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Record W2977238776 · doi:10.3390/ijerph16193651

Inter-Basin Water Transfer Supply Chain Coordination with Ramsey Pricing

2019· article· en· W2977238776 on OpenAlexaff
Zhisong Chen, Keith C.K. Cheung, Manyi Tan

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic theories and models
Canadian institutionsUniversity of Windsor
FundersNational Key Research and Development Program of ChinaChina Scholarship CouncilNational Natural Science Foundation of ChinaGovernment of Jiangsu ProvinceNanjing Normal University
KeywordsTariffSocial WelfareMicroeconomicsProfit (economics)EnforcementScheme (mathematics)Supply chainEconomicsCoordination gameWelfareTransfer pricingBusinessFinanceMarketing

Abstract

fetched live from OpenAlex

Often enough, social welfare and private benefit do not align for quasi-public goods/services. The inter-basin water transfer (IBWT) project provides a vivid example of this. In this paper, following the game-theoretical approach, we derive an optimal Ramsey pricing scheme to resolve these conflicts. We try to compare traditional supply chain management models with an optimal Ramsey pricing scheme, with an enforcement of coordination among firms. Using simulation techniques, we compute numerical estimates under three regimes: a standard equilibrium decision framework, a coordination decision model and a coordinated Ramsey pricing scheme. Our results show the relative welfare impact of different settings, revealing that the optimal pricing scheme based on the two-part tariff structure cannot only improve social welfare, but also ensure a target profit for participating firms. Lastly, our findings have strong policy implications for the government with profit regulation and the control of water resources.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.699
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.280
Teacher spread0.235 · 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 designNot applicable
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

Citations3
Published2019
Admission routes1
Has abstractyes

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