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Record W4295102547 · doi:10.1080/15378020.2022.2121587

Managerial decision-making during the COVID-19 pandemic and its impact on the sustainability initiatives of Canadian foodservice businesses

2022· article· en· W4295102547 on OpenAlexafffundabout
Emily Robinson, Bruce McAdams, Simon Somogyi, Kimberly Thomas-Francois

Bibliographic record

VenueJournal of Foodservice Business Research · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsUniversity of Guelph
FundersUniversity of Guelph
KeywordsSustainabilityPandemicBusinessGovernment (linguistics)Coronavirus disease 2019 (COVID-19)MarketingEconomic growthEconomics

Abstract

fetched live from OpenAlex

COVID-19 had a major impact on the Canadian foodservice sector. Like most countries, the pandemic in Canada resulted in various periods of lockdown. The pandemic placed great strain on many establishments and had a major impact on the pre-COVID-19 sustainability initiatives of the Canadian foodservice sector. The purpose of this study was to observe managerial decision-making in Canadian foodservice businesses during lockdown and reopening, focusing on the impact of those decisions on pre-COVID-19 sustainability initiatives. We linked the outcomes to the theory of decision-making by objection during times of crises. This study used semi-structured interviews over a two-month period in mid-2020 with three Canadian foodservice establishments. Our results showed that decision-making impacted the environmental sustainability initiatives in foodservice establishments by imposing a throwaway culture for food and personal protective equipment. The pandemic also impacted social and economic initiatives, created higher operation costs, a complexity of government intervention and the managing of mental health. This study showed that the COVID-19 pandemic provided an opportunity to develop theories of managerial decisions during crises and disasters that are natural, versus human-based crises, with pandemics situated between those two concepts. Future research could investigate the impact of decision-making on other initiatives within foodservice businesses.

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)0.010
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.006
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
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 head0.127
GPT teacher head0.390
Teacher spread0.263 · 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.

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
Published2022
Admission routes3
Has abstractyes

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