The Influence of Hospitality Leaders’ Relational Transparency on Followers’ Trust and Deviance Behaviors: Mediating Role of Behavioral Integrity

This paper investigates the effect of leader\u27s relational transparency on follower organizational deviance through followers’ perception of leader\u27s behavioral integrity and their trust in leader. Multi-level modeling results from a multisource survey-based field-study with 24 hospitality student project teams (N = 149) show that behavioral integrity mediates the relationship between leader\u27s relational transparency and follower\u27s trust in leader. Furthermore, multi-level path analysis suggests that leader\u27s relational transparency, a team-level construct, exerts a cross-level effect on follower\u27s organizational deviance through the mediating roles of behavioral integrity and follower\u27s trust in leader. The study has yielded theoretical and practical implications that are useful for hospitality leaders. © 201

Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction

Longitudinal analysis is important in many disciplines, such as the study of behavioral transitions in social science. Only very recently, feature selection has drawn adequate attention in the context of longitudinal modeling. Standard techniques, such as generalized estimating equations, have been modified to select features by imposing sparsity-inducing regularizers. However, they do not explicitly model how a dependent variable relies on features measured at proximal time points. Recent graphical Granger modeling can select features in lagged time points but ignores the temporal correlations within an individual's repeated measurements. We propose an approach to automatically and simultaneously determine both the relevant features and the relevant temporal points that impact the current outcome of the dependent variable. Meanwhile, the proposed model takes into account the non-{\em i.i.d} nature of the data by estimating the within-individual correlations. This approach decomposes model parameters into a summation of two components and imposes separate block-wise LASSO penalties to each component when building a linear model in terms of the past $\tau$ measurements of features. One component is used to select features whereas the other is used to select temporal contingent points. An accelerated gradient descent algorithm is developed to efficiently solve the related optimization problem with detailed convergence analysis and asymptotic analysis. Computational results on both synthetic and real world problems demonstrate the superior performance of the proposed approach over existing techniques.Comment: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 201

Species traits and the form of individual species–energy relationships

Environmental energy availability explains much of the spatial variation in species richness at regional scales. While numerous mechanisms that may drive such total species–energy relationships have been identified, knowledge of their relative contributions is scant. Here, we adopt a novel approach to identify these drivers that exploits the composite nature of species richness, i.e. its summation from individual species distributions. We construct individual species–energy relationships (ISERs) for each species in the British breeding avifauna using both solar (temperature) and productive energy metrics (normalized difference vegetation index) as measures of environmental energy availability. We use the slopes of these relationships and the resultant change in deviance, relative to a null model, as measures of their strength and use them as response variables in multiple regressions that use ecological traits as predictors. The commonest species exhibit the strongest ISERs, which is counter to the prediction derived from the more individuals hypothesis. There is no evidence that predatory species have stronger ISERs, which is incompatible with the suggestion that high levels of energy availability increase the length of the food chain allowing larger numbers of predators to exist. We find some evidence that species with narrow niche breadths have stronger ISERs, thus providing one of the few pieces of supportive evidence that high-energy availability promotes species richness by increasing the occurrence of specialist species that use a narrow range of resources

Modeling hierarchical relationships in epidemiological studies: a Bayesian networks approach

Hierarchical relationships between risk factors are seldom taken into account in epidemiological studies though some authors stressed the importance of doing so, and proposed a conceptual framework in which each level of the hierarchy is modeled separately. The objective of this paper was to implement a simple version of their framework, and to propose an alternative procedure based on a Bayesian Network (BN). These approaches were illustrated in modeling the risk of diarrhea infection for 2740 children aged 0 to 59 months in Cameroon. The authors implemented a (naïve) logistic regression, a step-level logistic regression and also a BN. While the first approach is inadequate, the two others approaches both account for the hierarchical structure but to different estimates and interpretations. BN implementation showed that a child in a family in the poorest group has respectively 89%, 40% and 18% probabilities of having poor sanitation, being malnourished and having diarrhea. An advantage of the latter approach is that it enables one to determine the probability that a risk factor (and/or the outcome) is in a given state, given the states of the others. Although the BN considered here is very simple, the method can deal with more complicated models.Bayesian networks; hierarchical model; diarrhea infection; disease determinants; logistic regression

Agent causation as a solution to the problem of action

My primary aim is to defend a nonreductive solution to the problem of action. I argue that when you are performing an overt bodily action, you are playing an irreducible causal role in bringing about, sustaining, and controlling the movements of your body, a causal role best understood as an instance of agent causation. Thus, the solution that I defend employs a notion of agent causation, though emphatically not in defence of an account of free will, as most theories of agent causation are. Rather, I argue that the notion of agent causation introduced here best explains how it is that you are making your body move during an action, thereby providing a satisfactory solution to the problem of action

Theories of developmental dyslexia: Insights from a multiple case study of dyslexic adults

A multiple case study was conducted in order to assess three leading theories of developmental dyslexia: the phonological, the magnocellular (auditory and visual) and the cerebellar theories. Sixteen dyslexic and 16 control university students were administered a full battery of psychometric, phonological, auditory, visual and cerebellar tests. Individual data reveal that all 16 dyslexics suffer from a phonological deficit, 10 from an auditory deficit, 4 from a motor deficit, and 2 from a visual magnocellular deficit. Results suggest that a phonological deficit can appear in the absence of any other sensory or motor disorder, and is sufficient to cause a literacy impairment, as demonstrated by 5 of the dyslexics. Auditory disorders, when present, aggravate the phonological deficit, hence the literacy impairment. However, auditory deficits cannot be characterised simply as rapid auditory processing problems, as would be predicted by the magnocellular theory. Nor are they restricted to speech. Contrary to the cerebellar theory, we find little support for the notion that motor impairments, when found, have a cerebellar origin, or reflect an automaticity deficit. Overall, the present data support the phonological theory of dyslexia, while acknowledging the presence of additional sensory and motor disorders in certain individuals