PurposeThe vision of Industry 4.0 concept is to create smart factories that will change the current processes of production and manufacturing system using smart machines to produce smart and intelligent products. The main aim of this research is to explore the enablers with regard to Industry 4.0 application in manufacturing industry in India as the available literature shows that manufacturing sector is still doubtful about the implementation of Industry 4.0.Design/methodology/approachSeventeen enablers that can affect the adoption of Industry 4.0 in the manufacturing industry in India have been explored through an extensive review of available literature and viewpoints of industry and academic experts. Total Interpretive Structural Modelling methodology (TISM) has been used to evaluate the interrelationships among these factors. A TISM model has been developed to extract the key enablers influencing Industry 4.0 adoption.FindingsThe result shows that Internet facility from government at reduced price, financial support and continued specialized skills training are the major enablers as they have strong driving power.Practical implicationsProper understanding of these enablers will help the managers and policymakers to explore the impact of each enabler on other enablers as well as the degree of relationships among them and to take concrete steps so that Industry 4.0 can be implemented successfully in the manufacturing sector in India.Originality/valueThis study is pioneer in exploring the enablers Industry 4.0 which is the most advanced concept that has the capability to change the future of Indian manufacturing sector if implemented judiciously and cautiously.

In healthcare industry, the phenomenon of Industry 4.0 is popular as Health 4.0 where the modern technologies are integrated with available data along with the use of artificial intelligence. The main objective of this paper is to explore the barriers of Health 4.0 application in healthcare sector in India. Fifteen barriers which can affect the adoption of Health 4.0 in the Indian healthcare sector have been identified through extensive literature review and opinions of healthcare industry and academic experts. ATISM (Total Interpretive Structural Modelling) model has been developed to extract the key barriers influencing Health 4.0 adoption which will guide the healthcare managers and decision makers to explore the effect of each barrier on other barriers as well as the degree of relationships among them. The result shows that lack of top management support, exclusive and skilled workforce requirement, inadequate maintenance support systems and political support are the major barriers as they have strong driving power. Timely action taken by the management to remove these hurdles will not only reduce the cost of medical procedures but also improve the quality of treatment so that the true potential of Health 4.0 can be utilized. KeywordsIndustry 4.0 . Health 4.0 . Health 4.0 barriers . Healthcare industry . Healthcare industrial revolution . Total interpretive structural modelling . MICMAC analysis * Vineet Jain

Purpose Organizations have to evaluate their internal and external environments in this highly competitive world. Strengths, weaknesses, opportunities and threats (SWOT) analysis is a very useful technique which analyzes the strengths, weaknesses, opportunities and threats of an organization for taking strategic decisions and it also provides a foundation for the formulation of strategies. But the drawback of SWOT analysis is that it does not quantify the importance of individual factors affecting the organization and the individual factors are described in brief without weighing them. Because of this reason, SWOT analysis can be integrated with any multiple attribute decision-making (MADM) technique like the technique for order preference by similarity to ideal solution (TOPSIS), analytical hierarchy process, etc., to evaluate the best alternative among the available strategic alternatives. The paper aims to discuss these issues. Design/methodology/approach In this study, SWOT analysis is integrated with a multicriteria decision-making technique called TOPSIS to rank different strategies for Indian medical tourism in order of priority. Findings SO strategy (providing best facilitation and care to the medical tourists at par to developed countries) is the best strategy which matches with the four elements of S, W, O and T of SWOT matrix and 35 strategic indicators. Practical implications This paper proposes a solution based on a combined SWOT analysis and TOPSIS approach to help the organizations to evaluate and select strategies. Originality/value Creating a new technology or administering a new strategy always has some degree of resistance by employees. To minimize resistance, the author has used TOPSIS as it involves group thinking, requiring every manager of the organization to analyze and evaluate different alternatives and average measure of each parameter in final decision matrix.

Purpose Medical tourism encourages the traveling of patients, expert healthcare professionals and promotes cross-border trade in healthcare services. The Indian medical tourism sector is facing new challenges as well as certain ethical and legal issues because of continuous market changes and patient’s requirements while at the same time advancements in current health services have also been observed. It is therefore very important to understand and address the issues of the medical tourists. The purpose of this paper is to evaluate the important factors which can make India an affordable medical tourism destination. Design/methodology/approach In this paper, the factors influencing Indian medical tourism sector have been explored by conducting literature review, they are ranked according to the results of a questionnaire-based survey and further analyzed by using the interpretive structural modeling (ISM) approach. The mutual relationships between these factors were identified to develop an ISM model so as to find out the important factors which can make India an affordable place for medical tourism. Findings The results of the survey and the model show that cost of medical procedures, facilitation, and care, the infrastructure of Indian hospitals, clinical excellence and the competence of doctors and staff are the top level factors. Practical implications It is very important to address the concerns of the patients coming to a developing country like India for availing medical services. This research has evaluated the important factors which can make India an affordable medical tourism destination. Originality/value This research assesses the effects of globalization on delivery of healthcare services in India by conducting critical analysis of the medical tourism industry by collecting original data from the international patients coming to India for different types of medical procedures so that a comprehensive model can be prepared which will help the hospitals and policymakers to improve the processes related to medical tourism.

