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Record W4405539624 · doi:10.55482/jcim.2024.34346

Exploring the Impact of Organizational Support, Perceived Productivity, and Employee Status on the Organizational Commitment during the Mandatory Telework of COVID-19 Pandemic: Empirical Evidence with Algerian Employees

2024· article· en· W4405539624 on OpenAlexvenueno aff
Toufik Serradj, A. Saidani

Bibliographic record

VenueJournal of Comparative International Management · 2024
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsProductivityOrganizational commitmentPandemicCoronavirus disease 2019 (COVID-19)Empirical evidenceBusiness2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Public relationsEconomicsEconomic growthPolitical scienceVirologyMedicine

Abstract

fetched live from OpenAlex

This study investigates the impact of mandatory teleworking during the coronavirus disease 2019 (COVID-19) pandemic on organizational commitment (OC) among employees in Algeria. A sample of 408 respondents were utilized, consisting of employees from public sector companies in Algiers. Data were collected through an online questionnaire, and the methodology employed is quantitative, using statistical analysis to examine the relationship between teleworking conditions and levels of OC. The results highlight significant associations between commitment levels and factors such as teleworking duration, perceived employer support, perceived productivity, and employee status. This research adds to the existing literature by examining the unique challenges faced by employees during mandatory teleworking, particularly in Algeria, where teleworking practices are still emerging. The study provides practical recommendations for organizations to strengthen employee commitment as they navigate the evolving work environment.

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 score0.101
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.137
GPT teacher head0.353
Teacher spread0.216 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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