scholarly journals Supply Chain Finance for Targeted Poverty Alleviation: A Case Study of Suning

2020 ◽  
Author(s):  
Shanliang Li ◽  
Shan Yan ◽  
Liwen Liu
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Traffic Control ◽  
Poverty Alleviation ◽  
Economic Benefits ◽  
Agricultural Product ◽  
Financial Measures ◽  
Supply Chain Finance ◽  
Agricultural Supply

The sudden emergence of ‘COVID-19’ in 2020 has tightened traffic control in various places, which has posed a huge challenge to the agricultural product supply chain. This research introduces the perspective of supply chain finance, uses in-depth case study methods, and takes Suning’s agricultural supply chain finance as an example to discuss how e-commerce companies relying on big data adopt agricultural supply chain finance practices to promote accurate poverty alleviation. By analyzing Suning’s four agricultural supply chain financial operation models, we find that the internal and external stakeholders of the enterprise are the driving factors for enterprises to adopt agricultural supply chain finance, and the adoption of agricultural supply chain finance measures has brought economic benefits and social benefits to enterprises benefit. Advanced big data tools, fintech and cooperation with other partners are necessary to adopt agricultural supply chain financial measures.

scholarly journals Measuring the Environmental Maturity of the Supply Chain Finance: A Big Data-Based Multi-Criteria Perspective

Logistics ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 22
Author(s):  
Hisham Alidrisi
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Multicriteria Decision Making ◽  
Analytic Network Process ◽  
Assessment Model ◽  
Self Assessment ◽  
Interpretive Structural Modeling ◽  
Supply Chain Finance ◽  
Network Process ◽  
Order Preference

This paper presents a strategic roadmap to handle the issue of resource allocation among the green supply chain management (GSCM) practices. This complex issue for supply chain stakeholders highlights the need for the application of supply chain finance (SCF). This paper proposes the five Vs of big data (value, volume, velocity, variety, and veracity) as a platform for determining the role of GSCM practices in improving SCF implementation. The fuzzy analytic network process (ANP) was employed to prioritize the five Vs by their roles in SCF. The fuzzy technique for order preference by similarity to ideal solution (TOPSIS) was then applied to evaluate GSCM practices on the basis of the five Vs. In addition, interpretive structural modeling (ISM) was used to visualize the optimum implementation of the GSCM practices. The outcome is a hybrid self-assessment model that measures the environmental maturity of SCF by the coherent application of three multicriteria decision-making techniques. The development of the Basic Readiness Index (BRI), Relative Readiness Index (RRI), and Strategic Matrix Tool (SMT) creates the potential for further improvements through the integration of the RRI scores and ISM results. This hybrid model presents a practical tool for decision-makers.

scholarly journals Hydrological Layered Dialysis Research on Supply Chain Financial Risk Prediction under Big Data Scenario

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Jia Liu ◽  
Shiyong Li ◽  
Xiaoxia Zhu
Keyword(s):  
Risk Management ◽  
Big Data ◽  
Supply Chain ◽  
Risk Analysis ◽  
Risk Prediction ◽  
Financial Institutions ◽  
Surface Runoff ◽  
Financial Risk ◽  
Supply Chain Finance ◽  
Runoff Model

In recent years, internet development provides new channels and opportunities for small- and middle-sized enterprises’ (SMEs) financing. Supply chain finance is a hot topic in theoretical and practical circles. Financial institutions transform materialized capital flows into online data under big data scenario, which provides networked, precise, and computerized financial services for SMEs in the supply chain. By drawing on the risk management theory in economics and the distributed hydrological model in hydrology, this paper presents a supply chain financial risk prediction method under big data. First, we build a “hydrological database” used for the risk analysis of supply chain financing under big data. Second, we construct the risk identification models of “water circle model,” “surface runoff model,” and “underground runoff model” and carry on the risk prediction from the overall level (water circle). Finally, we launch the supply chain financial risk analysis from breadth level (surface runoff) and depth level (underground runoff); moreover, we integrate the analysis results and make financial decisions. The results can enrich the research on risk management of supply chain finance and provide feasible and effective risk prediction methods and suggestions for financial institutions.

scholarly journals THE INFLUENCE OF SUPPLIER FAIRNESS PERCEPTION AND TRUST ON THE RELATIONSHIP QUALITY OF AGRICULTURAL PRODUCT SUPPLY CHAIN

2021 ◽  
Author(s):  
YU-LING SUN ◽  
ZE-YU ZHU ◽  
HUI YANG
Keyword(s):  
Supply Chain ◽  
Relationship Quality ◽  
Positive Impact ◽  
Agricultural Product ◽  
Direct Impact ◽  
Fairness Perception ◽  
Supply Chain Relationships ◽  
The Relationship ◽  
Agricultural Supply

Suppliers are important members of the agricultural product supply chain, and their behavior decisions may have a certain impact on the sustainable development of the agricultural product supply chain. From the perspective of agricultural product supplier trust, this paper studies the direct impact of agricultural product supplier trust on relationship quality and the indirect impact of supplier fairness perception on relationship quality. Based on the survey data of agricultural product suppliers, this paper uses the structural equation model method for empirical analysis. The analysis results show that fairness perception and trust perception have a significant positive impact on the quality of agricultural supply chain relationships, among which trust perception has a positive direct impact on the quality of agricultural supply chain relationships, while fairness perception has indirect influence on the quality of agricultural supply chain relationships through trust. In addition, information sharing, price satisfaction, income level and environmental certainty have a significant positive impact on suppliers’ fairness perception. Therefore, sellers comprehensively consider the fairness perception and trust perception of suppliers, which will help improve the relationship quality of the supply chain.

