bluuebunny/crossref_metadata_2025_split huggingface dataset:
How management groups’ reason when deciding to use a model focusing on systematic work environment management
Authors: Hellman Therese , Molin Fredrik , Eriksson Tomas , Svartengren Magnus 
Published: November 2019

PurposeThe purpose of this paper is to explore and describe the perspective of the management group regarding how they reasoned when deciding to engage in a model focussing on systematic work environment management, and what motives that influenced their decision.Design/methodology/approachThis qualitative study with semi-structured interviews includes 18 representatives from the management groups in 18 Swedish municipalities. Data were analysed with a constant comparative method.FindingsThe participants described two aspects that were of importance when making the decision; establishing commitment before making the decision and establishing strategies to legitimise the decision. Furthermore, they expressed motives that were linked both to their individual expectations and wishes and to policies and facts in their organisations. The participants experienced the model as a valuable tool in their organisations to increase employee participation and to provide structured support to their first-line managers.Practical implicationsThe managers’ motives were linked to individual expectations and external directives. These were often intertwined and influenced their decisions. When implementing this type of model, it is important to discuss decisions in a larger group to avoid building an organisational initiative on one person’s expectations. Furthermore, it is important to support the management’s work to establish commitment for the model in the municipal organisation.Originality/valueThis study adds to knowledge of the complexity of deciding and implementing models to support systematic work environment management in organisations.
Reputational intelligence: innovating brand management through social media data
Authors: Casado-Molina Ana-María , Ramos Celia M.Q. , Rojas-de-Gracia María-Mercedes , Peláez Sánchez José Ignacio 
Published: November 2019

Purpose
Companies are currently facing the challenge of understanding how their business is affected by the large volume of opinions continually generated by their stakeholders in social media regarding their intangible assets (experiences, emotions and attitudes). With this in mind, the purpose of this paper is to present an innovative management model, named E2AB, to measure and analyse reputational intangibles from digital ecosystems and their impacts on tangible assets.

Design/methodology/approach
The methodology applied was big data and business intelligence techniques. These methods were used in the computing process to obtain daily data from every asset guarantees that the model is validated with robust data. This model has been corroborated using data from the banking sector, specifically 402,383 net data inputs from the digital ecosystems.

Findings
This study illustrates the existence of a holistic influence of intangible assets over tangible assets. The findings demonstrate complex relationships between tangible and intangible assets, determined not only by the type of variable but also by its valence and intensity.

Practical implications
These findings may help chief communication officers and general managers a better understanding of how intangible assets extracted from online users’ opinions are related to their organisation’s tangible assets plus a chance to find out about their impact and how to manage them for a practical and agile decision making in real time.

Originality/value
It is a pioneering work in establishing a model, which demonstrates transversal and holistic relationships between relational intangible and tangible assets of firms from digital ecosystems, using business intelligence techniques.
How accurate are A-REIT IPO dividend forecasts?
Authors: Dimovski Bill , Ratcliffe Rebecca , Ratcliffe Christopher , Keneley Monica , Salzman Scott 
Published: November 2019

Purpose
The purpose of this paper is to investigate the accuracy of Australian Real Estate Investment Trust (A-REIT) initial public offering (IPO) dividend forecasts between 1994 and 2016.

Design/methodology/approach
This study compares the dividend forecasts of A-REIT IPOs for the first dividend forecast period in the prospectus, with the actual dividend declared for that forecast period. As well as simple descriptive summary measures, this study also employs an exact logistic regression approach to examine the factors that might influence the IPOs achieving or exceeding the dividend forecast.

Findings
The study identifies that the dividends declared, on average, were greater than the dividend forecast and that more than nine out of ten of the IPOs listed after 1999 achieved or exceeded their prospectus forecast. In addition the authors observe positive mean forecast errors, suggesting dividend forecasts in A-REIT IPOs, are cautiously biased. This is in contrast to the industrial company data reported in Brown et al. (2000) which suggest dividend forecasts are optimistically biased. The study also finds the A-REIT IPOs that did not forecast a dividend, generally did not pay a dividend.

