The study of voice behavior examines the inclination of staff and team members to speak up and contribute ideas to the team. In this article, we investigate how factors such as leader-member exchange (LMX), psychological safety and psychological empowerment influence such behavior. Our findings, which are based on a sample of 308 employees working for a state-owned telecommunications company on the Chinese mainland, indicate that ethical leadership promotes employees’ voice behavior through enhanced leader-member exchange, which also leads to greater feelings (...) of psychological safety and psychological empowerment. The theoretical and practical implications of these results are discussed. (shrink)

The purpose of crowd counting is to estimate the number of pedestrians in crowd images. Crowd counting or density estimation is an extremely challenging task in computer vision, due to large scale variations and dense scene. Current methods solve these issues by compounding multi-scale Convolutional Neural Network with different receptive fields. In this paper, a novel end-to-end architecture based on Multi-Scale Adversarial Convolutional Neural Network (MSA-CNN) is proposed to generate crowd density and estimate the amount of crowd. Firstly, a multi-scale (...) network is used to extract the globally relevant features in the crowd image, and then fractionally-strided convolutional layers are designed for up-sampling the output to recover the loss of crucial details caused by the earlier max pooling layers. An adversarial loss is directly employed to shrink the estimated value into the realistic subspace to reduce the blurring effect of density estimation. Joint training is performed in an end-to-end fashion using a combination of Adversarial loss and Euclidean loss. The two losses are integrated via a joint training scheme to improve density estimation performance.We conduct some extensive experiments on available datasets to show the significant improvements and supremacy of the proposed approach over the available state-of-the-art approaches. (shrink)

The Mobile Phone Addiction Index is a short instrument to assess mobile phone addiction. The Chinese version of this scale has been widely used in Chinese students and shows promising psychometric characteristics. The present study tested the construct validity and measurement invariance of the MPAI by gender in middle school adolescents. The data were collected from 1,395 high school students. Confirmatory factor analysis and multiple-group CFA for invariance tests were conducted on the MPAI model which consisted of 17 observed items (...) and 4 latent factors. Findings showed that the data fit the four-factor structure model well for both males and females. Furthermore, configural, metric, scalar, and residual invariance were established by gender. The results indicated that the MPAI has acceptable psychometric properties when used in adolescents. In addition, with the strict invariance requirements being satisfied, the underlying factor scores for MPAI can be meaningfully compared across genders. To our knowledge, this study is the first attempt to test the measurement invariance of the MPAI across male and female adolescents. Our results will support future research on mobile phone addiction in adolescents. (shrink)