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This paper demystifies the fluid workforce phenomenon increasingly discussed in the circles of organizational innovators and explores the characteristic aspects of the fluid workforce in the healthcare sector.

We analyze the concept and provide a generic review of definitions of a fluid workforce in relation to other similar concepts established in the academic and practitioner literature, contextualize the fluid workforce phenomenon in healthcare and distinguish relevant drivers and categories of fluid workers in this sector. We also discuss the implications of a fluid workforce for healthcare organizations, drawing on the health labor market and human resource management (HRM) practices frameworks.

The fluid workforce in healthcare is not new. Today’s main novelties are related to the wide diversity of types of fluid workforce that have emerged, the expanding scale of diffusion of the fluid workforce and the emergence of digital technologies to support HRM decisions. While a fluid workforce may provide solutions to address mismatches in the supply and demand of health workers, it can also worsen working conditions, increase dual practice and have implications for existing HRM practices.

We disentangle a novel term for the public sector, healthcare and HRM literature. We discern similarities and distinctions, presenting a framework for managing and analyzing this workforce at organizational and labor market levels in the healthcare sector. Acknowledging the challenges in estimating the existing fluid workforce labor market size, we offer practical methodologies to empirically estimate its prevalence within the healthcare industry and build an agenda for future research.

This paper aims to identify the key issues that healthcare knowledge-intensive organizations (KIPOs) should focus on to define themselves as socioenvironmentally and governance responsible for integrating environmental, social, and governance (ESG) logic into their business strategy. At the same time, this provides an understanding of how healthcare KIPOs contribute to achieving the Sustainable Development Goals of the 2030 Agenda.

Taking a cue from the model developed by the World Economic Forum, an “ESG Processing Map” was constructed to identify qualitative disclosures that a healthcare company should consider when implementing sustainability logic. The aspects investigated were processed, considering national and international standards, frameworks and disclosures. The social network analysis technique was used to systemize and combine the outcomes of these processes and analyze their consistency with sustainable development.

Through the “ESG Processing Map,” 13 areas of action and 27 topics specific to the health sector were defined on which to intervene in sustainability in order to concretely help HCOs to place specific corrective and improvement actions over time concerning socioenvironmental and governance aspects.

The paper provides contribute, on the one hand, to enriching and updating the academic literature on ESG logic in a still underexplored field and, on the other hand, to provide these types of organizations with a “compass” to guide and orient their business strategies towards sustainability.

The paper investigates how the engagement of a group of actors (the volunteers), previously unexplored in service ecosystems literature, contributes to generating new co-creation activities and well-being outcomes in the healthcare service ecosystem (HSE). Moreover, the study analyses how the provision and integration of volunteers’ resources help to explain the HSE self-adjustment favouring the re-humanisation of service.

The article zooms in on the volunteers’ activities in an HSE. A qualitative approach is adopted, and an empirical investigation is grounded in data gathered from Kids Kicking Cancer (KKC) Italia, a volunteer association operating in the paediatric oncology ward of Italian hospitals. Data are collected and triangulated through in-depth interviews, volunteers’ diaries and observations. The analysis is conducted by adopting an interpretative thematic analysis technique.

The study provides a conceptual framework explaining how volunteers’ value co-creation activities influence the HSE’s self-adjustment by leading to a re-humanisation of services. The paper also contributes to the state of knowledge by identifying seven categories of volunteers’ value co-creation activities, two of which are completely new in the literature (co-responsibility and empowerment).

The paper contributes to the service research literature by identifying empirically grounded value co-creation activities extending the understanding of self-adjustment and re-humanisation of the service ecosystem.

The main aim of this study is to highlight the significance of fostering social capital and improving the quality of work life (QWL) for the well-being of healthcare workers. The second objective of this research is to address a notable gap in the current knowledge by examining the mediating influence of QWL on the relationship between work-related social capital and life satisfaction within the healthcare profession.

This study used a cross-sectional research methodology to examine the complex relationships among the variables and included a sample of 330 individuals who are employed full-time in the healthcare profession in the North Indian Region.

The study confirms all research hypotheses, showing that social capital improves work life. Thus, work-life quality improves life satisfaction significantly. The mediation analysis in this study used bootstrapping to show that work-life quality mediates the association between social capital and life satisfaction.

Addressing social support issues and using effective human resource management tactics can improve employees’ work life and satisfaction. The findings are essential in collectivistic cultures because strong workplace relationships improve professional welfare.

This study differentiates itself by analysing social capital and QWL as multi-dimensional constructs inside the workplace, ensuring the results’ correctness and validity. This study provides a distinct viewpoint for scholars and practitioners, enhancing comprehension of the correlation between life satisfaction and work-related social capital within the healthcare industry.

The present article aims to examine the development of the theoretical framework surrounding collaborative consumption (CC) standards in recent years regarding European short-stay accommodation booking platforms. The sharing economy has significantly impacted the tourist accommodation market in recent years. Starting with the use of experimental data on CCs published on Eurostat in 2019, this article analyzes the correlation between choices of CCs for short-stay accommodation, employment and the economic crisis.

A vector autoregressive panel approach was applied to investigate the correlation between CC short-stay accommodation choices using panel organization data from 561 EU regions between 2018 and 2021.

Analyzing the connection between the main data panel variables, a positive correlation was found, followed by an increasing trend in CC use. A self-multiplying effect is generated; that is, the more people use CC, the more electronic captures occur. Consequently, the improvement of CC use and knowledge-intensive activities in short-stay accommodation is strongly linked with employment and GDP.

The originality of the investigation is to examine with a cross-sectional panel data overview the reasons that can push stakeholders to adopt CC and to clearly define a new perimeter of research in terms of the endpoint of CC in short-stay accommodation. Furthermore, the study seeks to assess the end-point congruence to utilize CC as a new gamble to accelerate digital knowledge in the hospitality sector.

