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Record W2160556417 · doi:10.1109/tem.2010.2098480

Information Technology and Distance-Induced Effort to Manage Offshore Activities

2011· article· en· W2160556417 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Engineering Management · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOutsourcing and Supply Chain Management
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsOffshoringSubmarine pipelineGeographical distanceProduction (economics)BusinessKnowledge managementService (business)Computer scienceOffshore outsourcingInformation technologyProcess managementIndustrial organizationMarketingEngineeringEconomicsOutsourcingMicroeconomics

Abstract

fetched live from OpenAlex

Offshoring can reduce the production cost of an activity. Yet, at the same time, because of the distance between the parties involved in the activity, it can generate management costs. This study proposes a model of the main drivers of the effort required to manage offshore activities. The model was developed from both the literature and the analysis of interviews conducted in 12 offshore information technology (IT) service providers. The model posits that distance plays an important role in the determination of the effort level. However, in addition to cultural and geographic distances, a more complex notion, labeled “perceived distance,” is posited to play an important role. The model also proposes that IT affects the effort to manage an offshore activity by facilitating formalization of the information exchanged and moderating the impact of geographic distance on the effort required.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.918
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.008
GPT teacher head0.176
Teacher spread0.167 · 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