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Record W4396773436 · doi:10.26784/sbir.v8i1.611

The reciprocity of perceived organizational support and employee engagement in SMEs during the COVID-19 pandemic

2024· article· en· W4396773436 on OpenAlexfundno aff
Vera Ferrón‐Vílchez, María Eugenia Senise Barrio, Rocío Llamas Sánchez

Bibliographic record

VenueSmall Business International Review · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicEmployee Performance and Management
Canadian institutionsnot available
FundersEuropean Regional Development FundConsejería de Transformación Económica, Industria, Conocimiento y UniversidadesInnovation, Science and Economic Development Canada
KeywordsPandemicCoronavirus disease 2019 (COVID-19)Reciprocity (cultural anthropology)Business2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Employee engagementPublic relationsPsychologyBusiness administrationPolitical scienceSocial psychologyVirologyMedicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

This paper examines the reciprocal relationship between perceived organizational support (POS) and employee engagement within small and medium-sized enterprises (SMEs) during the COVID-19 pandemic. During this crisis, a positive association was observed: SMEs that committed to their employees tended to see a corresponding engagement from their employees. To assess how performance influenced this relationship, the study also explored whether this reciprocal pattern varied with different levels of business performance—decreased, unchanged, or improved—relative to pre-crisis economic performance. An empirical analysis was conducted on a sample of 114 SMEs from the Andalusian region (Spain) using a regression model with mediating effects. The findings reveal that reciprocity between POS and employee engagement was evident during the pandemic and was particularly strong among SMEs belonging to the sub-sample with negative economic results.

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)0.004
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.071
GPT teacher head0.363
Teacher spread0.292 · 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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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