The impact of gender diversity on performance in services and manufacturing organizations

We present three competing predictions of the organizational gender diversity-performance relationship: a positive linear prediction, a negative linear prediction, and an inverted U-shaped curvilinear prediction. The paper also proposes a moderating effect of industry type (services vs. manufacturing). The predictions were tested using archival quantitative data with a longitudinal design. The results show partial support for the positive linear and inverted U-shaped curvilinear predictions as well as for the proposed moderating effect of industry type. The results help reconcile the inconsistent findings of past research. The findings also show that industry context can strengthen or weaken gender diversity effects.

Workforce gender diversity: Is it a source of competitive advantage?

Research on workforce diversity at the organisational level gained momentum in the 1990s, because of the growing trend in HR research to link HR practices with organisational performance. The new parallel wave of research focused on the business case for diversity, in which diversity was linked to organisational performance. However, the results of these studies, mainly focusing on linear diversity-performance relationships, have been inconsistent. Based on contrasting theories, this paper proposes three competing predictions of the gender diversity-performance relationship at the organisational level: a positive linear relationship derived from the resource-based view of the firm, a negative linear relationship derived from self-categorisation and social identity theories, and a U-shaped curvilinear relationship derived from the integration of the resource-based view of the firm with self-categorisation and social identity theories. The U-shaped relationship accounts for the inconsistent findings in past research, because different proportions of men and women produce different social dynamics that have different effects on organisational performance. Further, the proposed U-shaped relationship can have different slopes in the manufacturing and services industries. The paper contributes to the field of diversity by strengthening its weak theoretical foundations and by highlighting the industry differences.

The gender diversity-performance relationship in services and manufacturing organizations

Empirical findings on the link between gender diversity and performance have been inconsistent. This paper presents three competing predictions of the organizational gender diversity-performance relationship: a positive linear prediction derived from the resource-based view of the firm, a negative linear prediction derived from self-categorization and social identity theories, and an inverted U-shaped curvilinear prediction derived from the integration of the resource-based view of the firm with self-categorization and social identity theories. This paper also proposes a moderating effect of industry type (services vs. manufacturing) on the gender diversity-performance relationship. The predictions were tested in publicly listed Australian organizations using archival quantitative data with a longitudinal research design. The results show partial support for the positive linear and inverted U-shaped curvilinear predictions as well as for the proposed moderating effect of industry type. The curvilinear relationship indicates that different proportions of organizational gender diversity have different effects on organizational performance, which may be attributed to different dynamics as suggested by the resource-based view and self-categorization and social identity theories. The results help reconcile the inconsistent findings of past research that focused on the linear gender diversity-performance relationship. The findings also show that industry context can strengthen or weaken the effects of organizational gender diversity on performance.

Functional heterogeneity as a two-dimensional concept : empirical evidence for new venture teams

Previous research on entrepreneurial teams has failed to settle the controversy over whether team heterogeneity helps or hinders new venture performance. Reconciling this inconsistency, this paper suggests a new conceptual approach to disentangle differential effects of team heterogeneity by modeling two separate heterogeneity dimensions, namely knowledge scope and knowledge disparity. Analyzing unique data on functional experiences of the members of 337 start-up teams, we find support for our contention of team heterogeneity as a two-dimensional concept. Results suggest that knowledge disparity negatively relates to both start-ups’ entrepreneurial and innovative performance. In contrast, we find knowledge scope to positively affect entrepreneurial performance, while it shows an inverse U-shaped relationship to innovative start-up performance.

