Digital Supply Chain Finance Model in Thailand

The chapter aims to study  and to evaluate digital supply chain finance model in Thailand. The samples in the research study consisted of ten purposively selected experts consisted of three experts on supply chain, five experts on Digital Technology and three experts on the finance. Data were analysed by arithmetic mean and standard deviation. The research findings model seven elements namely main components, Buyer, supplier , Bank or Financial Institution. The ten experts agree that digital supply chain finance model in Thailand was high suitability and can be appropriately applied in actual work settings

A hybrid XGBoost-MLP model for credit risk assessment on Digital Supply Chain Finance

Supply Chain Finance (SCF) has gradually taken on digital characteristics with the rapid development of electronic information technology. Business audit information has become more abundant and complex, which has increased the efficiency and increased the potential risk of commercial banks, with credit risk being the biggest risk they face. Therefore, credit risk assessment based on the application of digital SCF is of great importance to commercial banks’ financial decisions. This paper uses a hybrid Extreme Gradient Boosting Multi-Layer Perceptron (XGBoost-MLP) model to assess the credit risk of Digital SCF (DSCF). In this paper, 1357 observations from 85 Chinese-listed SMEs over the period 2016–2019 are selected as the empirical sample, and the important features of credit risk assessment in DSCF are automatically selected through the feature selection of the XGBoost model in the first stage, then followed by credit risk assessment through the MLP in the second stage. Based on the empirical results, we find that the XGBoost-MLP model has good performance in credit risk assessment, where XGBoost feature selection is important for the credit risk assessment model. From the perspective of DSCF, the results show that the inclusion of digital features improves the accuracy of credit risk assessment in SCF

Integrating BWM and ARAS under hesitant linguistic environment for digital supply chain finance supplier section

In the era of intelligence and informatization, digital supply chain finance (DSCF) has become one of the important trends in the development of supply chain finance. With the gradual increase of DSCF suppliers and various requirements of small and medium-sized enterprises for suppliers in providing financing services, selecting the most suitable DSCF supplier is of great significance for most small and medium-sized enterprises to expand reproduction and improve competitiveness. To address such a decision-making problem, this paper proposes a new multi-expert multiple criteria decision-making model by integrating the Best Worst Method (BWM) and Additive Ratio ASsessment (ARAS) method under the hesitant fuzzy linguistic environment, in which the hesitant fuzzy linguistic BWM method is applied to determine the weights of criteria while the hesitant fuzzy linguistic ARAS method is proposed to rank the candidate suppliers. A case study is given to demonstrate the procedure of the proposed method for the selection of optimal DSCF suppliers, which shows the feasibility of the proposed method. Finally, sensitivity analysis and comparative analyses are provided to testify the applicability and superiority of the proposed method

Achieving European Policy Objectives through Financial Technology. ECRI Commentary No. 17, 16 November 2015

Alistair Milne argues in this ECRI Commentary that ‘FinTech’ (newly emerging Financial Technologies) can play a crucial role in achieving European policy objectives in the area of financial markets. These notably include increasing access by smaller firms to trade credit and other forms of external finance and completing the banking and capital markets unions. He points out, however, that accomplishing these objectives will require a coordinated European policy response, focused especially on promoting common business processes and the adoption of shared technology and data standards

Decision models for supplier selection in industry 4.0 era: a systematic literature review

Industry 4.0 comprises the application of different technological solutions so that business processes throughout the production chain are integrated. The supplier’s selection, considering the industry 4.0 requirements, is essential in promoting collaborative strategies between suppliers and manufacturers. In this context, this study presents a systematic literature review about quantitative models to support supplier selection in the industry 4.0 era. Fourteen studies were reviewed and characterized in different perspectives such as modelling, application, and validation of the decision model. The results revealed that most of the decision models were developed combining multicriteria decision-making (MCDM) with Artificial Intelligence (AI). Among the criteria related to the Industry 4.0 environment, the most frequent ones were information sharing, technological capacity, digital collaboration and engagement. The gathered results can be useful to guide researchers and managers in the development of computational tools to assist decision-making processes for supplier selection in Industry 4.0 era.info:eu-repo/semantics/publishedVersio

Research on the Realization Path of Intelligent Logistics in the “New Retail” Era

New retail is the product of innovation and transformation of e-commerce, physical retail and modern logistics. New retail relies on omni-channel logistics based on supply chain integration, order-driven precise logistics service and high intensity urban distribution carrying capacity, which has brought huge impacts and development opportunities to the logistics industry. At present, there are limitations in China\u27s intelligent logistics, both in terms of logistics infrastructure construction, logistics information services, and regulatory guarantee systems, which restrict the development of new retail . In order to realize the high-quality support of new retail by intelligent logistics, a trinity of intelligent logistics construction path of government guidance, market leadership, and social co-governance is proposed. We should accelerate the construction of intelligent logistics infrastructure under the guidance of the government, give full play to the leading role of the market to build an intelligent logistics information platform, and build a multi-security logistics security system through joint governance of all sectors of society to meet the overall objective of the high-quality support of logistics for new retail

