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.     

The antecedents of digital collaboration through an enhanced digital platform for destination management: A micro-DMO perspective

While the tourism sector shifts towards digital transformation, Destination Management Organisations (DMOs) often struggle to adapt to their changing technological environment. This study explores the antecedents of digital collaboration and develops a framework for micro-DMOs to enhance effective destination management through digital technologies. An integrated sequential qualitative approach was adopted by conducting multi-phase interviews, in addition to designing and trialling a real-world trial digital platform. The research provides empirical evidence that digital collaboration is essential for micro-DMOs, necessitating them to transform their current “websites” into digital platforms which act as a hub for business stakeholders to actively be involved in. Antecedents of successful digital collaboration include mutuality, trust, control, and leadership which may be manifested differently from non-digital collaboration. Additionally, the study identifies three aspects for digital collaboration; marketing, networking and knowledge sharing that demands specific attention. Our results have theoretical, methodological, and practical implications for academia, industry and policymakers.     

Antecedents of mobile payment loyalty: An extended perspective of perceived value and information system success model

Drawing on the information system success model and perceived value theory, we develop a research model to examine factors that may affect user satisfaction and loyalty of mobile payment platforms. Empirical data was collected from users using Alipay and WeChat Pay in China, and a total of 410 valid responses were gathered for data analysis. The results show that the multi-dimensional formative perceived value including benefits and sacrifice is important determinant of mobile payment user satisfaction and loyalty. The three benefit dimensions of functional value, experiential value and social value are more important value components than the two sacrifice dimensions of risk and cost, and experiential value is the dominant component of mobile payment users' value perception. As for the antecedents of perceived value, system quality and service quality mainly affect perceived benefits, while information quality has a greater impact on risk. The research results provide the contribution of specific value dimensions to users' perceived value and the impact of quality characteristics on specific perceived value for mobile payment platform providers, thus helping them to adopt effective strategies to strengthen market competitiveness and retain existing users.     

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.     

基于SD模型的装配式建筑供应链脆弱性研究

装配式建筑供应链的运作存在很多不确定性。为提高供应链管理效率，促进建筑业的发展，运用供应链运作参考(SCOR)模型对装配式建筑供应链脆弱因子进行识别，将装配式供应链系统划分为6个子系统；通过系统动力学（SD）模型对供应链脆弱性进行仿真。结果表明，装配制造流程是脆弱性最大的子系统，整个供应链的脆弱性随着建筑项目的推进而增大。     

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。     

中小型侦察监视特种飞机系统的设计技术

分析了当前国内外典型中小型特种飞机的特点和应用方向，阐述了中小型特种飞机系统的技术发展趋势。通过分析典型的特种通用飞机的性能和平台构型特点，详细描述了基于典型中小型特种飞机平台的机载侦察监视应用系统的组成、原理、主要性能及技术难点，并结合实际工程应用，介绍了系统的应用成果。应用分析表明，基于中小型特种飞机平台的机载平台的应用系统有较大的应用范围和市场前景。     

水资源管理的供给侧结构性改革研究

根据供给侧结构性改革的背景和基本内涵,对水资源供给侧结构性改革的内涵进行研究,提出了狭义和广义的水资源供给侧结构性改革的内容。在分析水资源需求新形势的基础上,提出了水资源供给侧结构性改革的要求。根据水循环理论提出了水资源管理是推动水资源供给侧结构性改革的重要抓手,并在最严格水资源管理制度的基础上,提出了符合水资源供给侧结构性改革要求的水资源管理制度。     

Size of nested cities

Models of cities based on conventional spatial market theory are unable to replicate a realistic size distribution. The stochastic process approach to size distribution, which assumes proportionate growth, does not provide an economic foundation for spatial trades. There is an apparent irreconcilability. We propose that since there is a continuum of equilibria in models of spatial markets with endogenous location, proportionate growth can work as equilibrium selection. We present computations for an urban configuration that has not been presented in the literature before. A small city locates inside a larger city's agricultural supply zone. This generates a larger variation in city size that may include a realistic size distribution.     

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.