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This paper aims to examine the relationship between employee dynamic capabilities (EDCs), innovative work behavior (IWB) and job performance (JP) among nurses in public hospitals in Iraq. It also determines the mediating role of IWB in the relationship between EDC and JP.

This study uses structural equation modeling via partial least squares (PLS-SEM) and bootstrapping estimation to analyze the model. A total of 425 respondents participated in the survey, though only 372 participants completed all the items in the questionnaire. Hence, 372 responses were analyzed after data screening.

This study indicates that EDC has a positive correlation with IWB among nurses in public hospitals in Iraq. It also shows that IWB has a positive relationship with JP. It further demonstrates that IWB has a positive mediating effect on the relationship between EDC and JP among nurses in Iraq’s public hospitals.

The implication of this study is that EDC can significantly predict IWB, while the latter is a significant predictor of JP among nurses in public hospitals in Iraq. Besides, the relationship between EDC and JP is significantly mediated by IWB. However, as a cross-sectional investigation showing a single snapshot in time, this study has some limitations in terms of establishing strict causality among the variables. Rather than extensive actual data, the findings are based on a log compiled by a key respondent. The findings are obtained from a survey conducted in one country, but certain variables, such as EDC, may have varying implications across different countries. Hence, future research can focus on a diverse range of countries, which could be used to ascertain the findings’ generalizability.

This study advances our understanding of the direct effect of the exploration and exploitation variables as well as the mediating effect of IWB in the relationship between EDC and JP among nurses in public hospitals in Iraq.

This research paper aimed to study the legal structure of top-performing health governance systems and compare them with the Indonesian health social security system to identify the main differences and provide recommendations for Indonesian and other developing countries’ health policymakers and administrators.

Using formative research with a conceptual approach and statute approach as method in this study. Data was gathered using the document study technique, which studies various documents, especially legal documents related to health law, linked to legal purpose theories. Moreover, the World Health Organization ranking was considered to choose the two countries (France and Singapore) with a high social health security system for comparative analysis. All data collected has been analyzed using a qualitative and theoretical basis. Content analysis was performed by analyzing the legal documents, and the regulatory framework of all three countries was deeply analyzed to draw conclusions and recommendations.

Indonesia has specific laws to implement a social security system in the health sector. However, the lack of the best medical facilities and infrastructure and weak implementation of existing laws were identified as major reasons behind the poor health security system compared to comparative countries. Also, as a developing nation Indonesian Government face budgetary pressures and huge population challenges to meet required standards. Thus, the financing approaches used by Singapore and France may help developing countries meet these challenges effectively. Therefore, there is a dire need to strengthen the social health security system all over the country with amendments to laws and ensure the implementation of prevailing laws and regulations.

Providing understanding related to the social security health system in Indonesia along with a detailed description of the sound social health security system in France and Singapore will further provide an avenue for the researchers to critically analyze this line of study to devise some valuable suggestions further and to draw loopholes in the system.

A comparative approach for legal studies in the health sector is rare. So, this research advanced the social security health system-related literature and legal studies on the health sector by using this comparative approach to develop policy insights and future research directions, which will further help the field to grow.

This paper aims to explore the intricate relationship between artificial intelligence (AI) and health information literacy (HIL), examining the rise of AI in health care, the intersection of AI and HIL and the imperative for promoting AI literacy and integrating it with HIL. By fostering collaboration, education and innovation, stakeholders can navigate the evolving health-care ecosystem with confidence and agency, ultimately improving health-care delivery and outcomes for all.

This paper adopts a conceptual approach to explore the intricate relationship between AI and HIL, aiming to provide guidance for health-care professionals navigating the evolving landscape of AI-driven health-care delivery. The methodology used in this paper involves a synthesis of existing literature, theoretical analysis and conceptual modeling to develop insights and recommendations regarding the integration of AI literacy with HIL.