Practical implications
The results will inform dividend seeking institutional and retail investors of the investment opportunities in A-REIT IPOs.

Originality/value
This paper adds to the discussion of the relative predictability of dividends of A-REIT IPOs compared to industrial company IPOs.
Physician leadership style predicts advanced practice provider job satisfaction
Authors: Guevara Robert S. , Montoya Jared , Carmody-Bubb Meghan , Wheeler Carol 
Published: November 2019

Purpose
This paper aims to examine the relationship between physician leadership style and advanced practice health-care provider job satisfaction.

Design/methodology/approach
A total of 320 advanced practice providers (nurse practitioners and physician assistants) in Texas rated their supervising/collaborating physicians’ leadership style using the Multifactor Leadership Questionnaire 5X Short (Bass and Avolio, 2000) and assessed their own job satisfaction using the Abridged Job Descriptive Index (Smith, Kendall and Hulin, 1969). Regression models tested the relationships between physician leadership styles and several facets of job satisfaction of advanced practice providers while controlling for advanced practice provider age, gender, ethnicity, years of experience, salary level, clinical practice setting, level of physician supervision/collaboration and advanced practice provider type.

Findings
The results demonstrated that physician transformational leadership accounted for between 4.4 and 49.1 per cent of the variance in job satisfaction depending on the aspect of job satisfaction. Satisfaction with job supervision and satisfaction with job in general were those in which transformational leadership was found to have the most impact, explaining 49.1 and 15.5%, respectively. Demographic variables such as advanced practice provider type, age, years of experience and number of hours per week of physician collaboration/supervision had small but statistically significant associations with job satisfaction.

Practical implications
Recommendations for physician leadership development focusing on transformational leadership as a way to increase the satisfaction among other providers on health-care teams are discussed.

Originality/value
This paper examines the impact of supervising/delegating physician leadership style on other nonphysician members of the health-care team, specifically advanced practice health-care providers.
An empirical evaluation of dynamic vs static withdrawal strategies
Authors: Johnston Ken , Hatem John , Carnes Thomas , Kosedag Arman 
Published: November 2019

Purpose
The purpose of this paper is to compare simple dynamic withdrawal strategies with the static withdrawal method, examining not only failure rates and ending wealth but also spending. All withdrawal strategies are adjusted for the Internal Revenue Service’s (IRS) required minimum distribution (RMD). In addition, this study investigates the use of small company stocks (SCS) in place of large company stocks (LCS). Results indicate SCS portfolios are superior to large. When returns are poor, some dynamic strategies will not ensure income for life. This study demonstrates that the simplest dynamic strategy is superior to two popular dynamic strategies.

Design/methodology/approach
Using historical overlapping periods, different withdrawal strategies are examined. Previous studies focused on failure rates and ending wealth. As discussed in Milevsky (2016) different statistical distributions can have similar tail properties (prob of failure) but dissimilar risk and return profile. The detailed examination of both spending and use of small stocks advances the literature in this area.

Findings
Results indicate that use of small stocks is superior to using large stocks in the portfolios. When US historical stock returns are adjusted downward, there is the potential that some dynamic strategies will not ensure income for life. This study demonstrates that the simplest dynamic strategy is superior to two popular dynamic strategies.

Originality/value
This paper is the first to examine, in detail, annual spending results for the retiree. Second, it is shown that, overall, SCS are superior to LCS for all stock/bond allocations. Even though absolute downside risk increases slightly, this increase in downside risk is dominated by the upside potential. In other words, the positive skewness of small stock returns along with the cumulative effects of compounding at a higher rate increases both the available wealth for spending and ending wealth. Third, IRS’s RMDs are taken into account for every withdrawal strategy examined. Lastly, it demonstrates that the simplest dynamic strategy is superior to two popular dynamic strategies.
Does response time predict withdrawal decisions? Lessons from a bank-run experiment
Authors: Kiss Hubert Janos , Rodriguez-Lara Ismael , Rosa-Garcia Alfonso 
Published: November 2019

