Performance Evaluations and Influencing Factors of the Agricultural Product Trade Supply Chain between China and Central Asian Countries

Abstract

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.

1. Introduction

Since China joined the WTO in 2001, China has become increasingly closer to economic and trade exchanges with countries in Central Asia (Central Asian countries refer to the five countries of Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan, and Turkmenistan). Data shows that the total bilateral trade between China and Central Asian countries increased by 20 times from 2000 to 2020, and the total imports and exports of China have also increased by about 10 times during the same period, which indicates the high-quality cooperation between China and Central Asian countries and its contribution the Chinese economy. Development has played an increasingly important role. At the same time, with the continuous deepening of cooperation between China and Central Asian countries, the field of trade cooperation is also continuously expanding, including the field of equipment, the field of agricultural products, the field of mineral fuel, and the field of logistics facilities. Moreover, China’s exports to Central Asian countries are mainly primary products. Central Asian countries are mainly resource–energy products for China’s exports. The trade between the two makes up for the other party’s development shortcomings and improves the efficiency of resource utilization (http://www.mofcom.gov.cn/article/beltandroad/index_zh.shtml, accessed on 31 October 2022).

In 2013, China proposed the “Belt and Road” initiative to provide development opportunities for countries. Relying on the existing bilateral and multilateral mechanisms between China and relevant countries, and with the existing and effective regional cooperation platforms, the “Belt and Road” aims to borrow the historical symbols of the ancient Silk Road, hold high the banner of peaceful development, actively develop economic cooperation partnerships with countries along the route, and jointly build a community of interests, a community of destiny, and a community of responsibility with political mutual trust, economic integration, and cultural tolerance, especially for Central Asian countries. At the same time, changes in the global natural environment and the shrinking world economy also challenged and impacted the cooperation between China and Central Asian countries. To this end, in 2016, the most important document of the Chinese government pointed out that in order to ensure domestic food security and the supply of major agricultural products, it is necessary to make full use of the two resources and markets at home and abroad, ameliorating insufficient domestic agricultural resources and improving the agricultural operation environment (https://www.fmprc.gov.cn/web/ziliao_674904/1179_674909/202206/t20220609_10700888.shtml, accessed on 31 October 2022).

In recent years, the union and games between global economies have shown an increasingly intense trend. A series of emerging technical methods have been introduced in the field of logistics in the 1990s, which have been continuously improved and updated in theory of logistics management. In order to meet the development of the times and meet customer requirements, the logistics field is gradually concrete, and plays an important role in work, information, and funds. Additionally, many subjects such as terminal consumers can promote the improvement of operating efficiency from production to circulation in the coordination of market participation subjects in various parties, creating a comprehensive supply chain is an important part of China’s economic development. The logistics industry’s medium and long-term development plan (2014–2020) clearly proposes to improve the industrial structure and implement the overall strategy of regional development to implement a good industrial chain development system. The development of the industrial chain requires the leading role and radiation role of regional logistics hub cities and national logistics hub cities, thereby achieving cross-regional coordinated development of the logistics industry. To this end, the important strategies such as the “Silk Road Economic Belt”, the “Yangtze River Economic Belt”, and the “Maritime Silk Road Economic Belt” proposed by China build a logistics channel and important logistics centers connected to China and foreign countries, in line with the development direction of national strategy. It focuses on building strategic transport arteries in West Asia, South Asia and Central Asia, and on building transport arteries and key aviation hubs connecting rivers and seas and land and sea in the face of ASEAN. It also builds a joint system between countries and provinces to achieve the goal of sharing information resources and connecting basic logistics facilities. Under this opportunity, the construction of the Silk Road Economic Belt and the strengthening of the construction of transportation arteries in the western region can optimize the regional transportation environment and promote the development of special agricultural products industry, bulk cargo logistics industry and mineral products industry.

Xinjiang, China, as the bridgehead of the “Belt and Road”, has a unique geographical advantage. Xinjiang, China, borders Kazakhstan, Kyrgyzstan and Tajikistan. It is an important channel and window to China to Central Asian countries. The construction of the “Belt and Road” can promote the western, eastern, and central regions, not only to play the key window function and regional advantages of Xinjiang’s opening to the west, but also to further promote the communication and interaction between West Asia, Central Asia, and South Asian countries. Essentially, therefore, as the key hub of traffic along the “Silk Road Economic Belt”, economic, trade logistics and cultural science education bases, Xinjiang needs to continuously improve its infrastructure and use unique geographical advantages to further consolidate its mportant core position. The “Fourteenth Five -Year Plan and the Outline of the Variety Outline of 2035” emphasized the need to vigorously build the modern transportation industry, focusing on the construction of the International Logistics Corridor. In accordance with the support of Xinjiang’s core area, with the support of important cities such as Kashgar and Urumqi, the hub logistics advantages are radiated to Qinghai, Ningxia, Gansu, Shanxi and other provinces to connect the logistics channels in the northwest region of China Unicom to build a domestic supply chain network. This will further promote the international logistics network connecting Western and Central Asia, and even European countries. Data shows that after the initiative of jointly building the “the Belt and Road” was put forward in 2013, the agricultural trade scale between China and Kyrgyzstan, Kazakhstan, Turkmenistan and Tajikistan increased by 39.6%, 30.7%, 14.7%, and 13.9%, respectively, in 2014 compared with the previous year. In 2021, Kazakhstan will rank first in the agricultural trade between China and the five Central Asian countries, with a total trade volume of 574 million USD, accounting for 53%. The second is Uzbekistan, with a total trade volume of 302 million USD, accounting for 28% (http://www.mofcom.gov.cn/article/beltandroad/index_zh.shtml, accessed on 31 October 2022). China’s agricultural products exported to the five Central Asian countries mainly include dried fruits, fresh fruits, drinks, etc. In 2021, China will mainly import wheat, oilseeds and barley from Kazakhstan, and cotton, flax, dried apricots and cherries from Kyrgyzstan; cotton and hemp silk are mainly imported from Tajikistan and Turkmenistan, and agricultural and sideline products such as dry beans and cotton and hemp silk are mainly imported from Uzbekistan. Additionally, with the advancement and popularization of internet technology, China’s supply chain development opportunities and challenges coexist. In recent years, the development of the supply chain has also faced certain opportunities and adjustments. On the one hand, the proposal of the “Belt and Road” initiative has brought development opportunities to the development of agricultural products. At the same time, the progress of internet technology has greatly improved the business environment, increased the trade volume between countries, and accelerated the rapid development of cross-border e-commerce. On the other hand, with the rapid development of China’s economy, the overall and related node companies of agricultural product trade supply chain and related node companies also face many problems (https://www.fmprc.gov.cn/web/ziliao_674904/1179_674909/202206/t20220609_10700888.shtml, accessed on 31 October 2022). Due to the rapid growth of China’s foreign trade, the infrastructure of important cities in related logistics hubs is lagging behind and cannot meet the throughput of goods. Meanwhile the high-quality and characteristic agricultural products produced by the majority of farmers are not tight enough with core enterprises, resulting in trade development dividends cannot benefit to the general public. Therefore, it is necessary to strengthen the construction of the agricultural product trade supply chain, strengthen the construction of high-quality agricultural product production bases in China, increase China’s agricultural products in the foreign agricultural product market, accelerate the process of agricultural industrialization, and then effectively realize the exchanges and docking with the international agricultural product trade market.

