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Decentralization has profound implications for many health systems. This study investigates the effect of health system decentralization in Organization for Economic Co-operation and Development (OECD) countries on public health security capacity and health service satisfaction.

Multiple linear regression analyses were employed for variables related to the level of health security capacity and satisfaction with the healthcare system while controlling for all socio-demographic variables from the European Social Survey, including over 44,000 respondents from 25 OECD countries. The Health Systems in Transition series of countries were used for assessing the decentralization level.

The result of multiple linear regression analyses showed that the level of decentralization in health systems was significantly associated with higher health security capacity (ß-coefficient 3.722, 95% confidence interval (CI) [3.536 3.908]; p=<0.001) and health service satisfaction (ß-coefficient 1.463, 95% CI [1.389 1.536]; p=<0.001) in the study. Countries with a higher level of decentralization in health policy tasks and areas were significantly likely to have higher health services satisfaction, whereas this satisfaction had a significant negative relation with the lower level of decentralization status of secondary/tertiary care services in OECD countries (ß-coefficient −5.250, 95% CI [−5.757–4.743]; p = 0.001).

This study contributes to a better understanding of the extent to which decentralization of health services affects public health safety capacity and satisfaction with health services, whereas the level of decentralization in OECD countries varies considerably. Overall, the findings highlight the importance of public health security and satisfaction with health care delivery in assessing the effects of decentralization in health services.

The purpose of this study is to identify organisational homeostasis factors in the context of healthcare organisations and to develop a conceptual model for green transformation.

The organisational homeostasis factors were determined by review of literature study and the opinions of healthcare experts. Scheduled interviews and closed-ended questionnaires are employed to collect data for this research. This study employed “TISM methodology” and “MICMAC analysis” to better comprehend how the components interact with one another and prioritise them based on their driving and dependence power.

This study identified 10 factors of organisational homeostasis in healthcare organisation. Recognition of interdependence, hormesis, strategic coalignment, consciousness on dependence of healthcare resources and cybernetic principle of regulations are the driving or key factors of this study.

The study's primary focus was on the organisational homeostasis factors in healthcare organisations. The methodological approach and structural model are used in a healthcare organisation; in the future, these approaches can be applied to other industries as well.

The key drivers of organisational homeostasis and the identified factors will be better comprehended and understood by academic and important stakeholders in healthcare organisations. Prioritizing the factors helps the policymakers to comprehend the organisational homeostasis for green transformation in healthcare.

In this study, the TISM and MICMAC analysis for healthcare is proposed as an innovative approach to address the organisational homeostasis concept in the context of green transformation in healthcare organisations.

The purpose of this study is to investigate the impact of rapid internationalization by emerging-market multinational enterprises (EMNEs) on their innovation performance. It also seeks to identify any potential moderating factors that could influence this relationship.

By analyzing data from listed Chinese MNEs from 2012 to 2022, this study applies a negative binomial regression model to test the research hypotheses.

This study uncovers an inverted U-shaped relationship between the internationalization speed of EMNEs and their innovation performance. It also suggests that strong absorptive, learning and managerial capacities could play positive moderating roles in the effect of internationalization speed on EMNEs’ innovation performance.

This study highlights rapid global expansion, promoting new knowledge acquisition for EMNEs. However, due to time-compression dilemmas with limited EMNE firm-specific advantages, overly accelerated internationalization hinders learning effectiveness. Additionally, this study reveals the critical importance of three firm-specific capacities in EMNEs – absorptive, learning and managerial capacities – in efficiently assimilating newly acquired knowledge from foreign markets and enhancing their innovation performance through rapid internationalization.

The issue of energy efficiency is becoming increasingly prevalent globally due to factors such as the expansion of the population, economic growth and excessive consumption that is not sustainable in the long run. Additionally, healthcare facilities and hospitals are facing challenges as their operational costs continue to rise. The research aim is to develop strategic frameworks for managing green hospitals, towards energy efficiency and corporate governance in hospitals and healthcare facilities.

This research employs a qualitative case study approach, with a sample of ten hospitals examined through interviews with senior management, executives and healthcare facilities managers. Relevant data was also collected from literature and analysed through critical appraisal and content analysis. The research methodology is based on the use of grounded theory research methodologies to build theories from case studies.

The research developed three integrated conceptual strategic frameworks for managing hospitals and healthcare facilities towards energy efficiency, green hospital initiatives and corporate governance. The research also outlined the concepts of green hospitals and energy efficiency management systems and best practices based on the conclusions drawn from the investigated case studies.

