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Record W2539265796 · doi:10.1002/joe.21757

Addressing Differences Between Inbound and Outbound Agents for Effective Call Center Management

2016· article· en· W2539265796 on OpenAlexaboutno aff
Saïd Echchakoui

Bibliographic record

VenueGlobal Business and Organizational Excellence · 2016
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsOpenness to experienceConscientiousnessIdentification (biology)BusinessCenter (category theory)Big Five personality traitsOrganizational identificationAssessment centerPersonalityPsychologyMarketingSocial psychologyApplied psychologyOrganizational commitmentExtraversion and introversion

Abstract

fetched live from OpenAlex

To contribute to the management of blended call centers, researchers explored the moderating effects of personality traits and organizational identification on the turnover intention of inbound and outbound agents in a Canadian call center. The results reveal that the level of organizational identification among inbound agents is lower than it is among outbound agents. Contrary to previous research, however, turnover intention among inbound employees was found to be lower than that among outbound employees. The results also illustrate that openness to experience, which serves to reduce turnover intention, is a trait common to both types of call center agents. The finding that two personality traits—conscientiousness and emotional stability—have a positive impact on organizational identification for both inbound and outbound call center agents can be used to improve recruitment selection processes at call centers of all types.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.082
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.056
GPT teacher head0.335
Teacher spread0.280 · 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

Citations9
Published2016
Admission routes1
Has abstractyes

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