Integration of DEMATEL-Based ANP with BOCR Merits for Hospital Sustainability: Evidence from Hospitals in Panama

Assessments studies are conducted to determine a business’ needs to achieve desired conditions. In the case of businesses, such goal is to profit and create value through goods or services. This research focusses on healthcare businesses, such as hospitals, where besides trying to make profit, must care for its patients’ safety and well-being. A novel assessment method will be proposed, in which the criteria interdependencies will be considered, instead of considering them independent. The study makes use of the BOCR analysis, where both positive and negative aspects are considered to get more comprehensive results. The interdependencies will then be assessed using the DANP Method, which will generate a causal diagram showing the total influence of one factor into the others, as well as their influential weights. Through this new application, we can demonstrate which factors are most important, most likely to occur, or have more impact on the business infrastructure

VIKOR Technique:A Systematic Review of the State of the Art Literature on Methodologies and Applications

The main objective of this paper is to present a systematic review of the VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) method in several application areas such as sustainability and renewable energy. This study reviewed a total of 176 papers, published in 2004 to 2015, from 83 high-ranking journals; most of which were related to Operational Research, Management Sciences, decision making, sustainability and renewable energy and were extracted from the “Web of Science and Scopus” databases. Papers were classified into 15 main application areas. Furthermore, papers were categorized based on the nationalities of authors, dates of publications, techniques and methods, type of studies, the names of the journals and studies purposes. The results of this study indicated that more papers on VIKOR technique were published in 2013 than in any other year. In addition, 13 papers were published about sustainability and renewable energy fields. Furthermore, VIKOR and fuzzy VIKOR methods, had the first rank in use. Additionally, the Journal of Expert Systems with Applications was the most significant journal in this study, with 27 publications on the topic. Finally, Taiwan had the first rank from 22 nationalities which used VIKOR technique

Odabir konkurentskih strategija u europskom bankarskom sektoru primjenom pristupa hibridnog odlučivanja

Strategic planning is an eJective tool for long-term planning and utilized by organizations and industries to achieve competitive advantage. Addressing difculties that the European banking sector struggled during and after the global financial crisis (GFC), the purpose of this paper is to raise important questions about the sustainability of the sector and oJers competitive strategy formulations for European policy makers. Empirical findings are accomplished by applying a three phase analysis of SWOT, an integrated model of DEMATEL-ANP (DANP), and fuzzy TOPSIS. Empirical findings from the SWOT analysis suggest a total of twelve factors, which are then incorporated to formulate four strategies. The DANP results illustrate that opportunities dimension has the highest impact and strengths has the lowest among others. The fuzzy TOPSIS results demonstrate that “the European Banking Union (EBU) is expected to remove divergence in the Euro area banking sector” is the most important strategy, whilst “the non-risk based leverage ratio (LR) requirement by Basel III” has the weakest importance among the strategy preferences.Strateško planiranje je učinkovit alat za dugoročno planiranje koje primjenjuju organizacije i industrije za postizanje konkurentske prednosti. S obzirom na poteškoće s kojima se europski bankarski sektor suočava za vrijeme i nakon globalne financijske krize (GFC), svrha ovog rada je podići važna pitanja o održivosti sektora i ponuditi formulacije konkurentnih strategija za europske kreatore politike. Empirijski rezultati postižu se primjenom SWOT analize u tri faze, integriranog modela DEMATEL-ANP (DANP) i ‘fuzzy’ (neizrazitog) TOPSIS-a. Empirijski rezultati SWOT analize ukazuju na ukupno dvanaest čimbenika, koji su potom uključeni u formuliranje četiri strategije. DANP rezultati potvrđuju da faktor prilika ima najveći utjecaj, a snage imaju najniži utjecaj u odnosu na ostala tri faktora. Neizraziti rezultati TOPSIS-a pokazuju da najvažnija strategija jest da “Europska bankovna unija (EBU) ukloni odstupanja u bankarskom sektoru u eurozoni”, dok “zahtjev Basel-a III o nerizičnom omjeru financijske poluge (LR)” ima najmanju važnost medu strategijskim prioritetima

Assessment of the performance of nurses based on the 360-degree model and fuzzy multi-criteria decision-making method (FMCDM) and selecting qualified nurses

