Who Are Canada’s Green Consumers? A Corporate Social Responsibility-Driven Typology
Bibliographic record
Abstract
As consumers become more socially responsible, companies are increasingly compelled to strengthen their green marketing strategies. Corporate Social Responsibility (CSR) serves as an essential promotional tool to engage consumers and enhance brand image. Research on consumer responses to CSR initiatives remains limited despite their importance, which hinders a full understanding of the complexities of modern green-consumer behavior and the design of effective promotional strategies. This study uses cluster analysis to develop a CSR-driven consumer typology for Canada. Based on an online survey of 602 respondents, it identifies three consumer segments: indifferent, eco-conscious, and skeptical consumers. This study examines both sociodemographic and behavioral factors to profile these groups and finds that behavioral factors—loyalty, word of mouth, brand equity, and purchase intention—are more effective than demographic variables in characterizing modern green consumers. It proposes a new typology approach that expands socially responsible consumption beyond environmental concerns to include both environmental and social dimensions through CSR. This broader perspective enables companies to better align their CSR practices with consumers’ needs. These findings offer practical insights and suggest that developing CSR-based promotional strategies tailored to different consumer segments can enhance the impact of CSR initiatives, improve consumer engagement, and strengthen brand relationships.
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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 | 0.003 | 0.005 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".