Tong Li

This paper investigates the role of business ethics consultants in translating business ethics into practical solutions within organizations. Despite the wealth of research on business ethics, practitioners often report difficulty in applying academic insights in their organizational context. To bridge this gap, organizations often engage external ethics consultants to help translate theory into practical solutions for navigating challenging ethical situations. Through 17 semi-structured interviews with ethics consultants who work in digital work environments, we developed the Assessment-Calibration-Synchronization framework, demonstrating how their translation work renders business ethics knowledge relevant and adoptable for their clients. This framework encompasses three phases: assessing ethical context, calibrating strategies to organizational goals, and synchronizing ethical practices. Our study contributes to the business ethics literature by offering insights into how ethics consultants translate business ethics into practice and promote ethical change. This research also offers practical guidance for organizations seeking to improve their ethical practices and for ethics consultants aiming to enhance their impact in corporate settings.

This study explores epistemic virtue as a new lens to scrutinize organizational behavior. Organizational epistemic virtues are the qualities of organizations that support the creation, sharing, and retaining of knowledge. We study how well organizations handle information and if that can prevent organizational misconduct. We propose a theoretical framework to link epistemic virtue to the prevention of misconduct and test this model using data from 822 U.S. companies. These companies are scored on six epistemic virtues by analyzing over one million online employee reviews using natural language processing. We focus on the epistemic virtues of curiosity, epistemic beneficence, epistemic justice, epistemic integration, humility, and open-mindedness. We find that companies with these virtues engage in less corporate misconduct, measured in terms of the number of penalties imposed by government agencies. We also give practitioners a framework to assess the epistemic virtues of organizations.

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.

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.

This study explores epistemic virtue as a new lens to scrutinize organizational behavior. Organizational epistemic virtues are the qualities of organizations that support the creation, sharing, and retaining of knowledge. We study how well organizations handle information and if that can prevent organizational misconduct. We propose a theoretical framework to link epistemic virtue to the prevention of misconduct and test this model using data from 822 U.S. companies. These companies are scored on six epistemic virtues by analyzing over one million online employee reviews using natural language processing. We focus on the epistemic virtues of curiosity, epistemic beneficence, epistemic justice, epistemic integration, humility, and open-mindedness. We find that companies with these virtues engage in less corporate misconduct, measured in terms of the number of penalties imposed by government agencies. We also give practitioners a framework to assess the epistemic virtues of organizations.

© 2014 American Chemical Society.Attempts to apply artificial nano/micromotors for diverse biomedical applications have inspired a variety of strategies for designing motors with diverse propulsion mechanisms and functions. However, existing artificial motors are made exclusively of synthetic materials, which are subject to serious immune attack and clearance upon entering the bloodstream. Herein we report an elegant approach that turns natural red blood cells into functional micromotors with the aid of ultrasound propulsion and magnetic guidance. Iron oxide nanoparticles are loaded into the RBCs, where their asymmetric distribution within the cells results in a net magnetization, thus enabling magnetic alignment and guidance under acoustic propulsion. The RBC motors display efficient guided and prolonged propulsion in various biological fluids, including undiluted whole blood. The stability and functionality of the RBC motors, as well as the tolerability of regular RBCs to the ultrasound operation, are carefully examined. Since the RBC motors preserve the biological and structural features of regular RBCs, these motors possess a wide range of antigenic, transport, and mechanical properties that common synthetic motors cannot achieve and thus hold considerable promise for a number of practical biomedical uses.

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.

This paper presents a numerical investigation of bird attitude angles affecting the soft-impact damage of a full fan assembly. Firstly, considering the geometry of a mallard, a real bird model is established by the Smoothed Particle Hydrodynamics method and calibrated with available test data. Then, complying with airworthiness requirements, simulations of a full-bladed fan assembly subjected to a real bird were conducted to determine the critical ingestion parameters. Furthermore, a real bird with different attitude angles aimed at a full fan assembly was simulated. Results show that attitude angles of the bird produce a significant impact on the effect of the bird strike on rotating blades and would increase the possibility of blade failures, especially for the yaw angle of -45° and the pitch angle of −60°. It is invaluable for commercial airlines and engine manufactures to provide safe flight and landing by adopting the real bird model with critical yaw and pitch angles in the design for resistance to bird ingestion.