Sequences of individual words make up media reports. And sequences of media reports constitute the power of the news media to influence corporate practices. In this paper, we focus on the micro-foundations of news reports to elaborate how an atmosphere of negative news reports following an initial exposure of corporate pollution activity can help stop such activity through their impact on corporate managers. We extend our understanding of the corporate governance effect of news media by considering two new aspects of (...) reports—one, the proportion of words in negative reports relative to the total number of words in all reports; and two, the geographical origin of news media. We suggest that the more negative the media coverage, and the more local this coverage, the greater the impact on corporations. Our study of news media reports from more than 600 newspaper sources on disciplining pollution activities of listed Chinese firms from 2004 to 2012 provides strong support for our hypotheses. These findings have valuable implications for the handling of pollution issues in transitional economies via the power of news words. (shrink)

Emotion recognition plays an important part in human-computer interaction. Currently, the main challenge in electroencephalogram -based emotion recognition is the non-stationarity of EEG signals, which causes performance of the trained model decreasing over time. In this paper, we propose a two-level domain adaptation neural network to construct a transfer model for EEG-based emotion recognition. Specifically, deep features from the topological graph, which preserve topological information from EEG signals, are extracted using a deep neural network. These features are then passed through (...) TDANN for two-level domain confusion. The first level uses the maximum mean discrepancy to reduce the distribution discrepancy of deep features between source domain and target domain, and the second uses the domain adversarial neural network to force the deep features closer to their corresponding class centers. We evaluated the domain-transfer performance of the model on both our self-built data set and the public data set SEED. In the cross-day transfer experiment, the ability to accurately discriminate joy from other emotions was high: sadness, anger, and fear on the self-built data set. The accuracy reached 74.93% on the SEED data set. In the cross-subject transfer experiment, the ability to accurately discriminate joy from other emotions was equally high: sadness, anger, and fear on the self-built data set. The average accuracy reached 87.9% on the SEED data set, which was higher than WGAN-DA. The experimental results demonstrate that the proposed TDANN can effectively handle the domain transfer problem in EEG-based emotion recognition. (shrink)

Extant literature suggests that firms may gain legitimacy through imitation. But little known is about whom foreign multinational enterprises (MNEs) will imitate, given that they have multiple social referents: home-country peers and host-country industry competitors. Drawing upon category theory, we develop a dynamic imitation model and explicate how MNEs’ categorization process is affected by social activism, which causes the shift from self-categorization to categorical imperative. We investigate this model in the context of MNE philanthropy and propose that the social movement (...) may delegitimize MNEs’ original self-category and change their imitation target. Using a hand-collected dataset of MNEs’ philanthropic donation for the 2008 Sichuan Earthquake in China, we find that MNEs imitate their home-country peers first but shift to host-country industry competitors after an online social movement. This is because the online social movement delegitimizes MNEs as a category and suggests host-country industry peers as the new model for comparison. Further, we find that liability of foreignness impedes whereas firm reputation facilitates an MNE’s adaptation after the online social movement. Our paper contributes to the literatures on MNEs’ imitation behavior and CSR in emerging market. We also contribute to category theory by integrating self-categorization and categorical imperative and highlighting the role of social movements. (shrink)

Business Ethics, the Environment & Responsibility, EarlyView.

Business Ethics, the Environment & Responsibility, Volume 31, Issue 1, Page 239-256, January 2022.

Through an analysis of survey data gathered from private firms in China, this study examines the impact of employee protection on corporate innovation ability. The results indicate that firms with more advanced employee protection have stronger innovation ability. Furthermore, the positive relationship between employee protection and corporate innovation ability is more pronounced in those enterprises with labor unions. Finally, a firm’s political connections strengthen the influence of employee protection on corporate innovation. These empirical findings highlight the positive consolidating effects of (...) labor unions and political connections and will be of value to policy makers in emerging markets in gauging the important drivers of corporate innovation ability. (shrink)