4 resultados para Design rules

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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This thesis consists of four essays on the design and disclosure of compensation contracts. Essays 1, 2 and 3 focus on behavioral aspects of mandatory compensation disclosure rules and of contract negotiations in agency relationships. The three experimental studies develop psychology- based theory and present results that deviate from standard economic predictions. Furthermore, the results of Essay 1 and 2 also have implications for firms’ discretion in how to communicate their top management’s incentives to the capital market. Essay 4 analyzes the role of fairness perceptions for the evaluation of executive compensation. For this purpose, two surveys targeting representative eligible voters as well as investment professionals were conducted. Essay 1 investigates the role of the detailed ‘Compensation Discussion and Analysis’, which is part of the Security and Exchange Commission’s 2006 regulation, on investors’ evaluations of executive performance. Compensation disclosure complying with this regulation clarifies the relationship between realized reported compensation and the underlying performance measures and their target achievement levels. The experimental findings suggest that the salient presentation of executives’ incentives inherent in the ‘Compensation Discussion and Analysis’ makes investors’ performance evaluations less outcome dependent. Therefore, investors’ judgment and investment decisions might be less affected by noisy environmental factors that drive financial performance. The results also suggest that fairness perceptions of compensation contracts are essential for investors’ performance evaluations in that more transparent disclosure increases the perceived fairness of compensation and the performance evaluation of managers who are not responsible for a bad financial performance. These results have important practical implications as firms might choose to communicate their top management’s incentive compensation more transparently in order to benefit from less volatile expectations about their future performance. Similar to the first experiment, the experiment described in Essay 2 addresses the question of more transparent compensation disclosure. However, other than the first experiment, the second experiment does not analyze the effect of a more salient presentation of contract information but the informational effect of contract information itself. For this purpose, the experiment tests two conditions in which the assessment of the compensation contracts’ incentive compatibility, which determines executive effort, is either possible or not. On the one hand, the results suggest that the quality of investors’ expectations about executive effort is improved, but on the other hand investors might over-adjust their prior expectations about executive effort if being confronted with an unexpected financial performance and under-adjust if the financial performance confirms their prior expectations. Therefore, in the experiment, more transparent compensation disclosure does not lead to more correct overall judgments of executive effort and to even lower processing quality of outcome information. These results add to the literature on disclosure which predominantly advocates more transparency. The findings of the experiment however, identify decreased information processing quality as a relevant disclosure cost category. Firms might therefore carefully evaluate the additional costs and benefits of more transparent compensation disclosure. Together with the results from the experiment in Essay 1, the two experiments on compensation disclosure imply that firms should rather focus on their discretion how to present their compensation disclosure to benefit from investors’ improved fairness perceptions and their spill-over on performance evaluation. Essay 3 studies the behavioral effects of contextual factors in recruitment processes that do not affect the employer’s or the applicant’s bargaining power from a standard economic perspective. In particular, the experiment studies two common characteristics of recruitment processes: Pre-contractual competition among job applicants and job applicants’ non-binding effort announcements as they might be made during job interviews. Despite the standard economic irrelevance of these factors, the experiment develops theory regarding the behavioral effects on employees’ subsequent effort provision and the employers’ contract design choices. The experimental findings largely support the predictions. More specifically, the results suggest that firms can benefit from increased effort and, therefore, may generate higher profits. Further, firms may seize a larger share of the employment relationship’s profit by highlighting the competitive aspects of the recruitment process and by requiring applicants to make announcements about their future effort. Finally, Essay 4 studies the role of fairness perceptions for the public evaluation of executive compensation. Although economic criteria for the design of incentive compensation generally do not make restrictive recommendations with regard to the amount of compensation, fairness perceptions might be relevant from the perspective of firms and standard setters. This is because behavioral theory has identified fairness as an important determinant of individuals’ judgment and decisions. However, although fairness concerns about executive compensation are often stated in the popular media and even in the literature, evidence on the meaning of fairness in the context of executive compensation is scarce and ambiguous. In order to inform practitioners and standard setters whether fairness concerns are exclusive to non-professionals or relevant for investment professionals as well, the two surveys presented in Essay 4 aim to find commonalities in the opinions of representative eligible voters and investments professionals. The results suggest that fairness is an important criterion for both groups. Especially, exposure to risk in the form of the variable compensation share is an important criterion shared by both groups. The higher the assumed variable share, the higher is the compensation amount to be perceived as fair. However, to a large extent, opinions on executive compensation depend on personality characteristics, and to some extent, investment professionals’ perceptions deviate systematically from those of non-professionals. The findings imply that firms might benefit from emphasizing the riskiness of their managers’ variable pay components and, therefore, the findings are also in line with those of Essay 1.

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Software architecture consists of a set of design choices that can be partially expressed in form of rules that the implementation must conform to. Architectural rules are intended to ensure properties that fulfill fundamental non-functional requirements. Verifying architectural rules is often a non- trivial activity: available tools are often not very usable and support only a narrow subset of the rules that are commonly specified by practitioners. In this paper we present a new highly-readable declarative language for specifying architectural rules. With our approach, users can specify a wide variety of rules using a single uniform notation. Rules can get tested by third-party tools by conforming to pre-defined specification templates. Practitioners can take advantage of the capabilities of a growing number of testing tools without dealing with them directly.

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OBJECTIVES To investigate the frequency of interim analyses, stopping rules, and data safety and monitoring boards (DSMBs) in protocols of randomized controlled trials (RCTs); to examine these features across different reasons for trial discontinuation; and to identify discrepancies in reporting between protocols and publications. STUDY DESIGN AND SETTING We used data from a cohort of RCT protocols approved between 2000 and 2003 by six research ethics committees in Switzerland, Germany, and Canada. RESULTS Of 894 RCT protocols, 289 prespecified interim analyses (32.3%), 153 stopping rules (17.1%), and 257 DSMBs (28.7%). Overall, 249 of 894 RCTs (27.9%) were prematurely discontinued; mostly due to reasons such as poor recruitment, administrative reasons, or unexpected harm. Forty-six of 249 RCTs (18.4%) were discontinued due to early benefit or futility; of those, 37 (80.4%) were stopped outside a formal interim analysis or stopping rule. Of 515 published RCTs, there were discrepancies between protocols and publications for interim analyses (21.1%), stopping rules (14.4%), and DSMBs (19.6%). CONCLUSION Two-thirds of RCT protocols did not consider interim analyses, stopping rules, or DSMBs. Most RCTs discontinued for early benefit or futility were stopped without a prespecified mechanism. When assessing trial manuscripts, journals should require access to the protocol.

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This work deals with parallel optimization of expensive objective functions which are modelled as sample realizations of Gaussian processes. The study is formalized as a Bayesian optimization problem, or continuous multi-armed bandit problem, where a batch of q > 0 arms is pulled in parallel at each iteration. Several algorithms have been developed for choosing batches by trading off exploitation and exploration. As of today, the maximum Expected Improvement (EI) and Upper Confidence Bound (UCB) selection rules appear as the most prominent approaches for batch selection. Here, we build upon recent work on the multipoint Expected Improvement criterion, for which an analytic expansion relying on Tallis’ formula was recently established. The computational burden of this selection rule being still an issue in application, we derive a closed-form expression for the gradient of the multipoint Expected Improvement, which aims at facilitating its maximization using gradient-based ascent algorithms. Substantial computational savings are shown in application. In addition, our algorithms are tested numerically and compared to state-of-the-art UCB-based batchsequential algorithms. Combining starting designs relying on UCB with gradient-based EI local optimization finally appears as a sound option for batch design in distributed Gaussian Process optimization.