Research on the application of smart supply chain finance in the financing of private scientific and technological enterprises in China

Supply chain finance (SCF) has experienced the development stages of offline SCF, online traditional SCF, and Internet SCF, and has developed to the stage of smart supply chain finance (SSCF) driven by digital technology in China. We analyze the theoretical framework of SSCF model from three aspects: loose coupling alliance organizational structure, visual operation and management process and symbiotic multi-agent coordination mechanism. In the financing of private scientific and technological enterprises, SSCF will show smart effects such as intelligent decision-making, harmonious service, penetrating management and digital risk control. Further, the process of SSCF providing financing services for private scientific and technological enterprises is designed. Finally, in view of the problems and challenges faced by private scientific and technological enterprises in the application of SSCF, we put forward countermeasures and suggestions from the aspects of expanding the dimension of smart transformation, building a perfect regulatory system and legal system, and strengthening the cultivation of compound talents in this paper

Research on Mode and Risk Prevention of Agricultural Supply Chain Finance based on E-commerce

The rapid development of e-commerce has a profound impact on agricultural supply chain finance (ASCF), which is of great significance to enhance the resilience of agricultural economic development, realize the poverty alleviation effect of agricultural enterprises, integrate agricultural supply chain resources and solve the financing difficulties of agricultural enterprises. We analyze the participants and functions of the ASCF mode based on e-commerce, and the contract framework of various participants when they operate in the ASCF platform in this paper. Based on the agricultural industry chain, we analyze the operation process of accounts receivable financing mode, inventory financing mode and prepayment financing mode based on E-commerce. Finally, in view of the natural risks, credit risks, logistics risks, technical risks and legal risks that may exist in ASCF based on e-commerce, the corresponding countermeasures are put forward from the aspects of dispersing natural risks, building digital credit risk assessment system, building agricultural logistics network system, improving technical risk monitoring system, and improving relevant laws and regulations policy recommendations

A review of ensemble learning and data augmentation models for class imbalanced problems: combination, implementation and evaluation

Class imbalance (CI) in classification problems arises when the number of observations belonging to one class is lower than the other. Ensemble learning combines multiple models to obtain a robust model and has been prominently used with data augmentation methods to address class imbalance problems. In the last decade, a number of strategies have been added to enhance ensemble learning and data augmentation methods, along with new methods such as generative adversarial networks (GANs). A combination of these has been applied in many studies, and the evaluation of different combinations would enable a better understanding and guidance for different application domains. In this paper, we present a computational study to evaluate data augmentation and ensemble learning methods used to address prominent benchmark CI problems. We present a general framework that evaluates 9 data augmentation and 9 ensemble learning methods for CI problems. Our objective is to identify the most effective combination for improving classification performance on imbalanced datasets. The results indicate that combinations of data augmentation methods with ensemble learning can significantly improve classification performance on imbalanced datasets. We find that traditional data augmentation methods such as the synthetic minority oversampling technique (SMOTE) and random oversampling (ROS) are not only better in performance for selected CI problems, but also computationally less expensive than GANs. Our study is vital for the development of novel models for handling imbalanced datasets

Supply chain finance: what are the challenges in the adoption of blockchain technology?

As an emerging information technology, blockchain has aroused extensive discussions around the world and been suggested as a solution to address current issues in supply chain finance (SCF). The Chinese government also attaches great importance to this technology, and many Chinese state-owned enterprises have invested in establishing their own blockchain research and development centres. However, there is a lack of studies on identifying challenges when deploying this technology; theoretical framework and conceptual exposition are also scarcely seen. Therefore, the aim of this study is to investigate the challenges and obstacles in the adoption of blockchain technology in SCF. An exploratory case study of a Chinese state-owned enterprise was conducted to build up an initial conceptual framework. Semi-structured interview was applied to collect data from the case firm's employees, top management, and technical specialists. The results of the analysis indicate that in the adoption of blockchain technology, there are technological, operational, and other challenges. From a technological perspective, framework identification, cross-chain interoperability, and data governance are major barriers; whereas, from an operational perspective, the new business process and transformation in the entire supply chain are identified as challenges. Besides, other obstacles such as the elimination of jobs and regulatory issues are also not neglectable. This study contributes to research on blockchain and supply chains by shedding light on the challenges of blockchain adoption through an exploratory case study of a Chinese state-owned enterprise. A conceptual framework was generated as a basis for future research, and the findings also provide insights for companies that may or are planning to adopt blockchain technology