Moderators of Career Calling and Job-Search Behaviors Among Unemployed Individuals

We examined the relationship between calling, job-search clarity, and job-search intensity in a cross-sectional study of Italian unemployed job seekers (N = 315). Structural equation modeling with observed variables and latent moderated structural equation models were adopted to test whether optimism, self-esteem, and perseverance moderate the relation between calling, job-search clarity, and job-search intensity. Perceiving a calling was positively related with job-search clarity and intensity, and these relations were stronger in individuals with lower levels of optimism, self-esteem, and perseverance. This study suggests that perceiving a calling is an important personal resource that is related to a clearer job-search goal and to more intense job-search activities and can support job seekers in personal adverse conditions. These results suggest integrating job-search behaviors in the work-as-calling theory and that incorporating the construct of calling into career counselors' practices may increase the efficacy of job-search activities.     

Household dynamics and fuelwood consumption in developing countries: a cross-national analysis

Previous research has suggested a link between household dynamics (i.e., average household size and number of households) and environmental impacts at the national level. Building on this work, we empirically test the relationship between household dynamics and fuelwood consumption, which has been implicated in anthropogenic threats to biodiversity. We focus our analysis on developing countries (where fuelwood is an important energy source). Our results show that nations with smaller average households consume more fuelwood per capita. This finding indicates that the household economies of scale are, indeed, associated with the consumption of fuelwood. In addition, we found that number of households is a better predictor of total fuelwood consumption than average household size suggesting a greater relative contribution to consumption levels. Thus, insofar as declining average household sizes result in increased number of households and higher per capita consumption, this trend may be a signal of serious threats to biodiversity and resource conservation. We also found further support for the ??energy ladder?? hypothesis that economic development reduces demand for traditional fuels.     

The percentile residual life up to time t0: Ordering and aging properties

Motivated by practical issues, a new stochastic order for random variables is introduced by comparing all their percentile residual life functions until a certain instant. Some interpretations of these stochastic orders are given, and various properties of them are derived. The relationships to other stochastic orders are studied and also an application in reliability theory is described. Finally, we present some characterization results of the decreasing percentile residual life up to time t₀ aging notion.     

Inferring gene regulatory networks by an order independent algorithm using incomplete data sets

Analyzing incomplete data for inferring the structure of gene regulatory networks (GRNs) is a challenging task in bioinformatic. Bayesian network can be successfully used in this field. k-nearest neighbor, singular value decomposition (SVD)-based and multiple imputation by chained equations are three fundamental imputation methods to deal with missing values. Path consistency (PC) algorithm based on conditional mutual information (PCA–CMI) is a famous algorithm for inferring GRNs. This algorithm needs the data set to be complete. However, the problem is that PCA–CMI is not a stable algorithm and when applied on permuted gene orders, different networks are obtained. We propose an order independent algorithm, PCA–CMI–OI, for inferring GRNs. After imputation of missing data, the performances of PCA–CMI and PCA–CMI–OI are compared. Results show that networks constructed from data imputed by the SVD-based method and PCA–CMI–OI algorithm outperform other imputation methods and PCA–CMI. An undirected or partially directed network is resulted by PC-based algorithms. Mutual information test (MIT) score, which can deal with discrete data, is one of the famous methods for directing the edges of resulted networks. We also propose a new score, ConMIT, which is appropriate for analyzing continuous data. Results shows that the precision of directing the edges of skeleton is improved by applying the ConMIT score.     

Simulation analysis of cold chain performance based on time–temperature data

Perishable goods are a fundamental source of revenue for the retail sector; their management, however, constitutes a severe challenge for retailers and supply chain partners. A significant cost in particular is the fraction of products perished through the supply chain, which also constitutes an ethical and environmental concern. Supply chain organisation and operative characteristics have a significant influence on this matter, as in fact ensuring suitable temperature conditions for the stock-keeping units throughout the supply chain is mandatory for perishable products. Recent developments in sensing and communication technologies allow detailed monitoring and control of cold chain; however, depending on the characteristics of the supply chain, an inherent risk of perished products is often inevitable, even in the hypothesis of perfect control. This article proposes a methodology to evaluate the performance of a cold chain in terms of expected product quality at the retail store, and to estimate the expected fraction of perished products, according to the supply chain configuration. The approach is based on Monte Carlo simulation, and implements referenced shelf-life models. A real application is also presented, involving a preliminary analysis and mapping of the supply chain activities based on time–temperature data, in order to demonstrate the practicability of the approach proposed.     

