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Record W3205796330

Domino's Pizza Enterprises: Weighted Average Cost of Capital

2021· article· en· W3205796330 on OpenAlexaff
Colette Southam, Paul W. Beamish, Matthew Winkler

Bibliographic record

VenueBond University Research Portal (Bond University) · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWorking Capital and Financial Performance
Canadian institutionsWestern University
Fundersnot available
KeywordsBusinessCost of capitalCapital (architecture)EconomicsFinanceOperations managementComputer scienceActuarial scienceMathematicsMicroeconomicsGeography
DOInot available

Abstract

fetched live from OpenAlex

On November 4, 2020, the group chief financial officer of Domino’s Pizza Enterprises Limited was tasked with determining the cost of capital in preparation for the corporate response to the COVID-19 pandemic. In planning for 2021, the company would need to make considerable investments throughout its franchises in Australia, New Zealand, Japan, and Europe. The cost of capital would be integral to these investment decisions. In the previous year, Domino’s Pizza Enterprises Limited had made A$98.9 million in investments, so the difference of a few per cent in capital costs could mean a swing in millions of dollars in expenditures. The chief financial officer had all background information including balance sheets, income statements, cash flow statements, common stock data, financial ratios, market return data, peer firm data, and an itemized list of debt obligations. Based on this information, he had to derive the company’s cost of capital using a weighted average cost of capital methodology.

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)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.058
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.007
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.023
GPT teacher head0.226
Teacher spread0.203 · 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 designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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