Selecting suitable entities to implement blockchain in green agricultural supply chains

Area of Science:

• Agricultural Economics
• Supply Chain Management
• Information Systems

Background:

• Existing research often designates blockchain implementers artificially, neglecting firms' economic willingness.
• This limits the practical application of blockchain in green agricultural supply chains.
• A gap exists in understanding endogenous decision-making for blockchain adoption.

Purpose of the Study:

• To explore firms' implementation willingness for blockchain in green agricultural supply chains.
• To identify optimal blockchain implementers based on economic factors.
• To provide decision-making insights for policymakers and practitioners.

Main Methods:

• Developed four game-theoretic models (none, retailer-only, manufacturer-only, both).
• Employed dual thresholds of deployment and operational costs to assess economic willingness.
• Utilized global optimization to capture internal economic motivations.

Main Results:

• Firms' willingness to implement blockchain is contingent on dual cost thresholds.
• Optimal implementer selection varies by cost scenarios: retailer-only (moderately high dual costs), manufacturer-only (balanced costs), joint (extremely high deployment costs).
• Extremely high operational costs result in no willing implementers; independent retailer implementation is most likely within thresholds.

Conclusions:

• Firms' blockchain implementation decisions are driven by economic willingness, not predetermined roles.
• A dual-cost threshold framework effectively categorizes optimal implementers under different scenarios.
• Understanding economic motivations is crucial for successful voluntary blockchain adoption in green supply chains.