Relationships between absenteeism,conservation group membership,and land management among family forest owners

Absentee landowners, or those who do not live on their forestland, own approximately 117 million acres of private forestland in the U.S. Thus, their land management decisions and activities influence the flow of forest-based goods and services. We explore the question of whether absentee family forest owners are less active land managers than resident landowners and whether membership in conservation organizations is associated with higher levels of land management activity by absentee owners. To examine these questions, we administered a mail survey to randomly-selected family forest landowners in Indiana. While we found some support for the contention that absentee owners are less active forestland managers than resident owners, we also found they are not necessarily inactive landowners. We found absentee owners were less likely to have: inspected their forestland for invasive plants, pulled or cut invasive plants, used herbicides to kill invasive plants, reduced fire hazard, or grazed livestock than resident owners. Absentee owners were more likely to be enrolled in the Indiana Classified Forest and Wildlands Program, a preferential forest property tax program. Absentee owners who are members of a conservation organization were more likely than absentee non-member owners to have undertaken a variety of land management activities, including: undertaking wildlife habitat improvement projects, inspecting their forestland for invasive plants, pulling or cutting invasive plants, enrolling in the Indiana Classified Forest and Wildlands program, and obtaining a management plan.     

High-frequency credit spread information and macroeconomic forecast revision

We examine whether professional forecasters incorporate high-frequency information about credit conditions when revising their economic forecasts. Using a mixed data sampling regression approach, we find that daily credit spreads have significant predictive ability for monthly forecast revisions of output growth, at both the aggregate and individual forecast levels. The relationships are shown to be notably strong during ‘bad’ economic conditions, which suggests that forecasters anticipate more pronounced effects of credit tightening during economic downturns, indicating an amplification effect of financial developments on macroeconomic aggregates. The forecasts do not incorporate all financial information received in equal measures, implying the presence of information rigidities in the incorporation of credit spread information.     

Forecasting value at risk and expected shortfall with mixed data sampling

I propose applying the Mixed Data Sampling (MIDAS) framework to forecast Value at Risk (VaR) and Expected shortfall (ES). The new methods exploit the serial dependence on short-horizon returns to directly forecast the tail dynamics of the desired horizon. I perform a comprehensive comparison of out-of-sample VaR and ES forecasts with established models for a wide range of financial assets and backtests. The MIDAS-based models significantly outperform traditional GARCH-based forecasts and alternative conditional quantile specifications, especially in terms of multi-day forecast horizons. My analysis advocates models that feature asymmetric conditional quantiles and the use of the Asymmetric Laplace density to jointly estimate VaR and ES.     

When profession trumps potential: The moderating role of professional identification in employees’ reactions to talent management

Abstract

This study aimed to investigate the role that a professionalized context plays in shaping employee reactions to talent management decisions. We examined the mediating role of felt obligation in the relationship between talent ratings and organizational citizenship behavior. Further, the study tested whether professional identification moderates the relationship between talent ratings and felt obligation towards the organization. Five hundred and ninety-eight teachers that had recently received ratings of their talent status responded to a survey questionnaire. Felt obligation mediated the relationship between talent ratings and organizational citizenship behavior. Furthermore, professional identification moderated the relationship between ratings of potential and felt obligation in such a way that the relationship was strongest for the teachers expressing the lowest professional identification. At high levels of professional identification, the relationship was not significant. These results indicate that conventional talent management might be less effective for increasing favorable attitudes and behaviors among employees in highly professionalized contexts, such as the education sector.     

HR managers’ talent philosophies: prevalence and relationships with perceived talent management practices

Abstract

HR managers have different beliefs about the nature, value, and instrumentality of talent—referred to as ‘talent philosophies’. In line with cognitive psychology, we reason that talent philosophies are similar to mental models that influence how HR managers interpret and use talent management (TM) practices within their organizations. In this article, we explore the prevalence of four different talent philosophies (exclusive/stable; exclusive/developable; inclusive/stable; inclusive/developable) in a sample of 321?HR managers. We then explore how talent philosophies relate to organizational context (i.e. size, ownership form, multinational orientation) as well as to HR managers’ perceptions of their organization’s TM practices. Cluster analysis corroborated the presence of the four talent philosophies in our dataset. All four talent philosophies were represented almost equally often in the overall dataset. Organizational size was found to be related to talent philosophies, such that HR managers who worked in smaller organizations were more likely to hold an inclusive talent philosophy. We also found support for the relationship between talent philosophies and perceptions of the exclusiveness or inclusiveness of the organization’s definition of talent, and its degree of workforce differentiation. Contrary to expectations, results did not support a link between talent philosophies and perceived talent identification criteria.     

