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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,878 papers · 148 categories

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6.3%12.5%18.8%25.0% · Jul 199319922001200920172026
48 results for Supplier Relationships

Supply uncertainty leads to inefficient supply chain network formation.

problem How supply uncertainty affects supply chain network structure.
method Modeling a supply chain network with uncertain yield, where retailers and suppliers must form relationships and compete.
result Retailers tend to link to too few suppliers, leading to insufficient diversification of the supply base.

Supply Chain Management often requires independent organizations to work together to achieve shared objectives. This collaboration is necessary when coordinated actions benefit the group more than the uncoordinated efforts of individual firms. Despite the commonly reported benefits that can be gained in close relations…

2016-10-10abs ↗pdf ↗

Paper proposes machine learning for pricing 3D printing services in marketplaces.

problem Inefficient pricing methods for 3D printing services in marketplaces.
method Data mining and machine learning methods to estimate price ranges based on supplier and customer characteristics.
result Machine learning model achieves 65% accuracy for US suppliers and 59% for Europe suppliers in classifying 3D printer listings.

Supplier learns to price contracts against a learning retailer.

problem Designing data-driven pricing policies for a supplier facing a learning retailer.
method Connecting to non-stationary online learning, proposing dynamic pricing policies for discrete and continuous demand.
result Supplier's pricing policies lead to sublinear regret bounds under various retailer learning policies.

Suppliers (including companies and individual prosumers) may wish to protect their private information when selling items they have in stock. A market is envisaged where private information can be protected through the use of differential privacy and option contracts, while privacy-aware suppliers deliver their stock a…

2015-09-22abs ↗pdf ↗

Approach for assessing supply chain cyber risks using expert judgment and forecasting.

problem Supply chain managers face challenges in assessing cyber risks affecting business factors.
method Structured expert judgment and forecasting models to assess various attack techniques and impacts.
result Facilitates implementation of risk management activities and decision-making processes.

Supply chain resilience depends on balancing competition and self-interest.

problem Maintaining resilience in decentralized supply chains under uncertainty and competition.
method Modeling competitive suppliers and retailers with yield uncertainty and congestion, analyzing network formation.
result Decentralized supply chains can form resilient networks through competition and self-interest, contrary to intuition.

Study develops smart contract framework for procurement under demand variability.

problem Operational and economic implications of smart contract adoption under moderate uncertainty.
method Multi-supplier model with endogenized adoption costs, supplier readiness, and inventory penalties; analytical and numerical results.
result Partial adoption strategies support moderate demand variability, while excessive digital investment reduces profitability.

We model a nonlinear price curve quoted in a market as the utility indifference curve of a representative liquidity supplier. As the utility function we adopt a g-expectation. In contrast to the standard framework of financial engineering, a trader is no more price taker as any trade has a permanent market impact via a…

2017-02-05abs ↗pdf ↗

FS-GCLSTM predicts stock returns by leveraging value-chain relationships.

problem Traditional time series models fail to capture complex interdependencies in modern markets.
method FS-GCLSTM integrates value-chain networks and graph convolutions to predict stock returns.
result FS-GCLSTM consistently delivers superior portfolio performance compared to traditional models.

Study a market with uncertain informed traders, finding price impact depends on both asset value and informed trader count distribution.

problem Uncertain participation of informed traders in a market with limit orders.
method Characterized equilibrium by a fixed point integral equation, analyzed large order asymptotics, solved numerically.
result Equilibrium price impact depends on both asset value and distribution of informed traders, not just expected number of informed traders.

Although standard economics textbooks are seldom interested in production networks, modern economies are more and more based upon suppliers/customers interactions. One can consider entire sectors of the economy as generalised supply chains. We will take this view in the present paper and study under which conditions lo…

2005-07-13abs ↗pdf ↗

Network models assume unrealistic idiosyncratic risk, which can be mitigated by allowing for correlated shocks.

problem Network models assume idiosyncratic risk, which can be unrealistic and lead to incorrect predictions.
method Proposed a production-based asset pricing model to account for substitutability between trade partners and correlation in supply and demand shocks.
result Assets positively exposed to average propagation of upstream and downstream shocks earn lower average risk premia.

This paper optimizes revenue and resource balance in network revenue management.

problem Maximizing revenue while ensuring fair resource consumption across different suppliers.
method Introduces a regularized revenue objective and a primal-dual UCB algorithm for continuous prices and balancing.
result Achieves a worst-case regret of O~(N5/2T)\widetilde O(N^{5/2}\sqrt{T}) for revenue maximization and balancing.

