ABSTRACT
Investment in education technology (EdTech) is a complex decision problem for universities during the post-Covid era. With the objective to assess the quality and adoptability of education supply chain, a novel analytical evaluation model approach is proposed, based on quality function deployment and combinative distance-based assessment. To deal with uncertainty in the evaluation process, fuzzy theory is integrated into the model. To establish the house of quality matrix, technology-based stakeholders' requirements were identified and classified in four dimensions: economic and financial, technology adoption, sustainability, competencies. Moreover, nine supplier criteria were assumed. Based on expert evaluations, the results suggest that financial credit and supplier collaboration are the most prominent attributes to evaluate suppliers, while environmental commitment is sorted as the least important criterion. The results reveal that the three dominant suppliers, which provide the best response to the identified criteria, are providers of cloud service technology. © 2022
ABSTRACT
The efficiency of transport companies is a very important factor for the companies themselves, as well as for the entire economic system. The main goal of this paper is to develop an integrated model for determining the efficiency of representative transport companies over a period of eight years. An original model was developed that includes the integration of DEA (Data Envelopment Analysis), PCA (Principal Component Analysis), CRITIC (Criteria Importance Through Inter criteria Correlatio), Entropy and MARCOS (Measurement Alternatives and Ranking according to the COmpromise Solution) methods in order to determine the final efficiency of transport companies based on 10 input-output parameters. The results showed that the most efficient business performance was achieved in the period 2014-2017, followed by slightly less efficient results. Then, extensive sensitivity analysis and comparative analysis were performed, which confirmed, to some extent, the previously obtained results. In the sensitivity analysis, 30 scenarios with changes in the weights of criteria were created, while the comparative analysis was carried out with three other MCDM (Multi-Criteria Decision-Making) methods. Finally, the rank correlation index was determined using the Spearman and WS (Wojciech Salabun) correlation coefficients. According to the final results, very efficient years can be separated that can be the benchmark for furthering the business.
ABSTRACT
Level-based weight assessment (LBWA) model is a recently introduced algorithm for determining criteria weights for multi-criteria group decision making. In this paper, the authors aim to extend the basic framework of LBWA in the picture fuzzy (PF) environment using actual score (AS) measures of the picture fuzzy numbers (PFN). They apply this extended framework in addressing a real-life problem pertaining to social entrepreneurship or social entrepreneurs (SE) in the context of COVID-19. They endeavor to identify the critical challenging factors of SE in the new normal. They list the challenges as revealed through literature review and take the opinion of a group of SEs using PF linguistic scale. They then apply the proposed framework, actual score-based picture fuzzy LBWA. They notice that ability to withstand disruption risk and show resilience and fund availability and creation of a supporting business ecosystems are the major challenges that SEs face in the new normal. They carry out validity checking and sensitivity analysis, which show reasonable consistency and stability in the result.
ABSTRACT
Purpose: The coronavirus disease 2019 (COVID-19) pandemic has subjected a considerable strain on the healthcare (HC) systems around the world. The most affected countries are developing countries because of their weak HC infrastructure and meagre resources. Hence, building the resilience of the HC system of such countries becomes essential. Therefore, this study aims to build a resilience-based model on the HC sector of Pakistan to combat the COVID-19 and future pandemics in the country. Design/methodology/approach: The study uses a novel hybrid approach to formulate a model based on resilient attributes (RAs) and resilient strategies (RSs). In the first step, the multi-criteria decision-making (MCDM) technique, i.e. full consistency method (FUCOM) is used to prioritize the RAs. Whereas, the fuzzy quality function deployment (QFD) is used to rank the RSs. Findings: The findings suggest “leadership and governance capacity” to be the topmost RA. Whereas “building the operational capacity of the management”, “resilience education” and “Strengthening laboratories and diagnostic systems” are ranked to be the top three RSs, respectively. Practical implications: The model developed in this study and the prioritization REs and RSs will help build resilience in the HC sector of Pakistan. The policymakers and the government can take help from the prioritized REs and RSs developed in this study to help make the current HC system more resilient towards the current COVID-19 and future pandemics in the country. Originality/value: A new model has been developed to present a sound mathematical model for building resilience in the HC sector consisting of FUCOM and fuzzy QFD methods. The main contribution of the paper is the presentation of a comprehensive and more robust model that will help to make the current HC system of Pakistan more resilient. © 2021, Emerald Publishing Limited.
