Improving Decision-Making for Electric Vehicle Battery Technology
Author Information
Author(s): Qiwen Ye
Primary Institution: School of Economics & Management, South China Normal University, Guangzhou, China
Hypothesis
Can the extended DEMATEL method effectively analyze intuitionistic fuzzy information in decision-making for electric vehicle battery technology?
Conclusion
The study identifies four cause factors and six effect factors that influence the development of electric vehicle battery technology.
Supporting Evidence
- The study identifies critical factors affecting electric vehicle battery technology.
- Expert opinions were aggregated to form a comprehensive analysis of the factors.
- The extended DEMATEL method provides a structured approach to decision-making under uncertainty.
Takeaway
This study helps understand what makes electric vehicle batteries better by looking at different important factors and how they relate to each other.
Methodology
The study uses the extended DEMATEL method to analyze intuitionistic fuzzy information from expert judgments on electric vehicle battery technology.
Potential Biases
Potential bias from expert opinions and the assumption of equal expertise among decision-makers.
Limitations
The study assumes equal weight for all decision-makers and focuses only on quantitative attributes.
Participant Demographics
Participants included three experts from academia and three from the automotive industry.
Digital Object Identifier (DOI)
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