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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.

This study investigated the relationship between last-mile distribution or delivery (LMD) and commodity access through the mediating role of commodity availability and commodity security and the moderating effect of supply chain integration (SCI).

The study adopted the survey research design and employed the questionnaire instrument in collecting primary data from respondents in Eastern Regional Health Institutions in Ghana. The total number of valid responses received was 204. The partial least squares structural equation modeling (PLS-SEM) approach was adopted to analyze the relationship between the study variables.

The findings showed that there is a positive and significant relationship between LMD and commodity availability as well as LMD and commodity security. Moreover, while the relationship between commodity availability and commodity access is positive and significant, that between commodity security and commodity access is positive but insignificant. Furthermore, there is a positive and statistically significant relationship between LMD and commodity access. The study discovered that the interaction between LMD and commodity access is insignificant and negatively affected by SCI.

To the best of the authors' knowledge, no previous studies have empirically verified the effect of LMD on commodity access in the presence of mediating factors such as commodity availability and commodity security and SCI as the moderating factors.

Regardless of the diverse research on big data analytics (BDA) across different supply chains, little attention has been paid to exploit this information across service supply chains. The healthcare supply chains, where supply chain operations consume the second highest expenditures, have not completely attained the potential gains from data analytics. So, this paper explores the challenges of BDA at various levels of healthcare supply chains.

Drawing on the resource-based view (RBV), this research explores the various challenges of big data at organizational and operational level of different nodes in healthcare supply chains. To demonstrate the links among supply chain nodes, the authors have used a supplier-input-process-output-customer (SIPOC) chart to list healthcare suppliers, inputs (such as employees) supplied and used by the main healthcare processes, outputs (products and services) of these processes, and customers (patients and community).

Using thematic analysis, the authors were able to identify numerous challenges and commonalities among these challenges for the case of healthcare supply chains across United Arab Emirates (UAE). An applicable exploration on organizational (Socio-technical) and operational challenges to BDA can enable healthcare managers to acclimate efficient and effective strategies.

The identified common socio-technical and operational challenges could be verified, and their impacts on the sustainable performance of various supply chains should be explored using formal research methods.

This research advances the body of literature on BDA in healthcare supply chains in that (1) it presents a structured approach for exploring the challenges from various stakeholders of healthcare chain; (2) it presents the most common challenges of big data across the chain and finally (3) it uses the context of UAE where government is focusing on medical tourism in the coming years.

Originality of this work stems from the fact that most of the previous academic research in this area has focused on technology perspectives, a clear understanding of the managerial and strategic implications and challenges of big data is still missing in the literature.

This paper aims to explore the antecedents and consequences of service chain flexibility (SCF) in healthcare service delivery.

A structural model was developed based on a literature review. A 29-indicator questionnaire was circulated among service providers in the healthcare system across India, and 253 valid responses were received, corresponding to a response rate of 46%. The research model was assessed using a cross-sectional research design, and the data were analyzed by structural equation modeling using analysis of moment structures (AMOS) software.

Service orientation (SO), technology integration (TI), knowledge sharing (KS) and supply chain integration (SCI) were identified as antecedents of SCF, the consequence of which is responsiveness in service delivery (RSD). Furthermore, patient-centered care moderates the relationship between SCF and RSD.

This paper highlights the impact of SCF on RSD in healthcare organizations. Consideration of the four constructs of SO, TI, KS and SCI as antecedents of SCF and, in turn, RSD may be one of the limitations. Future work may identify other theoretical constructs with potential impacts on SCF and RSD. Furthermore, eight months for data collection could have resulted in early-late response bias. This study was operationalized in India and may reflect political, economic, social, technological, environmental and legal factors unique to India.

The study provides suggestions to practitioners for building RSD by leveraging SO, TI, KS and SCI in flexibility-driven service chain processes. Recognizing the relationships among these constructs can aid in the timely formulation of corrective actions and patient-centric policies.

This paper highlights how focusing on a SCF can promote RSD. This understanding may aid the design of processes that develop patient-centricity and deliver health as a social good in an effective manner.

The empirical evidence from this study can help hospitals integrate and build flexibility in their functions, thus enabling them to deliver responsiveness in care.

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 purpose of the study is to comprehend medical service quality, information quality and system quality toward actual use of Tele-Health in rural India. The study further validates the impact of the actual use of Tele-Health on sustainable development, thus providing implications to improve upon the Tele-Health penetration in India.