Impact of AI on health-care delivery: The integration of AI technologies in health-care is reshaping the industry, offering unparalleled opportunities for improving patient care, optimizing clinical workflows and advancing medical research. Significance of HIL: HIL, encompassing the ability to access, understand and critically evaluate health information, is crucial in the context of AI-driven health-care delivery. It empowers health-care professionals, patients and the broader community to make informed decisions about their health and well-being. Intersection of AI and HIL: The convergence of AI and HIL represents a critical juncture, where technological innovation intersects with human cognition. AI technologies have the potential to revolutionize how health information is generated, disseminated and interpreted, necessitating a deeper understanding of their implications for HIL. Challenges and opportunities: While AI holds tremendous promise for enhancing health-care outcomes, it also introduces new challenges and complexities for individuals navigating the vast landscape of health information. Issues such as algorithmic bias, transparency and accountability pose ethical dilemmas that impact individuals’ ability to critically evaluate and interpret AI-generated health information. Recommendations for health-care professionals: Health-care professionals are encouraged to adopt strategies such as staying informed about developments in AI, continuous education and training in AI literacy, fostering interdisciplinary collaboration and advocating for policies that promote ethical AI practices.

To enhance AI literacy and integrate it with HIL, health-care professionals are encouraged to adopt several key strategies. First, staying abreast of developments in AI technologies and their applications in health care is essential. This entails actively engaging with conferences, workshops and publications focused on AI in health care and participating in professional networks dedicated to AI and health-care innovation. Second, continuous education and training are paramount for developing critical thinking skills and ethical awareness in evaluating AI-driven health information (Alowais et al., 2023). Health-care organizations should provide opportunities for ongoing professional development in AI literacy, including workshops, online courses and simulation exercises focused on AI applications in clinical practice and research.

This paper lies in its exploration of the intersection between AI and HIL, offering insights into the evolving health-care landscape. It innovatively synthesizes existing literature, proposes strategies for integrating AI literacy with HIL and provides guidance for health-care professionals to navigate the complexities of AI-driven health-care delivery. By addressing the transformative potential of AI while emphasizing the importance of promoting critical thinking skills and ethical awareness, this paper contributes to advancing understanding in the field and promoting informed decision-making in an increasingly digital health-care environment.

Innovation management in the healthcare sector has undergone significant evolutions over the last decades. These evolutions have been investigated from a variety of perspectives: clusters, ecosystems of innovation, digital ecosystems and regional ecosystems, but the dynamics of networks have seldom been analyzed under the lenses of entrepreneurial ecosystems (EEs). As identified by Cao and Shi (2020), the literature is silent about the organization of resource allocation systems for network orchestration in EEs. This article investigates these elements in the healthcare sector. It discusses the strategic role played by entrepreneurial support organizations (ESOs) in resource allocation and elaborates on the distinction between sponsored and nonsponsored ESOs in EEs. ESOs are active in network orchestration. The literature explains that ESOs lift organizational, institutional and cultural barriers, and support entrepreneurs' access to cognitive and technological resources. However, allocation models are not yet discussed. Therefore, our research questions are as follows: What is the resource allocation model in healthcare-related EEs? What is the role played by sponsored and nonsponsored ESOs as regards resource allocation to support the emergence and development of EEs in the healthcare sector?

The article offers an explanatory, exploratory, and theory-building investigation. The research design offers an abductive research protocol and multi-level analysis of seven (sponsored and nonsponsored) ESOs active in French healthcare ecosystems. Field research elaborates on semi-structured interviews collected between 2016 and 2022.

This article shows explicit complementarities between top-down and bottom-up resource allocation approaches supported by ESOs in the healthcare sector. Despite explicit originalities in each approach, no network orchestration model prevails. Multi-polar coordination is the rule. Entrepreneurs' access to critical technological and cognitive resources is based on resource allocation modalities that differ for sponsored versus nonsponsored ESOs. Emerging from field research, this research also shows that sponsored and nonsponsored ESOs manage their roles in different ways because they confront original issues about organizational legitimacy.

