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Record W2889520412 · doi:10.5267/j.msl.2018.8.002

The effect of organizational identification on job embeddedness: Evidence from new generation of rural migrant workers in China

2018· article· en· W2889520412 on OpenAlexvenueno aff
Tang Meirun, Jennie Soo Hooi Sin, Chuah Chin Wei

Bibliographic record

VenueManagement Science Letters · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsJob embeddednessEmbeddednessMigrant workersChinaIdentification (biology)Organizational identificationBusinessDemographic economicsJob satisfactionLabour economicsOrganizational commitmentPsychologyEconomic growthSocial psychologySociologyPolitical scienceEconomics

Abstract

fetched live from OpenAlex

The purpose of this paper was to examine the relationships among work overload (WO), compensation (COM), organizational identification (OI) and organization embeddedness (OE) in the context of manufacturing industry in China through social identity theory. A 37-item questionnaire was filled by 384 new generation of rural migrant workers. Data were examined through a two-stage of first-order of reflective model and second-order reflective-formative hierarchical model using PLS-SEM. The empirical results indicate that COM and OI positively and significantly predicted OE, while WO was found to have no direct effect on OE. In addition, COM positively and significantly was associated with OI, whereas WO affected OI, negatively. Further examination of the mediation effects of OI revealed that OI could fully mediate the relationship between WO and OE. Moreover, OI also had a partial mediator role in the relationship between COM and OE. The study concluded with several implications and recommendations for future research.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.348

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.013
GPT teacher head0.244
Teacher spread0.232 · 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

Citations12
Published2018
Admission routes1
Has abstractyes

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