Social responsibility and its differential effects on the retailers’ portfolio of private label brands
Bibliographic record
Abstract
Abstract Purpose The purpose of this paper is to explore how social responsibility initiatives can be integrated into different tiers of retailers' private label brands (PLB) and introduces a conceptual model and opposing predictions building on research in social responsibility and evolutionary psychology. The empirical evidence from two studies suggests that retailers should consider the type of PLB (i.e. quality tier) in the introduction of social responsibility initiatives. Design/methodology/approach To investigate opposing predictions, the authors conducted two experiments with presence of social responsibility initiative and PLB quality tier as the factors. The authors present the results from 168 Canadian consumers focussing on two product categories. Findings The findings of two experiments are more consistent with an explanation based on resource synergy beliefs rather than costly signaling theory. Social responsibility initiatives enhanced consumer evaluations of high-quality PLBs, but hurt consumer evaluations of low-tier PLBs. Practical implications Retailers should differentiate the way they accommodate social responsibility initiatives based on the type of their PLBs. Specifically, the beneficial effect of social responsibility initiative only exist for high-tier PLBs. Introducing social responsibility initiatives may hurt preference for low-tier PLBs. Originality/value This paper is the first to propose two theoretical models that address how social responsibility initiatives can affect consumer evaluations of PLBs. The initial empirical evidence is more coherent with resource synergy beliefs explanation rather than costly signaling explanation. These results suggest that social responsibility initiatives have asymmetric effects for different tiers of retailers' PLBs.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".