MétaCan
Menu
Back to cohort
Record W4402813161 · doi:10.1287/msom.2022.0643

Innovative Business Models in Ocean-Bound Plastic Recycling

2024· article· en· W4402813161 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueManufacturing & Service Operations Management · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBusinessIndustrial organizationMarketingOperations managementEconomics

Abstract

fetched live from OpenAlex

Problem definition: About 30 million tons of plastic waste reaches the oceans each year, mostly from low- and middle-income coastal countries. We study novel business models of firms aiming to reduce ocean plastic pollution with a triple-bottom-line (TBL) objective—a weighted sum of profit, environmental impact, and social impact. These firms sell (a) plastic offsets and (b) segregated plastic. Methodology/results: We develop and analyze models where a firm partners with a local plastic recycling supply chain to sell (a), (b), or both via collecting and recycling ocean-bound plastic. Considering additionality (i.e., that the firm can only sell plastic offsets based on recycled plastic that is additional to the plastic recycled without the firm’s presence), we solve the equilibrium outcomes by maximizing the firm’s TBL objective. For the special case of a for-profit firm, we show that additionality can decrease the firm’s social and environmental impacts when selling (a) only or when selling both (a) and (b). Additionality may also alter the effect of the local recycled plastic market (i.e., the number of collectors and the recycled plastic price) on the firm. We find similar insights under the TBL objective via a numerical study calibrated with real data. Managerial implications: When firms decide whether to integrate and promote additionality, they must be careful because it may not only reduce their profit but also, reduce their social and environmental impacts. Moreover, we find that selling both (a) and (b) can generate a much higher TBL objective value than selling either one alone. We also find that firms employing a TBL objective can generate much larger environmental and social impacts with a slight reduction in profits than profit-maximizing firms. Our model and results provide insights into new initiatives for tackling ocean plastic pollution. Funding: O. Baron and G. Romero are both supported by the Natural Science and Engineering Research Council of Canada. Z. Zhang is partially supported by the Fundamental Research Funds for the Central Universities of Xiamen University [Grant 20720241012]. S. X. Zhou is partially supported by the Hong Kong Research Grants Council General Research Fund [Grant CUHK-14500921], the National Natural Science Foundation of China [Grant 72394395], and the Asian Institute of Supply Chains and Logistics. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0643 .

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.013
GPT teacher head0.220
Teacher spread0.207 · 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