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This paper presents a novel Multiple Criteria Decision Making methodology for assessing and prioritizing medical tourism destinations under uncertainty. A systematic evaluation and assessment approach is proposed by incorporating analytic hierarchy process and multi‐attributive border approximation area comparison methods in the rough environment. Rough number is used to aggregate individual judgements of decision makers and express their true perception to handle vagueness without any prior information. Rough analytic hierarchy process analyses the relative importance of criteria based on their preferences given by experts, whereas rough multi‐attributive border approximation area comparison evaluates the alternative sites based on the criteria weights. A case study of prioritizing different sites (cities) in India for medical tourism services is shown to demonstrate the applicability of the proposed method. Among different criteria “quality of infrastructure of healthcare institutions” is observed to be the most important criteria in our analysis, followed by “supply of skilled human resources and new job creations” and “Chennai” is found to be the best medical tourism site in India. Finally, a comparative analysis and validity testing of the proposed method are elaborated, and the methodology provides a standard for select medical tourism sites on the basis of different criteria.

Optimal selection of sustainable materials in construction projects can benefit several stakeholders in their respective industries with the triple bottom line (TBL) framework in a broader perspective of greater business value. Multiple criteria of social, environmental, and economic aspects should be essentially accounted for the optimal selection of materials involving the significant group of experts to avoid project failures. This paper proposes an evaluation framework for solving multi criteria decision making (MCDM) problems with incomplete weight information by extending the combinative distance assessment (CODAS) method with interval-valued intuitionistic fuzzy numbers. To compute the unknown weights of the evaluation criteria, this paper presents an optimization model based on the interval-valued intuitionistic fuzzy distance measure. In this study, we emphasize the importance of individual decision makers. To illustrate the proposed approach, an example of material selection in automotive parts industry is presented followed by a real case study of brick selection in sustainable building construction projects. The comparative study indicates the advantages of the proposed approach in comparison with the some relevant approaches. A sensitivity analysis of the proposed IVIF-CODAS method has been performed by changing the criteria weights, where the results show a high degree of stability.

Saparauskas (2019) An extended COPRAS model for multi-criteria decisionmaking problems and its application in web-based hotel evaluation and selection, Economic

Due to the increasing size of the population, society faces several challenges for sustainable and adequate agricultural production, quality, distribution, and food safety in the strategic project portfolio selection (SPPS). The initial adaptation of strategic portfolio management of genetically modified (GM) Agro by-products (Ab-Ps) is a huge challenge in terms of processing the agro food product supply-chain practices in an environmentally nonthreatening way. As a solution to the challenges, the socio-economic characteristics for SPPS of GM food purchasing scenarios are studied. Evaluation and selection of the GM agro portfolio management are the dynamic issues due to physical and immaterial criteria involving a hybrid multiple criteria decision making (MCDM) approach, combining modified grey Decision-Making Trial and Evaluation Laboratory (DEMATEL), Multi-Attributive Border Approximation area Comparison (MABAC) and sensitivity analysis. Evaluation criteria are grouped into social, differential and beneficial clusters, and the modified DEMATEL procedure is used to derive the criteria weights. The MABAC method is applied to rank the strategic project portfolios according to the aggregated preferences of decision makers (DMs). The usefulness of the proposed research framework is validated with a case study. The GM by-products are found to be the best portfolio. Moreover, this framework can unify the policies of agro technological improvement, corporate social responsibility (CSR) and agro export promotion.