Testing How Management Matters in an Era of Government by Performance Management

Public administration finds itself in an era of government byperformance management, which is reflected in the widespreadassumption that management is a key determinant of performance,and that it is reasonable to expect managers to measurably improveorganizational effectiveness. This article joins a growing literaturein seeking to conceptualize and empirically test how externalenvironmental influences and internal management factors combineto create performance, relying on data from the 2002–2003National Administrative Studies Project (NASP-II) survey ofstate government health and human services officials. We categorizemanagerial efforts to facilitate organizational performanceas determined either through their interactions with the organizationalenvironment, or through employing workable levers to changeinternal organizational culture, structure, and technology.Among the external environmental variables we find that thesupport of elected officials and the influence of the publicand media have a positive impact on effectiveness. Among internalmanagement choices, the ability to create a developmental organizationalculture, establish a focus on results through goal clarity,and decentralize decision-making authority are all positivelyassociated with organizational effectiveness.     

Shared frailty model based on reversed hazard rate for left censored data

Frailty models are used in the survival analysis to account for the unobserved heterogeneity in the individual risks to disease and death. To analyze the bivariate data on related survival times (e.g., matched pairs experiments, twin or family data), the shared frailty models were suggested. In this article, we introduce the shared gamma frailty models with the reversed hazard rate. We develop the Bayesian estimation procedure using the Markov chain Monte Carlo (MCMC) technique to estimate the parameters involved in the model. We present a simulation study to compare the true values of the parameters with the estimated values. We apply the model to a real life bivariate survival dataset.     

Effect of a new selection procedure on adaptive estimation

Adaptive estimation of parameters of some failure time distributionsis considered. A new procedure named the F-procedure has beendeveloped for selecting an appropriate model out of two possible models by Pandey et.al. (1991). Applying this F-procedure adaptive estimatorsof parameters of exponential, Wei bull, inverse Gaussian (IG) and Wald failure time distributions have been proposed in this paper. Comparison of these estimators has been undertaken with MLE's of the respective parameters and with some previous adaptiveestimators by simulation of samples using the Monte Carlo method.Adaptive estimation of parameters of some failure time distributions is considered. A new procedure named the F-procedure has been developedfor selecting an appropriate model out of two possible models by Pandey et.al. (1991). Applying this F-procedure adaptive estimators of parameters of exponential, Wei bull, inverse Gaussian (IG) and Wald failure time distributions have been proposed in this paper. Comparison of these estimators has been undertaken with MLE's of the respective parameters and with some previous adaptive estimators by simulation of samples using the Monte Carlo method.     

Do Mission Statements Matter for Nonprofit Performance?

In this exploratory study, we examine whether organizational mission statement attributes make a difference to the performance of nonprofit performing arts organizations. We use text analysis to measure two semantic attributes—activity and commonality—of mission statements. We examine whether these attributes are associated with improved performance for the instrumental and expressive functions of nonprofit performing arts organizations. Our findings indicate that the mission statement attribute activity is associated with improved performance for both instrumental and expressive functions. Our analysis of nonfindings for the mission statement attribute commonality suggests that there is a need to develop and use content analysis tools tailored to nonprofit contexts.     

Correlated gamma frailty models for bivariate survival data

Frailty models are used in the survival analysis to account for the unobserved heterogeneity in individual risks to disease and death. To analyze the bivariate data on related survival times (e.g., matched pairs experiments, twin or family data) the shared frailty models were suggested. Shared frailty models are used despite their limitations. To overcome their disadvantages correlated frailty models may be used. In this article, we introduce the gamma correlated frailty models with two different baseline distributions namely, the generalized log logistic, and the generalized Weibull. We introduce the Bayesian estimation procedure using Markov chain Monte Carlo (MCMC) technique to estimate the parameters involved in these models. We present a simulation study to compare the true values of the parameters with the estimated values. Also we apply these models to a real life bivariate survival dataset related to the kidney infection data and a better model is suggested for the data.     

Knowledge sharing for innovation performance improvement in micro/SMEs: an insight from the creative sector

Abstract

As economies become more reliant on innovative, knowledge-intensive firms, understanding the interaction between knowledge and improving innovation performance is increasingly important. Although most UK businesses are micro, small or medium-sized enterprises (micro/SMEs), knowledge management research has tended to focus on large companies Knowledge sharing can be critical for innovation performance, especially for smaller players with limited resources. Our study presents an insight from micro/SMEs operating in the highly knowledge-intensive and innovative games/entertainment software development sector. Using a mixed method approach, we investigate knowledge sharing and its contribution to firm innovation performance improvements. Our findings suggest that micro/SMEs are at the forefront of the creative sector precisely because of their smaller size. Our study reveals evidence of knowledge donation but limited evidence of knowledge collection in the knowledge sharing process. We develop a model highlighting the importance of industry context, individual knowledge and organizational size in knowledge sharing for innovation performance.     

Sociocultural Contexts of Time to First Sex Among Hispanic Adolescents

This investigation examines the sociocultural influences on risk of first sex among a representative sample of Hispanic (primarily of Mexican origin) teens living in Los Angeles County. Teen acculturation (measured as language of interview) moderates the effects of gender on risk of sex, with less acculturated teens exhibiting the greatest gender difference. Teens living with both biological parents have significantly lower risk of sex and the effect of family acculturation (measured as generational status) operates through teens' language of interview. Neither measure of parent‐youth relationship (socioemotional support, parental control) is significant. Hispanic teens living in low‐density Hispanic neighborhoods have significantly higher risk of sex than do teens living in neighborhoods with higher levels of ambient hazards. The results highlight the importance of characterizing sociocultural influences at multiple levels of aggregation.     

Nonparametric bayes estimation of the survival function from a record of failures and follow-ups

In some observational studies, we have random censoring model. However, the data available may be partially observable censored data consisting of the observed failure times and only those nonfailure times which are subject to follow-up. Suzuki (1985) discussed the problem of nonparametric estimation of the survival function from such partially observable censored data. In this article, we derive a nonparametric Bayes estimator of the survival function for such data of failures and follow-ups under a Dirichlet process prior and squared error loss. The limiting properties such as the mean square consistency, weak convergence and strong consistency of the Bayes estimator are studied. Finally, the procedures developed are illustrated by means of an example.     

Gamma shared frailty model based on reversed hazard rate

Abstract

Frailty models are used in survival analysis to account for unobserved heterogeneity in individual risks to disease and death. To analyze bivariate data on related survival times (e.g., matched pairs experiments, twin, or family data), shared frailty models were suggested. Shared frailty models are frequently used to model heterogeneity in survival analysis. The most common shared frailty model is a model in which hazard function is a product of random factor(frailty) and baseline hazard function which is common to all individuals. There are certain assumptions about the baseline distribution and distribution of frailty. In this paper, we introduce shared gamma frailty models with reversed hazard rate. We introduce Bayesian estimation procedure using Markov Chain Monte Carlo (MCMC) technique to estimate the parameters involved in the model. We present a simulation study to compare the true values of the parameters with the estimated values. Also, we apply the proposed model to the Australian twin data set.