Hasil untuk "Balance of trade"

Qazi Salman Khalid, Shahid Maqsood, Jabir Mumtaz et al.

Abstract Urban logistics services, such as municipal solid waste collection, play a crucial role in shaping cities’ sustainability. These services are significant contributors to fuel consumption, operational costs, and greenhouse gas emissions. Traditional vehicle routing models, such as the capacitated vehicle routing problem with time windows, typically focus on minimizing distance or cost, which indirectly impacts emissions. However, these models fail to address the growing need for sustainable and environmentally conscious logistics strategies. This study introduces the emission-capacitated vehicle routing problem with time windows (E-CVRPTW), a novel optimization formulation that explicitly integrates a load-dependent fuel consumption model and an emission objective. The formulation also incorporates fleet-level policy constraints, including a carbon budget and an emission-intensity ceiling, providing a more comprehensive approach to minimizing both operational costs and environmental impacts. To solve the E-CVRPTW, a hybrid guided local search (HGLS) approach is employed with additional embedded features: (i) a novel cheapest insertion first initialization to generate high-quality starting solutions; (ii) adaptive feature penalties to diversify the search, while controlled neighborhood switching between 2-opt and 3-opt moves ensures an optimal balance between intensification and diversification. These features help the proposed algorithm to achieve better optimization solutions. Moreover, a rigorous experimental protocol using the Solomon and Gehring-Homberger benchmark instances demonstrates that HGLS, with additional features, significantly improves fuel consumption and emission reductions compared to baseline heuristics. Furthermore, a real-world case study on municipal waste collection reveals that optimized routing plans reduce fuel consumption and CO2 emissions by 9–11% while lowering total costs by 8–9%. The optimized solutions also meet strict policy targets under constrained conditions, showcasing the potential of E-CVRPTW in real-world applications. A sensitivity analysis explores the trade-offs among fuel prices, carbon prices, and emission weights, providing valuable insights for decision-makers in urban service planning and sustainability-focused policy formulation.

Nathalie van Vliet, Neal Millar, Rudolph Anthony Roberts et al.

The yellow-spotted river turtle (Podocnemis unifilis) is widely distributed across the Amazon, Orinoco, and Essequibo River basins. Studies from the Amazon and Orinoco regions highlight the species’ importance to local communities for food, income, and cultural heritage, as well as the significant threats it faces. To expand knowledge in the Essequibo River basin and assist with population management, the goal of this study was to assess turtle and egg consumption, as well as nest and turtle numbers, in the South Rupununi River in Guyana, and finally to propose sustainable management strategies that balance conservation goals with community needs, by comparing egg consumption rates with potential flood-related losses. Based on interviews conducted with 125 out of 185 Wapichan households from Sand Creek community, our findings showed that 12.0% of households (n = 15) collect annually an average of 41.87 eggs per household, while 22.4% of households (n = 28) harvest an average of 3.32 turtles per household per year. Households with more children tend to consume higher amounts of turtle eggs and meat, and those engaging in turtle harvesting report higher levels of turtle meat consumption. The primary motivation for turtle capture is consumption, particularly during culturally significant occasions, though turtles are also used for local trade, as pets, and for their shells. At the community level, the estimated annual consumption of 929 eggs is lower than the estimated 1,210 eggs lost annually to flooding on monitored beaches. However, the estimated 138 turtles harvested village-wide exceeds the number of adult turtles observed per survey day in 2021 (n = 13) and 2022 (n = 19). Our analysis suggests that during years with early floods, local egg demand could be met by rescuing at-risk nests located near the river, without increasing natural egg mortality. To offset wild turtle harvests, we recommend hatching at least 182 rescued eggs ex-situ and managing them through extensive farming systems. This approach could reduce adult turtle harvests, particularly of females. To achieve sustainable management, we propose monitoring all beaches where eggs are harvested, implementing a nest rescue program during floods, and establishing extensive turtle farming systems. These measures could shift egg harvesting from wild populations to controlled ex-situ programs, helping to conserve the yellow-spotted river turtle while supporting community needs.

Deepi Singh, Dana Golden, Gaurav Bhansali et al.

