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Criminal victimization is known to influence households' moving decisions, but theories suggest that the processes leading to a moving decision can vary across racial and ethnic groups. Drawing from current literature, we hypothesized that victimization would have a stronger effect on moving decisions for Whites than for Blacks or Hispanics, and that racial/ethnic residential segregation would moderate the impact of victimization on mobility. Using a longitudinal sample of 34,134 housing units compiled from the National Crime Victimization Survey for the 40 largest metropolitan areas in the United States (1995–2003), we found results that both support and contradict the hypotheses. Specifically, White residents display consistent evidence that victimization is a significant predictor of household mobility. Blacks and Hispanics, in contrast, are more varied in their moving behavior after victimization. In addition, significant differences exist among these groups in responses to victimization and in how mobility is influenced by residential segregation. Higher levels of residential segregation play a part in the victimization–mobility relationship among Blacks in a way that is more complex than we hypothesized.

This study examines the microlevel process of housing turnover between Blacks and Whites to assess whether crime plays an important role in the racial transition of neighborhoods. The study uses a unique, longitudinal version of the National Crime Survey in which each dwelling's close neighbors are identified. After controlling for household characteristics and the characteristics of their close neighbors, crime occurring in nearby areas is found to increase the chances of White‐to‐Black turnover while decreasing the chances of Black‐to‐White turnover. This change occurs even though the directly victimized houses do not necessarily have a probability of racial turnover different than that of other houses nearby. The findings suggest the presence of structural constraints that limit the housing opportunities for Blacks and constrain their choice of residence to comparatively unsafe neighborhoods. They also indicate that "White avoidance," in which Whites systematically bypass high‐crime neighborhoods, is important in maintaining the relationship between race and crime.

This article investigates the impact of criminal victimization on household residential mobility. Existing research finds that direct experiences with crime influence mobility decisions, such that persons who suffer offenses near their homes are more likely to move. The current study extends this line of inquiry to consider whether indirect victimization that involves neighbors also stimulates moving. The analysis uses the National Crime Survey to estimate multilevel models that incorporate data from individual households and their spatially proximate neighbors. The results show that the link between direct victimization and moving continues to hold after controlling for neighborhood context. Indirect property victimization also leads to moving, with effects about equal in size to those of direct victimization. In contrast, no evidence is found that violent victimization that occurs in neighboring homes influences mobility, probably because most of these events are nonstranger violence that provokes less anxiety for neighbors.

Americans move frequently, and moving alters their risks of victimization. This study uses unique longitudinal, multilevel data from the 1980–1985 National Crime Survey to examine the effects of residential turnover on household victimization. The two major findings of the study are as follows: First, housing turnover is a transition that independently increases the risk that a dwelling will experience a crime. This finding is true even controlling for persistent differences in crime vulnerability between dwellings. Second, changes in the composition and routine activities of households also alter the risks of victimization. These findings provide support for social disorganization and crime opportunity theories.

AbstractUntil recently, national‐level data on criminal victimization in the United States did not include information on immigrant or citizenship status of respondents. This data‐infrastructure limitation has hindered scientific understanding of whether immigrants are more or less likely than native‐born Americans to be criminally victimized and how victimization may vary among immigrants of different statuses. We address these issues in the present study by using new data from the 2017–2018 National Crime Victimization Survey (NCVS) to explore the association between citizenship status and victimization risk in a nationally representative sample of households and persons aged 12 years and older. The research is guided by a theoretical framing that integrates insights from studies of citizenship with the literature on immigration and crime, as well as with theories of victimization. We find that a person's foreign‐born status (but not their acquired U.S. citizenship) confers protection against victimization. We also find that the protective benefit associated with being foreign born does not extend to those with ambiguous citizenship status, who in our data exhibit attributes similar to the known characteristics of undocumented immigrants. We conclude by discussing the implications of our findings and the potential ways to extend the research.

AbstractUsing data from the Area‐Identified National Crime Victimization Survey (NCVS), we provide a national assessment of the impact of neighborhood immigrant concentration on whether violence is reported to the police. By drawing on multiple theoretical perspectives, we outline how the level of violence reporting could be higher or lower in immigrant neighborhoods, as well as how this may depend on individual race/ethnicity and the history of immigration in the county in which immigrant neighborhoods are located. Controlling for both individual‐ and neighborhood‐level conditions, our findings indicate that within traditional immigrant counties, rates of violence reporting in immigrant neighborhoods are similar to those observed elsewhere. In contrast, within newer immigrant destinations, we observe much lower rates of violence reporting in neighborhoods with a large concentration of immigrants. Our study findings reveal comparable patterns for Whites, Blacks, and Latinos. The results have important implications for theory, policy, and future research.