This paper studies the performance evaluation and influencing factors of agricultural product trade supply chain. The research on the performance evaluation and related influencing factors of agricultural product trade supply chain is not an integrated system as a whole, and there is no mature research on the construction of indicator system of influencing factors of agricultural product trade supply chain performance, most of which are scored by experts. Subjective evaluation methods and ostensibly related research are lacking in objective performance evaluation and empirical research combining theory and practice. Therefore, research on methods that can provide reference for agricultural trade supply chain performance evaluation, construction of relevant evaluation indicators, empirical analysis of relevant influencing factors, and improvement path of performance improvement is relatively lacking.

2. Literature Review

The trade supply chain is an important carrier of cross-border procurement. With the acceleration of economic globalization, especially due to the development of modern technologies such as transportation, the internet, and communications, the world is becoming smaller and smaller, forming a “global village”. A comprehensive study of the theoretical achievements related to cross-border e-commerce of agricultural products, agricultural product transactions, and cross-border logistics of agricultural products has come to the conclusion that cross-border e-commerce of agricultural products plays the role of means, cross-border transportation of agricultural products plays the role of channels and processes, and agricultural products transactions play the role of goals and tasks. In addition, the mutual checks and balances among e-commerce, cargo transportation, and agricultural product transactions are also the key incentives for the three to achieve “cross-border” integration. In terms of the system dimension, the integration of the three is in a sense dependent on the stable operation of the agricultural product trading supply chain system. The supply chain is a worldwide chain that integrates information collection, product circulation and marketing, product manufacturers, and procurement of production materials [1,2,3]. Cross-border supply chain refers to the general term for the import and export supply chain of products between two countries or regions, and involves a series of activities such as production, e-commerce, logistics, and cross-border sales involved in import and export trade activities [4,5,6,7] (Figure 1).

There are a lot of studies about agricultural product trade supply chains. Three types of topics are discussed in the following sections.

2.1. Performance Evaluation and Methods of Agricultural Product Trade Supply Chain

According to relevant literature at home and abroad, there are a few research results on the performance and risk of the agricultural product trade supply chain, and the main content of the research focuses on the evaluation of general agricultural product supply chain performance and risk. To study the performance evaluation mechanism of an agricultural products transportation system connected with agricultural supermarkets, a corresponding hierarchical analysis framework was designed, combining three aspects: the environment, the operation effect of the mechanism, and the internal structure of the mechanism. Additionally, 34 specific evaluation indicators of three layers have been formed [8,9]. The agricultural product supply chain constructed a structural equation model for the performance evaluation of the agricultural product supply chain in line with the development principle from three aspects: finance, operation and environmental responsibility [10]. The supply chain performance factors of agricultural product circulation enterprises mainly include industrial scale, cost, agricultural product competitiveness, industry environment, learning and growth ability, integration of agricultural product supply chain, etc. [11]. Some scholars constructed a performance evaluation of agricultural product supply chain using the DEA method from six aspects: procurement cost, warehouse and distribution cost, order timeliness rate, warehouse turnover rate, high quality rate, and net profit rate [12]. The performance evaluation index system of agricultural green supply chain from the aspects of pollution reduction, resource utilization rate, waste recycling rate, resource reuse rate, and the green environmental protection awareness of the agricultural product supply chain.

It is true that with the proposal of the “Belt and Road” joint construction initiative, the accelerated pace of agricultural cooperation between China and countries along the route and the “going global” of agricultural products, and the prominence of cross-border agricultural product trade, some researchers have paid attention to the risks of agricultural supply chain cooperation [13]. In terms of industry risk, social risk, policy risk, natural risk, man-made risk, and biological risk, the intuition level fuzzy model was used to construct the agricultural product supply chain cooperation risk evaluation index system [14]. The Analytic Hierarchy Process (AHP) model was used to construct an index system for the risk assessment of agricultural product supply chain from the aspects of the internal environment and the external environment of the agricultural product supply chain [15]. Factor analysis was used to study the cross-border e-commerce evaluation index system; the criterion layer includes 8 first-level indicators, and the index layer includes 15 second-level indicators [16]. In order to construct and improve the performance system for evaluating the supply chain of agricultural products, it is necessary to effectively improve the efficiency of operation and management, improve the corresponding profit level, effectively distribute the income, and at the same time improve the responsiveness of the market, set reasonable prices [17]. The supply chain of agricultural products involves some stakeholders, which need to be evaluated objectively and effectively, and ultimately achieve the goal of judging the overall system performance of the supply chain [18]. The method of benchmarking to conduct a comparative study on the development of the agricultural product value chain and the operation effect of the agricultural product supply chain in Italy, Spain, Egypt, Morocco, and Tunisia, and revealed the differences. There is a great relationship between the effect and the maturity level of the value chain, The different cities in the development of the agricultural product value chain are embodied in the ability to transform innovative technologies and the ability to respond to market demand [19]. In the process of world integration of the transportation industry, cross-border transportation and multimodal transportation will greatly contribute to the development of cross-border e-commerce, and clarify the future of the cross-border freight industry [20]. Development needs to focus on exploring how to coordinate the operation of transnational e-commerce. The supply chain operation mode of local cross-border e-commerce and third-party freight companies should integrate three levels of information, business content, and business processes [21]. In the world product chain and supply chain, the important way to realize the transfer of raw materials to the distribution and terminal service market lies in logistics transportation, combined with the long-term operation of the freight industry. E-commerce technology means the operability of the multinational e-commerce supply chain is explored from the perspective of multimodal transport [22].

2.2. Cross-Border E-Commerce and Logistics of Agricultural Products

From a national perspective, problems such as unbalanced development present potential hidden dangers that affect the quality and safety of agricultural products. Lack of a sound logistics mechanism and the establishment of a sound information security and credit guarantee mechanism have always become domestic cross-border agricultural products. The development of e-commerce is hindered [23]. Cross-border e-commerce agricultural products are often affected by factors of quality and safety, including the update rate of legislative norms, warehouse management software, selection of logistics enterprises, customs clearance procedures, the proportion of cold chain transportation, quality certification, etc. [24]. The whole process of cross-border agricultural product circulation needs to be equipped with cold chain infrastructure. At present, the level of cold chain facilities in China and developed countries is quite different, and the problems of high cost and low efficiency make the development of cross-border agricultural products e-commerce face challenges and larger practical problems [25]. Although overseas warehouses and border warehouses improve the efficiency of cross-border logistics and overseas service quality, there are problems such as high costs [26]. Cross-border logistics has become one of the biggest obstacles to the development of e-commerce [27]. E-commerce logistics still has high costs, poor timeliness, a low degree of transparency and visualization, and a lack of high-end service capabilities and lack of high-end services [28]. The development model of cross-border logistics is showing an increasingly innovative trend. Logistics and transportation are part of the operation process of cross-border e-commerce, and consumers pursue better products and services. However, merchants are more inclined to consider costs and expenses. Cross-border logistics and transportation play an intermediate role between the two parties, and its operation effect and efficiency will have an impact on cross-border e-commerce.