High Voltage Direct Current (HVDC) technology is a cornerstone of efficient Offshore Wind Farm (OWF) power transmission. This review examines the integration of HVDC technology in OWFs, considering collection and transmission aspects. The analysis is structured around four key dimensions: economic considerations, connection topologies, converter designs, and technical modeling. It begins with an in-depth economic analysis, evaluating cost-effectiveness, reliability, and market dynamics, focusing on investment, operational costs, and lifecycle expenses. Building on this foundation, the review explores various collection and transmission architectures, highlighting their technical and economical trade-offs, and evaluates power converter designs for efficiency, reliability, and offshore adaptability. Finally, advanced modeling and simulation techniques are reviewed to optimize system performance, enhance reliability, and balance computational efficiency. Throughout each of the four sections, economic and technical constraints are considered together. This helps to improve understanding of how systems can be designed in a way that meets the constraints of both fields and to enhance the feasibility on both dimensions. These insights provide a holistic framework for sustainable and economically viable Offshore Wind Energy (OWE) integration, offering practical guidance for developers and grid operators involved in the planning, deployment, and operation of HVDC-enabled offshore wind systems.

Irish Lorraine B. Pabuayon, Jessica Joy B. Bicaldo, Zelalem A. Alemar et al.

In semi-arid environments, crop production is heavily impacted by drought, salinity, and low nutrient availability. These marginal environmental conditions disrupt photosynthetic efficiency, translocation, and assimilate partitioning, all of which lead to yield reductions. As a result, maximizing crop productivity under marginal environments requires plants to effectively balance assimilate production (source strength) with use or storage (sink strength). Understanding the relative trade-offs between resources devoted to plant sources and sinks is critical to the development of resilient, productive crops. This review synthesizes research identifying physiological, morphological, and developmental traits that improve source and sink strength under stress conditions in semi-arid regions. Key source-related traits include intrinsic water-use efficiency, sustained photosynthetic capacity under stress, the stay-green phenotype, and favorable leaf area and canopy architecture. Sink traits such as stable reproductive organ development, phenotypic plasticity, root-shoot balance, and optimized phenological timing are highlighted as critical to maintaining sink strength under limiting conditions. We also assess the potential of advanced genetic, biotechnological, and ''omics'' approaches to develop climate-resilient crops, while addressing inherent trade-offs. Finally, we discuss emerging tools and conceptual frameworks that hold promise for improving selection and management of source–sink traits in climate-resilient cropping systems. This review provides a framework for integrating physiological, morphological, and developmental traits into breeding programs aimed at improving source-sink dynamics and advancing sustainable crop production in semi-arid and other marginal environments.

Jung-Ho Kim, Sudo Yi, Sang-Hwan Gwak et al.

To understand how fluctuations arise and are distributed in international trade, a question crucial for economic risk assessment and policymaking, we analyze strong adverse fluctuations-collapsed trades-defined as individual trades with sharp annual volume declines. Adopting a hypergraph framework for a fine-scale trade-centric representation of international trade, we find that collapsed trades (hyperedges) are clustered and their occurrence decays algebraically with trade volume (weight), which suggests inhomogeneous, epidemic-like spreading of collapse in the international trade hypergraph. Modeling collapse propagation as a contagion process and analyzing its dynamics, we show that a positive degree-weight correlation and a volume-decaying collapse rate synergistically suppress the onset of global collective collapse. Notably, the degree-weight correlation persisted but the volume-decay of the collapse rate weakened during the 2008-2009 global economic recession, resulting in a broader collapse spread. Our study shows how the interplay between structure and dynamics stabilizes complex systems.

Hana Samad, Michael Akinwumi, Jameel Khan et al.

As machine learning models are increasingly embedded into society through high-stakes decision-making, selecting the right algorithm for a given task, audience, and sector presents a critical challenge, particularly in the context of fairness. Traditional assessments of model fairness have often framed fairness as an objective mathematical property, treating model selection as an optimization problem under idealized informational conditions. This overlooks model multiplicity as a consideration--that multiple models can deliver similar performance while exhibiting different fairness characteristics. Legal scholars have engaged this challenge through the concept of Less Discriminatory Algorithms (LDAs), which frames model selection as a civil rights obligation. In real-world deployment, this normative challenge is bounded by constraints on fairness experimentation, e.g., regulatory standards, institutional priorities, and resource capacity. Against these considerations, the paper revisits Lee and Floridi (2021)'s relational fairness approach using updated 2021 Home Mortgage Disclosure Act (HMDA) data, and proposes an expansion of the scope of the LDA search process. We argue that extending the LDA search horizontally, considering fairness across model families themselves, provides a lightweight complement, or alternative, to within-model hyperparameter optimization, when operationalizing fairness in non-experimental, resource constrained settings. Fairness metrics alone offer useful, but insufficient signals to accurately evaluate candidate LDAs. Rather, by using a horizontal LDA search approach with the relational trade-off framework, we demonstrate a responsible minimum viable LDA search on real-world lending outcomes. Organizations can modify this approach to systematically compare, evaluate, and select LDAs that optimize fairness and accuracy in a sector-based contextualized manner.

