{"title":"Financing Efficiency Calculation of Energy Enterprises Based on Internet of Things","authors":"Jingjing Wu, Yajuan Zhang","doi":"10.1155/2022/7262788","DOIUrl":null,"url":null,"abstract":"In order to conduct a special study on the financing efficiency of a certain industry, the authors propose a method for calculating the financing efficiency of energy enterprises based on the Internet of Things. Combining the DEA method with the Bootstrap method, taking the IoT data of 30 SME boards and 30 energy companies listed on the ChiNext listed in 2010 as a research sample, and using R language and Deap2.1 software, the financing efficiency from 2011 to 2015 is calculated. Experimental results show that from 2011 to 2015, only 28.3% of the enterprises reached the effective state of technical efficiency on average, and the financing efficiency of energy enterprises was generally inefficient. The pure technical efficiency value of the whole enterprise decreases year by year, and its technical efficiency value lower than its scale efficiency is the main reason that its technical efficiency is generally not high.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"7 1","pages":"1-8"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"J. Sensors","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2022/7262788","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In order to conduct a special study on the financing efficiency of a certain industry, the authors propose a method for calculating the financing efficiency of energy enterprises based on the Internet of Things. Combining the DEA method with the Bootstrap method, taking the IoT data of 30 SME boards and 30 energy companies listed on the ChiNext listed in 2010 as a research sample, and using R language and Deap2.1 software, the financing efficiency from 2011 to 2015 is calculated. Experimental results show that from 2011 to 2015, only 28.3% of the enterprises reached the effective state of technical efficiency on average, and the financing efficiency of energy enterprises was generally inefficient. The pure technical efficiency value of the whole enterprise decreases year by year, and its technical efficiency value lower than its scale efficiency is the main reason that its technical efficiency is generally not high.