Performance measurement of the complaint and failure management process
Performance measurement of the complaint and failure management process
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投诉和失败管理流程的绩效衡量
DOI：
10.1080/10686967.2019.1689801
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发表时间：
2020
影响因子：
--
通讯作者：
Robert H.
中科院分区：
文献类型：
--
作者：
Ruessmann;Maximilian;Hellebrandt;Thomas;Ulrich;Telpis;Rutten;Schmitt;Robert H.
在本文中，我们实证调查之间的联系，投诉和故障管理（CFM）过程的性能和其潜在的影响因素。与早期的文献相比，我们从整体上考虑CFM过程，而在过去，它只是部分集中（例如，客户关系管理）。我们有兴趣回答两个问题：（1）影响CFM过程性能的因素是什么？(2)CFM绩效指标的实施是否与CFM流程绩效正相关？首先，为了回答这些问题，我们概念化的结构理论上与CFM过程的性能和验证的测量工具。其次，我们进行了非参数相关性检验（斯皮尔曼），以调查的数据的基础上的结构之间的关系的调查研究77家公司。研究结果提供了经验证据，CFM绩效测量，数据导向和管理层的关注，积极影响CFM过程中的绩效。此外，我们将过程成熟度确定为性能改进的杠杆。在这方面，我们提供了一个CFM过程成熟度的措施，包括三个主要阶段：“数据收集和组织”，“故障评估和消除”和“实施和知识转移”。我们的分析表明，相关性研究结果高度依赖于公司规模，仅适用于员工超过1,000人的公司。
In this paper, we empirically investigate linkages between the performance of the complaint and failure management (CFM) process and its potentially influencing factors. In contrast with earlier literature, we consider the CFM process holistically, while in the past it was only partially in focus (e.g., customer relationship management). We are interested to answer two questions: (1) What factors influence CFM process performance? (2) Does the implementation of CFM performance measures correlate positively with CFM process performance? First, to answer these questions, we conceptualized constructs theoretically related to CFM process performance and validated the measurement instrument. Second, we carried out non-parametric tests of correlation (Spearman) to investigate relationships between the constructs based on the data of a survey study among 77 companies. The findings provide empirical evidence that CFM performance measurement, data orientation and management attention positively influence CFM process performance. Additionally, we identified process maturity as lever for performance improvements. In this regard, we provide a CFM process maturity measure consisting of three main phases: “data collection and organization”, “failure valuation and elimination” and “implementation and knowledge transfer”. Our analyses showed that correlation findings are highly dependent on company size and only hold for companies with more than 1,000 employees.