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This study demonstrates how becoming a high-reliability institution in health care is a priority, given the high-risk environment in which an error can result in harm. Literature conceptually supports the need for highly reliable health care facilities but does not show a comprehensive approach to operationalizing the concept into the daily workforce to support patients. The Veterans Health Administration closes the gap by documenting a case study that not only demonstrates specific actions and functions that create a high-reliability organization (HRO) for safety and improvement but also created a learning organization by spreading the knowledge to other facilities.

The authors instituted a methodology consisting of assessments, training and educational simulations to measure, establish and operationalize activities that identified and prevented harmful events. Visual communication boards were created to facilitate team huddles and discuss improvement ideas. Improvements were then measured and analyzed for purposeful outcomes and return on investment (ROI).

HRO can be operationalized successfully in health care systems. Measurable outcomes verified that psychological safety was achieved through the identification and participation of 3,184 process improvement projects over a five-year period, which yielded a US$2.8m ROI. Documented processes and activities were used for educational teachings, which were disseminated to other Veteran Affairs Medical Center’s through the Truman HRO Academy.

This case study is limited to one hospital in the Veterans Health Administration (VHA) network. As the VHA continues to deploy the methods outlined to other hospitals, the authors will perform incremental data collection and ongoing analysis for further validation of the HRO methods and operations. Hospitalists can adapt the methods in the case study for practical application in a health care setting outside of VHA. Although the model is rooted in health care, the methods may be adapted for use in other industries.

This case study overcomes the limitations within literature regarding operationalizing HRO by providing actual activities and demonstrations that can be implemented by other health care facilities.

Resilience as a novel concept has attracted the most attention in the management of engineering systems. The main goal of engineering systems is production assurance and increasing customer satisfaction which depends on the suitable performance of mechanical equipment. “A resilient system is defined as a system that is resistant to disruption and failures and can recover itself and returns to the state before failure as soon as possible in the case of failure.” Estimate the value of the system’s resilience to increase its resilience by covering the weakness in the resilience indexes of the system.

In this article, a suitable approach to estimating resilience in complex engineering systems management in the field of mining has been presented. Accordingly, indexes of reliability, maintainability, supportability, efficiency index of prognostics and health management of the system, and ultimately the organization resilience index, have been used to evaluate the system resilience.

The results of applying this approach indicate the value of 80% resilience if the risk factor is considered and 98% if the mentioned factors are ignored. Also, the value of 58% resilience of this organization’s management group indicates the weakness of situational awareness and weakness in the vulnerable points of the organization.

To evaluate the resilience in this article, five indicators of reliability, maintainability, and supportability are used as performance indicators. Also, organization resilience and the prognostic and health management of the system (PHM) are used as management indicators. To achieve more favorable results, the environmental and operational variables governing the system have been used in performance indicators, and expert experts' opinions have been used in management indicators.

Organizations working in high-hazard environments contribute significantly to modern society and the economy, not only for the valuable resources they hold but also for the indispensable products and services they provide, such as power generation, transportation and defense weapons. Therefore, the main purpose of this study is to develop a framework that outlines future research on systems safety and provides a better understanding of how organizations can effectively manage hazard events.

In this research, we developed the high hazard theory (HHT) and a theoretical framework based on the grounded theory method (GTM) and the integration of three established theoretical perspectives: normal accident theory (NAT), high reliability theory (HRT) and resilience engineering (RE) theory.

We focused on the temporal aspect of accidents to create a timeline showing the progression of hazard events and the factors contributing to safety and hazards in organizations. Given the limitations of the previous theories in providing a coherent explanation of hazard event escalation in high-hazard organizations (HHOs), we argue that the highlighted theories can be more complementary than contradictory regarding their standpoints on disasters and accident prevention.

A proper appreciation of the hazard nature of organizations can help reduce their susceptibility to failure, prevent outages and breakdowns of systems, identify areas for improvement and develop strategies to enhance performance.

By developing HHT, we contribute to systems safety research by developing a new, refined theory and enrich the theoretical debate. We also expand the understanding of scholars and practitioners about the characteristics of organizations working in high-hazard environments.

This study investigates how artificial intelligence (AI) chatbots persuade customers to accept their recommendations in the online shopping context.

Drawing on the elaboration likelihood model, this study establishes a research model to reveal the antecedents and internal mechanisms of customers' adoption of AI chatbot recommendations. The authors tested the model with survey data from 530 AI chatbot users.

The results show that in the AI chatbot recommendation adoption process, central and peripheral cues significantly affected a customer's intention to adopt an AI chatbot's recommendation, and a customer's cognitive and emotional trust in the AI chatbot mediated the relationships. Moreover, a customer's mind perception of the AI chatbot, including perceived agency and perceived experience, moderated the central and peripheral paths, respectively.

This study has theoretical and practical implications for AI chatbot designers and provides management insights for practitioners to enhance a customer's intention to adopt an AI chatbot's recommendation.

1. The study investigates customers' adoption of AI chatbots' recommendation.

2. The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

3. The central and peripheral cues are generalized according to cooperative principle theory.

4. Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

5. Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

6. Customers' mind perception positively moderates the central and peripheral paths.

The study investigates customers' adoption of AI chatbots' recommendation.

The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

The central and peripheral cues are generalized according to cooperative principle theory.

Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

Customers' mind perception positively moderates the central and peripheral paths.

This study investigates the relationships between data governance (DG), business analytics capabilities (BAC), and decision-making performance (DMP), with a focus on the mediating effects of big data literacy (BDL) and data analytics competency (DAC).

