Leadership,creativity, and innovation: A critical review and practical recommendations

Leadership is a key predictor of employee, team, and organizational creativity and innovation. Research in this area holds great promise for the development of intriguing theory and impactful policy implications, but only if empirical studies are conducted rigorously. In the current paper, we report a comprehensive review of a large number of empirical studies (N?=?195) exploring leadership and workplace creativity and innovation. Using this article cache, we conducted a number of systematic analyses and built narrative arguments documenting observed trends in five areas. First, we review and offer improved definitions of creativity and innovation. Second, we conduct a systematic review of the main effects of leadership upon creativity and innovation and the variables assumed to moderate these effects. Third, we conduct a systematic review of mediating variables. Fourth, we examine whether the study designs commonly employed are suitable to estimate the causal models central to the field. Fifth, we conduct a critical review of the creativity and innovation measures used, noting that most are sub-optimal. Within these sections, we present a number of taxonomies that organize extant research, highlight understudied areas, and serve as a guide for future variable selection. We conclude by highlighting key suggestions for future research that we hope will reorient the field and improve the rigour of future research such that we can build more reliable and useful theories and policy recommendations.     

Learning How and Learning What: Effects of Tacit and Codified Knowledge on Performance Improvement Following Technology Adoption

This paper examines effects of tacit and codified knowledge on performance improvement as organizations gain experience with a new technology. We draw from knowledge management and learning curve research to predict improvement rate heterogeneity across organizations. We first note that the same technology can present opportunities for improvement along more than one dimension, such as efficiency and breadth of use. We compare improvement for two dimensions: one in which the acquisition of codified knowledge leads to improvement and another in which improvement requires tacit knowledge. We hypothesize that improvement rates across organizations will be more heterogeneous for dimensions of performance that rely on tacit knowledge than for those that rely on codified knowledge (H1), and that group membership stability predicts improvement rates for dimensions relying on tacit knowledge (H2). We further hypothesize that when performance relies on codified knowledge, later adopters should improve more quickly than earlier adopters (H3). All three hypotheses are supported in a study of 15 hospitals learning to use a new surgical technology. Implications for theory and practice are discussed.     

Statistical inference and visualization in scale-space for spatially dependent images

SiZer (SIgnificant ZERo crossing of the derivatives) is a graphical scale-space visualization tool that allows for statistical inferences. In this paper we develop a spatial SiZer for finding significant features and conducting goodness-of-fit tests for spatially dependent images. The spatial SiZer utilizes a family of kernel estimates of the image and provides not only exploratory data analysis but also statistical inference with spatial correlation taken into account. It is also capable of comparing the observed image with a specific null model being tested by adjusting the statistical inference using an assumed covariance structure. Pixel locations having statistically significant differences between the image and a given null model are highlighted by arrows. The spatial SiZer is compared with the existing independent SiZer via the analysis of simulated data with and without signal on both planar and spherical domains. We apply the spatial SiZer method to the decadal temperature change over some regions of the Earth.     

Non-ignorable missing covariate data in survival analysis: a case-study of an International Breast Cancer Study Group trial

Summary.  Non-ignorable missing data, a serious problem in both clinical trials and observational studies, can lead to biased inferences. Quality-of-life measures have become increasingly popular in clinical trials. However, these measures are often incompletely observed, and investigators may suspect that missing quality-of-life data are likely to be non-ignorable. Although several recent references have addressed missing covariates in survival analysis, they all required the assumption that missingness is at random or that all covariates are discrete. We present a method for estimating the parameters in the Cox proportional hazards model when missing covariates may be non-ignorable and continuous or discrete. Our method is useful in reducing the bias and improving efficiency in the presence of missing data. The methodology clearly specifies assumptions about the missing data mechanism and, through sensitivity analysis, helps investigators to understand the potential effect of missing data on study results.     

Blessed assurance: Religion, anxiety, and tranquility among US adults

A growing body of research investigates the possible relationships between religion and mental health. After developing a series of arguments linking various aspects of religion with anxiety and tranquility, we test relevant hypotheses using data from the 1996 General Social Survey. Results show that frequency of religious attendance and the belief in an afterlife are inversely associated with feelings of anxiety and positively associated with feelings of tranquility. However, frequency of prayer has no direct association with either outcome. Strong beliefs in the pervasiveness of sin are positively linked with anxiety but unrelated to tranquility. Finally, belief in an afterlife and frequency of prayer buffer the adverse effects of poor health and financial decline on anxiety. Implications of these findings are discussed along with study limitations and promising directions for future research.     

Determinants of sexual arousal and accuracy of its self-estimation in sexually functional males

Men with and without sexual dysfunction present with varying patterns of agreement between subjective estimates of sexual arousal and more objective psychophysiological measures of the same construct. This relative accuracy seems to be associated with sexual function, with men who have sexual dysfunction presenting less accurate estimations (mostly reporting below measured arousal levels). The purpose of this study is to clarify the processes underlying sexual arousal and the accuracy of its self-estimation. We looked at potential predictors of sexual arousal (subjective and physiological) and accuracy in estimating objective sexual arousal in a sample of 60 sexually functional males. Predictors included pre-existing sexual attitudes (erotophobia), both trait and state positive and negative affect, self-focused attention, and interoceptive awareness. Results indicate that this sexually functional sample generally reported below their own erection level. Interestingly, trait negative affect was associated with somewhat lower levels of subjective arousal and higher levels of physiological arousal. On the other hand, state positive affect facilitated both subjective and objective arousal and increased somewhat the accuracy of estimates of erectile responding. Pre-existing sexual attitudes as well as variations in self-focused attention and interoceptive awareness evidenced little effect on sexual arousal or the accuracy of its estimation.     

Child welfare privatization: quantitative indicators and policy issues

The purpose of this study was to demonstrate the development of safety, permanency, and child well-being indicators by using administrative data sets as well as by using these indicators as tools for evaluating Florida's Community-Based Care (CBC) initiative. Longitudinal data from 37 counties including 4 counties that implemented community-based care were examined in this study. The results of the study indicated that the overall performance of CBC counties is at least as good as the performance of their comparison run by the state counties. The findings that emerged from this study may provide important lessons for developing a performance measurement system in the child welfare field.     

An attribution model of public discrimination towards persons with mental illness

In this study, we build on previous work by developing and estimating a model of the relationships between causal attributions (e.g., controllability, responsibility), familiarity with mental illness, dangerousness, emotional responses (e.g., pity, anger, fear), and helping and rejecting responses. Using survey data containing responses to hypothetical vignettes, we examine these relationships in a sample of 518 community college students. Consistent with attribution theory, causal attributions affect beliefs about persons' responsibility for causing their condition, beliefs which in turn lead to affective reactions, resulting in rejecting responses such as avoidance, coercion, segregation, and withholding help. However, consistent with a danger appraisal hypothesis, the effects of perceptions of dangerousness on helping and rejecting responses are unmediated by responsibility beliefs. Much of the dangerousness effects operate by increasing fear, a particularly strong predictor of support for coercive treatment. The results from this study also suggest that familiarity with mental illness reduces discriminatory responses.