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Performance Variables (performance + variable)
Selected AbstractsDeterminants of compensation: A study of pay, performance, and gender differences for fundraising professionalsNONPROFIT MANAGEMENT & LEADERSHIP, Issue 4 2008Debra J. Mesch This study examines the determinants of compensation for fundraising professionals by addressing the following research questions: (1) Is there a significant pay-performance relationship? (2) What are the factors that affect bonus and salary? (3) Is there a gender-pay gap for individuals who are in the role of fundraisers? Data were collected over a four-year period from a national sample of fundraising professionals employed across all industry classifications. Amount of money raised was the primary performance variable of interest. Bivariate tests for differences between males and females, as well as two-stage simultaneous regressions, were used to determine the effects of fundraising performance on the pay of fundraisers. Results indicated a significant and positive pay-performance linkage across all fundraising positions, particularly for chief development officers, as well as a consistent gender-pay gap across fundraising positions. [source] A Microbial Biosensor for p -Nitrophenol Using Arthrobacter Sp.ELECTROANALYSIS, Issue 14 2003Yu Lei Abstract This article reports the construction, optimization of performance variables and analytical characterization of a sensitive and selective microbial amperometric biosensor for measurement of p -nitrophenol (PNP), a U.S. Environmental Agency priority pollutant. The biosensor consisted of PNP-degrading/oxidizing bacteria Arthrobacter sp. JS443 as biological sensing element and a dissolved oxygen electrode as the transducer. The best sensitivity and response time were obtained using a sensor constructed with 1.2,mg dry wt. of cells and operating in pH,7.5, 50,mM citrate-phosphate buffer. Using these conditions, the biosensor was able to measure as low as 28,ppb (0.2,,M) of PNP selectively without interference from structurally similar compounds, such as phenol, nitrophenols and chlorophenols. The service life of the microbial biosensor is around 5,days when stored in the operating buffer at 4,°C. The applicability to lake water is demonstrated. [source] Financial performance and the long-term link with HR practices, work climate and job stressHUMAN RESOURCE MANAGEMENT JOURNAL, Issue 4 2005Marc van Veldhoven Using data front a large financial services organisation in the Netherlands, this article reports a longitudinal study at the business unit level. The study addresses the question of which longitudinal relations exist between survey data on perceived HR practices, work climate and job stress on the one hand, and prospective and retrospective financial performance on the other. Data from 223 business units were available for this study. Eight scales were selected from an employee survey answered by 18,142 respondents. These were aggregated to mean scores at the business unit level. Financial performance is operationalised by a yearly profits-to-costs ratio. Correcting for employee and business unit characteristics, the eight survey scales predict 22 per cent of the variance in business unit financial performance in the year after the survey.,Co-operation between departments' appears to be the most important predictor. Equally strong evidence was friund for a reverse causation sequence: business unit financial performance in the year before the survey was a significant predictor for four out of eight survey scales, especially for ,co-operation between departments' and ,job security'. The results underline the importance of studying variance in HR and performance variables within large organisatiuns, and the possibilities of using employee surveys in this research context. Limitations and implications of the findings are discussed. [source] A dynamic mathematical model of a shell-and-tube evaporator. validation with pure and blend refrigerantsINTERNATIONAL JOURNAL OF ENERGY RESEARCH, Issue 3 2007R. Llopis Abstract This work presents a mathematical model of a shell-and-tube evaporator based on mass continuity, energy conservation and heat transfer physical fundamentals. The model is formulated as a control volume combination that represents the different refrigerant states along the evaporator. Since the model is based on refrigerant and secondary fluid states prediction, it can be easily adapted for modelling any type of evaporator. The strategy of working with physical fundamentals allows the steady- and dynamic-state analysis of any of its performance variables. The paper presents a steady-state validation made with two pure refrigerants (HCFC-22, HFC-134a) and with a zeotropic blend (HFC-407C), and a dynamic validation with transient experimental tests using HCFC-22. The model prediction error is lower than 5% and it is well in accordance with actual dynamic behaviour. Copyright © 2006 John Wiley & Sons, Ltd. [source] Branch Network and Modular Service Optimization for Community BankingINTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, Issue 5 2002G. Ioannou In the information society, what is clearly changing is the role and image of bank branches in order to satsify in a more efficient way customers' needs. This paper develops an integrated approach to assist the bank's management in reconfiguring a branch network according to the dictates of the market. We are seeking the optimum number of branches and the optimum mix of services that each branch should offer in order to maximize the revenue,generating measures