The impact of temperature on mortality in Tianjin, China : a case-crossover design with a distributed lag non-linear model

Background There has been increasing interest in assessing the impacts of temperature on mortality. However, few studies have used a case–crossover design to examine non-linear and distributed lag effects of temperature on mortality. Additionally, little evidence is available on the temperature-mortality relationship in China, or what temperature measure is the best predictor of mortality. Objectives To use a distributed lag non-linear model (DLNM) as a part of case–crossover design. To examine the non-linear and distributed lag effects of temperature on mortality in Tianjin, China. To explore which temperature measure is the best predictor of mortality; Methods: The DLNM was applied to a case¬−crossover design to assess the non-linear and delayed effects of temperatures (maximum, mean and minimum) on deaths (non-accidental, cardiopulmonary, cardiovascular and respiratory). Results A U-shaped relationship was consistently found between temperature and mortality. Cold effects (significantly increased mortality associated with low temperatures) were delayed by 3 days, and persisted for 10 days. Hot effects (significantly increased mortality associated with high temperatures) were acute and lasted for three days, and were followed by mortality displacement for non-accidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. Conclusions In Tianjin, extreme cold and hot temperatures increased the risk of mortality. Results suggest that the effects of cold last longer than the effects of heat. It is possible to combine the case−crossover design with DLNMs. This allows the case−crossover design to flexibly estimate the non-linear and delayed effects of temperature (or air pollution) whilst controlling for season.

The impact of temperature on years of life lost in Brisbane, Australia

Temperature is an important determinant of health. A better knowledge of how temperature affects population health is important not only to the scientific community, but also to the decision-makers who develop and implement early warning systems and intervention strategies to mitigate the health effects of extreme temperatures. The temperature–health relationship is also of growing interest as climate change is projected to shift the overall temperature distribution higher. Previous studies have examined the relative risks of temperature-related mortality, but the absolute measure of years of life lost is also useful as it combines the number of deaths with life expectancy. Here we use years of life lost to provide a novel measure of the impact of temperature on mortality in Brisbane, Australia. We also project the future temperature-related years of life lost attributable to climate change. We show that the association between temperature and years of life lost is U-shaped, with increased years of life lost for cold and hot temperatures. The temperature-related years of life lost will worsen greatly if future climate change goes beyond a 2 �C increase and without any adaptation to higher temperatures. This study highlights that public health adaptation to climate change is necessary.

Effects of extreme temperatures on years of life lost for cardiovascular deaths : a time series study in Brisbane, Australia

Background: Extreme temperatures are associated with cardiovascular disease (CVD) deaths. Previous studies have investigated the relative CVD mortality risk of temperature, but this risk is heavily influenced by deaths in frail elderly persons. To better estimate the burden of extreme temperatures we estimated their effects on years of life lost due to CVD. Methods and Results: The data were daily observations on weather and CVD mortality for Brisbane, Australia between 1996 and 2004. We estimated the association between daily mean temperature and years of life lost due to CVD, after adjusting for trend, season, day of the week, and humidity. To examine the non-linear and delayed effects of temperature, a distributed lag non-linear model was used. The model’s residuals were examined to investigate if there were any added effects due to cold spells and heat waves. The exposure-response curve between temperature and years of life lost was U-shaped, with the lowest years of life lost at 24 °C. The curve had a sharper rise at extremes of heat than of cold. The effect of cold peaked two days after exposure, whereas the greatest effect of heat occurred on the day of exposure. There were significantly added effects of heat waves on years of life lost. Conclusions: Increased years of life lost due to CVD are associated with both cold and hot temperatures. Research on specific interventions is needed to reduce temperature-related years of life lost from CVD deaths.

Larger or broader : performance implications of size and diversity of the knowledge worker's egocentric network. [更多或更广：知识员工个人中心网络大小和 多样性对绩效的影响]

Management scholars and practitioners emphasize the importance of the size and diversity of a knowledge worker's social network. Constraints on knowledge workers’ time and energy suggest that more is not always better. Further, why and how larger networks contribute to valuable outcomes deserves further understanding. In this study, we offer hypotheses to shed insight on the question of the diminishing returns of large networks and the specific form of network diversity that may contribute to innovative performance among knowledge workers. We tested our hypotheses using data collected from 93 R&D engineers in a Sino-German automobile electronics company located in China. Study findings identified an inflection point, confirming our hypothesis that the size of the knowledge worker's egocentric network has an inverted U-shaped effect on job performance. We further demonstrate that network dispersion richness (the number of cohorts that the focal employee has connections to) rather than network dispersion evenness (equal distribution of ties across the cohorts) has more influence on the knowledge worker's job performance. Additionally, we found that the curvilinear effect of network size is fully mediated by network dispersion richness. Implications for future research on social networks in China and Western contexts are discussed.