This study aims to investigate the combined use of System Dynamics (SD) applications in Enterprise Engineering (EE) research and practice. SD application in EE is becoming widely accepted as a tool to support decision-making processes and for capturing relationships within enterprises.

A systematic literature review (SLR) is conducted using a standard SLR method to provide a comprehensive review of existing literature. The search was conducted on ten platforms identifying 30 publications which were analysed through the use and development of a codebook.

The SLR showed that 90% of the result set consisted of peer-reviewed academic conferences and journal papers. The SLR identified a highly dispersed author set of 83 authors. Amongst these authors, Vinay Kulkarni was an active author who has co-authored up to four publications in this research area. The analysis further revealed that the combined use of SD applications and EE is an emerging research area that still needs to develop in maturity. While all phases of EE have received attention, the current research work is more focused on the design phase. The important gap between model development and implementation is identified.

The study elucidates the existing status of interdisciplinary research combining techniques from the SD and EE disciplines, suggesting future research topics that combine the strengths of these existing disciplines.

This study specifically seeks to investigate the strategic implementation of machine learning (ML) algorithms and techniques in healthcare institutions to enhance innovation management in healthcare settings.

The papers from 2011 to 2021 were considered following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. First, relevant keywords were identified, and screening was performed. Bibliometric analysis was performed. One hundred twenty-three relevant documents that passed the eligibility criteria were finalized.

Overall, the annual scientific production section results reveal that ML in the healthcare sector is growing significantly. Performing bibliometric analysis has helped find unexplored areas; understand the trend of scientific publication; and categorize topics based on emerging, trending and essential. The paper discovers the influential authors, sources, countries and ML and healthcare management keywords.

The study helps understand various applications of ML in healthcare institutions, such as the use of Internet of Things in healthcare, the prediction of disease, finding the seriousness of a case, natural language processing, speech and language-based classification, etc. This analysis would help future researchers and developers target the healthcare sector areas that are likely to grow in the coming future.

The study highlights the potential for ML to enhance medical support within healthcare institutions. It suggests that regression algorithms are particularly promising for this purpose. Hospital management can leverage time series ML algorithms to estimate the number of incoming patients, thus increasing hospital availability and optimizing resource allocation. ML has been instrumental in the development of these systems. By embracing telemedicine and remote monitoring, healthcare management can facilitate the creation of online patient surveillance and monitoring systems, allowing for early medical intervention and ultimately improving the efficiency and effectiveness of medical services.

By offering a comprehensive panorama of ML's integration within healthcare institutions, this study underscores the pivotal role of innovation management in healthcare. The findings contribute to a holistic understanding of ML's applications in healthcare and emphasize their potential to transform and optimize healthcare delivery.

This systematic review aims to examine integrating innovative work behavior through transformational leadership in the Saudi healthcare sector. A thorough literature research was carried out to address this problem.

A total of 50 papers reporting research on innovative work behavior, healthcare organizational performance and transformational leadership were included in the review.

As employees are motivated and developed, their innovative work behaviors are boosted, which improves organizational performance. It can be concluded that innovative work behavior and transformational leadership are correlated. The capacity of a healthcare company to create and execute benefits to the employees may assure service delivery efficiency in employees' performance.

This systematic review will allow contemporary advancements, efficient health status monitoring and reliable solutions that aid optimal, equal and effective treatment in Saudi’s healthcare industry.

In an innovative workplace, workers may pitch fresh ideas to their management. Hence, employees see their employer as more transformational.

The purpose of this study is to examine the role of artificial intelligence (AI) in transforming the healthcare sector, with a focus on how AI contributes to entrepreneurship and value creation. This study also aims to explore the potential of combining AI with other technologies, such as cloud computing, blockchain, IoMT, additive manufacturing and 5G, in the healthcare industry.

Exploratory qualitative methodology was chosen to analyze 22 case studies from the USA, EU, Asia and South America. The data source was public and specialized podcast platforms.

The findings show that combining technologies can create a competitive advantage for technology entrepreneurs and bring about transitions from simple consumer devices to actionable healthcare applications. The results of this research identified three main entrepreneurship areas: 1. Analytics, including staff reduction, patient prediction and decision support; 2. Security, including protection against cyberattacks and detection of atypical cases; 3. Performance optimization, which, in addition to reducing the time and costs of medical procedures, includes staff training, reducing capital costs and working with new markets.

This study demonstrates how AI can be used with other technologies to cocreate value in the healthcare industry. This study provides a conceptual framework, “AI facilitators – AI achievers,” based on the findings and offer several theoretical contributions to academic literature in technology entrepreneurship and technology management and industry recommendations for practical implication.

Given the growing significance of contemporary socio-economic and infrastructural conversations of Public-Private Partnerships (PPP), this research seeks to provide a general overview of the academic landscape concerning PPP.

To offer a nuanced perspective, the study adopts the Latent Dirichlet Allocation (LDA) methodology to meticulously analyse 3,057 journal articles, mapping out the thematic contours within the PPP domain.

The analysis highlights PPP's pivotal role in harmonising public policy goals with private sector agility, notably in areas like disaster-ready sustainable infrastructure and addressing rapid urbanisation challenges. The emphasis within the literature on financial, risk, and performance aspects accentuates the complexities inherent in financing PPP and the critical need for practical evaluation tools. An emerging focus on healthcare within PPP indicates potential for more insightful research, especially amid ongoing global health crises.

This study pioneers the application of LDA for an all-encompassing examination of PPP-related academic works, presenting unique theoretical and practical insights into the diverse facets of PPP.