Cross-Sectoral Inter-Country Linkages under the Belt and Road Initiative: Chinese ICT Services Value Added Inflows to Manufacturing Exports in the New Eurasian Land Bridge Economies

Cieśłik, Ewa

doi:10.3390/su12208675

Cited by 3 publications

(2 citation statements)

References 35 publications

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“…As the core of AI, machine learning is rising. Deep learning is a new method in machine learning [27], and it is a method based on artificial neural networks, which include the feedforward deep network, feedback deep network, and bidirectional deep network [28]. The deep belief network belongs to the bidirectional deep network in deep learning.…”

Section: Deep Belief Networkmentioning

confidence: 99%

Application of Deep Belief Network for Sustainable Development via Deep Learning to Export Credit Risk Assessment Under the Belt and Road Strategy

Li,

Pu,

Song

et al. 2023

Advances in Transdisciplinary Engineering

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The purpose of the study is to reduce the export credit risk of enterprises, and the export credit risk assessment of enterprises under the belt and road strategy based on deep learning is discussed. First, the research background and deep belief networks are introduced. Second, the contrast divergence algorithm based on the deep belief model is improved on the restricted Boltzmann machine. Finally, the deep belief network of classification and partition is constructed and simulated. The results show that the test accuracy of the classification and partition of the restricted Boltzmann machine (CPRBM) constructed is higher than that of the restricted Boltzmann machine (RBM). When the accuracy of the algorithm is verified under the condition of unbalanced two classification samples in a relatively small amount of datasets, the accuracy of the CPRBM algorithm is 93.71%, and the accuracy of the RBM algorithm is 89.86%. In the optimization stage of the deep belief networks, the convergence rate of the CPRBM is slower than that of the RBM. Since the optimized system increases the penalty term in the first training stage of the deep belief networks, the penalty term is canceled in the second stage of optimization. At three time points, the algorithm accuracy of the CPRBM is higher than that of the RBM. The simulation results are consistent with the previous experimental results. Although the accuracy is not high at the third time point, the CPRBM algorithm still has some advantages. Compared with the accuracy of the support vector machine (SVM) and the deep extreme learning machine (DELM), the CPRBM algorithm based on deep belief networks has the highest accuracy at any time point. The CPRBM algorithm constructed has obvious advantages compared with common models, and the overall performance of the algorithm is better. The conclusions provide the support for the sustainable development of the economy under the Belt and Road strategy.

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Section: Deep Belief Networkmentioning

confidence: 99%

Application of Deep Belief Network for Sustainable Development via Deep Learning to Export Credit Risk Assessment Under the Belt and Road Strategy

Li,

Pu,

Song

et al. 2023

Advances in Transdisciplinary Engineering

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“…The New Eurasian Land Bridge (Cieślik, 2020;Pomfret, 2021), also called the Eurasian Land Bridge or the Northern Route, is a link between the 2nd Pan-European Transport Corridor (Berlin-Minsk-Moscow-Nizhny Novgorod) and the 2nd Railway Cooperation Organization Corridor (Moscow-Astana-Lianyungang). It runs through China, Kazakhstan, Russia, Belarus, Poland and reaches Western Europe.…”

Section: Digitisation Of the New Silk Road Supply Chainmentioning

confidence: 99%

Analysis of Digitalisation Needs Improving the Supply Chain Efficiency for New Silk Road Transport Corridor

Nowak

Kirchner

Koliński

2022

Ekonomska misao i praksa

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Based on a review of scientific literature, as well as a detailed analysis of business processes, it should be stated that the increase in the volume of sales on a global scale generates not only the need to analyse the development of business, but above all the need to conduct scientific research in the field of improving logistics processes and information flow in the supply chain. The relatively long time of delivery of ordered goods, the complexity of customs processes and logistic service make it necessary to apply innovative digitalization solutions in order to be able to monitor and react quickly to disruptions. These analyses are most noticeable in global supply chains, which is why the New Silk Road became the research area. In this paper, the authors focused on conducting a review of digitalisation solutions that improve the efficiency in supply chains. The review was conducted both in the research aspect, by verifying knowledge on the subject in the scientific literature available on the Web of Science and Scopus databases, but also in the practical aspect, by analysing needs and trends in the use of supply chain digitalisation in business practice. The research aspect was based on the application of the CANVAS model for the identification of business needs in the supply chain digitalisation aspect and on surveys for importance degree analysis for the identified needs in business practice. The research carried out in this area is the result of cooperation between Lukasiewicz Research Network – Poznan Institute of Technology and Poznan School of Logistics. The research was conducted in 2021 and the first half of 2022 among Polish logistic companies.

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Assessment of the Drivers and Effects of International Science and Technology Cooperation in Xinjiang in the Context of the Belt and Road Initiative

Wang

Dong

2023

Sustainability

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International science and technology (S&T) cooperation is one of the important ways to ensure the continuous development of a national innovation system. “One Belt One Road” advocates the concepts of common business, common construction, and sharing, and new countries and regions are constantly added. However, different countries/regions have different natural and socio-economic characteristics, so the main controlling factors affecting their international S&T cooperation may not be the same. Therefore, this paper uses a combination of multi-source data and multiple methods to collectively construct an assessment model of the driving effect of international S&T cooperation in Xinjiang. The evaluation results of the entropy-weighted TOPSIS model show that the contributions of S&T level, city nature, and S&T investment to international S&T cooperation in Xinjiang are 22.9%, 22.3%, and 20.4%, respectively. Singapore, Germany, and Russia are the top three countries in terms of the effectiveness of international S&T cooperation with Xinjiang. The results of the STIRPAT model show that the total number of R&D personnel and the number of R&D personnel per 1000 workers are the main factors affecting the driving effect of international S&T cooperation. The former can be regarded as the stabilizer of international S&T cooperation. This paper’s findings can provide theoretical support for the efficient integration of diverse advantageous resources among cooperating subjects.

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Cross-Sectoral Inter-Country Linkages under the Belt and Road Initiative: Chinese ICT Services Value Added Inflows to Manufacturing Exports in the New Eurasian Land Bridge Economies

Cited by 3 publications

References 35 publications

Application of Deep Belief Network for Sustainable Development via Deep Learning to Export Credit Risk Assessment Under the Belt and Road Strategy

Application of Deep Belief Network for Sustainable Development via Deep Learning to Export Credit Risk Assessment Under the Belt and Road Strategy

Analysis of Digitalisation Needs Improving the Supply Chain Efficiency for New Silk Road Transport Corridor

Assessment of the Drivers and Effects of International Science and Technology Cooperation in Xinjiang in the Context of the Belt and Road Initiative

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