2.3. The Relationship between International Trade, Investment and Supply Chain

Compared with developing countries in general, the bottleneck of development in Central Asian countries lies in the underdevelopment of related transportation and other infrastructure, which not only affects the development of their own foreign trade, but also restricts the flow of capital with other neighboring countries [29]. The weak infrastructure of Central Asian countries is a bottleneck restricting the attraction of foreign investment in agriculture and affects bilateral trade [30]. China and Central Asian countries have complementary geographical advantages and resource endowments. The focus of agricultural investment is to focus on the infrastructure related to agricultural trade, to build inter-industry investment platforms, and to build cross-border agricultural industry chains, as well as promoting the development of bilateral cross-border supply chains [31]. Capital-related business investment is to change the performance of trade supply chains [32]. Some scholars selected variables such as China’s direct investment flow to countries along the Silk Road Economic Belt, China’s import trade volume of countries along the Silk Road Economic Belt, and the level of overseas engineering cooperation between China and countries along the Silk Road Economic Belt. This paper explores the degree of the formation of a multinational supply chain, and analyzes the relevant influencing factors [33]. Export and investment indicators to measure the development of a cross-border supply chain is based on the research of global supply chain country trade theory, and the global supply chain is the flow of products on a global scale to realize the supply chain through import and export trade [34,35,36]. The growth of the logistics factor input (transportation and warehousing infrastructure, logistics-related information technology) can reduce the cost of foreign trade to the greatest extent and stimulate the growth of foreign trade, and the volume of logistics and transportation promotes the increase of foreign trade, and the development of logistics and transportation system should be given priority to promote the progress of foreign trade [37,38]. Achieving connectivity will effectively strengthen the supply chain links between the two countries, enhance the trade and investment relevance of members in the region, reduce the flow costs of production factors and products, and create software and hardware conditions for regional economic integration [39].

From the relevant literature research, it is found that the relationship between international trade and foreign direct investment cannot be separated from the development of supply chain cooperation. Cross-border supply chain management belongs to the category of management research, and related issues such as foreign investment and international trade belong to the category of economics research [33,34]. Therefore, this paper argues that international trade, foreign direct investment and cross-border supply chains are closely related. In order to objectively reflect the performance status and important influencing factors of the agricultural trade supply chain between China and Central Asian countries, based on the basic facts of the agricultural trade supply chain, combined with the relevant theoretical knowledge of logistics, information flow, capital flow, business flow, and supply chain risk related to the supply chain, and comprehensively considering the characteristics of each link of the agricultural trade supply chain, the performance evaluation index system of the agricultural trade supply chain is constructed from an objective perspective. The existing literature rarely mentions the influencing factors and indicators of the agricultural trade supply chain performance, and the existing literature does not reach an agreement on the influencing factors of the agricultural trade supply chain performance. On the basis of this evaluation index system, combined with the micro and macro related content, the paper constructs the influencing factors indicators of the agricultural trade supply chain performance in China and Central Asia, and conducts relevant empirical analysis.

3. Materials and Methods

3.1. Data Envelopment Analysis (DEA)

The main methods used by domestic and foreign scholars for supply chain performance evaluation include: the DuPont analysis method, the balanced score method, the analytic hierarchy process (AHP), the Wall score method, the Delphi method, the fuzzy analysis method, the DEA, and other comprehensive data analysis methods, in view of the different main concerns and evaluation angles of various methods in the research process, among which the AHP, the Wall score method, the Delphi method, the fuzzy analysis method, etc., and the advantages of the above methods are simple and easy to implement, but they have the disadvantages of strong subjectivity and more anthropic factor interference. Moreover, the process of performance evaluation and analysis of the trade supply chain is a systematic project affected by many factors, and there are many processing links, so all performance evaluation methods have their own advantages and disadvantages. By comparing the evaluation principles and processes of various methods, it can be seen that DEA method has natural advantages in the problem of multiple inputs and multiple outputs [40]. In the model of the DEA method, the weights of variables are obtained through mathematical programming, rather than being assigned subjectively by the evaluator, and there is no requirement on whether the measurement units of the input-output indicators are consistent. DEA method does not need to know the functional relationship between indicators in advance, as long as it can accurately find comprehensive and representative input and output indicators. Compared with other methods, DEA method has more prominent advantages in eliminating subjective human factors and simplifying mathematical operations. Therefore, this paper uses the DEA method to measure the performance of the agricultural product trade supply chain between China and Central Asia. DEA is a brand-new research field using the intersection of operations research, management science and mathematical economics [41]. Due to the use of panel DEA method, this paper not only stabilizes the frame of reference, but also effectively deals with the problem of temporal condition changes, and in order to make the performance evaluation method more reliable, we refer to the authoritative existing literature [42]. At present, the most representative DEA methods have two basic models, the BCC model and the CCR model. CCR model is the first and most basic model of DEA proposed by Charnes, Cooper, and Rhodes (1978) [43]. The basic assumption of the CCR model is that the return to scale of the decision-making unit (DMU) is unchanged. Theoretically, the production process corresponding to this CCR model should meet the convexity assumption, conicity assumption, invalidity assumption and minimum assumption. However, in some cases, it is inaccurate to describe the production possibility with convexity and conicity. In actual trading activities, this assumption is often untenable, while the BCC model is an improved version of the CCR model, which assumes that the return to scale is variable. Due to the changing environment, it is impossible to maintain the same production scale, and the assumption that the return to scale is constant is difficult to realize in reality. The scale will affect the output benefit of social production. Therefore, the BCC model was proposed by Banker, Charnes, and Cooper in 1984. It was improved by the CCR model. The model assumes variable returns to scale, which can not only calculate the comprehensive benefits of DMUs, but also calculate the technical benefits and scale benefits of DMUs, and the output orient BCC model will be adopted for empirical analysis. DEA method is a mature performance evaluation method is the performance evaluation method of this paper [44] (Figure 2).

Figure 2. Flow Chart of Performance Evaluation.

Figure 2. Flow Chart of Performance Evaluation.

$$\left\{\begin{array}{l}\min \theta -\epsilon ({\stackrel{⌢}{e}}^T{S}^{-}+e^T{S}^{+})\\ {\displaystyle \sum _{j=1}^m{X}_j}{\lambda }_j+S^{-}=\theta X_0\\ {\displaystyle \sum _{j=1}^m{Y}_j{\lambda }_j-S^{+}}=Y_0\\ {\displaystyle \sum _{j=1}^m{\lambda }_j=1}\\ S^{-}\ge 0;S^{+}\ge 0;{\lambda }_j\ge 0\end{array}\right.$$

(1)

Among them, j = 1,2 …, m represents the decision-making unit (DMU), X represents the input vector, Y represents the output vector, S⁻, S⁺ represents the slack, and θ represents the overall efficiency. When θ = 1, S⁻ = 0, S⁺ = 0, it indicates the optimal comprehensive performance state of the decision-making unit. When θ = 1, S⁻ > 0, S⁺ > 0, it means that the decision-making unit is weakly effective; when θ < 1, it means that the decision-making unit is invalid.

