Machine Learning Techniques in Bankruptcy Prediction: A Systematic Literature Review DOI
Απόστολος Δασίλας,

Anna Rigani

Published: Jan. 1, 2023

The main objective of this systematic literature review is to unveil the prevailing trend employing cutting-edge models for bankruptcy prediction a period spanning from 2012 mid-2023. Employing PRISMA method, we reviewed 262 empirical studies on prediction. Prior extensive research has shown that integration more advanced techniques, such as hybrid model, enhances accuracy and robustness, leading reliable forecasts. While financial ratios have traditionally played central role in models, places emphasis significance incorporating non-financial ratios. Non-financial capture qualitative intangible factors management competence, corporate governance practices and, market reputation. inclusion these ratios, alongside enables comprehensive evaluation firm's health improves predictions. also addresses challenges limitations associated with incorporation Our shows there current toward development combine multiple methodologies variables improve accuracy. Researchers are actively addressing challenge imbalanced datasets by exploring developing specialized techniques handling data. Moreover, during it essential consider range metrics, including sensitivity specificity, along other relevant obtain assessment model performance.

Language: Английский

Roles of AI: Financing selection for regretful SMEs in e-commerce supply chains DOI
Xin Yao, Xiyan Li,

Sachin Kumar Mangla

et al.

Transportation Research Part E Logistics and Transportation Review, Journal Year: 2024, Volume and Issue: 189, P. 103649 - 103649

Published: July 9, 2024

Language: Английский

Citations

7
Machine learning techniques in bankruptcy prediction: A systematic literature review DOI
Απόστολος Δασίλας,

Anna Rigani

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: 255, P. 124761 - 124761

Published: July 14, 2024

Language: Английский

Citations

7
Diagnosis with incomplete multi-view data: A variational deep financial distress prediction method DOI

Yating Huang,

Zhao Wang, Cuiqing Jiang

et al.

Technological Forecasting and Social Change, Journal Year: 2024, Volume and Issue: 201, P. 123269 - 123269

Published: Feb. 17, 2024

Language: Английский

Citations

5
Innovative Machine Learning Approaches for Complexity in Economic Forecasting and SME Growth: A Comprehensive Review DOI Creative Commons

Mustafa I. Al-Karkhi,

Grzegorz Rza̧dkowski

Journal of Economy and Technology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

Citations

0
Emerging Technologies for Small and Medium Enterprises (SMEs) Growth DOI
Wasswa Shafik

Advances in logistics, operations, and management science book series, Journal Year: 2025, Volume and Issue: unknown, P. 173 - 196

Published: Feb. 7, 2025

Emerging technologies such as ChatGPT, Blockchain, Robotics, and Artificial Intelligence (AI) are transforming the growth trajectory of Small Medium Enterprises (SMEs). ChatGPT enhances customer engagement automates communication, enabling personalized services efficient support. Blockchain fosters trust transparency in transactions, streamlining supply chains securing digital contracts. Robotics revolutionizes manufacturing logistics, boosting productivity through automation reducing operational costs. AI optimizes business processes with predictive analytics intelligent decision-making, driving innovation competitiveness. This paper explores how these empower SMEs to overcome traditional barriers, scale operations, achieve sustainable a rapidly evolving economy.

Language: Английский

Citations

0
Patent value prediction in biomedical textiles: A method based on a fusion of machine learning models DOI Creative Commons
Y. He,

K F Deng,

Jiawei Han

et al.

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(4), P. e0322182 - e0322182

Published: April 24, 2025

Patent value prediction is essential for technology innovation management. This study aims to enhance management in the field of biomedical textiles by processing complex patent information improve accuracy predicting values. A grading method based on a fusion machine learning models proposed, utilizing 113,428 textile patents as research sample. The combines BERT (Bidirectional Encoder Representations from Transformers) and stacking strategy classify predict class using both textual structured features. We implemented this textiles, leading development BioTexVal—the first dedicated model domain. BioTexVal’s lies employing that integrates multiple predictive while leveraging unstructured data during training. Results have shown approach significantly outperforms previous methods. Validated spanning 2003 2023, BioTexVal achieved an 88.38%. uses average annual forward citations indicator distinguishing grades. may require adjustments characteristics when applied other fields ensure its effectiveness.

