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I examine social capital's impact on financial reports. Based on the social capital literature, I predict that the quality of the financial reports is higher when a firm is headquartered in a region with high social capital. Consistent with this prediction, I find that the firms that are headquartered in this type of region in the USA have a lower probability of committing fraud by misrepresenting financial information. Further, I find that the firms in regions with high social capital have lower levels of discretionary accruals and much more readable annual reports.

PurposeThe author aims to study and predict the sustainability governance performances of firms using an advanced grey prediction model. The case implication of the prediction model is also studied considering select firms in the Indian context.Design/methodology/approachThe author has proposed an advanced grey prediction model, the first-entry grey prediction model (FGM (1, 1)) for forecasting the sustainability governance performances of firms. The proposed model is tested using the periodic data of sustainability governance performances of 10 Indian firms.FindingsThe author observes that the majority of firms (6 out of 10) show dipping performances for sustainability governance for the future predicted period. This throws insights into the direction of improving good governance practices for Indian firms.Practical implicationsThe idea and motivation for sustainability-focussed governance need a bi-directional focus from the side of managers that act as the agents and from the side of shareholders that act as the principals, as seen from an agency theory perspective for sustainability governance.Social implicationsSustainability governance culture can be inculcated to a firm at the strategic level by having a bi-directional focus from managers and shareholders, so as to enhance the social and environmental sustainability performances.Originality/valueThe governance performance evaluations for firms particularly in developing countries were not dated back more than a decade or two. Hence, the author implements a prediction model that can be best suited, when there are small periodic data sets available for prediction.

The empirical literature that examines cross-national patterns of state repression seeks to discover a set of political, economic, and social conditions that are consistently associated with government violations of human rights. Null hypothesis significance testing is the most common way of examining the relationship between repression and concepts of interest, but we argue that it is inadequate for this goal, and has produced potentially misleading results. To remedy this deficiency in the literature we use cross-validation and random forests to determine the predictive power of measures of concepts the literature identifies as important causes of repression. We find that few of these measures are able to substantially improve the predictive power of statistical models of repression. Further, the most studied concept in the literature, democratic political institutions, predicts certain kinds of repression much more accurately than others. We argue that this is due to conceptual and operational overlap between democracy and certain kinds of state repression. Finally, we argue that the impressive performance of certain features of domestic legal systems, as well as some economic and demographic factors, justifies a stronger focus on these concepts in future studies of repression.

Many visualisations used in the climate communication field aim to present the scientific models of climate change to the public. However, relatively little research has been conducted on how such data are visually processed, particularly from a behavioural science perspective. This study examines trends in visual attention to climate change predictions in world maps using mobile eye-tracking while participants engage with the visualisations. Our primary aim is to assess engagement with the maps, as indicated by gaze metrics. Secondary analyses assess whether social context (as social viewing compared to solitary viewing) affects these trends, the relationship between projection types and visual attention, compare gaze metrics between scientific map and artwork viewing, and explore correlations between self-reported climate anxiety scores and attention patterns. We employed wearable, head-mounted eye-tracking to collect data in relatively naturalistic conditions, aiming to enhance ecological validity. In this research, participants engaged with ten world maps displaying near- and far-term climate projections across five data categories, adapted from the online interactive atlas provided by the International Panel on Climate Change (IPCC). To compare scientific information processing with aesthetic perception, participants also viewed two large-scale artworks. Responses to the Climate Change Anxiety Scale (CCAS) were also collected. Participants viewed the displays alone (single-viewing condition, N = 35) or together with a partner (paired-viewing condition, N = 12). Results revealed that the upper parts of the maps, particularly the continental Europe, received significant attention, suggesting a Euro-centric bias in viewing patterns. Spatial gaze patterns were similar between single and paired conditions, indicating that the visual attributes of the maps predominantly shaped attention locations. Although dwell times were comparable, the paired condition showed higher fixation counts, shorter average fixation durations, and longer scanpaths, suggesting a potentially dissociable viewing strategy and more exploratory viewing patterns influenced by social interaction. No substantial differences were observed in attention across projection timeframes or types, although individual variations were noted. Artwork viewing exhibited notably shorter average fixation durations compared to climate map viewing, potentially reflecting different visual engagement styles. Despite positive linear correlations among the four CCAS subscales, there was no apparent correlation between CCAS scores and main gaze metrics, indicating a lack of a direct relationship between self-reported anxiety and gaze behaviour. In summary, visual attention to climate change visualisations appears to be mainly influenced by the inherent visual attributes of the maps, but the social context may subtly influence visual attention. Additionally, the comparison with aesthetic viewing highlights relatively distinct attentional patterns in scientific versus aesthetic engagements.

