Inequality in digital skills and the adoption of online safety behaviors

ABSTRACT

Cyber-safety behaviors are important in preventing the loss of an individual's digital assets and ensuring the safety of important daily online activities. Individuals’ cyber-safety is also critical for national cybersecurity. The issue is highly relevant for Israel, a country that relies on the digital capabilities of its workers for its major technology industries and is also often a target of cyberwarfare and cybercrime attacks. The purpose of this study is to identify the determinants of cyber-safety behavior. We investigate the role of age, gender and education in the use of safety-related digital skills and antivirus software. Using a 2014 survey of a national sample of Internet users in Israel (N?=?1850), we found that age, gender, education and quality of access are associated with the level of users’ digital security skills. In addition, these skills and the frequency of conducting financial activities online are the main determinants of antivirus behaviors. Our results expand the understanding of cyber-safety by showing that social and digital disparities are reproduced in the use of measures to prevent online threats, putting the digitally disadvantaged at greater risk of becoming victims of online threats.     

Your work may be killing you! Workaholism,sleep problems and cardiovascular risk

This study tests the relationships between workaholism (i.e. working excessively and compulsively), sleep problems and cardiovascular risk in 537 employees from five Spanish hospitals. Four types of worker (i.e. workaholics, positive workers, compulsive workers and hard workers) were distinguished, and their health indicators were compared. The results showed that workaholics experienced significantly more sleep problems (i.e. morning tiredness, sleeping while driving and sleeping fewer hours both on weekdays and at weekends, with poorer quality), had higher relative risk scores, and consumed more caffeine and alcohol than the other patterns of worker (positive, compulsive and hard workers). Further analyses revealed that sleep problems fully mediated the relationship between workaholism (i.e. working excessively and compulsively) and cardiovascular risk. The study emphasizes the fact that being a workaholic might be a significant risk factor for having sleep problems and cardiovascular disease.     

Success factors of management consulting

Management consulting as a service has become part of almost every medium to big company’s daily business. Despite management consulting’s high practical relevance the scientific discussion of this discipline is relatively young and needs to advance. Notably, there is little empirical research that focuses on the conceptualization and operationalization of management consulting’s success factors from a client perspective. Therefore, in this article we theoretically conceptualize and subsequently operationalize critical success factors of management consulting. Also, we examine those factors’ particular impact on management consulting success. Based on a survey of 255 companies and structural equation modeling, we show that six out of seven theoretically derived success factors have a significant positive effect on management consulting success. In particular, Consultant Expertise, Intensity of Collaboration and Common Vision have a strong impact on the performance of management consulting.     

ASSESSING SOCIAL COSTS OF INEFFICIENT PROCUREMENT DESIGN

This paper considers the social costs implied by inefficient allocation of contracts in a first‐price, sealed‐bid procurement auction with asymmetric bidders. We adopt a constrained (piecewise linear) strategy equilibrium concept and estimate the structural parameters of the bidders' distribution of costs. We estimate social costs defined as the predicted cost difference between the winning firm and the most efficient bidding firm. We also compare the expected procurement costs under two different auction formats. The data is collected from procurement auctions of road painting in Sweden during 1993–1999. The results indicate that the social costs of inefficient contract allocation is about 2% of total potential production cost and that an efficient second‐price auction would lower the expected procurement cost by 2.5%. (JEL: D44, H57, C15)     

Robust Nonparametric Confidence Intervals for Regression‐Discontinuity Designs

In the regression‐discontinuity (RD) design, units are assigned to treatment based on whether their value of an observed covariate exceeds a known cutoff. In this design, local polynomial estimators are now routinely employed to construct confidence intervals for treatment effects. The performance of these confidence intervals in applications, however, may be seriously hampered by their sensitivity to the specific bandwidth employed. Available bandwidth selectors typically yield a “large” bandwidth, leading to data‐driven confidence intervals that may be biased, with empirical coverage well below their nominal target. We propose new theory‐based, more robust confidence interval estimators for average treatment effects at the cutoff in sharp RD, sharp kink RD, fuzzy RD, and fuzzy kink RD designs. Our proposed confidence intervals are constructed using a bias‐corrected RD estimator together with a novel standard error estimator. For practical implementation, we discuss mean squared error optimal bandwidths, which are by construction not valid for conventional confidence intervals but are valid with our robust approach, and consistent standard error estimators based on our new variance formulas. In a special case of practical interest, our procedure amounts to running a quadratic instead of a linear local regression. More generally, our results give a formal justification to simple inference procedures based on increasing the order of the local polynomial estimator employed. We find in a simulation study that our confidence intervals exhibit close‐to‐correct empirical coverage and good empirical interval length on average, remarkably improving upon the alternatives available in the literature. All results are readily available in R and STATA using our companion software packages described in Calonico, Cattaneo, and Titiunik (2014d, 2014b).     

‘The Castaways of Life’: A study of organizational remembering within the context of a Chilean Geriatric Hospital

This paper explores the phenomenon of organizational memory within the context of a Chilean Geriatric Hospital that has undergone profound institutional transformations during the last 40 years. The effects of such transformations have reinforced an emphasis on progress at the expense of remembering and integrating the past of the institution as a hospice. The study reveals that this institutional past reverberates in the hospital's working dynamics, which contributes to generating confusion in collective identity, as well as to affect the accomplishment of primary tasks and people's well-being. Access to organizational memory is carried out by the registration of some members' remembering practices about the hospital's past, which are analysed through a hermeneutic method. The study is ethnographic and interpretative, and the recollection of data combines interviews, methods of observation, and the revision of documents.     

Properties of the stochastic approximation EM algorithm with mini-batch sampling

Statistics and Computing - To deal with very large datasets a mini-batch version of the Monte Carlo Markov Chain Stochastic Approximation Expectation–Maximization algorithm for general latent...     

Parameter identifiability in a class of random graph mixture models

We prove identifiability of parameters for a broad class of random graph mixture models. These models are characterized by a partition of the set of graph nodes into latent (unobservable) groups. The connectivities between nodes are independent random variables when conditioned on the groups of the nodes being connected. In the binary random graph case, in which edges are either present or absent, these models are known as stochastic blockmodels and have been widely used in the social sciences and, more recently, in biology. Their generalizations to weighted random graphs, either in parametric or non-parametric form, are also of interest. Despite these many applications, the parameter identifiability issue for such models has only been touched upon in the literature. We give here a thorough investigation of this problem. Our work also has consequences for parameter estimation. In particular, the estimation procedure proposed by Frank and Harary for binary affiliation models is revisited in this article.     

Nonparametric geometric outlier detection

Outlier detection is a major topic in robust statistics due to the high practical significance of anomalous observations. Many existing methods, however, either are parametric or cease to perform well when the data are far from linearly structured. In this paper, we propose a quantity, Delaunay outlyingness, that is a nonparametric outlyingness score applicable to data with complicated structure. The approach is based on a well‐known triangulation of the sample, which seems to reflect the sparsity of the pointset to different directions in a useful way. We derive results on the asymptotic behavior of Delaunay outlyingness in case of a sufficiently simple set of observations. Simulations and an application to empirical data are also discussed.