This article presents a theory of empathetic leadership and its initial test. Empathetic leadership provides a model of how leader understanding and support improves follower behaviors and affective states. For this article, we explored the link between empathetic leadership and follower performance. Specifically, we tested the causal processes by which empathetic language influences follower performance. These processes include follower job satisfaction and innovation. Findings support model hypotheses and provide preliminary causal support for the model.

The purpose of the current study was to extend organizational communication scholarship by examining the influence of culture on the use of motivating language by supervisors in Mexican organizations. Furthermore, the influence of motivating language on employees’ perceptions of their supervisors’ communication competence and their own job satisfaction and organizational commitment was examined. Participants included 158 full-time employees from a number of organizations located in Mexico. The current findings indicate that supervisors in organizations located in Mexico, tend to use direction-giving language most frequently followed by meaning-making language and empathetic language. Direction-giving language was also indicated as the greatest predictor of communication and organizational outcomes. A discussion of the current findings highlighting expectancy violations theory was also offered.

International trade, in particular exports and imports, are regarded as important factors that can increase the economic development of the Latin American and Caribbean (LAC) countries. However, little is known whether the ability of these countries to strengthen their global positions in trade can be affected by the pervasiveness of local corruption. The objective of this study is to analyze the impact of corruption on exports and imports in LAC countries. Our empirical results from the gravity model indicate that local corruption strongly reduces exports in the region. Thus, we conclude that LAC would be able to achieve more export growth if corruption in the region was effectively reduced.RESUMEN. Se considera que el comercio internacional, primordialmente el ramo de las exportaciones e importaciones, son factores importantes que pueden fomentar el desarrollo econo´mico de los paı´ses de Latinoame´rica y del Caribe (LAC). No obstante, existe una inco´gnita cuanto al grado en que la habilidad de estos paı´ses en fortalecer sus posiciones comerciales globales, pueda verse afectada por la omnipresente influencia de la corrupcio´n local. Este estudio tiene por objeto analizar el impacto que la corrupcio´n ejerce sobre las exportaciones e importaciones en los paı´ses de Latinoame´rica y el Caribe. El resultado empı´rico obtenido emana de un modelo de gravedad, que indica que la corrupcio´n local reduce drásticamente las exportaciones en la regio´n. Consecuentemente, llegamos a la conclusio´n de que dichos paı´ses podrı´an aumentar aún más sus exportaciones, si se llegase realmente a restringir la corrupcio´n en la regio´n.RESUMO. O come´rcio internacional, principalmente as importações e exportações, são vistas como fatores importantes capazes de intensificar o desenvolvimento econômico dos paı´ses da Ame´rica Latina e do Caribe (ALC). No entanto, pouco se sabe se a capacidade desses paı´ses no que tange o fortalecimento de suas posições globais no come´rcio pode ser afetada pela difusão da corrupção local. O objetivo do presente estudo e´analisar o impacto da corrupção nas importações e exportações dos paı´ses da ALC. Os nossos resultados empı´ricos derivados do modelo de gravidade indicam que a corrupção local reduz muito as exportações da região. Por isso, concluı´mos que a ALC conseguiria obter um maior crescimento das exportações se a corrupção na região fosse restringida com eficácia.

The most fundamental problem currently associated with structural equation modeling employing the partial least squares method is that it does not properly account for measurement error, which often leads to path coefficient estimates that asymptotically converge to values of lower magnitude than the true values. This attenuation phenomenon affects applications in the field of business data analytics; and is in fact a characteristic of composite-based models in general, where latent variables are modeled as exact linear combinations of their indicators. The underestimation is often of around 10% per path in models that meet generally accepted measurement quality assessment criteria. The authors propose a numeric solution to this problem, which they call the factor-based partial least squares regression (FPLSR) algorithm, whereby variation lost in composites is restored in proportion to measurement error and amount of attenuation. Six variations of the solution are developed based on different reliability measures, and contrasted in Monte Carlo simulations. The authors' solution is nonparametric and seems to perform generally well with small samples and severely non-normal data.

This study analyzes the competing roles of economic wealth and corruption on software piracy based on the supply-demand perspective. The study argues that even though greater economic wealth may encourage people to buy legal software instead of using pirated software, the ease of access to pirated copies in the open market as a result of corruption can have a stronger influence on the decision to use pirated software. The empirical results also reveal that while an increase in economic wealth can reduce software piracy, its effect tends to be moderated by the level of corruption in a country. These results indicate that a pricing strategy that makes software more affordable is not a sufficient policy for combating software piracy. Additional policies aimed at combating corruption should be implemented concomitantly for effective resolution of this problem.