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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.

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.

This study aims to deal with the paucity of studies in the stages of the development of loyalty behaviour of customers in the healthcare context by incorporating three crucial service quality dimensions (physical environment, personnel quality and technical quality) and also investigating trust and commitment as mediating factors.

Survey data were obtained from 420 respondents admitted to government hospitals in Kerala employing a convenience sampling method. The formulated hypotheses were tested using partial least square structural equation modelling.

Results indicate that patient satisfaction, trust and commitment can create favourable behavioural intentions amongst patients. When patients reveal higher trust, they are more inclined to value healthcare services and willing to commit to a long-term relationship, resulting in increased patient loyalty.

Organisational efforts should improve trust and commitment and build a good relationship between service providers and patients. Efforts should be taken to raise the standard of technical and personnel aspects, and a focus on physical infrastructure should also be considered to build a favourable behavioural intention to revisit and positive referrals.

This is the first empirical study to analyse technical quality, personnel quality and physical environment along with the mediating effect of trust, and commitment in a four-stage loyalty development model in the healthcare context of Kerala, India.

Health-care marketing typically entails a coordinated set of outreach and communications designed to attract consumers (patients in the health-care context) who require services for a better health outcome and guide them throughout their health-care journey to achieve a higher quality of life. The purpose of this study is to understand the progress and trends in healthcare marketing strategy (HMS) literature between 2018 and 2022, with a special emphasis on the pre- and post-Covid-19 periods.

The authors examine 885 HMS-related documents from the WOS database between 2018 and 2022 that were extracted using a keyword-based search strategy. After that, the authors present the descriptive statistics related to the corpus. Finally, the authors use author co-citation analysis (ACA) and bibliographic coupling (BC) techniques to examine the corpus.

The authors present the descriptive statistics as research themes, emerging sub-research areas, leading journals, organisations, funding agencies and nations. Further, the bibliometric analysis reveals the existence of five thematic clusters: Cluster 1: macroeconomic and demographic determinants of healthcare service delivery; Cluster 2: strategies in healthcare marketing; Cluster 3: socioeconomics in healthcare service delivery; Cluster 4: data analytics and healthcare service delivery; Cluster 5: healthcare product and process innovations.

This study provides an in-depth analysis of the advancements made in HMS-related research between 2018 and 2022. In addition, this study describes the evolution of research in this field from before to after the Covid-19 pandemic. The findings of this study have both research and practical significance.

To the best of the authors’ knowledge, this is the first study of its kind to use bibliometric analysis to identify advancements and trends in HMS-related research and to examine the pattern before and after Covid-19 pandemic.

The purpose of this paper is to give an overview of artificial intelligence (AI) and other AI-enabled technologies and to describe how COVID-19 affects various industries such as health care, manufacturing, retail, food services, education, media and entertainment, banking and insurance, travel and tourism. Furthermore, the authors discuss the tactics in which information technology is used to implement business strategies to transform businesses and to incentivise the implementation of these technologies in current or future emergency situations.

The review provides the rapidly growing literature on the use of smart technology during the current COVID-19 pandemic.

The 127 empirical articles the authors have identified suggest that 39 forms of smart technologies have been used, ranging from artificial intelligence to computer vision technology. Eight different industries have been identified that are using these technologies, primarily food services and manufacturing. Further, the authors list 40 generalised types of activities that are involved including providing health services, data analysis and communication. To prevent the spread of illness, robots with artificial intelligence are being used to examine patients and give drugs to them. The online execution of teaching practices and simulators have replaced the classroom mode of teaching due to the epidemic. The AI-based Blue-dot algorithm aids in the detection of early warning indications. The AI model detects a patient in respiratory distress based on face detection, face recognition, facial action unit detection, expression recognition, posture, extremity movement analysis, visitation frequency detection, sound pressure detection and light level detection. The above and various other applications are listed throughout the paper.

Research is largely delimited to the area of COVID-19-related studies. Also, bias of selective assessment may be present. In Indian context, advanced technology is yet to be harnessed to its full extent. Also, educational system is yet to be upgraded to add these technologies potential benefits on wider basis.

First, leveraging of insights across various industry sectors to battle the global threat, and smart technology is one of the key takeaways in this field. Second, an integrated framework is recommended for policy making in this area. Lastly, the authors recommend that an internet-based repository should be developed, keeping all the ideas, databases, best practices, dashboard and real-time statistical data.

As the COVID-19 is a relatively recent phenomenon, such a comprehensive review does not exist in the extant literature to the best of the authors’ knowledge. The review is rapidly emerging literature on smart technology use during the current COVID-19 pandemic.

This study aims to investigate and test the impact of competitive priorities, in terms of quality, speed, dependability, flexibility, cost and patient engagement, on patient satisfaction with healthcare services. It considers patients’ rather than managers’ points of view to collect responses about competitive priorities.

This research employed a cross-sectional survey design to analyze a sample of customers through an empirical study of 488 patients in Qatar’s healthcare service context.

The confirmatory factor analysis results show that competitive priorities and engagement positively and significantly impact patient satisfaction.

Researchers can use this methodology to explore the role of competitive priorities in different service contexts and sectors. The researchers conducted the study in Qatar; therefore, the results are not generalizable to all healthcare sectors. However, regardless of geographic location, the research approach can be used in healthcare.