Nicolas Apfel, Holger Breinlich, Nick Green et al.

Gravity equations are often used to evaluate counterfactual trade policy scenarios, such as the effect of regional trade agreements on trade flows. In this paper, we argue that the suitability of gravity equations for this purpose crucially depends on their out-of-sample predictive power. We propose a methodology that compares different versions of the gravity equation, both among themselves and with machine learning-based forecast methods such as random forests and neural networks. We find that the 3-way gravity model is difficult to beat in terms of out-of-sample average predictive performance, especially if a flexible specification is used. This result further justifies its place as the predominant tool for applied trade policy analysis. However, when the goal is to predict individual bilateral trade flows, the 3-way model can be outperformed by an ensemble machine learning method.

Jurek Preker

We introduce a novel equilibrium concept that incorporates Knightian uncertainty into the cursed equilibrium (Eyster and Rabin, 2005). This concept is then applied to a two-player game in which agents can engage in trade or refuse to do so. While the Bayesian Nash equilibrium predicts that trade never happens, players do trade in a cursed equilibrium. The inclusion of uncertainty enhances this effect for cursed and uncertainty averse players. This contrasts general findings that uncertainty reduces trade but is consistent with behavior that has been observed in experiments.

Pavlos Nikolaidis

Global efforts aiming to shift towards renewable energy and smart grid configurations require accurate unit commitment schedules to guarantee power balance and ensure feasible operation under different complex constraints. Intelligent systems utilizing hybrid and high-level techniques have arisen as promising solutions to provide optimum exploration–exploitation trade-offs at the expense of computational complexity. To ameliorate this requirement, which is extremely expensive in non-interconnected renewable systems, radically different approaches based on enhanced priority schemes and Boolean encoding/decoding have to take place. This compilation encompasses various mappings that convert multi-valued clausal forms into Boolean expressions with equivalent satisfiability. Avoiding any need to introduce prior parameter settings, the solution utilizes state-of-the-art advancements in the field of artificial intelligence models, namely Boolean mapping. It allows for the efficient identification of the optimal configuration of a non-convex system with binary and discontinuous dynamics in the fewest possible trials, providing impressive performance. In this way, Boolean mapping becomes capable of providing global optimum solutions to unit commitment utilizing fully tractable procedures without deteriorating the computational time. The results, considering a non-interconnected power system, show that the proposed model based on artificial intelligence presents advantageous performance in terms of generating cost and complexity. This is particularly important in isolated networks, where even a-not-so great deviation between production and consumption may reflect as a major disturbance in terms of frequency and voltage.

Neil A. Chriss

This is the third paper in a series concerning the game-theoretic aspects of position-building while in competition. The first paper set forth foundations and laid out the essential goal, which is to minimize implementation costs in light of how other traders are likely to trade. The majority of results in that paper center on the two traders in competition and equilibrium results are presented. The second paper, introduces computational methods based on Fourier Series which allows the introduction of a broad range of constraints into the optimal strategies derived. The current paper returns to the unconstrained case and provides a complete solution to finding equilibrium strategies in competition and handles completely arbitrary situations. As a result we present a detailed analysis of the value (or not) of trade centralization and we show that firms who naively centralize trades do not generally benefit and sometimes, in fact, lose. On the other hand, firms that strategically centralize their trades generally will be able to benefit.

