Migrant women’s economic success in Russia: objective reality and subjective assessment

This study contributes to the growing body of literature on the outcomes of labour migration by focusing on the effects of migrant legal status on the economic and perceptual measures of migration success. To study the effects of legal status, we use a sample of Central Asian migrant women who work in Russia and of their native counterparts who occupy the same positions on the labour market. Similar to the studies in the developed settings, we find that a temporary legal status is associated with an earnings penalty and that permanent legal status corrects this earning disparity. We also find that both temporary and permanent migrant status is positively associated with perceptions of pay inequality but that, irrespective of these perceptions, both types of migrants are more likely to be satisfied with their jobs than natives. We interpret these findings within the legal and social context of migrant economic incorporation in Russia and relate them to the findings from other migrant-receiving settings.     

Immigration,opportunity, and assimilation in a technology economy

Theory and Society - We examine access to institutions and opportunity for entrepreneurs in a rising tech economy. A significant proportion of entrepreneurs and CEOs of tech firms in the American...     

Measuring servitization progress and outcome: the case of ‘advanced services’

The purpose of this paper is to establish a framework for assessing the progress and outcome of a manufacturer’s transformation towards becoming a provider of ‘advanced services’ – a complex bundling of products and services, whereby manufacturers offer capabilities and outcomes instead of products alone. ‘Advanced services’ represent the most complex offering in the current servitization trend amongst manufacturers. However, current performance measures lack the breadth and focus to assess progress or outcomes, and so support research and practice of organisational transformation efforts required. To address this gap the paper investigates how a manufacturer’s efforts to become an ‘advanced services’ provider can be comprehensively measured, and develops a framework for assessing the transformation journey towards becoming an ‘advanced services’ provider. The research method is based on (1) a systematic literature review process to create a comprehensive set of service-related performance measures that are available to assess a manufacturer’s servitization efforts, followed by (2) an engagement with an expert panel to synthesise the identified measures and create a set of ‘advanced services’ performance measures. The proposed framework is presented as a scorecard that can be used in practice to assess the progress and outcome of a manufacturer’s transformation towards becoming a provider of ‘advanced services’.     

Erratum to: Mapping the Regional Divide in Europe: A Measure for Assessing Quality of Government in 206 European Regions

Social Indicators Research -     

Bayesian estimation and case influence diagnostics for the zero-inflated negative binomial regression model

In recent years, there has been considerable interest in regression models based on zero-inflated distributions. These models are commonly encountered in many disciplines, such as medicine, public health, and environmental sciences, among others. The zero-inflated Poisson (ZIP) model has been typically considered for these types of problems. However, the ZIP model can fail if the non-zero counts are overdispersed in relation to the Poisson distribution, hence the zero-inflated negative binomial (ZINB) model may be more appropriate. In this paper, we present a Bayesian approach for fitting the ZINB regression model. This model considers that an observed zero may come from a point mass distribution at zero or from the negative binomial model. The likelihood function is utilized to compute not only some Bayesian model selection measures, but also to develop Bayesian case-deletion influence diagnostics based on q-divergence measures. The approach can be easily implemented using standard Bayesian software, such as WinBUGS. The performance of the proposed method is evaluated with a simulation study. Further, a real data set is analyzed, where we show that ZINB regression models seems to fit the data better than the Poisson counterpart.     

Safety Stock,Excess Capacity or Diversification: Trade‐Offs under Supply and Demand Uncertainty

Firms mitigate uncertainty in demand and supply by carrying safety stock, planning for excess capacity and diversifying supply sources. In this study, we provide a framework to jointly optimize these three levers in a periodic review infinite horizon setting, and in particular we examine how one can reduce inventory and capacity investments through proper diversification strategies. Observing that a modified base‐stock inventory policy is optimal, we find that the capacity‐diversification problem is well behaved and characterize the optimal mix of safety stock, excess capacity and extra number of supply sources. We find that higher supply uncertainty results in higher safety stock, more excess capacity, and higher diversification. But safety stock and diversification are non‐monotonic in demand uncertainty. Our results can be extended to situations in which suppliers are heterogeneous, and can be used to develop effective heuristics.     

Expediting youth's entry into employment whilst overlooking precariousness: Flexi‐employability and disciplinary activation in Hong Kong

With an emphasis placed on supply‐side interventions such as skills training and incentives enhancement, active labor market polices (ALMPs) are strongly promoted by international organizations and widely adopted across different welfare regimes to boost employment rates. This article first presents the under‐examined relationship between ALMPs and employment precariousness, which has posed a challenge to the neoliberal notion of employability and activation. Youth‐focused employment policies tend to speed up employment entry whilst downplaying the risk of precariousness and the importance of job quality, and thus further reinforcing the belief that engaging in precarious employment is tolerable if not inevitable. The article then examines the case of Hong Kong, which illustrates that its relatively low rate of youth unemployment may conceal the unfavorable employment conditions confronted by youth. It is argued that the service‐led employment policies and short‐term vocational training define the employability of young workers in terms of labor flexibilities. The coined phase of “flexi‐employability” is characterized by promoting youth's readiness for, and adaptability to, the volatilities and changing demands of the labor market. Arguably, the disciplinary approach to youth activation would only strengthen the work‐first principle by enforcing young people to take up jobs available and leave welfare as soon as possible, but without thoroughly addressing the risks and insecurities generated by the labor market in undermining their well‐being.     

Heterogeneity in treatment effects across diverse populations

Differences in patient characteristics, including age, sex, and race influence the safety and effectiveness of drugs, biologic products, and medical devices. Here we provide a summary of the topics discussed during the opening panel at the 2018 Johns Hopkins Center for Excellence in Regulatory Science and Innovation symposium on Assessing and Communicating Heterogeneity of Treatment Effects for Patient Subpopulations: Challenges and Opportunities. The goal of this session was to provide a brief overview of FDA-regulated therapeutics, including drugs, biologics and medical devices, and some of the major sources of heterogeneity of treatment effects (HTE) related to patient demographics, such as age, sex and race. The panel discussed the US Food and Drug Administration's role in reviewing and regulating drugs, devices, and biologic products and the challenges associated with ensuring that diverse patient populations benefit from these therapeutics. Ultimately, ensuring diverse demographic inclusion in clinical trials, and designing basic and clinical research studies to account for the intended patient population's age, sex, race, and genetic factors among other characteristics, will lead to better, safer therapies for diverse patient populations.