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Purpose – In this chapter, we examine individual- and country-level differences in perceived job insecurity in the 27 European Union countries (EU27) within a multilevel framework.

Design/methodology/approach – We primarily focus on cross-national differences in perceived job insecurity in the EU27 and consider several possible explanations of it, including flexible employment practices, economic conditions, labor market structure, and political institutions. We examine both individual- and country-level determinants using multilevel partial proportional odds models based on individual-level data from the 2006 Eurobarometer 65.3 and country-level data from a variety of sources.

Findings – We find that European workers feel most insecure in countries with high unemployment, low union density, low levels of part-time and temporary employment, relatively little social spending on unemployment benefits, and in post-socialist countries.

Research limitations/implications – The findings from this study suggest that flexible employment practices do not necessarily cause workers to feel insecure in their jobs. This is likely due to the different nature of part-time and temporary employment in different institutional contexts.

Originality/value – This study is one of the most comprehensive accounts of perceived job insecurity in Europe given the focus on a larger number of countries and macro-level explanations for perceived job insecurity.

The administration of social assistance benefits is devolved to local agencies in Belgium, which raises questions about how much variation in spell lengths of benefit receipt is associated with differences across agencies. We address this issue by analysing the monthly hazard of benefit exit using administrative record data for 14,270 individuals in 574 welfare agencies. Our random-effects model allows for differences in both the observed and unobserved characteristics of beneficiaries and of local agencies. There are large differences in median benefit duration for individuals serviced by different welfare agencies: the range is from two months to more than 24 months. We find strong associations between beneficiary characteristics (sex, age, foreign nationality, citizenship acquisition, work history and being a student) and spell length. The estimates show higher odds of exiting social assistance receipt in bigger municipalities and in agencies which provide more generous supplementary assistance, and also strong evidence of shorter episodes in agencies where active labour market programme participation rates are higher.

This study aims to assess the satisfaction level of middle-income group (MIG) residents of government group housings of Kolkata, India. Further, a Composite Satisfaction Index (CSI) was also devised for assessing the satisfaction level.

The satisfaction level was assessed in three domains – “within premises”, “at neighbourhood” and “with cost” – incurred and questionnaires were designed to conduct primary survey. Question on overall level of satisfaction “with location” was also included. All satisfaction responses were recorded on a five-point Likert scale. Subsequently, a CSI – a weighted average of satisfaction for attribute “with location” and “with cost” – was devised. The weights were assigned through expert opinion survey using Delphi technique. Data being ordinal in nature, a two-step approach was adopted – initially through exploratory factor analysis, contributing attributes were identified and later a Generalised Ordered Logit Model was fitted in STATA. “Monetary benefits” were calculated as a difference of actual expenditure incurred from recommended expenditure towards regular transportation and housing. Mean satisfaction scores for attributes “with cost” were validated with “monetary benefits”.

Attribute “with cost” contributed significantly towards the overall level of satisfaction “with location”. The computed CSI values also comply with the findings, indicating the reliability of the index in similar contexts. The government group housing model was successful in its outreach towards the intended beneficiaries.

The CSI devised will help the MIG in identifying appropriate residential housing locations and enable policymakers in reviewing group housings.

Residential satisfaction studies were not specific to MIG residents considering attribute “with cost”. Hence, this study contributed to the existing knowledge in this specific context.

The purpose of this paper is to theorize the heightened exposure to information via the internet can lead citizens to be more critical about political conditions in their countries because using social media increases the likelihood of being exposed to dissident information. Further, the authors argue that the degree to which information is restricted, or internet access is limited, across countries can decrease this effect simply because the likelihood of exposure to a dissident flow is diminished.

The authors used survey data from the 2010 Latino Barometer to estimate a series of multilevel models to test whether citizens’ attitudes about the political conditions and about democracy in their respective countries worsen, and whether this effect is stronger in countries with higher internet freedom.

The results confirm that social media use has a negative influence on citizens’ attitudes about their national political conditions. In addition, respondents from those countries with more internet freedom tended to have more positive attitudes about their democracy and political conditions, generally. However, as a result of more internet freedom, the negative effects of internet and social media use on these attitudes was more pronounced in countries with more internet freedom.

