As a bridge and link between China and Central Asian countries, logistics infrastructure plays an important role in the process of forming a new development pattern of “dual circulation” and mutual promotion. Based on the panel data of Central Asian countries from 2010 to 2019, this paper uses random effect model to analyze the impact on the cross-border agricultural product supply chain between China and Central Asian countries. The results show that the logistics development level, railway transport connectivity, road transport connectivity, economic development level, market size, and common border of Central Asian countries positively affect the development level of the supply chain at different significance levels. Among them, the degree of railway transport connectivity has the greatest impact on the supply chain, followed by the common border, and then the level of logistics development. Moreover, the geographical advantage cannot be underestimated and it plays a positive role in promoting the high-quality development of cross-border agricultural product supply chain. China borders Kazakhstan, Kyrgyzstan, and Tajikistan, and the agricultural product import and export trade quota is significantly greater than that of other Central Asian countries. Based on the analysis, we propose to strengthen efforts to build a high-quality logistics system, build an efficient land transport network, and break through cross-border logistics congestion and difficulties.
With the development of global economic integration and the continuous promotion of the “Belt and Road” initiative, the agricultural trade supply chain has become an important part of the agricultural trade supply chain of countries along the “Belt and Road”. Through transnational connectivity, the level of economic and trade cooperation has been improved, providing favorable conditions for the development of a high-quality trade supply chain serving broad areas. Therefore, building a sound and stable supply chain of agricultural products has important practical and theoretical significance for improving the level of economic and trade cooperation of countries along the “Belt and Road” and promoting China’s high-quality economic development. The results show that the trend line of agricultural product trade supply chain performance between China and Central Asia shows a significant downward trend (non-Data Envelopment Analysis efficiency still accounts for a large proportion, and the comprehensive benefits are affected by economies of scale, which is mainly related to the economic conditions of Central Asian countries). The influencing factors of each dimension have significant positive effects on the performance of the agricultural trade supply chain between China and Central Asia to varying degrees and can maximize the performance of China’s Central Asian agricultural trade supply chain through the influencing factors of each dimension of Central Asian countries within the optimal promotion interval. This study recommends improving the information processing efficiency of both parties, predicting market demand, and shortening relevant payment and trade links to improve the efficiency of logistics and transportation between China and Central Asian countries. China’s assistance to the logistics and transportation infrastructure of Central Asian countries can effectively strengthen the connectivity between China and Central Asian countries to promote the overall performance level of the supply chain and achieve mutually beneficial results.
Expanding employment channels for rural households is a crucial means of enhancing the income of rural residents and enhancing the quality of rural employment. This study examines the impact of digital skills on rural laborers’ employment choices and explores the underlying mechanisms by using data from the China Family Panel Studies (CFPS) spanning 2014–2018. By employing various models, including the Probit, IV, mediated effects, and propensity-score-matching methods, the study reveals that digital skills have a significant impact on rural laborers’ employment choices. Specifically, digital skills increase rural labor’s employment opportunities in nonfarm and employed employment while reducing the proportion of informal employment. Additionally, the analysis indicates that the main channels through which digital skills influence rural labor’s employment choices are human and social capital. A heterogeneity analysis further reveals that work-study and social-entertainment skills have a more significant effect on rural laborers’ nonfarm and employed employment opportunities while inhibiting informal employment. Hence, to enhance the quality of future rural employment, the government must encourage rural workers to enhance their digital literacy and digital application skills while improving digital infrastructure.
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