Online Shopping Malls: Behavioral Impacts of Short- and Long-term 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
This study addresses how customers develop loyalty toward focal stores within an online shopping mall, and how this construct affects behavioral mall loyalty in both the short- and long-term. We employ a type II Tobit model to dynamically capture the short- and long-term impacts of store loyalty on purchase incidence and purchase amount. We further embed this model within a model of store loyalty formation to elucidate its driving factors. Applying the models to purchase history data of new customers in an online shopping mall, we observe that store loyalty has an immediate negative effect on purchase incidence; however, given a purchase, this variable increases the purchase amount in the long-term. Additionally, the formation of store loyalty appears to be significantly affected by gender, age, cumulative purchase amount, cumulative purchase frequency, and time trend. We discuss the implications of these findings for mall owners in an effort to increase revenue contribution of their tenants.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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