The existing literature divides the performance evaluation status into four levels. The content of this chapter draws on the classification methods of related scholars to classify the performance evaluation status according to the standard, as shown in

Table 1. Performance Evaluation Status.

0~0.35	0.35~0.65	0.65~0.85	0.85~1.00
poor	medium	good	high quality

.

3.2. Tobit Model

In some cases, it is easy to see that although the dependent variable is a continuous variable, due to certain constraints, the data is truncated or deleted, so that the value of the dependent variable is fixed within a certain range. This dependent variable is called a restricted dependent variable. The problem studied in this chapter is the influencing factors of the development efficiency of the digital economy. The dependent variable is the comprehensive benefit (DEA) of the performance of the agricultural trade supply chain. The value range of the benefit is 0–1, which just conforms to the characteristics of the restricted dependent variable model. At this time, if the general regression model is used for analysis, it is easy to make a deviation between the results obtained and the real results. As one of the restricted dependent variable models, the Tobit regression model is usually applied to the analysis of the restricted explanatory variables, which can just make up for this defect. Therefore, this chapter will use the Tobit model to conduct regression analysis on the influencing factors of agricultural product trade supply chain performance [45]. This model can be seamlessly combined with the DEA model. The standard Tobit model is as shown in Formula (2).

$$y_i=\alpha +\beta x_i+{\epsilon }_i$$

(2)

where y_i is a dependent variable, and x_i is an independent variable, ε_i is the disturbance term.

3.3. Data Sources and Sample

This paper studies the performance evaluation of the agricultural product trade supply chain between China and Central Asian countries. Considering the availability of relevant data, the research sample is China and Central Asian countries (Kazakhstan, Kyrgyzstan, Tajikistan), and the research period is 2010–2019. The main data comes from the United Nations Open Trade Database (UN Comtrade), the World Bank Database (World Bank Database), China’s Foreign Investment Bulletin (Foreign Investment), the World Economic Forum, the website of the Ministry of Foreign Affairs of China, the “Belt and Road” Big Data Center, the Ministry of Transport and the Capital Airport, the Ministry of Commerce of the People’s Republic of China, the Asian Infrastructure Investment Bank, and the Ministry of Commerce of the People’s Republic of China. These sources have no direct data on policy communication, people–to–people bonds, infrastructure connectivity, and financial integration. Therefore, the principal component analysis is used to obtain the data, and the data is further dimensionless; the principal component analysis and factor analysis methods are more commonly used, and the relevant models will not be repeated (please refer to Appendix A for relevant data results).

The DEA method requires non-negative data in the application, and the public factor data of the indicators such as policy communication, people–to–people bond, infrastructure connection, and financial integration in the evaluation indicators have some negative values. Therefore, to avoid errors in the performance evaluation process and deviations in performance evaluation, the results are further subjected to dimensionless processing of data to make performance evaluation more accurate [46]. The processing formula:

$$x_{ij}^{’}=\frac{x_{ij}-x_j^{\min }}{x_j^{\max }-x_j^{\min }}(1\le j\le m)$$

(3)

Among them, $x_{ij}^{’}$ is the value after data processing, $x_{ij}^{’}\in \left[0.1,1\right]$; $x_{ij}$ is the original data value; $x_j^{\min }$ is the minimum value in the original data; $x_j^{\max }$ is the minimum value in the original data, and the evaluation index data is classified into the [0, 1] dimensionless interval.

3.4. Evaluation Index System

The performance evaluation index of the agricultural product trade supply chain should be based on the perspective of input and output, combined with the characteristics of agricultural product trade supply chain. We then analyzed its input and output related elements, so as to select the performance evaluation index.

Research on the relationship between international trade, investment, and supply chain has spread all over the academic world. Scholars have carried out related research from the perspectives of micro-management, meso-industrial economics, and macro-national competition. The cross-border supply chain has become an important means for countries to develop internationally. Helpman [47] proposed that international direct investment and international trade are the two basic forms of the international division of labor and the two most important international economic activities, and there is a substitute relationship between trade and investment. Foreign direct investment (OFDI) is one of the important ways of international economic division of labor [33]. The purpose of China’s agricultural foreign direct investment is to improve the development of agricultural product trade, to improve its position and competitiveness in the world agricultural product market, and to expand trade income [34]. From the perspective of the supply chain, trade in goods is a kind of flow of goods, which is an international logistics completed under the provisions of a trade contract. Logistics plays a key role in trade supply chain cooperation. Today’s logistics infrastructure construction is indeed a complex network infrastructure, including information technology and logistics services, infrastructure (ports, railways, roads, airports), and other logistics infrastructure investment motivations that are key to attracting and expanding trade, and infrastructure improvements require a lot of investment, which is critical to the level of supply chain performance and is conducive to trade supply chain, thereby promoting the economic development [30,31,33,34]. Compared with developing countries in general, the bottleneck of development in Central Asian countries lies in the underdevelopment of related transportation and other infrastructure, which not only affects the development of their own foreign trade, but also restricts the flow of capital with other neighboring countries (

Table 2. Partnership between China and Central Asian countries.

Serial No	Country	Partnership Level	Year of Promotion
1	Kazakhstan	New stage of comprehensive strategic partnership	2015
2	Kyrgyzstan	Strategic partnership	2013
3	Tajikistan	Comprehensive strategic partnership	2017
4	Turkmanstein	Strategic partnership	2014
5	Uzbekistan	Comprehensive strategic partnership	2016

Source: According to the website of the Ministry of Foreign Affairs of China.

).

In addition, with the accelerating process of global economic integration and the implementation of China’s “Belt and Road” initiative, the economies of all countries in the world have opened up and integrated with each other, forming an interconnected and mutually integrated whole. The trade supply chain is a product of economic integration plays a pivotal role in the economic development of various countries [33]. Of course, the relevant decision-making of supply chain cooperation between the two parties should be based on the understanding of all stakeholders, as well as policy communication, unimpeded trade, infrastructure connectivity, financial integration, and people–to–people bonds between stakeholders. This will lead to common development, mutual benefit, and a win-win situation. “Connectivity” is the strategic point of convergence and the intersection, which is the link between China and Central Asia to improve the performance level of agricultural trade supply chains.

(1)

Policy communication. A good policy relationship can close the institutional distance between the two countries, reduce the risk of cooperation between the two sides, and promote bilateral cooperation in all aspects. Empirical evidence from various countries shows that policy communication plays a key role in enhancing mutual policy trust between the two sides. China and Central Asian countries have signed various cooperation agreements, including investment protection, transportation cooperation, and labor export and other aspects to establish cooperative relations, and have established various partnerships. The cooperative partnership between China and Central Asian countries has improved significantly. Among them, China and Kazakhstan have the largest number of high-level policy communication visits. China adheres to the principle of “mutual consultation, joint construction and sharing” and promotes the construction of the “Belt and Road” to achieve important progress and remarkable results. In terms of policy communication and signed partnership documents with China, and cooperated with China to develop third-party markets [39].