This study examines the effect of the readability of firms' written communication on the behavior of sell-side financial analysts. Using a measure of the readability of corporate 10-K filings, we document that analyst following, the amount of effort incurred to generate their reports, and the informativeness of their reports are greater for firms with less readable 10-Ks. Additionally, we find that less readable 10-Ks are associated with greater dispersion, lower accuracy, and greater overall uncertainty in analyst earnings forecasts. Overall, our results are consistent with the prediction of an increasing demand for analyst services for firms with less readable communication and a greater collective effort by analysts for firms with less readable disclosures. Our results contribute to the understanding of the role of analysts as information intermediaries for investors and the effect of the complexity of written financial communication on the usefulness of this information.

Neonatal sepsis is a significant public health challenge across the globe, particularly, in low-resource settings. While early identification of at-risk patients is a recommended approach to reduce sepsis- related deaths, there is limited evidence from low-resource settings. Therefore, this study aimed to develop prediction models to estimate neonatal mortality among neonates with sepsis. The study was conducted among 975 neonates diagnosed with sepsis in the NICUs of two large hospitals in Bahir Dar city. Data were analyzed in R software, and regression analyses were performed. Receiver operating characteristic curve (ROC) and calibration plot were used to assess model performance, and internal validation was performed using bootstrapping technique. Sepsis accounted for 27.9% of neonatal deaths. Key predictors of mortality were low birth weight, late initiation of breastfeeding, gestational age, fifth-minute Apgar score, tachycardia, respiratory distress, and convulsions. The original and nomogram models demonstrated an AUC of 81.3% and 81.2%, respectively. In conclusion, the high incidence of sepsis-attributed mortality highlights the need for effective predictive tools. The nomogram, based on key clinical predictors such as low birth weight, late initiation of breastfeeding, prematurity, fifth-minute apgar score, tachycardia, respiratory distress, and convulsions, demonstrated very good discrimination, and calibration performances, These findings support the use of the model as a practical tool for early risk stratification and clinical decision-making in neonatal intensive care settings

PurposeTo address the challenges encountered in disaster responses, optimize resource utilization, minimize environmental and social impact, and ensure transparency and accountability, it is essential to review humanitarian supply chains and incorporate sustainability considerations. Humanitarian organizations can enhance their ability to deliver timely and effective assistance to those in need by continuously improving supply chain practices. Consequently, this work explores the convergence of two fast-growing domains: sustainability and humanitarian supply chain management (HSCM).Design/methodology/approachThe authors conducted a systematic literature review of peer-reviewed articles to identify the prominent research trends and themes from the two domains' interactions. The extant literature is represented under the theory, context, characteristics, and research method (TCCM) framework. The authors have utilized a stakeholder theory perspective to identify coordination and collaboration among the various stakeholders.FindingsThis study's review findings reveal five future research directions formulating this study's central themes: the role of environmental sustainability, coordination, and collaboration in building effective HSCs; the role of humanitarian aid for the responsive HSC; the influence of big data predictive analytics on the HSC performance; development and empirical validation of sustainable HSC performance framework; the role of HSC stakeholders in building effective and efficient HSCs.Originality/valueThere is no existing academic literature review available on sustainable HSCM. This review fills this void by fostering discussion about sustainable humanitarian supply chains where the authors notably propose the TCCM framework in the context of sustainable HSCM, followed by a stakeholder network.

This paper investigates whether and how the disclosure tone of earnings conference calls predicts future stock price crash risk. Using US public firms' conference call transcripts from 2010 to 2015, we find that firms with less optimistic tone of year-end conference calls experience higher stock price crash risk in the following year. Additional analyses reveal that the predictive power of tone is more pronounced among firms with better information environment and lower managerial equity incentives, suggesting that extrinsic motivations for truthful disclosure partially explain the predictive power of conference call tone. Our results shed light on the long-term information role of conference call tone by exploring the setting of extreme future downside risk, when managers have conflicting incentives either to unethically manipulate disclosure tone to hide bad news or to engage in ethical and truthful communication.