Development of pricing assessment methodology for used vehicles in Bangladesh’s automotive industry utilizing Delphi technique, analytic hierarchy process, and linear regression analysis

Md. Rasfeq Hossain (), Dewan Sabbir Ahammed Rayhan () and Iftekhar Uddin Bhuiyan ()
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Md. Rasfeq Hossain: Bangladesh University of Engineering and Technology (BUET)
Dewan Sabbir Ahammed Rayhan: Bangladesh University of Engineering and Technology (BUET)
Iftekhar Uddin Bhuiyan: Bangladesh University of Engineering and Technology (BUET)

Journal of Revenue and Pricing Management, 2025, vol. 24, issue 6, No 8, 624 pages

Abstract: Abstract The used vehicle business segment of Bangladesh’s automotive industry is expanding tremendously though this business faces significant challenges due to the absence of a justified pricing methodology. Traditionally, financial entities like banks and insurance companies often rely on a generic approach, applying a flat depreciation rate of 15% for assessing the price of used vehicles, disregarding the vehicle’s technical conditions. This study aimed to resolve this problem by introducing a comprehensive pricing assessment methodology that evaluates the technical conditions of the used vehicle and provides a fair price for the vehicle so that both the buyers and sellers are in a win–win situation. This study integrated the market surveys, the Delphi technique, the Analytical Hierarchy Process (AHP), and Linear Regression Analysis to develop a more equitable and comprehensive pricing mechanism for used vehicles named as ‘Pricing Chart’. The market survey was conducted through a meticulously designed questionnaire targeting current buyers and sellers of the used vehicle market. The survey, conducted in two phases, had a sample size of a hundred participants, determined through a sample size formula. The survey identified forty-three (43) pivotal factors that customers want while negotiating the price of a used vehicle. The most influential pivotal factors were the performance of the transmission (98% of respondents), vehicle brand (96%), and spare availability (95%). Moreover, the SWOT analysis based on the survey identified that the lack of technical assessment facilities, the absence of a recognized body, and the lack of structured pricing methods were the major weaknesses of the used vehicle market. Further, the Delphi technique elucidated 28 influential decision factors from the 43 pivotal factors, among them vehicle age, technical soundness, overall appearance, brand, and after-sales performance stand as the most critical factors. These factors were then prioritized using the AHP to ascertain their relative importance in pricing decisions. The 28 influential factors were evaluated and categorized into five (5) distinct groups for the experts to be able to respond rationally and consistently in the AHP analysis. Each group was allotted with four (4) individual sub-factors. The AHP resulted that the priority weights of engine performance, driving performance, physical appearances, vehicle brand, and vehicle history factors were 0.35, 0.17, 0.14, 0.17, and 0.17, respectively. This indicates that engine performance is the most influential factor for determining price and accounts for 35% of a used vehicle’s total cost. The four sub-factor of engine performance i.e., engine, fuel consumption, load capacity, and cooling system had an individual impact of 41%, 20%, 19%, and 20%, respectively, upon engine performance. The results of the linear regression analysis showed that vehicle depreciation increased over time, with R2 = 0.997, standard error = 0.017, slope = 0.044, and intercept = −0.011. According to the developed age index, a used vehicle’s life cycle had a 100% cumulative depreciation rate over 23 years, and if the vehicle was older than 23 years, the value stayed at 100%. The culmination of this work is a dynamic ‘Pricing Chart’ that has been substantiated through validation studies.

Keywords: Bangladesh automotive industry; Used vehicle assessment and pricing; SWOT analysis; Delphi technique; Analytical hierarchy process (AHP); Linear regression analysis (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1057/s41272-025-00534-9

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