(2)

Unimpeded trade. The problem of unimpeded trade is to solve the problems of investment and trade facilitation, which are from the government level, such as customs, tariffs and non-institutional trade barriers. There are more important issues that need to be resolved for unimpeded trade, that is, the issue of business cooperation between China and countries along the route. The smooth flow of trade between the two sides is conducive to investment facilitation, thereby improving infrastructure construction, realizing standardized and coordinated development, reducing transaction costs, promoting bilateral trade volume, and promoting the development of cross-border trade.

(3)

Financing. Financing is mainly to solve the problem of financial support for cooperation between the two parties, and it also relieves the financing constraints of foreign-funded enterprises, reduces operational risks, and provides channels for capital operation. In order to deepen cooperation with neighboring countries, China advocated the establishment of the Asian Investment Bank, which fundamentally solved the problem of financial support. In addition, China has established Chinese-funded banks in Central Asian countries, accelerated the currency swap between RMB and Central Asian countries, and improved financial connectivity between China and Central Asian countries, thereby promoting bilateral trade cooperation. By the end of 2020, China’s agricultural investment stock in Kazakhstan is 123 million USD, involving 16 Chinese funded agricultural enterprises in Kazakhstan; China’s agricultural investment stock in Tajikistan is 245 million USD, involving four Chinese-funded agricultural enterprises in Tajikistan, of which the representative agricultural production capacity cooperation projects cover wheat flour and vegetable oil processing, cattle and sheep breeding and slaughter processing, cotton planting and textile processing, and other fields (https://www.fmprc.gov.cn/web/ziliao_674904/1179_674909/202206/t20220609_10700891.shtml, accessed on 31 October 2022).

(4)

Facility connectivity. Through the connection of relevant infrastructure, countries can realize cross-border exchanges and logistics and transportation networks. This facilitates bilateral economic and trade cooperation. The improvement of infrastructure is conducive to reducing transportation costs, and facility connectivity places more emphasis on the smoothness of the logistics channel network and improves the speed of information transmission. The logistics and transportation infrastructure connectivity are an effective part of the supply chain system. In the cross-border supply chain, the infrastructure connectivity plays a linking role, and a healthy density of facility connectivity plays a beneficial role in supporting the development of the cross-border supply chain. Facility connectivity is particularly important to the economic and trade cooperation between China and Central Asian countries. Ports are important nodes of transportation and logistics between the two countries. At present, China and Central Asian countries have 12 ports, including 10 land ports (Alashankou, Khorgos, Baktu, Jimunai, Ahertubek, Dulata, Muzart, Irkeshtan, Turgat, Bederi, and Karasu), and 2 airports (Urumqi Airport and Kashgar Airpoort). Relying on the advantages of a large number of ports and broad market space, China’s Xinjiang region has continued to build pilot industrial parks, comprehensive bonded zones and economic development zones for transnational e-commerce, so as to promote the growth of the transnational trade supply chain. More than 70% of China’s China Europe trains pass through the Alashankou Port in Xinjiang, China, and the Alashankou Comprehensive Bonded Zone runs through 20 special railway lines. China and Central Asian countries have natural geographical advantages, which will help strengthen infrastructure connectivity and promote bilateral economic and trade cooperation (https://www.fmprc.gov.cn/web/ziliao_674904/1179_674909/202209/t20220915_10766226.shtml; https://www.imsilkroad.com/news/p/48241.html; http://www.nea.gov.cn/2014-05/14/c_133333331.htm, accessed on 31 October 2022).

(5)

People–to–people bond. People–to–people bonds are more reflected in cultural exchanges and personnel exchanges between the two countries. The flow of people between the two countries is the basis for economic, trade, and cultural exchanges and cooperation. Therefore, strengthening cultural exchanges, reducing cultural distance, and promoting people–to–people bonds between the two countries can not only reduce the cost of cooperation in all aspects of the two parties, it can also help to solve the cultural diversity problems faced by overseas operations. Additionally, after many rounds of consultations with SCO members and close preparations by various departments, the SCO Agricultural Technology Exchange and Training Demonstration Base has been established, which mainly carries out agricultural technology exchanges, education and training, demonstration and promotion for Central Asian countries, and creates a scientific and technological highland, a talent highland, an industrial highland, and an economic and trade highland serving the development of SCO’s modern agriculture. The logical relationship between interconnection and trade supply chain is shown in Figure 3.

This paper selects the availability of indicator data when evaluating the performance of the relevant supply chain. The selected indicators need to be logically related to the development of the agricultural product trade supply chain, that is, these indicators can reflect the input and output of the agricultural product trade supply chain. The variables of the process and results, and the rationality of the entire selection index can truly reflect the objective facts of the performance of the trade supply chain. Combined with the relevant theoretical analysis and the actual situation to determine the final performance evaluation index system, the specific content is shown in

Table 3. Performance Evaluation Index System.

Target Layer	First-Level Indicators	Secondary Indicators	Unit	Data Sources
Performance evaluation of agricultural product trade supply chain between China and Central Asia	input indicator	Direct investment in agriculture	Ten thousand USD	China Outbound Investment Bulletin
		Direct investment in logistics, transportation, warehousing and postal industry	Ten thousand USD	China Outbound Investment Bulletin
		Information technology direct investment	Ten thousand USD	China Outbound Investment Bulletin
		Policy communication	/	Chinese Ministry of Foreign Affairs website
		People–to–people bond	/	“One Belt, One Road” Big Data Center
		Infrastructure connectivity	/	Ministry of Transport and Capital Airport website
		Financial intermediation	/	Ministry of Commerce of China and Asian Infrastructure Investment Bank
	output indicator	Agricultural export trade	Ten thousand USD	UN comtrade
		Import trade of agricultural products	Ten thousand USD	UN comtrade
		Contribution rate of agricultural products trade to agricultural economic growth	%	China Agricultural Statistical Yearbook/Calculation Acquisition
		The pulling rate of agricultural product trade to agricultural economic growth	%	China Agricultural Statistical Yearbook/Calculation Acquisition

.

3.5. Interconnection Indicators

In the “Vision and Actions to Promote the Joint Construction of the Silk Road Economic Belt” proposed by China, five major cooperation priorities are clearly put forward, namely policy communication, infrastructure connectivity, unimpeded trade, financial integration, and people–to–people bonds. Among the “five links”, unimpeded trade itself reflects the connotation of the trade supply chain development. Therefore, when selecting variables, we focus on other “four links” for relevant analysis. This paper draws on the variable selection methods of relevant scholars and adopts principal component analysis (the principal component analysis method is more commonly used, and the relevant models will not be repeated; see Appendix A for relevant results) to reduce the dimensionality of relevant indicators to obtain indicators such as policy communication, infrastructure connectivity, financial integration, and people–to–people bonds. The relevant indicators are shown in

Table 4. Variable Definition and Description.

