Explicit Relative Performance Evaluation in Performance-Vested Equity Grants

Using data from FTSE 350 firms, we examine factors influencing explicit relative performance evaluation (RPE) conditions in performance-vested equity grants. We provide exploratory evidence on whether the use or characteristics of RPE are associated with efforts to improve incentives by removing common risk, other economic factors discussed in the RPE literature, or external pressure to implement RPE. We find that many of these economic factors, including common risk reduction, are more closely related to specific relative performance conditions than to the firm-level decision to use RPE in some or all of their equity grants. We also find that greater external monitoring by institutional investors or others is associated with plans with tougher overall RPE conditions. The relative performance conditions are binding in most RPE plans, with nearly two-thirds of the grants vesting only partially or not vesting at all. Further, we find evidence that vesting percentages vary in RPE and non-RPE plans

The multiplicity of performance management systems:Heterogeneity in multinational corporations and management sense-making

This field study examines the workings of multiple performance measurement systems (PMSs) used within and between a division and Headquarters (HQ) of a large European corporation. We explore how multiple PMSs arose within the multinational corporation. We first provide a first‐order analysis which explains how managers make sense of the multiplicity and show how an organization's PMSs may be subject to competing processes for control that result in varied systems, all seemingly functioning, but with different rationales and effects. We then provide a second‐order analysis based on a sense‐making perspective that highlights the importance of retrospective understandings of the organization's history and the importance of various legitimacy expectations to different parts of the multinational. Finally, we emphasize the role of social skill in sense‐making that enables the persistence of multiple systems and the absence of overt tensions and conflict within organizations

Signaling in Secret: Pay-for-Performance and the Incentive and Sorting Effects of Pay Secrecy

Key Findings: Pay secrecy adversely impacts individual task performance because it weakens the perception that an increase in performance will be accompanied by increase in pay; Pay secrecy is associated with a decrease in employee performance and retention in pay-for-performance systems, which measure performance using relative (i.e., peer-ranked) criteria rather than an absolute scale (see Figure 2 on page 5); High performing employees tend to be most sensitive to negative pay-for- performance perceptions; There are many signals embedded within HR policies and practices, which can influence employees’ perception of workplace uncertainty/inequity and impact their performance and turnover intentions; and When pay transparency is impractical, organizations may benefit from introducing partial pay openness to mitigate these effects on employee performance and retention

Machine Learning in Automated Text Categorization

The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last ten years, due to the increased availability of documents in digital form and the ensuing need to organize them. In the research community the dominant approach to this problem is based on machine learning techniques: a general inductive process automatically builds a classifier by learning, from a set of preclassified documents, the characteristics of the categories. The advantages of this approach over the knowledge engineering approach (consisting in the manual definition of a classifier by domain experts) are a very good effectiveness, considerable savings in terms of expert manpower, and straightforward portability to different domains. This survey discusses the main approaches to text categorization that fall within the machine learning paradigm. We will discuss in detail issues pertaining to three different problems, namely document representation, classifier construction, and classifier evaluation.Comment: Accepted for publication on ACM Computing Survey

Cytoplasmic Accumulation and Aggregation of TDP-43 upon Proteasome Inhibition in Cultured Neurons

Amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) are characterized by intraneuronal deposition of the nuclear TAR DNA-binding protein 43 (TDP-43) caused by unknown mechanisms. Here, we studied TDP-43 in primary neurons under different stress conditions and found that only proteasome inhibition by MG-132 or lactacystin could induce significant cytoplasmic accumulation of TDP-43, a histopathological hallmark in disease. This cytoplasmic accumulation was accompanied by phosphorylation, ubiquitination and aggregation of TDP-43, recapitulating major features of disease. Proteasome inhibition produced similar effects in both hippocampal and cortical neurons, as well as in immortalized motor neurons. To determine the contribution of TDP-43 to cell death, we reduced TDP-43 expression using small interfering RNA (siRNA), and found that reduced levels of TDP-43 dose-dependently rendered neurons more vulnerable to MG-132. Taken together, our data suggests a role for the proteasome in subcellular localization of TDP-43, and possibly in disease

Mouse models of frontotemporal dementia: a comparison of phenotypes with clinical symptomatology

Frontotemporal dementia (FTD) is the second most common cause of young onset dementia. It is increasingly recognized that there is a clinical continuum between FTD and amyotrophic lateral sclerosis (ALS). At a clinical, pathological and genetic level there is much heterogeneity in FTD, meaning that our understanding of this condition, pathophysiology and development of treatments has been limited. A number of mouse models focusing predominantly on recapitulating neuropathological and molecular changes of disease have been developed, with most transgenic lines expressing a single specific protein or genetic mutation. Together with the species-typical presentation of functional deficits, this makes the direct translation of results from these models to humans difficult. However, understanding the phenotypical presentations in mice and how they relate to clinical symptomology in humans is essential for advancing translation. Here we review current mouse models in FTD and compare their phenotype to the clinical presentation in patients