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Record W2740354948 · doi:10.1504/ijima.2017.10006732

CSR and CRM: the impact on purchase intentions

2017· article· en· W2740354948 on OpenAlexaff
Jeffrey Overall

Bibliographic record

VenueInternational Journal of Internet Marketing and Advertising · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsNipissing University
Fundersnot available
KeywordsWord of mouthMarketingAdvertisingBusinessQuality (philosophy)Consumer behaviourControl (management)Corporate social responsibilityPsychologyPublic relationsEconomics

Abstract

fetched live from OpenAlex

Positive word-of-mouth, trust, and satisfaction are important antecedents to consumer purchase intentions. However, the social responsibility activities and the focus of an organisation on their long-term success are also important antecedents of consumer purchase intentions, whereas aggressive attempts to control the decisions of others are not. From this, it appears that each of these theories separately explains a portion of consumer purchase intentions, but, put together, they provide a more holistic account of the process. To understand how each of these influences consumer purchase intentions, QCA is used to analyse data collected from 29 randomly selected companies from the 2013 Fortune 500 List. The core causal conditions that lead to consumer purchase intentions involve the presence of: long-term success, perceived social responsibility, word-of-mouth, satisfaction, and the absence of influence attempts. I contribute to theory by challenging the relationship quality literature by demonstrating that trust does not influence consumer purchase intentions.

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)0.002
metaresearch head score (Gemma)0.009
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 score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.021
GPT teacher head0.305
Teacher spread0.284 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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