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This paper aims to assess how patient safety culture and incident reporting differs across different professional groups and between long-term and acute care. The Hospital Survey On Patient Safety Culture (HSPOSC) questionnaire was used to assess patient safety culture. Data from the organizations’ incident reporting system was also used to determine the number of reported patient safety incidents.

Patient safety culture is part of the organizational culture and is associated for example to rate of pressure ulcers, hospital-acquired infections and falls. Managers in health-care organizations have the important and challenging responsibility of promoting patient safety culture. Managers generally think that patient safety culture is better than it is.

Based on statistical analysis, acute care professionals’ views were significantly positive in 8 out of 12 composites. Managers assessed patient safety culture at a higher level than other professional groups. There were statistically significant differences (p = 0.021) in frequency of events reported between professional groups and between long-term and acute care (p = 0.050). Staff felt they did not get enough feedback about reported incidents.

The study reveals differences in safety culture between acute care and long-term care settings, and between professionals and managers. The staff felt that they did not get enough feedback about reported incidents. In the future, education should take these factors into consideration.

Patient safety focuses on minimizing risks that might occur to patients during provision of healthcare. The purpose of this study was to explore healthcare practitioners’ attitudes towards patient safety inside different hospital settings in Jeddah, Kingdom of Saudi Arabia.

A descriptive, cross-sectional study was conducted on a sample of healthcare practitioners in main hospitals in Jeddah. Two main hospitals (one governmental and one private) were selected from each region of Jeddah (east, west, north and south), with a total number of eight out of thirty hospitals. Data were collected through the Attitudes to Patient Safety Questionnaire III that was distributed online. The questionnaire used a 5-point scale. Descriptive statistics were used. Comparisons were made by independent t-test and ANOVA. The statistical significance level was set at p < 0.05.

The study included 341 healthcare practitioners of different sexes and specialties in eight major governmental and private hospitals in Jeddah. “Working hours as error cause” subscale had the highest mean score (4.03 ± 0.89), while “Professional incompetence as error cause” had the lowest mean score (3.49 ± 0.97). The total questionnaire had a moderate average score (3.74 ± 0.63). Weak correlations between the average score of the questionnaire and sex, occupation and workplace were found (−0.119, −0.018 and −0.088, respectively).

Hospitals need to develop targeted interventions, including continuing professional development programs, to enhance patient safety culture and practices. Moreover, patient safety training is required at the undergraduate education level, which necessitates health professions education institutions to give more attention to patient safety education in their curricula.

The study contributed to the existing literature on patient safety culture in hospital settings in Jeddah, Saudi Arabia. The insights generated by the study can inform targeted interventions to enhance patient safety culture in hospitals and improve patient outcomes.

Errors are inevitable, resulting from the human condition itself, system failures and the interaction of both. It is essential to know how to deal with their occurrence, managing them. However, the negative tone associated with them makes it difficult for most organizations to talk about mistakes clearly and transparently, for fear of being harmed, preventing their detection, treatment and recovery. Consequently, errors are not managed, remaining accumulated in the system, turning into successive failures. Organizations need to recognize the inevitability of errors, making the system robust, through leadership and an organizational culture of error management. This study aims to understand the role of these influencing variables in an error management approach.

In this paper, the authors applied the methodology of a quantitative nature based on a questionnaire survey that analyses error management, leadership and the organizational culture of error management of 380 workers in Portuguese companies.

The results demonstrate that leadership directly influences error management and indirectly through the organizational culture of error management, giving this last variable a mediating role.

The study covers companies from different sectors of activity on a topic that is little explored in Portugal, but part of the daily life of organizations, which should deserve greater attention from directors and managers, as they assume a privileged position to promote and develop error management mechanisms. Error management must be the daily work of leaders. This study contributes to theoretical knowledge and business practice on error management.

This study aims to understand and compare how the mechanism of innovative processes in the information technology (IT) industry – the most innovative industry worldwide – is shaped in Poland and the USA in terms of tacit knowledge awareness and sharing driven by a culture of knowledge and learning, composed of a learning climate and mistake acceptance.

