What makes organizations so similar? We contend that the engine of rationalization and bureaucratization has moved from the competitive marketplace to the state and the professions. Once a set of organizations emerges as a field, a paradox arises: rational actors make their organizations increasingly similar as they try to change them. We describe three isomorphic processes-coercive, mimetic, and normative—leading to this outcome. We then specify hypotheses about the impact of resource centralization and dependency, goal ambiguity and technical uncertainty, and professionalization and structuration on isomorphic change. Finally, we suggest implications for theories of organizations and social change.

The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields (Chinese Translation)

A review of Internet of Things (IoT) embedded sustainable supply chain for industry 4.0 requirements

Multicriteria decision-making (MCDM) refers to making decisions in the presence of multiple and usually conflicting criteria. Fuzzy decision-making is used where vague and incomplete data exist for the solution. Fuzzy multicriteria decision-making is one of the most popular problems handled by the researchers in the literature. In this paper, we survey the latest status of fuzzy multicriteria decision-making methods and classify these methods dividing into two parts: fuzzy multiattribute decision-making (MADM) and fuzzy multiobjective decision-making (MODM). Most of the publications are on fuzzy MADM since there are a plenty of classical multiattribute decision-making methods in the literature. Tabular and graphical illustrations for each method are given.

/pdf/fuzzy-multicriteria-decision-making-a-literature-review-383hh8670r.pdf

Fuzzy Multicriteria Decision-Making: A Literature Review

A novel approach to risk assessment for occupational health and safety using Pythagorean fuzzy AHP & fuzzy inference system

A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping

Hospital Site Selection via Hesitant Fuzzy TOPSIS

The fundamental objective of supply chain management (SCM) is to integrate various suppliers to satisfy market demand. Supplier evaluation and selection is very important for establishing an effective supply chain. As a matter of fact, supplier selection consists of both qualitative and quantitative criteria, so it is considered as a multi criteria decision making (MCDM) problem. Under incomplete or uncertain information, the fuzzy set theory allows us make decisions with approximate reasoning. In order to overcome the uncertainty which is constituted by vague situations in supplier selection, we utilize the “extension of the PROMETHEE method in a fuzzy environment” (F-PROMETHEE). In this chapter, multi criteria supplier selection based on a fuzzy PROMETHEE method with an application to supplier selection decision problem is conducted. The main advantages of the methodology are the user friendliness coming from the linguistic evaluations, and the consideration of the vagueness or fuzziness inherent to the decision making environment. Hence, the method can be an efficient and effective methodology to be used by decision makers on supply chains. The proposed methodology can also be applied to any other selection problem.

https://www.springer.com/cda/content/document/cda_downloaddocument/9783642539381-c2.pdf?SGWID=0-0-45-1443617-p176445722

Multi Criteria Supplier Selection Using Fuzzy PROMETHEE Method

Failure modes and effects analysis (FMEA) is a step-by-step approach for identifying all possible failures in a design, a manufacturing or assembly process, or a product or service. The purpose of the FMEA is to take actions to eliminate or reduce failures, starting with the highest-priority ones. This article presents a basis for prioritizing the healthcare problems using FMEA with linguistic variables and fuzzy if–then rules. Severity rating of healthcare problems is handled under the categories of catastrophic, major, moderate, and minor events. MATLAB 2007 is used to obtain the results of fuzzy if–then rules for prioritizing healthcare failures. A numerical example is given for four possible healthcare problems to be prioritized, which are wrong patient, delay in therapy, wrong analgesic selection, and wrong drug.

Healthcare Failure Mode and Effects Analysis Under Fuzziness

Usage of Metaheuristics in Engineering: A Literature Review

Flexible job shop scheduling problem is a relaxation of the job shop scheduling problem and is one of the well-known combinatorial optimization problems that has wide applications in the industrial fields such as production management, supply chain, transport systems, manufacturing systems. In recent years, many researches have been carried out with different approaches—ranging from mathematical models to heuristic methods—to solve multi objective flexible job shop scheduling problems (FJSSP). This study aims to present the forms of scrutiny of multi-objective FJSSPs and various heuristic techniques used to solve problems in the last decade. This review will allow the reader to select specific methods and follow the guidelines set forth in their future research.

Ozlem Senvar

Papers

Hospital Site Selection via Hesitant Fuzzy TOPSIS

Multi Criteria Supplier Selection Using Fuzzy PROMETHEE Method

Healthcare Failure Mode and Effects Analysis Under Fuzziness

Usage of Metaheuristics in Engineering: A Literature Review

A research survey: heuristic approaches for solving multi objective flexible job shop problems