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Record W2019076574 · doi:10.1108/02652321211195695

The effect of behavioural activation and inhibition on CRM adoption

2012· article· en· W2019076574 on OpenAlexaff
Joseph Vella, Albert Caruana, Leyland Pitt

Bibliographic record

VenueInternational Journal of Bank Marketing · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsOriginalityCustomer relationship managementBusinessMarketingValue (mathematics)PersonalityKnowledge managementPsychologyComputer scienceSocial psychology

Abstract

fetched live from OpenAlex

Purpose This paper seeks to examine the effect of behavioural inhibition and behavioural activation systems on users' intention to adopt customer relationship management (CRM) applications. Design/methodology/approach Data for this study were collected from among managers of a major player in the community banking sector within the European Union. A total of 274 valid responses were obtained from 398 managers. Findings The results indicate that individuals with different combinations of BIS‐BAS levels demonstrate varying degrees of willingness in adopting and contributing towards the CRM system. Practical implications These results can be useful for human resources managers, who can screen individuals for positions requiring customer interface and effective use of CRM systems. The need to align employees' characteristics with CRM goals and strategies is critical to the successful application of CRM systems but has often not been given sufficient attention. Originality/value This paper demonstrates that individual behaviour can be attributed to different personality traits, which in turn can be traced back to physiological as well as psychological origins.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.194
Threshold uncertainty score0.201

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.262
Teacher spread0.241 · 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.

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

Citations12
Published2012
Admission routes1
Has abstractyes

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