Study samples were drawn from the IT industry in Poland (n = 350) and the USA (n = 370) and analyzed using the structural equation modeling method.

True learning derives from mistake acceptance. As a result of a risk-taking attitude and critical thinking, the IT industry in the USA is consistently innovation-oriented. Specifically, external innovations are highly correlated with internal innovations. Moreover, a knowledge culture supports a learning culture via a learning climate. A learning climate is an important facilitator for learning from mistakes.

This study revealed that a high level of mistake acceptance stimulates a risk-taking attitude that offers a high level of tacit knowledge awareness as a result of critical thinking, but critical thinking without readiness to take a risk is useless for tacit knowledge capturing.

Establishing the strength of a novel variable–mortgage debt as a fraction of US gross domestic product (GDP)–on forecasting capitalisation rates in both the US office and multifamily sectors.

The authors specify a vector error correction model (VECM) to the data. VECM are used to address the nonstationarity issues of financial variables while maintaining the information embedded in the levels of the data, as opposed to their differences. The cap rate series used are from Green Street Advisors and represent transaction cap rates which avoids the problem of artificial smoothness found in appraisal-based cap rates.

Using a VECM specified with the novel variable, unemployment and past cap rates contains enough information to produce more robust forecasts than the traditional variables (return expectations and risk premiums). The method is robust both in and out of sample.

This has direct implications for governmental policy, offering a path to real estate price stability and growth through mortgage access–functions largely influenced by the Fed and the quasi-federal agencies Fannie Mae and Freddie Mac. It also offers a timely alternative to interest rate-based forecasting models, which are likely to be less useful as interest rates are to be held low for the foreseeable future.

This study offers a new and highly explanatory variable to the literature while being among the only to model either (1) transactional cap rates (versus appraisal) (2) out-of-sample data (versus in-sample) (3) without the use of the traditional variables thought to be integral to cap rate modelling (return expectations and risk premiums).

This study aims to examine the micromechanisms of how knowledge culture fosters human capital development.

An empirical model was developed by using the structural equation modeling method based on a sample of 321 Polish knowledge workers employed in different industries.

This study provides direct empirical evidence that tacit knowledge sharing supports human capital, whereas tacit knowledge hiding does not, and this hiding is considered a waste of knowledge. If tacit knowledge does not circulate within an organization, it is a severe waste of an organization. The findings indicate that shame from making mistakes might impede the sharing of knowledge gained from making those mistakes, and in such cases, the knowledge remains hidden.

Leaders aiming to ensure human capital growth should implement an authentic learning culture composed of a learning climate and mistakes acceptance components that enable open discussion about mistakes on each organizational level.

The knowledge culture is found to be an essential element of building human capital but, at the same time, not sufficient without a learning culture, and its mistakes acceptance component. A permanent organizational learning mode that supports a continuous organizational shared mental model reframing is an antidote to tacit knowledge hiding.

The article investigates the patterns of asset impairment recognition in search of signs of “big bath” earnings management practices across an internationally diversified sample of public companies. It also elucidates the incentives that may underlie such practices and explores possible safeguards embedded in the existing corporate governance mechanisms.

The article applied static panel and binary logit models to an international firm-level panel dataset of 1045 public companies observed between 2003 and 2018.

Our empirical results suggest that recognition of asset impairment has no determinate impact on earnings volatility. Investigating the possibility of “big bath” earnings management practices, the authors found no impact of asset impairment recognition on total senior executive compensation in firms, which pay performance-based remuneration. The quality of corporate governance has appeared to impact the firms’ intertemporal proclivity to recognize asset impairment with those having the more entrenched and management-controlled boards being more likely to time impairment recognition by delaying it during exceptionally good and exceptionally bad years. While generally unlikely, recognition of asset impairment in a period with a recorded negative operating performance is found to be closely associated with key executive departures.