The study is limited to the initiatives and experiences of the healthcare facilities studied in the Middle East and North Africa (MENA) region.

The research findings, conclusions, recommendations and proposed frameworks and concepts contribute significantly to the existing body of knowledge. This research also provides recommendations for hospital managers and policymakers on how to effectively implement and manage energy efficiency initiatives in healthcare facilities.

The build-up of large-scale COVID-19 testing required an unprecedented effort of coordination within decentralized healthcare systems around the world. The aim of the study was to elucidate the challenges of vertical policy coordination between non-political actors at the national and regional levels regarding this policy issue, using Sweden as our case.

Interviews with key actors at the national and regional levels were analyzed using an adapted version of a conceptualization by Adam et al. (2019), depicting barriers to vertical policy coordination.

Our results show that the main issues in the Swedish context were related to parallel sovereignty and a vagueness regarding responsibilities and mandates as well as complex governmental structures and that this was exacerbated by the unfamiliarity and uncertainty of the policy issue. We conclude that understanding the interaction between the comprehensiveness and complexity of the policy issue and the institutional context is crucial to achieving effective vertical policy coordination.

Many studies have focused on countries’ overall pandemic responses, but in order to improve the outcome of future pandemics, it is also important to learn from more specific response measures.

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.

The lean startup approach (LSA) is extensively utilized by early-stage entrepreneurs, with “pivot” serving as a key pillar. However, there is a research gap concerning the boundary conditions impacting LSA and pivot decisions, especially when addressing societal challenges, as in the context of transformational entrepreneurship. In this regard, the healthcare sector, further compounded by a lack of research on startups and scale-ups, presents an embraced opportunity to provide multiple contributions for both theory and practice.

The present investigation employs a grounded approach to explore the experiences of the co-founders of a fast-growing Italian e-health startup. A narrative strategy was employed to organize conditions and evolving strategic action/interactions into three different pivoting phases of the startup – before the pivot, its enactment and aftermath – with primary and secondary data collected over a period of one year.

Pivoting in digital healthcare unfolded as a liminal experience marked by factors such as high regulation, multiple stakeholders, technological and symbolic ambivalence, resource-intensive demands and institutional actors acting as pathway pioneers, leading to an information overload and unforeseeable uncertainty to manage. These factors challenge entrepreneurs' ability to attain optimal distinctiveness, presenting the paradoxical need for vertical flexibility for scaling up.

By uniquely illuminating the sector’s constraints on entrepreneurial phenomena, this study provides a valuable guide for entrepreneurs and institutional actors in addressing societal challenges.

This study introduces a process model of transformational information crafting when pivoting, highlighting the role of entrepreneurs' transformational stance and platform-mediated solutions as engines behind strategies involving information breaking and transition, preceding knowledge-driven integration strategies.

Organizations have increasingly been compelled to engage in ecological businesses in recent decades, necessitating identifying environmental practices contributing to enhanced sustainability. One of the main reasons for doing this research is to see how far down the path to green transformational leadership (GTFL) in Green Human Resource Management (GHRM) practices in the healthcare industry in Pakistan. Additionally, this research aims to analyze how this change affects the long-term success of businesses in sustainable performance (SP).

To identify factors related to the study variables, the research utilized master journals, as well as the Web of Science and Scopus databases. The ISM-DEMATEL (Interpretive Structural Modeling - Decision Making Trial and Evaluation Laboratory) technique was employed to establish a hierarchical model. This model facilitated the identification of cause-and-effect relationships among factors, which were further elucidated using the DEMATEL interrelationship diagram.

The analysis of the results indicates that Green Training (F4), Green Job Analysis (F1), Intellectual Stimulation (F10), and Green Product Innovation (F9) are the primary factors that have a significant impact on achieving Environmental Policies and Regulations (F13), and Subjective Environment Norms (F14) of SP factors.

The study is implemented in the healthcare industry of Pakistan, with a focus on practical and managerial aspects. It encourages managers to develop and adapt their human resources policies and environmental strategies. Implementing safety health standards is crucial to mitigate the detrimental effects on the environment. The research was carried out during the period of the pandemic. The scope of this study was restricted to the healthcare industry in Pakistan.

In order to improve SP, this study presents a unique strategy combining sustainability into decision-making procedures with the function of GTFL in GHRM. Implementing safety health standards is crucial to mitigate the detrimental effects on the environment.

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.

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.