PurposeThe purpose of this paper is to analyze how response time in a laboratory experiment on bank runs affects withdrawal decisions.Design/methodology/approachIn the authors’ setup, the bank has no fundamental problems, depositors decide sequentially whether to keep the money in the bank or to withdraw, and they may observe previous decisions depending on the information structure. The authors consider two levels of difficulty of decision-making conditional on the presence of strategic dominance and strategic uncertainty. The authors hypothesize that the more difficult the decision, the longer is the response time, and the predictive power of response time depends on difficulty.FindingsThe authors find that response time is longer in information sets with strategic uncertainty compared to those without (as expected), but the authors do not find such relationship when considering strategic dominance (contrary to the hypothesis). Response time correlates negatively with optimal decisions in information sets with a dominant strategy (contrary to the expectation) and also when decisions are obvious in the absence of strategic uncertainty (in line with the hypothesis). When there is strategic uncertainty, the authors find suggestive evidence that response time predicts optimal decisions.Research limitations/implicationsBeing a laboratory experiment, it is questionable if depositors in real life behave similarly (external validity).Practical implicationsSince episodes of bank runs are characterized by strategic uncertainty, the result that under strategic uncertainty, longer response time leads to better decisions suggests that suspension of convertibility is a useful tool to curb banking panics.Originality/valueTo the best of authors’ knowledge, this is the first study concerning the relationship between response time and the optimality of decisions in a bank-run game.
Functional diversity improves tropical forest resilience: Insights from a long‐term virtual experiment
Authors: Schmitt Sylvain , Maréchaux Isabelle , Chave Jerome , Fischer Fabian Jörg , Piponiot Camille , Traissac Stéphane , Hérault Bruno 
Published: November 2019

Abstract

Human activities modify the disturbance regimes of tropical forests. Since tropical forests host high biological diversity, understanding the role of biodiversity in ecosystem recovery pathways and the underlying ecological mechanisms is crucial to predict the fate of tropical ecosystems. Studies relying on regularly censused forest plots, rarely include disturbed forests, are not long enough to assess long‐term forest dynamics and often lack repeatability.

We used an individual‐based model of tropical forest growth to assess the effect of species and functional diversity on long‐term ecosystem recovery from disturbance. We manipulated the number of species and functional assemblages across a large number of simulations and simulated different levels of disturbance. To investigate the ecological mechanisms that underlie the effect of biodiversity on forest functioning along recovery pathways, we partitioned the net effect of biodiversity on ecosystem properties into complementarity and selection effects over time.

We found that functional diversity improved tropical forest resilience after a disturbance. The complementarity effect dominated soon after the disturbance but was progressively surpassed by a selection effect as more competitive species dominated the forest community. This pattern increased with the intensity of the disturbance.

Synthesis. We found that the mechanisms through which biodiversity influences forest functioning depend on the ecosystem state, shifting from a dominant complementarity effect in recently disturbed systems to a selection effect in systems disturbed a long time ago. Our results thus suggest that the time since the last disturbance is a key to understanding biodiversity–ecosystem functioning relationships in tropical forests and can help reconcile previous contrasting results obtained with snapshots of ecosystem state in empirical studies.
Leaf drought tolerance cannot be inferred from classic leaf traits in a tropical rainforest
Authors: Maréchaux Isabelle , Saint‐André Laurent , Bartlett Megan K. , Sack Lawren , Chave Jérôme 
Published: November 2019

Abstract

Plants are enormously diverse in their traits and ecological adaptation, even within given ecosystems, such as tropical rainforests. Accounting for this diversity in vegetation models poses serious challenges. Global plant functional trait databases have highlighted general trait correlations across species that have considerably advanced this research program. However, it remains unclear whether trait correlations found globally hold within communities, and whether they extend to drought tolerance traits.

