Journal of Health Organization and Management最新文献

Purpose: As concerns for healthcare employee retention have grown, organizations are seeking new ways to improve employees' well-being. Drawing on the job demands-resources model, we identify two key predictors of affective well-being (i.e. leadership quality and workload) and articulate ways in which a sense of career calling moderates the main effects.

Design/methodology/approach: Responses from 396 employees working in 18 healthcare facilities in the Midwest USA were analyzed using structural equation modeling (SEM) to examine support for the hypotheses' main and moderating effects.

Findings: Results indicated that leadership quality related positively to affective well-being and workload related negatively. In addition, calling interacted with leadership quality, not workload, to influence well-being such that the stronger the calling, the weaker the relationship. In post hoc analyses, this pattern of interaction was found to apply to both measures of positive and negative affect.

Practical implications: Our study provides guidance for healthcare organizations, emphasizing the critical role of high-quality leadership in enhancing employees' well-being. Our findings help healthcare leaders identify where to focus their efforts. Specifically, the study suggests that employees with a weaker calling stand to gain the most in affective well-being from high-quality leadership.

Originality/value: This study is the first one to empirically examine the interaction effect between leadership and calling as it influences employees' well-being. Additionally, it contributes to the existing literature by examining affective well-being among healthcare workers, a combination that has been omitted by past research.

Purpose: To explore how contextual factors affect the practice of learning-oriented leadership in fragmented healthcare systems.

Design/methodology/approach: A qualitative case study using a participatory approach. Data were collected through semi-structured focus groups and interviews with leaders across hospital levels. Thematic analysis was applied.

Findings: Four contextual factors were identified: (1) multiple external drivers (why), (2) diverse actors and perspectives (who), (3) emergent, unpredictable change (how) and (4) organizational resources and support (what). The study refines the learning-oriented leadership framework in fragmented healthcare systems by emphasizing (1) cross-boundary leadership, (2) contradiction management, (3) leading for organizational learning under resource constraints and (4) differentiated leadership roles across levels.

Originality/value: By integrating empirical insights with expansive learning theory, the study advances the learning-oriented leadership framework and offers strategies for leadership and policy in complex healthcare systems.

Purpose: Research on management tool appropriation examines either the components of the tool or its nature (open or closed) separately. This article aims to enhance understanding by combining both research streams.

Design/methodology/approach: We combine two analytical frameworks: the four-dimensional model of tool appropriation (instrumental, political, cognitive, symbolic) and the concept of open and closed tools. Using a qualitative case study design, we examine the implementation of the Lebanese Hospital Accreditation System (LHAS) in a private hospital in Beirut from 2019 to 2020. Data were collected through 63 semi-structured interviews with 21 participants across three time periods.

Findings: The study reveals that the successful appropriation of LHAS depends on alternating between open and closed tool modes. The symbolic and instrumental dimensions are primarily closed to ensure legitimacy and consistency, while the political and cognitive dimensions remain open to promote contextual adaptation and participation. This oscillation is guided by the dissemination of an organizing vision, actively shaped by the hospital's CEO and communicated by empowered middle managers.

Research limitations/implications: Our study addresses a significant research gap by combining two distinct yet complementary approaches to tool appropriation that are often treated separately. Our findings reveal a unique relationship between the four dimensions of the tool appropriation process and offer a more nuanced understanding of malleable tools. Our findings enhance appropriation guided by a deliberate organizing vision and offer insights for overcoming the paradoxes of openness and closure and avoiding inconsistencies and tensions that could lead to inertia or weak arrangements when tool appropriation is deployed in pluralistic organizations.

Practical implications: The findings offer valuable insights for healthcare managers regarding the management of accreditation by maintaining consistency in core values while allowing flexibility in implementation. Transparent communication and empowering middle management are critical enablers.

Social implications: Our case allows us to suggest managerial implications that address the societal challenge of improving patient service quality. First, CEO leadership is essential for envisioning changes through daily activities. Second, CEOs should appoint and support middle managers in both spreading the vision and facilitating negotiations.

Originality/value: The study introduces the concept of a "selectively open" management tool and highlights the dynamic interplay among various dimensions of appropriation. It contributes to the literature by bridging rationalist and constructivist perspectives while offering a nuanced view of organizational change in pluralistic context

Purpose: Advancements in science and technology have integrated artificial intelligence (AI) into dentistry, improving treatment processes, operational efficiency, and clinical outcomes. However, AI adoption among dentists remains underexplored, hindering progress in oral healthcare. This study aims to identify key barriers to AI adoption and examine factors influencing dentists' intention to use AI.

