Estimating large-scale general linear and seemingly unrelated regressions models after deleting observations

A new numerical method to solve the downdating problem (and variants thereof), namely removing the effect of some observations from the generalized least squares (GLS) estimator of the general linear model (GLM) after it has been estimated, is extensively investigated. It is verified that the solution of the downdated least squares problem can be obtained from the estimation of an equivalent GLM, where the original model is updated with the imaginary deleted observations. This updated GLM has a non positive definite dispersion matrix which comprises complex covariance values and it is proved herein to yield the same normal equations as the downdated model. Additionally, the problem of deleting observations from the seemingly unrelated regressions model is addressed, demonstrating the direct applicability of this method to other multivariate linear models. The algorithms which implement the novel downdating method utilize efficiently the previous computations from the estimation of the original model. As a result, the computational cost is significantly reduced. This shows the great usability potential of the downdating method in computationally intensive problems. The downdating algorithms have been applied to real and synthetic data to illustrate their efficiency.     

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.     

Making Professional Decisions in Research: Measurement and Key Predictors

The professional decision-making in research (PDR) measure was administered to 400 National Institutes of Health (NIH)-funded and industry-funded investigators, along with measures of cynicism, moral disengagement, compliance disengagement, impulsivity, work stressors, knowledge of responsible conduct of research (RCR), and socially desirable response tendencies. Negative associations were found for the PDR and measures of cynicism, moral disengagement, and compliance disengagement, while positive associations were found for the PDR and RCR knowledge and positive urgency, an impulsivity subscale. PDR scores were not related to socially desirable responding, or to measures of work stressors and the remaining impulsivity subscales. In a multivariate logistic regression analysis, lower moral disengagement scores, higher RCR knowledge, and identifying the United States as one’s nation of origin emerged as key predictors of stronger performance on the PDR. The implications of these findings for understanding the measurement of decision-making in research and future directions for research and RCR education are discussed.     

Female Perceptions of Organizational Justice

This study examines women's conceptualization of the pervasive construct of organizational justice. A comprehensive four factor model was used to represent organizational justice while outcome variables were the important employee attitudes of job satisfaction, organizational commitment and turnover intentions. Structural equation modelling was used to analyse responses from 301 male and 147 female respondents. Differences were found for procedural, interpersonal and informational justices. It would appear female and male employees have differing responses to perceptions of justice. Justice had a diffuse effect for males, but not for females. For men, interpersonal justice predicted an increase in organizational commitment while procedural justice predicted a decrease in turnover intentions. For female employees, informational justice was found to increase commitment and reduce turnover intentions. The study highlights the need for all justice factors to be considered and for sex differences to be considered in future justice research.