Abstract

It may be intuitive to assume that the quality of issue corrective actions (iCA) for customers with mobile terminal (MT) issues can be improved by collecting samples of the faulty products in question for verifying the issues reported from the field. This study was created to test this hypothesis using three different established statistical analysis methods: binary logistic regression, Kruskal-Wallis statistical tests and Mood’s Median Test. The methods are used because the data collected from in-house database tool is categorical. In this study, these methods were employed to test if the presence or absence of corrective actions process (CAP) samples had any effect on the perceived quality of issue corrective actions (P-QoiCA) or any effect on the perceived quality of issue resolution time (P-QoiRT) for service to the customers. This study also examined the effect of the quality of the collected samples (QoSa) on the absolute issue resolution time (iRT). The study checked if the frequency of requests for samples differs between MT products of different software platforms (SW_P). Additionally the paper investigated how the sample collection turnaround time (SC-TAT) differed in different sales areas (SA). The main findings were that the collected samples had no measurable effect upon the P-QoiCA or on P-QoiRT.  Also it has been shown that QoSa and the SC-TAT had no effect on the absolute time (iRT) to resolve customers’ issues. In addition to the aforementioned findings, the study noted as an aside that the Moods’ median test found significant differences in iRT between different software platforms (SW_ P).

Key words: Corrective actions process (CAP)-samples, non-parametric tests, log-normal distribution, logistic regression, perceived quality.