Socioeconomic inequalities in cardiovascular mortality and the role of childhood socioeconomic conditions and adulthood risk factors : a prospective cohort study with 17-years of follow up

Background The mechanisms underlying socioeconomic inequalities in mortality from cardiovascular diseases (CVD) are largely unknown. We studied the contribution of childhood socioeconomic conditions and adulthood risk factors to inequalities in CVD mortality in adulthood. Methods The prospective GLOBE study was carried out in the Netherlands, with baseline data from 1991, and linked with the cause of death register in 2007. At baseline, participants reported on adulthood socioeconomic position (SEP) (own educational level), childhood socioeconomic conditions (occupational level of respondent’s father), and a broad range of adulthood risk factors (health behaviours, material circumstances, psychosocial factors). This present study is based on 5,395 men and 6,306 women, and the data were analysed using Cox regression models and hazard ratios (HR). Results A low adulthood SEP was associated with increased CVD mortality for men (HR 1.84; 95% CI: 1.41-2.39) and women (HR 1.80; 95%CI: 1.04-3.10). Those with poorer childhood socioeconomic conditions were more likely to die from CVD in adulthood, but this reached statistical significance only among men with the poorest childhood socioeconomic circumstances. About half of the investigated adulthood risk factors showed significant associations with CVD mortality among both men and women, namely renting a house, experiencing financial problems, smoking, physical activity and marital status. Alcohol consumption and BMI showed a U-shaped relationship with CVD mortality among women, with the risk being significantly greater for both abstainers and heavy drinkers, and among women who were underweight or obese. Among men, being single or divorced and using sleep/anxiety drugs increased the risk of CVD mortality. In explanatory models, the largest contributor to adulthood CVD inequalities were material conditions for men (42%; 95% CI: −73 to −20) and behavioural factors for women (55%; 95% CI: -191 to −28). Simultaneous adjustment for adulthood risk factors and childhood socioeconomic conditions attenuated the HR for the lowest adulthood SEP to 1.34 (95% CI: 0.99-1.82) for men and 1.19 (95% CI: 0.65-2.15) for women. Conclusions Adulthood material, behavioural and psychosocial factors played a major role in the explanation of adulthood SEP inequalities in CVD mortality. Childhood socioeconomic circumstances made a modest contribution, mainly via their association with adulthood risk factors. Policies and interventions to reduce health inequalities are likely to be most effective when considering the influence of socioeconomic circumstances across the entire life course and in particular, poor material conditions and unhealthy behaviours in adulthood.

Estimating the effects of ambient temperature on mortality : methodological challenges and proposed solutions