Managers can employ the developed scales to diagnose competitive priorities and improve customer service experiences.

The paper is original as it suggests using competitive priorities as a measurement tool for predicting patient satisfaction compared to prior research that mostly measured competitive priorities based on internal perspectives (managers’ perspectives). Further, this paper is original because it depends on the external perspective (customers’ perspective) for the competitive priorities for measuring patient satisfaction.

One of the most marginalized communities in India is the Lesbian, Gay, Bisexual and Transgender (LGBT) community which commonly experiences discrimination. Many studies have countered that the LGBT community faces high discrimination in the banking and financing industry. As a result, this study concentrates on this marginalized community and its acceptance and continuation habit regarding mobile wallets. Consequently, this study has considered continuance intentions as a response to confirm the progress of the mobile-wallet industry. Also, this study tried to study the relationship between behavioral intention (BI) and continuous intention (CI) which is seriously lacks in the library of literature. The research operationalized the stimulus–organism–response (SOR) framework for the conceptual model and surveyed 100 self-proclaimed members of the LGBT community in India. The analysis has been done using the partial least structure (PLS). The findings demonstrate that variables like perceived trust (PT) directly influence the BI. On the other hand, variables like perceived ease of use (PEoU), social influence (SI), and satisfaction (S) doesn’t influence BI of the LGBT Community. The main outcome was a favorable association between BI and CI. It will help the stakeholders to understand how important this new market avenue is and how it can be explored. To ensure safe and secure transactions, a group think tank composed of important parties (financial institutions, mobile-wallet providers, the government, security specialists, etc.) should make recommendations. Mobile-wallet providers will attain benefit from this study’s understanding of user categories and ability to tailor their service offers as per the community.

The use of technology in 4th industrial revolution is at its peak. Industries are trying to reduce the consumption of resources by effectively utilizing information and technology to connect different functioning agents of the manufacturing industry. Without digitization “Industry 4.0” will be a virtual reality. The present survey-based study explores the factual status of digital manufacturing in the Northern India.

After an extensive literature review, a questionnaire was designed to gather different viewpoints of Indian industrial practitioners. The first half contains questions related to north Indian demographic factors which may affect digitalization of India. The latter half includes the queries concerned with various operational factors (or drivers) driving the digital revolution without ignoring Indian constraints.

The focus of this survey was to understand the current level of digital revolution under the ongoing push by the Indian government focused upon digital movement. The analysis included non-parametric testing of the various demographic and functional factors impacting the digital echoes, specifically in Northern India. Findings such as technological upgradations were independent of type of industry, the turnover or the location. About 10 key operational factors were thoughtfully grouped into three major categories—internal Research and Development (R&D), the capability of the supply chain and the capacity to adapt to the market. These factors were then examined to understand how they contribute to digital manufacturing, utilizing an appropriate ordinal logistic regression. The resulting predictive analysis provides seldom-seen insights and valuable suggestions for the most effective deployment of digitalization in Indian industries.

The country-specific Industry 4.0 literature is quite limited. The survey mainly focuses on the National Capital Region. The number of demographic and functional factors can further be incorporated. Moreover, an addition of factors related to ecology, environment and society can make the study more insightful.

The present work provides valuable insights about the current status of digitization and expects to facilitate public or private policymakers to implement digital technologies in India with less efforts and the least resistance. It empowers India towards Industry 4.0 based tools and techniques and creates new socio-economic dimensions for the sustainable development.

The quantitative nature of the study and its statistical predictions (data-based) are novel. The clubbing of similar success factors to avoid inter-collinearity and complexity is seldom seen. The predictive analytics provided in this study is quite elusive as it provides directions with logic. It will help the Indian Government and industrial strategists to plan and perform their interventions accordingly.

This study intend to investigate a theoretical model looking at how particular tourist emotions, such as “joy,” “love,” and “positive surprise,” might predict their behavior by looking at how satisfied they are with their whole experience when visiting spas, and to examine the relationship of emotional experience, destination image, satisfaction and intention to revisit for spa tourism.

A sample of 345 individuals who traveled to Alleppey as domestic tourists participated in the research study. A non-probability (purposive) sampling method in this study. The structural model was analyzed using Structural Equation modeling (SEM), and the path coefficients were examined to test the hypotheses.

The results supported the hypotheses, indicating that specific emotions, image of the destination, and satisfaction significantly impacted tourists' intentions to revisit Alleppey as a spa tourism destination. This study demonstrated that “emotions of joy, love, and positive surprise” have a considerable influence on the image of the destination and satisfaction. The findings reveal a substantial correlation between satisfaction and behavioral intention (“Intention to revisit”). The research suggests that a higher degree of satisfaction would encourage visitors to revisit the location.

The research suggests that a higher degree of satisfaction would encourage visitors to revisit the location. This research offers vital information for developing, planning, and putting into practice tourism policies in the spa tourism sector. This article focuses on domestic travelers who travel to Alleppey, so the conclusions may not be relevant to research utilizing foreign tourists.

According to the literature study, and to the authors` knowledge, only limited number of studies that look at spa tourism from a wellness perspective. Additionally, Alleppey is used in the study as the study’s setting, providing insight into the visitor experiences of this expanding spa tourism business. This study gives understanding about how emotional experience predicts behavioral intentions.