The article corroborates the salient role of corporate governance mechanisms in shaping the intertemporal patterns of asset impairment recognition. The possible remedies to the phenomenon should be derived therefrom.

The authors examine the contemporaneous and causal association between tweet features (bullishness, message volume and investor agreement) and market features (stock returns, trading volume and volatility) using 140 South African companies and a dataset of firm-level Twitter messages extracted from Bloomberg for the period 1 January 2015 to 31 March 2020.

Panel regressions with ticker fixed-effects are used to examine the contemporaneous link between tweet features and market features. To examine the link between the magnitude of tweet features and stock market features, the study uses quantile regression.

No monotonic relationship is found between the magnitude of tweet features and the magnitude of market features. The authors find no evidence that past values of tweet features can predict forthcoming stock returns using daily data while weekly and monthly data shows that past values of tweet features contain useful information that can predict the future values of stock returns.

The study is among the earlier to examine the association between textual sentiment from social media and market features in a South African context. The exploration of the relationship across the distribution of the stock market features gives new insights away from the traditional approaches which investigate the relationship at the mean.

The cardiomegaly can be determined by the cardiothoracic ratio (CTR) which can be measured in a chest x-ray image. It is calculated based on a relationship between a size of heart and a transverse dimension of chest. The cardiomegaly is identified when the ratio is larger than a cut-off threshold. This paper aims to propose a solution to calculate the ratio for classifying the cardiomegaly in chest x-ray images.

The proposed method begins with constructing lung and heart segmentation models based on U-Net architecture using the publicly available datasets with the groundtruth of heart and lung masks. The ratio is then calculated using the sizes of segmented lung and heart areas. In addition, Progressive Growing of GANs (PGAN) is adopted here for constructing the new dataset containing chest x-ray images of three classes including male normal, female normal and cardiomegaly classes. This dataset is then used for evaluating the proposed solution. Also, the proposed solution is used to evaluate the quality of chest x-ray images generated from PGAN.

In the experiments, the trained models are applied to segment regions of heart and lung in chest x-ray images on the self-collected dataset. The calculated CTR values are compared with the values that are manually measured by human experts. The average error is 3.08%. Then, the models are also applied to segment regions of heart and lung for the CTR calculation, on the dataset computed by PGAN. Then, the cardiomegaly is determined using various attempts of different cut-off threshold values. With the standard cut-off at 0.50, the proposed method achieves 94.61% accuracy, 88.31% sensitivity and 94.20% specificity.

The proposed solution is demonstrated to be robust across unseen datasets for the segmentation, CTR calculation and cardiomegaly classification, including the dataset generated from PGAN. The cut-off value can be adjusted to be lower than 0.50 for increasing the sensitivity. For example, the sensitivity of 97.04% can be achieved at the cut-off of 0.45. However, the specificity is decreased from 94.20% to 79.78%.

Given the limited studies that have started to focus on contexts where integrated reporting (IR) is voluntarily adopted, this paper aims to explore the moderating role of institutional characteristics on the association between voluntary report release and analyst forecast accuracy.

This study uses a quantitative empirical research method grounded on voluntary disclosure theory to provide empirical evidence on an international sample of companies choosing to release integrated reports. Preliminarily, a cluster analysis is used to group countries according to institutional patterns. Multivariate analyses detect the associations between report release choice and analysts’ forecast accuracy across clusters. Multiple econometric approaches are used to address the endogeneity concerns.

IR release is not informative for the market unless considering systematic variations across different institutional settings. Analysts’ forecast is more accurate for IR adopters located in strong institutional enforcement settings than for all the other companies. In the strong institutional setting that is also characterized by a pluralistic society, IR release benefits for the market are conditioned by the fact that the choice to release IR depends on environmental, governance and social disclosure-based managers remuneration and disclosure requirements. In weak institutional settings, IR release is not beneficial for the forecast accuracy.

Academics and practitioners can gain understanding of the usefulness of voluntary IR across different institutional settings.

The study advances the understanding of the IR’s informativeness, overcoming the common dichotomous distinctions between strong and weak institutional settings.