The health impacts of exposure to ambient temperature have been drawing increasing attention from the environmental health research community, government, society, industries, and the public. Case-crossover and time series models are most commonly used to examine the effects of ambient temperature on mortality. However, some key methodological issues remain to be addressed. For example, few studies have used spatiotemporal models to assess the effects of spatial temperatures on mortality. Few studies have used a case-crossover design to examine the delayed (distributed lag) and non-linear relationship between temperature and mortality. Also, little evidence is available on the effects of temperature changes on mortality, and on differences in heat-related mortality over time. This thesis aimed to address the following research questions: 1. How to combine case-crossover design and distributed lag non-linear models? 2. Is there any significant difference in effect estimates between time series and spatiotemporal models? 3. How to assess the effects of temperature changes between neighbouring days on mortality? 4. Is there any change in temperature effects on mortality over time? To combine the case-crossover design and distributed lag non-linear model, datasets including deaths, and weather conditions (minimum temperature, mean temperature, maximum temperature, and relative humidity), and air pollution were acquired from Tianjin China, for the years 2005 to 2007. I demonstrated how to combine the case-crossover design with a distributed lag non-linear model. This allows the case-crossover design to estimate the non-linear and delayed effects of temperature whilst controlling for seasonality. There was consistent U-shaped relationship between temperature and mortality. Cold effects were delayed by 3 days, and persisted for 10 days. Hot effects were acute and lasted for three days, and were followed by mortality displacement for non-accidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. It is still unclear whether spatiotemporal models using spatial temperature exposure produce better estimates of mortality risk compared with time series models that use a single site’s temperature or averaged temperature from a network of sites. Daily mortality data were obtained from 163 locations across Brisbane city, Australia from 2000 to 2004. Ordinary kriging was used to interpolate spatial temperatures across the city based on 19 monitoring sites. A spatiotemporal model was used to examine the impact of spatial temperature on mortality. A time series model was used to assess the effects of single site’s temperature, and averaged temperature from 3 monitoring sites on mortality. Squared Pearson scaled residuals were used to check the model fit. The results of this study show that even though spatiotemporal models gave a better model fit than time series models, spatiotemporal and time series models gave similar effect estimates. Time series analyses using temperature recorded from a single monitoring site or average temperature of multiple sites were equally good at estimating the association between temperature and mortality as compared with a spatiotemporal model. A time series Poisson regression model was used to estimate the association between temperature change and mortality in summer in Brisbane, Australia during 1996–2004 and Los Angeles, United States during 1987–2000. Temperature change was calculated by the current day's mean temperature minus the previous day's mean. In Brisbane, a drop of more than 3 �C in temperature between days was associated with relative risks (RRs) of 1.16 (95% confidence interval (CI): 1.02, 1.31) for non-external mortality (NEM), 1.19 (95% CI: 1.00, 1.41) for NEM in females, and 1.44 (95% CI: 1.10, 1.89) for NEM aged 65.74 years. An increase of more than 3 �C was associated with RRs of 1.35 (95% CI: 1.03, 1.77) for cardiovascular mortality and 1.67 (95% CI: 1.15, 2.43) for people aged < 65 years. In Los Angeles, only a drop of more than 3 �C was significantly associated with RRs of 1.13 (95% CI: 1.05, 1.22) for total NEM, 1.25 (95% CI: 1.13, 1.39) for cardiovascular mortality, and 1.25 (95% CI: 1.14, 1.39) for people aged . 75 years. In both cities, there were joint effects of temperature change and mean temperature on NEM. A change in temperature of more than 3 �C, whether positive or negative, has an adverse impact on mortality even after controlling for mean temperature. I examined the variation in the effects of high temperatures on elderly mortality (age . 75 years) by year, city and region for 83 large US cities between 1987 and 2000. High temperature days were defined as two or more consecutive days with temperatures above the 90th percentile for each city during each warm season (May 1 to September 30). The mortality risk for high temperatures was decomposed into: a "main effect" due to high temperatures using a distributed lag non-linear function, and an "added effect" due to consecutive high temperature days. I pooled yearly effects across regions and overall effects at both regional and national levels. The effects of high temperature (both main and added effects) on elderly mortality varied greatly by year, city and region. The years with higher heat-related mortality were often followed by those with relatively lower mortality. Understanding this variability in the effects of high temperatures is important for the development of heat-warning systems. In conclusion, this thesis makes contribution in several aspects. Case-crossover design was combined with distribute lag non-linear model to assess the effects of temperature on mortality in Tianjin. This makes the case-crossover design flexibly estimate the non-linear and delayed effects of temperature. Both extreme cold and high temperatures increased the risk of mortality in Tianjin. Time series model using single site’s temperature or averaged temperature from some sites can be used to examine the effects of temperature on mortality. Temperature change (no matter significant temperature drop or great temperature increase) increases the risk of mortality. The high temperature effect on mortality is highly variable from year to year.

