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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.

The goal of this article is to provide an overview of healthcare entrepreneurship, both in terms of its current trends and future directions.

The article engages in a systematic review of extant research on healthcare entrepreneurship using the scientific procedures and rationales for systematic literature reviews (SPAR-4-SLR) as the review protocol and bibliometrics or scientometrics analysis as the review method.

Healthcare entrepreneurship research has fared reasonably well in terms of publication productivity and impact, with diverse contributions coming from authors, institutions and countries, as well as a range of monetary and non-monetary support from funders and journals. The (eight) major themes of healthcare entrepreneurship research revolve around innovation and leadership, disruption and technology, entrepreneurship models, education and empowerment, systems and services, orientations and opportunities, choices and freedom and policy and impact.

The article establishes healthcare entrepreneurship as a promising field of academic research and professional practice that leverages the power of entrepreneurship to advance the state of healthcare.

The article offers a seminal state of the art of healthcare entrepreneurship research.

This study aims to examine current research on the relationship between Operational Excellence and Healthcare 4.0 (H4.0) for healthcare organizations.

The authors have performed a systematic literature review of 102 documents published between 2011 and 2022 from the Scopus database to identify the research trends on Operational Excellence and H4.0. Through a descriptive bibliometric analysis, this study has highlighted the year-wise trend in publication, top authors, prominent sources of publications, the country-wise spread of research activities and subject area analysis. Furthermore, through content analysis, this study has identified four clusters and proposed directions for future research of each identified cluster.

Results reflect overall growth in this area, with a few parts of the world being underrepresented in research related to Operational Excellence and H4.0. The content analysis focused on describing challenges pertaining to healthcare industries and the role of Operational Excellence tools and H4.0 technologies in dealing with various healthcare delivery aspects. The authors concluded their analysis by proposing a theoretical framework and providing theoretical and managerial implications of the study.

To the best of the authors’ knowledge, the paper is one of the first to analyze the existing literature on the healthcare sector at the interface of Operational Excellence and H4.0 technologies. The conceptual framework and cluster-wise future research prepositions are some of the unique offerings of the study.

The purpose of this study is to introduce new tools to develop a more precise and focused bibliometric analysis on the field of digitalization in healthcare management. Furthermore, this study aims to provide an overview of the existing resources in healthcare management and education and other developing interdisciplinary fields.

This work uses bibliometric analysis to conduct a comprehensive review to map the use of the unified theory of acceptance and use of technology (UTAUT) and the unified theory of acceptance and use of technology 2 (UTAUT2) research models in healthcare academic studies. Bibliometric studies are considered an important tool to evaluate research studies and to gain a comprehensive view of the state of the art.

Although UTAUT dates to 2003, our bibliometric analysis reveals that only since 2016 has the model, together with UTAUT2 (2012), had relevant application in the literature. Nonetheless, studies have shown that UTAUT and UTAUT2 are particularly suitable for understanding the reasons that underlie the adoption and non-adoption choices of eHealth services. Further, this study highlights the lack of a multidisciplinary approach in the implementation of eHealth services. Equally significant is the fact that many studies have focused on the acceptance and the adoption of eHealth services by end users, whereas very few have focused on the level of acceptance of healthcare professionals.

To the best of the authors’ knowledge, this is the first study to conduct a bibliometric analysis of technology acceptance and adoption by using advanced tools that were conceived specifically for this purpose. In addition, the examination was not limited to a certain era and aimed to give a worldwide overview of eHealth service acceptance and adoption.

The goal of this research is to analyse the obstacles to the implementation of mobile health (mHealth) in India and to gain an understanding of the contextual inter-relationships that exist amongst those obstacles.

Potential barriers and their interrelationships in their respective contexts have been uncovered. Using MICMAC analysis, the categorization of these barriers was done based on their degree of reliance and driving power (DP). Furthermore, an interpretive structural modeling (ISM) framework for the barriers to mHealth activities in India has been proposed.

The study explores a total of 15 factors that reduce the efficiency of mHealth adoption in India. The findings of the Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC) investigation show that the economic situation of the government, concerns regarding the safety of intellectual technologies and privacy issues are the primary obstacles because of the significant driving power they have in mHealth applications.

Promoters of mHealth practices may be able to make better plans if they understand the social barriers and how they affect each other; this leads to easier adoption of these practices. The findings of this study might be helpful for governments of developing nations to produce standards relating to the deployment of mHealth; this will increase the efficiency with which it is adopted.

At this time, there is no comprehensive analysis of the factors that influence the adoption of mobile health care with social cognitive theory in developing nations like India. In addition, there is a lack of research in investigating how each of these elements affects the success of mHealth activities and how the others interact with them. Because developed nations learnt the value of mHealth practices during the recent pandemic, this study, by investigating the obstacles to the adoption of mHealth and their inter-relationships, makes an important addition to both theory and practice.

