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The purpose of this paper is to develop a comprehensive framework to identify and classify key medical tourism enablers (MTEs) and to study the direct and indirect effects of each enabler on the growth of medical tourism in India.

In this paper, an integrated approach using interpretive structural modeling (ISM) and Fuzzy Matrice d'Impacts Croisés Multiplication Appliquée á un Classement (FMICMAC) analysis has been developed to identify and classify the key MTEs, typically identified by a comprehensive review of literature and expert opinion. The key enablers are also modeled to find their role and mutual influence.

The key finding of this modeling helps to identify and classify the enablers which may be useful for medical tourism decision makers to employ this model for formulating strategies in order to overcome challenges and to become a preferred medical tourism destination. Integrated model reveals enablers such as medicine insurance coverage, international healthcare collaboration, and efficient information system as dependent enablers. No enabler is found to be autonomous enablers. The important enablers like healthcare infrastructure facilities and global competition are found as the linkage enablers. Research in medicine and pharmaceutical science, medical tourism market, transplantation law, top management commitment, national healthcare policy, competent medical and para-medical staffs are found as the independent enablers. Integrated model also establishes the direct and indirect relationship among various enablers.

The research provides an integrated model using ISM and FMICMAC to identify and classify various key enablers of medical tourism in India. In conventional cross-impact matrix multiplication applied to classification analysis, binary relationship of various enablers is considered. FMICMAC analysis helps to establish possibility of relationship among various enablers so that low-key hidden factors can be identified. The low-key hidden factors may initially exhibit marginal influence but they may show significant influence later on during analysis. The uncertainty and fuzziness of relationship among various enablers can be conveniently handled by FMICMAC and expert opinions can easily be captured. This research will help medical tourism decision makers to select right enablers for the growth of medical tourism in India.

The purpose of this paper is to identify the dimensions of service quality as well as of service loyalty in the context of medical tourism. It seeks to demonstrate the conceptualization of medical tourism service loyalty (MTSL) construct. This research also attempts to examine the effect of service quality dimensions on service loyalty dimensions of medical tourism.

The dimensions of service quality as well as of service loyalty are identified using an exploratory factor analysis. Next, the reliability and validity of the quality factors and loyalty factors are established through confirmatory factor analysis using AMOS 18.0 version. The related hypotheses are tested using structural equation modeling (SEM).

The paper identifies eight-factor construct for medical tourism service quality and three-factor construct for MTSL. It is found that the treatment satisfaction dimension of service quality has positive and significant impact on MTSL. It is also observed that, overall, medical tourism service quality has positive impact on MTSL.

These dimensions of service quality should be viewed as the levers of improving perceived service quality with respect to medical tourism. Examining the service quality dimensions’ impact on customer loyalty for medical tourism sector can offer the industry valuable insights regarding which aspects of the service to focus on in order to improve medical tourist’s satisfaction and loyalty toward the firms.

This paper introduces the concept of service quality and service loyalty in medical tourism sector. In conceptualizing MTSL, the authors propose an integration of behavioral measures, attitudinal measures and cognitive measures. The interrelationship between the service quality construct and medical loyalty construct was established using SEM. This is useful for the healthcare manager to measure the medical tourist’s perceptions of service quality on these dimensions as related to medical tourism performance.

The purpose of this paper is to assess the perceptions of safety officers on Occupational Health and Safety (OHS) norms extended to the workforce in Indian industries, understand implementation levels and find out deficiencies existing therein.

In this study, the authors utilized factor analysis to develop an instrument specifically responsible for assessing OHS norms in three major industrial sectors through a broad‐based questionnaire survey. The pattern of influence of input parameters on outputs such as injury level and material damage is difficult to establish, possibly due to existence of some nonlinear relationship among them. Therefore, a neural network approach is adopted to carry out sensitivity analysis and identify important deficient items.

Exploratory factor analysis has been carried out on the responses to the designed questionnaire. In total, nine factors with 23 items have been extracted and interpreted. As neural networks are capable of mimicking human cognitive process, the perceptions mechanism of safety officers can be easily modeled via neural networks. Sector‐wise deficient items have been identified and strategies for their improvement have been proposed.

The major limitation may be the number of industrial sectors considered in the study. Although the proposed model is quite generic, its performance needs to be tested with other categories of industries.

Although perceptions of safety officers on their immediate work environment help to formulate constructive safety policy and procedures, involvement of a few representatives from the workforce during the implementation level may assist to substantially reduce injury level and material damage, since the workers are more conversant with work practices, are exposed to risk environments and can sustain injuries if accidents occur.

The paper uses advanced statistical and intelligent techniques for assessment of OHS practices. A comparative evaluation of present practices among three major types of Indian industry has been made. Further, the paper proposes an OHS instrument for Indian industry. The paper offers new directions for researchers to devise a comprehensive methodology that aims at reducing occupational health risks.