Decision-Making under Uncertainty: How Easterners and Westerners Think Differently.

It has long been known that Easterners exhibit more conservative attitudes, cautiousness behaviors, and self-control ability than Westerners; people in Eastern countries show stronger defensive reactions to societal threats than Western people. Are East Asians really risk averters or do some richer underlying preferences drive their behaviors in their decision-making under uncertainty? To answer this question, we examined the risk and ambiguity attitudes of East Asian populations in both gain and loss domains using classical behavioral economic experimental methods. Based on our sample of university students, we found that Easterners are more risk intolerant but more willing to accept ambiguous conditions than their Westerner counterparts in the gain domain.

New method for emergency decision making with an integrated regret theory-EDAS method in 2-tuple spherical linguistic environment.

With the frequent occurrence of various emergency events, emergency decision making (EDM) has become an important research focus recently and many studies have been conducted to decrease the negative impact of emergencies. Normally, it is essential for decision makers to make satisfactory and reasonable emergency decisions in the shortest possible time as inappropriate decisions may result in enormous economic losses and serious social consequences. To ensure that an emergency response can be made efficiently, we propose a new EDM method by integrating regret theory and evaluation based on distance from average solution (EDAS) method within the 2-tuple spherical linguistic environment.

Decades on emergency decision-making: a bibliometric analysis and literature review.

When an emergency occurs, effective decisions should be made in a limited time to reduce the casualties and economic losses as much as possible. In the past decades, emergency decision-making (EDM) has become a research hotspot and a lot of studies have been conducted for better managing emergency events under tight time constraint. However, there is a lack of a comprehensive bibliometric analysis of the literature on this topic.

Failure Mode and Effect Analysis Based on Probabilistic Linguistic Preference Relations and Gained and Lost Dominance Score Method.

Failure mode and effect analysis (FMEA) is a widely used reliability management technology to evaluate the risk of potential failures in a system, product, or service. Nevertheless, the normal risk priority number (RPN) method has been extensively criticized for many deficiencies in practical applications. To overcome the drawbacks of traditional FMEA, plenty of methods have been suggested in previous studies.

An integrated multi-criteria decision making approach with linguistic hesitant fuzzy sets for E-learning website evaluation and selection.

Network teaching has been widely developed under the influence of COVID-19 pandemic to guarantee the implementation of teaching plans and protect the learning rights of students. Selecting a particular website for network teaching can directly affects end users' performance and promote network teaching quality. Normally, e-learning website selection can be considered as a complex multi-criteria decision making (MCDM) problem, and experts' evaluations over the performance of e-learning websites are often imprecise and fuzzy due to the subjective nature of human thinking.

Occupational Health and Safety Risk Assessment based on Combination Weighting and Uncertain Linguistic Information: Method Development and Application to a Construction Project.

OCCUPATIONAL APPLICATIONSOccupational hazards and work-related accidents are a substantial problem in countries around the world. Therefore, it is of great importance to develop appropriate techniques to assess and reduce the risk of occupational hazards. In many situations, however, exact data are inadequate to model real-life scenarios, because of the complexity of occupational health and safety (OHS) risk assessment problems.

Identification of Key Performance Indicators for Hospital Management Using an Extended Hesitant Linguistic DEMATEL Approach.

Performance analysis is of great significance to increase the operational efficiency of healthcare organizations. Healthcare performance is influenced by numerous indicators, but it is unrealistic for administrators to improve all of them due to the restriction of resources. To solve this problem, we integrated double hierarchy hesitant fuzzy linguistic term sets (DHHFLTSs) with the decision-making trial and evaluation laboratory (DEMATEL) and proposed a DHHFL- DEMATEL method to identify key performance indicators (KPIs) in healthcare management.

Failure mode and effects analysis for proactive healthcare risk evaluation: A systematic literature review.

Rationale, Aims, And Objectives: Failure mode and effects analysis (FMEA) is a valuable reliability management tool that can preemptively identify the potential failures of a system and assess their causes and effects, thereby preventing them from occurring. The use of FMEA in the healthcare setting has become increasingly popular over the last decade, being applied to a multitude of different areas. The objective of this study is to review comprehensively the literature regarding the application of FMEA for healthcare risk analysis.

Robot Evaluation and Selection with Entropy-Based Combination Weighting and Cloud TODIM Approach.

Nowadays robots have been commonly adopted in various manufacturing industries to improve product quality and productivity. The selection of the best robot to suit a specific production setting is a difficult decision making task for manufacturers because of the increase in complexity and number of robot systems. In this paper, we explore two key issues of robot evaluation and selection: the representation of decision makers' diversified assessments and the determination of the ranking of available robots.