Ravi Kashyap

We have designed an innovative portfolio rebalancing mechanism termed the Cascading Waterfall Round Robin Mechanism. This algorithmic approach recommends an ideal size and number of trades for each asset during the periodic rebalancing process, factoring in the gas fee and slippage. The essence of the model we have created gives indications regarding whether trades should be made on individual assets depending on the uncertainty in the micro - asset level characteristics - and macro - aggregate market factors - environments. In the hyper-volatile crypto market, our approach to daily rebalancing will benefit from volatility. Price movements will cause our algorithm to buy assets that drop in prices and sell as they soar. In fact, the buying and selling happen only when certain boundaries are crossed in order to weed out any market noise and ensure sound trade execution. We have provided several numerical examples to illustrate the steps - including the calculation of several intermediate variables - of our rebalancing mechanism. The Algorithm we have developed can be easily applied outside blockchain to investment funds across all asset classes at any trading frequency and rebalancing duration. Shakespeare As A Crypto Trader: To Trade Or Not To Trade, that is the Question, Whether an Optimizer can Yield the Answer, Against the Spikes and Crashes of Markets Gone Wild, To Quench One's Thirst before Liquidity Runs Dry, Or Wait till the Tide of Momentum turns Mild.

Mikhail Kaluzhsky

The institutionalization of digital trade is one of the most important directions in the formation of the information society in the Russian Federation. The studies reflect the emerging lag in the Russian economy readiness index to support online shopping. The author analyzes the reasons for the lag in the context of the institutional features of the development of digital trade. As the main obstacle that reduces the economic efficiency and competitiveness of digital trade, insufficient attention of the state to the formation of innovative institutions of the digital market is highlighted.

Yixuan Even Xu, Hanrui Zhang, Vincent Conitzer

Bilateral trade is one of the most natural and important forms of economic interaction: A seller has a single, indivisible item for sale, and a buyer is potentially interested. The two parties typically have different, privately known valuations for the item, and ideally, they would like to trade if the buyer values the item more than the seller. The celebrated impossibility result by Myerson and Satterthwaite shows that any mechanism for this setting must violate at least one important desideratum. In this paper, we investigate a richer paradigm of bilateral trade, with many self-interested buyers and sellers on both sides of a single trade who cannot be excluded from the trade. We show that this allows for more positive results. In fact, we establish a dichotomy in the possibility of trading efficiently. If in expectation, the buyers value the item more, we can achieve efficiency in the limit. If this is not the case, then efficiency cannot be achieved in general. En route, we characterize trading mechanisms that encourage truth-telling, which may be of independent interest. We also evaluate our trading mechanisms experimentally, and the experiments align with our theoretical results.

Matthew Smith, Yasaman Sarabi

Intra-firm trade describes the trade between affiliated firms and is increasingly important as global production is fragmented. However, statistics and data on global intra-firm trade patterns are widely unavailable. This study proposes a novel multilevel approach combining firm and country level data to construct a set of country intra-firm trade networks for various segments of the automotive production chain. A multilevel network is constructed with a network of international trade at the macro level, a firm ownership network at the micro level and a firm-country affiliation network linking the two, at the meso level. A motif detection approach is used to filter these networks to extract potential intra-firm trade ties between countries, where the motif (or substructure) is two countries linked by trade, each affiliated with a firm, and these two firms linked by ownership. The motif detection is used to extract potential country level intra-firm trade ties. An Exponential Random Graph Model (ERGM) is applied to the country level intra-firm trade networks, one for each segment of the automotive production chain, to inform on the determinants of intra-firm trade at the country level.

Yumou Fei

We study the two-agent single-item bilateral trade. Ideally, the trade should happen whenever the buyer's value for the item exceeds the seller's cost. However, the classical result of Myerson and Satterthwaite showed that no mechanism can achieve this without violating one of the Bayesian incentive compatibility, individual rationality and weakly balanced budget conditions. This motivates the study of approximating the trade-whenever-socially-beneficial mechanism, in terms of the expected gains-from-trade. Recently, Deng, Mao, Sivan, and Wang showed that the random-offerer mechanism achieves at least a 1/8.23 approximation. We improve this lower bound to 1/3.15 in this paper. We also determine the exact worst-case approximation ratio of the seller-pricing mechanism assuming the distribution of the buyer's value satisfies the monotone hazard rate property.

Chengyuan Han, Malte Schröder, Dirk Witthaut et al.

