University business students' perceptions of retail shopping behaviour
Bibliographic record
Abstract
Purpose Retail shopping behaviour is one of the major tenets of the retail marketing literature. The purpose of this research is to presents the empirical findings of two quantitative studies of Estonian and Canadian university students' interpretation and perceptions of retail shopping behaviour. Design/methodology/approach Paper and pencil questionnaires administered in Estonia and Canada. The data was analysed from two perspectives. The first was to determine if the retail service quality construct differed between the two samples, and secondly to use using confirmatory factor analysis, and regression analysis to test a model of shopping behaviour and to make comparisons between the shopping behaviour of university students in the two countries. Findings The results indicate a level of commonality in retail shopping perceptions, as well as non‐trivial differences in how shopping practice in terms of the construct structure, and individual service drivers, should be theorized. The Canadian sample indicated a greater focus on retail service quality perception at the sub‐dimension level while the Estonian sample indicated a greater focus on retail service quality at an overall or integrated level. Research limitations/implications The findings are limited as to the consumer type (university students) selected. This limitation is lessened as the university age sector represents one of the most dynamic and growing segments of the Estonian retail market. Practical implications Retail sales per capita within Estonia, and the other Baltic states, represents the fastest growing region in the European Union. Thus, there is a need for empirical and academic research that attempts to highlight the transferable (i.e. western) and the solely domestic consumer knowledge that will allow this growth to continue. Caution needs to be taken when simply implementing best retail practices from the West as erroneous conclusions may be drawn. It may not be the practices from the West that are fuelling the retail success, and thus research such as this helps to draw attention to the need to understand the more sustainable localized nature of retail shopping behaviour. Originality/value This paper represents an initial focus on an unknown area of retailing research.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".