Can AI benefit individual resilience? The mediation roles of AI routinization and infusion

The recent COVID-19 pandemic has raised concerns about individual resilience in the face of adversity. The abundant research suggested that artificial intelligence (AI) can help organizations handle changes during this challenging period. However, little empirical research has explored whether the presence of AI enhances individual resilience against adversities. Drawing on the reciprocal determinism theory, this study considers the formation of two typical post-adoption behaviors and their subsequent results in individual resilience. The structural equation modeling shows that AI factors (usability and sociability) and personal factors (self-efficacy) determine usage behaviors (routine and infusion use), in turn affecting individual resilience. The OLS results suggest the right half of the U-shaped relationships between infusion use and resilience. Two-step fsQCA offers three configurations resulting in high resilience under the different presence of AI factors and also suggests the roles of user behaviors. The study provides new theoretical enlightenment for the impact of digital service technology on individuals and enriches the existing literature on the usage of digital service technology. The findings provide practical implications for practitioners to design AI products better to improve smart service experience.     

Technology spillover effects and economic integration: evidence from integrating EU countries

The article uses time series for the period 1981–2008 to estimate the impact of foreign technology spillover effects on Greece, Ireland, Portugal and Spain, representing the integrating European Union (EU) countries. I restrict technology diffusion to EU-12 countries and compare the results to unrestricted technology diffusion from a sample of 32 OECD countries. Accounting for nonstationarity and co-integration, the dynamic OLS estimator is used to estimate the impact of foreign R&D stock on labour productivity, taking into account patent-, trade- and FDI-related technology diffusion channels. I find empirical evidence for trade-related foreign technology spillover effects for Greece and Ireland if technology diffusion is unrestricted. Restricting technology diffusion to EU-12 countries, there are significant foreign technology spillover effects from European integration for Portugal (patent related) and Spain (trade and FDI related). Moreover, the domestic R&D stock and education are significant drivers for labour productivity in integrating EU countries. The empirical results are robust for different regression specifications and sources of technology diffusion.     

外商直接投资对产业结构的影响研究——以浙江省为例

浙江省位于中国的东部沿海地区,是中国最富饶的长江三角洲地区省份之一.浙江作为中国一个发达的经济省份,在改革开放以后,浙江省的外商直接投资不断增长,出口结构也不断优化.因此,当前研究外商直接投资对浙江省产业结构的影响,提出有针对性的政策建议,为创造更好的投资环境,更有效的吸引外资和利用外资提供政策参考,具有很强的现实意义.本文利用浙江省1984-2010年的年度经济数据对浙江省FDI和产业结构的关系进行实证分析,从而发现FDI对优化产业结构的作用路径.实证结果表明:外商直接投资对第一产业结构的变化没有直接的原因,而对第二产业、第三产业结构的变化有着直接的原因.通过OLS进行简单线性回归分析,结果发现,平均FDI每增加1个百分点,第二产业上升15.18%;其次,平均FDI每增加1个百分点,第三产业上升8.85%.     

数学建模在医学病例中的构建及分析应用

此文依据2012"高教社杯"全国大学生数学建模竞赛C题提供的资料,针对中脑卒中发病病例信息以及相应期间当地的逐日气象资料,通过对脑卒中的发病环境、职业人群和发病年龄等因素进行统计分析。借助MATLAB计算软件,对平均压温湿度影响因素进行多元回归模型最小平方法(0LS)估计分析,并对回归模型进行分布检验,确定各项指标的权重,建立环境因素的数据模型,并有针对性进行对影响因素采取干预措施和预防措施提供数据依据。     

Improved forecasting of autoregressive series by weighted least squares approximate REML estimation

Restricted maximum likelihood (REML) estimation has recently been shown to provide less biased estimates in autoregressive series. A simple weighted least squares approximate REML procedure has been developed that is particularly useful for vector autoregressive processes. Here, we compare the forecasts of such processes using both the standard ordinary least squares (OLS) estimates and the new approximate REML estimates. Forecasts based on the approximate REML estimates are found to provide a significant improvement over those obtained using the standard OLS estimates.     

欠发达地区创新能力及影响因素的OLS分析——以辽西北地区为例

首先引用中国创新指标体系——钻石模型对欠发达地区的创新能力进行分析,并结合地区实际确定价值实现能力、技术实现能力、人才实现能力为影响欠发达地区创新能力的主要因素。在此基础上,构造回归方程对影响因素进行OLS分析,最后结合研究结果,提出提升欠发达地区创新能力的政策建议。     

影响中国原油进口量主要因素的实证分析

近年来,随着中国经济迅速发展,对原油的需求量不断加大,由于国内原油供给不足,中国原油进口数量持续增长,进口规模巨大,对外依存度逐年攀升,面临较大安全隐患。以1990～2013年相关数据为样本,采用OLS多元回归方法对影响中国原油进口贸易的因素进行实证分析。结果表明：世界原油产量、中国国内生产总值以及中国煤炭消费量是影响中国原油进口量的主要因素。据此,提出了相关建议。     

Government size and economic growth in emerging market economies: a panel co-integration approach

A significant positive influence of both government size and domestic investment on economic growth is found in the long run during 1970–2006 for a sample of 19 emerging market economies, employing panel co-integration testing and estimating the parameters using dynamic ordinary least square method, for all the indicators, excepting the case when one chooses general government final consumption expenditure as a percentage of GDP a measure of government size and gross capital formation as a percentage of GDP a measure of domestic investment, with per capita GDP a proxy for economic growth. The findings corroborate the argument that diverse results of the earlier studies are due to different measures adopted.     

Multivariate regression tests of the arbitrage pricing theory: The instrumental-variables approach

This article expands the theoretical basis upon which empirical testing of the arbitrage pricing theory (APT) rests. Specifically, it specifies linear restrictions for worlds in which the APT holds. These restrictions may, in principle, be tested. Since the regressors in the model are only “noisy” proxies for a specific linear transformation of the factors or mimicking portfolios, testing regressions suffer from an errors-in-variables problem. The standard econometric treatment for this problem is the instrumental-variables approach. A size-based example is employed to compare the test results derived from the instrumental-variables approach to those obtained via the ordinary least squares (OLS) method. The results from both methods cannot reject a two-factor APT for the size-sorted portfolio sample. The authors appreciate the helpful comments of Edwin Burmeister, Raymond Chiang, Steve Pruitt, participant at the 1989 Western Finance Association annual meetings, Indiana University, and University of Miami, and especially Shmuel Kandel.     

Estimating Beta

This paper presents evidence that Ordinary Least Squares estimators of beta coefficients of major firms and portfolios are highly sensitive to observations of extremes in market index returns. This sensitivity is rooted in the inconsistency of the quadratic loss function in financial theory. By introducing considerations of risk aversion into the estimation procedure using alternative estimators derived from Gini measures of variability one can overcome this lack of robustness and improve the reliability of the results.