Modeling business expansion as a stochastic control problem, the study finds that firms are incentivized to expand but may wait.
problem Optimizing business expansion under exposure constraints and opportunity costs.
method Formulated as a novel stochastic control problem combined with optimal stopping time, derived an explicit solution for exponential utility.
result Firms are incentivized to expand but may wait due to opportunity costs and other factors.
This review covers AI in finance, challenges, techniques, and opportunities.
problem Challenges and opportunities in AI applications in finance.
method Comprehensive categorization and overview of AI research in finance over decades.
result A dense roadmap of AI challenges, techniques, and opportunities in finance.
The financial crisis offers new business opportunities in heritage management.
problem Financial institutions' weakened financial condition due to fluctuating real estate property prices.
method Proactive management and stakeholder cooperation to stabilize and optimize properties.
result Properties can serve as a solid base for new business and investment opportunities.
Intel's system identifies and categorizes businesses for sales opportunities.
problem Identifying relevant new markets and customers for large enterprises.
method Mining public business web pages, enriching with external data, and using deep learning.
result Significantly boosts sales personnel's ability to discover new customers and partnerships.
Optimizes insurance profits under regulatory constraints.
problem Maximizing profits while adhering to regulatory and risk policies.
method Developed a formalism for in-force business profit optimisation.
result Identified optimal asset allocation and annual opportunity cost.
The paper proposes a ML workflow for B2B sales prediction.
problem Predicting business to business sales outcomes using subjective human evaluations.
method A two-pipeline ML approach on Azure ML, including data enrichment and model training.
result ML predictions improve accuracy and increase sales value.
New approach optimizes sales process for B2B businesses.
problem Optimizing the sales process for B2B businesses.
method Causal Predictive Optimization and Generation with three layers: prediction, optimization, and serving.
result Significant wins over legacy systems in LinkedIn implementation.
The paper explores how innovative financing solutions boost Moroccan businesses' performance.
problem Market volatility, ecological transitions, and technological change pose challenges to business sustainability.
method Examines innovative financing solutions like venture capital, green finance, crowdfunding, and blockchain.
result Embracing innovative financial strategies can transform business challenges into opportunities.
New approach uses physics principles to improve business analytics.
problem Current business analytics methods fail with new data.
method Divide KPIs into controllable and uncontrollable groups; apply physics principles to controllable ones.
result Improves understanding and optimization of controllable KPI dynamics.
Kaggle competitions offer valuable insights for business forecasting.
problem Lack of attention to Kaggle competitions in academic forecasting studies.
method Review of results from six Kaggle competitions featuring real-life business forecasting tasks.
result Global ensemble models outperform local single models in Kaggle competitions.
Introduces Quantum Data Center for quantum era benefits.
problem No specific problem stated; focuses on future potential.
method Combines QRAM and quantum networks.
result QDC offers efficiency, security, and precision.
The professional services sector is at a turning point, with some industries showing growth opportunities.
problem Identifying growth opportunities in the professional services sector after decades of growth.
method A simple framework applied to the US economic context to diagnose growth opportunities.
result The professional services sector is expected to stall at a national level, but some industries still offer growth opportunities.
Paper discovers process models from online event streams.
problem Discovering process models from continuous event streams.
method Generic architecture for process discovery in event streams.
result The proposed architecture enables process discovery from event streams.
DRL enhances economic modeling with deep learning methods.
problem Complex dynamic business environments in economics.
method Comprehensive review of DL, RL, and deep RL methods applied to economics.
result DRL provides better performance and higher accuracy in economic applications.
TDA improves understanding of B2B customer loyalty.
problem Understanding and strengthening B2B customer relationships.
method Topological Data Analysis applied to commercial data.
result TDA enhances customer base understanding and predictive model accuracy.
Machine learning aids in climate change mitigation and adaptation.
problem Reducing greenhouse gas emissions and societal adaptation to climate change.
method Identifying high-impact problems and leveraging machine learning in collaboration with other fields.
result Machine learning can fill existing gaps in climate change solutions.
