The effect of publicity choice on economic and environmental performances in the context of trade-in
Bibliographic record
Abstract
In response to the government’s call for sustainable development, a number of companies have initiated trade-in programs, which aim to boost sales and promote product recycling. Typically, companies that offer trade-in adopt brand publicity or trade-in publicity. Although implementing such publicity strategies can increase costs for companies, they also have the potential to enhance the growth of related businesses. Thus, companies need to carefully consider the pros and cons of adopting such initiatives. This paper develops three theoretical models to analyze production and pricing issues associated with different publicity contents that a manufacturer may choose. The results show that (1) brand publicity can increase new product price and sales, while trade-in publicity can increase trade-in demand and new product sales, while decreasing trade-in rebate. Interestingly, brand publicity has a crossover effect on trade-in decisions by increasing trade-in rebate; (2) both brand publicity and trade-in publicity are beneficial to both the manufacturer and customers; (3) however, the adoption of higher levels of publicity content does not necessarily result in more environmentally friendly outcomes. In our extended analysis, we also demonstrate that our primary findings remain robust even when the analytical formulations of publicity costs vary.
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.
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 | 0.003 | 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 | 0.002 |
| 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 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".