48 research outputs found
Environmental entrepreneurship and interorganizational arrangements : a model of social-benefit market creation
Research summary: Social-benefit markets, such as those for carbon trading, are becoming
increasingly popular for combating complex social and environmental problems. However,
their unique characteristics pose substantial challenges to market creation and
require novel entrepreneurial approaches. Integrating the entrepreneurship literature with
that of management information systems, we conceptualize social-benefit markets as a new
type of interorganizational arrangement and develop a model of social-benefit market creation.
First, we argue that a core entrepreneurial collective, comprising a plurality of
actors from government, business, and social movements, is essential. Second, we elaborate
a six-phase process through which the interests of entrepreneurs are aligned and
inscribed in a market artifact and the market is formed. The model is illustrated with reference
to the Western Climate Initiative’s carbon market creation efforts.
Managerial summary: Carbon markets have become a popular strategy for reducing
greenhouse gas emissions, with similar market-based solutions being proposed for
other social and environmental challenges. We refer to these new structures as socialbenefit
markets. Social-benefit market creation is a complex undertaking that will
require novel entrepreneurial approaches and new interorganizational information systems.
In an effort to reduce some of this complexity, we propose a model to explain
how entrepreneurs from government, business, and social movements must work collectively
to build social-benefit markets. We further elaborate a six-phase process
through which entrepreneurs are able to align their diverse interests and create a stable
market artifact. For managers from all sectors, our work offers actionable guidance
for forming collective ventures that deliver real social benefits. Copyright © 2017
Strategic Management Society
Employees’ Response to Corporate Greenwashing
Research on corporate greenwashing has expanded rapidly in recent years. At the same time, emerging studies in related literatures have found that employees are seeking out firms that are social and environmental leaders, and employee activism within firms is growing. However, the effect of firms’ exaggeration and misrepresentation of environmental claims, or greenwashing, on their own employees has been overlooked. Accordingly, we investigate greenwashing from an organizational psychology lens, exploring the impact it can have on employees, and whether these effects differ for different types of employees. Using data collected at three separate time points from a sample of employees educated in environmental science/sustainability, our results show that greenwashing was positively related to perceptions of corporate hypocrisy, which in turn, resulted in higher turnover intentions. We also found that these relationships were moderated by employees’ level of environmental education. By uncovering the deleterious effects greenwashing can have for employees and, by extension, for their employers, these findings generate insights into the extent to which corporate environmental communications can backfire
An Integrated Framework to Assess Greenwashing
In this paper we examine definitions of ‘greenwashing’ and its different forms, developing a tool for assessing diverse ‘green’ claims made by various actors. Research shows that significant deception and misleading claims exist both in the regulated commercial sphere, as well as in the unregulated non-commercial sphere (e.g., governments, NGO partnerships, international pledges, etc.). Recently, serious concerns have been raised over rampant greenwashing, in particular with regard to rapidly emerging net zero commitments. The proposed framework we developed is the first actionable tool for analysing the quality and truthfulness of such claims. The framework has widespread and unique potential for highlighting efforts that seek to delay or distract real solutions that are urgently needed today to tackle multiple climate and environmental crises. In addition, we note how the framework may also assist in the development of practices and communication strategies that ultimately avoid greenwashing
An Integrated Framework to Assess Greenwashing
Funding: This research was funded by the Department of Political Science at University of Vienna, Austria and the Institute at Brown for Environment and Society, USA, in association with Climate Social Science Network.Peer reviewedPublisher PD
Variants at multiple loci implicated in both innate and adaptive immune responses are associated with Sjögren’s syndrome
Sjögren’s syndrome is a common autoimmune disease (~0.7% of European Americans) typically presenting as keratoconjunctivitis sicca and xerostomia. In addition to strong association within the HLA region at 6p21 (Pmeta=7.65×10−114), we establish associations with IRF5-TNPO3 (Pmeta=2.73×10−19), STAT4 (Pmeta=6.80×10−15), IL12A (Pmeta =1.17×10−10), FAM167A-BLK (Pmeta=4.97×10−10), DDX6-CXCR5 (Pmeta=1.10×10−8), and TNIP1 (Pmeta=3.30×10−8). Suggestive associations with Pmeta<5×10−5 were observed with 29 regions including TNFAIP3, PTTG1, PRDM1, DGKQ, FCGR2A, IRAK1BP1, ITSN2, and PHIP amongst others. These results highlight the importance of genes involved in both innate and adaptive immunity in Sjögren’s syndrome
Whole-genome sequencing reveals host factors underlying critical COVID-19
Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease
Genetic mechanisms of critical illness in COVID-19.
Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 × 10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice
Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)
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Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial.
Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707