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Record W3123471466 · doi:10.3390/su13031352

Future Work Self and Employee Creativity: The Mediating Role of Informal Field-Based Learning for High Innovation Performance

2021· article· en· W3123471466 on OpenAlexaff
Qichao Zhang, Zhenzhong Ma, Long Ye, Ming Guo, Shuzhen Liu

Bibliographic record

VenueSustainability · 2021
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsUniversity of Windsor
FundersFundamental Research Funds for the Central Universities
KeywordsCreativityPersonalityPsychologyConsistency (knowledge bases)Knowledge managementValue (mathematics)Field (mathematics)Social psychologyComputer science

Abstract

fetched live from OpenAlex

In today’s highly uncertain environment, the value of creativity and innovation are increasingly critical. How individuals could improve their creativity and innovation performance has become the focus of attention. Future work self as an intrinsic motivation factor plays an important role in creativity and innovation. Based on the self-consistency theory, this study integrated proactive personality and informal field-based learning (IFBL) to explore the relationship between future work self and employee creativity to increase innovation performance. It used data from 201 R&D department employees in China’s high-tech companies. The results show that future work self has a positive effect on employee creativity and that IFBL mediates the relationship between future work self and employee creativity. This process is then positively moderated by a proactive personality. This study’s results help clarify the formation mechanism of creativity from the perspective of intrinsic motivation and indicate that future work self can drive individuals’ creativity and innovation efforts, especially under the consistency of self-concept, motivation and personality. This research also emphasizes the importance of IFBL in improving individual creativity and further organizational innovation performance. Implications for theory and management to help improve creativity and innovation performance are then discussed in detail.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.069
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.309
Teacher spread0.299 · 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

Citations24
Published2021
Admission routes1
Has abstractyes

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