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Record W4246484908 · doi:10.32920/ryerson.14667963

Understanding and Modelling the Impacts of a New Competitor on the Sales of Established Businesses Within Similar Markets

2021· preprint· en· W4246484908 on OpenAlexaffabout
Norman Scott

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicUrban and Freight Transport Logistics
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsFocus (optics)CorporationBusinessMarketingRegression analysisGeographic information systemGeographical distanceLocationIndustrial organizationSales managementGeographyComputer scienceFinance

Abstract

fetched live from OpenAlex

The research conducted for this study presents a Geographic Information Systems (GIS) and spatial analysis to understanding and modelling the impacts of a new competitor on the sales of established businesses within similar markets. Data for this analysis was provided by Canadian Tire Corporation (CTC).This study will outline and create trade areas for all stores in the Part Source network to determine which stores will be the focus of this study. Once focus stores have been determined, sales data was analyzed in two ways. The first analysis was conducted to determine the distance decay effects of the new competitor on sales. The second analysis utilized geographic weighted regression (GWR) models on expenditure and vehicle data.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score0.208

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.131
GPT teacher head0.219
Teacher spread0.088 · 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 designSimulation or modeling
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

Citations2
Published2021
Admission routes2
Has abstractyes

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Same topicUrban and Freight Transport LogisticsFrench-language works237,207