Online group buying behavior: A study of experiential versus material purchases
Bibliographic record
Abstract
Abstract More than 50 million consumers participate in online group buying, hence its importance to retailers cannot be ignored. Four studies are conducted to determine (a) whether customers' preferences to participate in group buying relative to buying alone are more in the case of experiential (vs. material) purchases; (b) underlying psychological mechanisms affecting an individual's willingness to invite additional buyers; and (c) the moderating role of analytic versus holistic thinking orientation within the mediational framework. Consistent with expectations, preferences to invite additional buyers to receive a further discount (vs. buying alone and taking the deal‐of‐the‐day) were greater for experiential purchases than material purchases. Three psychological motivators, namely social relatedness, conversational value, and anticipatory enjoyment, act as parallel mediators. Finally, moderated‐mediation analysis shows holistic thinking accentuates the mediational pathway of anticipatory enjoyment but not for social relatedness, whereas analytical thinking accentuates the mediational pathway of conversational value. Of practical relevance to those designing group buying websites is that offering an additional discount to buyers if they are willing to expend the effort to form a larger group not only reduced the number of individuals indicating that they would not make a purchase at all, but about a quarter of respondents indicated that they would endeavor to find additional buyers. In addition, there is a clear preference for experiential goods; and for material goods, the findings suggest drawing attention to the experiences that material goods offer.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".