Spatial Regression Models Using Inter-Region Distances in a Non-Random Context

This article considers spatial data z( s ₁), z( s ₂),…, z( s _n ) collected at n locations, with the objective of predicting z( s ₀) at another location. The usual method of analysis for this problem is kriging, but here we introduce a new signal-plus-noise model whose essential feature is the identification of hot spots. The signal decays in relation to distance from hot spots. We show that hot spots can be located with high accuracy and that the decay parameter can be estimated accurately. This new model compares well to kriging in simulations.     

Modelling of a thermomechanically coupled forming process based on functional outputs from a finite element analysis and from experimental measurements

In this paper, measurements from experiments and results of a finite element analysis (FEA) are combined in order to compute accurate empirical models for the temperature distribution before a thermomechanically coupled forming process. To accomplish this, Design and Analysis of Computer Experiments (DACE) is used to separately compute models for the measurements and the functional output of the FEA. Based on a hierarchical approach, a combined model of the process is computed. In this combined modelling approach, the model for the FEA is corrected by taking into account the systematic deviations from the experimental measurements. The large number of observations based on the functional output hinders the direct computation of the DACE models due to the internal inversion of the correlation matrix. Thus, different techniques for identifying a relevant subset of the observations are proposed. The application of the resulting procedure is presented, and a statistical validation of the empirical models is performed.     

Resolving Coparenting Dissatisfaction In Couples: A Preliminary Task Analysis Study

This study explored the change that unfolded when parents resolved their coparenting dissatisfaction during an Integrative Brief Systemic Intervention (IBSI) for parent couples. We conducted a task analysis (Greenberg, 2007) to build a model of resolving coparenting dissatisfaction. We compared a postulated model of change (rational model) based on theoretical and clinical assumptions to the observations of the actual change process that couples experienced in an IBSI (empirical analysis). The empirical analysis was conducted on six IBSI therapy cases (three exhibiting positive development and three exhibiting no development). We defined positive development in IBSI as moving from coparenting dissatisfaction to coparenting satisfaction. The final rational–empirical model included six steps that facilitated the resolution of coparenting dissatisfaction. This study contributes to deepening the knowledge of how coparenting may change during marital therapy.     

Always doing your best? Effort and performance in dynamic settings

Theory and Decision - Achieving an ambitious goal frequently requires succeeding in a sequence of intermediate tasks, some being critical for the final outcome, and others not. However, individuals...     

A data mining framework for targeted category promotions

This research presents a new approach to derive recommendations for segment-specific, targeted marketing campaigns on the product category level. The proposed methodological framework serves as a decision support tool for customer relationship managers or direct marketers to select attractive product categories for their target marketing efforts, such as segment-specific rewards in loyalty programs, cross-merchandising activities, targeted direct mailings, customized supplements in catalogues, or customized promotions. The proposed methodology requires customers’ multi-category purchase histories as input data and proceeds in a stepwise manner. It combines various data compression techniques and integrates an optimization approach which suggests candidate product categories for segment-specific targeted marketing such that cross-category spillover effects for non-promoted categories are maximized. To demonstrate the empirical performance of our proposed procedure, we examine the transactions from a real-world loyalty program of a major grocery retailer. A simple scenario-based analysis using promotion responsiveness reported in previous empirical studies and prior experience by domain experts suggests that targeted promotions might boost profitability between 15 % and 128 % relative to an undifferentiated standard campaign.     

Emotional labour profiles: Associations with key predictors and outcomes

ABSTRACT

The present study examines how three emotional labour strategies (hiding feelings, faking emotions, and deep acting) combine within different profiles of workers among two samples characterised by different types and intensity of customer contact. In addition, this research investigates the role of perceived workload as well as perceived organisational support, supervisor support, and colleagues support in the prediction of profile membership. Finally, this research also documents the relation between emotional labour profiles and adaptive and maladaptive work outcomes (job satisfaction, work performance, emotional exhaustion, sleeping problems, psychological detachment, and counterproductive work behaviours). Latent profile analysis revealed three similar emotional labour profiles in both samples. Results also showed the most desirable levels on all outcomes to be associated with Profile 3 (Low Emotional Labor/Low Surface Acting and Moderate Deep Acting), followed by Profile 2 (Moderate Emotional Labor/Moderate Surface Acting and High Deep Acting) and Profile 1 (High Emotional Labor), with most comparisons being statistically significant in both samples. In contrast, a more diversified pattern of findings was observed in the prediction of profile membership. For instance, perceived colleagues support did not predict membership into any of the profiles, while supervisor support predicted an increased likelihood of membership into Profile 3 relative to Profiles 1 and 2.     

Nonparametric Estimation of the Probability of Detection of Flaws in an Industrial Component,from Destructive and Nondestructive Testing Data,Using Approximate Bayesian Computation

We consider the problem of estimating the probability of detection (POD) of flaws in an industrial steel component. Modeled as an increasing function of the flaw height, the POD characterizes the detection process; it is also involved in the estimation of the flaw size distribution, a key input parameter of physical models describing the behavior of the steel component when submitted to extreme thermodynamic loads. Such models are used to assess the resistance of highly reliable systems whose failures are seldom observed in practice. We develop a Bayesian method to estimate the flaw size distribution and the POD function, using flaw height measures from periodic in‐service inspections conducted with an ultrasonic detection device, together with measures from destructive lab experiments. Our approach, based on approximate Bayesian computation (ABC) techniques, is applied to a real data set and compared to maximum likelihood estimation (MLE) and a more classical approach based on Markov Chain Monte Carlo (MCMC) techniques. In particular, we show that the parametric model describing the POD as the cumulative distribution function (cdf) of a log‐normal distribution, though often used in this context, can be invalidated by the data at hand. We propose an alternative nonparametric model, which assumes no predefined shape, and extend the ABC framework to this setting. Experimental results demonstrate the ability of this method to provide a flexible estimation of the POD function and describe its uncertainty accurately.     

Weather and Smiling Contagion: A Quasi Experiment with the Smiling Sunshine

Studies have shown that pleasant weather conditions (namely, sunshine) favor positive social relationships and improve moods. However, the effect of sunshine on one nonverbal expression that facilitates social relationships (namely, smiling) has never been studied. In a field experiment, men and women walking alone in the street were passed by a male or a female confederate who displayed a smile to the passersby. The contagion effect of smiling was measured. The study was carried out on days that were evaluated as being either sunny or cloudy, but precaution was taken to control the temperature and not to solicit participants when it rained. It was found that the display of a smile results in a smile more often on sunny days. The positive mood induced by the sun may explain such results.