Research
On-device research index

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.

168,742 papers · 148 categories

Trend · papers per month

12.5%25.0%37.5%50.0% · Jan 199519922001200920172026
48 results for consumer products

GBS uses machine learning to design products based on consumer preferences.

problem Designing products to meet consumer preferences.
method GBS is a discrete choice experiment that uses machine learning to adaptively construct paired comparison questions.
result GBS outperforms existing methods in accuracy and sample efficiency.

Study optimizes product assortment for retailers with repeated exposures and patience costs.

problem Optimizing product assortment for online retailers with repeated exposures and varying consumer patience.
method Developed a cascade multinomial logit model to capture repeated exposures and patience costs.
result Proposed an approximation solution to the assortment optimization problem.

Paper proposes a method to estimate consumer valuations from bundle sales data.

problem Estimating consumer valuations from bundle sales data using classical methods is challenging.
method Proposes an approach using EM algorithm and Monte Carlo simulation to estimate consumer valuations from bundle sales data.
result The approach can recover the distribution of consumers' valuations and is robust to unobserved no-purchases and clustered market segments.

Every year, thousands of people receive consumer product related injuries. Research indicates that online customer reviews can be processed to autonomously identify product safety issues. Early identification of safety issues can lead to earlier recalls, and thus fewer injuries and deaths. A dataset of product reviews …

2018-04-27abs ↗pdf ↗

This study examines how fashion consumption affects self-confidence and buying behavior in Iranian consumers.

problem Understanding the role of self-confidence in fashion buying behavior.
method A questionnaire was used to collect data from 400 consumers in Tehran's clothing market. Structural equations and factor analysis were employed to test the model.
result Interest in fashion, personal taste, utilitarianism, and new products positively impact self-confidence, and self-confidence positively impacts fashion buying behavior.

We develop a probabilistic consumer choice framework based on information asymmetry between consumers and firms. This framework makes it possible to study market competition of several firms by both quality and price of their products. We find Nash market equilibria and other optimal strategies in various situations ra…

2013-12-13abs ↗pdf ↗

The study improves load forecasting for electricity consumers using advanced machine learning models.

problem Improving short-term load forecasting for effective scheduling and decision-making.
method Proposes and evaluates statistical nonlinear models, including LSTM and GRU, for 15-min frequency electricity load forecasting.
result Advanced models outperform other models in out-of-sample forecasting accuracy, as shown by the Diebold-Mariano test.

Social interactions and personal tastes shape our consumption behavior of cultural products. In this study, we present a computational model of a cultural market and we aim to analyze the behavior of the consumer population as an emergent phenomena. Our results suggest that the final market shares of cultural products …

2007-07-16abs ↗pdf ↗

The paper develops a method to estimate consumer preferences from observed rankings.

problem Estimating consumer preferences from partial ranking information.
method Interpreting observed rankings as pairwise comparisons, modeling latent utility, and correcting for selection bias.
result The method improves recommendation performance, especially for previously unconsumed products.

An analytic model is presented that considers the evolution of a market of durable goods. The model suggests that after introduction goods spread always according to a Bass diffusion. However, this phase will be followed by a diffusion process for durable consumer goods governed by a variation-selection-reproduction me…

2013-06-14abs ↗pdf ↗

Novel method CHPCA simplifies complex market dynamics.

problem Quantifying interactions in rapidly evolving consumer goods markets.
method Complex Hilbert Principal Component Analysis (CHPCA) and Hodge decomposition.
result Revealed comovements and customer heterogeneity in consumer choice process.

Paper presents a novel time series clustering algorithm for financial inclusion.

problem Difficulty in understanding consumer financial behavior without restrictive credit scoring.
method Developed a novel time series clustering algorithm.
result Allows institutions to offer unique financial products based on customer needs.