Variable Name	Variable Meaning	Data Sources
Asian Investment Bank member countries	Is it a member of the Asian Investment Bank (Yes = 1, No = 0)	Asian Infrastructure Investment Bank website
Chinese bank	Whether the supply chain partner country has established a Chinese bank (Yes = 1, No = 0)	Ministry of Commerce website
Bilateral currency swap	Whether to sign a local currency swap agreement with China (Yes = 1, No = 0)	Ministry of Commerce website
RMB clearing	Whether to clear RMB (yes = 1, no = 0)	Ministry of Commerce website
Partnerships	Whether to establish a strategic partnership with China (yes = 1, no = 0)	Chinese Ministry of Foreign Affairs website
Confucius Institute (Cultural Exchange)	Whether to set up a Confucius Institute (Yes = 1, No = 0)	“One Belt, One Road” Big Data Center
Railway connectivity	Whether to open a freight train with China (Yes = 1, No = 0)	Ministry of Transport website
Road connectivity	Whether to open road cargo transportation with China (Yes = 1, No = 0)	Ministry of Transport website
Airline connectivity	Whether it has opened a flight with China (Yes = 1, No = 0)	Capital International Airport website

.

3.6. Indicators of Influencing Factors

By using the DEA-BCC model, the performance of the agricultural trade supply chain between China and Central Asia is evaluated and analyzed. The agricultural product trade supply chain is a complex system, and there are many factors that affect the performance of the agricultural product trade supply chain. What are the factors that lead to the decline of the overall agricultural product trade supply chain performance level, and what is the impact? In order to further study and analyze the main factors of China-Central Asia agricultural trade supply chain performance, relevant quantitative empirical analysis will be carried out. The existing literature has not yet formed the indicators of the influencing factors of the transnational agricultural supply chain performance. Therefore, the content of this section is based on the relevant literature and theoretical analysis stated above, combined with the performance evaluation subject to select the main influencing variable indicators. First, based on the key elements affecting the agricultural product trade supply chain, primary indicators are selected through the combination of relevant literature and factor analysis (see Appendix A for relevant results); then, indicators are screened according to the availability of indicator data. There are many influencing factors and indicators involved in the content to avoid the problem of collinearity between variables. For the convenience of subsequent analysis, the principal component analysis method is used to classify the indicators, and finally the relevant influencing variable indicators are determined.

(1)

Specific indicators

Based on the previous understanding, various related literatures and reports have been extensively integrated, based on the relevant materials of “E-commerce Research Report”, “Cross-border Logistics Research Report”, and “Indicator System of Agricultural Products Trade”. In this case, combined with the obtained data, an index system of influencing factors is established. The specific selection of relevant indicators is shown in

Table 5. Influencing factor indicators and measurement methods of selected performance.

Index	Specific Meaning	Unit	Indicator Properties	Data Sources
Quality of trade and transport related infrastructure	The composite score of the Logistics Performance Index reflects the efficiency of customs clearance procedures, the quality of infrastructure related to trade and transport quality, the ease of arranging competitively priced shipments, the quality of logistics services, the ability to track and trace shipments, and the availability of the perception of a country’s logistics based on the frequency of arrivals at the consignee within the time frame [48,49,50,51,52,53,54]	1–5	Positive indicator	WB
Convenience of international cargo transportation		1–5	Positive indicator	WB
Ability to track cargo		1–5	Positive indicator	WB
Timeliness of cargo transportation		1–5	Positive indicator	WB
Logistics service capability		1–5	Positive indicator	WB
Customs clearance efficiency	Cumbersome customs procedures [55,56,57,58]	1–5	Positive indicator	WB
Trust	The Credit Information Depth Index measures rules that can affect the scope, accessibility and quality of credit information obtained from public or private credit bureaus [59,60,61,62,63]	1–8	Positive indicator	WB
Information sharing	National Statistical Capability Index (capacity to provide various transaction information) [64,65,66]	0–100	Positive indicator	WB
Information security	The Disclosure Index measures the extent to which investors are protected through disclosure of ownership status and financial information [67]	0–10	Positive indicator	WB
Market environment	The better the market environment is, the more conducive it is to achieve coordinated development, promote supply chain development, increase demand for agricultural products, and increase trade volume [68,69]	1–7	Positive indicator	WEF
Availability of financial services	Ease of access to financial services [70,71]	1–7	Positive indicator	WEF
Affordability of financial services	The convenience of settlement and payment in trade activities [71]	1–7	Positive indicator	WEF
Availability of the latest technology	Ease of access to the latest technology [72,73]	1–7	Positive indicator	WEF
Adoption of new technologies by enterprises	Represents the degree of relevant trade, commercial technology utilization [74,75]	1–7	Positive indicator	WEF
Judicial independence	Does the judiciary deal with conflicts between trade supply chains independently [71,74,76]	1–7	Positive indicator	WEF
Agricultural policy costs	The extent of the impact of agricultural policies on agricultural trade [71]	1–7	Positive indicator	WEF
Prevalence of trade barriers	Are tariff barriers prevalent [71,73,77]	1–7	Positive indicator	WEF
Unconventional payment	Commodity inspection efficiency and customs clearance license for cross-border trade [78]	1–7	Positive indicator	WEF
Internet development	Represents the level of Internet technology and educational ability [72,73]	0–100	Positive indicator	WEF
Policy transparency	Whether the formulation of relevant trade policies is transparent [71,73,74]	1–7	Positive indicator	WEF
Safety management capabilities	Ethical behavior of the company, relevant funds and insurance security, and investor protection [79]	1–7	Positive indicator	WEF
Quality of information	Provide timely and accurate information [80,81]	1–7	Positive indicator	WEF

Note: WB—World Bank; WEF—World Economic Forum.

.

Combined with model construction, multi-dimensional empirical research is conducted to examine the logistics development and market environment of Central Asian countries, capital and e-commerce in Central Asian countries, business services and customs environment in Central Asian countries, Central Asian countries’ security management and related systems, resource sharing, etc. By adopting the DEA-BCC model, relevant indicators are selected to evaluate the performance, and the technical benefits, scale benefits and comprehensive benefits are analyzed. The comprehensive benefit index of China-Central Asia agricultural trade supply chain is used as the explained variable, and the regression analysis is carried out. Due to the study of the agricultural product trade supply chain, China is not included in the sample of influencing factors. The specific contents are shown in

Table 6. Regression variable design.

Variable Indicator	Specific Meaning	Variable Symbol	Variable Category
Agricultural trade supply chain performance	Performance Evaluation Comprehensive Benefit Index	SCP	Explained variable
Customs environment	obtained by principal component analysis	CEFAC1	Explanatory variables
Funding and e-Commerce	obtained by principal component analysis	FECFAC2	Explanatory variables
Safety management and trust and system	obtained by principal component analysis	SSFAC3	Explanatory variables
Logistics development and market	obtained by principal component analysis	LMFAC4	Explanatory variables
Sharing resources	obtained by principal component analysis	RSFAC5	Explanatory variables

.

4. Empirical Test and Analysis

4.1. DEA-BCC Comprehensive Evaluation Results

In order to make the evaluation results more complete, according to the above evaluation results, the overall performance evaluation analysis of the evaluation object is carried out. The specific content is shown in Table 5 and Table 6.

