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Open Access
Article
Publication date: 5 June 2023

Elias Shohei Kamimura, Anderson Rogério Faia Pinto and Marcelo Seido Nagano

This paper aims to present a literature review of the most recent optimisation methods applied to Credit Scoring Models (CSMs).

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Abstract

Purpose

This paper aims to present a literature review of the most recent optimisation methods applied to Credit Scoring Models (CSMs).

Design/methodology/approach

The research methodology employed technical procedures based on bibliographic and exploratory analyses. A traditional investigation was carried out using the Scopus, ScienceDirect and Web of Science databases. The papers selection and classification took place in three steps considering only studies in English language and published in electronic journals (from 2008 to 2022). The investigation led up to the selection of 46 publications (10 presenting literature reviews and 36 proposing CSMs).

Findings

The findings showed that CSMs are usually formulated using Financial Analysis, Machine Learning, Statistical Techniques, Operational Research and Data Mining Algorithms. The main databases used by the researchers were banks and the University of California, Irvine. The analyses identified 48 methods used by CSMs, the main ones being: Logistic Regression (13%), Naive Bayes (10%) and Artificial Neural Networks (7%). The authors conclude that advances in credit score studies will require new hybrid approaches capable of integrating Big Data and Deep Learning algorithms into CSMs. These algorithms should have practical issues considered consider practical issues for improving the level of adaptation and performance demanded for the CSMs.

Practical implications

The results of this study might provide considerable practical implications for the application of CSMs. As it was aimed to demonstrate the application of optimisation methods, it is highly considerable that legal and ethical issues should be better adapted to CSMs. It is also suggested improvement of studies focused on micro and small companies for sales in instalment plans and commercial credit through the improvement or new CSMs.

Originality/value

The economic reality surrounding credit granting has made risk management a complex decision-making issue increasingly supported by CSMs. Therefore, this paper satisfies an important gap in the literature to present an analysis of recent advances in optimisation methods applied to CSMs. The main contribution of this paper consists of presenting the evolution of the state of the art and future trends in studies aimed at proposing better CSMs.

Details

Journal of Economics, Finance and Administrative Science, vol. 28 no. 56
Type: Research Article
ISSN: 2077-1886

Keywords

Open Access
Article
Publication date: 19 July 2023

Michele Morais O. Pereira, Linda C. Hendry, Minelle E. Silva, Marilia Bonzanini Bossle and Luiz Marcelo Antonialli

This paper aims to investigate how the extant literature on sustainable supply chain management (SSCM) empirically explores the perspective of emerging economy suppliers operating…

1240

Abstract

Purpose

This paper aims to investigate how the extant literature on sustainable supply chain management (SSCM) empirically explores the perspective of emerging economy suppliers operating in global supply chains (GSCs). It thereby explains the role of emerging economy suppliers in determining the success of SSCM.

Design/methodology/approach

A systematic literature review of 41 empirical papers (published between 2007 and 2021) was conducted, involving both descriptive and thematic analyses.

Findings

The findings demonstrate that emerging economy suppliers have a key role in SSCM, given their use of positive feedback loops to proactively create remedies to surpass barriers using their collaboration mechanisms, and exploit authentic sustainability outcomes as reinforcements to drive further sustainability initiatives. The authors also demonstrate that suppliers are particularly focused on the cultural and institutional dimensions of sustainability. Finally, the authors provide an explanatory analytical framework to reduce the institutional distance between buyers and their global suppliers.

Research limitations/implications

This review identifies avenues for future research on the role of emerging economy suppliers in SSCM.

Practical implications

Recognising remedies to surpass barriers and reinforcements to drive new actions can aid SSCM in GSCs and improve understanding between buyers and suppliers.

Social implications

The valorisation of cultural and institutional issues can lead to more responsible supplier interactions and improved sustainability outcomes in emerging economies.

Originality/value

This review only analyses the viewpoint of emerging economy suppliers, whereas prior SSCM reviews have focused on the buyer perspective. Thus, the authors reduce supplier invisibility and institutional distance between GSC participants.

Access

Only Open Access

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