Investigating the Factors Influencing Parent Toy Purchase Decisions: Reasoning and Consequences
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
The purpose of this study is to explore and verify the main determinants of parent toy-choice decision-making by using a theoretical model for toy-selection decisions and exploring toy-purchasing behaviour empirically. After reviewing a large number of previous studies, this study’s model was developed and designed. A variety of determinants were identified and then categorized into six main broad categories, namely, purpose-of-using related factors, emotional-related factors, educational-related factors, cost-related factors as well as child and parent demographic-related factors. A quantitative methodology was adopted to test the study’s model by drawing on six hypotheses, which were then tested statistically. A self-administrative survey was developed to collect the preliminary data from customers (mainly parents) who had been involved in toy purchasing by applying the convenience sampling method. The study hypotheses were tested and the findings were also discussed in-depth.The study found that parent toy purchase decision id derived by a set of factors which are purposes of using-related factors, emotional-related factors, informational-related factors, cost-related factors, children demographical-related factors and parental demographical-related factors.
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.
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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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 it