Since strategic decisions associated with costs directly influence the income of companies in statically competitive markets, predicting the future income of supply chains (SCs) is a critical issue in the strategic supply chain network design (SCND). The origin of this research is a real-life problem in oil product supply chains in the Middle East, where all SC entities used to be government-related bodies with a centralized management system.
Recently, some governments have decided to privatize some facilities (devolution), at the retailer level, now considering only one wholesaler for each set of retailers. Therefore, for each private owner in the oil product industry, there will be just one regional wholesaler in addition to its dependent retailers.
This problem should be of interest to the following industries:
- Automotive fuel retail brands and their controlling oil companies: Total, Esso, Petronas, Shell, BP.
- Tire manufacturing companies: Bridgestone, Michelin, Goodyear, Continental and Pirelli.
- Car retailers in automotive supply chains: Ford, Vauxhall, BMW, Peugeot, VW.
- Oil product supply chains: e.g., a real-life oil product supply chain in a Middle–East country.
This study focuses on a single-product supply chain with two levels: At the upstream level, a manufacturer or a wholesaler supplies the product to retailers, which are at the downstream level and come up against retailers of another competing supply chain in the target market. Hence, the aim of the research is to predict the possible effects of future competition between the new entrant and an existing supply chain, integrating such forecasts into the SCND stage of the new supply chain. Combined with a SCND model, this projection can improve the future performance of the supply chain, compared to previous hierarchical decision-making structures. The models described combine elements of competition and SCND, which make them significantly different from those usually presented in the literature. This work intends to extend new, sufficiently rich, and flexible mathematical modelling frameworks to answer key research questions, that are commonly associated with supply chains, e.g.: Where should retail facilities be located? Or what kind of retail facilities are needed in terms of capacity?
Zanjirani Farahani R., Rezapour S., Drezner T., Amiri-Aref M. (2015). Locating and capacity planning for retailers of a new supply chain to compete on the plane. Journal of the Operational Research Society, 66(7), 1182-1205.