Background: Human resources is the most prominent asset of an organization. Despite the constant effort to design optimal and effective systems for assessing employees, evidence shows that managers are not satisfied with the methods and systems to assess employees. Objectives: Researchers wanted to assess the performance of nurses based on the 360-degree model and fuzzy multi-criteria decision-making technique (FMCDM) and selecting qualified nurses. Methods: The present study is descriptive and conducted in 2016 in a hospital at Kashan University of Medical Sciences. This study conducted in three �stages. 1) Identification of criteria and sub-criteria for the performance assessment that classified into five groups (technical skills, human skills, and perceived skills; individual characteristics; and compliance with the organization's rules and regulations). 2) Weighing the criteria and sub-criteria based on the DEMATEL-ANP (DANP) method in a fuzzy environment. 3) Assessing the performance of nurses based on the 360-degree model, which includes supervisors, coworkers, self-assessment, and patients and their companions. In this stage, four groups used the VIKOR questionnaire to assess the performance. Results: Among five criteria of assessment, �Human Skills� earned a top score, and among 21 sub-criteria, �Identify the strengths and weaknesses,� �Suitable relationships with patients,� and �Partnership with colleagues� earned the top score. In the 360-degree model, the supervisor's assessment score was 0.521, with the highest weight, and the self-assessment was 0.042 with the lowest weight. Finally, nurse 3 in children and infants ward earned the highest ranking. Conclusions: The advantage of the proposed method is more realistic results than other methods because the criteria and sub-criteria are weighted, and the importance of each is determined. Hospitals can use the results of this study to assess the performance of medical groups. © 2020 The Author(s) Health profession; Nursing; Assessing the performance, 360-Degree model, Fuzzy multi-criteria decision-making method and qualified nurses © 2020 The Author(s

Optimization of green electro-discharge machining using VIKOR

In the present study an efficient Multi-Criteria Decision Making (MCDM) approach has been proposed for optimization of green electro-discharge machining, because it is a commonly used non-traditional machining process. Green electro-discharge machining is a MultiCriteria Decision Making (MCDM) problem influenced by multiple performance criteria/attributes. These criteria attributes are of two types, qualitative and quantitative. Qualitative criteria estimates are generally based on previous experience and expert opinion on a suitable conversion scale. This conversion is based on human judgment; therefore, obtained result may not be accurate always. These are analyzed using AHP, QFD, Fuzzy techniques etc. reported in literature. So to find the solution of MCDM problems there should be converted quantitative criteria values into an equivalent single performance index called Multi-attribute Performance Index (MPI). Selection of the best alternative can be made in accordance with the MPI values of all the alternatives. In this text, present study highlights application of VIKOR method adapted from MCDM techniques for obtaining the accurate result. Detail methodology of VIKOR method has been illustrated in this report through a case study

Analyzing the global risks for the financial crisis after the great depression using comparative hybrid hesitant fuzzy decision-making models: Policy recommendations for sustainable economic growth

WOS: 000446770200169The aim of this study is to analyze the effects of global risks on financial crises. For this purpose, five different outstanding crises after the Great Depression of 1929 are taken into the consideration. Additionally, four different dimensions are selected regarding global risk by considering the Global Risk Report. Moreover, the hesitant fuzzy DEMATEL, the hesitant fuzzy VIKOR, and the hesitant fuzzy TOPSIS methodologies are used to reach this objective. We concluded that, with respect to global risks, the industry-based dimension has the highest importance in comparison to other dimensions. In addition, we also identified that the 2010 European debt crisis and the 1982 Latin American debt crisis were the most influenced crises in terms of global risk. The main reason for this is that the macroeconomic problems such as high inflation and unemployment had negative impacts on the industries of these countries. Another important point is that the results of the hesitant fuzzy VIKOR and hesitant fuzzy TOPSIS models are quite different, but they are the most similar when the experts do not reach the consensus. This situation shows that this analysis is quite appropriate with respect to the hesitant approach. While considering these aspects, we recommended that countries should firstly focus on the solutions related to industry level problems in order to minimize the global risk. Owing to this issue, it can be more possible to reach sustainable economic growth in the world

A Hybrid Multi-Criteria Decision Model for Technological Innovation Capability Assessment: Research on Thai Automotive Parts Firms