Modeling producer and consumer interactions in commodity markets with risk aversion.

problem Analyzing the impact of risk aversion on producer-consumer interactions in commodity markets.
method Linear-quadratic McKean-Vlasov stochastic differential game, martingale optimality principle, BSDEs.
result Characterization of Nash equilibrium and indifference prices.

Quality-designed consumer products are easy to recognize. Wouldn't it be great if the quality of financial products became just as apparent? This paper is addressed to financial practitioners. It provides an informal introduction to Quantitative Structuring -- a technology of manufacturing quality financial products (i…

2015-07-26abs ↗pdf ↗

Study copyright's impact on creative industries using AI-generated fonts.

problem Estimating supply and demand in creative industries with AI-generated content.
method Neural network embeddings, spatial regression, event-study analyses, structural model of supply and demand.
result Copyright can raise consumer welfare by encouraging product relocation.

We analyse four consecutive cycles observed in the USA for employment and inflation. They are driven by three oil price shocks and an intended interest rate shock. Non-linear coupling between the rate equations for consumer products as prey and consumers as predators provides the required instability, but its natural d…

2012-12-06abs ↗pdf ↗

The study finds variations in ownership structure and efficiency across sectors in Malaysia.

problem Investigate variations in ownership structure and firm efficiency across sectors in Malaysia.
method Frequency distributions of ownership structure, DEA under CRS and VRS, stratified random sampling.
result There are variations in firm ownership structure and efficiency across sectors in Malaysia.

A bipartite producer-consumer network is constructed to describe the industrial structure. The edges from consumer to producer represent the choices of the consumer for the final products and the degree of producer can represent its market share. So the size distribution of firms can be characterized by producer's degr…

2005-07-21abs ↗pdf ↗

Online reviews provided by consumers are a valuable asset for e-Commerce platforms, influencing potential consumers in making purchasing decisions. However, these reviews are of varying quality, with the useful ones buried deep within a heap of non-informative reviews. In this work, we attempt to automatically identify…

2017-05-06abs ↗pdf ↗

The paper examines logistic regression in sparse network settings, improving inference under varying degrees of dyadic dependence.

problem Improving inference in logistic regression with sparse network data.
method Sparse network asymptotics, martingale central limit theorem, variance decomposition.
result Sparse network asymptotics lead to better variance estimators for logistic regression.

Electricity accounts for 25% of global greenhouse gas emissions. Reducing emissions related to electricity consumption requires accurate measurements readily available to consumers, regulators and investors. In this case study, we propose a new real-time consumption-based accounting approach based on flow tracing. This…

2018-12-17abs ↗pdf ↗

Paper introduces RTT2Vec for real-time grocery recommendations, achieving 9.4% uplift over baselines.

problem Personalized grocery recommendations to improve user experience and sales.
method RTT2Vec deep architecture for real-time recommendations, approximate inference technique.
result 9.4% uplift in prediction metrics over baseline models.

Deep learning system improves accuracy of food packaging date verification.

problem Improper labeling of food packaging poses health risks.
method Multi-source deep domain adaptation for domain-invariant representations and class boundary alignment.
result Significant improvement in classification accuracy of use-by date verification.

Aesthetics are critically important to market acceptance. In the automotive industry, an improved aesthetic design can boost sales by 30% or more. Firms invest heavily in designing and testing aesthetics. A single automotive "theme clinic" can cost over $100,000, and hundreds are conducted annually. We propose a model …

2019-07-17abs ↗pdf ↗

Dynamic pricing aims to match power supply and demand in an energy transition.

problem Mismatch between renewable energy supply and consumer demand.
method Formalizes decision-making problem, designs forecasting models, and statistical demand response models.
result Dynamic pricing can synchronise power supply and demand effectively.

Bayesian networks improve product risk assessment by handling uncertainty and causality.

problem Limited handling of uncertainty and inability to incorporate causal explanations in existing methods.
method Bayesian Networks (BNs) for improved systematic product risk assessment.
result BN approach provides more powerful and flexible risk assessments.