These results suggest that the flow of information via the internet has substantial effect on how people feel about their government. This could be consequential for political stability, particularly in countries the conditions are not favorable. That said, these results also suggest that governments can actively decrease the odds of this dissidence building by controlling the flow of information.

Prior studies of criminal sentencing have largely focused on individual-level predictors of sentencing outcomes. The purpose of this paper is to examine the effects of a variety of theoretically derived community measurements of social threat and disadvantage on the criminal sentencing of convicted felons. This analysis permits an evaluation of whether legal ideals such as equality before the law and policy goals of equal treatment for like offenders are achieved.

The study examines data of individuals sentenced in the state of Florida and community level measurements of racial and ethnic threat and community disadvantage. Hierarchical generalized linear model is used to analyze the effect of these measures on the dichotomous in/out imprisonment variable, and standard hierarchical linear regression analysis is used to model the continuous dependent variable of sentence length.

The results provide support for the racial threat perspective though not for ethnic threat nor community disadvantage. The findings and their implications are discussed in terms of theory, research and policy.

Racial disparity in criminal justice practices is receiving increasing public and policy attention, as evidenced by the growing Black Lives Matter movement. Regarding sentencing, racial disparity remains a major research and policy question. While the current research and theoretical literature on sentencing is not conclusive, it is clear that race matters. As a result, racial disparity in sentencing needs to be a priority in subsequent “transitional criminology” efforts between researchers and policy makers to identify, explain and ultimately predict exactly how race impacts sentencing, and how to reduce it as a consideration from sentencing.

This study contributes to a growing body of literature that examines the social context of punishments by using several community level measurements of threat and disadvantage, while modeling the two-step sentencing outcome of imprisonment and sentence length.

Branching is one of the crucial strategic non-price actions for banks. Previous studies on the impact of state ownership upon banks focus on bank lending behavior. This paper aims to offer a novel investigation of how state ownership affects bank branching behavior by examining state-controlled commercial banks (SCCBs) in the context of the largest developing and transitional country China.

The two-part model (TPM) is applied to analyze the branching decision process. In the first stage, the dependent variable is the choice of bank branching dynamics and in the second stage the dependent variable is the number of new branches or the number of closed branches. For robustness check, the ordered probit selection model allowing for interdependence of the two stage decisions is also employed.

Using a unique dataset of bank branches in China, this paper finds that the branching decisions of Chinese SCCBs are driven by both profit motivated factors including population size, population density, income level, financial development and banking competition and politically motivated factors as represented with the proportion of SOEs. As a comparison, branching decisions of joint-stock banks in China are fully determined by profit motivated factors.

First, this study is the first to explore the effect of state ownership on bank branching decisions, providing a new insight on the literature regarding to the impact of state ownership on bank decisions. Second, this study explores the potential effect of politically motivated factors on bank branching decisions, filling the gap in bank branching literature. Third, this study can contribute to bank branching literature by enriching the limited understanding of how SCCBs make branching decisions. Lastly, this study applies novel empirical strategies to analyze bank branching decisions, including the TPM and the ordered probit selection model.

In most jurisdictions, resistance is the primary legal justification for police use of force. Identifying the correlates of resistance helps to anticipate non-compliance, increase officer safety, and maintain low rates of use of force. Following previous research on subject demeanor, the purpose of this paper is to argue that the presence of resistance is determined subjectively, based on an individual’s interpretation of a situation.

Binary and multinomial logistic regression models were used to analyze resistance reported in 878 interventions involving police use of force in a large Canadian city. A four-category measure similar to those commonly found in previous studies was used to build dependent variables and a series of 14 behaviors based on the actions of a subject was used as a predictor of reported resistance.

As expected, subject behavior was found to be a significant predictor of reported resistance. Officer and citizen characteristics (gender, race, age/experience) were weakly related to the outcome. Models were found to offer considerably better predictions when situational factors were included.

Perceptions of resistance were found to be influenced by a variety of factors, including, but not limited to, the subject’s actions.

There is an emerging literature focusing on the impact of late career transitions on health, but little is known so far about the role working time modulations might play in explaining older workers’ health. The paper aims to discuss this issue.

