MétaCan
Menu
Back to cohort

The Trade-Off Between Make or Buy Strategy and Their Relationship With Firm Performance

2023· article· en· W4382807090 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

VenueInternational Journal of Professional Business Review · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicImpulse Buying and Technology Impacts
Canadian institutionsThe Audio Recording Academy
Fundersnot available
KeywordsInsourcingOutsourcingPurchasingOrder (exchange)BusinessMarketingPurchase orderUnit (ring theory)Industrial organizationOperations managementEconomics

Abstract

fetched live from OpenAlex

Purpose: The question of whether to make or acquire something is a crucial conundrum that many companies must solve. A crucial step in the operation of a business is determining whether it is more cost effective to develop and manufacture components or services in-house or to purchase them from outside vendors. In order to provide managers in the General Company for Electrical and Electronic industries (GCEEI) in Iraq with assistance in evaluating sourcing choices, the purpose of this study is to address this subject by bringing the conventional make-or-buy literature up to date by adding fresh academic insights. Theoretical framework: the most prominent ideas and methods for deciding whether to produce something oneself or purchase it are explored, along with a literature analysis of relevant material. The phrases "make-or-buy" and "insourcing" and "outsourcing" were used to search for relevant articles in scholarly databases. Design/methodology/approach: We analyzed the data for the year (2022) that is collected through visits and meetings with the Managers, in the (GCEEI) by using two approaches: a. economic analysis and b. break-even analysis to help managers evaluate sourcing decisions. Findings: According break-even analysis for this case, the quantity should be manufactured is more than 4000 Unit so that the manufacturing costs are more than the purchase costs, then the company should go for buy if less than 4000 Unit. According to the results of the economic analysis, the manufacturing decision is the best in the three models because manufacturing costs are lower than purchasing cost. Research, Practical & Social implications: The findings recommend forming interdisciplinary teams consisting of professionals from many fields (buyers, R&D staff, quality representatives, etc.) to prevent making make-or-buy judgments under circumstances of faulty and inadequate data. Originality/value: Both professional and unskilled workers contribute to the company's success, and when decision-making and procurement become routine, a company's long-tenured employees may ease the burden of these recurring tasks.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.516
Threshold uncertainty score0.280

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.091
GPT teacher head0.315
Teacher spread0.225 · 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