A framework for encouraging retail customer feedback
Bibliographic record
Abstract
Purpose – The purpose of this study is to examine antecedents of the under researched area of customer feedback in a retail context with feedback defined as positive and negative comments as well as suggestions for product/service improvements. A market-oriented firm listens to customers and puts their feedback into practice. Research on customer engagement, which includes customer feedback, has recently surged. The preponderance of feedback research to date has been focused on customer complaint behavior which is negatively valenced. Much less attention has been paid to customer feedback (including sharing positive information, thoughts and suggestions for new ideas, in addition to negative information) even though it has great value for companies. This research addresses this gap by integrating literature on customer orientation and engagement and relationship marketing antecedents (social benefits) and outcomes (commitment) to better understand what retailers can do to encourage customer feedback through relationships with frontline employees. Design/methodology/approach – This study employs a cross-sectional, single retailer approach surveying 864 customers who have varying relationships to a coffee house. Findings – Conditional process analysis was used to test the hypothesized mediating and moderating relationships. Results were consistent with predictions, showing that retail employee customer-oriented behavior is mediated by customer social benefit perceptions to influence feedback. Further, social benefit perceptions will interact with the level of customer continuance commitment to impact feedback. Specifically, the impact of social benefits will be stronger when commitment to the retailer is higher. Originality/value – This research has academic and practical implications by increasing our understanding of an underrepresented and valuable aspect of engagement – customer feedback. Specifically, it addresses a key marketing research priority set forth in a 2010JSRspecial issue, calling for more work contributing to this topic. Also, this research implies managers have the ability to influence the amount of feedback that they receive by encouraging certain employee behaviors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.005 | 0.018 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".