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Green transformation is more than simply a trend; it is a way of life, a set of habits, a field of knowledge and a dedication to resource conservation. Going green is surely a creative and transformative process for both individuals and organizations. This paper aims to “identify,” “analyse” and “categorise” the readiness factors for green transformation process in health care using total interpretive structural modelling (TISM) and neutrosophic-MICMAC.

To address the study objectives, the study used TISM and neutrosophic-MICMAC analysis. To identify the readiness factors, a literature study was conducted, and the factors were face-validated by the healthcare experts. The factors influence on one another were captured by using a scheduled interview with a closed ended questionnaire. The TISM addressed the identification and analysing of factors and the categorization and ranking the readiness factors is addressed by using neutrosophic-MICMAC analysis.

This study identified 11 green transformation process readiness factors for healthcare organizations. The study states that the key factors or driving factors are awareness of green governance principle, environment leadership and management, green gap analysis, information and communication technology and innovation dynamics.

The factor ranking is sensitive to the respondents’ ratings. The study relied on the past literature and experts’ opinion may result in the subjective biases. The complex nature of healthcare ecosystem challenges to capture all the factors. The study focussed on Indian hospitals.

Study significantly impacts the healthcare practitioners, academicians and policymakers by providing critical insights into the readiness factors required for the healthcare green transformation process. The study offers a better understanding of the crucial or key or driving factors that aid in embracing green and sustainable practices.

Identifying a gap in conceptual and theoretical frameworks for green transformation readiness factors in healthcare organizations and in Indian context. The study addresses this gap by aiming to create a thorough theoretical framework and highlighted by its focus on Indian hospitals.

This paper aims to characterize a sample of Lean Six Sigma (LSS) projects in healthcare settings and discuss some specificities of operational excellence (OPEX) initiatives in hospitals and healthcare organizations in the USA.

A content analysis involving a sample of 23 documents shared by US hospitals was performed in order to achieve the research objectives. Such analysis was based on a conceptual framework developed from the literature review. It was also applied to a quantitative approach, including descriptive statistics, hypothesis testing and correspondence analysis that supported the research.

Most LSSH projects were focused on business transformation and strategic improvements. Simple techniques and tools were predominant such as descriptive statistics, process mapping, 5S and spaghetti charts, usually implemented by Green Belts and Black Belts through the define, measure, analyze, improve and control (DMAIC) method. In addition to the expressive findings reported, these projects' results have been aligned with lead time and operational cost reduction, quality improvement and capacity increase.

The study adds knowledge to the OPEX literature by analyzing the Lean Six Sigma healthcare (LSSH) in hospitals and healthcare institutions in the USA. It also demonstrates that different approaches, such as the kaizen event and DMAIC project show different results according to some techniques and tools applied in the hospital environment.

The empirical evidence presented in this study provides scenery of the LSS practices in the healthcare settings, highlighting the implementation areas, outcomes, tools and techniques mostly used in the North American healthcare institutions.

Lean Six Sigma in public and private healthcare organisations has received considerable attention over the last decade. Nevertheless, such process improvement methodologies are not generalizable, and their effective implementation relies on contextual variables. The purpose of this study is to explore the readiness of Italian hospitals for Lean Six Sigma and Quality Performance Improvement (LSS&QPI), with a focus on gender differences.

A survey comprising 441 healthcare professionals from public and private hospitals was conducted. Multivariate analysis of variance was used to determine the mean scores on the LSS&QPI dimensions based on hospital type, gender and their interaction.

The results showed that public healthcare professional are more aware of quality performance improvement initiatives than private healthcare professionals. Moreover, gender differences emerged according to the type of hospital, with higher awareness for men than women in public hospitals, whereas for private hospitals the opposite was true.

This study contributes to the Lean Six Sigma literature by focusing on the holistic assessment of LSS&QPI implementation.

This study informs healthcare managers about the revolution within healthcare organisations, especially public ones. Healthcare managers should spend time understanding Lean Six Sigma as a strategic orientation to promote the “lean hospital”, improving processes and fostering patient-centredness.

This is a preliminary study focussing on analysing inter-relationship between perceived importance of soft readiness factors such as gender dynamics as a missing jigsaw in the current literature. In addition, the research advances a holistic assessment of LSS&QPI, which sets it apart from the studies on single initiatives that have been documented to date.