of the branches within a community. The problem is modeled using a linear program that accounts for community performance as a function of performance variables that are explained by a set of external and internal factors, which reflect community characteristics and modular branch banking parameters, respectively. The relationships between factor and performance variables are identified using regression analysis. An iterative algorithm allows convergence to a solution that provides the best configuration of branches after all possible branch mergers and modular branch adjustments are accomplished. [source] Frailty in Older Mexican AmericansJOURNAL OF AMERICAN GERIATRICS SOCIETY, Issue 9 2005Kenneth J. Ottenbacher PhD Objectives: To identify sociodemographic characteristics and health performance variables associated with frailty in older Mexican Americans. Design: A prospective population-based survey. Setting: Homes of older adults living in the southwest. Participants: Six hundred twenty-one noninstitutionalized Mexican-American men and women aged 70 and older included in the Hispanic Established Populations for Epidemiologic Study of the Elderly participated in a home-based interview. Measurements: Interviews included information on sociodemographics, self-reports of medical conditions (arthritis, diabetes mellitus, heart attack, hip fracture, cancer, and stroke) and functional status. Weight and measures of lower and upper extremity muscle strength were obtained along with information on activities of daily living and instrumental activities of daily living. A summary measure of frailty was created based on weight loss, exhaustion, grip strength, and walking speed. Multivariable linear regression identified variables associated with frailty at baseline. Logistic regression examined variables predicting frailty at 1-year follow-up. Results: Sex was associated with frailty at baseline (F=4.28, P=.03). Predictors of frailty in men included upper extremity strength, disability (activities of daily living), comorbidities, and mental status scores (Nagelkerke coefficient of determination (R2)=0.37). Predictors for women included lower extremity strength, disability (activities of daily living), and body mass index (Nagelkerke R2=0.29). At 1-year follow-up, 83% of men and 79% of women were correctly classified as frail. Conclusion: Different variables were identified as statistically significant predictors of frailty in Mexican-American men and women aged 70 and older. The prevention, development, and treatment of frailty in older Mexican Americans may require consideration of the unique characteristics of this population. [source] Managing innovative R&D teamsR & D MANAGEMENT, Issue 3 2003Hans J. Thamhain Successful R&D groups not only generate innovative ideas, but also transfers these newly created concepts through the organizational system for economic gain. While innovation is not a random process, managers often argue that R&D performance is hard to measure and even more difficult to manage. An exploratory field study into technology-oriented R&D environments determines the principle factors that influence innovation-based performance of R&D teams. The results identify specific barriers and drivers to innovative team performance and provide insight into the type of an organizational environment and managerial leadership that is conducive to innovative R&D team performance. The data further suggest that many of the performance variables have their locus outside the R&D organization. Yet, managerial leadership style, both at the R&D team level and at senior management, has significant impact on creativity that ultimately affects R&D performance. [source] Corporate Governance and Performance: The REIT EffectREAL ESTATE ECONOMICS, Issue 1 2010Rob Bauer Real estate investment trusts (REITs) offer a natural experiment in corporate governance due to the fact that they leave little free cash flow for management, which reduces agency problems. We exploit a unique and leading corporate governance database to test whether corporate governance matters for the performance of U.S. REITs. We document for a sample including governance ratings of more than 220 REITs that firm value is significantly related to firm-level governance for REITs with low payout ratios only. Repeating the analysis with the complete database that includes more than 5,000 companies and a control sample of firms with high corporate real estate ratios, we find a strong and significantly positive relation between our governance index and several performance variables, indicating that the partial lack of a relation between governance and performance in the real estate sector might be explained by a REIT effect. [source] Process modeling and optimization of industrial ethylene oxide reactor by integrating support vector regression and genetic algorithmTHE CANADIAN JOURNAL OF CHEMICAL ENGINEERING, Issue 1 2009Sandip Kumar Lahiri Abstract This article presents an artificial intelligence-based process modeling and optimization strategies, namely support vector regression,genetic algorithm (SVR-GA) for modeling and optimization of catalytic industrial ethylene oxide (EO) reactor. In the SVR-GA approach, an SVR model is constructed for correlating process data comprising values of operating and performance variables. Next, model inputs describing process operating variables are optimized using Genetic Algorithm (GAs) with a view to maximize the process performance. The GA possesses certain unique advantages over the commonly used gradient-based deterministic optimization algorithms The SVR-GA is a new