Beyond the results listed above, the main originalities of the paper relate to the instantiation of multi-level analysis operated during field research and to the confrontation between sponsored versus nonsponsored ESOs in the domain of healthcare-related innovation management. This research shows that ESOs have practical relevance because they build original routes for resource allocation and network orchestration in EEs. Each ESO category (sponsored versus nonsponsored) provides original support for resource allocation. The ESO's legitimacy is inferred either from the sponsor or the services delivered to end-users. This research leads to propositions for future research and recommendations for practitioners: ESO managers, entrepreneurs, and policymakers.

Disasters and pandemics pose challenges to health-care provision. Accordingly, the need for adopting innovative approach is required in providing care to patient. Therefore, the purpose of this study is to present telehealth as an innovative approach for providing care to patients and reducing spread of the infection and advocates for the adoption of telehealth for digitalized treatment of patients.

An integrative review methodology of existing evidence was conducted to provide implications for integration of telehealth for digitalized treatment of patients. This paper draws on Technology Organization Environment (TOE) framework to develop a model and propositions to investigate the factors that influence telehealth adoption from the perspective of the supply side and the demand side of medical services.

Findings from this study discuss applications adopted for telehealth and recommendations on how telehealth can be adopted for medical-care delivery. More importantly, the findings and propositions of this study can act as a roadmap to potential research opportunities within and beyond the pandemic. In addition, findings from this study help provide guidelines on how health practitioners can rapidly integrate telehealth into practice for public health emergencies.

This study identifies the social, technological and organizational factors that influence telehealth adoption, and opportunities of adopting telehealth during the public health emergencies. This study concludes that specific policy changes to improve integration of interoperable solutions; data security; better physical infrastructures; broadband access; better transition and workflow balance; availability of funding and remuneration; regulations and reimbursement; awareness; and training will improve telehealth adoption during public health emergencies.

The aim of this paper is to describe and detail a new workforce initiative developed by a third sector organisation: the Multi-Modality Practitioner (MMP) approach, in the provision of support for individuals and families presenting in the community with multiple and varied needs.

This paper presents a case study on a third sector organisation’s pioneering workforce initiative – the MMP approach.

The MMP approach has been developed as an alternative to existing approaches designed to address “single issues”, providing those working in the fields of health and social care and beyond, with a range of technically eclectic interventions from different modalities and approaches, to enable them to appropriately meet the needs of individuals and families presenting with multiple needs.

This case study is limited to providing a rationale for the development of the MMP approach and a description. It does not include any formal analysis as a future evaluative paper will report on an independent theory-based examination of the MMP approach via Theory of Change and Contribution Analysis methodologies.

This case study describes the innovative role that the MMP approach as a workforce innovation plays in meeting multiple needs in the community when deployed as either a stand-alone approach, or one that can be integrated with existing community-based services including, but not limited to, mental health, employability, addiction, housing, homelessness, public health and child and family services.

The MMP approach constitutes a disruptive, pionneering, client-centred, workplace innovation that is trauma-informed, relational, strengths-based and continuity of care focused, capable of supporting individuals and families with multiple needs, negating onward referral and with potential to reduce demand on public services. It also provides those working in a range of health and social care roles with the opportunity to expand their therapeutic repertoire through high-quality, multi-skilled training in evidence-based and societally important, technically eclectic interventions drawn from a range of modalities.

Pluralistic practice and multimodal theories have been in existence for over two decades, the MMP approach however, whilst sharing some of these concepts and philosophies, differs in that it provides those trained in the approach with a ‘toolkit’ of interventions that are technically eclectic, drawn from a range of modalities and approaches and aimed at meeting multiple needs in a pragmatic and accessible manner. Furthermore, the Diploma in Multi-Modality Practice is the first training course of its kind available at postgraduate level.

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.

