Sepehr Hendiani

Developing a sustainable healthcare system directly depends on the level of maturity in environmental, social, and economic practices. Although there are huge number of researches considering environmental, social, and economic aspects, to the best of our knowledge, no approach was found which unifies these dimensions as an integrated method to assess the current status of sustainable development in healthcare organizations. In order to cope with this gap, this article suggests a method for analyzing the sustainability indicator in healthcare systems by manipulating the sustainability dimensions, criteria, and attributes. The following research has collected 62 attributes and 15 criteria for three sustainability dimensions. A new implementation method is also proposed to make this approach applicable in real-world problems. The contributions of this paper can be distinguished as the healthcare system’s sustainability level in imprecise conditions is obtained, the capability of identifying the weak points in implementing sustainability aspects is presented, and a new methodology for collecting the fundamental data for measuring the sustainability level in healthcare systems is given. The findings of this paper assist the practitioners and experts to successfully evaluate the sustainability level of healthcare systems and significantly improve the performance of them.

A sustainable manufacturing company depends on the developments in three aspects in order to minimize harmful impacts on the environment, improve the social relations, and simultaneously maximize the economic benefits. Despite the increasing types of investigations that researchers have carried out in environmental and economic aspects, the minimum attention has been paid to social relations. In response to this deficiency, this paper proposes a new framework to obtain the overall sustainability index in manufacturing companies by encapsulating the sustainability criteria/sub-criteria. This article collected 33 sub-criteria for five pillars of sustainability as social, environment, economic, technological advancement, and performance management. The key contributions of this paper are highlighted as the hierarchical method that obtains the status of sustainability in uncertain conditions, the ability to identify the weak points, and a new framework for gathering the data about sustainability performance in manufacturing companies. The findings of this paper will aid both policymakers and decision-makers to assess the sustainability status of manufacturing systems and improve the performances of them.

Fuzzy theory defined by Zadeh has been developed through both analytical and computational categories of diverse sciences in light of time. The goal of applying fuzzy theory is to incorporate uncertainties with conventional deterministic calculations to enhance the reliability of results. Since fuzzy theory has been developed and carried out by so many researchers, various types of generalizations including Z-Numbers, Type-2 fuzzy sets, Intuitionistic sets and hesitant sets, have been revealed to estimate real-world variables more accurately. Toward these goals Utility-Numbers or H-Numbers Theory is proposed with an ordered set of (n,M(n),N(n)), to assign satisfaction degrees to corresponding uncertain numbers. The first component, n, is a constraint on the values which a stochastic real-structured variable, X, may take. The following components,M(n),N(n), represent the maximum and minimum utilities assigned to first component, respectively. This paper first substantiates immediate H-Numbers as(n,M(n)), and the mathematical operations over them, then these H-Numbers are elaborated to (n,M(n),N(n)) in which minimum and maximum utility values are considered both. Meanwhile, the main contribution of proposed model leads to obtain satisfaction value for each fuzzy number component and helps practitioners to concentrate on total satisfaction that is aggregated by each alternative. The proposed model is validated by comparison tables and reasonable values over conventional fuzzy sets.