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Learning from errors is a complex process that requires careful support. Building on affective events theory, the purpose of this paper is to explore how a supportive learning from error climate can contribute to social learning from errors through affective and cognitive error responses by individual professionals.

A total of 139 early-career auditors completed an online questionnaire consisting of validated survey scales, allowing for serial mediation analysis to compare direct and indirect effects.

Learning from error climate was directly and positively related to engagement in social learning activities after committing an error. Furthermore, the authors found a double mediation by error strain (an affective error response) and reflecting on errors (a cognitive error response) on this relationship.

Organizations can actively encourage professionals to learn from their errors by creating a supportive learning from error climate and holding professionals accountable for their errors.

The present study enriches the authors’ understanding of the mechanisms through which learning from error climate influences engagement in social learning activities. It extends prior research on learning from errors by investigating the sequential effects of engagement in error-related learning activities performed individually and in social interaction.

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.

Building information modeling (BIM) is mostly limited to the design phase where two parallel processes exist, i.e. creating 2D-drawings and BIM. Towards the end of the design process, BIM becomes obsolete as focus shifts to producing static 2D-drawings, which leads to a lack of trust in BIM. In Scandinavia, a concept known as Total BIM has emerged, which is a novel “all-in” approach where BIM is the single source of information throughout the project. This paper's purpose is to investigate the overall concept and holistic approach of a Total BIM project to support implementation and strategy work connected to BIM.

Qualitative data were collected through eight semi-structured interviews with digitalization leaders from the case study project. Findings were analyzed using a holistic framework to BIM implementation.

The Total BIM concept was contingent on the strong interdependences between commonly found isolated BIM uses. Four main success factors were identified, production-oriented BIM as the main contractual and legally binding construction document, cloud-based model management, user-friendly on-site mobile BIM software and strong leadership.

A unique case is studied where BIM is used throughout all project phases as a single source of information and communication platform. No 2D paper drawings were used on-site and the Total BIM case study highlights the importance of a new digitalized construction process.

The purpose of this study is to examine whether and how analysts’ foreign ancestral origins would have an effect on analysts’ earning forecasts in particular and ultimately on firms’ information environment in general.

By inferring analysts’ ancestral countries based on their surnames, this study empirically examines whether analysts’ ancestral countries affect their earnings forecast errors.

Using novel data on analysts’ foreign ancestral origins from more than 110 countries, this study finds that relative to analysts with common American surnames, analysts with common foreign surnames tend to have higher earnings forecast errors. The positive relation between analyst foreign surnames and earnings forecast errors is more likely to be observed for African-American analysts and analysts whose ancestry countries are geographically apart from the USA. In contrast, this study finds that when analysts’ foreign countries of ancestry are aligned with that of the CEOs, analysts exhibit lower earnings forecast errors relative to analysts with common American surnames. More importantly, the results show that firms followed by more analysts with foreign surnames tend to exhibit higher earnings forecast errors.

Taken together, findings of this study are consistent with the conjecture that geographical, social and ethnical proximity between managers and analysts affect firms’ information environment. Therefore, this study contributes to the determinants of analysts’ earnings forecast errors and adds to the literature on firms’ information environment.

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 paper aims to solve the parameter identification problem to estimate the parameters in electrochemical models of the lithium-ion battery.

The parameter estimation framework is applied to the Doyle-Fuller-Newman (DFN) model containing a total of 44 parameters. The DFN model is fit to experimental data obtained through the cycling of Li-ion cells. The parameter estimation is performed by minimizing the least-squares difference between the experimentally measured and numerically computed voltage curves. The minimization is performed using a state-of-the-art hybrid minimization algorithm.

The DFN model parameter estimation is performed within 14 h, which is a significant improvement over previous works. The mean absolute error for the converged parameters is less than 7 mV.

To the best of the authors’ knowledge, application of a hybrid optimization framework is new in the field of electrical modelling of lithium-ion cells. This approach saves much time in parameterization of models with a high number of parameters while achieving a high-quality fit.

The purpose of this paper is to propose a system dynamic simulated process model for maintenance work management incorporating the Fourth Industrial Revolution (4IR) technologies.

The extant literature in physical assets maintenance depicts that poor maintenance management is predominantly because of a lack of a clearly defined maintenance work management process model, resulting in poor management of maintenance work. This paper solves this complex phenomenon using a combination of conceptual process modeling and system dynamics simulation incorporating 4IR technologies. A process for maintenance work management and its control actions on scheduled maintenance tasks versus unscheduled maintenance tasks is modeled, replicating real-world scenarios with a digital lens (4IR technologies) for predictive maintenance strategy.

A process for maintenance work management is thus modeled and simulated as a dynamic system. Post-model validation, this study reveals that the real-world maintenance work management process can be replicated using system dynamics modeling. The impact analysis of 4IR technologies on maintenance work management systems reveals that the implementation of 4IR technologies intensifies asset performance with an overall gain of 27.46%, yielding the best maintenance index. This study further reveals that the benefits of 4IR technologies positively impact equipment defect predictability before failure, thereby yielding a predictive maintenance strategy.

The study focused on maintenance work management system without the consideration of other subsystems such as cost of maintenance, production dynamics, and supply chain management.

The maintenance real-world quantitative data is retrieved from two maintenance departments from company A, for a period of 24 months, representing years 2017 and 2018. The maintenance quantitative data retrieved represent six various types of equipment used at underground Mines. The maintenance management qualitative data (Organizational documents) in maintenance management are retrieved from company A and company B. Company A is a global mining industry, and company B is a global manufacturing industry. The reliability of the data used in the model validation have practical implications on how maintenance work management system behaves with the benefit of 4IR technologies' implementation.

This research study yields an overall benefit in asset management, thereby intensifying asset performance. The expected learnings are intended to benefit future research in the physical asset management field of study and most important to the industry practitioners in physical asset management.

This paper provides for a model in which maintenance work and its dynamics is systematically managed. Uncontrollable corrective maintenance work increases the complexity of the overall maintenance work management. The use of a system dynamic model and simulation incorporating 4IR technologies adds value on the maintenance work management effectiveness.

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).

In this study, the authors want to identify current possible causes for citing and referencing errors in scholarly literature to compare if something changed from the snapshot provided by Sweetland in his 1989 paper.

The authors analysed reference elements, i.e. bibliographic references, mentions, quotations and respective in-text reference pointers, from 729 articles published in 147 journals across the 27 subject areas.

The outcomes of the analysis pointed out that bibliographic errors have been perpetuated for decades and that their possible causes have increased, despite the encouraged use of technological facilities, i.e. the reference managers.

As far as the authors know, the study is the best recent available analysis of errors in referencing and citing practices in the literature since Sweetland (1989).

This study aims to explore how individual personal growth initiative (PGI) mediates the relationship between a positive error orientation and job crafting. Furthermore, it explores the moderating role of the feedback from the leader in this relationship.

Data was collected through a survey conducted on 209 international employees from multiple occupations.

A positive error orientation is indirectly related to job crafting through its relationship with PGI. Also, feedback from leadership has a negative effect on the relationship between a positive error orientation and PGI. Indeed, the mediation effect of PGI on the relationship between a positive error orientation and job crafting loses significance when the leadership feedback is high.

As far as job crafting is concerned, it is essential to develop an error management culture to promote proactive behaviors among individuals.

Although the literature tends to highlight the positive effects of receiving feedback from the leader on employee’s professional development, this paper highlights the potential detrimental effects of leader feedback on PGI, therefore opening a new interesting area that demands attention.