This work has aimed to investigate the consumers’ green product purchase attitudes and behavioral intention during COVID-19 pandemic. Data was collected through a survey method of 503 consumers in Malaysia. Data were analyzed using the partial least square method. The findings revealed that fear of COVID-19 pandemic has a significant impact on green product behavioral intention. Green product literacy, green product orientation, and social influence have a significant influence on green product purchase attitudes. The results also indicated that consumers’ green (...) product purchase attitudes mediate the effect of green product literacy, green product orientation, and social influence on behavioral intention. The findings of this work will provide strategically relevant references to green marketers and retail managers in the understanding of consumers’ green product purchase attitudes and green product behavioral intention during the ongoing uncertainty of the COVID-19 pandemic. (shrink)

Bayesian approaches for estimating multilevel latent variable models can be beneficial in small samples. Prior distributions can be used to overcome small sample problems, for example, when priors that increase the accuracy of estimation are chosen. This article discusses two different but not mutually exclusive approaches for specifying priors. Both approaches aim at stabilizing estimators in such a way that the Mean Squared Error of the estimator of the between-group slope will be small. In the first approach, the MSE is (...) decreased by specifying a slightly informative prior for the group-level variance of the predictor variable, whereas in the second approach, the decrease is achieved directly by using a slightly informative prior for the slope. Mathematical and graphical inspections suggest that both approaches can be effective for reducing the MSE in small samples, thus rendering them attractive in these situations. The article also discusses how these approaches can be implemented in Mplus. (shrink)