The demand for healthcare innovation is increasing, and not much is known about how entrepreneurial firms search for and sell to customers in the highly regulated and complex healthcare market. Drawing on effectuation perspectives, we explore how entrepreneurial digital healthcare firms with disruptive innovations search for early customers in the healthcare sector.

This study uses a qualitative, longitudinal multiple-case design of four entrepreneurial Nordic telehealth firms. In-depth interviews were conducted with founders and senior managers over a period of 27 months.

We find that when customer buying conditions are highly flexible, case firms use effectual logic to generate customer demand for disruptive innovations. However, under constrained buying conditions firms adopt a more causal approach to customer search.

Managers need to gain a deep understanding of target buying environments when searching for customers. In healthcare sector markets, the degree of flexibility customers have over buying can constrain them from engaging in demand co-creation. In particular, healthcare customer access to funding streams can be a key determinant of customer flexibility.

We contribute to effectuation literature by illustrating how customer buying conditions influence decision-making logics of entrepreneurial firms searching for customers in the healthcare sector. We contribute to entrepreneurial resource search literature by illustrating how entrepreneurial firms search for customers beyond their networks in the institutionally complex healthcare sector.

Health care organizations’ decision-making for the future relies on anticipating changes. Reliable predictions are becoming increasingly difficult, creating anxiety and requires long-term adaptive planning to cope with unforeseen circumstances. The purpose of this study is to gain insights into the awareness of uncertainties that decision makers in healthcare have, particularly when making long-term investments.

This is a qualitative study with an explorative purpose. The data were collected through semi-structured and open interviews with board members of long-term care organizations.

The study revealed that respondents are most uncertain about the future financing of their real estate system. Another concern revealed is about the shortage of care professionals combined with an increasing demand for future care. Despite most decision makers do recognize uncertainties during the decision-making process, decision makers hardly address the level of these uncertainties. Although this study did find that some decision makers are aware of deep uncertainties, in terms of “unknown unknowns,” they have no actual approaches for dealing with such situations.

Decision makers at healthcare organizations are uncertain as to their ability to anticipate technological, economic, social and political developments, as well as predict future healthcare system transformations. Some decision makers are aware of deep uncertainties, in terms of “unknown unknowns” and “unidentified unknowns,” but they lack an actual approach to deal with such situations. This study examines how strategies adapt to unforeseen developments or how to deal with deep uncertainties in healthcare as complex adaptive system.

Business models (BMs) are becoming increasingly crucial for value creation in the healthcare sector. The study explores the conceptualization and application of BM concepts within the healthcare sector and investigates their evolution in emerging economies (EEs) and developed economies (DEs). This study aims to uncover these two contexts' shared characteristics and unique variances through a comparative analysis.

The paper systematically investigates and consolidates the literature on healthcare by employing the antecedents, decisions and outcomes (ADO) framework and finally examines 71 shortlisted articles published between 2003 and 2022.

The recognition of the BM within healthcare is increasing, both in EEs and DEs. EEs prioritize value creation and capture through cost efficiency, while DEs focus on innovation. Key theories employed include a resource-based view, the network theory and the theory of innovation. Case studies are commonly used as a methodology. Further research is needed to explore the decisions and outcomes of BMs.

The study adopts stringent filtration and keyword criteria, potentially excluding relevant research. Future researchers are encouraged to broaden their selection criteria to encompass a more extensive range of relevant studies.

Beyond comparing and highlighting gaps in BMs between EEs and DEs, benchmarking DE's healthcare business models (HBMs) helps healthcare organizations in EEs align their practices, mitigate risks and establish efficient healthcare systems tailored to their specific contexts. The study adopts stringent filtration and keyword criteria, potentially excluding relevant research. Future researchers are encouraged to broaden their selection criteria to encompass a more extensive range of relevant studies.

The study analyzes HBMs using an SLR framework perspective and provides practical implications for academicians and practitioners to enhance their decision-making.