Board age and gender diversity : a test of competing linear and curvilinear predictions

The inconsistent findings of past board diversity research demand a test of competing linear and curvilinear diversity–performance predictions. This research focuses on board age and gender diversity, and presents a positive linear prediction based on resource dependence theory, a negative linear prediction based on social identity theory, and an inverted U-shaped curvilinear prediction based on the integration of resource dependence theory with social identity theory. The predictions were tested using archival data on 288 large organizations listed on the Australian Securities Exchange, with a 1-year time lag between diversity (age and gender) and performance (employee productivity and return on assets). The results indicate a positive linear relationship between gender diversity and employee productivity, a negative linear relationship between age diversity and return on assets, and an inverted U-shaped curvilinear relationship between age diversity and return on assets. The findings provide additional evidence on the business case for board gender diversity and refine the business case for board age diversity.

The health effects of temperature : current estimates, future projections, and adaptation strategies

Climate change is expected to be one of the biggest global health threats in the 21st century. In response to changes in climate and associated extreme events, public health adaptation has become imperative. This thesis examined several key issues in this emerging research field. The thesis aimed to identify the climate-health (particularly temperature-health) relationships, then develop quantitative models that can be used to project future health impacts of climate change, and therefore help formulate adaptation strategies for dealing with climate-related health risks and reducing vulnerability. The research questions addressed by this thesis were: (1) What are the barriers to public health adaptation to climate change? What are the research priorities in this emerging field? (2) What models and frameworks can be used to project future temperature-related mortality under different climate change scenarios? (3) What is the actual burden of temperature-related mortality? What are the impacts of climate change on future burden of disease? and (4) Can we develop public health adaptation strategies to manage the health effects of temperature in response to climate change? Using a literature review, I discussed how public health organisations should implement and manage the process of planned adaptation. This review showed that public health adaptation can operate at two levels: building adaptive capacity and implementing adaptation actions. However, there are constraints and barriers to adaptation arising from uncertainty, cost, technologic limits, institutional arrangements, deficits of social capital, and individual perception of risks. The opportunities for planning and implementing public health adaptation are reliant on effective strategies to overcome likely barriers. I proposed that high priorities should be given to multidisciplinary research on the assessment of potential health effects of climate change, projections of future health impacts under different climate and socio-economic scenarios, identification of health cobenefits of climate change policies, and evaluation of cost-effective public health adaptation options. Heat-related mortality is the most direct and highly-significant potential climate change impact on human health. I thus conducted a systematic review of research and methods for projecting future heat-related mortality under different climate change scenarios. The review showed that climate change is likely to result in a substantial increase in heatrelated mortality. Projecting heat-related mortality requires understanding of historical temperature-mortality relationships, and consideration of future changes in climate, population and acclimatisation. Further research is needed to provide a stronger theoretical framework for mortality projections, including a better understanding of socioeconomic development, adaptation strategies, land-use patterns, air pollution and mortality displacement. Most previous studies were designed to examine temperature-related excess deaths or mortality risks. However, if most temperature-related deaths occur in the very elderly who had only a short life expectancy, then the burden of temperature on mortality would have less public health importance. To guide policy decisions and resource allocation, it is desirable to know the actual burden of temperature-related mortality. To achieve this, I used years of life lost to provide a new measure of health effects of temperature. I conducted a time-series analysis to estimate years of life lost associated with changes in season and temperature in Brisbane, Australia. I also projected the future temperaturerelated years of life lost attributable to climate change. This study showed that the association between temperature and years of life lost was U-shaped, with increased years of life lost on cold and hot days. The temperature-related years of life lost will worsen greatly if future climate change goes beyond a 2 °C increase and without any adaptation to higher temperatures. The excess mortality during prolonged extreme temperatures is often greater than the predicted using smoothed temperature-mortality association. This is because sustained period of extreme temperatures produce an extra effect beyond that predicted by daily temperatures. To better estimate the burden of extreme temperatures, I estimated their effects on years of life lost due to cardiovascular disease using data from Brisbane, Australia. The results showed that the association between daily mean temperature and years of life lost due to cardiovascular disease was U-shaped, with the lowest years of life lost at 24 °C (the 75th percentile of daily mean temperature in Brisbane), rising progressively as temperatures become hotter or colder. There were significant added effects of heat waves, but no added effects of cold spells. Finally, public health adaptation to hot weather is necessary and pressing. I discussed how to manage the health effects of temperature, especially with the context of climate change. Strategies to minimise the health effects of high temperatures and climate change can fall into two categories: reducing the heat exposure and managing the health effects of high temperatures. However, policy decisions need information on specific adaptations, together with their expected costs and benefits. Therefore, more research is needed to evaluate cost-effective adaptation options. In summary, this thesis adds to the large body of literature on the impacts of temperature and climate change on human health. It improves our understanding of the temperaturehealth relationship, and how this relationship will change as temperatures increase. Although the research is limited to one city, which restricts the generalisability of the findings, the methods and approaches developed in this thesis will be useful to other researchers studying temperature-health relationships and climate change impacts. The results may be helpful for decision-makers who develop public health adaptation strategies to minimise the health effects of extreme temperatures and climate change.

