Trends in online media relations: Web-based corporate press rooms in leading international companies

An analysis of 120 corporate websites from Denmark, France, Germany, Norway, Singapore, Spain, the United Kingdom and the United States reveals, for the first time, international results about the implementation and use of virtual press rooms. This article shows the importance that large international companies attribute to Web-based media centers to achieve organizational objectives and to meet journalists’ demands for information and audiovisual resources. The study also shows, however, that most press rooms are far from being complete, efficient, easy-to-use, reliable and updated on a daily basis. In fact, there is not a single country from those analyzed that consistently stands out from the rest. In most of them, good results in certain areas coexist with significant shortcomings in others, resulting in some cases in poor press rooms that may not achieve the desired public relations objectives.     

Approximation of density functions by orthogonal series with grouped data

Summary Letg(x) andf(x) be continuous density function on (a, b) and let {ϕ_j} be a complete orthonormal sequence of functions onL ₂(g), which is the set of squared integrable functions weighted byg on (a, b). Suppose that over (a, b). Given a grouped sample of sizen fromf(x), the paper investigates the asymptotic properties of the restricted maximum likelihood estimator of density, obtained by setting all but the firstm of the ϑ_j’s equal to0. Practical suggestions are given for performing estimation via the use of Fourier and Legendre polynomial series. Research partially supported by: CNR grant, n. 93. 00837. CT10.     

The Effect of Joint Control Training on the Performance of Multiply Controlled Behavior: A Systematic Literature Review Relevant to Children With Autism Spectrum Disorder and Other Developmental Disabilities

Skinner (1957) differentiated the roles of the speaker and the listener in a verbal encounter. Although not extensively emphasized, Skinner suggested an individual often behaves verbally even when responding as a listener. Children diagnosed with autism spectrum disorders (ASD) often display the absence of important, and basic verbal repertoires that limit their ability to engage in a variety of social skills or problem-solving skills. Joint control suggests that multiply controlled verbal responding involves functional control of two 2 or more stimuli or verbal operants. This systematic literature review provides a summary of publications specifying the relation and implications of the analysis of joint control and joint control training in the acquisition of multiply controlled, non-speaker behaviors (e.g., selection-based behavior; , sequencing behavior). The synthesis suggests that joint control training presents as a promising analytic tool in guiding interventions to teach complex, multiply controlled verbal and non-verbal repertoires to children diagnosed with autism ASD and/or other developmental disabilities. Recommendations for future research in joint control, as well as the implementation of joint control training, are provided.

     

Testing for Serial Independence: Beyond the Portmanteau Approach

Portmanteau tests are typically used to test serial independence even if, by construction, they are generally powerful only in presence of pairwise dependence between lagged variables. In this article, we present a simple statistic defining a new serial independence test, which is able to detect more general forms of dependence. In particular, differently from the Portmanteau tests, the resulting test is powerful also under a dependent process characterized by pairwise independence. A diagram, based on p-values from the proposed test, is introduced to investigate serial dependence. Finally, the effectiveness of the proposal is evaluated in a simulation study and with an application on financial data. Both show that the new test, used in synergy with the existing ones, helps in the identification of the true data-generating process. Supplementary materials for this article are available online.     

Are there electoral cycles of emigration? An empirical investigation based on European data

Economic literature suggests that economic factors and the availability of amenities act as determinants of migration choices together with socio‐demographic factors. Migration has also been found to be the consequence of political instability. This article argues that specific political events, i.e., democratic elections, may be linked to migration flows. By using European data over the 1999‐2012 time period, our system GMM estimations reveal that there is an emigration political cycle across European democracies and across the young democracies of Central and Eastern European countries. We observe that regular elections tend to diminish emigration ratios, whereas endogenous elections have the opposite effect. These results suggest special challenges for governments and oppositions, which are also discussed.     

Data-driven stochastic inversion via functional quantization

In this paper, we propose a new methodology for solving stochastic inversion problems through computer experiments, the stochasticity being driven by a functional random variables. This study is motivated by an automotive application. In this context, the simulator code takes a double set of simulation inputs: deterministic control variables and functional uncertain variables. This framework is characterized by two features. The first one is the high computational cost of simulations. The second is that the probability distribution of the functional input is only known through a finite set of realizations. In our context, the inversion problem is formulated by considering the expectation over the functional random variable. We aim at solving this problem by evaluating the model on a design, whose adaptive construction combines the so-called stepwise uncertainty reduction methodology with a strategy for an efficient expectation estimation. Two greedy strategies are introduced to sequentially estimate the expectation over the functional uncertain variable by adaptively selecting curves from the initial set of realizations. Both of these strategies consider functional principal component analysis as a dimensionality reduction technique assuming that the realizations of the functional input are independent realizations of the same continuous stochastic process. The first strategy is based on a greedy approach for functional data-driven quantization, while the second one is linked to the notion of space-filling design. Functional PCA is used as an intermediate step. For each point of the design built in the reduced space, we select the corresponding curve from the sample of available curves, thus guaranteeing the robustness of the procedure to dimension reduction. The whole methodology is illustrated and calibrated on an analytical example. It is then applied on the automotive industrial test case where we aim at identifying the set of control parameters leading to meet the pollutant emission standards of a vehicle.