Multi‐channel communication and consumer choice in the household furniture buying process
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
Purpose Furniture is among the important personal consumption expenditures for durable goods in the USA. Retailers and manufacturers offer different communication channels to assist consumers all through the process of acquiring furniture. The objective of the present study is to evaluate US consumers' channel use at different steps of the residential furniture‐buying process. Design/methodology/approach A cross‐section study was conducted by taking advantage of the structured nature of quantitative methods using a questionnaire for data collection and a socio‐demographic representative sample of US citizens. Consumers' use of six communication channels through five buying decision steps was assessed. Findings Results showed that the furniture retail store is the most important communication channel at each of the five considered buying process stages. Overall score of that channel was higher for females than males, indicating that women care more about communication when buying furniture. The internet was not of significant importance when buying furniture. Advertising was perceived as a significant means to gather information. Practical implications The study will help to orient companies' marketing strategies by making proper use of communication channels. It also shows marketing students the present state of consumers' communication channel preferences. Originality/value This paper gives unique insights into consumers' buying behavior that will help to design communication channels properly.
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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 | 0.004 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 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 it