Using the English Longitudinal Study of Ageing (ELSA) Waves 4–7, the paper assesses the association between the different types of change in working time, the total weekly working hours at baseline and the level of income and the change in Self-perceived health (SPH). The model controls for financial wealth, qualification, gender, age, the sector of activity and self-reported health at baseline.

Respondents who retire have a better SPH compared with those who keep working at constant working time. Those who work long hours benefit more from retiring. Respondents working long hours before being unemployed tend to be less affected by a negative change in SPH. Those who reduce working time by 50 per cent or more and work long hours at baseline have lower probabilities to be affected by a negative change in SPH compared with those who work fewer hours. Finally, low-paid workers are those who benefit the most from retiring or reducing working time.

Results point out the need to foster working time arrangements for low-paid workers to prevent adverse health impacts.

There is a significant association between change in working time and change in self-reported health that has not been examined by previous studies.

The active power filter with two-level inverter needs a high-rating coupling transformer for high-power applications. This complicates the control and system becomes bulky and expensive. The purpose of this paper is to motivate the use of multilevel inverter as harmonic filter, which eliminates the coupling transformer and allows direct control of the power circuit. The advancement in artificial intelligence (AI) for computation is explored for controller design.

The proposed scheme has a five-level cascaded H-bridge multilevel inverter (CHBMLI) as a harmonic filter. The control scheme includes one neural network controller and two fuzzy logic-based controllers for harmonic extraction, dc capacitor voltage balancing, and compensating current adjustment, respectively. The topology is modeled in MATLAB/SIMULINK and implemented using dSPACE DS1103 interface for experimentation.

The exhaustive simulation and experimental results demonstrate the robustness and effectiveness of the proposed topology and controllers for harmonic minimization for RL/RC load and change in load. The comparison between traditional PI controller and proposed AI-based controller is presented. It indicates that the AI-based controller is fast, dynamic, and adaptive to accommodate the changes in load. The total harmonic distortion obtained by applying AI-based controllers are well within the IEEE519 std. limits.

The simulation of high-power, medium-voltage system is presented and a downscaled prototype is designed and developed for implementation. The laboratory module of CHBMLI-based harmonic filter and AI-based controllers modeled in SIMULINK is executed using dSPACE DS1103 interface through real time workshop.

The purpose of this paper is to focus on the case where – by design – one needs to impute cross-country cross-survey (CCCS) data (situation typical for example among multinational firms who are confronted with the need to carry out comparative marketing surveys with respondents located in several countries). Importantly, while some work demonstrates approaches for single-item direct measures, no prior research has examined the common situation in international marketing where the researcher needs to use multi-item scales of latent constructs. The paper presents problem areas related to the choices international marketers have to make when doing cross-country/cross-survey research and provides guidance for future research.

Multi-country sample of real data is used as an example of cross-sample imputation (292 New Zealand exporters and 302 Finnish ones) the international entrepreneurial orientation (IEO) data. Three variations of the input data are tested: first, imputation based on all the data available for the measurement model; second, imputation based on the set of items based on the invariance structure of the joint items shared across the two groups; and third, imputation based both on examination of the invariance structures of the joint items and the performance of the measurement model in the group where the full data was originally available.

Based on distribution comparisons imputation for New Zealand after completing the measurement model with Finnish data (Model C) gave the most promising results. Consequently, using knowledge on between country measurement qualities may improve the imputation results, but this benefit comes with a downside since it simultaneously reduces the amount of data used for imputation. None of the imputation models leads to the same statistical inferences about covariances between latent constructs than as the original full data, however.

Considering multiple imputation, the present exploratory study suggests that there are several concerns and issues that should be taken into account when planning CCCSs (or split questionnaire or sub-sampling designs). Even if there are several advantages available for well-implemented CCCS designs such as shorter questionnaires and improved response rates, these concerns lead us to question the appropriateness of the CCCS approach in general, due to the need to impute across the samples.

The combination of cross-country and cross-survey approaches is novel to international marketing, and it is not known how the different procedures utilized in imputation affect the results and their validity and reliability. The authors demonstrate the consequences of the various imputation strategy choices taken by using a real example of a two-country sample. The exploration may have significant implications to international marketing researchers and the paper offers stimulus for further research in the area.