Resource Trade Research Articles

Real-World Geopolitical Influences on In-Game Financial Behaviour

This paper explores how real-world geopolitics can influence financial decision-making in virtual environments. The study primarily focuses on trading dynamics in a pandemic simulation game. The players manage resources and trade with each other to save their population. We compared two groups: one playing with made-up country names (control) and another with real country names (test). The players were not permitted to communicate outside of the resources the game provides and were finally ranked based on the number of months survived and trade volume. Our findings reveal two distinct player archetypes, one focusing on maximising trade volume and a second focusing on resource conservation. Real country names compared to color-coded labels seem to delay the perception of competition and reduce overall trade volume, suggesting increased immersion and a more conservative approach towards resource management. Observations from gameplay footage reveal instances of potential bias, with players forming diplomatic ties based on national identities. The data collected suggests that real-world geopolitics can influence financial behaviour in virtual environments as hypothesised. It also explores virtual environments to study how political narratives and dynamics affect human decision-making. The findings offer practical insights for game developers regarding fostering player engagement, mitigating bias, and creating fair economies. While parallels with real-world resource trading and allocation during pandemics were noted, further analysis would be required to explore these connections.

Trading in Turbulent Times: Unravelling the Interplay between Trade Policy Uncertainty and Geopolitics in Russian Mineral Resource Supply

Trade policy plays a pivotal role in shaping import and export volumes within the global economy. However, the escalation of geopolitical tensions has posed significant challenges to the smooth flow of mineral resource trade. This study aims to analyse the consequences of global trade policy uncertainty (TPU) and various measures of geopolitical risk (GPR), including terror threats, war threats and nuclear threats (NCT), on Russian mineral exports (MEX). The analysis covers the period from January 2013 to December 2021. By employing sophisticated quantile regression methodologies, such as the cross-quantilogram (CQ) and cross-spectral quantile coherency (CQC) techniques, this study uncovers a compelling interaction between TPU and Russian MEX across different market conditions. Interestingly, TPU exerts a significantly positive impact on the export volumes of Russian mineral resources. In contrast, the presence of GPRs, particularly warfare and terrorism, proves to be detrimental to MEX during bullish market phases across various memory horizons. Surprisingly, NCT stimulates mineral trade during bearish market conditions, both in monthly and annual timeframes. These findings remain robust and consistent even when the CQC technique is employed. In light of these pressing geopolitical challenges, this study underscores the importance of developing sustainable mineral trade policies that foster enhanced global cohesion. It is crucial to address these challenges effectively to ensure the smooth and efficient flow of mineral resources in the international trade landscape. JEL Codes: C22, F13, F14, P28, Q21, Q27

Digitalization of the economy and sustainability of metallic mineral production

Due to the adverse impacts of climate change on the environment and biodiversity, sustainability has become a critical issue. This paper investigates the impact of digitalization on the sustainability of metallic mineral production, particularly CO2 emissions, within the Regional Comprehensive Economic Partnership (RCEP). Using data from 1998 to 2020 and the cross-sectional FMOLS technique, the study finds that a 1% increase in ICT investment reduces CO2 emissions by 0.32%, and a 1% rise in Internet access decreases emissions by 0.28%. However, electrification increases emissions due to higher energy demand and fossil fuel reliance. Economic growth and metallic resource trade volume also elevate emissions. Policy recommendations include smart urban development, sustainable rural electrification, fostering internet access, and implementing green logistics in metallic production trade to enhance sustainability in RCEP countries.

Cost-effectiveness analysis of first-line sintilimab plus chemotherapy vs. chemotherapy alone for unresectable advanced or metastatic gastric or gastroesophageal junction cancer in China.

