System Review: A Text Analysis on Supply Chain Finance

Chao-Chen Hsieh, Jun-Zhi Chiu
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引用次数: 2

Abstract

Supply chain finance (SCF) is dynamic approach in banks’ proprietary platform and is becoming more flexible and transparent through ingenious technological solutions of effectively integrating the flows of logistics and capital into the financial service provider industry. The paper aims to utilize the TF-IDF technique in order to make greater contributions to future SCF researches and discusses different scopes of SCF and their relation to roll out SCF solutions. In efforts to demonstrate the importance role that frequency-inverse document frequency (TF-IDF) plays in retrieving information using various keywords within various document (otherwise known as text mining), this study will attempt to showcase the research findings from more than 250 academic database which focuses on supply chain finance between seller and buyer. In presenting the two leading components that impact the analysis of text mining, namely the mechanism and technological innovation of SCF. Through systematic review of the SCF is concerned with financial liquidity and the viability of SCF, this research will analyze the keyword frequencies and assess the significance of terms (or words) within this document collection separately. Finally, this report explores possible solutions for future research based on the current framework and data analysis in order to achieve capital gain, sustainability and viable replenishments.
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系统回顾:供应链金融的文本分析
供应链金融(SCF)是银行专有平台中的动态方法,通过巧妙的技术解决方案将物流和资金流有效地整合到金融服务提供商行业中,从而变得更加灵活和透明。本文旨在利用TF-IDF技术为未来的SCF研究做出更大的贡献,并讨论了SCF的不同范围及其相互关系,以推出SCF解决方案。为了证明频率逆文档频率(TF-IDF)在使用各种文档中的各种关键字检索信息(也称为文本挖掘)中发挥的重要作用,本研究将尝试展示来自250多个学术数据库的研究成果,这些数据库侧重于卖方和买方之间的供应链金融。介绍了影响文本挖掘分析的两个主要组成部分,即文本挖掘的机制和技术创新。本研究将通过系统回顾SCF与金融流动性和SCF可行性的关系,分别分析该文献集中的关键词频率和评估术语(或词)的重要性。最后,本报告在现有框架和数据分析的基础上探讨未来研究的可能解决办法,以实现资本增值、可持续性和可行的补充。
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