What is it about?
This article models R&D competition as a multi-effort asymmetric contest in which two firms invest costly effort to improve two components of product quality. Component quality depends on firms’ effort, competencies, and efficiencies, while overall quality is aggregated using a Cobb–Douglas technology with parameters governing the responsiveness of overall quality to component qualities. Effort costs are convex and separable, and firms’ market shares are determined through a micro-founded contest success function based on relative quality. The framework links optimal multicomponent effort decisions to both firm-specific and technological parameters, enabling comparative statics analysis. The results show that changes in structural parameters affect equilibrium effort in both components by altering competitive strength and competition intensity. Improvements in the weaker firm’s competency or efficiency increase effort by both firms, whereas improvements in the stronger firm in one component reduce effort across components when differences in competitive strength are large.
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Why is it important?
When firms must allocate effort across different aspects of R&D, they need to understand how changes in their and their competitors' competency, efficiency, and quality responsiveness affect their and competitors’ effort choices across these aspects. Consider the case of R&D efforts in quantum computing. The quality of quantum computing is highly responsive to hardware quality. The focus of hardware research is to develop stable and scalable qubits. The model delivers a set of results that has important practical implications. Modelling competency as a separate attribute allows the analysis to uncover new insights, highlighting the importance of gaining competency. A less efficient firm becomes more competitive due to increased competence. In general, the model suggests that firms would be induced to increase efforts across all components if the weaker firm gains competency or efficiency in one component. In contrast, if the stronger firm gains competency, both firms reduce effort.
Perspectives
While developing a new product, firms often need to allocate R&D efforts across multiple components or features of a single product to improve its quality in different dimensions, thereby enhancing the overall quality of the product. For example, enhancing the quality of an artificial intelligence (AI) system requires R&D efforts across several areas, such as the core reasoning and planning algorithms, tool integration and orchestration, user interfaces, scalability, and security. Integrating the large language models (LLM) in agentic AI systems with application programming interfaces (API) and enabling efficient data exchange between the LLMs and external tools boosts their overall effectiveness. The extant literature on R&D competition and investment in quality enhancement did not explicitly consider R&D efforts spent on multiple aspects of a product's quality, or the quality of different constituent components of the product, to enhance the product's overall quality. To address this need, this paper develops a formal model of R&D contests between two firms that compete in new product development by choosing efforts to improve their products' component qualities or features.
Dr Sumit Sarkar
XLRI Jamshedpur School of Business and Human Resources
Read the Original
This page is a summary of: Effort choice in a two-component R&D contest between heterogeneous firms, Oxford Economic Papers, July 2026, Oxford University Press (OUP),
DOI: 10.1093/oep/gpag026.
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