The study was conducted with 178 experienced managers in public service organizations, using a quantitative approach. Structural equation modeling (SEM) and mediation tests were employed to analyze the data.

The findings reveal that DG and BDL are critical antecedents for developing analytical capabilities. Big data literacy mediates the relationship between DG and BAC, while BAC mediates the relationship between DG and DMP. Furthermore, DAC mediates the relationship between BA capabilities and DMP, explaining most of the effect of BAC on DMP.

These results highlight the importance of DG in fostering BDL and analytical skills for improved decision-making in organizations.

By prioritizing DG practices that promote BDL and analytical capabilities, organizations can leverage business analytics to enhance decision-making.

Synthesizing theories of leadership, organizational fairness and organizational citizenship behaviour (OCB). This study explores how overall organizational fairness affects OCB by considering the mediating role of organization-based self-esteem (OBSE) and the moderating role of authentic leadership.

In two phases, survey data were collected from 79 job incumbents at a financial company.

The findings suggest that authentic leadership significantly affects the relationship between overall fairness perceptions and OCB. Moreover, OBSE was found to act as a mediator in this relationship.

Authentic leadership and organizational self-esteem play crucial roles in fostering a fair work environment that encourages employees to engage in citizenship behaviour. These findings underscore the importance of authentic leadership and OBSE in creating a fair work environment. These findings have implications for human resource management practices and leadership development programs.

Scholars in organizational behaviour have posited that fairness in the workplace is critical to facilitating effective leadership. However, more research is needed to investigate the interplay and mediating effects of fairness and leadership. The present study offers novel insights into the mediating mechanism of OBSE and its critical role in explaining the positive impact of overall fairness on employees’ OCB.

This study examines the correlation between ownership structure (OS) and financial reporting integrity (FRI), with emphasis on the impact of earnings quality (EQ) in the Egyptian context.

The study uses data from 472 firm-year observations of Egyptian publicly listed companies between 2014 and 2021 and carried out descriptive statistics, correlation tests, multiple regression analysis and two-stage least squares (2SLS) to test the hypotheses.

The results revealed that blockholders and institutional ownership significantly enhance reporting integrity through effective oversight and monitoring. The findings underscore the vital role of concentrated OS in overseeing reporting practices and mitigating managerial opportunism, thereby improving the transparency and reliability of financial disclosures in Egypt.

The findings enrich the literature on corporate governance and financial reporting quality and have important implications for policymakers, regulators and corporate stakeholders.

This work contributes valuable insights on how OS and EQ can bolster FRI, offering crucial information for combating financial crises and facilitating smooth business operations in Egypt.

Information security (InfoSec) policy violations are of great concern to all organisations worldwide, especially in the financial industry. Although the importance of InfoSec policy has been highlighted for many decades, InfoSec breaches still occur due to a low level of employee compliance and a lack of engagement and competence in high-level management. However, previous studies have primarily investigated the behavioural aspects of InfoSec policy compliance at the individual level rather than the managerial factors involved in constructing InfoSec policy and developing its effectiveness. Thus, drawing on neo-institutional theory and a transformational leadership framework, this research investigated the influence of external mechanisms and transformational leadership on InfoSec policy effectiveness.

The research model was implemented using field survey data from professional managers in the financial sector.

The results reported that neo-institutional mechanisms and transformational leadership shape InfoSec policy effectiveness in an organisation.

This study broadens current InfoSec policy research from an individual level to a managerial perspective and enhances the existing literature on neo-institutional and transformational leadership in the context of InfoSec. It highlights the need to evaluate InfoSec policy based on external factors and to support transformational leadership styles that promote InfoSec policy enforcement and effectiveness.

Drawing on the conservation of resources (COR) theory, this study aims to examine the effects of servant leadership and despotic leadership on employees’ happiness at work (HAW) through job crafting.

To test the hypothesized relationships, the data were collected from 309 Pakistani employees. Structural equation modeling was used to analyze the data.

The findings showed that servant leadership is an optimal leadership style for creating employees’ HAW. In addition, job crafting was found to mediate the effects of servant leadership on employees’ broad-based positive attitudinal outcome (HAW). Moreover, results showed that despotic leadership negatively influences employees’ HAW through job crafting.

This study is novel as it investigates how newer forms of positive (servant) and negative (despotic) leadership styles influence employees’ multidimensional attitudinal outcome (HAW) via job crafting. By doing so, this research extends the nomological network of servant leadership, despotic leadership, job crafting and HAW.

Drawing on the signaling theory and technology acceptance model, the main purpose of this study was to predict prospective employees' intentions to apply for jobs in a firm, with a special focus on the mediating role of attitudes toward corporate websites and the moderating role of perceived value fit.

Collecting data from a convenient sample of 318 prospective job candidates, the research hypotheses were tested using structural equation modeling (SEM) with AMOS (version 24) and SPSS Process Macro (version 3.4).

The test results revealed that prospective employees' attitudes toward corporate websites partially mediate the association of corporate reputations, perceived ease of use and perceived usefulness with their intentions to apply for jobs in an organization. Noticeably, perceived value fit moderated the perceived usefulness–application intentions link in such a way that the impact of perceived usefulness on intentions to apply appears higher for individuals with a low level (than a high level) of perceived value fit.

Consistent with the research findings, a notable theoretical contribution and practical implications for HR professionals have been discussed. This paper ends with outlining some limitations and future research directions.

Despite having the salient buffering effects of perceived value fit on the applicant attraction process, empirical study on this theoretical phenomenon is still sparse in a pre-employment context. This may be the first study that demonstrates under what circumstances prospective employees' job pursuit intentions could be optimized in respect of their perceived value fit within a single framework comprised of two theories.