Forecasting vehicle's spare parts price and demand

Abdallah Alalawin (The Hashemite University, Zarqa, Jordan)
Laith Mubarak Arabiyat (The Hashemite University, Zarqa, Jordan)
Wafa Alalaween (The University of Jordan, Amman, Jordan)
Ahmad Qamar (The Hashemite University, Zarqa, Jordan)
Adnan Mukattash (The Hashemite University, Zarqa, Jordan)

Journal of Quality in Maintenance Engineering

ISSN: 1355-2511

Publication date: 22 December 2020

Abstract

Purpose

These days vehicles' spare parts (SPs) are a very big market, and there is a very high demand for these parts. Forecasting vehicles' SPs price and demand are difficult because of the lack of data and the pricing of the SPs is not following the normal value chain methods like normal products.

Design/methodology/approach

A proposed model using multiple linear regression was developed as a guide to forecasting demand and price for vehicles' SPs. A case study of selected hybrid vehicle is held to validate the results of the research. This research is an original study depending on quantitative and qualitative methods; some factors are generated from realistic data or are calculated using numerical equations and the analytic hierarchy process (AHP) method; online questionnaire and expert interview survey.

Findings

The price and demand for SPs have a linear relationship with some independent variables is the hypothesis that is tested. Even though the proposed models are generally recommended for predicting demand and price, in this research the linear relationship models are not significant enough to calculate the expected price and demand.

Originality/value

This research should concern both academics and practitioners since it provides new intuitions on the distinctions between scientific and industrial world regarding SPs for vehicles as it is the first study that investigates price and demand of vehicles' SPs.

Keywords

Citation

Alalawin, A., Arabiyat, L.M., Alalaween, W., Qamar, A. and Mukattash, A. (2020), "Forecasting vehicle's spare parts price and demand", Journal of Quality in Maintenance Engineering, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JQME-03-2020-0019

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Publisher

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Emerald Publishing Limited

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