For 134 individual plants spanning a range of sizes and life forms (tree, liana, understorey species) within an Amazonian forest, we measured leaf drought tolerance (leaf water potential at turgor loss point, πtlp), together with 17 leaf traits related to various functions, including leaf economics traits and nutrient composition (leaf mass per area, LMA; and concentrations of C, N, P, K, Ca and Mg per leaf mass and area), leaf area, water‐use efficiency (carbon isotope ratio), and time‐integrated stomatal conductance and carbon assimilation rate per leaf mass and area. We tested trait coordination and the ability to estimate πtlp from the other traits through model selection. Performance and transferability of the best predictive model were assessed through cross‐validation.

Here πtlp was positively correlated with leaf area, and with N, P and K concentrations per leaf mass, but not with LMA or any other studied trait. Five axes were needed to account for >80% of trait variation, but only three of them explained more variance than expected at random. The best model explained only 30% of the variation in πtlp, and out‐sample predictive performance was variable across life forms or canopy strata, suggesting a limited transferability of the model.

Synthesis. We found a weak correlation among leaf drought tolerance and other leaf traits within a forest community. We conclude that higher trait dimensionality than assumed under the leaf economics spectrum may operate among leaves within plant communities, with important implications for species coexistence and responses to changing environmental conditions, and also for the representation of community diversity in vegetation models.
Recurrent seasonal changes in bacterial growth efficiency, metabolism and community composition in coastal waters
Authors: Baña Zuriñe , Abad Naiara , Uranga Ainhoa , Azúa Iñigo , Artolozaga Itxaso , Unanue Marian , Iriberri Juan , Arrieta Jesus M. , Ayo Begoña 
Published: November 2019

SummaryThe microbial response to environmental changes in coastal waters of the eastern Cantabrian Sea was explored for four years by analysing a broad set of environmental variables along with bacterial community metabolism and composition. A recurrent seasonal cycle emerged, consisting of two stable periods, characterized by low bacterial metabolic activity (winter) from October to March, and high bacterial metabolic activity (summer) from May to August. These two contrasting periods were linked by short transition periods in April (TA) and September (TS). The phylogenetic groups Alphaproteobacteria and Bacteroidetes were dominant during winter and summer respectively, and their recurrent alternation was mainly driven by the bloom of eukaryotic phytoplankton before TA and the bloom of prokaryotic phytoplankton before TS. Bacterial growth efficiency remained high and stable during the winter and summer periods but dropped during the two short transition periods. Our results suggest that bacterial growth efficiency should be considered a very resilient property that reflects different stages in the adaptation of the bacterial community composition to the environmental changes occurring throughout the seasonal cycle in this coastal ecosystem.
Effect of deprivation on in vitro fertilisation outcome: a cohort study
Authors: Richardson AL , Baskind NE , Karuppusami R , Balen AH 
Published: November 2019

ObjectiveTo determine whether socioeconomic deprivation affects IVF outcome independent of the number of cycles undertaken.DesignA retrospective review of prospectively collected data.SettingA tertiary level fertility clinic in the North of England.PopulationAll participants undergoing their first fresh single‐embryo transfer, funded by the National Health Service (NHS), between January 2012 and December 2017.MethodsFor each case, identified from the clinic database, we recorded the following: age; body mass index; FSH; number of eggs retrieved; ethnicity; cause of subfertility; stage of embryo transfer; and whether any adjuncts i.e. EmbryoGlue® or Time Lapse Imaging were used. Socio‐economic deprivation was assessed using the Index of Multiple Deprivation (IMD) determined by the residential postcode.Main outcome measuresClinical pregnancy (CP) and live birth (LB) rates across IMD quintiles.ResultsThree thousand ninety‐one women were included. Overall, CP and LB rates were 35.9% and 31.3% respectively. CP rates increased significantly from 31.0% in the most deprived group to 38.8% in the least deprived group (P < 0.01). Similarly, LB rates were significantly lower in the most deprived group compared with the least deprived group (26.8 versus 35.4%, P < 0.01). After adjusting for confounding variables, women in the least deprived group were significantly more likely to have a LB (aRR 1.18, 95% CI 1.00–1.39) than women in the most deprived group.ConclusionsMore socio‐economically deprived patients are significantly less likely to achieve a LB than less deprived patients independent of the number of cycles of IVF undertaken.Tweetable abstractMore deprived patients are less likely to have a LB per cycle of IVF than less deprived patients.
Pravastatin for early‐onset pre‐eclampsia: a randomised, blinded, placebo‐controlled trial
Authors: Ahmed A , Williams DJ , Cheed V , Middleton LJ , Ahmad S , Wang K , Vince AT , Hewett P , Spencer K , Khan KS , Daniels JP ,   the StAmP trial Collaborative Group
Published: November 2019

