Tolerance of Uncertainty: Links to Happenstance,Career Decision Self‐Efficacy,and Career Satisfaction

This study investigated the extent to which tolerance of uncertainty affects the relationship between happenstance skills and career satisfaction via career decision self‐efficacy. Moderated mediation analysis was conducted on data collected from 321 graduates (175 men, 146 women) of Korean universities making the school‐to‐work transition. Results showed that career decision self‐efficacy fully mediated the relationship between happenstance skills and career satisfaction. Furthermore, the moderation effect of tolerance of uncertainty had a significant impact on the relationship between happenstance skills and career decision self‐efficacy. Tolerance of uncertainty should be considered an important variable in happenstance career theory and intervention. Unplanned influences should also be considered important factors in the career decision‐making process.     

Leadership research and cognitive neuroscience: The state of this union

Advances in cognitive neuroscience and other approaches to understanding human behavior from a biological standpoint are only now beginning to filter into leadership research. The purpose of this introduction to the Leadership Quarterly Special Issue on the Biology of Leadership is to outline the organizational cognitive neuroscience approach to leadership research, and show how such an approach can fruitfully inform both leadership and neuroscientific research. Indeed, we advance the view that the further application of cognitive neuroscientific techniques to leadership research will pay great dividends in our understanding of effective leadership behaviors and as such, a future symbiosis between the two fields is a necessity.     

Decomposition of Changes in Korean Wage Inequality, 1998–2007

South Korea experienced a steep increase in wage inequality between the Asian financial crisis in 1997 and the global financial crisis in 2008. This paper investigates the causes of the sharp change during that time period by looking at the contributions of changes in the distributions of schooling and unionization. The effects are estimated applying two robust distributional function based decomposition methods on Korean Labor and Panel Survey data for the time period 1998–2007. The results suggest changes in the distribution of schooling can explain about 10 % of the changes in the 90/50 percentile wage gap. The declining unionization rate does not have much impact on the upward trend of Korean wage inequality. In addition, aggregate decomposition results suggest that changes in labor force composition can explain a significant proportion of the total wage changes in the upper-tail of the distribution. Based on our findings we provide a list of policy recommendations to address the wage inequality issue in Korea.     

Data envelopment analysis in the presence of measurement error: case study from the National Database of Nursing Quality Indicators® (NDNQI®)

Data envelopment analysis (DEA) is the most commonly used approach for evaluating healthcare efficiency [B. Hollingsworth, The measurement of efficiency and productivity of health care delivery. Health Economics 17(10) (2008), pp. 1107–1128], but a long-standing concern is that DEA assumes that data are measured without error. This is quite unlikely, and DEA and other efficiency analysis techniques may yield biased efficiency estimates if it is not realized [B.J. Gajewski, R. Lee, M. Bott, U. Piamjariyakul, and R.L. Taunton, On estimating the distribution of data envelopment analysis efficiency scores: an application to nursing homes’ care planning process. Journal of Applied Statistics 36(9) (2009), pp. 933–944; J. Ruggiero, Data envelopment analysis with stochastic data. Journal of the Operational Research Society 55 (2004), pp. 1008–1012]. We propose to address measurement error systematically using a Bayesian method (Bayesian DEA). We will apply Bayesian DEA to data from the National Database of Nursing Quality Indicators^® to estimate nursing units’ efficiency. Several external reliability studies inform the posterior distribution of the measurement error on the DEA variables. We will discuss the case of generalizing the approach to situations where an external reliability study is not feasible.     

A new stratified three-stage unrelated randomized response model for estimating a rare sensitive attribute based on the Poisson distribution

This article suggests an efficient method of estimating a rare sensitive attribute which is assumed following Poisson distribution by using three-stage unrelated randomized response model instead of the Land et al. model (2011 Land, M., S. Singh, and S. A. Sedory. 2011. Estimation of a rare sensitive attribute using poisson distribution. Statistics 46 (3):351–60. doi:10.1080/02331888.2010.524300.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) when the population consists of some different sized clusters and clusters selected by probability proportional to size(:pps) sampling. A rare sensitive parameter is estimated by using pps sampling and equal probability two-stage sampling when the parameter of a rare unrelated attribute is assumed to be known and unknown.

