Current Research Bulletin

Independent multibrand workshops operate under intense time pressure and depend heavily on external suppliers for spare parts. When parts sourcing is slow or opaque, workshop capacity is blocked, repair lead times increase, and customer trust erodes. This article examines how parts sourcing can be accelerated by combining four operational levers at the workshop level: systematic cross-referencing of part numbers, structured use of alternative suppliers, explicit return-risk management, and transparent communication of timelines and costs to customers. The study adopts a conceptual-empirical approach. It synthesises findings from fifteen peer-reviewed studies on automotive spare parts logistics, inventory control, demand forecasting, and aftermarket structures. Then it develops an illustrative scenario for a hypothetical multibrand workshop. The scenario contrasts a baseline single-supplier sourcing pattern with a framework-based approach that uses cross-referenced alternatives, a supplier portfolio, and recorded return-risk indicators as decision inputs. Using performance ranges reported in existing empirical research, the article demonstrates how expected sourcing lead times, direct parts costs, and return-related losses may change when the framework is implemented for fast-, medium-, and slow-moving parts. The analysis suggests that the proposed approach can reduce sourcing lead times for medium-moving items, stabilise service performance for slow-moving, high-criticality parts, and improve the overall balance between cost and quality without requiring large local stocks or complex optimisation tools. The article concludes with managerial recommendations for independent workshops and outlines directions for future field-based research.

multibrand workshop, automotive spare parts, cross-referencing, alternative suppliers, return-risk management, lead time, aftermarket logistics

1. Achetoui, Z., Mabrouki, C., & Mousrij, A. (2019). Performance measurement system for automotive spare parts supply chain: A categorization approach. Journal of Transportation and Logistics, 4(1), 31–50.
2. Achetoui, Z., Mabrouki, C., & Mousrij, A. (2022). A balanced performance measurement system for automotive spare parts supply chain. Scientific Journal of Silesian University of Technology. Series Transport, 116, 25–55.
3. Bacchetti, A., & Saccani, N. (2012). Spare parts classification and demand forecasting for stock control: Investigating the gap between research and practice. Omega, 40(6), 722–737.
4. De Leeuw, S., & Beekman, L. (2008). Supply chain-oriented performance measurement for automotive spare parts. International Journal of Automotive Technology and Management, 8(1), 56–70.
5. de Souza, R., Tan, A. W. K., Othman, H., & Garg, M. (2011). A proposed framework for managing service parts in automotive and aerospace industries. Benchmarking: An International Journal, 18(6), 769–782.
6. Huiskonen, J. (2001). Maintenance spare parts logistics: Special characteristics and strategic choices. International Journal of Production Economics, 71(1–3), 125–133.
7. Kennedy, W. J., Patterson, J. W., & Fredendall, L. D. (2002). An overview of recent literature on spare parts inventories. International Journal of Production Economics, 76(2), 201–215.
8. Krykawski, Y., & Fihun, N. (2012). Spare parts logistics of automobile enterprises in conditions of module production. Econtechmod: An International Quarterly Journal.
9. Li, S. G., & Kuo, Y. F. (2008). The inventory management system for automobile spare parts in a central warehouse. Expert Systems with Applications, 34(2), 1144–1153.
10. Mandják, T., Belaid, S., & Narus, J. A. (2018). The impact of institutional changes on the Tunisian auto parts aftermarket. IMP Journal, 12(1), 111–126.
11. Ranabhatt, N. (2025). Demand forecasting in the automotive industry: A systematic literature review. Inventions, 7(4), 73.
12. Rego, J. R. do, & de Mesquita, M. A. (2015). Demand forecasting and inventory control: A simulation study on automotive spare parts. International Journal of Production Economics, 161, 1–16.
13. Roda, I., Macchi, M., Fumagalli, L., & Viveros, P. (2014). A review of multi-criteria classification of spare parts: From literature analysis to industrial evidences. Journal of Manufacturing Technology Management, 25(4), 528–549.
14. Syntetos, A. A., Keyes, M., & Babai, M. Z. (2009). Demand categorisation in a European spare parts logistics network. International Journal of Operations & Production Management, 29(3), 292–316.
15. Turrini, L., & Meissner, J. (2019). Spare parts inventory management: New evidence from distribution fitting. European Journal of Operational Research, 273(1), 118–130.