and anxiety. The findings from a sample of 319 users belonging to Generation Z suggest that social media platforms need to understand user's compulsive usage that is resulting into fatigue and consequently anxiety. The role of government information support on reducing fatigue and anxiety is found to be positive. The relationship between ‘fear of missing out’, ‘phubbing’ and anxiety is found significant and shows presence of partial mediation. The study offers significant theoretical and practical implications. It is significant for the service providers and social media platforms to advance interfaces with minimum fatigue for the users and offers information support to the users to reduce stress caused by information load.     

Mining semantic features in current reports for financial distress prediction: Empirical evidence from unlisted public firms in China

It is difficult to predict the financial distress of unlisted public firms due to their longer disclosure cycle of accounting information and more inadequate continuity of market trading information compared to listed firms. In this paper, we propose a framework to predict the financial distress of unlisted public firms using current reports. Specifically, to better represent the meaning of current report texts, we propose a semantic feature extraction method based on a word embedding technology. Empirical results show that current reports contain more effective information for predicting the financial distress of unlisted public firms compared with periodic reports. In addition, semantic features extracted using our proposed method significantly improve the predictive performance, and their enhancing effect is superior to that of topic features and sentiment features. Our study also provides implications for stakeholders such as investors and creditors.     

Delegation and the regulation of U.S. financial markets

We analyze the institutional determinants of U.S. financial market regulation with a general model of the policy-making process in which legislators delegate authority to regulate financial risk at both the firm and systemic levels. The model explains changes in U.S. financial regulation leading up to the financial crisis. We test the predictions of the general model with a novel, comprehensive data set of financial regulatory laws enacted specifically between 1950 and 2009. The theoretical and empirical analysis finds that economic and political factors impact Congress’ decision to delegate regulatory authority to executive agencies, which in turn impacts the stringency of financial market regulation, and our estimation results indicate that political factors may have been stronger and resulted in inefficiencies.     

Is online-to-offline customer care support essential for consumer service?

Customer satisfaction is the main pillar for convenient and profitable retailing. The retail sector continuously tried to develop new strategies to improve consumer satisfaction. It is impossible to provide each service directly to the consumer by the retailer. In this direction, the retailer establishes customer care to provide the best service to consumers. Consumer care can provide promotional or prevention services, increasing the consumer's satisfaction level. This study is developed to show the impact of retailers' customer care service for an offline-to-online retailing strategy. The demand is consumer support, advertisement, and selling price dependent. For maintaining consumer service, some free home delivery policies are offered, when consumers ordered more than a certain percentage of the amount. Finally, the total profit of this O2O retailing system is calculated by the classical optimization technique. Some special cases are discussed in the numerical section to prove the impact of customer care services. Numerical results prove that customer care support enhances the profit by 48.20%, whereas investment in the advertisement and home delivery strategy helps the retail industry to earn 44.80% and 16.74% more profit, respectively. Finally, from this study, it is clear that customer care activities are essential to increase the profit of the retailing sector.     

金融周期、行业技术周期与经济结构优化

本文首先采用马尔科夫区制转移模型测算金融周期和12类行业的技术投入周期,进而采用交叉谱分析法和OLS法分析金融周期对行业技术周期的影响,结果发现:不同金融变量的周期具有异步性,各行业的技术投入周期具有明显差别;不同金融变量周期与行业技术投入周期之间存在不同的数量关联性,对不同的行业技术投入具有不同的影响作用;在繁荣阶段,金融市场和银行对各行业的技术投入都具有正向推动作用,但金融市场对高密度创新行业技术投入的推动作用更为显著,银行对低密度稳定行业技术投入的推动作用更为显著;在紧缩阶段,金融市场对高密度创新行业技术投入的紧缩效应更为剧烈,银行却对低密度稳定行业的技术投资下行起到缓解作用。根据这些事实和规律,可以引导利用各金融变量对具有发展前景的行业强化技术投资助推作用,提升经济结构优化效率。     

Improving forecasting performance using covariate-dependent copula models

Copulas provide an attractive approach to the construction of multivariate distributions with flexible marginal distributions and different forms of dependences. Of particular importance in many areas is the possibility of forecasting the tail-dependences explicitly. Most of the available approaches are only able to estimate tail-dependences and correlations via nuisance parameters, and cannot be used for either interpretation or forecasting. We propose a general Bayesian approach for modeling and forecasting tail-dependences and correlations as explicit functions of covariates, with the aim of improving the copula forecasting performance. The proposed covariate-dependent copula model also allows for Bayesian variable selection from among the covariates of the marginal models, as well as the copula density. The copulas that we study include the Joe-Clayton copula, the Clayton copula, the Gumbel copula and the Student’s $t$-copula. Posterior inference is carried out using an efficient MCMC simulation method. Our approach is applied to both simulated data and the S&P 100 and S&P 600 stock indices. The forecasting performance of the proposed approach is compared with those of other modeling strategies based on log predictive scores. A value-at-risk evaluation is also performed for the model comparisons.     

数据交易市场双边匹配模型与决策方法研究

针对平台视角下的数据交易供需双边匹配问题，基于双边匹配理论，提出了考虑模糊语言评价信息、区间数评价信息和0-1评价信息的混合型多属性匹配决策方法并定义了属性匹配满意度函数。以供需主体最大匹配满意度为目标，构建了数据交易供需双边匹配的多目标优化模型，并设计模型求解算法，将多目标化模型转化为单目标线性规划模型进行求解，以获取匹配结果。结果表明，通过对供需双方需求信息的详细分析，双边匹配结果能在最大程度上满足双方需求，同时，优化模型具有合理性及有效性。     

Changing International Financial Architecture: Growing Chinese Influence?

It is often said that the 21st century will be the Asian century. Based on population and gross domestic product projections, it certainly looks as if this will be so. Will the existing international financial institutions give more voices, votes, and top positions to Asia? Or will Asia create its own institutions that would rival the old architecture? This present paper argues, first, that China, and possibly India, will be in a position to be so influential that the international financial architecture may have to go through significant changes. Second, the three large crises in the last 20 years have made Asian countries more confident that they can manage capital flows by accumulating large foreign reserves and by adopting sound macrofinancial policies. After 2009, China started to push various initiatives that will amount to creating its own sphere of influence with new regional institutions in the future.     

Developing a financial conditions index for a post-transition country: the case of Croatia

The interconnection between financial and business cycles and the importance of surveillance over financial markets emphasise the need for the development of indicators that could trace financial conditions in a country. In this paper, we focus on developing a financial conditions index for a post-transition country – Croatia. Since financial conditions indices for post-transition markets differ from those for developed markets due to differences in the development of their financial systems and the availability of data, we show that financial conditions indices constructed for post-transition markets need to be tailored to the specifics of such markets.     

基于产业背景的金融控股集团协同机制研究

产业金控集团是当前我国产业资本借力资本市场发展实体经济的重要方式，但在 实际运行中存在协同机制不健全、协同效应发挥不足、产融结合的深度和广度不足等问题。本 文对国内外产业金融理论进行了文献综述，深入分析了产业金控集团产生的动因，指出了目前 产业金控集团在发挥协同效应中存在的不足。结合产业金控集团的优势和特点，从构建横向协 同机制和纵向协同机制的角度，探讨了完善产业金控集团协同机制的举措。