In this viewpoint article, the authors recognize the increased focus in health systems on co-design for innovation and change. This article explores the role of leaders and mangers in developing and enhancing a culture of trust in their organizations to enable co-design, with the potential to drive innovation and change in healthcare.

Using social science analyses, the authors argue that current co-design literature has limited focus on interactions between senior leaders and managers, and healthcare staff and service users in supporting co-designed innovation and change. The authors draw on social and health science studies of trust to highlight how the value-based co-design process needs to be supported and enhanced. We outline what co-design innovation and change involve in a health system, conceptualize trust and reflect on its importance within the health system, and finally note the role of senior leaders and managers in supporting trust and responsiveness for co-designed innovation and change.

Healthcare needs leaders and managers to embrace co-design that drives innovation now and in the future through people – leading to better healthcare for society at large. As authors we argue that it is now the time to shift our focus on the role of senior managers and leaders to embed co-design into health and social care structures, through creating and nurturing a culture of trust.

Building public trust in the health system and interpersonal trust within the health system is an ongoing process that relies upon personal behavior of managers and senior leaders, organizational practices within the system, as well as political processes that underpin these practices. By implementing managerial, leadership and individual practices on all levels, senior managers and leaders provide a mechanism to increase both trust and responsiveness for co-design that supports innovation and change in the health system.

This paper aims to improve our understanding of performance measurement systems in the health and care sector, by focussing on employee reactions to core performance measurement practices. Targets and monitoring are hypothesised to be associated with employee perceptions of job control, supportive management and job demands, which in turn, are expected to be linked to employee-wellbeing and organisational commitment.

Matched employee workplace data are extracted from a nationally representative and publicly available survey. Structural equation models are estimated.

Performance measurement systems are neither perceived as resources nor additional demands. Setting many targets and a focus on productivity can lead to negative employee outcomes, since these positively correlate with perceptions of job demands, which negatively correlate with employee wellbeing. However, monitoring financial performance and monitoring employee performance may be helpful to managers, as these are positively associated with employee perceptions of job control and supportive management, which positively correlate with job satisfaction and organisational commitment and, negatively, with anxiety. Overall, common criticisms of performance measurement systems in healthcare are questioned.

Given the lack of consensus on how performance measurement systems can influence employee experiences and outcomes, this study combines theories that argue for performance measurement systems in managing operations with models developed by psychologists to describe how perceptions of the work conditions can affect employee attitude and wellbeing. A conceptual model is therefore developed and tested, and potential direct and indirect effects of performance measurement systems in the health sector are inferred.

Due to the rapid development of artificial intelligence (AI) technology, increasing the use of AI in healthcare is critical, but few studies have explored the extent to which physicians cooperate with AI in their work to achieve productive and innovative performance, which is a key issue in operations management (OM). We conducted empirical research to answer this question.

We developed a conceptual model based on the ambidextrous perspective. To test our model, we collected data from 200 Chinese hospitals. One senior and one junior physician from each hospital participated in this research so that we could get a more comprehensive view. Based on the sample of 400 participants and the conceptual model, we examined whether different types of AI use have distinct impacts on physicians’ productivity and innovation by conducting hierarchical regression and post hoc tests. We also introduced team psychological safety climate (TPSC) and AI technology uncertainty (AITU) as moderators to investigate this topic in further detail.

We found that augmentation AI use is positively related to overall productivity and innovative job performance, while automation AI use is negatively related to these two outcomes. Furthermore, we focused on the impacts of the ambidextrous use of AI on these two outcomes. The results highlight the positive impacts of complementary use on both outcomes and the negative impact of balance on innovative job performance. TPSC enhances the positive impacts of complementary use on productivity, whereas AITU inhibits the negative impacts of automation and balanced use on innovative job performance.

In the age of AI, organizations face greater trade-offs between performance and technology management. This study contributes to the OM literature from the perspectives of operational performance and technology management in three ways. First, it distinguishes among different AI implementations and their diverse impacts on productivity and innovative performance. Second, it identifies the different conditions under which automation AI use and augmentation are superior. Third, it extends the ambidextrous perspective by becoming an early adopter of this approach to explore the implications of different types of AI use in light of contingency factors.

This literature review aims to assess the current research on healthcare job availability and skilled professionals. The objective of this research is to identify challenges caused by the imbalance between healthcare service demand and qualified professionals and propose potential solutions and future research directions.