AbstractResearchers in the United States have increasingly recognized that immigration reduces crime, but it remains unresolved whether this applies to people of different racial–ethnic and economic backgrounds. By using the 2008–2012 area‐identified National Crime Victimization Survey (NCVS), we evaluate the effect of neighborhood immigrant concentration on individual violence risk across race/ethnicity and labor market stratification factors in areas with different histories of immigration. The results of our analysis reveal three key patterns. First, we find a consistent protective role of immigrant concentration that is not weakened by low education, low income, unemployment, or labor market competition. Therefore, even economically disadvantaged people enjoy the crime‐reduction benefit of immigration. Second, we find support for threshold models that predict a nonlinear, stronger protective role of immigrant concentration on violence at higher levels of immigrant concentration. The protective function of immigration also is higher in areas of longer histories of immigration. Third, compared with Blacks and Whites, Latinos receive a greater violence‐reduction benefit of immigrant concentration possibly because they live in closer proximity with immigrants and share common sociocultural features. Nevertheless, immigrant concentration yields a diminishing return in reducing Latino victimization as immigrants approach a near‐majority of neighborhood residents. The implications of these results are discussed.

Although community responses to the problem of intimate partner violence typically focus on increasing and improving policing and social services, few studies have examined the relationship among police force size, social service providers, and women's safety at home. To address this issue, we use data from the National Crime Victimization Survey to examine patterns of intimate partner violence for 40 metropolitan statistical areas (MSAs) over a 16‐year period (1989–2004). We analyze the data using three‐level multilevel models, with individual respondents (N = 487,166) nested within years, nested within MSAs. Net of other important individual and contextual factors, the results show that women's likelihood of victimization is significantly lower in MSAs that employ more sworn officers per capita, whereas the states' mandatory arrest laws are not found to have significant independent effects. Above and beyond the effects of police force size, we also find a significant negative relationship between the size of the social service workforce and intimate partner violence. Future research should develop collaborative data collection efforts to examine the specific activities of police and social service workers in dealing with intimate partner violence so that the mechanisms underlying these significant relationships can be understood more clearly.

This article examines the impact of women's status on rates of violence against women using longitudinal data from the National Crime Survey and National Crime Victimization Survey for 40 U.S. metropolitan areas for the period 1980 to 2004. Drawing on feminist and routine activities perspectives, we specify hypotheses about the association between women's status and violent victimization, some of which predict different effects depending on whether the offender is a stranger, intimate, or known (nonintimate) other. Consistent with feminist and other perspectives, we find that absolute increases in women's labor force participation, income, and education are associated with decreases in intimate partner violence. Our findings also provide limited support for the backlash hypothesis by showing that increases in female labor participation relative to men are associated with increases in intimate partner violence but not with increases in violence by others. Consistent with routine activities theory, the data also indicate that absolute increases in female labor force participation are associated with increases in victimization by strangers and by known others. Furthermore, we find that absolute increases in female voter participation are associated with decreases in violence for all victim–offender relationship categories. The findings thus show that changes in the status of women have both positive and negative associations with violence victimization, and that comparative analyses of different types of violence are necessary for clarifying the sources of violence against women.

Purpose
The research on people and project factors is found extensively in general but not specific to software engineering. Secondly, the existing research has not concentrated on the communication and time complexity of the teams on software economics. The purpose this paper is to develop a model to investigate and quantify the impact of time pressure (TP) on software economics through the communication influence of software team sizes (TS).


Design/methodology/approach
A research model and five hypotheses are developed based on the gaps in the literature. The data set from International Software Benchmarking Standards Group repository is used for testing the hypotheses.


Findings
Important findings include: smaller TS tends to exert less TP on average; TP is directly proportional to software economics, however; and TP does not affect the productivity required for the software.


Research limitations/implications
The study has the following implications: Selection of an appropriate TS for project completion that ensures minimum pressure on team members; and maximize software outcomes in stress-free environment.


Practical implications
This work is useful for organizations carrying out software projects with teamwork. The project managers can benefit from the results while planning the team factors for achieving the project goals.


Social implications
The results uphold not to exert pressure on the team as it will not only affect the duly completion of the project but also the well-being of employees.


Originality/value
The paper is the first one where the proposition of TP estimation is done using TS and communication complexity, and empirically evaluating the impact of TP on four major software economics are the major key contributions of this research work.

Recompression supercritical carbon dioxide (SCO2) Brayton Cycle for the Chinese Initiative Accelerator Driven System (CiADS) is taken into account, and flexible thermodynamic modeling method is presented. The influences of the key parameters on thermodynamic properties of SCO2 Brayton Cycle are discussed and the comparative analyses on genetic algorithm and pattern search algorithm are conducted. It is shown that the cycle parameters such as turbine inlet temperature, pressure ratio, outlet temperature at the hot end of condenser, and terminal temperature difference of regenerator 1 and regenerator 2 have significant effects on the cycle thermal efficiency. The calculation results indicate that pattern search algorithm has better optimization performance and quicker calculating speed than genetic algorithm. The result of optimization of the parameters for CiADS with supercritical carbon dioxide Brayton Cycle is 35.97%. Compared with other nuclear power plants of SCO2 Brayton Cycle, CiADS with SCO2 Brayton Cycle does not have the best thermal efficiency, but the thermal efficiency can be improved with the reactor outlet temperature increases.