ABSTRACT
Hospitals around the world, as health institutions with a key role in the health system, face problems while providing health services to patients with various types of diseases. Currently, those problems are intensified due to the pandemic caused by SARS-CoV-2 virus. This pandemic has caused an extreme spread of the disease with constantly changing needs of patients which impacts the capacities and overall functioning of hospitals. In order to meet the challenge of the COVID-19 (COronaVIrus Disease- 2019) pandemic, health systems must adjust to new circumstances and establish separate hospitals exclusive for patients infected with SARS-CoV-2 virus. In the process of creating COVID-19 hospitals, health systems face a shortage of medical professionals trained for work in COVID-19 hospitals. Using this as a starting point, this study puts forward a two-phase model for the evaluation and selection of nurses for COVID-19 hospitals. Each phase of the model features a separate multiple-criteria model. In the first phase, a multiple-criteria model with a dominant criterion is formed and candidates who meet the defined requirements are evaluated. In the second phase, a modified multiple-criteria model is formed and used to evaluate medical professionals who do not meet the requirements of the dominant criterion. By applying this model, two groups of medical professionals are defined: 1) medical professionals who completely meet the requirements for working in COVID-19 hospitals and 2) medical professionals who require additional training. The criteria for evaluation of medical professionals in this multiple-criteria model are defined based on research conducted on medical professionals assigned to the COVID-19 Crisis Response Team during the COVID-19 pandemic in the Republic of Serbia. The model was tested on a real example of evaluating medical professionals assigned to the COVID-19 hospital in Sombor. The model for evaluating medical professionals presented in this paper can help decision makers in hospitals and national policy makers to determine the readiness level of hospitals for working in the conditions of the COVID-19 pandemic, as well as underline the areas in which hospitals are not ready to meet the challenges of the pandemic. © 2020 Regional Association for Security and crisis management. All rights reserved.
ABSTRACT
Healthcare systems worldwide are facing problems in providing health care to patients in a pandemic caused by the SARS-CoV-2 virus (COVID-19). The pandemic causes an extreme disease to spread with fluctuating needs among patients, which significantly affect the capacity and overall performance of healthcare systems. In addition, its impact on the sustainability of the entire economic and social system is enormous and certain sustainable management strategies need to be selected. To meet the challenges of the COVID-19 pandemic and ensure sustainable performance, national healthcare systems must adapt to new circumstances. This paper proposes an original multi-criteria methodology for the sustainable selection of strategic guidelines for the reorganization of a healthcare system under the conditions of the COVID-19 pandemic. The selection of an appropriate strategic guideline is made on the basis of defined criteria and depending on infection capacity and pandemic spread risk. The criteria for the evaluation of strategic guidelines were defined on the basis of a survey in which the medical personnel engaged in the crisis response team during the COVID-19 pandemic in the Republic of Serbia participated. The Level-Based Weight Assessment (LBWA) model and Measuring Attractiveness by a Categorical-Based Evaluation Technique (MACBETH) method were used to determine the weight coefficient criteria, while a novel fuzzy Ranking of Alternatives through Functional Mapping of Criterion Subintervals into a Single Interval (RAFSI) model was used to evaluate the strategic guidelines. The proposed multi-criteria methodology was tested in a case study in the Republic of Serbia. The validity of the proposed methodology is shown through the simulation of changes in input parameters of Bonferroni aggregation functions and through a comparison with other multi-criteria methodologies.