Identifying business opportunities for sustainable development: Longitudinal and experimental evidence contributing to the field of sustainable entrepreneurship

Which factors facilitate the identification of business opportunities for sustainable development? To answer this question, we develop a process model of sustainable opportunity identification. We argue that sustainable opportunity identification is a process with transitions from problem to solution identification and from solution to sustainable opportunity identification. Moreover, the transitions are facilitated by two factors—awareness of adverse consequences and entrepreneurial attitude—providing motivation and direction in the process. We tested our model in a field study (N = 107) and two experiments (N = 53 and N = 69). Our findings show that awareness of adverse consequences and entrepreneurial attitude influence the process of sustainable opportunity identification, explaining under which conditions people are more likely to identify business opportunities for sustainable development. Our study thus contributes to the field of sustainable entrepreneurship.     

The effect of mergers and acquisitions on environmental,social and governance performance and market value: Evidence from EU acquirers

This study explores the effect of environmental, social, and governance (ESG) performance on market value and performance in the context of mergers and acquisitions. We examine whether acquisition of targets with better ESG performance can help acquirers to increase their own ESG performance and whether the market values the increased ESG performance positively. Moreover, we explore whether the acquisition of targets with better ESG performance affects the market value of acquirers. For this study, we utilize a sample of 100 European mergers and acquisitions between 2003 and 2017, for which matching data on the ESG performance of both the target and acquiring firms are available. Our results show that the postmerger ESG performance of the acquirer increases following the acquisition of a target that has higher ESG performance than that of the acquirer in the premerger stage, whereas the postmerger market value of the acquirer increases following an increase in the acquirer's postmerger ESG performance in relation to its premerger ESG performance. Finally, we provide partial evidence of a positive relationship between the postmerger market value of the acquirer and the acquisition of a target with higher ESG performance than itself in the premerger stage.     

Do institutional investors drive corporate transparency regarding business contribution to the sustainable development goals?

Institutional investors show increasing interest in how companies align their corporate social responsibility strategies with the sustainable development goals (SDGs) proposed by the United Nations (UN). The information disclosed in this regard is essential to know and monitor business contribution to the 2030 Agenda. In this paper, we analyze the influence that institutional investors have on the adoption of the disclosure strategy established by UN and the Global Reporting Initiative (GRI)—GRI‐SDG Compass. The results obtained for a sample of 989 international companies, which prepare their sustainability reports following the GRI guidelines, show that ownership by foreign investors, pension funds, and “other” investors boosts the relevance of the information disclosed in relation to the 2030 Agenda. On the contrary, government, financial institutions, and cross holdings have no impact on the information systems developed.     

利用ACE值构造QC-LDPC码

为进一步提升中短码长下准循环低密度奇偶校验(Quasi-cyclic Low-density Parity-check,QC-LDPC) 码的纠错性能，提出了一种综合短环数目和环连通性的QC-LDPC码构造方法。首先，采用Golomb规则构造QC-LDPC码，对基矩阵中的部分元素进行替换预处理，初步降低短环数目；其次，采用所提的利用近似环外信息度（Approximate Cycle Extrinsic message degree，ACE）的消环掩模算法来优化QC-LDPC码，使得掩模后的校验矩阵具有较大的ACE平均值，最终完成QC-LDPC码的构造。该构造方法简单、通用性强，在短环数目和连通性间进行了平衡。与只考虑减少短环数目、增大围长等方法相比，该方法构造的QC-LDPC码有更加优异的纠错性能。     

人工智能在我国公共卫生建设中的应用与思考

新冠疫情的暴发以及长期防治对中国的公共卫生体系造成深远影响，给我国突发公共卫生事件应急与防控机制带来巨大的考验。在疫情防控的过程中，信息化技术为传统医疗机构带来瞩目的帮助与改变，人工智能、大数据、5G高速网络等新兴高科技的蓬勃发展在直接提升医疗水平方面表现出巨大潜力。本文就人工智能在疫情期间的医疗辅助功能展开讨论，并对未来我国公共卫生体系的建设进行了思考。