Where do customer loyalties really lie, and why? Gender differences in store loyalty
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose The purpose of this paper is to examine gender differences in store loyalty and how those differences evolve with age. Design/methodology/approach Data for the study were collected in a survey of 32,054 shoppers in more than 50 grocery stores belonging to the same chain. In total, 20 satisfaction items were factor-analysed, resulting in four satisfaction factors. A logistic regression with store exclusivity as the dependent variable was then run to test the research hypotheses. Findings This study finds that men are more loyal than women to the store chain, while women are more loyal than men to individual stores. Women’s loyalty is more influenced by their satisfaction with interaction with store employees, while for men loyalty is more influenced by satisfaction with impersonal dimensions. Store loyalty increases with age, an effect that cannot be explained solely by declining mobility and cognitive impairment. Research limitations/implications This research examines declared behavioural practices rather than actual behaviour. However, in view of the high frequency of purchases in the retail category examined, and also because of the large sample of over 50 different stores, declared practices should be highly correlated with actual behaviour. Practical implications Results from satisfaction surveys should be interpreted differently for men and women. Loyalty programmes may want to adapt their approach, to incorporate gender differences into their loyalty reinforcing measures. Social implications This paper should also help to a better understanding of loyalty programs for both men and women, younger and older people. Originality/value This is the first demonstration from an in store customer survey that the shopping experience drives store loyalty differently for men and women.
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.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 it