The Chinese Society of Clinical Oncology (CSCO) has recommended sintilimab plus chemotherapy (SINT + Chemo) as a standard first-line therapy for advanced gastric cancer or gastroesophageal junction cancer (GC/GEJC), based on the proven effectiveness and safety in the ORINT-16 trail. Its cost-effectiveness, however, remains to be evaluated. We established a partitioned survival approach (PartSA) model with a 10-year time horizon to determine whether SINT + Chemo (vs. chemotherapy) was more cost-effective as a first-line treatment for unresectable advanced or metastatic GC/GEJC. Survival data was generated from the ORIENT-16 trail. Cost calculation was limited to direct medical costs. Database of Hunan Public Resources Trading Service Platform was used as the source for obtaining drug prices. Other cost and utility values were gathered from established literature. Incremental cost-effectiveness ratio (ICER) was the primary output. Additionally, we conducted sensitivity analysis, subgroup analysis, and scenario analysis. In the base-case analysis, group SINT + Chemo showed an increase in utility value by 0.32 quality-adjusted life-years (QALYs) at an extra cost of $7988.43, resulting in an ICER of $25239.29/QALY, below the Chinese cost-effective willingness-to-pay (WTP) threshold of $38223.34. Upon further subgroup analysis according to patients' programmed death 1 ligand (PD-L1) combined positive score (CPS), the ICERs were $26341.01/QALY for patients highly expressing PD-L1 (CPS ≥5) and $17658.26/QALY for patients lowly expressing PD-L1 (CPS <5). Based on the sensitivity analysis, we found the PFS utility was the parameter that had the most significant impact on the model's outcomes. Moreover, in scenario analysis, the results remained consistent despite variations in the model's time frame. In China, SINT + Chemo is a more cost-effective option (vs. chemotherapy) as a first-line therapy for unresectable advanced or metastatic GC/GEJC, irrespective of PD-L1 expression levels.

Matching with contract-based resource trading in UAV-assisted MEC system

Matching with contract-based resource trading in UAV-assisted MEC system

The employment impacts of fossil fuel trade across cities in China: A telecoupling perspective

The trade of resources geographically bridges production and consumption, driving telecoupling between resource extraction and distant consumption. However, the telecoupling between employment and fossil fuels has not been quantitatively analyzed yet, presenting a barrier to employment management under the energy transition away from fossil fuels. Here we investigate the telecoupled employment driven by intercity fossil fuel trade in China. A spatially explicit inventory of 989 coal mines, 642 oil fields, and 461 gas fields has been compiled for analysis. The results show that 1560 k of workers extract fossil fuels to satisfy external energy demands (referred to as telecoupled employment), accounting for 70 % of total employment for fossil fuel extraction in China. The coal trade drives 58 % of the total telecoupled employment while oil and gas drive 42 %. 26 % of intercity telecoupled employment is transferred intra-provincially whereas 74 % is transferred interprovincially. 222 cities drive more employment from the consumption-based perspective than from the production-based perspective, while 91 cities see the reverse. It is of significance for fossil fuel exporters to incorporate this telecoupling (e.g. the direction and scale of telecoupled employment) into city policies to assess the transboundary employment impacts of the changes in energy demands of importers.

Dynamic optimisation of carbon allowance considering inter-provincial energy resources trade for emissions reduction: Case of China southern power grid

As the main carrier of natural resources into energy, the power industry is the world's largest carbon emitter, and its sustainable development will have far-reaching impacts on the utilization of natural resources and economic growth. Carbon trading market is a widely used tool to promote proactive emissions reductions in the electricity industry in different regions. On this basis, inter-provincial trading in the power industry creates a hidden carbon transfer between producers and consumers of energy resources. Therefore, it is necessary to construct systematic multi-period emission reduction measures to deal with the conflict and coordination of the operation of the two systems. In this study, to promote orderly emission reductions in the power industry in areas with different natural resource endowments, a two-tier decision-making model for carbon allowances allocation based on interactive model predictive control technique is constructed. The model readjustss the overall allowances by tracking the implied carbon transfer flows between regions and implementing a production-oriented allowance compensation mechanism, forming an optimisation strategy for carbon compliance cost and emission intensity in the power sector. The experimental results show that adjusting the regional allowance distribution in inter-provincial transmission can alleviate the impact of high emission reduction pressure on the overall carbon compliance cost, while the rolling horizon optimisation of the carbon baseline value can approach the expected emission reduction target in stages. Taking the Southern Power Grid as an example, this study ultimately provides policy recommendations for sustainable emission reductions under multi-period inter-provincial trade in energy resources.

Uncovering the structure and evolution of global virtual water and agricultural land network

The effective management and allocation of water and land resources is pivotal for ensuring global food security and facilitating the transition towards sustainable development. Combining multi-regional input-output analysis and complex network modelling, this study examining the spatial-temporal evolution and topological structures of multi-layer virtual water and agricultural land networks, analyzed the network characteristics of different countries/regions, and tested the network vulnerability between virtual water trade network and virtual agricultural land network. From the results, it is revealed that 30.9 %—34.14 % of global water resources and 32.9 %—40 % of global agricultural land are associated with international trade. Meanwhile, the geographical distribution of this trade has shifted from low-income countries to middle and high-income countries, showing three distinct fluctuations in their instability levels. Additionally, quantitative network analysis indicates that resource trade networks exhibit small-world characteristics with increasing trends in network density, clustering coefficient, and average path length values over time. Among the two disturbance scenarios, both virtual water and virtual agricultural land networks were more vulnerable under deliberate assault than under random failure, however, the agricultural land network demonstrates greater toughness compared to the virtual water network. These findings highlight the importance of sustainably managing global water and land resources within a framework for sustainable development which aims at promoting both worldwide food security and environmental protection simultaneously.

