Search

Corporate Social Innovation (CSI) has emerged as a research priority for multinational enterprises (MNEs) due to the increasing popularity of sustainable development solutions addressing wicked problems in the 21st century. Although most studies on CSI have focused on data from developed economies, emphasising the younger generation's forward-looking, sustainable, and environmentally friendly attitudes, there exists a gap in our understanding of the attitude of the older generation towards CSI practices of MNEs operating in emerging economies. The UN's SDG 3 advocates for the well-being of all at all ages. Despite this, healthcare outcomes in global-south countries fall below standard. Therefore, we conducted an in-depth critical analysis of textual data concerning CSI practices of 115 healthcare MNEs operating in 13 emerging economies. We quantified the number of CSI practices in their annual reports and operationalised the dependent variable using an entropy index to calculate the density and percentage score of CSI. Drawing on Upper Echelons, our analysis revealed that older CEOs are likelier to promote, initiate, and implement CSI in greater depth and breadth. These findings present a compelling case supporting the argument that CEOs and board members tend to contribute more to society as they age. We offer empirical evidence supporting the strengthening roles of senior board members and female board chairs. Our findings complement existing CSI studies from developed countries and illustrate how CEO and board characteristics influence the depth and breadth of CSI in emerging economies. Keywords Corporate social innovation * Multinational enterprises * Weak institutional contexts * CEO age, 1 Introduction The concept of Sustainable Development Goals (SDGs) has emerged as a research priority for international business (IB) scholars due to the increasing urgency for sustainable solutions to grand [...]

The workplace is more emotionally charged than ever. Gone are the days of checking your emotions at the door. Leaders today must be prepared to field emotional challenges and use [...]

Each year the nation's oldest fox hunt, the Piedmont Hunt (dating to 1840), goes off from the Upperville, Virginia, property of Alex and Jill Holtzman Vogel and their family of [...]

Innovation districts have emerged as a powerful force in the modern economy, fostering collaboration between businesses, research institutions and communities. These districts are defined as geographic areas where anchor university [...]

JOURNEY BEASLEY Journey Beasley is a rising junior at North Little Rock Center of Excellence. She strives to show her leadership skills and learn on a daily basis, in and [...]

Contents 1. Executive summary 2. Background to the Scenario design 2.1 Climate Stress Test process 2.2 Too Little Too Late scenario narrative 2.3 Too Little Too Late scenario timeline for [...]

Q. We have a well-established customer offering us an opportunity to get into electroless nickel work with an available line we have. Can you provide an overview of the benefits [...]

ESG, or environmental, social and governance, has moved from a niche investment management tool into the mainstream. Still, despite its rapid growth, it is widely misunderstood by investors, the media [...]

I've read about the 6.5 Carcano but Lee Harvey Oswald's name is often never mentioned. Thank you, Keith Wood, for reminding America in the May 2024 'Spent Cases' column. Years [...]