Capability Approach and Multidimensional Well-Being: The Italian Case of BES

This paper lies within the debate on GDP and beyond and provides an empirical assessment of the Italian equitable and sustainable well-being (BES) as a composite measure of multidimensional well-being. From a policy perspective, the goal is to deliver a reading of the Italian BES able to shed light on its usability. The aim is to offer a suitable method for making the information included in the BES more viable for policy design. To this end, the paper is grounded in an interpretation of the Italian BES through the lens of the capability approach and investigates the relations among BES indicators and life domains. The empirical assessment uses Italian data from the national survey “Aspects of daily life” and applies the Structural Equation Model to estimate several life capabilities and their causal path. Outcomes show the interrelated nature of multi-dimensional well-being and prove the role of exogenous causes in the determination of capabilities. Moreover, the paper provides a final ranking analysis where Italian regions are compared based on their position per capability and income performance. Results confirm, on one hand, the disparity of income and well-being measurements and the importance of multidimensional assessment for human development and, on the other, the importance of focusing on the single components of multidimensional well-being and their interconnections.     

Maintenance of submersible pumps in the septic tanks: ergonomic and biological risks to the worker

In this study was observed the maintenance task of submersible pumps septic tanks installed in industrial bathrooms. This maintenance activity operators are exposed to various biological and ergonomic risks. This type of activity requires its great physical performers who are also subject to contact with human waste in the form of liquids, gases and solids. Besides the problems mentioned, are still exposed to high temperatures that can cause diseases such as hyperthermia or heatstroke. These aspects were observed using the ergonomic assessment methodology in order to suggest improvements that are reflected in productivity and employee satisfaction.     

Human factors identification and classification related to accidents'causality on hand injuries in the manufacturing industry

The causes of occupational accidents from the perspective of human factors have been a subject which has received little attention into the field of scientific research. The aim of this research was to identify and classify the human factors that influence human errors and failures that cause accidents and injuries specifically on hands. Available studies related to the topic have been developed mainly for aerospace applications and are found insufficient to explain accidents causalities in the manufacturing industry. This research was developed in the assembly industry of automotive harnesses and was conducted following a mixed Cognitive Anthropological approach. This study was developed in two phases. During the first qualitative phase, participants freely listed their knowledge to identify elements of the cultural domain, then and in the second phase they performed the successive pile sort technique for the collection data to classify elements in the cultural domain. Statistical models like Cluster Analysis and Multidimensional Scaling were applied for results' validation purposes. As results, 70 different human factors were identified and in the second phase they were classified into 4 main categories which were: human error, unsafe conditions, individual factors, and organizational factors. Statistical methods validated these results.     

Employment status and education/employment relationship of PhD graduates from the University of Ferrara

Two sample surveys of Post-Docs were planned and carried out at the University of Ferrara in 2004 and 2007 aimed at determining the professional status of Post-Docs, the relationship between their PhD education and employment, and their satisfaction with certain aspects of the education and research program. As part of these surveys, two methodological contributions were developed. The first concerns an extension of the non-parametric combination of dependent rankings to construct a synthesis of composite indicators measuring satisfaction with particular aspects of PhD programs [R. Arboretti Giancristofaro and L. Salmaso, Global ranking indicators with application to the evaluation of PhD programs, Atti del Convegno “Valutazione e Customer Satisfaction per la Qualità dei Servizi”, Roma, 8–9 Settembre 2005, pp. 19–22; R. Arboretti Giancristofaro, S. Bonnini, and L. Salmaso, A performance indicator for multivariate data, Quad. Stat. 9 (2007), pp. 1–29; R. Arboretti Giancristofaro, F. Pesarin, and L. Salmaso, Nonparametric approaches for multivariate testing with mixed variables and for ranking on ordered categorical variables with an application to the evaluation of PhD programs, in Real Data Analysis, S. Sawilowsky, ed., a volume in Quantitative Methods in Education and the Behavioral Sciences: Issues, Research and Teaching, Ronald C. Serlin, series ed., Information Age Publishing, Charlotte, North Carolina, 2007, pp. 355–385]. The procedure was applied to highlight differences in the interviewed Post-Docs’ multivariate satisfaction profiles in relation to two aspects: education/employment relationship; employment expectations; and opportunities. The second consists of an inferential procedure providing a solution to the problem of hypothesis testing, where the objective is to compare the heterogeneity of two populations on the basis of sampling data [G.R. Arboretti, S. Bonnini, and F. Pesarin, A permutation approach for testing heterogeneity in two-sample categorical variables, Stat. Comput. (2009) doi: 10.1007/S11222-008-9085-8.]. The procedure was applied to compare the degrees of heterogeneity of Post-Doc judgments in the two surveys with regard to the adequacy of the PhD education for the work carried out.