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Record W2110439028 · doi:10.1093/jopart/muu034

Work-Group Knowledge Acquisition in Knowledge Intensive Public-Sector Organizations: An Exploratory Study

2014· article· en· W2110439028 on OpenAlexaff
Gregory Richards, Linda Duxbury

Bibliographic record

VenueJournal of Public Administration Research and Theory · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsCarleton UniversityUniversity of Ottawa
Fundersnot available
KeywordsKnowledge managementKnowledge value chainOrganizational learningPublic sectorKnowledge acquisitionPersonal knowledge managementPerceptionDomain knowledgeBody of knowledgeExplicit knowledgeRelevance (law)BusinessKnowledge surveyProcedural knowledgePsychologyComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Given that the performance of public-sector organizations is tied to the efficient use of knowledge, this exploratory study examined factors that influence knowledge acquisition by work groups in knowledge-intensive public-sector organizations. Based upon a review of the absorptive capacity and knowledge management literature, we defined knowledge acquisition as the change in the collective knowledge of groups over time. The amount of individual prior knowledge, and common knowledge among group members, managerial practices, and perceptions of knowledge applicability were identified as independent variables. Data were collected from 179 individuals representing 28 work groups in 7 public-sector organizations. Using multi-level regression, we found that homogeneity of knowledge at the group level and perceptions of knowledge applicability influenced acquisition, but that, contrary to much of the literature in this domain, prior-related knowledge did not have such an influence. Middle-management practices moderated the impact of knowledge applicability, suggesting that middle managers provide contextual information that permits group members to better understand the relevance of external knowledge. Implications for practice include the importance of training staff in teams to build homogeneity of knowledge, and ensuring that middle managers understand the organization’s strategy and their roles in the knowledge-utilization process. Implications for theory include the notion that prior knowledge can either encourage or obstruct knowledge acquisition. Dado que o desempenho de organizações do setor público é relacionado ao uso eficiente do conhecimento, este estudo exploratório examina fatores que influenciam a aquisição de conhecimento por grupos de trabalho em organizações do setor público de conhecimento intensivo. Com base em uma revisão da literatura sobre capacidade de absorção e conhecimento gerencial, nós definimos a aquisição de conhecimento como a mudança no conhecimento coletivo de grupos no decorrer do tempo. A quantidade de conhecimento individual prévio e o conhecimento comum entre os membros do grupo, das práticas gerenciais e percepções da aplicabilidade de conhecimento são identificadas como variáveis independentes. Os dados foram coletados de 179 indivíduos representando 28 grupos de trabalho em sete organizações do setor público. Utilizando regressão multinível, nós descobrimos que, no nível de grupo, a homogeneidade do conhecimento e as percepções da aplicabilidade deste conhecimento influenciam a aquisição, mas que, ao contrario de vasta literatura neste campo, prévio conhecimento não tem tanta influência. Práticas gerenciais de nível tático moderaram o impacto da aplicabilidade do conhecimento, sugerindo que gerentes médios fornecem informações contextuais que permitem aos membros do grupo um melhor entendimento da relevância de conhecimento externo. Implicações práticas incluem a importância do treinamento dos servidores em times para construir a homogeneidade do conhecimento e assegurar que os gerentes médios compreendam a estratégia organizacional e seus papéis no uso do conhecimento. Implicações teóricas incluem a noção de que conhecimento prévio pode tanto encorajar quanto obstruir a aquisição de conhecimento. Translated by Ricardo Gomes, University of Brasília

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0040.002
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.129
GPT teacher head0.410
Teacher spread0.281 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations59
Published2014
Admission routes1
Has abstractyes

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