Objective: To inform efforts to improve equity in the quality of behavioral health care by examining income-related differences in performance on HEDIS behavioral health measures in Medicare Advantage (MA) plans. Data Sources and Study Setting: Reporting Year 2019 MA HEDIS data were obtained and analyzed. Study Design: Logistic regression models were used to estimate differences in performance related to enrollee income, adjusting for sex, age, and race-and-ethnicity. Low-income enrollees were identified by Dual Eligibility for Medicare and Medicaid or receipt of the Low-Income Subsidy (DE/LIS). Models without and with random effects for plans were used to estimate overall and within-plan differences in measure performance. Heterogeneity by race-and-ethnicity in the associations of low-income with behavioral health quality were examined using models with interaction terms. Data Collection/Extraction Methods: Data were included for all MA contracts in the 50 states and the District of Columbia that collect HEDIS data. Principal Findings: For six of the eight measures, enrollees with DE/LIS coverage were more likely to have behavioral health conditions that qualify for HEDIS measures than higher income enrollees. In mixed-effects logistic regression models, DE/LIS coverage was associated with statistically significantly worse overall performance on five measures, with four large (>5 percentage point) differences (-7.5 to -11.1 percentage points) related to follow-up after hospitalization and avoidance of drug-disease interactions. Where the differences were large, they were primarily within-plan rather than between-plan. Interactions between DE/LIS and race-and-ethnicity were statistically significant (p < 0.05) for all measures; income-based quality gaps were larger for White enrollees than for Black or Hispanic enrollees. Conclusions: Low income is associated with lower performance on behavioral health HEDIS measures in MA, but these associations differ across racial-and-ethnic groups. Improving care integration and addressing barriers to care for low-income enrollees may improve equity across income levels in behavioral health care. KEYWORDS health care disparities, managed care organizations, Medicare, mental health, quality of care What is known on this topic * Higher-quality behavioral healthcare is associated with positive health outcomes, including improved mental health status and reduced risk of hospitalization. * Patients with limited income and resources face numerous barriers that can contribute to poorer quality care. * Prior research has found that Black and Hispanic Medicare Advantage enrollees receive lower-quality behavioral healthcare than White enrollees, but differences related to income have yet to be examined. What this study adds * Overall performance was statistically significantly lower for low-income enrollees than for higher income enrollees for five of eight measures examined, with large differences of 7.5-11.1 percentage points for four measures, * Large differences in performance were found for measures of follow-up after hospitalization and avoidance of drug-disease interactions, implicating coordination of care across multiple providers. * Income-related differences in performance varied across racial/ethnic groups, with larger deficits in performance among White enrollees than among Black or Hispanic enrollees., 1 | INTRODUCTION The use of behavioral health treatment has increased steadily over time, (1) but significant challenges remain with respect to the quality of care that patients receive as [...]

Summary and Key Findings * The financial system is exposed to a range of risks from climate change. Financial institutions have been making progress towards identifying and understanding these risks [...]

It is believed that cotton production originated more than 7,000 years ago. As a key component in global textiles for millennia, the various growing, harvesting and processing techniques have varied [...]

In 2006, British Turkish novelist Elif Shafak stood trial in Istanbul for the crime of "insulting Turkishness." What that meant, exactly, was anybody's guess. The charges carried with them a [...]

How the World Ran Out of Everything: Inside the Global Supply Chain. By Peter S. Goodman. June 2024. 416p. Mariner, $30 (9780063257924). 338. In October 2020, months after the world [...]

Under the microscope this spring: the Supreme Court, housing segregation, endemic poverty, police brutality, the patriarchy, immigration, whistleblowers, Hollywood abusers, cancel culture, the war in Ukraine, and Gerald Ford. TOP [...]

Hope springs eternal in a season marked by profiles of crusading lawmakers, tributes to female rule breakers, deep dives into landmark protest movements, stories of rescue and survival, and studies [...]

The Syracuse City School District (SCSD), accustomed to tight budgets and advocating to legislators for more funding, recently found itself in an unfamiliar position: It had more money than it [...]