Understanding the structure and formation of networks is a central topic in complexity science. Economic networks are formed by decisions of individual agents and thus not properly described by established random graph models. In this article, we establish a model for the emergence of trade networks that is based on rational decisions of individual agents. The model incorporates key drivers for the emergence of trade, comparative advantage and economic scale effects, but also the heterogeneity of agents and the transportation or transaction costs. Numerical simulations show three macroscopically different regimes of the emerging trade networks. Depending on the specific transportation costs and the heterogeneity of individual preferences, we find centralized production with a star-like trade network, distributed production with all-to-all trading or local production and no trade. Using methods from statistical mechanics, we provide an analytic theory of the transitions between these regimes and estimates for critical parameters values.

Mu-Yao Li, Li Wang, Wen-Jie Xie et al.

The importance of fertilizers to agricultural production is undeniable, and most economies rely on international trade for fertilizer use. The stability of fertilizer trade networks is fundamental to food security. We use three valid methods to measure the temporal stability of the overall network and different functional sub-networks of the three fertilizer nutrients N, P and K from 1990 to 2018. The international N, P and K trade systems all have a trend of increasing stability with the process of globalization. The large-weight sub-network has relatively high stability, but is more likely to be impacted by extreme events. The small-weight sub-network is less stable, but has a strong self-healing ability and is less affected by shocks. Overall, all the three fertilizer trade networks exhibit a stable core with restorable periphery. The overall network stability of the three fertilizers is close, but the K trade has a significantly higher stability in the core part, and the N trade is the most stable in the non-core part.

Hao Chen, David A. Bullock, Jose M. Alonso et al.

Plants often live in adverse environmental conditions and are exposed to various stresses, such as heat, cold, heavy metals, salt, radiation, poor lighting, nutrient deficiency, drought, or flooding. To adapt to unfavorable environments, plants have evolved specialized molecular mechanisms that serve to balance the trade-off between abiotic stress responses and growth. These mechanisms enable plants to continue to develop and reproduce even under adverse conditions. Ethylene, as a key growth regulator, is leveraged by plants to mitigate the negative effects of some of these stresses on plant development and growth. By cooperating with other hormones, such as jasmonic acid (JA), abscisic acid (ABA), brassinosteroids (BR), auxin, gibberellic acid (GA), salicylic acid (SA), and cytokinin (CK), ethylene triggers defense and survival mechanisms thereby coordinating plant growth and development in response to abiotic stresses. This review describes the crosstalk between ethylene and other plant hormones in tipping the balance between plant growth and abiotic stress responses.

Eriamiatoe Efosa Festus

This study investigates the role of logistics and its six components on trade flows in selected Economic Community of West Africa States (ECOWAS) countries. The impact of other macro-economic variables on trade flows was also investigated. Ten countries were selected in eight years period. We decomposed trade flows into import and export trade. The World Bank Logistics performance index was used as a measure of logistics performance. The LPI has six components, and the impact of these components on trade flows were also examined. The fixed-effect model was used to explain the cross-country result that was obtained. The results showed that logistics has no significant impact on both Import and export, thus logistics play no role on trade flows among the selected ECOWAS countries. The components of logistics except Timeliness of shipments in reaching the final destination ( CRC ),have no impact on trade flows. Income was found to be positively related to imports. Exchange rate, consumption and money supply, reserve and tariff have no significant impact on imports. Relative import price has an inverse and significant relationship with imports. GDP has a positive and significant impact on export trade. The study also found FDI, savings, exchange rate and labour to have insignificant impact on exports. Finally, we found that logistics is not a driver of trade among the selected ECOWAS countries. The study recommended the introduction of the single window system and improvement in border management in order to reduce the cost associated with Logistics and thereby enhance trade.

Nor' Aznin Abu Bakar

This paper aims to analyse the trade behaviour of four selected ASEAN countries (based on their export/import products) by using a co-integration analysis. The demand for exports and imports are estimated for the period before the currency crisis erupted ( 1963 -1995 ), using the dynamic OLS (DOLS) method. The Johansen Maximum Likelihood (JML) approach is also employed to compare the results obtained. The results show that foreign income has a significant impact on export demand, suggesting that foreign disturbance in the form of economic activities is likely to be transmitted to these countries. The Marshall Lerner conditions are easily met for the case of Malaysia and Thailand (DOLS and JML). For Indonesia and the Philippines, the sum of the price elasticities of exports and imports demands are less than unity, this can be explained by the J-curve, in which the currency depreciation will first worsen the trade balance before it improves and it takes time to affect the trade balance.