Upgrading the industrial structure for optimizing water-energy-carbon nexus in regional trade network

To take actions for the SDGs (Goals 6, 7, 9, 12, and 13), the world is undergoing intense industrial transformation and upgrading. However, there has been limited analysis of water-energy-carbon (WEC) nexus within regional trade network to uncover the effects of industrial restructuring. Here, this study explores the trade-related WEC flows in the Yangtze River Delta area (YRD) from 2012 to 2017 by four aspects (spatiotemporal status, sectors, WEC flowing synergies, and environmental-economic trade-off) based on an environmentally extended input-output analysis. The main results show that the resource supply network in the YRD has been optimized, with enhanced synergies of WEC flows. Resource trade in the YRD has shifted from traditional heavy industry (HV Ⅰ) to high-tech manufacturing industry (HV Ⅱ). The share of trade-related WEC in demand of HV Ⅱ among all sectors increased by 10, 5, and 15 percentages, while the share in demand of HV Ⅰ decreased by 15, 10, and 10 percentages during this transition period. This study also discloses an environmental-economic contradiction arising in regional trade: low-carbon and high-value-added economic development in some regions may be premised on relocating environmental resource pressures. Hence, this study could assist policymakers in analyzing sustainable industrial transition models for regional integration clusters and in formulating targeted interregional resource trade policies to alleviate development gaps.

Research on Energy Trading Mechanism Based on Individual Level Carbon Quota

High economic growth is accompanied by substantial consumption of fossil energy and significant negative externalities on the ecological environment. The global warming effect resulting from environmental pollution caused by energy has brought energy carbon emissions into the forefront of social attention. Establishing a carbon trading market is an essential measure to achieve the “double carbon” goal, with individual and household carbon emissions accounting for 70% of China’s total emissions. Constructing an individual-level carbon trading market will facilitate the efficient realization of this goal. However, addressing the challenge of handling vast amounts of data and network congestion in relation to frequent but small-scale individual carbon trading has become an urgent issue that needs to be resolved. In light of this, the present study designs a digital technology-based framework for the carbon market trading system and proposes an individual carbon asset price-based model for carbon market trading, aiming to establish a research framework for the carbon quota market. Furthermore, blockchain technology is employed as the underlying technology in the proposed carbon trading market model to cater to individual-level carbon trading services and achieve optimal matching between carbon quota suppliers, thereby enhancing profitability of the carbon trading platform. The numerical results obtained from the model demonstrate that in absence of government subsidy mechanisms, individual-level carbon trading can effectively reduce total consumer emissions. The present study successfully overcomes the carbon lock-in effect of consumer groups and achieves the generation and trading of individual carbon assets despite capital constraints. This study facilitates accumulation and trade of individual carbon resources, reduces overall consumer emissions, enhances environmental benefits at societal level, and provides a foundation for governmental decision-making.

The impact of Chinese investment on access to clean and sustainable energy in Africa

The objective of this study is to examine the relationship between Chinese investment and access to clean and sustainable energy in African countries. We are motivated by the increasing engagement between China and Africa and the priority of sustainable energy for both partners. We employ robust econometric modelling, including fixed effects and the two-step Generalized Method of Moments, on a panel sample of 43 African countries over 19 years. The results show that Chinese energy investment in Africa is significantly associated with increased access to sustainable electricity. This effect is more pronounced in resource-rich countries, suggesting that China is more attracted to these countries due to the opportunities for resource trade in the form of partnerships. The policy implication of this finding is that it highlights the importance of African governments developing favourable strategies and policies to attract more Chinese investments in the energy sector.

