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This study aims to effectively support decision-makers in evaluating leading e-commerce companies in Vietnam from a sustainability perspective. In addition, this study evaluates and analyzes criteria that affect the performance of e-commerce companies in Vietnam to find the best practices for e-commerce implementation of managers. In this way, companies can save costs and increase marketing and promotion efficiency, helping to reach more customers. In doing so, an integrated framework based on MCDM is proposed for the first time in e-commerce industry assessment. In the first stage, the fuzzy decision making trial and evaluation Laboratory method is applied to determine the weights of 9 criteria based on collected data. This study lists prominent quantitative evaluation criteria, taking into account the sustainability aspect. In the second phase, ranking the top 12 e-commerce companies in Vietnam according to their performance based on these nine criteria was done by applying the neutrosophic fuzzy axiomatic design method. According to an analysis of the data, the external financial assistance coefficient (12.7%) is the most crucial factor determining how competitive international e-commerce businesses are. The results of this study can help underperforming companies make strategic decisions to improve their performance. Integrating these two techniques provides a new method for evaluating global trading companies that have hitherto remained unaddressed in the trading industry and, therefore, leave a gap that needs to be investigated. [ABSTRACT FROM AUTHOR]

The product design process, fraught with uncertainties and ambiguities in its requirements and constraints, commonly traverses multiple stages, each emphasizing distinct design aspects. This engenders heterogeneity in decision-making criteria, rendering the effective integration of information from various stages of product design decision-making (PDDM) a pivotal task in identifying the optimal design solution. Surprisingly, limited research has attended to the challenge of consolidating such heterogeneous information across multiple PDDM stages. To bridge this gap, our study employs real numbers, interval numbers, and linguistic terms to capture the heterogeneous judgments of decision-makers. We fuse the Maximization Deviation Method with the analytic hierarchy process (AHP) for determining indicators' weights, while decision-makers' weights are derived through a dual consideration of uncertainty measure using fuzzy entropy and a distance-minimization model applied to the PDDM matrix for achieving consistency. Leveraging the advantage of axiomatic design, product design alternatives are evaluated based on their PDDM information content of PDDM matrices. Given the multistage nature of product design, stages' weights are computed by assessing the information content and consistency degree of PDDM matrices at each stage. Ultimately, our approach achieves multistage heterogeneous decision-making fusion in product design through information axiom weighting. A case study involving the decision-making process for a specific numerical control machine design illustrates the efficacy of our method in integrating multistage heterogeneous PDDM data, yielding a comprehensive perspective on the viability of product design schemes. Results show that the ranking sequence of the product design schemes solidifies to x3 > x2 > x1 in stages 2 and 3 of PDDM, diverging from the initial order observed in stage 1 (x2 > x3 > x1), while the fused result from the multistage heterogeneous PDDM analysis aligns with the later stages' rankings, indicating the credibility and persuasiveness are fortified. This methodology thus offers a robust framework for synthesizing and navigating the uncertainties and complexities inherent in multistage heterogeneous PDDM contexts. [ABSTRACT FROM AUTHOR]