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One of the global ecological problems is the excessive carbon dioxide emissions generated by vehicles in the transport sector, including passenger transport. Therefore, the objective of this investigation was to develop a model that supports the prediction of vehicle variants that will be satisfactory to the customer in terms of: (i) quality level and (ii) environmental impact throughout the life cycle. This model was developed with the following techniques: TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), LCA (Life Cycle Assessment), SMARTER (Specific, Measurable, Achievable, Relevant, and Time-bound), Pareto–Lorenz, and the Multi-Criteria Decision Method rule (7 ± 2). A model test was carried out for production variants of the electric vehicle BEV (battery electric vehicle) for which the quality level and life cycle assessment were estimated. Vehicle quality levels ranged from 0.15 to 0.69, with a weight of 0.75. However, vehicle life cycle scores were estimated in the range of 0.25 to 0.57, with a weight of 0.25. Ultimately, the level of the vehicles' LCA ranged from 0.18 to 0.62. As a result, it was shown that on the basis of various modifications of the quality level of vehicle variants and the corresponding environmental impacts throughout their life cycle, it is possible to predict the vehicle variant that is most satisfactory for the customer and, at the same time, environmentally friendly. The originality of the model relies on supporting the making of sustainable design decisions and the planning of vehicle improvement actions according to customer expectations. Therefore, the model can be used to analyse different types of vehicles by producers and dealers of these products. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative model designed to predict the optimal product prototype within the framework of sustainable development. The model takes into account both quality and environmental impact throughout the entire life cycle of the product, with a specific focus on light electric vehicles. By incorporating customer expectations using the Weighted Sum Model, the model assesses vehicle quality based on the importance of various criteria. Employing life cycle evaluations guided by the Pareto-Lorenz rule, environmental impact for vehicle prototypes is modeled. The resulting Quality-Environmental Indicator of LCA (QLCA) facilitates a qualitative environmental analysis, aiding in the selection of prototypes that align with customer expectations. The model proves effective in guiding decisions related to product development, providing a comprehensive approach to evaluating product value. Notable contributions to the scientific community include the introduction of the QLCA model, which integrates quality and environmental assessments, and underscores the significance of open innovation, sustainable development, and sensitivity analysis for organizational adaptation. Future research directions involve adapting the model to larger customer samples, exploring production costs, and assessing its applicability across diverse industries and contexts to enhance its universality and practical implications. [ABSTRACT FROM AUTHOR]