Search results

The purpose of this study is to examine the structure of the international fossil fuel trade network (IFFTN) and assess its effects on CO₂ emissions and global trade patterns. This research integrates complex network theory with econometric analysis to explore the dynamics of fossil fuel trade and its implications for environmental quality across various countries. Specifically, the study analyses the roles of different countries within this global network, examines the relationship between trade volumes and environmental impacts and evaluates how advancements in renewable energy generation could mitigate these effects. Through this comprehensive examination, the study seeks to provide an in-depth understanding of the trade-environment nexus.

The study uses data on international fossil fuel trade from 2005 to 2020, which includes 74 countries categorized as high-income, low-income and Asian economies based on their roles in the global market. This research constructs the IFFTN, where countries are depicted as nodes and trade links as edges. The authors analyse network parameters, such as degree, density and clustering coefficient, along with trade metrics like strength and centrality. These parameters are integrated into a panel fixed effects model, with the robustness of the findings confirmed through dynamic ordinary least squares (DOLS) analysis.

The study finds that the dynamic fossil fuel trade network includes key players such as the USA, China, France, India, the Netherlands and South Korea. It demonstrates increased connectivity and dependence among these countries, directly correlating with higher CO₂ emissions. However, this correlation is mitigated by the adoption of renewable energy, particularly in Asia and high-income countries. The impact on environmental quality is mediated through scale, technique and composition effects, suggesting significant environmental improvements through enhanced industry structure, technological progress and economies of scale.

This study recognizes several limitations. First, the categorization of countries into Asian economies, low-income and high-income groups may oversimplify the intricate effects of economic status on environmental impacts. Second, focusing primarily on per capita CO₂ emissions may neglect other critical environmental indicators. Future research should consider examining regional variations and including a wider range of environmental metrics. This approach would offer a more detailed perspective on the nuanced interactions between economic development and environmental sustainability, enhancing the depth and applicability of the findings.

To address the challenges of the IFFTN and CO₂ emissions, several practical policy measures are recommended. Governments should enhance international cooperation by establishing global platforms for sharing best practices and initiating technology transfer agreements to accelerate the adoption of energy-efficient technologies. Additionally, a phased transition towards more sustainable energy sources is crucial, involving increased investment in the renewable energy sector alongside incentives for adopting green technologies. On the trade front, governments should modify trade partnerships to address congestion externalities, fostering a shift towards more sustainable and environmentally friendly trade practices.

The social implications of the IFFTN are profound. As global reliance on fossil fuels continues, communities face heightened health risks due to increased pollution. Transitioning to renewable energy can alleviate these health concerns and the creation of green technologies, enhancing social well-being. Moreover, equitable access to energy-efficient solutions can reduce energy poverty, particularly in low-income countries, fostering greater societal resilience and inclusivity.

This study offers a pioneering examination of the trade-energy nexus across 74 countries, using complex network models to analyse diverse economic settings, particularly in Asian economies dominated by non-renewable energy. It identifies key market players and assesses their impact on dynamics such as congestion and market power. Additionally, the study explores the positive effects of renewable energy capacity on these relationships, highlighting its crucial role in driving sustainable energy transitions and enhancing the understanding of indirect trade-environment interactions.

While the literature has highlighted the impacts of COVID-19, there is limited evidence on the gendered determinants of the impact of COVID-19 among small-scale rural traders in developing and emerging economies.

Cross-border fish traders who had operated before and during the COVID-19 pandemic were interviewed in a survey conducted in Zambia and Malawi. Logistic regressions among male and female traders were employed to assess the gendered predictors.

Heterogeneous effects in geographical location, skills, and knowledge were reported among male cross-border traders. Effects of household structure and composition significantly influenced the impact of COVID-19 among female traders. Surprisingly, membership in trade associations was associated with the high impact of COVID-19.

Due to the COVID-19 pandemic and the migratory nature of cross-border fish traders, the population of cross-border fish traders at the time of the study was unknown and difficult to establish, cross-border fish traders (CBFT) at the landing sites and market areas were targeted for the survey without bias.

This paper addresses a gap in the literature on understanding gendered predictors of the impacts of COVID-19 among small-scale cross-border traders.

This study presents the impact of Economic Policy Uncertainty (EPU)-induced Trade Supply Chain Vulnerability (TSCV) on the Small and Medium-Sized Enterprises (SMEs) in India by leveraging the World Bank Enterprise Survey data for 2014 and 2022. Applying econometric techniques, it examines firm size’ influence on productivity and trade participation, providing insights for enhancing SME resilience and trade participation amid uncertainty.