Design/methodology/approach: A quantitative cross-sectional approach was employed, utilizing self-administered questionnaires distributed online and across various dental clinics and hospitals in Ankara, Turkey. A total of 440 dentists participated in the study. Data analysis was conducted using SPSS and SmartPLS.

Findings: The study found that AI-anxiety negatively affects the intention to adopt AI in dentistry, showing a medium (almost large) effect that is stronger than other UTAUT factors such as performance expectancy, effort expectancy, and social influence, which demonstrated only small effects. Dentists with higher anxiety about learning and sociotechnical blindness are less likely to adopt AI, while concerns about job replacement and AI-configuration have less but still significant impact.

Research limitations/implications: These results contribute to the growing body of knowledge on technology adoption in oral healthcare and provide practical implications for technology developers, policymakers, and other stakeholders seeking to facilitate AI integration in dentistry.

Originality/value: This study provides novel insights into AI adoption in dentistry, offering guidance for future development and integration, and addressing a critical research gap in a growing field-particularly in Turkey, where implementation is still in its early stages.

Purpose: As healthcare business organizations face mounting pressure from civil society to act responsibly, they are expanding and strategically restructuring their CSR activities. Under the umbrella of CSR, cause-related marketing (CRM) campaigns are a means of fundraising available to healthcare firms engaging in socially responsible activities to improve global health. While healthcare organizations increasingly emphasize CSR implementation, its precise nature within the context of CSR authenticity has not been systematically investigated. Adopting self-compassion theory as a platform, this study has demonstrated novel relationships for gaining deeper insights into the key predictors of CSR authenticity in healthcare organizations.

Design/methodology/approach: The authors collected 882 responses and adopted the hybrid SEM-IPMA-ANN (Structural Equation modelling- Importance Performance Map Analysis- Artificial Neural Network) method to confirm the proposed model's significant predictors influencing CSR authenticity.

Findings: The findings provide an extended knowledge of self-compassion theory, thus contributing to the extant literature on CSR domain and healthcare marketing. The ANN findings established that social connectedness was the strongest predictor of CSR authenticity, followed by trust in the CRM campaign, isolation, mindfulness, common humanity, self-kindness, over-identification, and self-judgement. The IPMA result, consistent with ANN findings, revealed that social connectedness and trust in CRM campaigns were of relatively higher importance when predicting CSR authenticity.

Originality/value: The study contributes to our knowledge, and the findings would have implications for CSR practitioners in developing effective CRM campaigns for healthcare organizations. The conclusions would offer invaluable intelligence to CRM marketers, healthcare service practitioners, ad-campaign business professionals, and non-profit managers to manage critical and informed decisions.

Purpose: Healthcare professionals working in medico-social institutions encounter significant physical and psychological challenges that can compromise their overall well-being. This study aims to investigate the impact of interventions based on the Snoezelen approach in mitigating psychosocial risks, particularly stress.

Design/methodology/approach: A qualitative exploratory pilot study was employed, utilizing non-directive interviews with 66 healthcare professionals. The study aimed to gather in-depth insights into participants' subjective experiences and perceptions of Snoezelen-based interventions.

Findings: Participants reported that Snoezelen environments fostered relaxation, emotional regulation, and a sense of personal renewal. Key themes included the creation of a calming sensory atmosphere, facilitation of emotional release, reduction of inner tension and strengthened interpersonal connections. These experiences collectively contributed to improved stress management and workplace well-being.

Research limitations/implications: As the data are based on self-reported experiences from a specific group, generalizability may be limited. Future research could investigate the long-term effects and broader applications across diverse healthcare contexts.

Practical implications: The findings suggest that incorporating Snoezelen spaces or similar interventions into medico-social institutions could serve as a valuable strategy for reducing stress and providing professional support.

Social implications: Enhancing the well-being of healthcare workers through sensory-based approaches can lead to improved service quality, benefiting both staff and users of medical and social institutions.

Originality/value: This study offers original empirical data on the use of Snoezelen interventions among healthcare professionals, an area that has received limited attention. It contributes to the literature by emphasizing the value of sensory-based, non-directive approaches to promote professional well-being.

Purpose: This study refines equity theory by explaining the mediating roles of job frustration and job dissatisfaction, as well as the moderating role of personal income in the relationship between discriminatory workplace favoritism and hospital employees' intent to quit.

