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Record W2047673798 · doi:10.1108/ejm-04-2012-0207

E-relationship marketing: a cognitive mapping introspection in the banking sector

2014· article· en· W2047673798 on OpenAlexaff
Isabelle Brun‐Heath, Fabien Durif, Line Ricard

Bibliographic record

VenueEuropean Journal of Marketing · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsUniversité du Québec à MontréalUniversité de Moncton
Fundersnot available
KeywordsOriginalityMarketingUsabilityRelationship marketingQuality (philosophy)Exploratory researchIntrospectionCustomer satisfactionBusinessKnowledge managementPsychologyMarketing managementComputer scienceSociologyCreativitySocial psychology

Abstract

fetched live from OpenAlex

Purpose – The aim of this paper is to explore and better understand e-relationship marketing and to identify elements (key concepts) that are predominant to ensure success via the internet. Design/methodology/approach – The exploratory cognitive mapping technique (Cossette, 2004) employs three types of respondents, namely a banking expert, online banking customer and academic expert. Findings – The study points up similarities with traditional relationship marketing (e.g. satisfaction, commitment by bank) and identifies several new concepts spawned by the web-based environment. More precisely, the study highlights the importance of the simplicity and ease of the customer's web experience. Research limitations/implications – The exploratory and qualitative nature of this study opens the door to validation with a broader sample using a self-administered questionnaire developed based on the cognitive mapping technique. Practical implications – In addition to guaranteeing customer satisfaction, it is important: that customers perceive the bank's investment in and commitment to the e-relationship strategy; and, that customers enjoy a highly positive web experience (e.g. perceived quality of site and ease-of-use). Originality/value – Research findings result in an enhanced understanding of e-relationship marketing. Also, given the combination of sparse use of cognitive mapping in marketing and investigation of three different types of subjects (banking expert, online banking customer and academic expert), the findings lend originality while making a substantive theoretical contribution to topical literature.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.050
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0500.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.232
Teacher spread0.198 · 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 teacher head, not a consensus.

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

Citations43
Published2014
Admission routes1
Has abstractyes

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