Identifying Key Performance Indicators for Holistic Hospital Management with a Modified DEMATEL Approach.

Performance analysis is an important way for hospitals to achieve higher efficiency and effectiveness in providing services to their customers. The performance of the healthcare system can be measured by many indicators, but it is difficult to improve them simultaneously due to the limited resources. A feasible way is to identify the central and influential indicators to improve healthcare performance in a stepwise manner.

An integrated decision making approach for assessing healthcare waste treatment technologies from a multiple stakeholder.

With increased worldwide awareness of environmental issues, healthcare waste (HCW) management has received much attention from both researchers and practitioners over the past decade. The task of selecting the optimum treatment technology for HCWs is a challenging decision making problem involving conflicting evaluation criteria and multiple stakeholders. In this paper, we develop an integrated decision making framework based on cloud model and MABAC method for evaluating and selecting the best HCW treatment technology from a multiple stakeholder perspective.

Health-Care Waste Treatment Technology Selection Using the Interval 2-Tuple Induced TOPSIS Method.

Health-care waste (HCW) management is a major challenge for municipalities, particularly in the cities of developing nations. Selecting the best treatment technology for HCW can be regarded as a complex multi-criteria decision making (MCDM) issue involving a number of alternatives and multiple evaluation criteria. In addition, decision makers tend to express their personal assessments via multi-granularity linguistic term sets because of different backgrounds and knowledge, some of which may be imprecise, uncertain and incomplete.

Fuzzy Petri nets Using Intuitionistic Fuzzy Sets and Ordered Weighted Averaging Operators.

Fuzzy Petri nets (FPNs) are an important modeling tool for knowledge representation and reasoning, which have been extensively used in a lot of fields. However, the conventional FPN models have been criticized as having many shortcomings in the literature. Many different models have been suggested to enhance the performance of FPNs, but deficiencies still exist in these models.

Application of interval 2-tuple linguistic MULTIMOORA method for health-care waste treatment technology evaluation and selection.

The management of health-care waste (HCW) is a major challenge for municipalities, particularly in the cities of developing countries. Selection of the best treatment technology for HCW can be viewed as a complicated multi-criteria decision making (MCDM) problem which requires consideration of a number of alternatives and conflicting evaluation criteria. Additionally, decision makers often use different linguistic term sets to express their assessments because of their different backgrounds and preferences, some of which may be imprecise, uncertain and incomplete.

Conceptual framework for holistic dialysis management based on key performance indicators.

This paper develops a theoretical framework of holistic hospital management based on performance indicators that can be applied to dialysis hospitals, clinics or departments in Japan. Selection of a key indicator set and its validity tests were performed primarily by a questionnaire survey to dialysis experts as well as their statements obtained through interviews. The expert questionnaire asked respondents to rate the degree of "usefulness" for each of 66 indicators on a three-point scale (19 responses collected).

A theoretical framework for holistic hospital management in the Japanese healthcare context.

Objective: This paper develops a conceptual framework for performance measurement as a pilot study on holistic hospital management in the Japanese healthcare context.

Methods: We primarily used two data sources as well as expert statements obtained through interviews: a systematic review of literature and a questionnaire survey to healthcare experts. The systematic survey searched PubMed and PubMed Central, and 24 relevant papers were elicited.

Assessment of health-care waste disposal methods using a VIKOR-based fuzzy multi-criteria decision making method.

Nowadays selection of the appropriate treatment method in health-care waste (HCW) management has become a challenge task for the municipal authorities especially in developing countries. Assessment of HCW disposal alternatives can be regarded as a complicated multi-criteria decision making (MCDM) problem which requires consideration of multiple alternative solutions and conflicting tangible and intangible criteria. The objective of this paper is to present a new MCDM technique based on fuzzy set theory and VIKOR method for evaluating HCW disposal methods.

Knowledge acquisition and representation using fuzzy evidential reasoning and dynamic adaptive fuzzy Petri nets.

The two most important issues of expert systems are the acquisition of domain experts' professional knowledge and the representation and reasoning of the knowledge rules that have been identified. First, during expert knowledge acquisition processes, the domain expert panel often demonstrates different experience and knowledge from one another and produces different types of knowledge information such as complete and incomplete, precise and imprecise, and known and unknown because of its cross-functional and multidisciplinary nature. Second, as a promising tool for knowledge representation and reasoning, fuzzy Petri nets (FPNs) still suffer a couple of deficiencies.