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Record W4388108404 · doi:10.5267/j.ijdns.2023.10.005

The impact of digitized customer behaviors on performance: The mediating and the moderating role of digitized CRM

2023· article· en· W4388108404 on OpenAlexvenueno aff
Sura I. Al-Ayed, Ahmad Adnan Al-Tit

Bibliographic record

VenueInternational Journal of Data and Network Science · 2023
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
FundersQassim University
KeywordsExtant taxonCustomer relationship managementModerationBusinessMarketingLift (data mining)Sample (material)PsychologyKnowledge managementComputer scienceSocial psychologyData mining

Abstract

fetched live from OpenAlex

The aim of this study is to explore the effect of digitized customer behavior on performance in the presence of digitized CRM as a mediating and a moderating variable. Research data was gathered using an online questionnaire completed by a convenience sample of marketing employees in service companies. The questionnaire was designed using a five-point Liker scale. The results showed that digitized customer behavior had a significant effect on performance, digitized CRM played a significant mediating role between digitized customer behavior and performance while had no significant moderating part in such an effect. Consequently, it was concluded that for companies to lift their performance, a digitized CRM program is a key prerequisite. This study contributes to the extant literature through highlighting the importance of digitized CRM for performance enhancement. Scholars and practitioners are required to consider the effects of digitized CRM on organizational outcomes.

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)0.002
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.749
Threshold uncertainty score0.429

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.001
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 head0.017
GPT teacher head0.303
Teacher spread0.286 · 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 designSimulation or modeling
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

Citations15
Published2023
Admission routes1
Has abstractyes

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