We extend this method to the case of stratified population by applying stratified pps sampling and stratified equal probability two-stage sampling. An empirical study is carried out to show the efficiency of the two proposed methods when the parameter of a rare unrelated attribute is assumed to be known and unknown.     

Fitting competing risks data to bivariate Pareto models

This paper revisits two bivariate Pareto models for fitting competing risks data. The first model is the Frank copula model, and the second one is a bivariate Pareto model introduced by Sankaran and Nair (1993 Sankaran, P. G., and N. U. Nair. 1993. A bivariate Pareto model and its applications to reliability. Naval Research Logistics 40 (7):1013–1020. doi:10.1002/1520-6750(199312)40:7%3c1013::AID-NAV3220400711%3e3.0.CO;2-7.[Crossref], [Web of Science ®] , [Google Scholar]). We discuss the identifiability issues of these models and develop the maximum likelihood estimation procedures including their computational algorithms and model-diagnostic procedures. Simulations are conducted to examine the performance of the maximum likelihood estimation. Real data are analyzed for illustration.     

Identifying Changing Aviation Threat Environments Within an Adaptive Homeland Security Advisory System

A critical component of aviation security consists of screening passengers and baggage to protect airports and aircraft from terrorist threats. Advancements in screening device technology have increased the ability to detect these threats; however, specifying the operational configurations of these devices in response to changes in the threat environment can become difficult. This article proposes to use Fisher information as a statistical measure for detecting changes in the threat environment. The perceived risk of passengers, according to prescreening information and behavior analysis, is analyzed as the passengers sequentially enter the security checkpoint. The alarm responses from the devices used to detect threats are also analyzed to monitor significant changes in the frequency of threat items uncovered. The key results are that this information‐based measure can be used within the Homeland Security Advisory System to indicate changes in threat conditions in real time, and provide the flexibility of security screening detection devices to responsively and automatically adapt operational configurations to these changing threat conditions.     

How do I get my way? A meta-analytic review of research on influence tactics

Despite considerable research investigating the role of influence tactics on work-related outcomes in organizations, consensus on the effectiveness of influence tactics has been elusive. Specifically, there is a lack of integration concerning the relationships between proactive influence tactics and their outcomes. We investigate the effectiveness of 11 influence tactics from a comprehensive perspective using meta-analytic techniques. In particular, the current study focuses on relationships between each of the 11 influence tactics (i.e., rational persuasion, exchange, inspirational appeal, legitimating, apprising, pressure, collaboration, ingratiation, consultation, personal appeals, and coalition) and task- and relations-oriented outcomes. In addition, we investigate the moderating effects of the direction of influence tactics, measurement of influence tactics, singular influence tactic (versus use of a combination of influence tactics), independence of data sources, and study setting involved in the study. Regardless of task- and relations-oriented outcomes, based on 49 independent samples (N = 8987), our results show positive relationships between outcomes and rational persuasion, inspirational appeal, apprising, collaboration, ingratiation, consultation, and a negative relationship between pressure and outcomes. Rational persuasion is the only tactic which held stable positive relationships with both categories of outcomes regardless of moderating factors. Implications and directions for future research in the area of influence tactics are discussed.     

Never easy to say “sorry”: Exploring the interplay of crisis involvement,brand image,and message appeal in developing effective corporate apologies

This study examines how the interplay among crisis involvement, brand image, and message appeal impacts the effectiveness of an apology in the context of a corporate crisis. To determine apology effectiveness, a 2 (crisis involvement: high vs. low) × 2 (brand image: symbolic vs. functional) × 2 (message appeal type: emotional vs. informational) experimental design was employed. The results demonstrate that the three-way interaction is significant, especially in the low-crisis involvement condition. The study concludes with a discussion of theoretical and practical implications and directions for future research.