Study on insurance risk management and sustainable development.
problem Lack of attention to non-climate change aspects of sustainable development in insurance.
method Analysis of recent developments and legislative initiatives in insurance risk management.
result Strategies for small- and medium-sized enterprises to manage sustainable development risks.
In this chapter the complex systems are discussed in the context of economic and business policy and decision making. It will be showed and motivated that social systems are typically chaotic, non-linear and/or non-equilibrium and therefore complex systems. It is discussed that the rapid change in global consumer behav…
Study confirms USD/JPY rises at Gotobi days, suggesting trading strategy.
problem Verifying trading strategy based on Gotobi anomaly.
method Analyzing USD/JPY rate trends and examining arbitrage opportunities.
result Valid trading strategy identified for Gotobi anomaly.
This study integrates cost-sensitive and causal classification methods.
problem Improving classification model performance in business decision-making.
method A unifying evaluation framework for cost-sensitive and causal classification.
result Conventional classification is a specific case of causal classification.
Network analysis helps prevent money laundering by identifying risky clients and suspicious clusters.
problem Preventing money laundering using social network analysis.
method Real-world data analysis, network metrics, predictive models, visual analysis.
result Risk profiles can be predicted using social network metrics.
After the shocking series of bankruptcies started in 2008, the public does not trust anymore the classical methods of assessing business risks. The global economic severe downturn caused demand for both developed and emerging economies' exports to drop and the crisis became truly global. However, this current crisis of…
Graph theory enhances dynamic business insights in BA models.
problem Static BA models fail to capture dynamic business insights from data.
method Integrating graph theory into BA models for extensible data-driven analytics.
result Graph theory enables automatic generation of business insights.
Paper assesses risks of stablecoins, from lending to business-to-business.
problem Credit risks in decentralized stablecoin issuance.
method Examines mechanisms, risks, and mitigation strategies at each layer.
result Potential for scaling stablecoins while maintaining systemic health.
Overview of deep reinforcement learning, including elements and applications.
problem Optimizing decision-making in complex environments.
method Combining deep learning with reinforcement learning algorithms.
result Effective in diverse applications like games, robotics, and NLP.
Kurdistan Region is a tourist hub. This research analyzes other Non-Oil Sectors that have huge attractions of Foreign Direct Investments into the Kurdistan Region from 2005 to 2013. Comparative analysis was carried out between Iraq and the Region, and among influential Sectors of the Economy. T-test and ANOVA are stati…
Study shows credit expansion in mortgage markets influenced U.S. business cycle.
problem Lack of causal evidence in cross-country business cycle studies.
method Unique research design combining cross-metropolitan U.S. data.
result Credit expansion caused stronger booms and busts in house-related industries.
Large corporate credit models may be adapted for small business risk assessment.
problem Limited data and lack of credit analysts for small businesses.
method Adapting large corporate credit risk models for small businesses.
result Adapted models can predict small business credit risk effectively.
Framework uses deep learning to analyze large documents and identify their logical structure.
problem Analyzing large, multi-themed documents with diverse topics.
method Deep learning techniques to model and extract logical and semantic structure.
result Framework effectively identifies and classifies different sections of documents.
LLMs can collude in market divisions, maximizing profits.
problem Strategic collusion of LLM agents in multi-commodity markets.
method Examined LLMs in Cournot competition frameworks, analyzing pricing and resource allocation strategies.
result LLMs can monopolize specific commodities without direct human input or explicit collusion commands.
System constructs public competitor graph from financial reports.
problem Time-consuming and expert-laden manual extraction of corporate relationships.
method Financial report processing to generate reliable knowledge graph of corporate relationships.
result More than 83% of S\&P 500 companies' competition relationships retrieved.
