R&D and pricing strategies in the intelligent vehicle supply chain under cross-organizational cooperative models

跨组织合作模式下智能汽车供应链的研发和定价策略

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Abstract

With the development of automotive intelligence, vehicle manufacturers and technology companies have engaged in cross-industry cooperative research and development (R&D), leading to new cooperative R&D models. In this context, this paper develops game-theoretic models for four distinct cooperative frameworks: the technology-dominant model, the supplier-cooperation model, the manufacturer-dominant model, and the joint decision-making model. This paper aims to explore the conditions under which different cooperative R&D models are applicable and examines the strategic choices associated with each model. The results indicate that if a company is a core industry player, the core component supplier should select the technology-dominant model, while the vehicle manufacturer should choose the manufacturer-dominant model. If it is not a core player, the joint decision-making model is the next best choice. If the goal of R&D cooperation is achieving a high level of intelligence rather than short-term profits, the manufacturer-dominant model is more suitable. Though price wars may emerge, under the technology-dominant model, the supply chain adopts a quality strategy. Across the other three models, quality strategies remain consistent. As the consumer price sensitivity coefficient increases, the supply chain is more likely to adopt both quality and low-price strategies simultaneously. These findings offer valuable insights for making R&D and pricing strategy decisions under cross-organizational cooperative models in the intelligent vehicle supply chain.

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