Drivers of Impulse Buying at Retail Stores: Mediating Role of Customers’ Loyalty
Bibliographic record
Abstract
The major objective of this study was to examine the impact of drivers of impulse buying on the customers’ loyalty and to assess the mediating effect of customers’ loyalty to the impulse buying at the retail stores. In order to meet the objective, a questionnaire survey was conducted among 529 customers of retail stores. SMARTPLS3 was used to analyze the data collected from the survey. Findings suggest that CSR, store attractiveness and trust positively contribute to create loyalty of retailers and it positively impact on impulse buying at stores. The model tested in this study was significant and can be used by retailers to enjoy competitive advantage. Further, it was found that loyalty is mediating between these drivers of impulse buying and impulse buying. While loyalty positively mediating between all variables, loyalty negatively mediates between commitment and impulse buying. The model tested in this study is significant and useful for retailers to create loyalty and trigger impulse buying enabling to achieve competitive advantage in retailing. When retailers adopt this model in their business, retailers can establish loyalty and generate impulse buying. Therefore, retailers need to build up trust among customers, engaging in CSR activities, keeping their stores very attractive and having long term relationship to create commitment with customers.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".