Study evaluates sustainability of European banks using a new model.
problem Lack of a framework to evaluate sustainability of banking business models.
method Delphi-Analytic Hierarchy Process method to develop and assess the model.
result Norwegian and German banks have higher sustainability of their business models.
New method builds business taxonomies from corporate reports.
problem Challenging to classify emerging market industries.
method Concept-level hierarchical clustering of annual reports.
result Automatic construction of business taxonomies.
Bayesian model uses mobile data to assess business resilience after hurricanes.
problem Evaluating economic impact of extreme shocks on businesses.
method Bayesian structural time series model with mobile phone data.
result Estimates business resilience after hurricanes, revealing key characteristics.
Survey shows users value usability over functionality in process discovery tools.
problem Users prioritize usability over functional aspects in process discovery tools.
method A survey was conducted with 66 respondents to gather feedback on process discovery tools.
result Users prefer usability over functionality in process discovery tools.
Endogenous business cycles explain higher comovement across countries.
problem Standard models struggle to explain high comovement in business cycles across countries.
method Developed a demand-driven reduced-form model with strategic complementarities and international trade linkages.
result Combining endogenous business cycles with exogenous shocks matches empirical comovement levels.
Survey of EEG market and machine learning applications.
problem Improving neurology through data-driven research.
method Comprehensive survey of EEG applications and market.
result Machine learning enhances EEG applications and market growth.
Machine learning predicts US and EuroZone business cycles with high accuracy.
problem Predicting the business cycle phases in US and EuroZone.
method Three machine learning approaches were compared: Multinomial Logistic Regression (MLR) achieved the best results.
result MLR achieved 65.25% accuracy for EuroZone and 75% for US in predicting business cycle phases.
This report aims to improve trust in AI by explaining machine learning models.
problem Understanding and trusting automated decision-making systems.
method Survey and distillation of literature on explainable machine learning.
result Survey findings help practitioners understand and apply explainable methods.
Deep learning predicts business process events with high precision.
problem Predicting next events in business processes.
method Recurrent neural networks applied to deep learning.
result Deep learning surpasses state-of-the-art in prediction precision.
As Internet-based commerce becomes increasingly widespread, large data sets about the demand for and pricing of a wide variety of products become available. These present exciting new opportunities for empirical economic and business research, but also raise new statistical issues and challenges. In this article, we su…
Deep learning detects anomalies in SAP HANA KPIs.
problem Detecting problems in high-dimensional KPIs from DBMSs.
method Two complementary DL approaches: temporal and spatial learning.
result Experimental results confirm the effectiveness of the system and models.
Fine-tuning LLMs with observational data can lead to spurious correlations, but DeconfoundLM can mitigate this.
problem Aligning LLMs with human preferences and business objectives using observational data.
method DeconfoundLM, a method that removes confounders from reward signals.
result DeconfoundLM improves recovery of causal relationships and mitigates spurious correlations.
Unified metric SCV models subscription business revenue.
problem Analyzing revenue contribution of subscription businesses.
method Bayesian probabilistic model with exponential decay for churn.
result Exact and approximate closed-form solutions for revenue.
The analysis of the theoretical material revealed the lack of consensus on defini-tion of the tax stimulation of innovation-active business entities within the re-gional taxation. The definition tax stimulation of innovation-active business en-tities is specified.
Examines international taxation's impact on Georgian businesses.
problem Impact of international taxation on Georgian business entities.
method Analyzes types, features, and approaches of international taxation.
result Provides recommendations to correct current taxation issues.
CONDA-PM framework helps analyze concept drift in business processes.
problem Analyzing changes in business processes over time.
method Systematic Literature Review and framework development.
result Highlights areas needing research to complement existing efforts.
Enhances insurance loss models using InsurTech data and machine learning.
problem Traditional insurance loss models lack predictive accuracy due to limited data sources.
method Combining proprietary claims data with InsurTech data and applying machine learning techniques.
result Improved predictive accuracy of the loss model through machine learning.