Data was collected from 326 healthcare practitioners practicing Tele-Health in North Indian states and Structural Equation Modeling was applied to validate the conceptual framework.

The results indicated that medical service quality, information quality and system quality influence Tele-Health behavioral intentions which in turn impact actual use and sustainable development. This research draws upon a conceptual framework to deepen our understanding of Tele-Health by providing an all-inclusive overview.

The massive topography of India with a prime rural populace instills the need for timely healthcare facilities. Tele-Health is a solution to all these problems but is at a nascent stage. Therefore, there is a vital need to study the factors which improve the penetration of Tele-Health in the Indian context. The model that emerged from the study may be validated by other Indian sub-continental countries so that Tele-Health may be implemented hassle-free.

This article aims to address the need for a more structured partnership between civilian and military healthcare, particularly in the context of cross-border threats in the EU. While both systems are driven by the same goal of providing high-quality healthcare services and achieving optimal patient outcomes, they operate under different national approaches and resources.

Two recent crises are presented as examples that highlight the necessity of cooperation between civilian and military medical systems. The Covid-19 Pandemic and the Ukrainian Conflict are described based on the experience gathered by the author as a member of the NATO Centre of Excellence for Military Medicine and form the base to shape a broader perspective on the future of civil-military interaction in healthcare at the European Union level.

The ability to deliver coordinated responses during crises depend on the level of interoperability, preparation and mutual understanding. To improve synergies, a structured partnership should be established, prioritizing common standards of care and shared best practices. Integrating military and civilian healthcare pathways can be especially beneficial in situations where patients are moved from the point of injury or sickness across different military and civilian structures to receive the most appropriate treatment and rehabilitation for their conditions.

The relationship between military and civilian healthcare systems is often discussed at multinational level, but a clear focus is lacking concerning their shared mission, distinct functions and potential for cross-border collaboration.

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.

The scope of this study is to explore and summarize the pool of dimensions, models and measurement techniques of service quality used in healthcare services and to propose a comprehensive conceptual model for practitioners and researchers.

This research employs a comprehensive review of available literature by using multiple keywords on different electronic repositories using the recommendations of the PRISMA approach for the selection of articles. A critical analysis of available studies helped in compiling a list of core service quality dimensions in healthcare services.

This paper presents a comprehensive account of different dimensions and their measurement items used by various researchers to assess service quality in healthcare systems. Most of the researchers have used SERVQUAL model either in its original or modified form while the others have proposed and used totally different dimensions to assess the service quality in healthcare. Many dimensions are just an existing dimension of SERVQUAL that has undergone a name change while others are completely new. The dimensions used by many researchers have items drawn from more than one dimension of SERVQUAL model. The availability of so many dimensions and models adds to the confusion that researchers and practicing managers experience when determining the appropriate model to be used in their work. To mitigate this confusion, there is a need to develop a comprehensive model; the current work is an attempt to meet this need. Through our analysis, we identify four major service quality dimensions: clinical quality, infrastructural quality, relationship and managerial quality and propose a model named CIRMQUAL.

After exploring all available models in the domain of healthcare, this research presents the best possible areas to enhance the quality of healthcare services. It also enhances the research insights for academicians and working professionals by developing and proposing a comprehensive model for measuring healthcare service quality. The proposed model covers almost all of the service quality dimensions used by other researchers and will make the choice of dimensions/model easy for the future researchers/practitioners interested in measuring and improving the quality of services offered by their healthcare units. Such a comprehensive model has not been developed by any researcher thus far.

The relevance of analytics to the healthcare supply chain is increasing with emerging trends and technologies. This study examines how analytics are used in the healthcare supply chain in the “new normal” environment.

A systematic literature review was conducted by extracting research articles related to analytics in the healthcare supply chain from Scopus. The author used a hybrid review approach that combines bibliometric analysis with a theories, contexts, characteristics, and methodology (TCCM) framework-based review to identify various themes of analytics in the healthcare supply chain.

The hybrid review strategy yielded results that focus on prevalent theories, contexts, characteristics, and methodologies in the field of healthcare supply chain analytics. Future research should explore the resulting antecedents, decision-making processes and outcomes (ADO) framework, which integrates technological, economic, and societal concerns and outcomes. Future research agendas could also seek to apply theoretical perspectives in the field of analytics in the healthcare supply chain.

The result of a review of selected studies adds to the current body of work and contributes to the growth of research in the field of analytics in the healthcare supply chain. It also provides new directions to healthcare supply chain managers and academic scholars.