Objective: To introduce a novel analytical approach for randomized controlled trials that are underpowered because of low participant enrollment or engagement. Data Sources: Reanalysis of data for 805 patients randomized as part of a pilot complex care intervention in 2015-2016 in a large delivery system. In the pilot randomized trial, only 64.6% of patients assigned to the intervention group participated. Study Design: A case study and simulation. The 'Distillation Method' capitalizes on the frequently observed correlation between the probability of subjects' participation or engagement in the intervention and the magnitude of benefit they experience. The novel method involves three stages: first, it uses baseline covariates to generate predicted probabilities of participation. Next, these are used to produce nested subsamples of the randomized intervention and control groups that are more concentrated with subjects who were likely to participate/engage. Finally, for the outcomes of interest, standard statistical methods are used to re-evaluate intervention effectiveness in these concentrated subsets. Data Extraction Methods: We assembled secondary data on patients who were randomized to the pilot intervention for one year prior to randomization and two follow-up years. Data included program enrollment status, membership data, demographics, utilization, costs, and clinical data. Principal Findings: Using baseline covariates only, Generalized Boosted Regression Models predicting program enrollment performed well (AUC 0.884). We then distilled the full randomized sample to increasing levels of concentration and reanalyzed program outcomes. We found statistically significant differences in outpatient utilization and emergency department utilization (both follow-up years), and in total costs (follow-up year two only) at select levels of population concentration. Conclusions: By offering an internally valid analytic framework, the Distillation Method can increase the power to detect effects by redefining the estimand to subpopulations with higher enrollment probabilities and stronger average treatment effects while maintaining the original randomization. KEYWORDS biostatistical methods, internal validity, learning health system, participant responsiveness, randomized controlled trial What is known on this topic * Randomized trials to test new care delivery models are often underpowered due to lowerthan-expected participation among the randomized intervention population. * In these scenarios, intent-to-treat analyses may produce false-negative results, but as-treated analyses are likely to be biased by selection effects. What this study adds * This study introduces a novel approach for analyzing trials when a large proportion of patients randomized to treatment received an insufficient amount of the intervention. * The Distillation Method can increase power by redefining the estimand to focus on patients with a higher probability of engaging with and benefiting from the intervention while retaining randomization status., 1 | INTRODUCTION By the time they are completed, randomized trials to test the effectiveness of new care delivery models are often underpowered. (1) Overly optimistic estimates of effect sizes [...]

Based in Sheboygan, WI, Iron Supports makes brackets and corbels for granite countertops, shelves, cabinets and fireplace mantels. The company began in a garage, but soon blossomed into a bustling [...]

Just in time for San Diego Comic-Con, we're back with another bursting-at-the-seams comics and graphic novels seasonal preview. Once again, comics reviews editor Meg Lemke and manga specialist Shaenon K. [...]

The Electric Vehicle Revolution: Five Visionaries Leading the Charge. By Kenneth K. Boyer. Aug. 2024. 266p. Rowman & Littlefield, $36 (9781538190746); e-book, $34 (9781538190753). 629.22. Boyer, an author, professor, and [...]

Justice Deferred MARGARET BURNHAM Margaret Burnham's commitment to civil rights and the Black struggle has taken her from 1960s Mississippi, where she was a staffer for the Student Nonviolent Coordinating [...]

For school districts in which parents want a stronger voice in prioritizing pandemic-related stimulus funds, technology can play an important role in communication and dialogue, which ultimately makes for better [...]

One summer night in the 1970s, Claire Messud's parents brought her and her older sister to visit friends who also had young children. Sent off to amuse themselves, the kids [...]

Of the many attractions Jackson, Wyo., has to offer--world-class skiing, stunning national parks, grown men and women in cowboy hats--recent visitors to the Teton County Library may have experienced the [...]

Objective: To model children's mental health policy making dynamics and simulate the impacts of knowledge broker interventions. Data sources: Primary data from surveys (n = 221) and interviews (n = 64) conducted in 2019-2021 with mental health agency (MHA) officials in state agencies. Study design: A prototype agent-based model (ABM) was developed using the PARTE (Properties, Actions, Rules, Time, Environment) framework and informed through primary data collection. In each simulation, a policy is randomly generated (salience weights: cost, contextual alignment, and strength of evidence) and discussed among agents. Agents are MHA officials and heterogenous in their properties (policy making power and network influence) and policy preferences (based on salience weights). Knowledge broker interventions add agents to the MHA social network who primarily focus on the policy's research evidence. Data collection/extraction methods: A sequential explanatory mixed method approach was used. Descriptive and regression analyses were used for the survey data and directed content analysis was used to code interview data. Triangulated results informed ABM development. In the ABM, policy makers with various degrees of decision influence interact in a scale-free network before and after knowledge broker interventions. Over time, each decides to support or oppose a policy proposal based on policy salience weights and their own properties and interactions. The main outcome is an agency-level decision based on policy maker support. Each intervention and baseline simulation runs 250 times across 50 timesteps. Principal findings: Surveys and interviews revealed that barriers to research use could be addressed by knowledge brokers. Simulations indicated that policy decision outcomes varied by policy making context within agencies. Conclusions: This is the first application of ABM to evidence-informed mental health policy making. Results suggest that the presence of knowledge brokers can: (1) influence consensus formation in MHAs, (2) accelerate policy decisions, and (3) increase the likelihood of evidence-informed policy adoption. KEYWORDS health policy/politics/law/regulation, mental health, state health policies What is known on this topic * Dissemination barriers, such as lacking access to contextually relevant evidence, have been found to inhibit the use of research evidence in public agency policy making. * Prior research suggests the knowledge brokers could address these barriers. What this study adds * When knowledge brokers are present, evidence-informed policies may be more likely to be adopted. * The presence of knowledge brokers can influence consensus formation in public agencies. * The process of simulation model development and the results here serve as a prototype for agent-based models that employ social network analysis to model policy making within agencies., 1 | INTRODUCTION Policy making is a complex process. (1,2) Complex processes are characterized by behaviors that dynamically interact over time through feedback loops and evolving, nonlinear relationships to 'create [...]

