Monitoring negative sentiment scores and time between customer complaints via one-sided distribution-free EWMA schemes

Abstract

Customer complaints about a product or service can be evaluated using the sentiment intensity (S) and time interval (T) of negative reviews. Previous control chart-based research applied two-sided schemes to detect upward and downward shifts in S and T. However, managers are interested in shifts related to frequent and severe customer complaints. One-sided schemes focusing on specific shifts are preferable to traditional schemes focusing on all shifts. Therefore, we propose one-sided distribution-free exponentially weighted moving average (EWMA) schemes to detect these specific shifts, including the increase in S, the decrease in T, and the possible increase in the variability of either variable. We devise the schemes by combining the individual p-values of the modified Wilcoxon rank-sum and Mood test statistics. We provide detailed implementation steps and post-signal diagnostic plans. The proposed schemes can timely detect anomalies in customer complaints and diagnose the cause of variations. In the simulation study, the proposed schemes exhibit robustness under in-control cases and outperform the existing schemes under most out-of-control cases. Finally, we use JingDong (JD) laptop reviews to verify the effectiveness of the proposed method.