Judging from the overall performance evaluation data of DEA-BCC, the average performance level of China and Central Asia agricultural product trade supply chain is 0.621, and the performance status is in the middle range. There is an obvious downward trend, which indicates that there are some key problems. The overall technical benefit is at a relatively high level, and the comprehensive benefit is mainly affected by the scale benefit. The change trend of the scale benefit is similar to the comprehensive benefit. It shows that China and Central Asian countries can further develop their development potential by adjusting and optimizing resources. It is necessary to adjust the direction of resource input and improve the resource utilization rate of both sides. According to the actual situation of both sides and supply chain related investment, policy communication, logistics and transportation foundation Facility connectivity, financial connectivity and other aspects are effectively adjusted to achieve the optimal allocation of resources, thereby achieving close cooperation. The specific results are shown

Table 7. Performance Evaluation Results.

	Decision Unit	Technical Benefits TE	Economies of Scale SE(k)	Overall Benefit OE(θ)	DEA Validity
Performance evaluation	2010	1.000	1.000	1.000	DEA valid
	2011	1.000	0.907	0.907	Not DEA valid
	2012	1.000	0.615	0.615	Not DEA valid
	2013	0.946	0.643	0.621	Not DEA valid
	2014	0.969	0.717	0.712	Not DEA valid
	2015	0.858	0.490	0.436	Not DEA valid
	2016	0.792	0.499	0.438	Not DEA valid
	2017	0.815	0.430	0.364	Not DEA valid
	2018	0.816	0.573	0.502	Not DEA valid
	2019	0.858	0.620	0.552	Not DEA valid

and

Table 8. Overall Evaluation Results.

Decision Unit	Technical Benefits TE	Economies of Scale SE(k)	Overall Benefit OE(θ)	Overall Average Performance	Performance Status
	Returns to Scale	Returns to Scale	Returns to Scale
2010	-	-	-	0.621	medium
2011	-	irs	irs
2012	-	irs	irs
2013	irs	irs	irs
2014	irs	irs	irs
2015	irs	irs	irs
2016	irs	irs	irs
2017	irs	irs	irs
2018	irs	irs	irs
2019	irs	irs	irs

Note: In the table, the drs is decreasing return to scale, the irs is increasing return to scale, - is fixed return to scale.

and Figure 4.

From the perspective of the overall return to scale, except for 2010, the other years were in a state of increasing returns to scale, and the overall performance was low, which means that if the scale is too small, the scale can be expanded to increase efficiency. To further improve cooperation in relevant policy communication, infrastructure and other aspects, to increase resource input in all aspects, form economies of scale, and improve resource management capabilities, thereby improving the performance level of China and Central Asia’s agricultural trade supply chain.

In the process of cooperation, the main reason for the low performance is that the cooperation value of the agricultural product trade supply chain, their respective resource input, technology, management and other capabilities are different. Therefore, we should consider the advantages of their agricultural resources to further develop greater development potential by adjusting and optimizing resources. In the process of agricultural product trade supply chain cooperation, we should combine the resource value of partners.

4.2. The Relationship between Technical Benefit, Scale Benefit and Comprehensive Benefit

Comprehensive benefit is the product of technical benefit and scale benefit, so comprehensive benefit, technical benefit and scale benefit interact and restrict each other. Technical benefits refer to the benefits generated by the decision-making unit through the improvement of the relevant management level and technical level. Scale benefit is the standard to measure whether an organization’s production scale is in the most appropriate scale. The value of scale benefit is equal to the comprehensive benefit divided by the technical benefit. In order to correctly judge the impact and restriction degree of the technical benefits and scale benefits on the comprehensive benefits of the agricultural product trade supply chain, in this section, the comprehensive benefit, technical benefit, comprehensive benefit and scale benefit of the scatter chart are used to analyze their impacts and constraints. The closer the points in the scatterplot are to the diagonal line, the stronger the impact and restriction of technical benefits and scale benefits on comprehensive benefits, and vice versa.

As can be seen from Figure 5, from the scatter plot of comprehensive benefit and technical benefit, most of the scatter points deviate from the diagonal line, indicating that the impact of technical benefit on comprehensive benefit is relatively small. From the scatter plot of comprehensive benefits and scale benefits, scatter points are on the diagonal or closer to the diagonal, which indicates that scale benefits have a greater impact on comprehensive benefits and have a closer relationship. In a word, the scale benefit of the agricultural trade supply chain affects and restricts the overall benefit more.

4.3. Panel Tobit Regression Test

Referring to the existing research, this section will use the Tobit regression model for parameter estimation [47]. The basic model settings are as follows:

$$SC{P}_{it}=\alpha C{E_{it}}^{FAC1}+\gamma FE{C_{it}}^{FAC2}+\varphi S{S_{it}}^{FAC3}+\phi L{M_{it}}^{FAC4}+\zeta R{S_{it}}^{FAC5}+u_i+u_t+{\epsilon }_{it}$$

(4)

where i is the ith country and t represents the tth period. Among them, SCP represents the performance of the agricultural product trade supply chain, LM represents the logistics development and market environment of the Central Asian countries, FEC represents the capital and e-commerce of the Central Asian countries, CE represents the customs environment of the Central Asian countries, and SS represents the relevant security management and trust of the Central Asian countries. RS represents resource sharing among Central Asian countries, u_i represents the individual random error term, u_t represents the time random error term, and ε_it represents the disturbance term.

It draws a scatter plot between China and Central Asian countries’ cross-border agricultural product supply chain performance and various influencing factors (Figure 6).

According to the scatter plot shown above, there is a relatively obvious positive relationship between the influencing factor variables of each dimension and the cross-border agricultural product supply chain. A sound environment is conducive to improving the efficiency of the trade supply chain and promoting the cooperation. In addition, the dimensional variables have different effects on the performance of the agricultural product trade supply chain. The slope of the regression line is fitted, and this correlation does not explain the problem. As for the relationship between the specific variables of each dimension and the performance of the agricultural product trade supply chain, the relationship between the two needs to be established on the basis of detailed quantitative analysis, and the specific empirical analysis results will be further given in

Table 9. Model (4) Regression Estimation.

Variable	Explained Variable SCP
	OLS Model		Panel Tobit Random Effects Model		Random Effects Model
	Coef	p Value	Coef	p Value	Coef	p Value
CEFAC1	−0.1612 *** (−7.66)	0.000	−0.4922 *** (−3.08)	0.002	−0.1612 *** (−5.66)	0.000
FECFAC2	0.0203 (0.56)	0.582	0.2150 *** (2.93)	0.003	0.0203 (0.71)	0.475
SSFAC3	0.1342 *** (3.17)	0.004	0.3655 *** (10.90)	0.000	0.1342 *** (4.71)	0.000
LMFAC4	0.0471 * (1.82)	0.082	0.2590 ** (1.97)	0.049	0.0471 * (1.66)	0.098
RSFAC5	−0.0194 (−0.72)	0.479	0.0453 (0.79)	0.427	−0.0194 (−0.68)	0.496
—Cons	0.7922 *** (25.29)	0.000	0.6018 *** (12.77)	0.000	0.7922 *** (28.28)	0.000
Wald chi2			36.22		57.93
F	19.24
p	0.0000		0.0000		0.0000
Individual RE			Yes
Time RE			Yes
R2	0.6588		0.6015
n	30

Note: ***, **, and * represent significant at the 1%, 5%, and 10% levels, respectively, and the t and z statistics are in brackets.