Operational decisions and game analysis in the agricultural supply chain: invest or not?

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Qinyi Zhang ◽  
Wen Cao ◽  
Zhichao Zhang
Keyword(s):  
Supply Chain ◽  
Agricultural Products ◽  
Price Sensitivity ◽  
Agricultural Product ◽  
Sales Volume ◽  
Product Price ◽  
Content Type ◽  
Game Analysis ◽  
Preservation Technology ◽  
Agricultural Supply

PurposeWith the rapid growth of the economy, people have increasingly higher living standards, and although people simply pursued material wealth in the past, they now pay more attention to material quality and safety and environmental protection. This paper discusses the lack of motivation for investing in fresh-keeping technology for agricultural products by individual members of an agricultural supply chain composed of a supplier and a retailer by means of mathematical models and data simulations and discuss the optimal price-invest strategies under different sales models.Design/methodology/approachFirst, based on the model of no investment by both sides (NN), this paper considers three models: supplier only (MN), retailer only (NR) and cooperative investment (MR). Then, the authors analyze the influence of consumer price sensitivity and freshness sensitivity on the investment motivation of agricultural products under four models. Subsequently, the paper makes a sensitivity analysis of the optimal strategies under several models, and makes a game analysis of the suppliers and retailers of agricultural products. Finally, we conduct an empirical analysis through specific values.FindingsThe results show that (a) when the two sides cooperate, the amount of investment is largest, the freshness of the agricultural products is highest, and the sales volume is greatest; however, when both sides do not invest, the freshness of agricultural products and sales volume are lowest. (b) The price and freshness sensitivity of the consumer have an impact on investment decisions. Greater freshness sensitivity corresponds to a higher investment, higher agricultural product price, greater sales volume, and greater supply chain member income and overall income; however, greater price sensitivity corresponds to a lower investment, lower agricultural product price, lower sales volume, fewer supply chain members and lower overall income. (c) The investment game between the supplier and retailer is not only related to the sensitivity to price and freshness but also to the coordination coefficients of interest. At the same time, the market position of agricultural products should be considered when making decisions. The market share of agricultural products will affect the final game equilibrium and then affect the final benefit of the supply chain and individual members.Practical implicationsThese results provide managerial insights for enterprises preparing to invest in agricultural products preservation technology.Originality/valueAt present, the main problem is that member enterprises of agricultural supply chains operate based on their own benefits and are resistant to investing alone to improve the freshness of agricultural products. Instead, they would prefer that other members invest so that they may reap the benefits at no cost. Therefore, the enterprises in each node of the agricultural product supply chain are not motivated enough to invest, and competition and game states are observed among them, and such behavior is definitely not conducive to improving the freshness of agricultural products. However, the current research on agricultural products is more about price, quality and greenness, etc., and there are few studies on agricultural investment. Through the establishment of the model, this paper is expected to provide theoretical suggestions for the supply chain enterprises that plan to invest in agricultural products preservation technology.

scholarly journals Analysis on Internet Financial Business and Construction of Credit System

2020 ◽  
Vol 3 (2) ◽  
Author(s):  
Anzhi Yang
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Evaluation System ◽  
Mobile Internet ◽  
The Internet ◽  
Credit Evaluation ◽  
Supply Chain Finance ◽  
Industrial Chain ◽  
Internet Finance ◽  
Credit Evaluation System

Internet finance is a new emerging financial model, using the Internet as a platform, big data and cloud computing as the basis. Supply Chain Finance is the easiest way to enter Internet finance. The third-party companies or institutions can invest in Internet financial companies by integrating their industrial chain practices into designing the financial products to reduce credit costs and improve safety. At the same time, it will increase mobile Internet, big data and operational services. Also, it can make full use of the Internet financial platform to provide value-added services for higher and lower enterprise and consolidate the core status of the company in the industrial chain. However, an important issue that needs to be concerned during developing Supply Chain Finance is the construction of a system for credit evaluation. Due to the lack of a unified credit evaluation system, the development of the existing Supply Chain Financial companies suffers from difficulties. Many newly launched companies have difficulties operating due to the lack of a credit evaluation system. Therefore, proper and effective credit indicators are essential for the development of enterprises under Internet finance. From the micro perspective, it is conducive for enterprises to improve their credit under the constraints of indicators, and it can solve the problem of capital raising; from the macro perspective, it is conducive to the standardized development of China’s Internet finance and promotes the comprehensive economic development. Based on this, analyzing the model of Internet financial business and developing an enterprise’s credit index system is beneficial to the development of China’s Internet finance.

Sign in / Sign up

Export Citation Format

Share Document