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Record W2791837440 · doi:10.3390/su10030828

The Effect of Introducing Upgraded Remanufacturing Strategy on OEM’s Decision

2018· article· en· W2791837440 on OpenAlexaff
Bangyi Li, Zhe Wang, Yue Wang, Juan Tang, Xiaodong Zhu, Zhi Liu

Bibliographic record

VenueSustainability · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsRemanufacturingCannibalizationBusinessOriginal equipment manufacturerSubsidyEnvironmentally friendlyIndustrial organizationValue (mathematics)Environmental economicsEconomicsManufacturing engineeringEngineeringComputer science

Abstract

fetched live from OpenAlex

Although remanufacturing has great economic and environmental potential, internal cannibalization, and lack of consumer acceptance of remanufactured products prevent original equipment manufacturer (OEM) from realizing the full potential value through remanufacturing. Practices show that remanufactured products can realize their value by the donation, besides resale. Thus, this paper incorporates the donation of remanufactured products with government subsidy and presents an upgraded remanufacturing strategy to expand the demand for remanufactured products and weaken the internal cannibalization of remanufactured products. We respectively construct the two-period game model with and without upgraded remanufacturing and explore the effect of upgraded remanufacturing on production decision, economic and environmental benefits. The main conclusions are as follows. The donation subsidy is negatively related with the sale quantity of remanufactured products, but is positively related with the donation quantity of remanufactured products and the quantity of new products. The donation subsidy expands the demand for remanufactured products and weakens internal cannibalization of remanufactured products. Whether the upgraded remanufacturing strategy is profitable depends on the fixed cost of the remanufacturing. When consumers consider remanufactured products environmentally friendly, the government can realize an OEM’s win-win situation where the economic and environmental benefits get improved by adjusting the donation subsidy. Otherwise, introducing upgraded remanufacturing makes the environment worse. Comparatively speaking, a low-cost and environmentally friendly manufacturer is relatively easier to achieve the win-win situation through donation subsidy.

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)0.004
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
Threshold uncertainty score0.940

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.005
GPT teacher head0.244
Teacher spread0.239 · 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 designOther design
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

Citations25
Published2018
Admission routes1
Has abstractyes

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