What drives customer engagement after a service failure? The moderating role of customer trust
Bibliographic record
Abstract
Abstract This study investigated the relationships between complaint handling, customer experience, and customer engagement, as well as the moderating effect of customer trust prior to a service failure. The results were obtained from 320 Indonesian consumers of courier, express, and parcel services. Favourable employee behaviour was found to be the most effective complaint handling effort that influenced customer experience, followed by organizational procedures and then compensation, indicating that positive customer experience led to customer engagement. Additionally, this study revealed that higher levels of customer trust prior to a service failure reduced the positive effects of complaint handling efforts on customer experience. This finding suggests that customers with higher levels of trust in a firm are less sensitive to that firm's complaint handling and recovery efforts. This article contributes to the literature on customer engagement in the service failure and recovery contexts, especially in developing countries. It examines the most influential complaint handling dimensions for predicting customer engagement following service failures. Furthermore, this study is one of the first to explore the moderating role of customer trust in service failure and recovery literature.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".