Quality of services: an application with customer complaint data from a telecommunication company

J. Achcar, Daniel Marcos Godoy
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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.
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服务质量:电信公司客户投诉数据应用程序
利用统计过程控制(SPC)方法对某电信公司的服务质量标准进行评价是本文的主要目的。该研究使用了2018年1月至2019年11月收集的数据集,这些数据集与该公司提供的技术服务引起的每月和每周客户投诉数量有关。将投诉数据转换为对数尺度的多元线性回归模型和原始投诉数据的泊松回归模型发现了影响周/月投诉数量的显著因素。此外,根据统计模型预测未来的投诉数量,可能对公司在一年中不同时间规划不同部门的技术人员人数有好处,从而改善电话公司提供的服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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