The mental healthcare is experiencing an ever-growing surge in understanding the consumer (e.g., patient) engagement paradox, aiming to vouch for the quality of care. Despite this surge, scant attention has been given in academia to conceptualize and empirically investigate this particular aspect. Thus, drawing on the Stimulus-Organism-Response (S-O-R) paradigm, the study explores how patients engage with healthcare service providers and how they perceive the quality of the healthcare services.

Data were collected from 279 respondents, and the derived conceptual model was tested by using Smart PLS 3.2.7 and PROCESS. To complement the findings of partial least squares (PLS)-based structural equation modeling (SEM), the present study also applied fuzzy set qualitative comparative analysis (fsQCA) to identify the necessary and sufficient conditions to explore substitute conjunctive paths that emerge.

Findings show that patients’ perceived intimacy (PI), cohesion and privacy enhance the quality of mental healthcare service providers. The results also suggest that patients’ PI, cohesion and privacy have indirect effects on the perceived quality of care (PQC) by the service providers through consumer engagement. The fsQCA results derive that the relationship among conditions leading to patients’ perception of the quality of care in regard to mental healthcare service providers is complex and is best reflected as multiple and conjectural causation configurations.

The findings from this research contribute to the advancement of studies on patients’ experiences by empirically examining the unique dynamics of interaction between consumers (patients) and mental healthcare service providers, thereby enriching both the literature on social interactions and the understanding of the consumer–provider relationship.

The results of this study provide practical implications for mental healthcare service providers on how to combine the study variables to enhance the quality of care and satisfy more patients.

A significant research gap has ascertained the inter-relationship between PI, cohesion, privacy, engagement and PQC from the perspective of mental healthcare service providers. This research is one of the primary studies from a managerial and methodological standpoint. The study contributes by combining symmetric and asymmetric statistical tools in service marketing and healthcare research. Furthermore, the application of fsQCA helps to understand the interactions that might not be immediately obvious through traditional symmetric methods.

In a competitive environment, eHealth small and medium-sized enterprises’ (SMEs’) barriers to survival differ from those of large enterprises. Empirical research on barriers to eHealth SMEs in less prosperous areas has been largely neglected. This study fills this gap by employing an integrated approach to analyze barriers to the development of eHealth SMEs. The purpose of this paper is to address this issue.

The authors collected data through semi-structured interviews and conducted thematic analysis to identify 16 barriers, which were used as inputs into total interpretive structural modeling (TISM) to build interrelationships among them and identify key barriers. Cross-impact matrix multiplication applied to classification (MICMAC) was then applied validate the TISM model and classify the 16 barriers into four categories.

This study makes significant contributions to theory by identifying new barriers and their interrelationships, distinguishing key barriers and classifying the barriers into four categories. The authors identify that transcultural problems are the key barrier and deserve particular attention. eHealth SMEs originating from regions with cultural value orientations, such as hierarchy and embeddedness, that differ from the UK’s affective autonomy orientation should strengthen their transcultural awareness when seeking to expand into UK markets.

By employing an integrated approach to analyze barriers that impede the development of eHealth SMEs in a less prosperous area of the UK, this study raises entrepreneurs’ awareness of running businesses in places with different cultural value orientations.

Due to its ability to support well-informed decision-making, business intelligence (BI) has grown in popularity among executives across a range of industries. However, given the volume of data collected in health-care organizations, there is a lack of exploration concerning its implementation. Consequently, this research paper aims to investigate the key factors affecting the acceptance and use of BI in healthcare organizations.

Leveraging the theoretical lens of the “unified theory of acceptance and use of technology” (UTAUT), a study framework was proposed and integrated with three context-related factors, including “rational decision-making culture” (RDC), “perceived threat to professional autonomy” (PTA) and “medical–legal risk” (MLR). The variables in the study framework were categorized as follows: information systems (IS) perspective; organizational perspective; and user perspective. In Jordan, 434 healthcare professionals participated in a cross-sectional online survey that was used to collect data.

The findings of the “structural equation modeling” revealed that professionals’ behavioral intentions toward using BI systems were significantly affected by performance expectancy, social influence, facilitating conditions, MLR, RDC and PTA. Also, an insignificant effect of PTA on PE was found based on the results of statistical analysis. These variables explained 68% of the variance (R²) in the individuals’ intentions to use BI-based health-care systems.

To promote the acceptance and use of BI technology in health-care settings, developers, designers, service providers and decision-makers will find this study to have a number of practical implications. Additionally, it will support the development of effective strategies and BI-based health-care systems based on these study results, attracting the interest of many users.

To the best of the author’s knowledge, this is one of the first studies that integrates the UTAUT model with three contextual factors (RDC, PTA and MLR) in addition to examining the suggested framework in a developing nation (Jordan). This study is one of the few in which the users’ acceptance behavior of BI systems was investigated in a health-care setting. More specifically, to the best of the author’s knowledge, this is the first study that reveals the critical antecedents of individuals’ intention to accept BI for health-care purposes in the Jordanian context.