More is better or in waste? A resource allocation measure of government grants for facilitating firm innovations

Anyu Yu, Qin Zhang, Rongjian Yu and Yu Cheng

Technological Forecasting and Social Change, 2023, vol. 197, issue C

Abstract: To strengthen firms' innovation capability and improve innovation performance, it is not surprising for the government to grant them financial funding. Previous research in allocation of government grants fails to quantitatively identify the wastes within, which leaves a significant research gap. This study contributes to the literature by proposing a novel data envelopment analysis model to deal with the misallocation issue. We first propose a centralized allocation model with the output-oriented focus to identify the effectively used resources or wastes. An algorithm is then proposed to determine the optimal total amounts of allocated resources and eliminate possible wastes. In an application of allocating government grants for high-tech firms, the proposed approach investigates government’s optimal allocation plan of innovative subsidy and tax reduction. We find the mixed impacts of grants on innovation performance and diverse allocation results across different types of firms. More government grants are suggested to be allocated, but excessive investment and unnecessary waste should be alerted in allocation. Impacts of returns to scale characteristics and innovation failure rates on allocation results are also explored. Our results affirm the effectiveness of the proposed approach and provide solid policy implications.

Keywords: Data envelopment analysis; Resource allocation; Government grants; Waste in allocation; Innovation performance (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:197:y:2023:i:c:s0040162523006030

DOI: 10.1016/j.techfore.2023.122918

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