{"title":"服务质量:电信公司客户投诉数据应用程序","authors":"J. Achcar, Daniel Marcos Godoy","doi":"10.14807/IJMP.V12I4.1352","DOIUrl":null,"url":null,"abstract":"The evaluation of the service quality standard of a telecommunication company using statistical process control (SPC) methods is the main goal of this paper. The study used a dataset collected from January 2018 to November 2019 associated with monthly and weekly customer complaint counts due to the technical services provided by the company. Multiple linear regression models with the count data transformed to a logarithmic scale and Poisson regression models with the original count data detected some significant factors affecting the weekly/monthly complaint counts. In addition, forecasts of future complaint counts based on the statistical models could be of interest for the company to plan the number of technicians in different sectors at different times of the year leading to improvements in the service provided by the telephone company.","PeriodicalId":54124,"journal":{"name":"Independent Journal of Management & Production","volume":null,"pages":null},"PeriodicalIF":0.4000,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quality of services: an application with customer complaint data from a telecommunication company\",\"authors\":\"J. Achcar, Daniel Marcos Godoy\",\"doi\":\"10.14807/IJMP.V12I4.1352\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The evaluation of the service quality standard of a telecommunication company using statistical process control (SPC) methods is the main goal of this paper. The study used a dataset collected from January 2018 to November 2019 associated with monthly and weekly customer complaint counts due to the technical services provided by the company. Multiple linear regression models with the count data transformed to a logarithmic scale and Poisson regression models with the original count data detected some significant factors affecting the weekly/monthly complaint counts. In addition, forecasts of future complaint counts based on the statistical models could be of interest for the company to plan the number of technicians in different sectors at different times of the year leading to improvements in the service provided by the telephone company.\",\"PeriodicalId\":54124,\"journal\":{\"name\":\"Independent Journal of Management & Production\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2021-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Independent Journal of Management & Production\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14807/IJMP.V12I4.1352\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MANAGEMENT\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Independent Journal of Management & Production","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14807/IJMP.V12I4.1352","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MANAGEMENT","Score":null,"Total":0}
Quality of services: an application with customer complaint data from a telecommunication company
The evaluation of the service quality standard of a telecommunication company using statistical process control (SPC) methods is the main goal of this paper. The study used a dataset collected from January 2018 to November 2019 associated with monthly and weekly customer complaint counts due to the technical services provided by the company. Multiple linear regression models with the count data transformed to a logarithmic scale and Poisson regression models with the original count data detected some significant factors affecting the weekly/monthly complaint counts. In addition, forecasts of future complaint counts based on the statistical models could be of interest for the company to plan the number of technicians in different sectors at different times of the year leading to improvements in the service provided by the telephone company.