Soccer Scores,Short-Term Mood and Fertility

European Journal of Population - Previous research has shown that seemingly irrelevant events such as unexpected outcomes in sporting events can affect mood and have relevant consequences for...     

Social and Economic Determinants of Reproductive Behavior Before the Fertility Decline. The Case of Six Italian Communities During the Nineteenth Century

In recent decades, main demographic historical research assessed the importance of bio-demographic components in human reproduction, before the diffusion of birth control and contraceptive techniques. According to this dominant view, before fertility decline, marital fertility was mainly regulated by biological and physiological factors and socio-economic factors played only a limited and indirect role. In order to demonstrate the importance of non-biological components, the present study focuses on six pre-transitional communities situated in different geographic areas of Italy. The work aims to demonstrate how fertility levels could significantly be affected by social and economic factors even in natural fertility populations, before the diffusion of contraceptives. Micro-level data are collected from several historical sources, and discrete-time event history models are applied to female reproductive careers in order to estimate effects of socio-economic status, household structure, and price fluctuations on marital fertility, controlling for several bio-demographic factors. Despite clear differences in geographic localization and environment, marital reproductive behavior appeared to be significantly and constantly affected by socio-economic status, household composition, and price levels in all the investigated communities.     

A finite mixture model for multivariate counts under endogenous selectivity

We describe a selection model for multivariate counts, where association between the primary outcomes and the endogenous selection source is modeled through outcome-specific latent effects which are assumed to be dependent across equations. Parametric specifications of this model already exist in the literature; in this paper, we show how model parameters can be estimated in a finite mixture context. This approach helps us to consider overdispersed counts, while allowing for multivariate association and endogeneity of the selection variable. In this context, attention is focused both on bias in estimated effects when exogeneity of selection (treatment) variable is assumed, as well as on consistent estimation of the association between the random effects in the primary and in the treatment effect models, when the latter is assumed endogeneous. The model behavior is investigated through a large scale simulation experiment. An empirical example on health care utilization data is provided.     

A New Perspective on Neonatal Smiling: Differences Between the Judgments of Expert Coders and Naive Observers

To better understand the form and recognizability of neonatal smiling, 32 newborns (14 girls; M = 25.6 hr) were videorecorded in the behavioral states of alertness, drowsiness, active sleep, and quiet sleep. Baby Facial Action Coding System coding of both lip corner raising (simple or non‐Duchenne) and lip corner raising with cheek raising (Duchenne smile) was followed by a smile recognition task using 48 naive observers. Both types of smiles were detected in all behavioral states. Lip corner raising with cheek raising (Duchenne smiling) tended to predominate in active (rapid eye movement) sleep, suggesting a potential tie to early constituents of emotion. A significant portion of the typically briefer lip corner raising distinguished by expert coders was not recognized as smiling by the naive observers. These briefer actions may represent a motor phenomenon idiosyncratic to the neonatal period.     

Variance component models for longitudinal count data with baseline information: epilepsy data revisited

Random effect models have often been used in longitudinal data analysis since they allow for association among repeated measurements due to unobserved heterogeneity. Various approaches have been proposed to extend mixed models for repeated count data to include dependence on baseline counts. Dependence between baseline counts and individual-specific random effects result in a complex form of the (conditional) likelihood. An approximate solution can be achieved ignoring this dependence, but this approach could result in biased parameter estimates and in wrong inferences. We propose a computationally feasible approach to overcome this problem, leaving the random effect distribution unspecified. In this context, we show how the EM algorithm for nonparametric maximum likelihood (NPML) can be extended to deal with dependence of repeated measures on baseline counts.     

Assessment of Organizational Trust: Italian Adaptation and Factorial Validity of the Organizational Trust Inventory

Trust influences interactions among individuals and organizations but has been an elusive concept to define and measure. The Organizational Trust Inventory (OTI) measures three dimensions of organizational trust, as defined by Cummings and Bromiley (in: Kramer and Tyler (eds) Trust in Organizations, 1996), believing or feeling that others: keep commitments, negotiate honestly, and do not take excessive advantage. This research presents an original adaptation of the OTI for the Italian people. It can now be used to evaluate trust regarding colleagues, managers, suppliers, subordinates, clients, and organizations. Using a sample of 490 employees and structural equation modeling, we consider the validity of the questionnaire and the theoretical model articulation both across different counterpart and countries. Besides, we develop a new reduced-form of the questionnaire (OTI/R), which offers better psychometric properties than the long form.     

Managing crowdsourced software testing: a case study based insight on the challenges of a crowdsourcing intermediary

Crowdsourcing has gained much attention in practice over the last years. Numerous companies have drawn on this concept for performing different tasks and value creation activities. Nevertheless, despite its popularity, there is still comparatively little well-founded knowledge on crowdsourcing, particularly with regard to crowdsourcing intermediaries. Crowdsourcing intermediaries play a key role in crowdsourcing initiatives as they assure the connection between the crowdsourcing companies and the crowd. However, the issue of how crowdsourcing intermediaries manage crowdsourcing initiatives and the associated challenges has not been addresses by research yet. We address these issues by conducting a case study with a German start-up crowdsourcing intermediary called testCloud that offers software testing services for companies intending to partly or fully outsource their testing activities to a certain crowd. The case study shows that testCloud faces three main challenges, these are: managing the process, managing the crowd and managing the technology. For each dimension, we outline mechanisms that testCloud applies for facing the challenges associated with crowdsourcing projects.     

Knowing,Power and Materiality: A Critical Review and Reconceptualization of Absorptive Capacity

Most studies on absorptive capacity (AC) are based on assumptions that are characteristic of viewing knowledge from an epistemology of possession (knowledge is possessed by individuals and is transferrable). However, the literature on managing knowledge (or better knowledge work) acknowledges also an epistemology of practice (knowledge is unpredictable and dynamic and constituted in and through practice). Moreover, the literature on AC is relatively silent on the relationship between knowledge and power. In this paper, the authors argue that the AC construct should be interpreted in light of the possession and the practice perspectives of knowledge and power. The analysis includes a systematic literature review of AC that supports the authors' claims and, based on this, they suggest an interpretation of the construct that takes into account knowledge–power relationships. This review and theorizing contribute to a richer and processual view of AC.     

Happiness in Italy: Translation,Factorial Structure and Norming of the Subjective Happiness Scale in a Large Community Sample

The Subjective Happiness Scale (SHS) is one of the most commonly used measures of happiness. Many translations and validation studies have been carried out in different countries and languages. The aim of the current paper was to investigate the psychometric properties of the Italian translation of the SHS and to provide normative data. The SHS was administered with life satisfaction items, anxiety and depression scales to a community sample of 993 participants, aged 18–85 years, living in different parts of Italy. Age and gender distributions were stratified according to the population pyramid. Confirmatory Factor Analysis supported the unidimensionality of the SHS, with acceptable fit indexes (NNFI = .96; CFI = .99; RMSEA = .08; 95 % C.I. [.04–.12]). Multi-group analyses supported total invariance of the SHS measurement model for males and females, and partial invariance for younger (i.e., 18–44 years old) and older (i.e., 45–85 years old) participants. Significant correlations with satisfaction items, anxiety and depression provided evidence for concurrent validity. These findings showed that the Italian SHS translation is a reliable and valid tool, which adds to existing translations and validation studies in different countries and languages.