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Record W4386588211 · doi:10.31387/oscm0540397

On the Effectiveness of Option Contracts under Supply Disruption

2023· article· en· W4386588211 on OpenAlexaff
Joong Y. Son

Bibliographic record

VenueOperations and Supply Chain Management An International Journal · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain and Inventory Management
Canadian institutionsMacEwan University
Fundersnot available
KeywordsBusinessEconomics

Abstract

fetched live from OpenAlex

This paper studies the effectiveness of implementing option contracts for the procurement of seasonal products subject to short selling season, demand uncertainty, and supply-side disruption.The research intends to show how profitability and product availability can be enhanced both locally and globally by combining the long-term wholesale price contract and option contracts.Using the newsvendor model, the paper aims to identify business settings with respect to disruption parameters, demand uncertainty, and the option pricing under which the use of option contracts could improve supply chain performance.The main contribution of this research is that the effectiveness of option contracts is investigated under the impact of the supply-side disruption in addition to the demand uncertainty.The option contract-based portfolio procurement displays significant performance enhancement in terms of both the retailer profitability and the reduction in the lost sales quantity when supply-side disruptions prevail.The study of the procurement management subject to seasonal disruption can be readily applied to numerous business situations where the disruption can lead to devastating impacts such as the insufficient or untimely supply of COVID-19 vaccines with limited shelf life.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.854
Threshold uncertainty score0.905

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.265
Teacher spread0.245 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations1
Published2023
Admission routes1
Has abstractyes

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