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Record W4328024862 · doi:10.5267/j.uscm.2023.3.004

The effect of COVID-19 on human resource management practices and organizational sustainability

2023· article· en· W4328024862 on OpenAlexvenueno aff
Tahir Masood Qureshi, Marija Runić Ristić, Slobodan Adžić

Bibliographic record

VenueUncertain Supply Chain Management · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityBusinessSustainability organizationsHuman resource managementEnvironmental resource managementManagementEconomics

Abstract

fetched live from OpenAlex

The current study tries to identify the impact of COVID-19 on human resource management practices, business processes, and organizational sustainability. Furthermore, it identified the impact of sustainable HRM practices on hypermarkets' sustainability. The outbreaks of COVID-19 have considerably impacted organizations and businesses all over the world. Most companies were not ready to face such force majeure. Moreover, like everywhere else in the world COVID-19 has significantly affected HRM functions and organizational sustainability in the organizations in Gulf Cooperation Council (GCC) countries. The research is based on a survey of 363 HR practitioners working in hypermarkets in the GCC countries to examine the impact of the pandemic COVID-19 on organizational sustainability. The findings reveal the negative impact of COVID-19 on human resource management practices, business processes, and organizational sustainability. Furthermore, they identify the positive impact of sustainable HRM practices and effective business processes on hypermarkets' sustainability. Finally, the results show that effective business processes and sustainable HRM practices annihilate the negative effect of COVID-19 on organizational sustainability in hypermarkets operating in the GCC countries. This study is unique since it is conducted during the pandemic period and analyses the negative impact of Covid-19 on organizations in the GCC countries. Moreover, it suggests solutions to minimize the negative effect of COVID-19 on organizational sustainability.

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)0.005
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.793
Threshold uncertainty score0.845

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.034
GPT teacher head0.311
Teacher spread0.277 · 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 designTheoretical or conceptual
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

Citations3
Published2023
Admission routes1
Has abstractyes

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