The efficient appraisal of technological innovation capabilities (TICs) of enterprises is an important factor to enhance competitiveness. This study aims to evaluate and rank TICs evaluation criteria in order to provide a practical insight of systematic analysis by gathering the qualified experts’ opinions combined with three methods of multi-criteria decision making approach. Firstly, Fuzzy Delphi method is used to screen TICs evaluation criteria from the recent published researches. Secondly, the Analytic Hierarchy Process is utilized to compute the relative important weights. Lastly, the VIKOR method is used to rank the enterprises based on TICs evaluation criteria. An empirical study is applied for Thai automotive parts firms to illustrate the proposed methods. This study found that the interaction between criteria is essential and influences TICs; furthermore, this ranking development of TICs assessment is also one of key management tools to simply facilitate and offer a new mindset for managements of other related industries

Intelligent Multi-Attribute Decision Making Applications: Decision Support Systems for Performance Measurement, Evaluation and Benchmarking

Efficiency has been and continues to be an important attribute of competitive business environments where limited resources exist. Owing to growing complexity of organizations and more broadly, to global economic growth, efficiency considerations are expected to remain a top priority for organizations. Continuous performance evaluations play a significant role in sustaining efficient and effective business processes. Consequently, the literature offers a wide range of performance evaluation methodologies to assess the operational efficiency of various industries. Majority of these models focus solely on quantitative criteria omitting qualitative data. However, a thorough performance measurement and benchmarking require consideration of all available information since accurately describing and defining complex systems require utilization of both data types. Most evaluation models also function under the unrealistic assumption of evaluation criteria being dependent on one another. Furthermore, majority of these methodologies tend to utilize discrete and contemporary information eliminating historical performance data from the model environment. These shortcomings hinder the reliability of evaluation outcomes leading to inadequate performance evaluations for many businesses. This problem gains more significance for business where performance evaluations are tied in to important decisions relating to business expansion, investment, promotion and compensation. The primary purpose of this research is to present a thorough, equitable and accurate evaluation framework for operations management while filling the existing gaps in the literature. Service industry offers a more suitable platform for this study since the industry tend to accommodate both qualitative and quantitative performance evaluation factors relatively with more ease compared to manufacturing due to the intensity of customer (consumer) interaction. Accordingly, a U.S. based food franchise company is utilized for data acquisition and as a case study to demonstrate the applications of the proposed models. Compatible with their multiple criteria nature, performance measurement, evaluation and benchmarking systems require heavy utilization of Multi-Attribute Decision Making (MADM) approaches which constitute the core of this research. In order to be able to accommodate the vagueness in decision making, fuzzy values are also utilized in all proposed models. In the first phase of the study, the main and sub-criteria in the evaluation are considered independently in a hierarchical order and contemporary data is utilized in a holistic approach combining three different multi-criteria decision making methods. The cross-efficiency approach is also introduced in this phase. Building on this approach, the second phase considered the influence of the main and sub-criteria over one another. That is, in the proposed models, the main and sub-criteria form a network with dependencies rather than having a hierarchical relationship. The decision making model is built to extract the influential weights for the evaluation criteria. Furthermore, Group Decision Making (GDM) is introduced to integrate different perspectives and preferences of multiple decision makers who are responsible for different functions in the organization with varying levels of impact on decisions. Finally, an artificial intelligence method is applied to utilize the historical data and to obtain the final performance ranking. Owing to large volumes of data emanating from digital sources, current literature offers a variety of artificial intelligence and machine learning methods for big data analytics applications. Comparing the results generated by the ANNs, three additional well-established methods, viz., Adaptive Neuro Fuzzy Inference System (ANFIS), Least Squares Support Vector Machine (LSSVM) and Extreme Learning Machine (ELM), are also employed for the same problem. In order to test the prediction capability of these methods, the most influencing criteria are obtained from the data set via Pearson Correlation Analysis and grey relational analysis. Subsequently, the corresponding parameters in each method are optimized via Particle Swarm Optimization to improve the prediction accuracy. The accuracy of artificial intelligence and machine learning methods are heavily reliant on large volumes of data. Despite the fact that several businesses, especially business that utilize social media data or on-line real-time operational data, there are organizations which lack adequate amount of data required for their performance evaluations simply due to the nature of their business. Grey Modeling (GM) technique addresses this issue and provides higher forecasting accuracy in presence of uncertain and limited data. With this motivation, a traditional multi-variate grey model is applied to predict the performance scores. Improved grey models are also applied to compare the results. Finally, the integration of the fractional order accumulation along with the background value coefficient optimization are proposed to improve accuracy