Design/methodology/approach: The study consists of two samples. In the first sample, survey questionnaires were administered to 267 public hospital employees in Turkey. In the second sample, 1,426 university healthcare students in Turkey answered four different scenarios that narrated school favoritism as well as students' frustration, dissatisfaction and intent to quit. Structural equation modeling and ANOVA statistical analyses were conducted.

Findings: Workplace favoritism positively affected employees' intent to quit through the mediation of job frustration and job dissatisfaction. The mediating role of job frustration between workplace favoritism and intent to quit was stronger for high-income than for low-income employees and students.

Practical implications: Favoring one employee may result in voluntary organizational exit by other employees, which is costly for the organization. Favoritism may encourage employees who were not previously prone to favoritism to seek favoritism. This may create a cycle that spreads favoritism further within the organization.

Originality/value: This is the first study to investigate the role of income in the relationship between workplace favoritism and employees' intent to quit.

Purpose: In a world marked by systemic challenges, innovative performance management approaches are needed to enhance the detection of organizational dysfunctions and provide proactive support for undertaking timely strategy reversals. This paper explores how artificial intelligence (AI) can support the development of resilience in healthcare organizations facing increasing environmental, demographic and financial challenges.

Design/methodology/approach: The study adopts the Design Science Research Methodology (DSRM) to develop the Resilient AI Performance Optimization Framework (RAIPOF). An illustrative application supports the framework's validation.

Findings: The RAIPOF offers new insights into the use of AI in advancing healthcare resilience by providing a structured approach to integrating AI-driven tools with organizational processes. The framework embeds AI-enhanced smart key performance indicators (KPIs) - descriptive, predictive and prescriptive - into performance systems to align strategic planning with real-time operational data and resilience indicators.

Practical implications: RAIPOF equips healthcare managers with a structured approach for anticipatory decision-making, proactive resource allocation and continuous improvement, particularly in volatile and high-risk settings.

Originality/value: This study advances the literature on organizational resilience by positioning AI not merely as a technological enhancement but as a strategic enabler of adaptive governance. By bridging the gap between operational metrics and strategic foresight, the framework challenges traditional static and siloed approaches to performance management and contributes to the interdisciplinary integration of AI, health informatics and organizational theory.

Purpose: Nursing incivility remains a pervasive issue in healthcare settings, impacting nursing individuals and organizational dynamics. Drawing on ego-depletion theory, we investigate the trickle-down effects of nursing supervisor incivility on nursing employee incivility toward coworkers. It further examines state self-control resource depletion as a mediating mechanism and trait self-control as a boundary condition moderating this indirect relationship.

Design/methodology/approach: A three-wave, time-lagged and single-source data was administered to nursing staff across seven major public and private sector hospitals to empirically test the proposed moderated mediation model.

Findings: Mediation analyses reveal that supervisor incivility depletes nursing employees' state self-control resources, which in turn leads to coworker-directed incivility. Moderated mediation results further demonstrate that this indirect effect is attenuated for employees with high trait self-control, suggesting that trait self-control buffers against the depletion process and reduces the trickle-down effect.

Originality/value: We advance the nursing incivility literature by identifying a self-regulatory mechanism through which incivility cascades within healthcare teams and by emphasizing the protective role of individual differences in trait self-control. These findings offer both theoretical insights and practical implications for managing interpersonal mistreatment in hierarchical healthcare settings.

Purpose: The aim of this study is to present, from the service providers' perspective, a multi-level integrative approach toward prioritization of the factors that are important for healthcare service quality (HSQ). This is necessary to assign and apportion resources and attention to specific areas of concern and help in their improvement, leading to satisfying the overall objective of improving healthcare delivery in the Indian context.

Design/methodology/approach: We employed an integrated decision-making trial and evaluation laboratory (DEMATEL), interpretive structural modelling (ISM), and Matrice d'Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) approach to identify the key factors influencing HSQ. We classify these variables into different groups based on their influence and dependence power. Sensitivity analysis is used to verify the consistency of the responses across scenarios and the robustness of the results.

Findings: The study's findings indicate that the key factors influencing HSQ are (1) quality of medical staff (experience, education), (2) government support (funding, insurance, etc.), and (3) availability of doctors and support staff. These factors are both cause and driver factors. Sensitivity analysis indicates that the outcomes are reliable and consistent across different sample sizes.

Originality/value: Previous studies predominantly used SERVQUAL to assess HSQ from the customer's view or end-user's viewpoint, with little focus on multi-criteria decision making (MCDM). This study uniquely evaluates HSQ from the service provider's perspective using integrated MCDM methods. It also demonstrates the utility of integrated decision-making tools for tackling complex, interdependent challenges in healthcare quality enhancement.