Complex Network of Aviation E-Services in the Belt and Road Initiative: A Heuristic Study of Small Data based on Block Modeling

ABSTRACT

The aviation e-service system is an important part of support for business communication in regions covered by Belt and Road initiative. In exploring the role of airline companies in this system, we examine the structure of the network, which consists of airlines interconnections based on small data of individual attributes of aviation companies in aviation e-services, and study these interconnections across different groups using block modeling. The heuristic solution of airline companies in development of international communication and cooperation is further discussed. Among our policy implications for global managers, we suggest the enhancement of cross-regional cooperation among airlines.     

我国“一带一路”沿线地区风险投资时空分布及影响因素研究

深入分析我国“一带一路”沿线地区风险投资时空格局及影响因素，有助于促进创新创业与企业发展、提高区域科技创新水平。运用空间分析方法和空间计量模型，对2003-2018年我国“一带一路”沿线139个城市风险投资的时空分布特征及影响因素进行分析，结果表明：①沿线地区的风险投资发展具有不均衡性，呈现为沿海高、西部低的分异格局；②风险投资的全局自相关系数均为正，呈现出明显的空间集聚特征；③风险投资机构数、国家高新区数量、风险投资退出、政府引导基金发展、财政科技支出对区域风险投资具有显著促进作用，环境污染对风险投资有一定抑制作用。随着ESG投资理念逐渐获得认可，沿线地区可以通过提升绿色发展水平促进风险投资发展。     

Board directors with foreign experience and stock price crash risk: Evidence from China

This study examines the impact of board directors with foreign experience (BDFEs) on stock price crash risk. We find that BDFEs help reduce crash risk. This association is robust to a series of robustness checks, including a firm fixed effects model, controlling for possibly omitted variables, and instrumental variable estimations. Moreover, we find that the negative association between BDFEs and crash risk is more pronounced for firms with more agency problems, weaker corporate governance, and less overall transparency. Our findings suggest that the characteristics of board directors matter in determining stock price crash risk.     

智能制造有利于增加企业技术创新投入吗——基于智能制造试点的准自然实验

智能制造是我国制造业转型升级的主攻方向,而如何准确客观评价智能制造的实施效果成为亟待解决的问题.从技术创新投入视角,将智能制造试点政策实施视为一次准自然实验,采用2011-2019年制造业上市企业面板数据,通过PSM-DID方法研究智能制造对企业技术创新投入的影响.研究结果表明,智能制造显著影响企业技术创新投入,即通过提升客户集成度、供应商集成度进而提高企业技术创新投入,且促进作用仅发生在民营企业和非高新技术行业中.该发现扩展了现有研究外延,同时,为解决当前国际困局和促进智能制造的持续推广提供了重要实践价值.     

(Under)Mining local residential property values: A semiparametric spatial quantile autoregression

Rock mining operations, including limestone and gravel production, have considerable adverse effects on residential quality of life due to elevated noise and dust levels resulting from dynamite blasting and increased truck traffic. This paper provides the first estimates of the effects of rock mining—an environmental disamenity—on local residential property values. We focus on the relationship between a house's price and its distance from a nearby rock mine. Our analysis studies Delaware County, Ohio, which, given its unique features, provides a natural environment for the valuation of property‐value‐suppressing effects of rock mines on nearby houses. We improve upon the conventional approach to evaluating adverse effects of environmental disamenities based on hedonic house price functions. Specifically, in the pursuit of robust estimates, we develop a novel (semiparametric) partially linear spatial quantile autoregressive model which accommodates unspecified nonlinearities, distributional heterogeneity, as well as spatial dependence in the data. We derive the consistency and normality limit results for our estimator as well as propose a consistent model specification test. We find statistically and economically significant property‐value‐suppressing effects of being located near an operational rock mine which gradually decline to insignificant near‐zero values at roughly a 10‐mile distance. Our estimates suggest that, all else equal, a house located a mile closer to a rock mine is priced, on average, at about 2.3–5.1% discount, with more expensive properties being subject to larger markdowns.     

Impulse response function analysis of the impacts of land value-added tax policy on government performance

In this study, an epsilon-based network data envelopment analysis is employed to construct assessment mechanisms for government performance. Moreover, performance indicators of two dimensions of tax collection efficiency and financial effectiveness are measured. We propose a vector autoregression model in which all economic variables are regarded as dependent variables to address the disadvantages of traditional regression model. The conclusions are as follows: (a) measures of tax collection efficiency deteriorated, whereas those of financial effectiveness improved. (b) In an impulse response analysis of the model, an increase in government-published land values produced significantly increased tax collection efficiency.     

Social media affordances in entry‐level employees’ socialization: employee agency in the management of their professional impressions and vulnerability during early stages of socialization

This study examined how entry‐level employees interacted with social media during three stages of organizational socialization. They navigated between four different media affordances (persistence, editability, visibility, and association) while experiencing them as both enabling and constraining in different socialization stages. Qualitative interview data analysis revealed during anticipatory socialization, job applicants realized visibility and persistence in relation to institutional and individualized socialization. During encounter, new employees managed personal and professional life boundaries carefully against the association and visibility affordances. Although some participants used both public and enterprise social media for obtaining job‐related information and understanding coworkers and company culture, during metamorphosis, most interviewees adopted passive information seeking strategies and experienced a paradoxical tension between the enabling and constraining affordances of social media. Findings are discussed with regards to employees’ exertion of agency in managing their professional impressions and coping with high levels of uncertainty and vulnerability during early stages of socialization.     

Volatility forecasting: long memory,regime switching and heteroscedasticity

In this article, we account for the first time for long memory, regime switching and the conditional time-varying volatility of volatility (heteroscedasticity) to model and forecast market volatility using the heterogeneous autoregressive model of realized volatility (HAR-RV) and its extensions. We present several interesting and notable findings. First, existing models exhibit significant nonlinearity and clustering, which provide empirical evidence on the benefit of introducing regime switching and heteroscedasticity. Second, out-of-sample results indicate that combining regime switching and heteroscedasticity can substantially improve predictive power from a statistical viewpoint. More specifically, our proposed models generally exhibit higher forecasting accuracy. Third, these results are widely consistent across a variety of robustness tests such as different forecasting windows, forecasting models, realized measures, and stock markets. Consequently, this study sheds new light on forecasting future volatility.