MétaCan
Menu
Back to cohort
Record W4388297176 · doi:10.5267/j.uscm.2023.9.021

Quality in Peruvian service companies in the context of COVID-19

2023· article· en· W4388297176 on OpenAlexvenueno aff
Jorge Benzaquen, Juan OBrien

Bibliographic record

VenueUncertain Supply Chain Management · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBusiness, Innovation, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsCertificationBusinessContext (archaeology)MarketingLikert scaleService (business)Service qualityQuality (philosophy)Quality management systemCoronavirus disease 2019 (COVID-19)Business administrationAccountingOperations managementQuality managementManagementEconomicsStatisticsMathematicsMedicine

Abstract

fetched live from OpenAlex

The motivation of this study is to provide empirical evidence of service companies’ performance regarding nine dimensions in a total quality management model during the COVID-19 pandemic. The nine dimensions highlight strategic company activities, and it allows a comparative analysis of the overall effect of having a QMS such as ISO 9001:2015 on Peruvian service companies. A total of 630 Peruvian service companies were surveyed for this study. The questionnaire included 35 Likert-scale items that were further classified into nine (9) dimensions. The Mann-Whitney U test was used to estimate any significant differences between the ISO 9001 certified and non-certified companies. Our findings showed that the performance of ISO 9001:2015 certified companies was significantly higher than that of non-certified companies in all dimensions. Moreover, our findings showed that managers in ISO 9001:2015 certified companies effectively implemented the nine dimensions of the model. The originality of this study lies in proving the positive effect of having a QMS in service companies in a context of slow economic growth and decline of consumer demand such as the COVID-19 pandemic. The findings might encourage service companies, especially those in developing countries, to allocate the necessary resources to obtain a QMS such as the ISO 9001:2015.

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)0.003
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 score0.330
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.075
GPT teacher head0.282
Teacher spread0.207 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueUncertain Supply Chain ManagementSame topicBusiness, Innovation, and EconomyFrench-language works237,207