• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.561-573
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• 2021

Knowing how to build and maintain consumer trust is crucial for e-commerce. Despite the number of empirical studies that have explored the factors that influence consumer trust, none of them considers the relative importance of different antecedents and how they interact to influence consumer trust. Therefore, based on the integrated Decision Making Trial and Evaluation Laboratory (DEMATEL) and Interpretive Structural Modeling (ISM) approaches, we establish a hierarchical structural model, which not only demonstrates the intensity of the relationships but also identifies the interdependence among the drivers of consumer trust in E-commerce. The findings confirm that propensity to trust is the most important determinant of consumer trust. The brand-related factors and platform-related factors are prominent in the process of building trust as they influence consumer trust indirectly through propensity to trust. Geographic location, demographic variables, and high security are identified as the root causes that affect consumer trust through other trust antecedents. Furthermore, the findings of this study offer valuable insights into an important element of e-commerce and provide a useful platform for future research. More represented samples and factors are encouraged for further research to ensure research fairness and minimize consumer distrust and uncertainty.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.53-62
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• 2020

The COVID 19 pandemic has led to a new global recession and is still causing a lot of issues because of the delays in the employment of people. This scenario has severe consequences for many countries' labor markets in the world. This problem's complexity and importance requires an integrated method of subjective and objective evaluation rather than intuitive decisions. This research aims to investigate sustainable indexes for assessing the unemployment problem by using a Multi-Criteria Decision-Making Model (MCDM). Grey theory and Decision Making Trial and Evaluation Laboratory (GDEMATEL) are deployed to transform the experts' opinions into quantitative data. The analysis based on 20 crucial criteria is employed to determine the weights of sustainability of unemployment problems. The results revealed that the top ten of determinants are Economic growth, Industrialization, Foreign direct investment, Real GDP per capita, Education level, Trade Openness, Capacity Utilization Rate, Urbanization, Employability skills, Education system expansion, which have the most significant effects on the unemployment rate under COVID 19 impacts. Furthermore, GDEMATEL could effectively assess the sustainable indicators for unemployment problems in "deep and wide" aspects. The study proposes the Grey MCDM model, contributes to the literature, provides future research directions, and helps policymakers and researchers achieve the best solutions to the unemployment problems under "economic shocks."

• Nuclear Engineering and Technology
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• v.56 no.9
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• pp.3472-3482
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• 2024

This study proposes a modified extended cognitive reliability and error analysis method (CREAM) for achieving a more accurate human error probability (HEP) in advanced control rooms. The traditional approach lacks failure data and does not consider the common performance condition (CPC) weights in different cognitive functions. The modified extended CREAM decomposes tasks using a method that combines structured information analysis (SIA) and the extended CREAM. The modified extended CREAM performs the weight analysis of CPCs in different cognitive functions, and the weights include cognitive, correlative, and important weights. We used the extended CREAM to obtain the cognitive weight. We determined the correlative weights of the CPCs for different cognitive functions using the triangular fuzzy decision-making trial and evaluation laboratory (TF-DEMATEL), and evaluated the importance weight of CPCs based on the interval 2-tuple linguistic approach and ensured the value of the importance weight using the entropy method in the different cognitive functions. Finally, we obtained the comprehensive weights of the different cognitive functions and calculated the HEPs. The accuracy and sensitivity of the modified extended CREAM were compared with those of the basic CREAM. The results demonstrate that the modified extended CREAM calculates the HEP more effectively in advanced control rooms.