Purpose Lean concept is implemented in healthcare organizations, as it deals with improvement processes so that best services may be provided to the patients and competitive advantage may be achieved. The purpose of this paper is to evaluate the important factors which influence implementation of lean principles in the healthcare industry. Design/methodology/approach The factors influencing lean implementation in the healthcare industry have been determined through literature review and results of a survey where questionnaires were distributed among 325 healthcare professionals. Fuzzy Interpretive Structural Modeling (FISM) approach has been used to analyze the interrelationships among these factors. A FISM model has been developed to extract the key factors influencing lean implementation. Findings Results of the survey and model show that lean leadership, professional organizational culture and teamwork and interdepartmental cooperation are the top level factors. Clarity of organizational vision, communication of goals and results, follow up and evaluations are the factors with strong driving as well as strong dependence power. Even a slight action taken on these factors will have a significant impact on other factors. Practical implications The healthcare professionals and managers can acquire information from the drive power dependence matrix so that they can thoroughly understand the relative importance, interdependencies and relationships among these factors. The model will help in determining the hierarchy of various actions and activities which may be taken by the management for managing the factors that remarkably affect the lean management in hospitals. Social implications In this paper, only 15 variables appropriate for the Indian healthcare industry have been identified. The model developed in the present research has not been validated statistically which can be done by structural equation modeling (SEM). Originality/value Though there are various studies which depict that lean principles have been implemented successfully in various industries, there are few studies specifying the application of lean principles in healthcare sector in India. This paper is an attempt to identify various factors which are important for application of Lean concept in the healthcare sector.

Purpose Diabetes mellitus has become a major world health problem that has unenviable impacts on health of the people including quality of life (QOL) also and in which person’s physical and psychological state, social commitments and relationships and his interaction with the environment is affected. This shows that there is an urgent need for behavior change and considerable educational strategies for proper management and rehabilitation (Reddy, 2000). This research has identified and ranked the significant factors which affect the QOL in diabetic patients in India. The paper aims to discuss these issues. Design/methodology/approach In this paper, nine factors which affect the QOL in diabetic patients in India have been identified through review of the literature and evaluated by total interpretive structural modeling (TISM) approach, i.e. an extended version of ISM. In this approach, interpretations of the interrelationship among factors have been discussed. Therefore, TISM approach has been used to develop the model and the mutual interactions among these factors. Findings The results of the model and MICMAC analysis indicate that diet restriction, body pain and satisfaction with treatment are the top-level factors. Practical implications Identification of the factors that have a remarkable effect on the QOL in diabetic patients is very important so that the doctors and other healthcare professionals may handle these factors efficiently and proper rehabilitation can be provided to such patients. Originality/value This paper has used an application of the TISM approach to interpret the mutual relationship by using the tool of interpretive matrix and has developed a framework to calculate the drive and the dependence power of factors using MICMAC analysis. The issues related to QOL are extremely important, as they can strongly anticipate a person’s capability to govern his lifestyle with disease like diabetes mellitus and maintain good health in the long run. This shows the urgent requirement of an optimized model which can predict and interpret the relationships among these factors. In this research, the interrelationships among these factors have been developed and interpretations of these interactions have been given to develop a comprehensive model so that QOL of diabetic patients may be improved.

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While there are rampant deaths reported worldwide due to novel corona virus (COVID-19) on one side, hypertension, diabetes and renal failure are emerging comorbidities with mortality risk due to respiratory failure on the other side. The link of these morbidities with renin angiotensin system (RAS) and angiotensin converting enzyme-2 (ACE2) as the site of the multiplication of COVID-19 has widely been accepted. The objective of this research report was to delineate the clinical characteristics with COVID-19 infection with RAS and to consider its significance not just for the search of novel antiviral drugs, but for the management and prevention of death of patients with COVID-19. Methods: It was a retrospective case series analysis of demographic and clinical data with associated comorbidities of 206 deaths reported in India up to 10th April 2020. The data were available from the official release from Ministry of Health and Family welfare, Government of India. This was followed by a literature search to correlate the available evidence for their possible relationship with RAS. Results: The demographic data were consistent with those reported from other countries. The death (53.4%) was more common in patients with age above 60 years and men (69.3%) were more susceptible as compared to women (30.68%).We found that 50.5% of the deceased patients had pre-existing comorbidities. Diabetes and hypertension were the major comorbidities in 27.8% and 22.1% of the deceased cases respectively. Although respiratory and cardiac problems were prevalent at the time of death, the pre-existing pulmonary disease was comparatively less prevalent. Only 13.6% of the deceased were having pre-existing respiratory problems and 6.2% had cardiac ailments. We could correlate the reports that RAS plays a significant role in the prognosis of the disease. Conclusions: Patients with cardiovascular diseases, diabetes mellitus and hypertension are at greater risk for developing COVID-19 infection. There may be massive derangement of the entire RAS after the attack of COVID-19 and hence, patients with these pre-existing comorbidities and on ACE inhibitors or angiotensin receptor blockers should be monitored carefully considering the role of RAS in the prognosis of COVID-19 infections.