Türkiye in International Energy Trade: Implementation of Social Network Analysis

Energy resources are fundamental inputs in almost every sector and play a crucial role in development and economic stability. This situation has increased the importance of keeping energy costs low, becoming a significant factor in attaining global superiority. In the contemporary era, where states represent the highest level of the organization, the strategic importance of these resources has been further exposed. The strategic value of energy resources, predominantly encompassing fossil fuels such as oil, natural gas, and coal, has precipitated intense global competition. The dynamics of energy resource trade have transcended mere profit-driven motives, transforming into a tool wielded by governments for various political objectives. This paradigm shifts underscores the vitality of energy supply security, prompting the formulation of energy trade networks guided by policies and national strategies. Within these networks, participating actors exhibit diverse traits shaped by distinct circumstances, assuming varied roles through pre-existing relationships. The purpose of the research is to examine the energy trade network of Türkiye, implementing the social network analysis method that integrates empirical data and mathematical approaches. The study aims to unveil pivotal aspects of the network, including its size within the global energy trade landscape, density, relational ties among actors, centrality, and brokerage degrees. The research aims to contribute valuable insights to understanding Türkiye's positioning in the global energy trade through these analyses. The results indicate that the volume of Türkiye's energy trade network accounts for around 1/3 of the global energy trade. While no single dominant actor exists in the network, specific entities demonstrate significant brokerage power. The analysis highlights the impact of global energy players, including Russia, the United States, and some European countries. Finally, the study involves recommendations for future research, anticipating a continued exploration of the complicated dynamics shaping energy trade networks on a global scale.

Feed balances for ruminant livestock: gridded estimates for data−constrained regions

Demand for animal−source foods and livestock feed are forecast to increase across sub-Saharan Africa. In this context, there is a need to estimate the availability of livestock feed to support decision−making at local, sub-national and national levels. In this study, we assess feed balances for ruminant livestock in Ethiopia and Burkina Faso. Feed availability was estimated using remotely sensed products and detailed feed composition data. Feed requirements were estimated for maintenance, growth, lactation, gestation and locomotion using a data−intensive model. Biomass available as animal feed was estimated to be 8.6 tonnes of DM per hectare in the Ethiopian highlands and midlands, 3.2 tonnes DM per hectare in the Ethiopian lowlands, 2.9 tonnes DM per hectare in Burkina Faso’s Sudanian agro-ecological zone and 1.0 tonne DM per hectare in the Sahel. The energy requirements of lactating cows were estimated to be 62.1 Megajoules (MJs) per animal per day in the Ethiopian highlands and midlands, 62.7 MJ in the Ethiopian lowlands, 88.5 MJ in Burkina Faso’s Sudanian agro-ecological zone and 53.1 MJ per animal per day in the Sahel. Feed scarcity hotspots are most prominently located in the Ethiopian highlands and the Sahelian agro-ecological zone of Burkina Faso. Demand−side policy and investment initiatives can address hotspots by influencing herd sizes, nutritional requirements and herd mobility. Supply−side policy and investment initiatives can secure existing feed resources, develop new sources of feed and incentivise trade in feed resources. Improving feed balances will be of value to decision−makers with the aims of optimising livestock productivity, minimising exposure to climatic shocks and minimising greenhouse gas emission intensity.

A new era for African health systems: Market shaping and the African Continental Free Trade Area (AfCFTA)

AbstractThe COVID‐19 pandemic has forced a reflection on the origins of supplies in African healthcare market and underscored the need for an increase in local manufacturing of medical supplies. Several African countries’ health markets have been heavily reliant on imports. First, this article demonstrates how the African healthcare market has had a high import dependency and the role that the African Continental Free Trade Area (AfCFTA) could play to reverse this. It is estimated that African countries import between 80% and 94% of medical supplies, 75% of testing kits, between 70% and 95% of pharmaceuticals, and 99% of vaccines. Second, during the COVID‐19 pandemic, countries imposed export restrictions which impacted the flow of medical supplies to African countries. This finding highlighted the limited production capabilities on the African continent and reiterated the need to strengthen continental value chains and local manufacturing capacity to establish the continent's New Public Health Order. Third, there was the emergence of local innovations seeking to minimize the impact of these supply chain disruptions. Using case studies on the local production of COVID‐19 testing kits and personal protective equipment, the article highlights progress made toward health market reform. It calls attention to the implementation of the AfCFTA to strengthen the supply, manufacturing, and trade of medical resources. Fourth, this article highlights countries that have African‐made pharmaceuticals and vaccinations and the importance of regional hubs to expand these products in African healthcare markets. It concludes by discussing investments made to expand local manufacturing of health products.