strategy for chemical process modeling and optimization. The major advantage of the strategies is that modeling and optimization can be conducted exclusively from the historic process data wherein the detailed knowledge of process phenomenology (reaction mechanism, kinetics, etc.) is not required. Using SVR-GA strategy, a number of sets of optimized operating conditions leading to maximized EO production and catalyst selectivity were obtained. The optimized solutions when verified in actual plant resulted in a significant improvement in the EO production rate and catalyst selectivity. On présente dans cet article des stratégies de modélisation et d'optimisation de procédés reposant sur l'intelligence artificielle, à savoir la méthode basée sur la régression des vecteurs de soutien et l'algorithme génétique (SVR-GA) pour la modélisation et l'optimisation du réacteur d'oxyde d'éthylène (EO) industriel catalytique. Dans la méthode SVR-GA, un modèle de régression des vecteurs de soutien est mis au point pour corréler les données de procédé comprenant les valeurs des variables de fonctionnement et de performance. Par la suite, les données d'entrée du modèle décrivant les variables de fonctionnement du procédé sont optimisées à l'aide de l'algorithme génétique (GA) dans l'optique de maximiser la performance du procédé. Le GA possède certains avantages uniques par rapport aux algorithmes d'optimisation déterministes basés sur les gradients communément utilisés. La SVR-GA est une nouvelle stratégie pour la modélisation et l'optimisation des procédés. Le principal avantage de ces stratégies est que la modélisation et l'optimisation peuvent être menées exclusivement à partir des données de procédés historiques, et il n'est pas nécessaire de connaître en détail la phénoménologie des procédés (mécanisme de réaction, cinétique, etc.). À l'aide de la stratégie SVR-GA, plusieurs séries de conditions opératoires optimisées conduisant à une production d'EO et une sélectivité de catalyseur maximisées ont été obtenues. Les solutions optimisées vérifiées en installations réelles permettent une amélioration significative du taux de production d'EO et de la sélectivité du catalyseur. [source] Traits, neighbors, and species performance in prairie restorationAPPLIED VEGETATION SCIENCE, Issue 3 2010R.E. Roberts Abstract Questions: Are traits related to the performance of plant species in restoration? Are the relationships between traits and performance consistent across the functional groups of annual forbs, perennial forbs and grasses? Do the relationships between traits and performance depend on neighboring functional groups? Location: A former agricultural field, being restored to native upland prairie, in the Willamette Valley of western Oregon, USA. Methods: Twenty-eight native species, representing three functional groups, were sown in seven different combinations. Eleven functional traits were measured from plants in the laboratory and in the field. Correlations between individual traits and performance variables were measured and regression techniques used to determine which sets of traits were most strongly related to performance. Results: Sets of traits explained up to 56% of variation in cover, and up to 48% of variation in establishment frequency. The relationships between traits and performance were influenced by functional group identity; the functional group identity of neighboring species also influenced species' cover and the relationships between traits and cover. Species' establishment rate in monoculture was the trait most strongly correlated to both establishment and cover in mixtures. In multi-trait models, annual forb functional group identity was strongly related to establishment in mixtures, and height, leaf weight ratio at 7 d and seed mass were strongly related to cover. Conclusions: Multiple-trait models should be a useful way of predicting the performance of species prior to sowing in restoration. The functional group identity of each species and the other species being sown may need to be taken into account when making predictions. [source] Application of Multivariate Data Analysis for Identification and Successful Resolution of a Root Cause for a Bioprocessing ApplicationBIOTECHNOLOGY PROGRESS, Issue 3 2008Alime Ozlem Kirdar Multivariate Data Analysis (MVDA) can be used for supporting key activities required for successful bioprocessing. These activities include process characterization, process scale-up, process monitoring, fault diagnosis and root cause analysis. This paper examines an application of MVDA towards root cause analysis for identifying scale-up differences and parameter interactions that adversely impact cell culture process performance. Multivariate data analysis and modeling were performed using data from small-scale (2 L), pilot-scale (2,000 L) and commercial-scale (15,000 L) batches. The input parameters examined included bioreactor pCO2, glucose, lactate, ammonium, raw materials and seed inocula. The output parameters included product attributes, product titer, viable cell density, cell viability and osmolality. Time course performance variables (daily, initial, peak and end point) were also evaluated. Application of MVDA as a diagnostic tool was successful in identifying the root cause and designing experimental conditions to demonstrate and correct it. Process parameters and their interactions that adversely impact cell culture performance and product attributes were successfully identified. MVDA was successfully used as an effective tool for collating process knowledge and increasing process understanding. [source] | |||||||||||||