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Record W2886068993 · doi:10.1002/kpm.1585

Assessing the impact of customer knowledge management on organizational performance

2018· article· en· W2886068993 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueKnowledge and Process Management · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsWilfrid Laurier UniversityToronto Metropolitan University
Fundersnot available
KeywordsKnowledge managementBalanced scorecardCustomer knowledgeOrganizational performanceBusinessProcess (computing)Process managementPerformance measurementOrganizational learningOrganizational behavior managementComputer scienceOrganizational behavior and human resourcesCustomer advocacyMarketingService quality

Abstract

fetched live from OpenAlex

This study aims to discover how customer knowledge management (CKM) enhances organizational performance. For this purpose, a process‐oriented framework is developed to examine the relationship among organizational knowledge infrastructure, CKM processes, CKM capabilities, and organizational performance. Organizational knowledge infrastructure includes both “customer relationship management infrastructure” and “knowledge management infrastructures.” The balanced scorecard dimensions are used for measuring organizational performance. Based on process‐oriented approach, infrastructures enhance CKM capabilities through CKM processes and consequently improve firm performance. The research framework is evaluated by a questionnaire survey in 51 software companies in Iran. The empirical work indicated that constructed measures demonstrate the key psychometric properties including reliability and validity. The findings also demonstrate mediating role of CKM processes and CKM capabilities on the relationship between CKM and organizational performance. It means that firms with improved CKM process capabilities enjoy better organizational performance.

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.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.806
Threshold uncertainty score0.917

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.031
GPT teacher head0.382
Teacher spread0.351 · 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