Firm-level training in local economic systems: Complementarities in production and firm innovation strategies

The paper presents a conceptual review over the main aspects concerning the role of human capital investments and training activities within production processes, followed by empirical evidence on two local economic systems in Northern Italy, based on recent survey data. Theoretical and empirical considerations are brought together in order to provide new insights on the role of training and the factors associated to training activities at firm level.The potential driving factors of training here analysed compounds structural characteristics, labour demand dynamics, human resource management practices, workforce features, and firm performances. We observe that training activities emerge positively associated with high-performance practices, innovative labour demand features, workforce skill level, firm size, and are affected by labour flexibility in various directions. Empirical evidence confirms most previous results but also adds further important insights. The analysis suggests that a widening gap, between few innovatively evolving and many stagnant firms, could characterise the future dynamics of the Region. The high relevance of structural variables, labour demand factors and HRM/innovation practices shows that regional industrial policies and labour policies should be jointly implemented for increasing potential firm productivity. This is a key concern for the current debate on local systems economic development in the European and Italian environment.     

SIMPCA: a framework for rotating and sparsifying principal components

We propose an algorithmic framework for computing sparse components from rotated principal components. This methodology, called SIMPCA, is useful to replace the unreliable practice of ignoring small coefficients of rotated components when interpreting them. The algorithm computes genuinely sparse components by projecting rotated principal components onto subsets of variables. The so simplified components are highly correlated with the corresponding components. By choosing different simplification strategies different sparse solutions can be obtained which can be used to compare alternative interpretations of the principal components. We give some examples of how effective simplified solutions can be achieved with SIMPCA using some publicly available data sets.     

Model selection in high-dimensional noisy data: a simulation study

In many practical applications, high-dimensional regression analyses have to take into account measurement error in the covariates. It is thus necessary to extend regularization methods, that can handle the situation where the number of covariates p largely exceed the sample size n, to the case in which covariates are also mismeasured. A variety of methods are available in this context, but many of them rely on knowledge about the measurement error and the structure of its covariance matrix. In this paper, we set the goal to compare some of these methods, focusing on situations relevant for practical applications. In particular, we will evaluate these methods in setups in which the measurement error distribution and dependence structure are not known and have to be estimated from data. Our focus is on variable selection, and the evaluation is based on extensive simulations.     

Abnormalising minorities. The state and expert knowledge addressing the Roma in Italy

This article expands the research on abnormalisation and the construction of social deviance of minorities. It focuses on the relationships between state practices, policies and expert knowledge addressing the Roma in Italy; it does so by first contextualising recent ethnographic findings on Turin authorities’ social inclusion practices addressing Roma within the history of national and regional policies for Roma; it then contextualises those policies within the history of expert knowledge about Roma. Unlike what other studies on abnormalisation suggest, we argue that the abnormalisation of Roma in Italy is not primarily predicated upon the idea that they are at present unfit to follow the norms of the majority; rather, it stays upon a historically rooted representation of Roma oscillating between the poles of potential re-educability and potential dangerousness. In the conclusion we encourage further comparative research on abnormalisation, especially including practices and knowledge addressing other European minorities such as the Jews.     

Underground testing: Name-altering practices as probes in electronic music

Name-altering practices are common in many creative fields—pen names in literature, stage names in the performing arts, and aliases in music. More than just reflecting artistic habits or responding to the need for distinctive brands, these practices can also serve as test devices to probe, validate, and guide the artists’ active participation in a cultural movement. At the same time, they constitute a powerful probe to negotiate the boundaries of a subculture, especially when its features are threatened by appropriation from the mass-oriented culture. Drawing evidence from electronic music, a field where name-altering practices proliferate, we outline dynamics of pseudonymity, polyonymy, and anonymity that surround the use of aliases. We argue that name-altering practices are both a tool that artists use to probe the creative environment and a device to recursively put one’s creative participation to the test. In the context of creative subcultures, name-altering practices constitute a subtle but effective form of underground testing.     

Psychophysical conditions and hormonal secretion in nurses on a rapidly rotating shift schedule and exposed to bright light during night work

The psychophysical conditions of 15 young female nurses, working in a rapidly-rotating shift system (2-2-2-2), modified according to some psychophysiological criteria, and exposed to short period (4 × 20 min) of bright light (2350 Lux) during their night duty, were studied in order to evaluate their adaptation to night work and to test a possible positive effect on it of bright light. Subjective evaluations of work load and psychophysical conditions, performance measures, hormonal excretion (cortisol, 6-sulphatoxymelatonin and catecholamines), oral temperature and activity-sleep logs were taken during the shiftwork cycle, comprising one morning, one afternoon and two consecutive nights under normal and bright light. The results showed that this rapidly-rotating shift system had little effect upon the normal circadian rhythms of the body. Moreover, the lengthening of the night shift to 10 h can be considered to be acceptable, provided that work load is reduced and there are sufficient rest pauses available. On the other hand, the reduction to 7 h of the length of the day shifts and delayed start of the morning shift to 07:00 h appeared to be convenient both in relation to the work load and sleep duration. Some positive effects of bright light upon psychophysical conditions and performance efficiency were noted, while hormonal excretion and body temperature did not show any effect of bright light; in particular, melatonin excretion was not suppressed appreciably by the bright light used.     

Psychophysical conditions of air traffic controllers evaluated by the standard shiftwork index

Abstract

In the ambit of a large epidemiological survey on the Italian population of air traffic controllers, an evaluation of their health conditions was carried out using the Standard Shiftwork Index (SSI). The study took into consideration 572 male air traffic controllers, aged between 23 and 59 years, of whom 301 were engaged in three large Regional Centres, 189 in thirteen Airport Towers and 82. formerly active controllers, were working in administrative offices. The former controllers showed worse health levels, in particular minor psychological disorders and chronic fatigue. Sixteen of them had been transferred to administrative jobs because of health impairment, owing to severe diseases of the nervous, gastrointestinal and cardiovascular systems. Such disorders, and musculoskeletal ones, were mostly reported by the active controllers. The controllers engaged in Regional Centres showed more sleep disturbances than those engaged in towers. Beside age, some personal characteristics appeared to influence health and well-being. Neuroticism was correlated with chronic fatigue, digestive and cardiovascular complaints, minor psychological disorders, cognitive and somatic anxiety. On the other hand, morningness was correlated negatively with sleep disturbances on morning shift, and positively with sleep duration both on morning shift and rest days.     

Computation of Sharp Bounds on the Expected Value of a Supermodular Function of Risks with Given Marginals

We show that the rearrangement algorithm (RA) introduced in Puccetti and Rüschendorf (2012 Puccetti, G., Rüschendorf, L. (2012). Computation of sharp bounds on the distribution of a function of dependent risks. Journal of Computational and Applied Mathematics 236(7):1833–1840.[Crossref], [Web of Science ®] , [Google Scholar]) to compute distributional bounds can be used also to compute sharp lower and upper bounds on the expected value of a supermodular function of d random variables having fixed marginal distributions. Compared to the analytical methods existing in the literature the algorithm is widely applicable, more easily obtained and gives insight into the dependence structures attaining the bounds.     

Dimensionality reduction approach to multivariate prediction

The authors consider dimensionality reduction methods used for prediction, such as reduced rank regression, principal component regression and partial least squares. They show how it is possible to obtain intermediate solutions by estimating simultaneously the latent variables for the predictors and for the responses. They obtain a continuum of solutions that goes from reduced rank regression to principal component regression via maximum likelihood and least squares estimation. Different solutions are compared using simulated and real data.