The main objective of this study is to comprehensively investigate individuals' vaccination intention against COVID-19 during the second wave of COVID-19 spread in Vietnam using a novel hybrid approach. First, the Decision-Making Trial and Evaluation Laboratory based on Grey Theory (DEMATEL-G) was employed to explore the critical factors of vaccination intention among individuals. Second, Partial Least Squares-Structural Equation Modeling (PLS-SEM) was applied to test the hypotheses of individual behavioral intention to get the vaccine to prevent the outbreak of COVID- 19. A panel of 661 valid respondents was collected from June 2021 to July 2021, and confidentiality was maintained for all data obtained. The results identified that perception of COVID-19 vaccination and trust in vaccination strategy directly associated with individuals' COVID-19 immunization. Hence, the perceived severity of COVID-19 has an indirect impact onCOVID- 19 vaccination intentions via the perception of the COVID-19 vaccine. These findings indicated that the government's information about vaccines is necessary for the new phase of vaccination intervention strategies in Vietnam. Therefore, the study suggests that the government needs to give complete information about the role of vaccines prioritizes transparency in official information about COVID-19 vaccines to allay concerns about side effects, allowing for the most appropriate policy formulation and implementation to encourage public vaccination. Future studies can apply PLS-SEM and other MCDMmodels with the fuzzy, hesitant numbers to re-evaluate the feasibility, validity and reliability of this research's proposed model. © 2022 Tech Science Press. All rights reserved.

A Hybrid Grey DEMATEL and PLS-SEM Model to Investigate COVID-19 Vaccination Intention

The complexity of human resource management (HRM) requires an integrated method of subjective and objective evaluation rather than intuitive decisions such as multicriteria decision-making (MCDM). This study proposes a hybrid Genetic Algorithm and Decision-Making Trial and Evaluation Laboratory (GA-GDEMATEL)-based grey theory systems approach to solve personnel selection problems in a real-case study from a Vietnamese agriculture manufacturing and services corporation. First, the GDEMATEL approach is deployed to investigate the causal relationship between the proposed criteria and determine the subjective weights of recruitment criteria. Second, the GA model utilizes selection, crossover, and mutation with a new objective function of Minimizing Distance to Ideal Solution (MDIS) to find the optimal solution for robust recruitment based on GDEMATEL weights. Notably, the GA-GDEMATEL could be exploited effectively in a short time to optimize personnel selection in “deep and wide” aspects. Moreover, the study’s findings on recruiting evaluation and selection problems provide a support model and new research perspectives to the literature and help managers achieve the best solution by dealing with qualitative and quantitative criteria more effectively.

/pdf/ga-gdematel-a-novel-approach-to-optimize-recruitment-and-2elpib1j.pdf

GA-GDEMATEL: A Novel Approach to Optimize Recruitment and Personnel Selection Problems

Application of MADM methods in Industry 4.0: A literature review

Coronavirus diseases 2019 (COVID-19) pandemic is an essential challenge to the health and safety of people, medical members, and treatment systems worldwide. Digital technologies (DTs) have been universally introduced to improve the treatment of patients during the pandemic. Nevertheless, only a few governments have been partly successful in executing the DT strategies. In this regard, it is critical to demonstrate a suitable strategy for the governments. This problem is built based on the experts' opinions with some conflicting criteria to evaluate various types of alternatives. Hence, this research presents a new multi-criteria decision-making (MCDM) model under uncertain conditions. For this reason, interval-valued intuitionistic fuzzy sets (IVIFSs) are employed to help decision-makers (DMs) evaluate in a broader area and cope with uncertain information. Moreover, a new extended weighting method based on weighted distance-based approximation (WDBA) and a new combined ranking approach are proposed to determine the DMs' weights and rank the alternatives under IVIF conditions. The developed weighting method is constructed based on computing the DMs' weights with objective criteria weights. Furthermore, a new ranking approach is proposed by obtaining two ranking indexes separately: The first and second ranking indexes are calculated according to the positive and negative ideal solutions distances and the nature of criteria weights, respectively. Afterward, the final values of rankings are computed by considering a new aggregating procedure. The results of the proposed model represent the first alternative as the best strategy. Comparisons between the IVIF-TOPSIS and IVIF-VIKOR methods are also provided to investigate the proposed model to determine the rankings of main alternatives. Sensitivity analyses are conducted to check the reliability and the robustness of the model. For this purpose, criteria weights are analyzed to compute the dependencies' degree of the new extended weighting method. The dependencies of the ranking model are discussed on the criteria weights as well. 

/pdf/a-multi-criteria-decision-making-model-with-interval-valued-2q0ump7u.pdf

A Multi-Criteria Decision-Making Model with Interval-Valued Intuitionistic Fuzzy Sets for Evaluating Digital Technology Strategies in COVID-19 Pandemic Under Uncertainty

A two-phased decision-making based grey theory framework for the best choice of payment methods in international trade

As an essential and exciting topic in financial management, MCDM has been widely used in evaluating financial performance to improve the suitability and reliability of financial indicators with respect to the impacts of both qualitative and quantitative information. This chapter aims to present a hybrid MCDM approach to evaluate the Vietnamese banking sector's performance under COVID-19 impacts. The proposed method utilizes The Criteria Importance Through Intercriteria Correlation (CRITIC) technique to determine objective weights of financial ratios. Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is employed to obtain the cause-effect relationship and the subjective weights based on experts’ judgments. Bank alternatives’ ranking is estimated using the ﻿Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach. The empirical data of 23 Vietnamese commercial banks gathered from 2019-Q3/2020 is illustrated. The results of this chapter show that the COVID-19 pandemic has significant effects on the quality of assets, the liquidity of banks, and the growth rate. When the economy slows down, banks face the challenge of keeping up with demand and raising additional resources to balance the situation. For better intelligent risk management systems, faster digital transformation is needed for the Vietnamese banking system. Furthermore, the proposed method offers useful insights and is applicable to many businesses, proving helpful in dealing with complex criteria problems for stakeholders.

P. H. Nguyen

Papers

A Hybrid Method of MCDM for Evaluating Financial Performance of Vietnamese Commercial Banks Under COVID-19 Impacts