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Measure What Matters: A Dual Outcome Service Quality Model for Government Service Delivery

机译:衡量问题:政府服务提供的双重结果服务质量模型

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Measuring customer service quality evaluations has been important since the rise of the service industry and many models in this area have been published. Most models focus on one outcome with a set of predictors. These outcomes are often ill defined and concepts are used interchangeably causing issues in creating good and consistent measures of quality. In this study we develop a new model combining multiple outcome variables and a series of predictors to show the interdependent nature of service outcomes. We test the model using machine learning based on survey responses from 3702 Dutch people. The results indicate that two types of outcome variables are important; quality of the outcome and satisfaction with the process. Each is predicted in different ways by four dimensions. This means governments could benefit from a better specification of the desired outcomes of service delivery and targeted measurement approaches.
机译:自服务行业兴起以来,衡量客户服务质量评估就变得非常重要,并且已经发布了该领域的许多模型。大多数模型集中于一组预测因素的一个结果。这些结果通常定义不清,概念可互换使用,从而导致在创建良好且一致的质量度量标准方面出现问题。在这项研究中,我们开发了一个新模型,该模型结合了多个结果变量和一系列预测变量,以显示服务结果的相互依赖性。我们基于来自3702位荷兰人的调查回复,使用机器学习对模型进行了测试。结果表明,两种类型的结果变量很重要。结果的质量和对过程的满意度。通过四个维度以不同的方式预测每一个。这意味着政府可以从对服务交付的预期结果和目标衡量方法的更好规范中受益。

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