Research on the Association Between Perceived Neighborhood Environment and Life Satisfaction Among Older Adults in Shanghai, China: Do Social Capital And Gender Matter?

This study examined the mediator role of social capital on the association between perceived neighborhood environment and life satisfaction among older adults in urban China, and further tested the moderating effect of gender in the above paths (i.e., from neighborhood environment to life satisfaction; from neighborhood environment to social capital; from social capital to life satisfaction). We used quota sampling approach to recruit 472 respondents aged 60 years old or older in Shanghai in 2020. From the perspective of structural equation modeling, multiple group analysis was conducted to examine the proposed hypotheses. The measurement model of social capital was well established in urban Chinese community contexts. Based on the whole sample, the results of the mediation model showed that social capital played a mediation role in the association between neighborhood environment and life satisfaction. Furthermore, the results of multiple group analysis showed that the association between neighborhood environment and cognitive social capital was only significant among older women. The findings highlight the role of neighborhood environment and social capital in building age-friendly communities.

With them or watching: Entitativity is Facebook Status Updates

Are Facebook status updates groups? If Facebook status updates are groups, then they may be an understudied yet fundamental unit of analysis for understanding Facebook. Using entitativity and self-categorization theories, we examine how status updates are perceived as groups by the status updaters. Results suggest that people who post status updates iterpret the responders to their status updates as groups. Further, using multiple group analysis, we demonstrate that interacting with status update responders creates a stronger and more robust assessment of the group. Our study suggests that theories about groups, particularly groups in which people are members, may be a new, useful theoretical stream for researchers.

Does coping mediate the effect of financial threat on life satisfaction? A multigroup analysis

The year of 2007 was marked by one of the most severe global financial crises, which led to an increase of psychopathological symptoms that negatively affected life satisfaction. This research analyzed how financial threat was associated with life satisfaction and how coping, as a mediating variable, influenced this relationship. The theoretical model was tested through a sample of 901 Portuguese individuals, averaging 37 years old (SD=12.86). A structural equation modelling (SEM) was used to obtain the results, by using a multiple-group analysis. Overall, the results showed that financial threat is negatively associated with life satisfaction and that proactive coping strategies have a positive association with life satisfaction.The results obtained from coping as a mediating variable were not significant (considering the total sample). However, when we performed a multiple-group analysis, in the group of individuals with lower levels of financial threat, the mediation effect was statistically significant, showing an almost total attenuation of the crisis’s negative effects on life satisfaction. Thusly, we can infer that the mediating role of coping depends on the level of perceived financial threat. Since periods of financial threat have a negative impact on individuals’ psychological health, coping strategies can mitigate this relationship by decreasing the aforementioned negative impact.

The Impact of Outsourcing on the Performance of Small and Medium Enterprises in Vietnam

This study examines the impact of using outsourced services on the performance of small and medium enterprises (SMEs) in Vietnam. The primary data used to analyze this study's main objectives were collected by the survey with the structured questionnaire and the expert interview with semi-structured interview guidelines. A total of 742 SMEs using outsourced services in the study area participated in the survey. The study employs Cronbach’s alpha test, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), structural equation modelling (SEM), and multiple-group analysis for variables measurements and model testing. The study also investigates the influences of the degree of outsourcing on the enterprise’s performance. The results show that the degree of outsourcing has a low impact on financial performance, particularly ROS, ROE, and ROA (R2 = 0.013). Also, the degree of outsourcing has impacts on non-financial performance. The multiple-group analysis results indicate the different influences of the outsourcing degree on the different types of enterprises’ performance. The degree of outsourcing has a stronger impact on micro-enterprises' performance than the small and medium-sized enterprises. The commercial and service enterprises have higher performance when outsourcing than others. The outsourcing degree has a stronger impact on the performance of the enterprises that operated for more than nine years than others. The results show that there are different influences of the outsourcing degree on the performance of the enterprises that have different outsourcing situations. According to the findings, this study proposes the three main managerial implications to improve outsourcing effectively, such as strengthening outsourcing risk management, deciding on outsourcing depend on the enterprises’ characteristics, and managing the relationship between stakeholders.

Multiple Group Analysis in Multilevel Data Across Within-Level Groups: A Comparison of Multilevel Factor Mixture Modeling and Multilevel Multiple-Indicators Multiple-Causes Modeling

The purpose of this two-part study is to evaluate methods for multiple group analysis when the comparison group is at the within level with multilevel data, using a multilevel factor mixture model (ML FMM) and a multilevel multiple-indicators multiple-causes (ML MIMIC) model. The performance of these methods was evaluated integrally by a series of procedures testing weak and strong invariance models and the latent group mean differences testing after holding for factorial invariance. Two Monte Carlo simulation studies were conducted under the following conditions: number of clusters, cluster size, and the design type in groups. A multilevel one-factor confirmatory factor analysis (CFA) model as a research model in Study 1 was investigated to compare the results under different conditions with those of previous studies. A multilevel two-factor CFA model as a research model in Study 2 was evaluated by fitting alternative models that can be applied when the model is complicated. The results indicated that the two methods were reasonable in multilevel multiple groups analysis across within-level groups. However, pros and cons were found between the two methods. In the multilevel one-factor CFA model, ML MIMIC model was slightly better when the sample size is small. In the multilevel complex model, two alternative models of ML FMM were recommended because the weak invariance testing of ML MIMIC was considerably time-consuming. Finally, it was shown that information criteria, which are criteria for determining whether factorial invariance is established, need to be applied differently according to the sample size conditions. Guidelines for this situation are provided.