Implementation of MGWR-SAR models for investigating a local particularity of European regional innovation processes

Furková, Andrea

doi:10.1007/s10100-021-00764-3

Cited by 8 publications

(4 citation statements)

References 31 publications

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“…Like GWR-SAR, MGWR-SAR can also portray both spatial autocorrelation and spatial heterogeneity. Its expression is shown below [ 38 ].…”

Section: Methods and Modelsmentioning

confidence: 99%

“…Addressing these issues is an assessment of China's emergency response capacity in the face of major public health events and an exploration of the equity of resource allocation across China's vast regions. They require cutting-edge research models as tools to accurately identify the spatial distribution characteristics of NAT institutions by comparatively assessing the model fitness of different functions [ 38 – 41 ].…”

Section: Introductionmentioning

confidence: 99%

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Spatial effects of public health laboratory emergency testing institutions under COVID-19 in China

Shi

Wang

Bai

et al. 2023

Int J Equity Health

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Background The transmission of 2019 novel coronavirus (COVID-19) has caused global panic in the past three years. Countries have learned an important lesson in the practice of responding to COVID-19 pandemic: timely and accurate diagnosis is critical. As an important technology of virus diagnosis, nucleic acid testing (NAT) is also widely used in the identification of other infectious diseases. However, geographic factors often constrain the provision of public health services such as NAT services, and the spatial nature of their resource allocation is a significant problem. Methods We used OLS, OLS-SAR, GWR, GWR-SAR, MGWR, and MGWR-SAR models to identify the determinants of spatial difference and spatial heterogeneity affecting NAT institutions in China. Results Firstly, we identify that the distribution of NAT institutions in China shows a clear spatial agglomeration, with an overall trend of increasing distribution from west to east. There is significant spatial heterogeneity in Chinese NAT institutions. Secondly, the MGWR-SAR model results show that city level, population density, number of tertiary hospitals and number of public health emergency outbreaks are important factors influencing the spatial heterogeneity of NAT institutions in China. Conclusions Therefore, the government should allocate health resources rationally, optimise the spatial layout of testing facilities, and improve the ability to respond to public health emergencies. Meanwhile, third-party testing facilities need to focus on their role in the public health emergency response system as a market force to alleviate the inequitable allocation of health resources between regions. By taking these measures to prepare adequately for possible future public health emergencies.

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“…Like GWR-SAR, MGWR-SAR can also portray both spatial autocorrelation and spatial heterogeneity. Its expression is shown below [ 38 ].…”

Section: Methods and Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatial effects of public health laboratory emergency testing institutions under COVID-19 in China

Shi

Wang

Bai

et al. 2023

Int J Equity Health

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“…(1) User-based CFA. The main step of this algorithm is to construct the user-item rating interaction matrix, use the top k with the highest similarity as the neighborhood of the target user, make rating predictions for items not viewed by the target user in the neighborhood, and sort the top N items according to the predicted scores from largest to smallest to generate the final Top-N list of recommended items [5].…”

Section: Cfamentioning

confidence: 99%

Symbiosis Theory and Game Model of Yangtze River Delta Integrated Regional Innovation Ecosystem Based on Collaborative Filtering Algorithm

Zhao

2023

Advances in Transdisciplinary Engineering

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The Yangtze River Delta has gathered talents, capital, technology and many other innovative elements, becoming the region with the highest level of economic development and the most active scientific and technological innovation in China. But at the same time, there are still a series of problems in the development of the Yangtze River Delta, such as the uncoordinated development of the regional innovation system, the imperfect innovation policy system, and the difficulty in adapting to the new era and the rapidly changing external environment. There is a certain gap between the Yangtze River Delta and the world’s leading innovation regions. Therefore, this paper uses the collaborative filtering algorithm (CFA) to study the policy coordination, technology coordination and cultural coordination of the “two provinces and one city” innovation ecosystem in the Yangtze River Delta integrated region, and establishes a dynamic game model for the stakeholders of regional innovation and ecological environment symbiosis, which is beneficial to the realization of coordinated development in the Yangtze River Delta region.

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“…Dutta et al (2020) claimed that it assists countries in overcoming their chronic problems. A huge body of literature such as Brenner and Broekel (2011), Ivanov and Avasilcăi (2014), Smith (2005), Banu (2018), Walker et al (2002), Kim et al (2020), Cirera and Muzi (2020), Ligardo-Herrera et al (2019), Blažek and Kadlec (2019), Furková (2022), and Yu et al (2021), among others, emphasizes the importance of this issue. Further, the existing literature reviews demonstrate the growing interest of researchers in this subject (see Wolfe, 1994;Cooper, 1999;Becheikh et al, 2006;Bloch and Bugge, 2013;Dziallas and Blind, 2019;Haefner et al, 2021;Vrontis and Christofi, 2021).…”

Section: Introductionmentioning

confidence: 99%

Novel Comprehensive MEREC Weighting-Based Score Aggregation Model for Measuring Innovation Performance: The Case of G7 Countries

Ecer¹,

Ayçın²

2022

Informatica

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Innovation can be the greatest hope of overcoming economic challenges. This paper aims to evaluate countries concerning their innovation performances. We introduce an innovation performance evaluation methodology by considering objective factors and applying seven reliable MCDM methods: MEREC, CODAS, MABAC, MARCOS, CoCoSo, WASPAS, and MAIRCA. MEREC calculates the relative weights of indicators considered, while the other techniques decide the ranking order of G7 countries. The Borda rule is then employed to gain an aggregated ranking order. “Business sophistication” is the most critical indicator, whereas the US has the best position regarding the overall ranking. Sensitivity control is as well conducted.

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Implementation of MGWR-SAR models for investigating a local particularity of European regional innovation processes

Cited by 8 publications

References 31 publications

Spatial effects of public health laboratory emergency testing institutions under COVID-19 in China

Spatial effects of public health laboratory emergency testing institutions under COVID-19 in China

Symbiosis Theory and Game Model of Yangtze River Delta Integrated Regional Innovation Ecosystem Based on Collaborative Filtering Algorithm

Novel Comprehensive MEREC Weighting-Based Score Aggregation Model for Measuring Innovation Performance: The Case of G7 Countries

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