Competitive Pricing for Resource Trading in Sliced Mobile Networks: A Multi-Agent Reinforcement Learning Approach

The emergence of network slicing as a flagship technology in 5G networks has not only enhanced network expansion and flexibility in resource management for service continuity, but also provided an avenue for establishing a viable market for resource sharing. To optimize the network's resource usage, stakeholders are encouraged to take pragmatic steps toward dynamic resource sharing. This paper designs a techno-economic model for the strategic interactions among multiple competing mobile virtual network operators (MVNOs) and their users in a trading marketplace. We formulate the dynamic pricing problem as a two-stage Stackelberg game, where the MVNOs are leaders, and the users are followers. In the first stage, the MVNOs compete to set their differentiated unit prices using a negotiation mechanism while considering system-level network load. Then, the users decide their purchasing volumes to match the prices of the MVNOs. We transform the game-based optimization problem into a stochastic Markov decision process (MDP) problem and propose a multi-agent deep Q-network (MADQN) method that obtains an optimal solution for the formulated game. Simulation results and analysis reveal that the proposed algorithm achieves convergence under the competitive pricing scheme (CPS) and independent pricing scheme (IPS) while enhancing MVNOs and users' utilities at acceptable levels.

A Multi-Scale Convolutional Neural Network Combined with a Portable Near-Infrared Spectrometer for the Rapid, Non-Destructive Identification of Wood Species

The swift and non-destructive classification of wood species holds crucial significance for the utilization and trade of wood resources. Portable near-infrared (NIR) spectrometers have the potential for rapid and non-destructive wood species identification, and while several studies have explored related methodologies, further research on their practical application is needed. To address this research gap, this study proposes a multi-scale convolutional neural network (CNN) combined with a portable NIR spectrometer (wavelengths range: 908 to 1676 nm) for wood species identification. To enhance the capability of directly extracting robust features from NIR spectral data collected by a portable spectrometer, the Gramian angular field (GAF) method is introduced to transform 1-dimensional (1D) NIR spectral data into 2-dimensional (2D) data matrices. Furthermore, a multi-scale CNN model is utilized for direct feature extraction. The representation by 2D matrices, instead of 1D NIR spectral data, aligns with 2D convolutional operations and enables a more robust extraction of discriminative features. In the experimental phase, eight wood species were identified using the proposed method, alongside commonly used multivariate data analysis and machine learning (ML) methods. The StratifiedGroupKFold dataset partitioning approach and five-fold cross-validation were used. Additionally, nine spectral preprocessing methods were compared, and principal component analysis (PCA) was used for feature extraction in the ML method. Evaluation metrics, such as accuracy, precision, and recall, were adopted to assess the performance of the methods. The proposed multi-scale CNN model, in combination with 2D GAF matrices of the 1D spectral data, yielded the most accurate results with a mean accuracy of 97.34% in the five-fold validation. These findings present a new approach for the construction of a rapid, non-destructive, and automatic wood species identification method using a portable NIR spectrometer.

Job satisfaction moderates the effect of competence and training on employee performance, a study on SMEs members of the Intako in Cooperative Sidoarjo Regency

This research is entitled "Job satisfaction moderates the effect of competence and training on employee performance", a study on SMEs members of the Intako in Cooperative Sidoarjo Regency. The purpose of this study is First, to test and analyze the effect of competence on the performance of employees of SMEs members of the Intako Cooperative in Sidoarjo Regency, to test and analyze the effect of training on the performance of employees of SMEs members of the Intako Cooperative in Sidoarjo Regency. Second, to test and analyze job satisfaction, moderating the effect of competence on the performance of SME employees who are members of the Intako Cooperative in Sidoarjo Regency. Third, to test and analyze job satisfaction moderating the effect of training on the performance of SME employees who are members of the Intako Cooperative in Sidoarjo Regency. The contributions in this study are: First, the contribution of theories, namely the results of this research is expected to provide a deep picture and understanding of the performance of SME employees who are members of the Intako Cooperative in Sidoarjo Regency. As well as references for similar studies in the future Second, the practical contribution of the results of this study is expected to be a reference for SMEs members of the Intako Cooperative to improve factors that affect employee performance. Third, policy contribution, namely the results of this research, is expected to be useful and used as input or evaluation in implementing government programs, especially in terms of community empowerment / SMEs carried out by the Office of Cooperatives and MSMEs, Industry, Trade, and Energy of Mineral Resources in Sidoarjo Regency. The data analysis technique used in this study, researchers used moderation analysis with data processing using the SmartPLS program version 3.0 starting from model measurement (outer model), model structure (inner model) and hypothesis testing. The results of testing the hypothesis of the model show that: First, competence has a significant effect, on employee performance, which means that the competencies possessed by employees are very good so that they have a meaningful influence on improving employee performance, so it can be said that the more competence increases, employee performance also increases. Second, training has a significant effect on employee performance, which means that the training provided by employees is good and has a meaningful influence on improving employee performance, so it can be said that the more training increases, of course employee performance increases. Third, job satisfaction is able to moderate the effect of competence on employee performance variables. Four, job satisfaction is able to moderate training on employee performance.

