Used Durables and Online Buying: An Attitudinal Study of Indian Youth
Bibliographic record
Abstract
The present paper is an empirical paper based on an online survey conducted in the first quarter of the year 2013. Preliminary findings were presented at an international conference in the last quarter of 2013, and changes were made based on suggestions received from the co-delegates. The study attempts to investigate the attitude, perception, and motivation of Indian youth, especially management students, regarding their adoption of a distinguished selling/ buying online platform for used laptops through a consumer to consumer discount e-commerce portal. With an exploratory research design, this paper uses multivariate analyses to draw perceptual mapping of the proposed portal vis-à-vis other e-commerce sites. It simulates a business model with an integrated value chain from acquisition and selling of used laptops at a discounted price to a value added after sales/ post purchase service in a committed manner. A focus group discussion was carried out initially among the sampling units from the sampling frame of a management college to understand the antecedents. Based on the findings, a questionnaire was developed and pre-tested through a survey design. Across its two stages, the research used both exploratory and descriptive design in sequence. The second part of the research helps in conceptualizing an optimum marketing mix, and explaining differentiation and positioning variables for the commercial launch of such a venture. However, the current paper discusses only the first part of the study.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".