Service tasks of board of directors: A literature review and research agenda in an era of new governance practices

In their seminal review article on board of directors, Johnson, Daily, and Ellstrand (1996) distinguished between the control, service, and resource dependence tasks of the board and called for a stronger focus on board service tasks. Following this call, service tasks of boards have been subject to increased scholarly attention, with new theoretical perspectives and methods introduced. This paper aims at presenting the current state of research on board service tasks, departing from, and building on, the contribution of Johnson and colleagues. In doing so, we employ an Input-Process-Output-Context framework and craft an agenda for how future research could accommodate new governance practices and progress the field. Our review is relevant and timely as studies on the subject are gaining traction both in corporate governance and general management journals. Furthermore, our review on board service tasks proposes new alternative approaches to studying corporate governance which are especially appropriate in times in which a rethink of corporate governance frameworks and concepts is urgently needed.     

A Novel Approach to Chemical Mixture Risk Assessment—Linking Data from Population‐Based Epidemiology and Experimental Animal Tests

Humans are continuously exposed to chemicals with suspected or proven endocrine disrupting chemicals (EDCs). Risk management of EDCs presents a major unmet challenge because the available data for adverse health effects are generated by examining one compound at a time, whereas real‐life exposures are to mixtures of chemicals. In this work, we integrate epidemiological and experimental evidence toward a whole mixture strategy for risk assessment. To illustrate, we conduct the following four steps in a case study: (1) identification of single EDCs (“bad actors”)—measured in prenatal blood/urine in the SELMA study—that are associated with a shorter anogenital distance (AGD) in baby boys; (2) definition and construction of a “typical” mixture consisting of the “bad actors” identified in Step 1; (3) experimentally testing this mixture in an in vivo animal model to estimate a dose–response relationship and determine a point of departure (i.e., reference dose [RfD]) associated with an adverse health outcome; and (4) use a statistical measure of “sufficient similarity” to compare the experimental RfD (from Step 3) to the exposure measured in the human population and generate a “similar mixture risk indicator” (SMRI). The objective of this exercise is to generate a proof of concept for the systematic integration of epidemiological and experimental evidence with mixture risk assessment strategies. Using a whole mixture approach, we could find a higher rate of pregnant women under risk (13%) when comparing with the data from more traditional models of additivity (3%), or a compound‐by‐compound strategy (1.6%).     

Organizational Reputation and the Securities and Exchange Commission's Failed Regulatory Revolution

When do regulatory innovations fail? I provide a novel organizations‐based answer to this question by developing an institutional‐reputational approach to regulatory politics. Regulators cannot hope to monitor the vast majority of market activities, so they must rely on the regulated to condition their behavior on the regulator's reputation: beliefs and expectations concerning the regulator's goals and capabilities. Regulators thus pursue daily activities while being mindful of how these activities will shape their reputation and thus their ability to achieve future goals. However, even long‐standing reputations are rendered fragile when rival actors use the organization's reputation to cross‐purposes. Thus, while reputation represents a major source of power, reputation also proves fragile when organizations face conflicting reputational demands. The fragility of reputations provides a novel explanation of an understudied phenomenon: failed regulatory revolutions. I develop this theory through the analysis of innovative Securities and Exchange Commission activity in disclosure law following the Watergate investigation.     

How Does Performance Management Affect Workers? Beyond Human Resource Management and Its Critique

While performance management (PM) is pervasive across contemporary workplaces, extant research into how performance management affects workers is often indirect or scattered across disciplinary silos. This paper reviews and synthesizes this research, identifies key gaps and explores ‘recognition theory’ as a nascent framework that can further develop this important body of knowledge. The paper develops in three main stages. The first stage reviews ‘mainstream’ human resource management (HRM) research. While this research analyses workers’ reactions to performance management in some depth, its focus on serving organizational goals marginalizes extra‐organizational impacts. The second stage reviews more critical HRM research, which interprets performance management as a disciplinary, coercive or inequitable management device. While this literature adds an important focus on organizational power, there is scope to analyse further how PM affects workers’ well‐being. To develop this strand of PM research, the third stage turns to the emerging field of recognition theory independently developed by Axel Honneth and Christophe Dejours. The authors focus especially on recognition theory's exploration of how (in)adequate acknowledgement of workers’ contributions can significantly affect their well‐being at the level of self‐conception. Although recognition theory is inherently critical, the paper argues that it can advance both mainstream and critical performance management research, and also inform broader inquiry into recognition and identity at work.     

慢市一种全新的舒适生活

或许,你听过或看过“慢活”这个名词,却不了解“慢活”是什么?它是全球正刮着的一股新风潮,有一群人极力鼓倡、推行着慢食、慢工、慢动、慢性、慢疗和慢闲运动,以一种正常而平衡的速度生活着……     

Determinants of Self-Rated Health Among Canadian Seniors Over Time: A Longitudinal Population-Based Study

Self-rated health has been found to be an effective and inexpensive measure of people’s overall health. Although cross-sectional studies have identified determinants of self-rated health (SRH), there is a limited insight into the determinants of SHR overtime and their impact on the change of SRH overtime. This present study compares determinants of SRH among a large community-dwelling cohort of Canadian seniors (N = 3255) at three points in time (1991, 1996, and 2001), and examines the effects of determinants on change in SRH over a 10-year period. Data analyzed were from the Canadian Study of Health and Aging—a large-scale longitudinal population-based study conducted between 1991 and 2001. The results showed that most seniors (over 80 %) rated their health as good, and their SRH remained surprisingly constant over time. Only a person’s physical and instrumental functioning and the number of chronic diseases were consistently associated with SRH at each point in time (1991, 1996, and 2001). Factors including cognition, daily functioning, chronic disease, and availability of help were significantly linked to self-rated health over time. These determinants should be considered important stimuli for improving health among seniors.     

Estimation in the generalized linear empirical bayes model using the extended quasi-likelihood

A generalized linear empirical Bayes model is developed for empirical Bayes analysis of several means in natural exponential families. A unified approach is presented for all natural exponential families with quadratic variance functions (the Normal, Poisson, Binomial, Gamma, and two others.) The hyperparameters are estimated using the extended quasi-likelihood of Nelder and Pregibon (1987), which is easily implemented via the GLIM package. The accuracy of these estimates is developed by asymptotic approximation of the variance. Two data examples are illustrated.     

Constrained optimal designs for regressiom models

An attempt of combining several optimality criteria simulaneously by using the techniques of nonliear programming is demonstrated. Four constrained D- and G-optimality criteria are introduced, namely, D-restrcted, D_s-restricted, A-restricted and E-restricted D- and G-optimality. The emphasis is particularly on the polynomial regression. Examples for quadratic polynomial regression are investigated to illustrate the applicability of these constrained optimality criteria.