Language: Английский

Citations

0
FORECASTING CURRENT ASSETS OF ENTERPRISES TO SUPPORT FINANCIAL AND ECONOMIC SECURITY AND PREVENT BANKRUPTCY DOI Open Access
Iryna Mihus,

Rostyslav Zaiets

Смарт-економіка підприємництво та безпека, Journal Year: 2024, Volume and Issue: 2(1), P. 29 - 37

Published: March 29, 2024

Current assets are an important part of the operational activity any business entity and key importance in maintaining financial economic security enterprise.Current enterprise have a significant impact on production activity, innovation, competitiveness, personnel, logistics, etc.They help to avoid interruptions effectively commercialize innovative products market.It is impossible form effective policies concepts development without taking into account current assets.Thus, there conceptual need develop methodology for forecasting company's assets, which will ensure support prevent bankruptcy.The information resource our research was reported data JSC "Poltavaholod", TM "Kozub Product", LLC "Reshetylivskiy Maslozavod", "Lubensky Dairy Plant" (trademark "Harmony") "Orzhitskyi Molokozavod" "Zarog") period 2018-2022.In order understand theoretical essence stability enterprise, we deeply studied regarding legislative regulation bankruptcy procedure.In reveal topic article, used system statistical economic-mathematical methods.The results modeling enterprises proved that largest projected increase value 2024 held by "Poltavaholod" 18.86%, followed 14.95%, lowest growth this indicator recorded at "Reshetylivskii Maslozavod" 0.11%.The analysis 0.11% unable maintain due weak level efficiency assets.This company closest among other analyzed companies.The specified method great stimulating entities.This technique be useful entrepreneurs who developing promising strategies aimed future development, policy conservation, environmentalization use human resources.

Language: Английский

Citations

3
Integrating deep learning and multi-attention for joint extraction of entities and relationships in engineering consulting texts DOI

Binwei Gao,

Yuquan Hu,

Jianan Gu

et al.

Automation in Construction, Journal Year: 2024, Volume and Issue: 168, P. 105739 - 105739

Published: Sept. 12, 2024

Language: Английский

Citations

3
The impact of artificial intelligence on corporate financial asset allocation: Moderating role of organizational dynamic capabilities DOI
Yu Li,

Huiyi Zhong,

Qiye Tong

et al.

International Review of Financial Analysis, Journal Year: 2024, Volume and Issue: 96, P. 103773 - 103773

Published: Nov. 1, 2024

Language: Английский

Citations

3
Assessing trade supply chain vulnerability and trade participation of SMEs in India: insights from a comprehensive analysis DOI
Tapas Sudan, Rashi Taggar

International Journal of Productivity and Performance Management, Journal Year: 2024, Volume and Issue: unknown

Published: July 23, 2024

Purpose This study presents the impact of Economic Policy Uncertainty (EPU)-induced Trade Supply Chain Vulnerability (TSCV) on Small and Medium-Sized Enterprises (SMEs) in India by leveraging World Bank Enterprise Survey data for 2014 2022. Applying econometric techniques, it examines firm size’ influence productivity trade participation, providing insights enhancing SME resilience participation amid uncertainty. Design/methodology/approach The techniques focus export along with variables such as total exports, size, productivity, capital intensity. It addresses crucial factors direct import intermediate goods foreign ownership. Utilizing Cobb-Douglas production function, estimates Total Factor Productivity, mitigating endogeneity multicollinearity through a two-stage process. Besides, uses case North Indian SMEs engaged manufacturing activities their adoption mitigation strategies to combat unprecedented EPU. Findings Results reveal that EPU-induced TSCV reduces impacting employment size. Increased driven technological adoption, correlates improved performance. highlights negative particularly smaller firms. Moreover, implement cost-based, supplier-based, inventory-based more than technology-based risk-based strategies. Practical implications recommendations include promoting increased imports inward investment enhance small firms’ integration during economic Tailored support firms, considering limited capacity, is crucial. Encouraging firms engage international adopting diverse SC associated policy uncertainty are vital considerations. Originality/value explores SMEs’ dynamics, offering nuanced policymakers analysis unveils patterns behavior, influencing

Language: Английский

Citations

2