Parental participation has gained significant attention in environmental psychology, which has revealed a need for an instrument that can measure parental participation with children regarding environmental issues. The present study met this need by validating the parental participation in the environment scale. This process began with 45 Chinese parents participating in an individual interview and group discussions, which helped generate a list of eighteen parent-child environmental activities. The activities were then modified and validated in the current study with a diverse (...) group of 969 parents recruited from six major Chinese cities. Both score structure evidence and generalizability evidence were obtained within this sample, and psychometric tests suggested a single factor construct with nine items. Once the PPE scale was revised, it showed measurement invariance across the parent who responded to the items, across the child’s primary caregiver, across the family’s living region, as well as across the family’s income group. Finally, evidence based on relations to other variables showed a relationship among parents’ PPE, pro-environmental behavior, and connectedness with nature. As a result, the study provided a novel measure to assess pro-environmental socialization via parental participation. (shrink)

Volatility is widely used in different financial areas, and forecasting the volatility of financial assets can be valuable. In this paper, we use deep neural network and long short-term memory model to forecast the volatility of stock index. Most related research studies use distance loss function to train the machine learning models, and they gain two disadvantages. The first one is that they introduce errors when using estimated volatility to be the forecasting target, and the second one is that their (...) models cannot be compared to econometric models fairly. To solve these two problems, we further introduce a likelihood-based loss function to train the deep learning models and test all the models by the likelihood of the test sample. The results show that our deep learning models with likelihood-based loss function can forecast volatility more precisely than the econometric model and the deep learning models with distance loss function, and the LSTM model is the better one in the two deep learning models with likelihood-based loss function. (shrink)

Unfounded—conspiracy and health—beliefs about COVID-19 have accompanied the pandemic worldwide. Here, we examined cross-nationally the structure and correlates of these beliefs with an 8-item scale, using a multigroup confirmatory factor analysis. We obtained a two-factor model of unfounded (conspiracy and health) beliefs with good internal structure (average CFI = 0.98, RMSEA = 0.05, SRMR = 0.04), but a high correlation between the two factors (average latent factor correlation = 0.57). This model was replicable across 50 countries (total N = 13,579), (...) as evidenced by metric invariance between countries (CFI = 0.96, RMSEA = 0.06, SRMS = 0.07) as well as scalar invariance across genders (CFI = 0.98, RMSEA = 0.04, SRMS = 0.03) and educational levels (CFI = 0.98, RMSEA = 0.04, SRMS = 0.03). Also, lower levels of education, more fear of COVID-19, and more cynicism were weakly associated with stronger conspiracy and health beliefs. The study contributes to knowledge about the structure of unfounded beliefs, and reveals the potential relevance of affective (i.e., fear of COVID-19) and cognitive (i.e., cynicism) factors along with demographics, in endorsing such beliefs. In summary, we obtained cross-cultural evidence for the distinctiveness of unfounded conspiracy and health beliefs about COVID-19 in terms of their structure and correlates. (shrink)

Building on institutional theory, we examine the effect of politicians' hometown favouritism on a firm's philanthropic engagement in China. We propose that firms headquartered in the politicians' hometowns tend to reduce their philanthropic investment because identification with their hometown activates the politicians' tendency to extend political legitimacy to hometown firms. Analysing a large sample of publicly listed Chinese firms for 2003–2015, we demonstrate that hometown firms evade their social responsibility by taking advantage of the incumbent provincial political leader's “home bias”. (...) We also find that such a “home bias” effect exists when the political leader comes into power and disappears after the leader leaves office. Further analyses show that the firms' political dependency strengthens the “home bias” effect, so that firms in sensitive industries, with greater financial resources and private ownership, are more likely to evade their social engagement by taking advantage of the politicians' hometown favouritism. Our study highlights the critical role of hometown connections in corporate social responsibility in the Chinese relationship-based business system. It also advances a normative institutional assessment of hometown-based favouritism by highlighting its distinct dynamics and impacts on focal firms' social decision-making. (shrink)

How learning a second language changes our brain has been an important question in neuroscience. Previous neuroimaging studies with different ages and language pairs spoken by bilinguals have consistently shown plastic changes in brain systems supporting executive control. One hypothesis posits that L2 experience-induced neural changes supporting cognitive control, which is responsible for the selection of a target language and minimization of interference from a non-target language. However, it remains poorly understood as to whether such cognitive advantage is reflected as (...) stronger controlled processing or increased automatic inhibition processing. In this study, using functional MRI we scanned 27 Chinese-English late bilinguals while they performed a Simon task. Results showed that bilinguals with higher L2 vocabulary proficiency performed better in the Simon task, and more importantly, higher L2 vocabulary proficiency was associated with weaker activation of brain regions that support more general cognitive control, including the right anterior cingulate cortex, left insula and left superior temporal gyrus. These results suggest that L2 experience may lead to a more automatic and efficient processing in the inhibitory control task. Our finding provides an insight into neural activity changes associated with inhibitory control as a function of L2 proficiency. (shrink)