SummaryObjectiveWomen with pre‐eclampsia have elevated circulating levels of soluble fms‐like tyrosine kinase‐1 (sFlt‐1). Statins can reduce sFlt‐1 from cultured cells and improve pregnancy outcome in animals with a pre‐eclampsia‐like syndrome. We investigated the effect of pravastatin on plasma sFlt‐1 levels during pre‐eclampsia.DesignBlinded (clinician and participant), proof of principle, placebo‐controlled trial.SettingFifteen UK maternity units.PopulationWe used a minimisation algorithm to assign 62 women with early‐onset pre‐eclampsia (24+0–31+6 weeks of gestation) to receive pravastatin 40 mg daily (n = 30) or matched placebo (n = 32), from randomisation to childbirth.Primary outcomeDifference in mean plasma sFlt‐1 levels over the first 3 days following randomisation.ResultsThe difference in the mean maternal plasma sFlt‐1 levels over the first 3 days after randomisation between the pravastatin (n = 27) and placebo (n = 29) groups was 292 pg/ml (95% CI −1175 to 592; P = 0.5), and over days 1–14 was 48 pg/ml (95% CI −1009 to 913; P = 0.9). Women who received pravastatin had a similar length of pregnancy following randomisation compared with those who received placebo (hazard ratio 0.84; 95% CI 0.50–1.40; P = 0.6). The median time from randomisation to childbirth was 9 days (interquartile range [IQR] 5–14 days) for the pravastatin group and 7 days (IQR 4–11 days) for the placebo group. There were three perinatal deaths in the placebo‐treated group and no deaths or serious adverse events attributable to pravastatin.ConclusionsWe found no evidence that pravastatin lowered maternal plasma sFlt‐1 levels once early‐onset pre‐eclampsia had developed. Pravastatin appears to have no adverse perinatal effects.Tweetable abstractPravastatin does not improve maternal plasma sFlt‐1 or placental growth factor levels following a diagnosis of early preterm pre‐eclampsia #clinicaltrial finds.
The impact of the Medicaid high‐risk ob care management program in New York State
Authors: Park Young Joo , Weinberg Stephen , Cogan Lindsay W. 
Published: November 2019

AbstractObjectivesTo examine the effect of high‐risk obstetrics (HROB) care management on infant health and Medicaid expenditures.Data Sources/Study SettingMedicaid administrative data and vital statistics from 2011 to 2013. In New York State, all Medicaid managed care plans provide HROB care management to their members.Study DesignWe conducted a retrospective cohort study with a nonequivalent control group. Selection bias was addressed by using probit and OLS models with the Heckman correction and inverse probability weight with regression adjustment.Principal FindingsWhile program enrollment was associated with poor infant health outcomes (low birthweight, very low birthweight, preterm delivery, and gestational age), correcting for sample selection substantially improved most of these outcomes. All infant health outcomes significantly improved as the number of weeks in the program increased. We found that a 1‐week increase in program duration is associated with a 0.01 percentage point decrease in low birthweight and a 0.03 percentage point decrease in very low birthweight. Further, a 1‐week increase in program duration decreases the probability of preterm delivery by 0.01 percentage points and increases gestational age by 0.14 days. Medicaid expenditures for maternity care and newborn delivery were not significantly or materially affected by program enrollment or program duration.ConclusionsHigh‐risk obstetrics care management appears to successfully identify individuals with high‐risk pregnancies and improve health without substantially increasing medical expenses.