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method was employed as the guiding framework for conducting this review. A qualitative research design analyzed 38 peer-reviewed, evidence-based research works from 50 journal publications. Inclusion criteria focused on empirical studies, observational research and comprehensive reviews published within the last ten years. Thematic and discourse analysis categorized themes and factors explored in selected publications.

The findings highlight significant challenges in the healthcare sector regarding job availability and skilled professionals. Developed countries face understaffed healthcare facilities, resulting in increased workloads and compromised care. Developing countries experience high rates of unemployment among healthcare graduates due to limited resources and mentorship.

Improving educational infrastructure, expanding training opportunities and increasing healthcare investments are crucial for nurturing a skilled workforce. Implementing effective retention policies, fostering international collaborations and addressing socioeconomic determinants can create a sustainable job market.

The healthcare sector faces critical challenges in balancing job availability and skilled professionals. Strategic solutions are proposed to create a sustainable and equitable healthcare workforce. By implementing recommendations and conducting further research, access to quality healthcare and global public health outcomes can be improved.

The objective of this study is to systematically identify, categorize and assess the driving factors and interdependencies associated with various types of healthcare waste. The study specifically focuses on waste that has been managed or is recommended for treatment through the application of Lean Six Sigma (LSS) methodologies.

To accomplish the study’s objectives, interpretive structural modeling (ISM) was utilized. This analytical tool aided in quantifying the driving power and dependencies of each form of healthcare waste, referred to as “enablers,” as well as their related variables. As a result, these enablers were classified into four distinct categories: autonomous, dependent, linkage and drivers or independents.

In the healthcare sector, the “high cost” (HC) emerges as an autonomous variable, operating with substantial independence. Conversely, variables such as skill wastage, poor service quality and low patient satisfaction are identified as dependent variables. These are distinguished by their low driving power and high dependency. On the flip side, variables related to transportation, production, processing and defect waste manifest strong driving forces and minimal dependencies, categorizing them as independent factors. Notably, inventory waste (IW) is highlighted as a salient issue within the healthcare domain, given its propensity to engender additional forms of waste.

Employing the ISM model, along with comprehensive case study analyses, provides a detailed framework for examining the complex hierarchies of waste existing within the healthcare sector. This methodological approach equips healthcare leaders with the tools to accurately pinpoint and eliminate unnecessary expenditures, thereby optimizing operational efficiency and enhancing patient satisfaction. Of particular significance, the study calls attention to the key role of IW, which often acts as a trigger for other forms of waste in the sector, thus identifying a crucial area requiring focused intervention and improvement.

This research reveals new insights into how waste variables are structured in healthcare, offering a useful guide for managers looking to make their waste-reduction strategies more efficient. These insights are highly relevant not just for healthcare providers but also for the administrators and researchers who are helping to shape the industry. Using the classification and ranking model developed in this study, healthcare organizations can more easily spot and address common types of waste. In addition, the model serves as a useful tool for practitioners, helping them gain a deeper, more detailed understanding of how different factors are connected in efforts to reduce waste.

Sexual and reproductive health (SRH) interventions demand diverse services, encompassing medical, social and psychological care to ensure the overall wellbeing of service users. In the absence of multidisciplinary response to SRH interventions, service users could be deprived of crucial SRH services, which could undermine their safety and wellbeing. Based on this knowledge, our study was designed to map the interprofessional space in primary healthcare (PHC) facilities in Ebonyi State, Nigeria that deliver SRH services.

Interviews with 20 health workers and group discussions with 72 young people aged 15–24 years provided the data for the study. We analyzed data deductively, focusing on the assessments of the presence or absence of specific professionals that are typically expected to provide different aspects of SRH services.

We found conspicuous absence of laboratory diagnostic, social care, psycho-cognitive and some medical services expected of primary care. These absences necessitated unnecessary referrals, encouraged breaches in confidentiality, undermined social care and justice, increased cost of care and discouraged young clients from utilizing SRH services provided in PHCs. Our study, therefore, emphasizes the need for integrated care in the delivery of SRH services, which would involve relevant diverse professionals contributing their expertise toward comprehensive care for SRH service users.

The study provides human resource insights toward strengthening primary healthcare in Nigeria vis-à-vis efficient delivery of SRH services to guarantee the health security of service users.