The econometric techniques focus on export participation, along with variables such as total exports, firm size, productivity, and capital intensity. It addresses crucial factors such as the direct import of intermediate goods and foreign ownership. Utilizing the Cobb-Douglas production function, the study estimates Total Factor Productivity, mitigating endogeneity and multicollinearity through a two-stage process. Besides, the study uses a case study of North Indian SMEs engaged in manufacturing activities and their adoption of mitigation strategies to combat unprecedented EPU.

Results reveal that EPU-induced TSCV reduces exports, impacting employment and firm size. Increased productivity, driven by technological adoption, correlates with improved export performance. The study highlights the negative impact of TSCV on trade participation, particularly for smaller Indian firms. Moreover, SMEs implement cost-based, supplier-based, and inventory-based strategies more than technology-based and risk-based strategies.

Policy recommendations include promoting increased imports and inward foreign direct investment to enhance small firms’ trade integration during economic uncertainty. Tailored support for smaller firms, considering their limited capacity, is crucial. Encouraging small firms to engage in international trade and adopting diverse SC mitigation strategies associated with policy uncertainty are vital considerations.

This study explores the impact of EPU-induced TSCV on Indian SMEs’ trade dynamics, offering nuanced insights for policymakers to enhance SME resilience amid uncertainty. The econometric analysis unveils patterns in export behavior, productivity, and factors influencing trade participation during economic uncertainty.

The game strategies differ when different regions participate in the oil game. Under what circumstances will different participants choose cooperation or sanction strategies? This is the core issue of this paper.

Regarding the current and future game behavior between different regions in the oil trade, this paper constructs an evolutionary game model between two regions to explore the possibility of sanctions strategies between the two sides in different situations.

The research finds: (1) When the benefits of in-depth cooperation between the two regions are greater, both sides tend to adopt cooperative strategies. (2) When the trade conflict losses between the two regions are smaller, both sides adopt sanctions strategies. (3) When a strong region trades with a weak region, if the former adopts a sanctions strategy, the net profits are greater than the benefits of in-depth cooperation between the two regions. If the latter adopts a sanctions strategy, the net profits are less than the trade conflict losses between the two regions. There will be the strong region adopting a sanctions strategy and the weak region adopting a non-sanctions strategy. At this time, the latter should reasonably balance the immediate and future interests and give up some current interests in exchange for in-depth cooperation between the two regions. Otherwise, it will fall into the situation of unilateral sanctions by the strong against the weak.

There is no paper in the existing literature that uses the evolutionary game method to analyze the oil game problem between the two regions. This paper constructs a two-party evolutionary game model composed of crude oil importers and crude oil exporters and, based on this, analyzes the evolutionary stability between the two regions under sanctions and cooperation strategies, which enriches the energy research field.

This study deals with changes in European Union's (EU's) trade potential in Machinery (HS 84–85) and Transportation (HS86-89) products.

The study uses a Structural Gravity model, Poisson Pseudo Maximum Likelihood (PPML) estimation together with panel data for the years 2002–2018 and a two-step procedure that employs predicted values of bilateral trade to compare potential to actual trade.

Results for Machinery products suggest a potential to expand trade with existing Regional Trade Agreements (RTAs) in the American continent, and countries of the IGAD region in Africa. In Transportation, a high trade potential with RTAs is found in the Americas, Africa and the Middle East. Policy suggestions concentrate on opportunities for enhancing trade relations through trade liberalization and agreement proliferation.

There are no studies to date, that examine “collective” measure of EU trade potential, that treats the EU as a single country. Changes in existing opportunities to expand trade, common for EU members, are of special interest for policy formulation, especially after the recent turmoil presented by the Global Financial Crisis (GFC) and the Greek Economic Crisis (GEC). Treating the EU as a single entity, is necessary for the formulation of an effective, common, EU trade policy. This study concentrates on the manufacturing sector to examine existing opportunities for the EU to expand trade, after the GFC and the GEC. This article deals with Machinery (HS 84 and 85) and Transportation (HS 86 through 89) products as they comprise a significant part of total EU exports, reaching 41% of total exports in 2016. Finally, this study offers a unique illustration of results through trade potential heat maps.

This study examines whether common directors are guilty of contagion of corporate frauds from the customer side and, if so, how contagion occurs. Moreover, it explores a way to mitigate it, which is the increased digital orientation of firms.

Secondary data analysis is applied in this paper. We extract supply chain relations from the China Stock Market and Account Research (CSMAR) database as well as corporate fraud data from the same database and the official website of the China Securities Regulatory Commission (CSRC). Digital orientations are estimated through text analysis. Poisson regression is conducted to examine the moderating effect of common directors and the moderated moderating effect of the firms’ digital orientations.

By analysing the 2,096 downstream relations from 2000 to 2021 in China, the study reveals that corporate frauds are contagious through supply chains, while only customers’ misconduct can contagion to upstream firms. The presence of common directors strengthens such supply chain contagion. Additionally, the digital orientation can mitigate the positive moderating effect of common directors on supply chain contagion.

