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Data · dataset · 2026

Data Set for the Stackelberg Game Model of Secondary Utilization of Power Batteries via Informal Channels

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Description

This dataset is the complete supporting data for the article "Research on the Game Model of Power Battery Cascade Utilization Considering Informal Recycling Channels", including the mathematical derivation process of the theoretical model, as well as a complete set of numerical simulation codes and underlying data results. In response to the reality of the disorderly expansion of informal channels (small workshops) in the new energy vehicle power battery recycling market, this study constructs a Stackelberg game model composed of government, hierarchical utilization enterprises, and formal and informal recyclers.

The dataset fully demonstrates the pricing decision-making logic of enterprises utilizing tiers under dual channel competition, as well as the market evolution effects of government subsidies and regulatory policies. The dataset mainly consists of the following three parts: Mathematical proof and theoretical derivation: Detailed records of the construction of objective functions for each game subject, the process of solving equilibrium solutions based on reverse induction, and key analytical processes such as the negative qualitative proof of the Hessian Matrix for the social welfare function. MATLAB numerical simulation source code: a core script for game equilibrium solving based on MATLAB.

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The code has built-in parameter adjustment modules and core solving functions, which can dynamically simulate market response trajectories in different scenarios such as fine deterrence, compliance cost fluctuations, regulatory cost constraints, and social environmental benefits. Visualize underlying data (Origin compatible format): a structured data table output through simulation operations. The data covers dual Y-axis 2D sequence data of policy substitution effects, as well as 3D high-density grid (Matrix) data of social welfare optimization and technological synergy effects, which can be directly used for non-destructive reproduction of high-precision scientific charts. This dataset has high repeatability and can provide a reference benchmark for theoretical deduction and algorithm implementation for researchers in the fields of closed-loop supply chain management, reverse logistics optimization, and environmental regulation policy design. 

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Inferred from text
Simulation 75% · Tabular 65%
Provenance · 1 source records, 11 field assertions
SourceKeyLast seenRaw
ScienceDB10.57760/sciencedb.j00204.000219 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].local:field:earth-environmentalmapping · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:engineeringmapping · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:humanitiesmapping · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:life-sciencesmapping · scidb cnconnector:scidb_cn@1.0.0
concepts[field].local:field:social-sciencemapping · scidb cnconnector:scidb_cn@1.0.0
concepts[method].local:method:simulationenrichment · scidb cnkeyword-concept-rules@1.0.0title+description (75%)
concepts[modality].local:modality:tabularenrichment · scidb cnkeyword-concept-rules@1.0.0title+description (65%)
descriptionsource · scidb cnconnector:scidb_cn@1.0.0/metadata/dc/description
license_textsource · scidb cnconnector:scidb_cn@1.0.0
publication_datesource · scidb cnconnector:scidb_cn@1.0.0
titlesource · scidb cnconnector:scidb_cn@1.0.0/metadata/dc/title