Efficiency of scientific and technological resource allocation in Chengdu–Chongqing–Mianyang Urban agglomeration: based on DEA–Malmquist index model
Ruochen Li,
Yuyan Luo (),
Borui Chen,
Huan Huang and
Ping Liu
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Ruochen Li: Southwest Jiaotong University
Yuyan Luo: Chengdu University of Technology
Borui Chen: Chengdu University of Technology
Huan Huang: Chengdu University of Technology
Ping Liu: Chengdu University of Technology
Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2024, vol. 26, issue 4, No 90, 10483 pages
Abstract:
Abstract Based on the scale, distribution, and structure of scientific and technological resource allocation, the basic characteristics of scientific and technological resource allocation in Chengdu–Chongqing–Mianyang were analyzed, and the relevant panel data of the three places and the whole region were analyzed using the data envelopment analysis (DEA)-Malmquist index model, spanning the period of 2010–2019. The results show that the overall efficiency of scientific and technological resource allocation in Chengdu–Chongqing–Mianyang shows an upward trend during the study period, which is attributed to the significant increase in the rate of technological progress. The rapid growth in Chongqing and Mianyang is attributed to good policy support, rapid renewal of facilities and institutions, and improved management experience. The relative slowdown in the rate of technological progress in Chengdu may be due to industrial restructuring, coupled with a shift in economic technology from high growth to high quality development. At the same time, Chengdu–Chongqing–Mianyang region is more inclined to cultivate its own R&D capabilities, and the accumulation and upgrading of innovation management technologies are insufficient to meet its innovation needs. Finally, the study proposes countermeasures to improve the efficiency of science and technology resource allocation in Chengdu–Chongqing–Mianyang from macro and micro perspectives.
Keywords: Scientific and technological resources; Chengdu–Chongqing–Mianyang urban agglomeration; Resource allocation efficiency; DEA–Malmquist evaluation model (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10668-023-03153-9
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