A study of non-profit organisations in cause-related marketing
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 – Cause-related marketing (CRM) involves firms working in partnership with non-profit organizations (NPOs). While CRM offers a range of potential benefits to NPOs, some managers are reluctant to partake in these ventures. The purpose of this paper is to uncover their concerns and highlight what can be done to improve their experience of CRM. Design/methodology/approach – This paper uses semi-structured interviews with 160 UK NPO managers and a stakeholder theory framework to document their experience of the CRM process and investigate what they can do to improve it. Findings – It identifies three types of concerns relating to issues of: organizational identity, alliance risks, and the prioritization of NPO stakeholders. The analyses also uncover a number of strategies used by NPO managers to safeguard their organisations. Research limitations/implications – By focusing not only on the measurable outcomes of CRM but also on its processes, the authors provide a more thorough analysis of CRM and its impact on NPOs. Practical implications – By emphasizing potential NPO stakeholder dissent, the authors' study provides a list of pitfalls that may help NPO managers select more suitable corporate partners, come better prepared to the negotiation table, improve the selection and training of negotiators, and generally manage the CRM process more efficiently. Originality/value – Studies of CRM have been predominantly from the corporate perspective. Consequently, the understanding of CRM from an NPO viewpoint remains limited both theoretically and empirically. The authors' paper complements this literature by investigating NPO managers' concerns about the process of CRM.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.028 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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