{"title":"System Review: A Text Analysis on Supply Chain Finance","authors":"Chao-Chen Hsieh, Jun-Zhi Chiu","doi":"10.13189/ujm.2020.080201","DOIUrl":null,"url":null,"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.","PeriodicalId":211193,"journal":{"name":"Universal journal of management","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Universal journal of management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.13189/ujm.2020.080201","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.