基于GM(1,1)模型的造纸业上市公司财务研究——以冠豪高新为例

财务风险是企业调整发展战略、提升管理水平的重要参考指标之一。财务风险预测模型的建立能够预测企业在中短期内的财务风险,为企业敲响警钟。以造纸业上市公司冠豪高新为例,选取近五年财务杠杆系数为风险指标,建立GM(1,1)风险预测模型,结果显示该公司短期内财务风险呈下降趋势,调查发现这主要得益于产品成本的降低以及营销策略的改变。     

系统性金融风险的历史考察与防范对策

深入学习习近平在中国共产党第十九次全国代表大会上的报告，在考察20世纪以来的12次金融危机的基础上，对系统性金融风险发生的根源进行了研究，并结合我国当前系统性金融风险面临的形势，提出了防范系统性金融风险的对策建议。研究表明，将过去100多年引发金融危机的系统性金融风险的根源与我国当前的金融形势进行比较分析，可以发现我国面临的系统性金融风险形势十分严峻，必须在党的领导下，采取打击金融腐败、适当收紧货币政策、完善金融监管体系、维护币值稳定、加强金融科技监管等相关政策来防止系统金融风险的发生。     

创新生态系统视角下价值共创如何影响企业创新绩效——一个有调节的中介模型

以创新生态系统为视角，引入创新资源互动与生态系统规范机制为中介变量和调节变量，探究价值共创如何影响企业创新绩效。基于307家企业样本数据，运用结构方程模型、Bootstrap和层级回归方法对数据进行分析。研究发现：创新生态系统中，价值共创不完全直接影响企业创新绩效；创新资源互动部分中介价值共创对企业创新绩效的影响；生态系统规范机制部分正向调节价值共创对创新资源互动的影响。最后提出，创新生态系统调控方与企业要差异化地制定提升创新绩效的实施方案，营造活跃的创新资源互动氛围，形成并完善系统内生态规范机制。     

Asymmetric information consolidation and price discovery: Inferring bad news from insider sales

Due to the paucity of sources of negative firm‐specific information, US capital markets have more difficulty identifying and incorporating bad news into stock prices than they do good news. Even though insider selling is a potentially important proxy for undisclosed bad news, researchers have difficulty ex ante identifying information‐based sales due to an inability to separate liquidity‐motivated from information‐based insider trades. We hypothesize that when insiders in multiple firms sell shares of one firm in which they are insiders and at the same time buy shares of other insider portfolio firms, the sale is more likely to be information‐based, since the proceeds are reinvested. Conversely, when an insider sells one firm without purchasing others or sells multiple insider firms the sale is likely liquidity‐motivated. We find that insider sales identified as information‐based using this algorithm are followed by significant negative abnormal returns. Information‐based sales are also more likely to be associated with delistings, earnings declines and earnings restatements. Analysts are also more likely to revise their earnings forecasts downwards for these firms. It is thus possible to ex ante identify insider sales with information content. Our results will be of interest to investors and also to regulators designing insider trading rules.     

Crisis leadership in economic recession: A three-barrier approach to offset external constraints

An economic recession is a type of crisis originated from external factors that may imperil an organization’s survival depending on the intensity and duration of the crisis. In peripheral European countries, such as Portugal, the recent financial crisis had devastating effects on various business activities. As a result, Portugal represents an important case study in examining how some corporate leaders have handled the economic recession successfully. I interviewed 20 corporate managers to capture their perceptions of the leadership traits and behaviors exhibited by their CEOs in guiding their companies through the recession. In economic recessions, negative constraints do not affect the most effective leaders, who instead erect barriers against the high-pressure conditions to create a supportive, positive work environment. In order to achieve maximum effectiveness, leaders must act as blocking agents against the negative social impacts of the economic crisis, including the fragility of trust in organizational life (i.e., a barrier against distrust), uncertainty of the future (i.e., a barrier against uncertainty), and toxic emotions (i.e., a barrier against toxic emotions).     

An innovation to improve health outcomes in Amajuba district,KwaZulu-Natal,South Africa

Systems’ thinking places high value on understanding the context. This study focused on the collection of disaggregated data in order to understand the context, to facilitate improvement of health outcomes. The aim of this article was to assess the implementation of municipal ward-based health data collection (disaggregated data) and health care workers’ perceptions of this data collection process. This cross-sectional study used mixed methods in Amajuba district. The participants were professional nurses at the Primary Health Care level. Of the 131 respondents, 123 (93.9%) collected municipal ward-based health data, and found it useful. Opportunities for improving data collection were identified. Disaggregation of the data at ward level contributes to a better understanding of the target population’s health, assists planning for health needs and enables provision of targeted interventions in order to improve health outcomes, to prevent financial regression and waste of health resources.     

Lobbying as a potent political marketing tool for firm performance: A closer look

This study endeavors to enhance political marketing literature about the impact of lobbying on firm performance. Our sample is composed of 140 U.S. firms and spans the years 2007–2014 to encompass the 2007–2009 recession and the subsequent recovery period. Our findings indicate that lobbying expenses positively contribute to firm performance. Also, government contracts in both ways, dollar amount and number of government contracts, act as mediators between lobbying expenses and firm performance. In addition, organizational slack moderates the relationship between lobbying expenses and government contracts. The managerial implications suggest that lobbying expenses can be leveraged as a potent tool for firm performance. Firms with larger lobbying efforts acquired both, higher dollar amounts and a greater number of government contracts.     

互联网金融规制与市场有效性改善*——来自中国网络借贷行业的证据

中国的互联网金融经历了一个先创新发展后监管规制的过程，本文通过对网络借贷行业的实证研究，分析监管规则的出台实施对新型互联网融资市场有效性的影响。实证结果表明，网络借贷平台资金的银行存管、持有ICP证等强制性规定缓解了投资者、平台企业与借款人之间的信息不对称，对克服早期平台间通过竞相承诺高回报率来吸引投资者导致的“柠檬市场”问题、对解决网贷市场上缺乏平台风险性高低有效信号的问题都起到了正向作用，有助于互联网融资市场的有效性提高。     

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.     

In the city: The John Lewis partnership and planned shopping centres

A defining feature of large-scale retailing during the period 1950–1980 was the emergence and evolution of planned shopping centres. During the 1950s, department stores in the United States were in the vanguard of this phenomenon. In contrast, British department stores continued operating from traditional high street sites, and had limited opportunities for expansion within planned shopping centres until the 1970s. This paper addresses the connection between department store retailing and the development of the planned shopping centre in Britain from the perspective of one enterprise: the John Lewis Partnership. The article demonstrates that the Partnership was willing to operate department stores within centrally located shopping centres, but was circumspect about operating stores in non-centrally located shopping centres.