Comparison of Incentive Strategies on the Buyer’s Decision-making Process Using PLS-SEM Approach
Bibliographic record
Abstract
This study examined the comparison of different formats of displaying external reference prices while the customer has time constraints throughout the purchasing procedure and a plethora of product involvement. In addition, it investigates the crucial effect of external reference price, time pressure, and product involvement on the customers’ willingness to purchase and their decision-making. The study’s statistical population is the students in one of Iran’s Universities. Data was collected through questionnaires and online. Data was analyzed using Smart-PLS and SPSS software. The study’s results illustrated that the percentage of external reference prices for the general display format significantly impacted the buyer’s decision-making process more than other external reference price formations. In addition, based on the outcomes, external reference price significantly influences product involvement and time constraints. The study showed that gender does not impact time pressure and product involvement. However, another approach has been used to prove this otherwise. Moreover, the study postulates that emotional intelligence may have an intermediary effect during the interaction between the external reference price and product involvement.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".