Love of variety and the welfare effects of trade in renewable resources

We analyze welfare effects of trade in renewable resources, which is induced by consumer love of variety in resource consumption. We model two countries, one being relatively wealthy in labor and capital, the other one being relatively resource abundant. For open-access resources, we show that trade freeness benefits the country that is wealthy in labor and capital, as it improves access to a larger variety of resources, especially to those of the resource-abundant country. The resource-abundant country also benefits from improved access to variety, but due to the increased resource demand and resulting overuse, this country’s welfare may depend on trade freeness in a non-monotonic fashion. We derive conditions such that welfare first decreases and then increases when trade freeness varies from autarky to costless trade. In direct comparison, autarky may generate higher welfare than costless trade only under restrictive conditions, in particular if endowments are very asymmetric and if the love of variety effect is weak. We also consider resource harvesting under private property rights and show that only for a sufficiently low discount rate the welfare increase from trade freeness in the resource-abundant country is sustainable.

Examining the Coopetition Relationships in Renewable Energy Trade among BRI Countries: Complexity, Stability, and Evolution

The Belt and Road Initiative (BRI) has significantly transformed the traditional energy market and reshaped international cooperation and conflict dynamics through its expanding trade in renewable energy resources. This study focuses on examining the complex and evolving nature of coopetition relationships in the renewable energy trade among BRI countries from 2013 to 2020. Understanding the interplay between cooperation and competition in this sector is crucial for comprehending the dynamics and stability of these trade relationships. Using a signed network approach, the findings of this study reveal that the countries predominantly exhibit a cooperative relationship. However, as time progresses, a notable pattern emerges, characterized by the coexistence of “competitive cooperation” and “cooperative competition”. In addition, coopetition group clustering is strongly influenced by geographical location. China, as a key player in the BRI, demonstrates a coopetition group characterized by a high inflow and low outflow pattern. Furthermore, the implementation of the BRI has greatly improved the overall stability of trade along the route. However, the coexistence of competition and cooperation among nations has increased the uncertainty of trade relations, thereby exerting a certain level of influence on their stability. Based on these findings, this study proposes policy recommendations to strength renewable energy trade relationships along the BRI route.

Resources and utilization of medicinal plants in countries and regions involved in "the Belt and Road" Initiative

The protection, development, and utilization of medicinal plant resources are important cornerstones of maintaining human health. However, due to factors such as the reduction of high-quality land resources, deterioration of ecological environments, and excessive and disorderly resource development, medicinal plant resources are becoming scarce, and some of them are insufficiently supplied. With the proposal of &quot;the Belt and Road&quot; Initiative, the cooperation between China and &quot;the Belt and Road&quot; partners(the countries and regions involved in &quot;the Belt and Road&quot; Initiative)is increasingly close, which provides a new opportunity for carrying out trade of medicinal plant resources and alleviating the problem of imbalance and relative inadequacy of medicinal plant resources in countries. This study first determined the distribution and species information of plant resources in countries and regions involved in &quot;the Belt and Road&quot; Initiative by investigating the database of plant distribution and that of medicinal plant resources. Then, according to the published data from the International Union for Conservation of Nature(IUCN) and the Convention on International Trade in Endangered Species of Wild Fauna and Flora(CITES), this study identified the rare and endangered medicinal plants and the medicinal plants under trade control in countries and regions involved in &quot;the Belt and Road&quot; Initiative and finally sorted out the list of potential medicinal plant resources in countries and regions involved in &quot;the Belt and Road&quot; Initiative that can be used by China. This data resource can not only be used for the overall protection of important endangered species but also scientifically guide the development and utilization of medicinal resources, providing guidance and a theoretical basis for the sustainable development of medicinal plant resources in countries and regions involved in &quot;the Belt and Road&quot; Initiative.