A Lagrangian approach to nonlinear modeling of anti-roll tanks

This paper presents two novel nonlinear models of u-shaped anti-roll tanks for ships, and their linearizations. In addition, a third simplified nonlinear model is presented. The models are derived using Lagrangian mechanics. This formulation not only simplifies the modeling process, but also allows one to obtain models that satisfy energy-related physical properties. The proposed nonlinear models and their linearizations are validated using model-scale experimental data. Unlike other models in the literature, the nonlinear models in this paper are valid for large roll amplitudes. Even at moderate roll angles, the nonlinear models have three orders of magnitude lower mean square error relative to experimental data than the linear models.

Time pressure and coworker support mediate the curvilinear relationship between age and occupational well-being

As the proportion of older employees in the workforce is growing, researchers have become increasingly interested in the association between age and occupational well-being. The curvilinear nature of relationships between age and job satisfaction and between age and emotional exhaustion is well-established in the literature, with employees in their late 20s to early 40s generally reporting lower levels of occupational well-being than younger and older employees. However, the mechanisms underlying these curvilinear relationships are so far not well understood due to a lack of studies testing mediation effects. Based on an integration of role theory and research from the adult development and career literatures, this study examined time pressure, work–home conflict, and coworker support as mediators of the relationships between age and job satisfaction and between age and emotional exhaustion. Data came from 771 employees between 17 and 74 years of age in the construction industry. Results showed that employees in their late 20s to early 40s had lower job satisfaction and higher emotional exhaustion than younger and older employees. Time pressure and coworker support fully mediated both the U-shaped relationship between age and job satisfaction and the inversely U-shaped relationship between age and emotional exhaustion. These findings suggest that organizational interventions may help increase the relatively low levels of occupational well-being in certain age groups.

Corporate Environmental and Economic Performance of Japanese Manufacturing Firms: Empirical Study for Sustainable Development

This study examines the relationship between environmental performance and economic performance in Japanese manufacturing firms. The environmental performance indicators include CO2 emissions and the aggregate toxic risk associated with chemical emissions relative to sales. Return on assets (ROA) is used as an indicator of economic performance. We demonstrate that there is a significant inverted U-shaped relationship between ROA and environmental performance calculated by aggregated toxic risk. We also find that the environmental performance increases ROA through both returns on sales and improved capital turnover. However, we observe a significant positive relationship between financial performance and environmental performance based on CO2 emissions. These findings may provide evidence for the consequences of firms' environmental behavior and sustainable development. © 2012 John Wiley & Sons, Ltd and ERP Environment.