.

Formula (4) shows the Central Asian countries customs environment (CE), funds and e-commerce (FEC), security management and trust and system (SS), logistics development and market environment (LM), information resource sharing (RS), and cross-border agricultural supply chain performance levels (SCP^θ). The model estimation results are shown in Table 9. It can be seen from the model estimation results that the regression results of the influence of Central Asian countries’ trust and customs environment on the performance of China-Central Asian cross-border agricultural product supply chain show that the standardization coefficient is −0.4922 (p < 0.002), which is significant at the 1% level. The negative impact indicates that the existing relevant customs environment has certain obstacles to the performance of the cross-border agricultural supply chain. The regression results of the influence of capital and e-commerce factors (FEC) show that the standardization coefficient is 0.2150 (p < 0.003), which is significant at the 1% level, indicating that capital and e-commerce factors in Central Asian countries have a significant impact on the performance of the supply chain. The supply chain performance has a positive impact. The regression results of the impact of safety management and related systems (SS) on the performance of the supply chain show that the standardization coefficient is 0.3655 (p < 0.000), which is significant at the 1% level, indicating that the Central Asian countries safety management and related systems have a strong positive impact on the performance. The more transparent the relevant safety management capabilities of Central Asian countries and related agricultural product trade systems, the more conducive to the performance of cross-border agricultural product supply chains, which is conducive to the mutual understanding of each other. The regression results of the impact of logistics development and market environment factors (LM) on the performance show that the standardization coefficient is 0.2590 (p < 0.049), which is significant at the 5% level, indicating that the logistics of Central Asian countries development and market environment have a positive impact on the supply chain performance. The more complete the relevant logistics and transportation infrastructure, the higher the logistics capacity, which is conducive to the efficiency of logistics and transportation and improves the level of supply chain performance; the better the market environment, the more conducive to supply the coordination of each link in the chain will help the smooth operation of the supply chain, thereby promoting the overall performance level of the supply chain and achieving mutual benefits. The regression results of the information resource sharing factor (RS) on the performance show that the standardization coefficient is 0.0453 (p < 0.427), indicating that the information resource sharing of Central Asian countries has a certain effect on the performance of the supply chain. There was a positive effect, but since it did not pass the significance test, the effect is not strong.

5. Discussion and Conclusions

According to the DEA-BCC calculation results, the overall performance evaluation index of the performance evaluation of the agricultural product trade supply chain is 0.615. It is consistent with the basic logic of an agricultural trade supply chain. The overall performance evaluation results show an obvious downward trend, which shows that there are some key problems. The technical benefits are generally at a relatively high level, and the comprehensive benefits are mainly affected by scale benefits. Technical benefits refer to the benefits generated by the decision-making unit through the improvement of the relevant management level and technical level. The technical benefits of the trade supply chain reflect the influence of the technical level and relevant management level of the agricultural product trade supply chain after excluding the influence of the scale factor. The scale remained unchanged from 2010 to 2012, but from 2013 to 2019 it has a downward trend, and it is now returning to an upward trend. On the whole, the performance shows that the existing technology utilization ability and management ability still have more room for improvement and development, and the technology needs to be improved and the supply chain management needs to be strengthened to achieve the highest performance level. From the perspective of scale benefits, the return to scale in 2010 remains unchanged. In terms of overall performance, it indicates a downward trend, in the state of increasing returns to scale, and the performance level is in the lower middle range.

According to the Central Asian countries’ customs environment, funds and e-commerce, security management, trust, systems, logistics development and market environment, information, resource sharing, and other factors, the performance level of the agricultural product trade supply chain carry out relevant empirical analysis. From the results of influencing factors, the customs environment of Central Asian countries has a negative and significant inhibitory effect on the performance of the agricultural trade supply chain; this shows that the existing customs environment has certain obstacles to the performance of the agricultural trade supply chain. Funds and e-commerce in Central Asian countries, security management and trust and systems in Central Asian countries, logistics development and market environment have a significant positive role in promoting agricultural product trade supply chain performance to varying degrees, which is consistent with the basic situation of reality.

China and Central Asian countries should proceed from their respective advantages in agricultural resources, more fully reflect the value of cooperation in the supply chain of agricultural products trade between China and Central Asia, and reflect their respective capabilities in resources, technology, management, etc., and further develop them by adjusting and optimizing resources. Greater development potential, in the process of agricultural product trade supply chain cooperation, the resource value of partners should be combined, efforts should be made to reduce the production and trade costs of each link of the agricultural product trade supply chain, and efforts should be made to improve the interests of the cooperative members of the agricultural product trade supply chain. The connection mechanism and interest connection are the core link of the agricultural product trade supply chain cooperation and supply chain formation, which realizes the seamless connection of information, transactions and settlements between cooperative members of the agricultural product trade supply chain. Efforts should be made to implement measures according to local conditions, pay attention to scientific thought and rationality, and make effective adjustments according to the actual situation of both parties and supply chain-related aspects such as investment, policy communication, logistics and transportation infrastructure connectivity, and financial integration, so as to achieve the optimal allocation of resources. The cooperation level of the agricultural product trade supply chain will strengthen the overall benefits brought by the agricultural product trade supply chain cooperation and improve the overall performance of the agricultural product trade supply chain.

The better development of e-commerce, the more conducive to changing the inefficiency of previous economic and trade cooperation, improving the information processing efficiency of both parties, and shortening the relevant payment and related trade links; the logistics and transportation efficiency of the Central Asian countries and the forecast market demand are relatively underdeveloped. The logistics and transportation infrastructure of China’s aid to the Central Asian countries can effectively strengthen the interconnection between China and the Central Asian countries. National security management and related systems have a significant positive impact on cross-border agricultural product supply chain performance. In the process of cross-border trade, the related security management of partner countries and the improvement of the transparency of related trade policies can effectively reduce trade conflicts between countries and transaction costs, which is conducive to optimizing the impact environment, helping China and Central Asian countries to cooperate in the agricultural product trade supply chain, and promote the growth of agricultural trade flow. The information resource sharing of Central Asian countries has a positive impact on the performance of agricultural product trade supply chain, but it has not passed the significance test, and the impact is not large. Therefore, work should be undertaken to improve the ability to integrate agricultural resources, make use of the Shanghai Cooperation Organization, and strengthen multilateral transport infrastructure cooperation. Work should also be done to improve the supporting environment for the coordination of cross-border e-commerce and cross-border logistics of agricultural product, and to strengthen policy communication according to local conditions, and strengthen support for Chinese enterprises in the overall layout of the supply chain of agricultural products trade.

This paper also has certain study limitations. The existing research on agricultural product trade supply chain is less, the relevant theoretical research is not deep enough, and the complete system has not been formed, which brings certain difficulties to this article. As the performance evaluation of the agricultural trade supply chain is relatively complex and extensive, the performance evaluation of the trade supply chain not only involves the main body of the whole supply chain system, but also involves many aspects such as the process and technical support in the operation process. In the future, I hope that the selection of evaluation indicators in this paper, based on previous studies, will improve the performance evaluation of agricultural trade supply chain.