CSR types and the moderating role of corporate competence
Bibliographic record
Abstract
Purpose This paper aims to investigate the impact of different types of corporate social responsibility (CSR; i.e. value-creating CSR, promotional CSR and philanthropic CSR) on consumer responses and the moderating role of corporate competence. Design/methodology/approach The authors tested the hypotheses by using two empirical studies – a survey and an experimental study. The evidence is generated based on generalized linear model repeated-measures ANOVAs for the survey study and two-way factorial ANOVAs for the experimental study. Findings The findings show that in general, consumers respond to value-creating CSR more favorably than to philanthropic CSR or promotional CSR. In addition, corporate competence moderates consumers’ responses to different types of CSR in such a way that promotional CSR is more likely to have the desired effects when carried out by low-competency rather than by high-competency firms, whereas value-creating CSR is more effective for high-competency firms than for low-competency ones. Philanthropic CSR works equally in both types of firms. Research limitations/implications This research answers a long-term call to study the differential consumer effects of various CSR types. It also identifies perceived corporate competence, an important consumer-based corporate factor, as a potential moderator of consumers’ response to CSR types. Practical implications Armed with the findings, companies can choose CSR practices that fit with their company characteristics. This research offers important and specific managerial implications to firms with different company profiles on their CSR choices. Originality/value Given that today’s managers are faced with the challenge of selecting desirable CSR activities from a group of options, the authors answered the call by studying the differential effects of a wide array of CSR choices and provide important practical guidance to managers. For the first time in the literature, the study also investigates the potential interactive effects between specific CSR types and corporate competence on consumer reactions. This inquiry bears significant relevance to the ongoing discussions concerning whether and how company characteristics generate influences on the outcomes of CSR strategies.
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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 | 0.009 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".