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Record W3157239021 · doi:10.1108/jocm-08-2020-0237

Influence of knowledge sharing, innovation passion and absorptive capacity on innovation behaviour in China

2021· article· en· W3157239021 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

VenueJournal of Organizational Change Management · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsMcMaster University
Fundersnot available
KeywordsAbsorptive capacityPassionKnowledge sharingKnowledge managementStructural equation modelingBusinessAntecedent (behavioral psychology)MarketingPsychologySocial psychologyComputer science

Abstract

fetched live from OpenAlex

Purpose This paper aims to address the question of what can significantly impact employees' IB and how employees' IB may be effectively stimulated by investigating key factors such as employees' knowledge sharing, innovation passion, absorptive capacity and risk-taking behaviour on workplace innovation. The moderating role of risk-taking behaviour on the link between absorptive capacity and innovation behaviour is also investigated. Design/methodology/approach Based on the principles of social exchange theory, the study design explores the complex relationship among knowledge sharing, innovation passion, absorptive capacity and risk-taking vis-à-vis employees' innovation behaviour within a unified analysis framework. Methodologically, employees in the information technology industry in China were surveyed via a questionnaire instrument, with a total of 318 valid questionnaires being collected online. Following a reliability and validity test of the questionnaire, the Smart PLS was used to verify the research model. Findings Statistically significant results reported were as follows: (1) employees' innovation behaviour is positively impacted by knowledge sharing, innovation passion and absorptive capacity; (2) employees' innovation behaviour is negatively impacted by risk-taking behaviour; (3) knowledge sharing is positively impacted by innovation passion; (4) absorptive capacity is positively impacted by innovation passion; and (5) risk-taking behaviour regulates the relationship between absorptive capacity and innovation behaviour. Research limitations/implications Owing to limited research resources, 318 front-line employees were surveyed via an online questionnaire vis-à-vis the sampling method only, specifically taking knowledge sharing, innovation passion, absorptive capacity and risk-taking behaviour as antecedent variables with implications on how employees' innovation behaviour may be stimulated. Originality/value The mechanism of augmenting employees' innovation behaviour is chiefly explained from the perspective of innovation passion and risk-taking behaviour, which are conducive towards promoting employees' willingness to improve knowledge sharing and innovation behaviour. The social exchange theory is used as a basis to form an integrated model for the research, contributing to a cumulative theoretical perspective for future work on the impact of innovation passion and risk-taking behaviour on innovation.

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: Empirical
Teacher disagreement score0.654
Threshold uncertainty score0.376

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
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 head0.050
GPT teacher head0.306
Teacher spread0.257 · 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