Employee perception of corporate social responsibility authenticity: A multilevel approach

Stakeholder interest in the accuracy of Environment Social and Governance (ESG) data and Corporate Social Responsibility (CSR) authenticity has increased, as more companies are disclosing their ESG data. Employees are one of the most important stakeholders of a company, and they have access to more CSR information than other external stakeholders. Employees have a dual role of observing and participating in CSR. Employee perceptions of CSR authenticity play a key role in the positive effects of CSR. In this study, the research model was analyzed through multilevel analysis to contribute to the literature on the mechanism by which CSR affects employees’ job attitudes and perceptions of CSR authenticity. First, hypothesis testing confirmed that external CSR is positively associated with employees’ perceptions of CSR authenticity. Second, CSR authenticity mediates a positive relationship between external CSR and emotional commitment. As the direct effect of external CSR on emotional commitment was not statistically significant, it could be confirmed that the full mediation relationship was significant through CSR authenticity. This study makes three theoretical contributions to the literature on employees’ perceptions of CSR. First, it examines the mechanism of the impact of CSR on employees. By examining the mechanism by which employees recognize and interpret CSR, this study attempts to uncover the black box that CSR affects employees. Second, this study contributes to the literature on CSR authenticity by explaining the mediating role of CSR authenticity in the relationship between CSR and employee job attitudes through construal level theory. Finally, this study contributes to the employee-based CSR literature by analyzing the effect of CSR as an organizational-level variable on emotional commitment as an individual-level variable through multilevel structural equation modeling (MSEM)

Requirements for Trustworthy Artificial Intelligence and its Application in Healthcare

Objectives Artificial intelligence (AI) technologies are developing very rapidly in the medical field, but have yet to be actively used in actual clinical settings. Ensuring reliability is essential to disseminating technologies, necessitating a wide range of research and subsequent social consensus on requirements for trustworthy AI. Methods This review divided the requirements for trustworthy medical AI into explainability, fairness, privacy protection, and robustness, investigated research trends in the literature on AI in healthcare, and explored the criteria for trustworthy AI in the medical field. Results Explainability provides a basis for determining whether healthcare providers would refer to the output of an AI model, which requires the further development of explainable AI technology, evaluation methods, and user interfaces. For AI fairness, the primary task is to identify evaluation metrics optimized for the medical field. As for privacy and robustness, further development of technologies is needed, especially in defending training data or AI algorithms against adversarial attacks. Conclusions In the future, detailed standards need to be established according to the issues that medical AI would solve or the clinical field where medical AI would be used. Furthermore, these criteria should be reflected in AI-related regulations, such as AI development guidelines and approval processes for medical devices

The BDNF Val66Met Polymorphism Affects the Vulnerability of the Brain Structural Network

Val66Met, a naturally occurring polymorphism in the human brain-derived neurotrophic factor (BDNF) gene resulting in a valine (Val) to methionine (Met) substitution at codon 66, plays an important role in neuroplasticity. While the effect of the BDNF Val66Met polymorphism on local brain structures has previously been examined, its impact on the configuration of the graph-based white matter structural networks is yet to be investigated. In the current study, we assessed the effect of the BDNF polymorphism on the network properties and robustness of the graph-based white matter structural networks. Graph theory was employed to investigate the structural connectivity derived from white matter tractography in two groups, Val homozygotes (n = 18) and Met-allele carriers (n = 55). Although there were no differences in the global network measures including global efficiency, local efficiency, and modularity between the two genotype groups, we found the effect of the BDNF Val66Met polymorphism on the robustness properties of the white matter structural networks. Specifically, the white matter structural networks of the Met-allele carrier group showed higher vulnerability to targeted removal of central nodes as compared with those of the Val homozygote group. These findings suggest that the central role of the BDNF Val66Met polymorphism in regards to neuroplasticity may be associated with inherent differences in the robustness of the white matter structural network according to the genetic variants. Furthermore, greater susceptibility to brain disorders in Met-allele carriers may be understood as being due to their limited stability in white matter structural connectivity

Exploring the Organizational Culture’s Moderating Role of Effects of Corporate Social Responsibility (CSR) on Firm Performance: Focused on Corporate Contributions in Korea

