Higher Education Hot Spots: Using Local Indicators of Spatial Association

Lyke, Austin

doi:10.1002/ir.20286

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Spatial Econometric Characteristics1

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2021

2023

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Cited by 2 publications

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“…Local Indicators of Spatial Association (LISA) analysis is applied to the Global Moran's I statistic to test the spatial association of independent variables and dependent variables (Anselin, 1988;Anselin & Florax, 2012;Bednář & Halásková, 2018;Bivand & Wong, 2018;Lyke, 2018;Song et al, 2020;Ali, 2021;Tao & Chen, 2022)…”

Section: Spatial Econometric Characteristicsmentioning

confidence: 99%

Knowledge input and innovation in Visegrad Group (V4) regions: A spatial econometric approach

Wibisono

2023

BGSS

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This paper argues that one of the reasons why innovation in one country leaves another behind could be its spatial geography. Questions relevant to R&D development and technological change are raised on how knowledge inputs affect innovation in the Visegrad Group (V4) (Czech Republic, Hungary, Poland, and Slovakia) and how these factors are spatially dependent. The study results show that regional knowledge inputs (R&D expenditure and R&D personnel) play an essential role in innovation development in Visegrad Group (V4). The study findings also emphasize the importance of R&D funding support in the public sector and R&D personnel capabilities in promoting innovation. This paper intends to make an initial contribution to innovation studies taking regions of Visegrad Group (V4) as the analyzed object and suggests the development of spatial modeling using more up-to-date data to yield more reliable and in-depth results.

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