Study on supply chain networks using wire transfers in Brazil.

problem Understanding economic integration and specialization in Brazilian cities.
method Constructed a directed and weighted network of wire transfers between cities, analyzed centrality measures, and used econometric analysis.
result Disassortative mixing pattern in trade network, stronger after recession, and impact of court efficiency on economic transactions.

The recently announced Energy Union by the European Commission is the most recent step in a series of developments aiming at integrating the EU's gas markets to increase social welfare (SW) and security of gas supply. Based on a spatial partial equilibrium model, we analyze the changes in consumption, prices, and SW up…

2015-12-16abs ↗pdf ↗

This paper shows how we can build a model for transactions when goods are given away in the expectation of a later settlement. In settings where people keep track of their social accounts we are able to redefine concepts like account balance, yield curve and the law of diminishing returns. The model provides us with a …

2014-01-19abs ↗pdf ↗

Modeling trading behavior with information signals and limit order books, showing market impact and equilibrium properties.

problem Analyzing the impact of information signals on trading behavior and market equilibrium in limit order books.
method Static equilibrium model with profit-maximizing investors and competitive dealers, using iterative algorithms and asymptotic analysis.
result The market impact of large trades follows a power law with fat tails and a logarithmic law with lighter tails, and the order book flattens as noise trading increases.

Optimal online learning for joint pricing and resource allocation.

problem Maximizing net profit in dynamic pricing and resource allocation with stochastic demand.
method Developed an efficient algorithm using a Lower-Confidence Bound (LCB) meta-strategy over multiple OCO agents.
result Achieved ildeO(Tmn) ilde{O}(\sqrt{Tmn}) regret, optimal with respect to time horizon TT.

This paper explores using graph neural networks for stock market predictions, improving accuracy with richer data.

problem Limited accuracy in financial market predictions using traditional methods.
method Combines graph neural networks with company knowledge graphs for better prediction.
result Significant improvement in prediction accuracy compared to benchmarks.

The kind of realized mission inflows the sensitivity to risk. Among other factors, the risk results from decision about liquid assets investment level and liquid assets financing. The higher the risk exposure, the higher the level of liquid assets. If the specific risk exposure is smaller, the more aggressive could be …

2013-01-16abs ↗pdf ↗

In this article we quantify the bullwhip effect (the variance amplification in replenishment orders) when demands and lead times are predicted in a simple two-stage supply chain with one supplier and one retailer. In recent research the impact of stochastic order lead time on the bullwhip effect is investigated, but th…

2013-09-27abs ↗pdf ↗

Blockchain markets with paid-priority trading can lead to biased prices and reduced liquidity.

problem Discrete clearing and paid-priority in blockchain markets lead to biased prices and reduced liquidity.
method Developed a model to evaluate the viability of blockchain markets under discrete clearing and paid-priority.
result Paid-priority ordering induces endogenous selection, leading to biased prices and reduced liquidity.

Study examines pricing strategies in competitive supply chains with discrete prices.

problem Inaccurate assumptions in traditional SC models for pricing decisions.
method Examines a SC model with one supplier and two manufacturers, considering customer demand segmentation and discrete price setting.
result Nash equilibria among manufacturers are not unique, and low denomination factors can lead to instability.

New model forecasts power consumption with high accuracy over months to years.

problem Probabilistic forecasting of power consumption in a middle-term horizon.
method Combines traditional time-series analysis with weather conditions using Gaussian Process.
result Promising results in Out-of-Sample density forecasts up to one year.

Since governments give stimulus to firms and expect the spillover effect by fiscal policies, it is important to know the effectiveness that they can control the economy. To clarify the controllability of the economy, we investigate a firm production network observed exhaustively in Japan and what firms should be direct…

2016-04-05abs ↗pdf ↗

In e-commerce, content quality of the product catalog plays a key role in delivering a satisfactory experience to the customers. In particular, visual content such as product images influences customers' engagement and purchase decisions. With the rapid growth of e-commerce and the advent of artificial intelligence, tr…

2018-11-12abs ↗pdf ↗

LoCEC classifies user relationships in large social networks, addressing sparsity issues.

problem Sparse relationship feature and label data in real social platforms.
method Local Community-based Edge Classification (LoCEC) framework with three-phase processing.
result Effective and efficient classification of user relationships in large-scale networks.