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Record W2026361890 · doi:10.1108/17538370810866340

A study of out‐sourcing versus in‐sourcing tasks within a project value chain

2008· article· en· W2026361890 on OpenAlexaff
David L. McKenna, Derek H.T. Walker

Bibliographic record

VenueInternational Journal of Managing Projects in Business · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOutsourcing and Supply Chain Management
Canadian institutionsBell (Canada)
Fundersnot available
KeywordsInsourcingOutsourcingProcurementBusinessContext (archaeology)Process managementStrategic sourcingBusiness processCompetitive advantageValue (mathematics)Knowledge managementComputer scienceMarketingStrategic planning

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to investigate a case of in‐sourcing a key resource verses using the standard mode of operation of utilizing an established out‐sourcing firm. The studied organisation is a large telecommunication firm in North America. The aim of the paper is to illustrate how a new approach to the organisational procurement decision making process to facilitate competitive advantage was influenced by simplicity rather than simple cost reduction. Design/methodology/approach Single illustrative case study testing the usefulness of the composite out‐sourcing decision framework decision making framework together with a clear focus on total value adding elements of service delivery. Findings The analysis that in‐sourcing critical tasks or processes are advantageous to the case study organization as well as to the smaller internal department that it directly impacts. Research limitations/implications When undertaking business projects or programs of projects, there are many cases where business processes may be outsourced or sub‐contracted. While out‐sourcing does, and will in the future, play a large role in cost reduction and giving the buying firm the ability to focus on core competencies, there is still the niche market to in‐source critical tasks and retain critical resources. Decisions need to be based on value contribution rather than simple cost reduction. Originality/value This paper's value has been to illustrate some frameworks, tools and techniques used to explain how a particular insourcing/outsourcing decision was undertaken in a business project context and it explains the rationale behind decisions being made.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.056
GPT teacher head0.290
Teacher spread0.234 · 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

Citations18
Published2008
Admission routes1
Has abstractyes

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