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Record W1499655691 · doi:10.1108/bfj-01-2013-0003

Corporate philanthropy and channel impact in food security

2015· article· en· W1499655691 on OpenAlexaff
Sylvain Charlebois, Julia Hughes, Sebastian Hielm

Bibliographic record

VenueBritish Food Journal · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMarketingContext (archaeology)Argument (complex analysis)Product (mathematics)Exploratory researchChannel (broadcasting)BusinessFood marketingMarketing channelSociologyComputer science

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to discuss how corporate philanthropy influences channel behaviour in the context of food security. Design/methodology/approach – The authors chose an exploratory case-study design to guide the investigation, based on Yin’s (1994) argument that case studies are the preferred strategy when “how” or “why” questions are being posed, and when the focus is on a modern phenomenon within a real-life context. A survey study was focused on formal interviews onsite where product development and marketing occurred. Findings – It is known that the concepts of power and dependency are central to channel relationships. In food distribution, it has been argued that food distributors hold more power than food processors due to end-user proximity (Ruyteret al., 1996). For corporate altruism acts to have an impact when generated by functions other than distribution and retailing, one can only argue that channel members would require a significant number of antecedents to be successful. In Campbell’s case, as shown in Table I, many became enabling to a successful outcome while others arguably made the project more challenging. Research limitations/implications – With food security, the authors would need to consider other relationships within the marketing channel. The macro-environment of the marketing channel could also be incorporated in a future study. This study also does not compare other campaigns related to a similar product. In fact, it is believed that Nourish is unique in that it is the first ready-to-eat, ready-to-ship food product which was developed with the intent to serve the greater good. Practical implications – Philanthropic acts by one company can influence other channel members when intent is driven by clear altruistic and politically strategic motives, and reflects individualistic and paternalistic attitudes. Campbell’s was paternalistic but attempted to serve many causes at once. Committing to only one cause in the future may help consolidate resources and corporate energy around one single cause. Social implications – Corporate philanthropy describes the action when a corporation voluntarily donates a portion of its resources to a societal cause. Nourish’s case is different in that it is not just a linear transactional gift between a corporation and an organization actively involved in the cause. The project relies on the active participation of other channel members, including consumers, to support the campaign led by Campbell’s. It was a form of an extendable altruistic venture which allowed all channel members to contribute to the cause. Originality/value – Food processors that want to address the issue of food security or any other societal causes, domestically or abroad, will not cease. The challenge for food processors lies in the functional nature of their role within marketing channels. Since they do not transact with consumers directly, they depend on distributors and retailers to relay their philanthropic convictions to consumers. Based on the Nourish case, this study set out a series of antecedents which would support similar initiatives.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0060.003
Open science0.0000.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.000

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.

Opus teacher head0.064
GPT teacher head0.270
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2015
Admission routes1
Has abstractyes

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