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Record W2141310647 · doi:10.1177/0160017609331398

How Office Firms Conduct Their Location Search Process?

2009· article· en· W2141310647 on OpenAlexaff
Ilan Elgar, Eric J. Miller

Bibliographic record

VenueInternational Regional Science Review · 2009
Typearticle
Languageen
FieldEngineering
TopicUrban and Freight Transport Logistics
Canadian institutionsUniversity of TorontoIBI Group (Canada)
Fundersnot available
KeywordsBusinessSatisficingProcess (computing)Decision-makingMarketingEconomies of agglomerationLocationEconomicsComputer scienceEconomic growthMicroeconomicsGeography

Abstract

fetched live from OpenAlex

Office location has important impact on urban form and the transportation system in urban areas. One of the ways to study office location decisions uses surveys of managers and owners of office firms regarding the firm location decision process. The following article presents an analysis of the results gathered in Survey of Office Location Decisions (SOLD)—a Web-based retrospective survey, designed to provide some insight into location decision making of office firms. The main conclusion of the article is that office firms participating in the survey (mainly small and medium sized offices) exhibit a satisficing rather than utility maximizing location decision making. In addition, the results indicate that agglomeration has only a minor role in location decisions by office firms.

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)0.004
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0080.009
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0100.006

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 head0.103
GPT teacher head0.311
Teacher spread0.208 · 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 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

Citations19
Published2009
Admission routes1
Has abstractyes

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