The purpose of this study was to examine the role of organizational culture in helping to translate corporate social responsibility (CSR) into firm performance. We employed arguments from the CSR strategy view to highlight the effectiveness of CSR and the contingency approach to explain the vertical fit between CSR and the organizational culture in a firm. Furthermore, we examined the moderating influence of organizational culture on the CSR–firm performance linkage. The results suggest that some organizational cultures moderate the relationship between CSR and financial outcomes, and that organizational culture may play an important role in enhancing a positive relationship between CSR and firm performance

Clinical Implication of Adherent Perinephric Fat in Robot-Assisted Partial Nephrectomy: Validation With Video Review

ObjectiveTo assess the impact of adherent perinephric fat (APF) on perioperative outcomes of robot-assisted partial nephrectomy (RAPN). MethodsA total of 562 Asian patients with kidney tumors received RAPN and their Mayo adhesive probability (MAP) scores were evaluated. APF was determined intraoperatively and confirmed by a second surgical video review and perioperative data were compared according to the MAP score. The associations of APF with clinical factors were examined using logistic regression analyses. Subgroup (classified according to who performed the surgery) analysis was conducted to assess if the perirenal dissection time is significantly correlated with APF. ResultsA total of 118 consecutive patients were classified into two groups according to APF. Patients in the APF group needed significantly longer perirenal fat dissection time (p < 0.001) and longer hospital stay (p = 0.028). MAP score (Odds ratio [OR]: 2.71, 95% Confidence interval [CI]: 1.56-4.71, p < 0.001), body mass index (OR: 1.24, 95% CI: 1.04-1.47, p = 0.016), and perirenal fat dissection time (OR: 1.11, 95% CI: 1.03-1.19, p = 0.004) were significantly associated with the presence of APF. Perirenal fat dissection time was significantly correlated with APF presence in two of three surgeon subgroups (ss = 8.117, p = 0.023; ss = 7.239, p = 0.011). ConclusionsPreoperative MAP score and perirenal fat dissection time were significantly associated with APF during RAPN.N

CMOS Saturated Power Amplifier With Dynamic Auxiliary Circuits for Optimized Envelope Tracking

A CMOS saturated power amplifier (PA) is developed for optimally implementing the envelope-tracking (ET) transmitter. The CMOS saturated PA is used to maximize the efficiency of the ET PA. The dynamic feedback control and the biasing techniques at the gates of the common-gate stage and the common-source of the cascode structure are proposed to improve the dynamic range, linearity and efficiency. The fully-integrated CMOS PA with a supply modulator is fabricated using a 0.18-mu m RF CMOS technology. For a long-term evolution signal at 1.85 GHz with a 10-MHz bandwidth and a 16-quadrature amplitude modulation 7.5 dB peak-to-average power ratio, the ET-based CMOS PA module delivers a power-added efficiency of 37.6%, an error vector magnitude of 2.4%, and an an evolved universal terrestrial radio access adjacent channel leakage ratio (ACLR(E-UTRA)) of -36.8 dBc at an average output power of 26.5 dBm. The proposed auxiliary circuits enable the ET-based CMOS PA to provide the significantly improved performance.111514sciescopu

Dynamic Feedback and Biasing for a Linear CMOS Power Amplifier with Envelope Tracking

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Time-delayed stochastic volatility model

We propose a multivariate stochastic volatility model with time-delayed interactions, and study its emergent dynamics. The proposed model takes the form of an agent-based model with the Cucker-Smale mechanism, time-delayed interactions and regime-switching. It exhibits a collective behavior ''flocking" emerging from the all-to-all coupling with time-delayed interactions induced by the finite propagation speed of communications. We assume that the realized volatility path switches randomly between two regimes. In this setting, we provide theoretical and numerical solutions of the proposed model and show that our proposed theoretical framework is sufficient for volatility's exponential convergence toward a constant asymptotic value. The longer time-delay makes a volatility converge faster with a lower variance, and we also fit system parameters in the model with the daily observations on stock return and volatility to show model's high prediction power in both in and out of sample tests. (C) 2021 Elsevier B.V. All rights reserved.N