This study highlights the importance of understanding supply chain contagion through corporate fraud by (1) emphasising the existence of the contagion effects of corporate frauds; (2) understanding the potential channel in the process of contagion; (3) considering how digital orientation can mitigate this contagion and (4) recognising that the effect of contagion comes only from the downstream, not from the upstream.

Predicting commodity futures trading volumes represents an important matter to policymakers and a wide spectrum of market participants. The purpose of this study is to concentrate on the energy sector and explore the trading volume prediction issue for the thermal coal futures traded in Zhengzhou Commodity Exchange in China with daily data spanning January 2016–December 2020.

The nonlinear autoregressive neural network is adopted for this purpose and prediction performance is examined based upon a variety of settings over algorithms for model estimations, numbers of hidden neurons and delays and ratios for splitting the trading volume series into training, validation and testing phases.

A relatively simple model setting is arrived at that leads to predictions of good accuracy and stabilities and maintains small prediction errors up to the 99.273th quantile of the observed trading volume.

The results could, on one hand, serve as standalone technical trading volume predictions. They could, on the other hand, be combined with different (fundamental) prediction results for forming perspectives of trading trends and carrying out policy analysis.

The purpose of this paper that will address in this paper are: how to implement and test a reliable Block-chain-based energy system for the EU energy payments and logistic? What are the main results, impacts and implications of a Block-chain-based energy system for the EU energy payments and logistic?

The main aim of this study is to propose a Block-chain-based method to offer a secure, reliable and transparent method for energy logistic and payments for European Energy Transactions. To accomplish that aim, the research method of the study follows the design science research approach of smart contracts in the EU Energy logistic and payments. This research approach mainly consists of five sequential steps which are (1) problem and motivation identification, (2) solution objectives definition, (3) design and development and (4) demonstration and evaluation.

Results of data model demonstrate that the Block-chain-based energy system here can be used for any EU energy payments and logistics. Based on the data results of the model that mentioned above enhance the security and the integrity of the energy payments and logistic by using cryptographic techniques and consensus mechanisms to prevent and detect any tampering or falsification of the data on the Block-chain.

This paper represents a genuine piece of research that contributes to the field by providing new insights and understanding. The findings presented are the result of rigorous analysis and have not been previously published or submitted elsewhere for consideration.

Global value chains (GVCs) are facing unprecedented pressures arising from structural changes in the global economy and exogenous shocks including military conflicts and the aftermath of COVID-19. Considering the importance of value chain analysis in the current environment, the purpose of the study is to provide an up-to-date overarching global value chain literature review study that offers suggestions for research and practice to ensure resilient value and supply chains.

The authors provide a comprehensive review of literature of the value chain, commodity chain and production network research based on a systems overview of 5,628 publications to identify the extent of research on vulnerabilities and resilience of value chains globally and gaps therein. To provide the systems overview, the authors use scientometric content co-occurrence analysis methods to analyze and identify gaps within the existing literature.

Based on this overarching review of the literature, the authors identify gaps in the literature primarily related to the issue of unpreparedness of value chains to exogenous shocks. The authors suggest future research directions and propose an integrative model along with recommendations for restructuring value chains for resilience amidst exogenous shocks.

This study carries out an overarching study of interdisciplinary GVC literature in the age of geopolitical and societal challenges and is thus able to offer holistic insights and propositions for future research.

This paper aims to explore blockchain integration strategies within a three-level livestock meat supply chain in which consumers have a preference for quality trust in livestock meat products. The paper investigates three questions: First, how does consumers’ preference for quality trust affect blockchain integration and transaction decisions among supply chain participants? Second, under what circumstances will retailers choose to participate in the blockchain? Finally, how can other factors such as blockchain costs and supplier–retailer partnership value affect integration decisions?

This paper formulates a supply chain network equilibrium model and employs the logarithmic-quadratic proximal prediction-correction method to obtain equilibrium decisions. Extensive numerical studies are conducted using a pork supply chain network to analyze the implications of blockchain integration for different supply chain participants.

The results reveal several key insights: First, suppliers’ increased blockchain integration, driven by higher quality trust preference, can negatively affect their profits, particularly, with excessive trust preferences and high blockchain costs. Second, an increase in consumers’ preference for quality trust expands the range of unit operating costs for retailers engaging in blockchain. Finally, the supplier–retailer partnership drives retailer blockchain participation, facilitating enhanced information sharing to benefit the entire supply chain.

This study provides original insights into blockchain integration strategies in an agricultural supply chain through the application of the supply chain network equilibrium model. The investigation of several key factors on equilibrium decisions provides important managerial implications for different supply chain participants to address consumers’ preference for quality trust and enhance overall supply chain performance.