Criterion for evaluating used car purchases in India using MCDM: an automobile solution towards a circular economy

Sakhhi Chhabra et al.

International Journal of Logistics Economics and Globalisation2025https://doi.org/10.1504/ijleg.2025.146823article
ABDC C
Weight
0.50

What the paper says

The rise in purchasing and maintenance costs of new cars has accelerated the used vehicle market. However, car buyers' decision-making criteria for selecting used cars in emerging markets do not mimic the same trend as the new car market for developed nations. To evaluate used car buyers' purchases, we approached car dealers and salespeople to understand preferred attributes and sub-attributes. Subsequently, we apply analytic hierarchy process (AHP) to evaluate data collected from buyers. The results indicated that the number of kilometres, price, and age of the car are sequentially the key attributes used car buyers consider. Also, they are less brand-conscious than new-car buyers, prefer petrol vehicles over diesel, and stated Maruti as the preferred brand compared to Hyundai and Toyota. These findings shall aid dealers and resellers in accelerating used car sales in the emerging market and help achieve the circular economy goal by decarbonising transportation.

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https://doi.org/https://doi.org/10.1504/ijleg.2025.146823

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@article{sakhhi2025,
  title        = {{Criterion for evaluating used car purchases in India using MCDM: an automobile solution towards a circular economy}},
  author       = {Sakhhi Chhabra et al.},
  journal      = {International Journal of Logistics Economics and Globalisation},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijleg.2025.146823},
}

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Criterion for evaluating used car purchases in India using MCDM: an automobile solution towards a circular economy

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.