Adding a painting robot to a production process can bring with it improved quality and productivity. The functionality and cost of robotic paint systems has improved tremendously over the past [...]

In a world of uncertainty, there are some things you can count on: sunburns, stubbed toes, Bennifer drama. Thankfully, among the happier certainties are a fall season stacked with eagerly [...]

Objective: To examine the relationships between nonpharmacological treatment (NPT) utilization and opioid prescriptions and doses and whether these relationships vary according to the type of NPT service received. Data Source: Secondary data from the US Military Health System, nationwide. Study Design: Patterns of NPT utilization and opioid prescriptions were analyzed over the 23 months after initial pain treatment (index visit). Regression models were used to examine the relationship between opioid prescription use in a given month and NPT service utilization in the three preceding months, using person fixed effects to control for time-invariant patient characteristics, as well as time fixed effects. Analyses were stratified by whether the patient filled an opioid prescription in the first 30 days post index visit. Data Extraction Methods: Administrative data on health care utilization were extracted from the US Military Health System Data Repository for Army service members who returned from deployments in Afghanistan and Iraq that ended in fiscal years 2008 to 2014 and had at least one outpatient visit with a primary diagnosis of musculoskeletal pain in the subsequent year. Principal Findings: Utilization of any NPT service in the past 3 months was positively associated with filling an opioid prescription in the given month, regardless of whether the patient was initially prescribed opioids (percentage point difference [PP] =2.87, P < 0.01) or not (PP = 0.83, P < 0.01). However, for those not initially prescribed opioids, use of any NPT service in the past 3 months was negatively associated with mean daily opioid dose in the given month (morphine milligram equivalent dose = -0.4017, P < 0.01). For those initially prescribed opioids, NPT was not associated with opioid dose. Conclusions: NPT only reduced the prescription opioid daily dose for some patients, whereas the probability of receiving an opioid prescription was positively associated with NPT. Future research should assess whether recent system-level policies and program changes influence referral and opioid prescribing patterns. KEYWORDS complementary therapies, military health, musculoskeletal pain, nonpharmacological treatment, opioid analgesics, prescriptions, What is known on this topic? * Relative to clinical guidelines, opioids are excessively prescribed in pain management and many believe this could be reduced through more and earlier receipt [...]

Although coronavirus fell from first to third place among the issues global consumers are most worried about, according to Ipsos' October 2021 What Worries the World monthly surveys (28 countries, [...]

Just over one-quarter of global consumers surveyed by Ipsos' Global Health Monitor Service (27 markets, October 2020) cited mental health among the top health issues affecting their country, just behind [...]

Organic Social Media: How to Build Flourishing Online Communities. By Jenny Li Fowler. Dec. 2023. 232p. Kogan Page, paper, $29.99 (9781398612976); e-book (9781398612983). 658.872. Fowler, director of social media strategy [...]

Things couldn't have gone much better for a 28-year-old debut author in 1996. There were blurbs from Jay Mclnerney ('a funny, sad, nasty little gem of novel') and Tama Janowitz [...]